DAC BAA Research Topics

By Kyle BondOctober 27, 2022

Current Research Topics for the

DEVCOM Analysis Center Broad Agency Announcement For Applied Research



All current DEVCOM Analysis Center (DAC) research topics can be found at: https://www.army.mil/article/261533. Changes to these topics will be made using the website on an as needed basis. DAC will consider whitepapers and proposals that may not directly align to a topic published by a DAC Technical Point of Contact (TPOC), but can demonstrate a strong alignment to DAC’s mission and core competencies listed within Appendix A. This document is a printed copy of the current DAC research topics as of the noted print date. DAC maintains a daily static snapshot of the DAC research topic website to ensure submissions are aligned with listed research topics on the day of submission. Interested parties are encouraged to continually browse the DAC research topic website and review the DAC Broad Agency Announcement (BAA) for instructions on submissions.

The DEVCOM Analysis Center Broad Agency Announcement for Applied Research,


is available on https://www.grants.gov/ and https://sam.gov/

Title: Methodologies and Techniques to Analyze Assistive Automation (AA) & Artificial Intelligence (AI) enabled systems

Announcement ID: DAC BAA-001

TPOC: Dr. Thomas Stadterman, (410) 278-6295, thomas.j.stadterman.civ@army.mil

DAC Office: Office of the Chief Scientist

Domain: Data & Analysis, Foundational Research, Lifecycle Engineering

DAC Foundational Research Competencies: Mission Effectiveness, Human Engineering and Performance, Decision Support

Army Modernization Priorities: Network/C3I

Keywords: assistive automation, artificial intelligence, analysis, framework, modeling and simulation, data science, machine learning, emergent behaviors

Many projected Army capabilities will exploit AA/AI. Unfortunately, scientific treatment of AA/AI systems has tended to one of two extremes. Often the systems are treated as black boxes where systems - and Soldier/Driver/Airline Passengers lives - are entrusted to machine learning (ML) algorithms that have been trained and tested over data sets that have sometimes been of dubious provenance. The other extreme is to directly assess the quality of the ML being used as well as the adequacy of the training and testing data sets. Neither of these extremes supports scientifically informed decision making about the desired capabilities.

Analysis, Test & Evaluation organizations require “intermediate” level scientific tools that enable analyses of the effects and impacts of the Army’s transformation in AA/AI capabilities. Current Army analysis methodologies that contended with a much simpler set of analysis problems typically focused at the particular system or at the network levels are not adequate to the current problem. The required “intermediate” level science will answer more complex questions than the black box approach permits, and thus provide the Army a significant leap forward in analysis techniques, methodologies, and mindsets by focusing at the area where all weapons, mission command, and other systems converge and merge their operations with network connections. The Army must identify, articulate, and develop new and advanced scientific and analysis methods that can gauge how well proposed Army AA/AI systems are taking advantage of new state-of-the-art AA/AI capabilities, mitigating new threats posed by advancing adversary capabilities, and adapting to radically new contested environments.

The new methods and techniques must consider credible mission context and the environments in which the systems will operate with a complex, systems-of-systems environment. The proliferation of unmanned aerial systems, the challenges of dense urban environments, and the benefits and risks of manned-unmanned teaming all require enhanced analysis tools. Utilizing modern research in AA/AI, simulation, simulation languages, emerging mathematical techniques, and human factors analysis advancements will improve capabilities to explore the continuum of military operations. The scientific techniques and new analysis methodologies will address the complexity inherent in interactions between systems, including humans and multiple, autonomous, and potentially intelligent learning machines. Analyses will also explore the rapid growth of adversary capabilities, in areas such as cyber and electronic warfare, due to advancing commercial technologies.

Strategic opportunities within AA/AI analysis include:

i.       Research from computational science and extramural research on advanced mathematical, statistical, and modeling and simulation techniques, such as predictive sciences, uncertainty quantification, advance computational algorithms, and data intensive techniques.

ii.     Research from human sciences to explore the human dimension of AA/AI use in future conflict, including human/machine interfaces and cognitive decision making processes.

iii.   Research from the information sciences regarding communication, processing, storage, and retrieval of information, for example research on digital RF technology.

iv.   Research to identify readily observable input variables during AA/AI systems use that have the most explanatory power concerning the military utility of the systems.

v.      Research to identify readily observable output variables during AA/AI systems use that have the most explanatory power concerning the military utility of the systems

vi.   Research associated with emergent behaviors, associated failure modes and mechanisms, and reliability associated with AI-enabled complex systems.

Title: Scientific Understanding and Analytical Methodology for Multi-Domain Operations (MDO)

Announcement ID: DAC BAA-002

TPOC: Dr. Thomas Stadterman, (410) 278-6295, thomas.j.stadterman.civ@army.mil

DAC Office: Office of the Chief Scientist

Domain: Data & Analysis, Science & Technology, Lifecycle Engineering

DAC Foundational Research Competencies: Mission Effectiveness Analysis, Decision Support

Army Modernization Priorities: Network/C3I

Keywords: multi-domain operations, MDO, framework


National leaders have long been concerned that the Army is losing overmatch. The loss is driven largely by leap-ahead technology gains by near-peer adversaries. Army Senior Leaders (ASL) responded to these challenges by recognizing that improved systems by themselves are no longer sufficient to obtain and maintain overmatch. To fight and win in anticipated future operating environments (FOE) novel warfighting concepts are also required. One such concept is Multi-Domain Operations (MDO). To flesh out the details of MDO, ASL introduced additional new terminology for describing the future fight. The new terms, used in the Army Modernization Strategy (AMS) and elsewhere, include calibrated force posture, multi-domain formations, strategic maneuver, deep maneuver, competition, contested spaces, convergence, cross-domain, cross-domain fires, cross-domain maneuver, synergy, decisive space, dislocate, dis-integrate, and others. In some cases traditional terminology has been re-defined; for example, “battlefield” now includes all domains (air, land, space, and cyberspace, the electromagnetic spectrum, and the information environment).

Making useful quantitative scientific assessments of the many aspects of the MDO environment is a new challenge for Army RDT&E. The Army needs a new scientific picture that adequately reflects the complex systems and technologies including cyber and electromagnetic activities, swarming munitions, autonomous systems, and human-agent teaming. The new picture will be underpinned by a mathematical framework of complexity and emergence theory and will integrate physics and engineering-based models with appropriate tactics, techniques, and procedures. The new scientific picture will also include advanced data analysis tools, which will generate the knowledge required by decision makers and others to fully assess the causes and implications of system performance within complex, multi-domain, and operationally relevant environments. Required analysis tools include appropriate measures of effectiveness and associated metrics of performance, as well as unique ways to visualize the results and intuitively appreciate the impacts of various ways of operating across domains.

Specific strategic opportunities within MDO analysis include:

i.     Research into quantifying calibrated forced posture. This will require identifying the dominant observable variables that drive proper force calibration for both friendly and enemy forces. It will also require consideration of socio-cultural, and other non-traditional methods for nullifying effective command and control and reducing force effectiveness.

ii.    Research into picturing and portraying a friendly multi-domain formation in a fashion that is simultaneously accurate, intuitively clear for Commanders and their staffs, and sufficiently robust that it is clear when the friendly formation needs to be supplemented or otherwise modified.

iii.  Research into sound quantification of the (doctrinally) novel concepts of competition and convergence. For example when are two competitors equal? When have US forces pursued competition effectively? What are appropriate combinatorial tools for assessing the mathematics of convergence? What are appropriate analytical and M&S means for objectively analyzing and assessing a given state of competition and the associated calibrated force structure?

iv.  Research into the many cross-domain synergies that are postulated by MDO doctrine. What are the appropriate mathematical tools to quantify cross domain outcomes, for example, when cyber-attacks, kinetic attacks, and EW jamming are applied simultaneously? How should we calculate the synergy gained in such cross-domain attacks? How do we determine the appropriate geospatial boundaries for cross-domain consideration?

Title: The Science and Analysis of Systems of Systems (SOS)

Announcement ID: DAC BAA-003

TPOC: Dr. Thomas Stadterman, (410) 278-6295, thomas.j.stadterman.civ@army.mil

DAC Office: Office of the Chief Scientist

Domain: Data & Analysis, Foundational Research

DAC Foundational Research Competencies: Mission Effectiveness Analysis, Human Engineering and Performance, Cyber Resilience

Army Modernization Priorities:

Keywords: model and simulations, methodologies, framework, analysis, systems of systems


Information dependencies among disparate elements of the Army force are increasingly a feature of contemplated Future Operating Environments (FOE). The optimum target for a platoon might be selected by a corps asset that is dozens or even hundreds of kilometers away. This kind of dependency implies that any adequate understanding or analysis of the Army SOS must avoid some of the traditional assumptions which traditional Army analysis has made. One such assumption, which has not always been clearly stated by Army scientists and analysts, is that events taking place in different parts of the battlefield may usefully be regarded as independent events. Although the assumption has never been mathematically or scientifically valid, it did yield reasonable approximations of combat outcomes when the FOE of interest were, for example, meeting engagements in the Fulda Gap. For cross-domain warfare, the independence assumption has nothing to recommend it.

What is now needed are methodologies and tools to characterize the performance of systems of systems at the engineering level so that the exact interactions between and across Army systems can be accurately portrayed in Army M&S and analysis. This level of detail is required to support the full range of planned capabilities in the FOE. The new M&S and analysis capability is crucial as the Army assesses future technology and system tradeoffs. The new tools must rise above the “eaches” and illuminate the effectiveness of competing capability SOS packages and technologies rather than just individual systems. To fully realize this capability requires new engineering metrics (e.g., mission success or failure, Soldier and equipment survivability, weapon systems lethality, and cyber and electronic warfare for friendly and enemy forces and the quality and throughput of network operations) while developing algorithms that can be validated and used with approved scenarios.

Specific strategic opportunities within SOS science and analysis include:

i.     Development of engineering-level methods for quantifying the performance of the SOS. Research on the question of when, if ever, the traditional assumption that all events are independent may retain validity in the SOS context. How should we assess the sustainment needs of the SOS beyond the needs of the component systems?

ii.    Analysis of Soldier-SOS interactions will presumably require different analytical tools and models than traditional Human Systems Integration (HSI) analysis of Soldier interaction with a single system. How should we characterize the specific requirement for such tools, and how should we set about developing them?

iii.  Research on whether there are simplified (i.e. non-engineering level) methods of assessing SOS performance that may yield acceptable quality results for at least some classes of cases.

iv.  Research and development of improved technical capability to analyze the resilience of Army systems when other systems in the SOS are not available. As the number of cross-system dependencies increases, this challenge becomes more and more important. How should we assess the new vulnerabilities that arise because of these SOS dependencies?

v.    Research on tactically relevant packages of Army communications systems and collateral technologies at varying levels of fidelity. The Army needs to understand when an engineering level of fidelity is required and when cruder and less detailed approximations may suffice.

Title: Analytical Methodology for Future Army Systems Enabled by Quantum Technology (Quantum)

Announcement ID: DAC BAA-004

TPOC: Dr. Thomas Stadterman, (410) 278-6295, thomas.j.stadterman.civ@army.mil

DAC Office: Office of the Chief Scientist

Domain: Data & Analysis, Science & Technology

DAC Foundational Research Competencies: Mission Effectiveness Analysis

Army Modernization Priorities: Networks

Keywords: quantum, analytics, PNT, cryptography


Quantum technology has progressed from an idea many (including Albert Einstein) regarded as spooky in the 1930s to practical laboratory demonstrations of the potential utility of entanglement and other quantum phenomena. Enormous sums of money are being spent in the US and abroad to move these laboratory demonstrations into practical technologies. Experts disagree on how long it might take for the remaining barriers to be overcome in such a way that it would be practical for the Army to use quantum technology enabled systems in tactical environments. Despite this disagreement, it is prudent for the Army analytical community to think about tools for evaluating the leap-ahead gains that may be available with quantum technologies. This analytical exercise is critical because the potential gains are not merely percentage improvements but rather capabilities that can fundamentally change essential aspects of ground combat in favor of the side with the quantum solutions.

There is a rough consensus that there are four areas where quantum breakthroughs might make dramatically improved technologies available to Army warfighters. These potential breakthrough areas are: computing and simulation; communications and networking; sensors and imaging; and position, navigation, and timing (PNT). DAC must begin developing tools for analyzing quantum systems that enable entirely new Army capabilities. The specific opportunities mentioned below are representative of the kinds of questions Army analysis will need to be equipped to answer when these technologies begin to be realized.

Representative research opportunities within Quantum technology analysis include:

i.     If a quantum computer allowed realization of all binary states at once rather than one at a time, what new simulation applications might be practical for battlefield use by current Army systems? Could the ability to solve classically insoluble cryptographic problems allow Army systems to exploit enemy networks on the battlefield?

ii.    If quantum communications and network tools allowed unbreakable quantum key distribution (QKD), how would this facilitate both tactical battlefield communications and support of tactical operations with national assets?

iii.  What options would quantum PNT offer to tactical commanders using current systems, especially during periods when GPS is denied? What potential new vulnerabilities would be introduced if the Army were dependent on atomic clocks for timing? Which Army systems could exploit quantum clocks with better-than-GPS timing for tactical advantage, and how should we quantify that advantage?

What new analytical techniques or M&S will be required to assess the effectiveness of the nearest term quantum inertial sensors like accelerometers and gyroscopes? If very broad-band quantum RF sensors (Rydberg) are incorporated into sensors for detection in difficult (tunnels, bunkers) environments, what new measurement or M&S capability will be required for effectiveness assessment? What existing EW systems could benefit from this type of technology? Is our current suite of measurement and M&S tools sufficient to assess the effectiveness of quantum EW capabilities?

Title: Artillery - Hypersonics Data and Analysis

Announcement ID: DAC BAA-005

TPOC: David Fordyce, (410) 278-6340, david.f.fordyce.civ@army.mil  

DAC Office: Artillery, Aviation, Air Defense & Experimentation

Domain: Science & Technology, Data & Analysis

DAC Foundational Research Competencies: Integrated Materiel Performance, Ballistics Analysis

Army Modernization Priorities: long range precision fires, soldier lethality, air and missile defense

Keywords: hypersonic, materials, ballistics, analysis


Development of weapons traveling at hypersonic speeds by near-peer and other countries requires a response by the Army – both in protecting U.S. assets, personnel, and the Homeland, and development of our own hypersonic offensive capability. In order to successfully accomplish these goals, the physics and impacts of these weapons (glide body, kinetic projectiles, ramjets and scramjets) traveling greater than Mach 5 close to the ground must be clearly understood. This understanding requires data and analytic methods to fully describe the effects of the environment on the vehicle in flight, and the weapon/target interaction (terminal ballistic conditions).

In flight: To understand the structural response in flight through terminal target engagement, material models are required considering 1) rate effects, 2) strain hardening, and 3) thermal softening. There is almost no data in the hypersonics community which includes thermal softening. Other researchers can attest to this. Most tensile & split-Hopkinson bar experiments are performed at a reference temperature. These characterizations are needed on a span of temperatures that approach the melting temperature of the projectile skin. In addition to material modeling, understanding the ability of the munition to maneuver at these speeds is critical.

Weapon/Target interaction: To understand the effect of the hypersonic vehicle on ground-fixed (structures/bunkers), ground-mobile (tanks, military or other vehicles), or maritime targets (ships/underwater vehicles), the terminal ballistic conditions must be known. This includes phenomena such as striking/penetration and mass/shape of fragments or single large mass projectiles, synergistic effects such as blast/fragmentation, ground shock, or cross-domain effects such as an electromagnetic pulse created by the weapon functioning.

Analysis of these weapons requires a multi-disciplinary approach and assessment/extension of existing models or creation of new ones into the hypersonic realm. Development of appropriate data of the effects of these weapons will likely require experimentation, as well as intelligence of the technologies of what near-peer and other nations have developed/are developing.

Title: Network Vulnerability and Effects Assessment Methodology (N-VEAM)

Announcement ID: DAC BAA-006

TPOC: Dr. Jayashree Harikumar, (575) 678-8616, jayashree.harikumar.civ@army.mil

DAC Office: Cyber

Domain: Data & Analysis

DAC Foundational Research Competencies: Cyber Resilience, Electronic Warfare (EW) Threat Defense

Army Modernization Priorities: Network/C3I

Keywords: electromagnetic warfare, cyber, vulnerabilities, CEMA, artificial intelligence, machine learning, Li-Fi, communications


The goal of this research area is to develop analytical methodology and capabilities to characterize hardware and software that enable Electromagnetic Warfare and Cyber capabilities to assess operations of Army Network and communication platforms and dismounts, while maintaining freedom to maneuver, communicate, and sense. This endeavor strives to develop a holistic cross-domain analysis and assessment methodology for network and communication technologies faced with advanced Cyber Electromagnetic Activity (CEMA). These investigations are critical to identifying vulnerabilities of United States systems and technologies so that network and network-enabled systems can be hardened as early in development as possible.

Core applied research areas include:

i.           Vulnerability (Intrusion) Detection using AI and ML: analyze in a lab environment implementations of Army relevant AI ML systems, their vulnerabilities and mitigation techniques.

ii.        Personal Area Networks: focuses on high bandwidth using military applications (e.g. Wi-Fi, Bluetooth).

iii.     Cybersecurity of Systems on Cloud: research on emerging cloud technologies to improve the cybersecurity posture of cloud systems. This project looks to create cloud testbeds for the new technologies, proof of concepts, use cases, prototypes, tools, and methodologies to enhance the cyber analysis and assessment of cloud technologies considered for fielding. This applied research program will engage with experts from partner universities.

iv.      LiFi Cyber: focuses on identifying protocol vulnerabilities on LiFi devices.

v.         Cellular Communications: develop scenarios to conduct controlled experiments on a simulated network communications backbone;

vi.      Adversarial AI: look to create Adversarial AI proof of concepts, use cases, prototypes, tools, and methodologies to support the analysis of AI technologies being fielded; engage with Machine Learning experts from partner universities on Army relevant areas such as autonomous systems, image recognition assistive robots, network security, etc.

Results from this research will inform DEVCOM DAC, DEVCOM C5ISR, DEVCOM ARL, PEO C3T & Network Cross Functional Team. The expected payoff is the establishment of critical analysis elements that leads to a well-designed measure of merit and development of an analysis and assessment database. Ultimately, this will affect the quality of CEMA future assessments, which is critical to the development of a robust modernized Army network.


Title: Human-Technology Cooperation in Defense Command and Control Operations

Announcement ID: DAC BAA-007

TPOC: John Hawley, (915) 568-2896, john.k.hawley.civ@army.mil, and

Jamison Hicks, (334) 255-2206, jamison.s.hicks.civ@army.mil

DAC Office: Human Systems Integration

Domain: Data & Analysis, Lifecyle Engineering

DAC Foundational Research Competencies: Human Engineering and Performance, Humans in Complex Systems, Decision Support

Army Modernization Priorities: Soldier Lethality, Network/C3I

Keywords: analysis and experimentation, sociotechnical systems, C3I


Dramatic recent progress in enabling technologies such as artificial intelligence (AI) has led many to believe that unprecedented degrees of autonomy can safely, reliably, and effectively be introduced into current and future military systems. Autonomy has the potential to enable dramatic changes in military capabilities and force composition. Until recently, the only systems capable of automated operations, for periods of time and under restricted circumstances, were those employed in Air and Missile Defense (AMD). However, the Army has a checkered history with automated systems. For example, 18% of engagements by the Patriot AMD system during Operation Iraqi Freedom (OIF) were fratricides. Work conducted by the U.S. Army Combat Capabilities Development Command (DEVCOM) Army Research Laboratory (ARL) following OIF suggested inadequate concepts and methods for structuring and evaluating automated AMD command and control (C2) capabilities as they progressed through development contributed to those incidents. Training to support automated operations also was judged to be inadequate and remains a challenging issue. Recent research and operational experience reinforce this concern as to how the reliability and safety of highly automated systems will be evaluated and verified prior to their field deployment: assuring performance in accord with command intent. This situation is likely to be increasingly problematic as more advanced technologies such as machine learning increasingly are applied to system control both in AMD and other warfighting domains.

The DEVCOM Analysis Center is responsible for (1) providing HSI support to PMs during system development, (2) providing HSI evaluation support to ATEC during test and evaluation, and (3) the preparation of the HSI Assessments used during Milestone decision reviews prior to system fielding. The main goal of this research is to develop methodologies and products that will support DAC in performing its three-fold mission. Core areas of research interest include the following. These core areas apply to AMD as well as other Army warfighting domains:

i.              Effective use of automation in C2 operations. Soldier cooperation with increasingly intelligent C2 systems; trust in automation to include trust in emerging AI- and machine-learning-based decision support applications; strategies for progressive automated support to C2 operations; and methods to assess and enhance system control in accord with command intent.

ii.             Effective supervisory control of automated C2 systems. Strategies to support human command-progressive machine control of automated C2 operations; concepts for implementing and assessing multi-echelon supervisory control in C2 operations; and concepts for structuring and supporting high-level strategic human control such that the overall control complex is as trusted, reliable, and safe as technology and the cognitive limits of command oversight will permit.

iii.           Support for rapid and enhance sense making in C2 operations centers: Design of warfighter-machine interfaces to facilitate effective human oversight of complex operations, design principles for human-centric decision support applications, macro cognitive considerations in operations center and information system design, and strategies for effective operational integration of modernizing materiel components into operations center practices.

iv.           Development, demonstration, and evaluation of innovative training methods for C2 and related system control situations: Practical methods for rapidized cognitive task analysis; development and application of accelerated expertise methods in C2 training; innovative considerations in the development of capabilities to support effective and efficient training in tactical units, and including trainee performance assessment and feedback.

The products of this research are intended to support the DEVCOM Analysis Center in performing its assigned system development and evaluation missions involving each of the core areas noted above. A related objective of this research is determining reasonable limits of human performance and expertise in the oversight of complex C2 operations and related control situations.

Title: Human-Systems Integration Analysis – Artificial Intelligence/Machine Learning for Army System Development and Assessment

Announcement ID: DAC BAA-008

TPOC: John Hawley, (915) 568-2896, john.k.hawley.civ@army.mil, and Jamison Hicks, (334) 255-2206, jamison.s.hicks.civ@army.mil

DAC Office: Human Systems Integration

Domain: Data & Analysis

DAC Foundational Research Competencies: Human Engineering and Performance, HIS Methodology, Modes, Tools, and Simulations

Army Modernization Priorities: Network/C3I

Keywords: deep learning, artificial intelligence, machine learning, data science


The Army currently collects a vast amount of aviation data during simulation and testing. This includes image and video data, flight control inputs, button and switch actuation, voice and text communication, and structured/unstructured data sets for a variety of combat and non-combat missions (e.g. health, maintenance, logistics, and operations). The vast scale of collecting and analyzing this data is a challenge to human-driven/human-only solutions to collection, processing, and analysis. The goals of this work are to increase the Army’s capacity to process and analyze the data by assisting and augmenting HSI analysts through the application of artificial intelligence (AI) and machine learning (ML) algorithms, to include deep learning algorithms.

Core areas of applied research interest are listed below. These core areas apply to Aviation as well as other Army warfighting domains.

i.       New methodology for automating data collection during missions and analyzing the large datasets (e.g., data mining) that are collected via automation.

ii.     Experimental investigation and prototype development of AI/ML algorithms and capabilities with the goal of helping HSI analysts perceive and understand dynamic and unknown environments. Includes the creation of comprehensive models of real-world environments in which AI/ML entities facilitate course of action development by displaying intuition and improvisation characteristics in real-time, dynamic scenarios.

iii.   New frameworks and tools for the creation of tailored algorithms to perform discrete tasks within innovative AI/ML computational environments for use in Army operationally relevant experimentation and test.

iv.   New labeling techniques to generate massive scale annotated data for supervised deep learning techniques.

v.      New methods of edge computation to bring deep learning algorithms to constrained computational environments.

vi.   Methods to evaluate and determine the effectiveness of algorithmic approaches.

vii. Interfaces for the display, search, and interaction with algorithmically derived metadata and tabular structured algorithmic output; new techniques, hardware, software, and tools for the training, testing, and validating of algorithms; and storage and indexing capabilities for local algorithmically-produced data.

The products of this applied research are intended to support DAC analysts in performing system development and assessments of Army modernization and fielded systems. This will help reduce the time required for data collection and analysis during simulation and testing, provide more in-depth analysis of system design, and enhance pilot-system performance

Title: Human-Systems Integration Analysis – Augmented Reality Displays for Enhanced Crew Situational Awareness

Announcement ID: DAC BAA-009

TPOC: John Hawley, (915) 568-2896, john.k.hawley.civ@army.mil, and

Jamison Hicks, (334) 255-2206, jamison.s.hicks.civ@army.mil

DAC Office: Human Systems Integration

Domain: Data & Analysis

DAC Foundational Research Competencies: Human Engineering and Performance

Army Modernization Priorities: Next Generation Combat Vehicle, Future Vertical Lift

Keywords: augmented reality, symbology


Army pilots utilize 2 dimensional (2D) moving maps on a cockpit Panel Mounted Display (PMD) populated with symbology to identify points of interest (e.g., airfields, friendly forces, threats, restricted operating zones). Pilots must focus their attention on the PMD (inside the cockpit) to identify these points of interest and interpret their location in 3 dimensional (3D) space. Additionally, PMD's require significant interpretation and spatial reasoning to identify terrain features and interpret the overall battlefield state. Augmented Reality (AR) overlays can provide that information in an “out-the-window” (OTW) format that allows for faster spatial recognition and reduced reaction time to perform crew tasks. 3D point of interest representations and dynamic infographics (DIG) could help provide pilots with enhanced situational awareness of spatial location, threat level, and battlefield movement and keep them heads-up/eyes-out during flight.

The goals of this work are to develop novel and intuitive methods, processes, and AR overlays and displays and to identify performance benefits (i.e., quicker reaction time, higher situational awareness, lower workload, enhanced battlefield management) of providing 3D objects in OTW space (augmented reality). It supports Army modernization requirements for mission operations in degraded visual environments, single pilot operations, and battlefield management for multi-domain operations (MDO).

Core areas of applied research interest are listed below. These core areas apply to aviation as well as other Army warfighting domains.

i.                   Develop immersive virtual environment (e.g., full-motion simulator) with heads-up or helmet mounted display technology with augmented reality symbology sets.

ii.                 Consensus on symbology designs and mode-based (e.g., MEDEVAC, Attack, Search & rescue, Fire Fighting, etc.) missions.

iii.               Incorporation of DIG’s in full mission profiles for all crew and passengers (e.g., pilots, passengers, medics) with AR symbology to provide a common operating picture.

iv.               Multi-Crew scenarios – Pilots, co-pilots, and non-rated crewmembers performing tasks while using AR/VR technology. Including, but not limited to, Medevac, Reconnaissance, Attack, and Training/Exercise missions.

v.                  Multi-ship – multiple pilots (and/or crews) simulating flight formations and group missions with AR/VR technology (multi-aircraft search and rescue or coordinated fire fighting).

vi.               “Live” use of AR in a real-world environment with technology similar to Microsoft HoloLens to display symbology “out-the-window”.

vii.             MDO scenarios – communications, procedures, and tactics with other military platforms utilizing AR symbology and advanced cockpit/crew display configurations.

viii.           Create a ‘Holodeck’ environment with automated data collection capabilities for future studies.

ix.               Understand and develop futuristic type user interfaces using hand gestures and eye gaze. The products of this applied research are intended to support DEVCOM DAC HSID analysts in performing system development and assessments of Army modernization and fielded systems for increased situational awareness and enhanced system performance.

Title: Cybernetic Systems (Inferring Human Intent for Seamless Human-Artificial Intelligence Interactions)

Announcement ID: DAC BAA-010

TPOC: Dr. Norbou Buchler, (410) 278-9403, norbou.buchler.civ@army.mil

DAC Office: Human Systems Integration

Domain: Data & Analysis

DAC Foundational Research Competencies: Human Engineering and Performance

Army Modernization Priorities: Network/C3I

Keywords: data collection, artificial intelligence, machine learning, analysis, cybernetics


This area focuses on developing a standard data-service, analytics, and inference engine of human intent based on repository of continuous human-machine interactions and workflows to enable seamless collaborative decision-support by AI systems and advanced command by intent relationships. Currently, there is no standard collection or analysis of human-system interactions data-streams (mouse, key, application use) that can be leveraged across networked systems for human-system measurement, analysis, and adaptations.

The nature of work across multi-domain operations (MDO) is constantly changing due to an adaptive adversary, evolving threats & concepts of operations, and the blistering pace of technological change to include tools and systems that are increasingly capable of autonomy with AI technologies. A major focus within all domains is the interaction between human operators and their tools. The complexity of modern AI limits our ability to intuit the impacts of using new technologies. Almost all domains have extensive digital collections as networked systems regularly collect large system repositories of logged human-computer interactions (HCI). Such data-streams have largely been ignored and not leveraged into system engineering requirements for advanced capabilities. From a cybernetics perspective (e.g. regulation of human-AI systems), human-activity data-streams can provide continuous and virtuous feedback loops between human and AI system to effectively achieve ongoing system adaptations for decisive conjoined actions. We seek to leverage current methods and analytical approaches that leverage these HCI data-streams to improve the definition and resolution of operator and system performance to support DoD AI technological maturation (data-driven metrics/benchmarks), enable virtuous human-AI feedback-loops, and develop command by intention capabilities (machine learning classification).

Core research areas include:

i.                   Continuous Monitoring of Human-AI Systems: current acquisition strategies involve discrete operational test events to assess fit and functionality. This overlooks the impacts of changing operating conditions, workforce, adversaries and AI models. This core research area introduces instrumentation that will accommodate continual monitoring and analysis of human-machine teaming as a common data-stream standard.

ii.                 Human-Systems Task Analysis: develops capabilities for the collection and analysis, playback, search/filtering, and machine learning (ML) automation of operator and AI system activity, tool use & interactions, and performance metrics to support after action review (AARs) and test & evaluation in developmental & training exercises. The platform will support both real-time data analytics over the course of a scenario experiment/exercise as well as post-hoc/ playback data analysis.

iii.               Command by Intent: the derivation/prediction of operator workflow with machine-learning classifiers can improve and supplement traditional assessment methodology, and also enable the human-system feedback loops and continuous optimizations necessary for adaptive AI, tailored decision-support to human operators, and command by intent relationships with AI systems. This research area is critical for multi-domain technologies in the C5ISR domain and has wide ranging implications for how we design and incorporate human agency into all high-risk actionable AI-supported work domains.

The near-peer great powers competition will be dominated by the armed forces most able to command advances in artificial intelligence. Communist China embodies centralized decision-making and batch execution (command by planning), whereas the U.S. embodies a more advanced command by intent Mission Command doctrine by delegation of purpose. Developing AI systems capable of dynamic command by intent capabilities within and across multi-domain operations (MDO) necessitates that our machines are purposively aligned with high-level information fusion of operator task-level workflows. Such data-feeds require a highly-contextualized representation of human workflows (tactics, techniques, and procedures) with continuous machine-level inference (and alignment to) derivations of human intent. This could prove to be a decisive-edge for agile and adaptive conjoined human and machine (AI) optimizations to counter debilitating first-strike capabilities and cyber (advanced persistent threat: APT, zero-day) threats.

Title: Humans in Multi-Agent Systems

Announcement ID: DAC BAA-011

TPOC: Dr. Norbou Buchler, (410) 278-9403, norbou.buchler.civ@army.mil

DAC Office: Human Systems Integration

Domain: Data & Analysis

DAC Foundational Research Competencies: Human Engineering and Performance, Cyber Resilience

Army Modernization Priorities: Network/C3I, soldier lethality

Keywords: Human-machine teaming, artificial intelligence, machine learning, decision aides


This area focuses on providing the critical technological breakthroughs needed for future Army multi-, mixed-agent teams across distributed network systems. These technologies must effectively merge human and agent capabilities for collaborative decision making and enhanced team performance; ensure that diverse teams of Soldiers comprehend new and critical information to maintain unprecedented situation awareness; and interact effectively with Soldiers and noncombatants to foster trust and gain community acceptance and influence across cultures and within complex, dynamic, politically sensitive environments. These complex multi-agent networked teams will enable faster and better informed decisions; reduce Soldier workload; provide otherwise unachievable levels of situation understanding and management; and maintain strategic and tactical advantages in future operating environments requiring the integration of cyber-human-physical dimensions.

The objective of this research is to provide the critical technological breakthroughs needed to shape current and future networked operational environments consisting of Army multi-agent, mixed-agent (humans, robots, associate agents, and intelligent systems) in distributed network systems to: (1) effectively enable teaming among human, robotic, and mixed-agent capabilities for collaborative decision-making and enhanced team performance in dynamic, and complex socio-technical environments; (2) ensure that diverse teams of Soldiers comprehend new and critical information to achieve unprecedented situational awareness, while maintaining optimal information burden on individuals; and (3) interact effectively with Soldiers and noncombatants in civil military scenarios to foster trust and gain community acceptance across cultures, and within complex, dynamic, and politically sensitive environments; and visualize and understand the complex dense urban environment battlespace and the diverse socio- cultural dynamics in a dense urban environment to allow Soldiers to effectively execute mission plans, sustain military forces, predict population behavior, and provide humanitarian support to civil populations.

Core research areas include:

i.       Social Sensing of Human-Agent Teams: social sensing platforms for empirically-based behavioral analysis of small team networked interactions from a variety of digital and analog sensors with automated, scalable approaches flexible enough to store variable datatypes stemming from a plethora of data sources. This include pre-processing vast amounts of noisy digital and sensor data-streams to distill key human-system performance meta-data.

ii.     Diagnostics of Socio-Technical Systems: teamwork diagnostics and intelligent decision-support capabilities to track, manage, and significantly impact team readiness and performance with a focus of understanding their interaction with AI tools and autonomous systems, with an emphasis on mission command and the cyber domain.

iii.   Socio-Cultural Influences: captured in virtual agents for training and operational contexts, such as supporting civil military applications that leverage open-source intelligence to gain understanding of the socio-cultural dimensions for mission application and to combat emerging cognitive warfare capabilities.

These research results will apply network science approaches to inform interface design for mission command and distributed and collaborative decision making with heterogeneous AI and autonomous systems, maintaining unit readiness, as well as informing organizational design and tools for an applied understanding of the socio-cultural dimensions to the mission.

Title: Human Systems Integration (HSI) Modeling and Analysis

Announcement ID: DAC BAA-012

TPOC: Andrew Bodenhamer, (573) 563-6031, andrew.s.bodenhamer.civ@army.mil

DAC Office: Human Systems Integration

Domain: Data & Analysis

DAC Foundational Research Competencies: Human Engineering and Performance, Cyber Resilience

Army Modernization Priorities: Soldier Lethality

Keywords: human-machine teaming, artificial intelligence, machine learning, decision aides, simulation


The HSI Modeling and Analysis opportunity focuses on developing effective models and methodologies for predicting and enhancing human, system of system, and mission capabilities throughout the acquisition cycle. These efforts concentrate on identifying human capabilities and limitations within physical, perceptual and cognitive areas to develop and inform methodologies, novel tools, visualizations, interfaces, and decision aids; integrate the HSI domains; and develop technical, parametric system assessments.

The inclusion of physical, perceptual, and cognitive analyses to determine early, cost effective insertion of HSI criteria, capabilities, requirements, and performance specifications within the acquisition process will optimize Soldier-System performance and reduce overall program cost at the system of systems level. Application of these HSI methodologies will provide insight into the Soldiers’ capabilities and operation of systems and will highlight issues and gaps that need to be addressed to achieve an overall balanced system design. The deployment and utilization of these tools and methodologies must keep pace with increasingly advanced and shortened program acquisition schedules. Additionally, human performance data crucial to supporting development of acquisition requirements needed to assess future systems must be updated to apply to current and future technologies, such as the inclusion of manned-unmanned teaming and artificial intelligence. Studies and the resultant human performance data to support development of acquisition requirements, specifications and early system analyses needs to be performed. Practical design, analysis, and operational support tools need to be developed, deployed, and refined so that HSI practitioners can make effective use of the human performance data to achieve the goal of optimizing Soldier-System performance and minimizing cost in emerging system development efforts.

The Human System Modeling and Analysis focus area investigates and advances the sciences relevant to two performance challenges: 1) identifying Soldier performance tradeoffs on mission demands, environment, human characteristics, equipment and technology; and 2) understanding human factors that include sensing, perceptual and cognitive processes, ergonomics, biomechanics, and the tools and methodologies required to manage interaction within these areas and within the required capabilities for future Army warfighting functions. In developing and updating models, tools, and techniques capable of predicting and enhancing human, system and mission capabilities, four research foci will be emphasized:

i.                   Identify, develop, and apply human performance measures of effectiveness and human figure modeling tools.

ii.                 Integrate Human Factors, Mathematics, Statistics, System Engineering, to generate complex and critical tasks combinations that provide the necessary analytical data to support physical, perceptual and cognitive workload assessment and trade space analysis.

iii.               Develop digital engineering approaches to represent the Soldier as a system while considering physical effects, cognitive load, and demographic influences in the context of Soldier Systems Integration.

iv.               Conduct research to identify HSI capabilities, and develop requirements and performance specifications early on in the acquisition cycle for All Domain Protection required capabilities to: increase situational awareness and understanding, assess and improve individual readiness, lighten soldier physical and cognitive workloads, infer and aid in decision making, understand the operational environment, counter obstacles and hazards, and provide command and control to converge protection effects across all domains.

In performing system design analyses with integrated complex human performance behavior, Human Systems Modeling and Analysis aims to shape technology development and system design for the Future Force.

Title: Maneuver Support and Protection: Preserving Essential Capabilities

Announcement ID: DAC BAA-013

TPOC: Robert Clark, (573) 563-5912, robert.d.clark1.civ@army.mil

DAC Office: Human Systems Integration

Domain: Data & Analysis, Lifecyle Engineering

DAC Foundational Research Competencies: Mission Effectiveness Analysis, Decision Support

Army Modernization Priorities: Soldier Lethality

Keywords: analysis, system of systems


This opportunity in Protection focuses on preservation of means, assets and activities to sustain operation of equipment, systems, man-machine teaming, and connectivity despite interference, disruption, assault or combat. Methods to integrate, synchronize and implement layered protection, continue global joint power projection, harden systems, disperse movement and conceal assets is applicable for both military and civilian purposes. Overall preservation of means, assets and activities suggests both overlapping protective methods and a system-of-systems continual update with a shared view of an operating status, Common Operating Picture (COP), as an innate running understanding of how well an asset, force or operation is protected. Estimations that account for factors such as human performance, level of physical protection, status of protective equipment, rates of degradation, and also predict damage impacts help anticipate the durability of forces and the scope of effectiveness or mission readiness. Anticipation of time-changing threat abilities to interfere, degrade or halt friendly forces or operations is translated to creating techniques, technologies or approaches that sustain human performance in degrading conditions, such as CBRN (chemical, biological, radiological or nuclear) contamination, to leveraging networked sensors that provide high-fidelity assessments of hazards, to modeling situations dynamically, to monitoring personnel physiologically and mentally; to detecting and anticipating radiological or mined hazards, to assessing adoption of disposable versus cleanable (decontaminated) assets, and to creating autonomous warning. Some of the solution sets being considered that need significant research are reactive armor, improved detection at standoff ranges, leveraging of unmanned systems, value of manned-unmanned teaming, protective equipment, protocols and vaccines with tolerable physiological and psychological burdens, low-fidelity but high-density multi-modal sensors. Research on methods of regulating, controlling, supervising, analyzing, and understanding people and activities could provide insight to the preserve-protect-enable in the rule of law balance, support consolidation of gained assets-facilities-land, and counter irregular threats. Investigations are of interest that help sustainment and preservation of physical plants such as communities, bases, installations or critical infrastructure like dams, oilfields, nuclear facilities, industrial facilities, depots, airfields, ports, rail nodes against disruption, during heavy usage and through recovery and can be applied to civil, industrial and military operations. Research topic areas include but are not limited to:

i.                   Can Maneuver Support and Protection Situational Understanding be informed by system-of -systems analysis techniques; integration into future Army designs of common operating pictures of maneuver support and/or protection; modeling interconnectedness and interlinking of law operations, security, prisoner/prisoner-or-war operations, and civilian activity; schemes and technologies integrating forensics and biometrics, alerts, alarms; tradeoffs and approaches to resiliency; modeling cognitive and physical recovery of people, systems and assets?

ii.                 Can Maneuver Support or Protection performance be augmented by hardware and software solutions such as machine-based systems, or man-machine, or mostly- human systems compared in effectiveness, durability, and least burdensome; balances between mobile, concealed and hardening approaches for protecting assets; efficiencies achieved by layering various survivability methods and technologies; establishing detain-protect-document paradigms for non-combatants or captured enemies; autonomous wide area security; non-lethal methods, individual restraints, energy barriers, and sensors with military and/or civil applicability; threats or hazards measurements as degradations to human-performance, system-of-systems capability continuance and mission effectiveness; and full spectrum obscurations and deception approaches?

Title: Maneuver Support and Protection: Deny Enemy Freedom of Action

Announcement ID: DAC BAA-014

TPOC: Robert Clark, (573) 563-5912, robert.d.clark1.civ@army.mil

DAC Office: Human Systems Integration

Domain: Data & Analysis, Lifecycle Engineering

DAC Foundational Research Competencies: Mission Effectiveness Analysis, Decision Support

Army Modernization Priorities: Soldier Lethality, Next Generation Combat Vehicle

Keywords: metrics, modeling and simulation, maneuver support


The goal of this research in Maneuver Support is to develop novel and efficient methods, processes and effective approaches to limit enemy ability to move, see, understand or strike friendly forces, designated assets, communities or areas. Threat operation throughout all domains such as battlespace, air and orbital space, logistic support areas, bases, and civilian communities across the electromagnetic and seismic-acoustic spectrums or the physical and information environments may be addressed as potential enemy action space that should be defended. Broad investigation areas include all-domain command and control processes; measures against weapons of mass destruction; preventing mass effects; conducting counter-mobility with obstacles or hazards; limiting effectiveness of enemy observation and sensors; characterizing and countering unconventional warfare; degrading enemy intelligence, surveillance and reconnaissance; understanding threat activities and anticipating impending attacks; persistent surveillance; detecting enemy all-domain deception; reducing enemy speed, standoff, communication and decision making; shaping the physical environment even in the threat’s rear areas where long-range and domain effects originate and denying enemy use of key and strategic terrain. Research questions include but are not limited to:

i.                   Can a system-of-systems approach provide an innately understandable running estimate of enemy freedom of action shareable across all forces; what predictive and modeling approaches are helpful in denying enemy freedom of action; how can enemy intelligence, surveillance and reconnaissance be eliminated, reduced or fooled?

ii.                 Would designs to physically alter the ground, soil bearing, vegetation, infrastructure stability, and trafficability be effective and environmentally responsible; could obscurants effectively deny enemy but not friendly situational understanding; what are approaches to reduce consequences or neutralize use of weapons of mass destruction or mass effect; what approaches are possible to restrict enemy freedom in their rear areas?

Title: Maneuver Support and Protection: Enable Persistent Access

Announcement ID: DAC BAA-015

TPOC: Robert Clark, (573) 563-5912, robert.d.clark1.civ@army.mil

DAC Office: Human Systems Integration

Domain: Data & Analysis, Lifecycle Engineering

DAC Foundational Research Competencies: Mission Effectiveness Analysis, Decision Support

Army Modernization Priorities: Soldier Lethality, Next Generation Combat Vehicle

Keywords: metrics, modeling and simulation, maneuver support


The opportunities in this aspect of Maneuver Support focus on ensuring organizations can establish and retain operational locations and support areas, establish and retain mobility corridors, and to access decisive spaces. Lodgment operations as part of global power projection will require bases and temporary camps that can serve as recovery, rearm/refuel and logistic centers, training spaces, allow capability improvement, equipment adoption and adjustment of tactics and techniques, and safe spaces for force restoration and resilience. Army and/or natural disaster emergency response forces must have assured mobility along lines communication and movement corridors as well as across unimproved terrain. This implies that these elements can detect and counter obstacles and hazards from standoff to preserve their own freedom of movement and can provide a secure environment over wide or deep areas.

Research questions are not limited but include:

i.                   What methods shall assure timely mobilization and deployment from strategic support areas to the joint areas of operations; can security and mobility support that protects and secures critical capabilities-assets-activities, lines communication, and movement corridors be accomplished with man-machine teaming that reduces human exposure to risks; what schemes allow crossing of wet gaps flow rates of up to ten feet per second and dry gaps of any width for heavy military and construction equipment (120-150 tons) at mission critical speeds; how can these groups detect and counter obstacles and hazards from a distance without significantly changing rates or direction of movement?

ii.                 How can general engineering methods provide timely and secure facilities and assets to create and sustain protected locations, logistics, support and deployment areas with minimal transportation and material flows, what procedures and methods can be effectively transferred to local civilian workforces, can a systems-of-systems approach identify, analyze and predict infrastructure vulnerabilities, impacts from buildup of facilities and forces; can utilities and energy flows be designed to efficiently be emplaced and operated as discrete networks; how will human-infrastructure systems be measured for efficiency, effectiveness and environmental accountability?


Title: Maneuver Support and Protection: Understand the Operation Environment

Announcement ID: DAC BAA-016

TPOC: Robert Clark, (573) 563-5912, robert.d.clark1.civ@army.mil

DAC Office: Human Systems Integration

Domain: Data & Analysis, Lifecycle Engineering

DAC Foundational Research Competencies: Mission Effectiveness Analysis

Army Modernization Priorities: Soldier Lethality

Keywords: CBRN, modeling and simulation, human-machine teaming


Protection of friendly operations and providing Maneuver Support requires a deep understanding of the continually challenging operational environment. The operational environment is the composite of conditions, circumstances and influences that affect the employment of capabilities and bear on the decisions of the commanders. The Future Army faces new and unprecedented challenges to work with allies and unified action partners to understand the operational environment across all domains. Broad research areas include but are not limited to threat sensing, geospatial data collection, 2D and 3D mapping of surface-subsurface-interior spaces, terrain and infrastructure assessment and mobility assessment. Some of the research questions are:

i.              How can US and partners have interoperable bases and access rights; share mapping of the electromagnetic spectrum and computer networks; assess friendly vulnerabilities and determine protection requirements; maintain an innately understandable status of the operational environment; collect data on threats, obstacles and hazards; develop recovery and mitigation strategies from incidents; visualize and understand the physical, cognitive and virtual environments characterizing threat activities and environmental hazards; employ autonomous capability to generate, manage, analyze, and disseminate geospatial data?

ii.             Can early warning from CBRN reconnaissance and surveillance be integrated across all US and partner assets from all-source information flow; how can machine intelligence assessment and trend development efficiently leverage sensor integration and analysis from rapid, on-the-move reconnaissance including unmanned aerial and ground platforms and swarms; will coupling of criminal and mob information from multiple sources create a clear understanding of security threats; how can battlefield forensics and biometrics authenticate friendly forces, identify and target threat actors, explosives or CBRN hazards, cybercrimes and physical crime to counter all domain threats, hazards and obstacles; what factors within human-machine interactions can be best leveraged in each use case?

Title: Sustainment Performance and Mission Success Impacts

Announcement ID: DAC BAA-017

TPOC: Dr. David Mortin, (410) 652-8594, david.e.mortin.civ@army.mil

DAC Office: Sustainment

Domain: Lifecycle Engineering

DAC Foundational Research Competencies: Decision Support, Reliability, Availability, and Maintainability

Army Modernization Priorities:

Keywords: supply chain, sustainment, data analytics


Most of an Army weapon system’s life cycle costs are associated with sustainment (approximately 70%). With accelerated schedules to meet Warfighter’s needs, the Army assumes more risk for sustainment, reliability, and mission success. This area focuses on the development and refinement of the modeling and simulation that will provide Army decision makers the link between weapon system performance (as a system of systems), mission success, and the long-term sustainment and readiness impacts that we must budget for. This area will leverage current initiatives that have formed a foundation for the necessary data analysis, visualization, and trades structure.

This research space aims to understand how sustainment parameters affect overall system performance and what decisions need to be made to optimize sustainment positioning in order to maximize overall longstanding system performance and availability. On the domestic front, this idea has become ever more poignant as we saw mass disruption in US commercial supply lines in 2020-2021 due to COVID-19. The ability to plan and assure supply for manufacturing and sustainment drastically changed standard business processes.

What factors, parameters, and data points are needed to understand the overall supply and sustainment posture? Which are the most critical to the overall system? How can we model that system in order to project impacts and help inform decision makers?

Title: Reliability of alternative methods for energy generation and storage alternatives

Announcement ID: DAC BAA-018

TPOC: Dr. Richard Heine, (443) 643-8317, richard.w.heine.civ@army.mil

DAC Office: Sustainment

Domain: Data & Analysis, Lifecycle Engineering

DAC Foundational Research Competencies: Integrated Materiel Performance, Reliability, Availability, and Maintainability

Army Modernization Priorities: Next Generation Combat Vehicle

Keywords: energy generation, electrification, energy storage, alternative fuel


With the increasing electrification of Army systems, alternative methods of energy generation and storage are required to maintain or reduce the logistics footprint according to the tenets of Multi-Domain Operations. Often these alternative methods come with an increase in complexity or contain novel technologies. This area will focus on assessing the technology maturity and complexity and the resulting effect on system reliability.

In parallel within the commercial market, how can we assess the complexities of the inclusion of electric car, hydrogen vehicles, fuel cell, etc. in the domestic markets. Will the additional of large solar arrays and a multitude of residential roof arrays increase the reliability of the overall energy footprint or create a unreliable unsteady variance? Will all the extra electronics and advanced control systems provide an integrated foundation or a sustainment cost that exceeds the value gained?

This research area looks to understand the factors that will balance the increased capabilities envisioned in a more robust electrification vs the reliability of the systems to make that power realizable and how to model and assess that dynamic.

Title: Using Neural Networks to Improve Army Forecasting

Announcement ID: DAC BAA-019

TPOC: Mr. Kevin Shorter, (717) 870-1881, kevin.e.shorter.civ@army.mil

DAC Office: Sustainment

Domain: Data & Analysis, Lifecycle Engineering

DAC Foundational Research Competencies: Decision Support

Army Modernization Priorities:

Keywords: forecasting, inventory planning, machine learning, pattern recognition


Inventory requirements determination and evaluation models, such as those used every day by the Army to manage billions of dollars of wholesale inventories, are designed to answer two fundamental questions: when to order and how much to order. In order to answer those questions effectively, inventory models universally require a description of the processes governing the demand for the items supported by the supply system. The most fundamental datum in the description of the demand process for an item is a forecast of the average monthly demand (AMD). An accurate forecast of AMD is essential to establishing effective stock policies and inventory levels.

The Army has used and studied many classical forecasting techniques for wholesale AMD. Yet, historical evidence shows that these classical techniques are failing to provide accurate forecasts of wholesale (National Level Inventory Control Points) AMD. The repeated failures of classical techniques to accurately forecast Army wholesale AMD indicates that there are probably too many time varying factors affecting wholesale AMD to be successfully included in a viable classical forecasting model. However, advancements in neural networks raise the intriguing and very real possibility that the “pattern recognition” capabilities of neural nets can be used to accurately forecast wholesale AMD. In this study DAC will investigate the feasibility of using neural network and machine learning technology to forecast peacetime wholesale AMD. If feasible, DAC will develop a prototype neural network that will be “trained” to consider all the possible factors that affect peacetime wholesale AMD and then to forecast wholesale AMD for use in Army wholesale inventory models.

Title: Using Machine Learning and Open Source Big Data Platforms to Enable Prognostics and Predictive Maintenance

Announcement ID: DAC BAA-020

TPOC: Mr. Scott Kilby, (410) 652 3135, Thomas.s.kilby.civ@army.mil

DAC Office: Sustainment

Domain: Data & Analysis, Lifecycle Engineering

DAC Foundational Research Competencies: Decision Support

Army Modernization Priorities: Next Generation Combat Vehicle

Keywords: data analysis, predictive maintenance, efficiency, logistics, internet of things


The U.S. Army’s intention is to implement prognostics and predictive logistics (PL)for their ground vehicle fleet. PL can have many benefits including informing the vehicle crew of impending vehicle system failures, informing the unit commander that they may lose capability of one of their vehicles, and informing the unit level and fleet level logistic support organizations that a specific part needs to be ordered. In addition, prognostics and predictive analytics helps to ensure that the maintenance/sustainment organization is better prepared to efficiently conduct the repair of vehicles since they can plan and schedule the future maintenance event which provides greater vehicle readiness and ensures mission success due to awareness of current and future health condition of the vehicle fleet.

Predictive maintenance technologies and methods have been successfully applied across manufacturing industries, electrical power generation, and more recently for commercial vehicles over the last 40 years. The U.S. Army is wisely following these industries in the application of predictive maintenance to improve the efficiencies and effectiveness of their maintenance and logistic organizations.

Successful commercial industries are utilizing the latest wave of technology known as Industrial Internet of Things (IIoT) to implement predictive maintenance capability at their facilities and for their critical mobile assets. The IIoT four key technologies include edge devices, cloud computing, telematics, and machine learning analytics. All four of these technologies have been implemented by the Army with varying levels to enable predictive maintenance with the exception of telematics. Though telematics is one of the key technologies to enable data driven fleet management it has been the most difficult to implement for the Army, due to cyber concerns, implementation costs, and CONOPS complexity. The unique challenge for the Army is that all of their critical assets are not only mobile but they are deployed to locations where telematics are not readily available compared to commercial industry operating locations. Finding a solution to deploy telematics that is cost effective and cyber secure is a challenge the Army is looking to solve.

Due to the challenges of telematics implementation, the ability for the U.S. Army to effectively implement predictive maintenance with prognostics for their ground vehicle fleet with a maximum effectiveness relies on the ability to process the sensor data in real time at the edge. Enabling the capability to gather and process vehicle data using on-platform edge devices for prognostics and then transferring data off-platform so additional predictive analytics can be implemented at the Enterprise on-premises sites and/or cloud locations is the approach that will provide the greatest positive impact to the Army.

In order to implement a complete solution to enable PL for Army ground vehicles, an on-platform data processing for prognostics and predictions using edge devices, a deployable telematic solution, and scalable Enterprise analytics is required to serve the entire ground vehicle fleet. One of the major enablers for this objective is the integrated vehicle health management (IVHM) edge system. The IVHM capability can vary from basic warnings and diagnostic faults all the way through embedded prognostics and health predictions and status. With a fully integrated IVHM, machine learning and health algorithms can be run not only in the Enterprise but on the vehicle or asset itself. To date, most of the advanced analytics has occurred in the Enterprise where there is more processing power and access to other data sources. Evolving the analytical capabilities that are present in the Enterprise to where they can be executed on the IVHM is the ultimate goal. To get there the Army will continue to leverage Enterprise analytics and industry lessons learned to advance analytics to prognostics.

Title: Solar Panel Performance Analysis

Announcement ID: DAC BAA-021

TPOC: Mr. Kevin Guite, (410) 278-2143, kevin.m.guite.civ@army.mil

DAC Office: Sustainment

Domain: Data & Analysis, Lifecycle Engineering

DAC Foundational Research Competencies: Energy Science, Integrated Materiel Performance

Army Modernization Priorities: Next Generation Combat Vehicle

Keywords: solar chargers, battery


Analysis of commercially available solar charging systems have shown that current solar products are safe and durable products capable of recharging and maintaining multiple 6TAGM battery sets that power Army tactical wheeled vehicles. Research on perovskite structures and absorber materials shows the potential for these components to be able to increase the efficiency of solar energy conversion at reduced weight and production cost when compared to current solar cell designs. As these new solar cell technologies are formulated into solar charging products, an opportunity is available to analyze their performance against current solar cell technologies and determine their impact for Army systems. An examination of the efficiency and performance of these emerging products will provide for a better understanding of their impact to vehicle readiness and sustainment costs for the Army’s fleet of tactical wheeled vehicles and electric generator sets.

The goal of this technical program is to enable the analysis of the performance of the new solar cell technologies when recharging and maintaining 6TAGM batteries that are the primary battery systems in Army tactical wheeled vehicles. Collaborative efforts with Army research organizations, academic institutions, and industry experts will lead to the development of properly sized and durable solar products suitable for use on Army systems. An analysis of solar products utilizing the new solar cell technology would occur in both static and operational test scenarios across multiple seasons and in varying environmental conditions. Sustained battery voltage levels and recharge times will be collected and compared against measures from commercially available systems to assess the improved performance from the new technologies. The focus of this initiative is to quantify the performance of emerging solar cell technologies and to better understand their ability to support the Army’s goals of enabling precision logistics, supporting multi-domain operations, and contributing to improvements to readiness and sustainment resources required.

Title: Modeling & Simulation (M&S) Tools and Algorithms to Assess Electromagnetic Pulse (EMP) Vulnerability, Survivability, and Mitigation / Shielding

Announcement ID: DAC BAA-022

TPOC: Mr. Robert Hessian, (410) 278-3582, Robert.t.hessian.civ@army.mil

DAC Office: Soldier and Ground Analysis

Domain: Data & Analysis, Lifecycle Engineering

DAC Foundational Research Competencies: Electronic Warfare (EW) Threat Defense

Army Modernization Priorities: Soldier Lethality, Next Generation Combat Vehicle

Keywords: electromagnetic pulse, EMP, modeling and simulation


This opportunity focuses on developing and improving M&S tools and algorithms to expand knowledge in two key areas:

i.       Assessing mitigation and/or protection factors from EMP effects. This can include additional technologies used to isolate equipment from coupling effects and/or the use of physical or environmental structures (e.g. concrete walls, terrain, surge protectors, other electrical circuit components, etc.) to assess shielding mitigation from EMPs.

ii.     Assessing the resulting voltage/current due to coupling between an exposed component (e.g. wire, antenna, etc.) and unexposed component from an EMP exposure.

The development of these M&S tools and algorithms in the EMP area will provide the foundation for developing, integrating, and implementing nuclear threat environments and effects into existing component-level and system-level computational M&S capabilities. Further, these efforts will enable the Army to make faster, more-informed modernization decisions; provide understanding of EMP effects on the battlefield; and enable operational units to maintain strategic and tactical advantages in future nuclear operating and Multi-Domain Operations (MDO) environments.

The objective of this research addresses two aspects related to EMP exposure. The first aspect centers on understanding protective measure performance. More specifically, the research is to investigate materials, data, and available methods that accurately simulate the attenuation and/or mitigation of the effects of an EMP exposure. Moreover, the research would include developing the framework, plans, and executing demonstrations, tests, and analysis/assessments for the development of protection factors (similar to that which exist for exposure to nuclear radiation). This would include developing a test approach to identify potential shielding materials to be analyzed, how the data would be generated, conducting data collection, and performing the evaluation/assessment of the data collected. Development of performance protection factors will consider different material thicknesses, as well as the strength of isolation devices (e.g., surge protection) from the pulses that may be experienced. The result of this research would be data characterizing attenuation based on shielding or coupling protections vice EMP source strength. Ultimately, the objective is to develop shielding performance functions/algorithms for military equipment for use in computational M&S tools in lieu of repeated physical testing for future new items.

The second aspect addresses understanding the coupling performance in exposed elements (e.g., antenna) for a range of EMP source strengths, to include angle of attack (e.g. perpendicular, parallel, etc.). Based on data collected, a coupling assessment should enable the derivation of an algorithm to assess voltage and current from the point of coupling to the associated system. Coupling of components represents a vulnerability to platforms as the associated exposed elements (e.g., antennas, sensors, etc.) are typically not protected from traditional physical shielding mechanisms. The research conducted shall enable the performance data, information, and analysis/assessment to inform design of future mitigation/protection capabilities for associated operating systems, and for assessing the vulnerability of specific components, systems, and/or platforms in M&S environments.

Overall, being able to leverage M&S tools with this complete set of capabilities enables a reduction in future physical testing needs at great savings to Project Managers and Materiel Developers. Improved understanding of EMP effects will improve M&S capabilities in support of battlefield simulations, as well as design development of future platforms. Ultimately, with sufficient data, assessment of design development options via M&S, as opposed to building prototypes for testing to determine performance, will accelerate the design cycle, reduce costs, and support the development of more effective equipment.

Title: Automated Geometry Simplification to Support Rapid SLV Analysis

Announcement ID: DAC BAA-023

TPOC: Mr. Clifford Yapp, (410) 278-1382, clifford.w.yapp.civ@army.mil

DAC Office: Warfighter & Futures Integration

Domain: Data & Analysis, Lifecycle Engineering

DAC Foundational Research Competencies: Decision Support

Army Modernization Priorities: Soldier Lethality

Keywords: modeling and simulation, machine learning



Modern SLV (Survivability, Lethality, and Vulnerability) analysis workflows often involve improvement, correction and simplification of commercially generated manufacturing Computer Aided Design (CAD) geometric models to achieve vehicle representations suitable for analysis purposes. Because these geometries are often extremely large, representing manufacturing level detail, they can present resource challenges for computational systems tasked with running the analyses.

Traditional Constructive Solid Geometry (CSG) Boolean tree representations of vehicles offer advantages for this type of analysis, but the standard geometric representation used in most models today is Non-Uniform Rational B-Spline Boundary Representations (NURBS Breps). Although NURBS offers greater representational flexibility than CSG, most shapes needed to represent vehicle targets may be either exactly expressed or approximated with CSG techniques. An automated means of converting existing NURBS geometries to a CSG representation (automated meaning not requiring manual human intervention in the conversion process) would allow the analysis community to realize both the benefits of leveraging pre-existing vehicle descriptions and the performance advantages of CSG representation.

A viable conversion technique would move beyond exactly representing shapes to recognizing based on user supplied parameters when a simpler, more compact shape would suffice. For example, if a cylinder and a mating hole are modeled with rounded corners, and the modeler has supplied the conversion process a size threshold below which simplification should occur, the conversion routine should automatically recognize that a basic cylinder primitive can be used to represent the cylinder and hole shapes rather than approximating the rounding at the edges.

Rapid turn-around in analysis is a key component of iteratively evaluating and improving designs. With a faster and easier analysis process, we can reduce costs and refine to better designs within available time and personnel resources. Geometric model preparation and analysis are long standing areas of focus for efficiency improvements, and automatically leveraging CSG representations to improve those metrics is an area of interest.

Title: Personnel Survivability

Announcement ID: DAC BAA-024

TPOC: TPOC: Mr. Ronald Bowers, (410) 278-3348, ronald.a.bowers2.civ@army.mil

DAC Office: Warfighter & Futures Integration

Domain: Data & Analysis

DAC Foundational Research Competencies: Mission Effectiveness Analysis, Human Engineering and Performance

Army Modernization Priorities: Soldier Lethality

Keywords: soldier survivability, SLV, experimentation, analysis, modeling and simulation


The Personnel Survivability research area concentrates on the advancement of research and analysis to identify, understand, quantify, and model the effects of threat-target interactions on combat personnel, including injury assessment, performance, and operational effectiveness. Advances in research and experiments in the area of personnel survivability are foundational to the identification and development of scientific techniques to: 1) mitigate injury and enhance the survivability of Soldiers facing the wide range of battlefield threats, including ballistic, thermal, toxic substances, and less-than-lethal anti-personnel weapons; 2) enhance lethality of antipersonnel ballistic munitions; and 3) understand the effects of current and future weapons against personnel and protective systems. In addition to Soldier protection, Soldier survivability is assessed in terms of Soldier lethality, situational awareness, and the ability to effectively communicate and operate undetected when needed.

This research focuses on describing a systematic plan of multidisciplinary research that addresses critical questions about the nature of human injury mechanisms and the interactions of the Soldier with enabling technologies that provide protection, lethality, mobility, information, communication and concealment. It addresses adaptive behavior on the battlefield to increase survivability in a hostile environment and the development of methodologies and models to address critical questions surrounding these interactions and implications on Soldier survivability.

DAC will apply these methodologies to identify the benefits and risks associated with new technologies prior to system design and integration supporting capabilities, such as Adaptive Soldier Architecture and trade space analysis of new individual Soldier and squad technologies. DAC will transition our products for use internally and to other DoD users to interactively conduct complex, credible analyses that meet their varied needs as these new technologies mature and are applied to conceptual and developmental Army systems. Using this approach we will extend our subject matter expertise in performing early SLV analysis to “the left” for early SLV (Survivability, Lethality, and Vulnerability) analysis and to “the right” for use in evaluation through the acquisition process, as well as to operational users for mission planning purposes.

This research will also investigate and advance understanding and modeling the Soldier as a system to look at personnel survivability. Personnel survivability is characterized in terms of injury, degraded Soldier performance and capability with and without injury, and risks to long-term quality of life given injury. Because personnel survivability depends on enabling capabilities provided by a number of technologies, personnel survivability is studied in the context of the Soldier as a system, where Soldier lethality and the Soldiers’ ability to sense, communicate, and to operate undetected are also taken into consideration.

The strategic approach includes:

i.                   Fundamental and applied research projects to understand and quantify human survivability and performance to develop human injury and performance models.

ii.                 Applied research to understand and characterize next-generation Soldier augmentation systems, protective systems, novel protective materials and future non-lethal and lethal systems that target precision, scalable effects and improved range, the ability to sense and communicate on the battlefield, and to operate undetected.

iii.               Development, maintenance, and application of SLV analysis capability that is adaptable, interoperable, and interactive; enables analyses of complex interactions in a mission/capabilities context, exploits emerging computation capabilities and can be used within a collaborative simulation.

iv.               Development, application, verification, validation, and transition of tools, techniques and methodologies for testing, analyzing, and evaluating Soldier performance and survivability.

Title: Simplified Combat Simulation to Support Science and Technology (S&T) Community

Announcement ID: DAC BAA-025

TPOC: Mr. Zachary Steelman, (410) 278-0357, zachary.l.steelman.civ@army.mil

DAC Office: Warfighter & Futures Integration

Domain: Data & Analysis

DAC Foundational Research Competencies: Mission Effectiveness Analysis

Army Modernization Priorities:

Keywords: combat simulation, scenarios, data analytics


Prioritizing mission effectiveness early on in the development cycle will allow the Army to target technology development resources and efforts to those that will deliver the greatest impact for the warfighter. Current Combat Simulation (CS) capabilities requires the user to have extensive experience in performing mission effectiveness analysis in order to deliver accurate and impactful results. This requirement prohibits the use of these simulations by members of the S&T community to prioritize mission impact to inform engineering decision during the technology development process.

Developing a simplified user interface that works in conjunction with OneSAF would provide the critical capability to adequately represent S&T. Having a user interface that does not require extensive experience in the execution of OneSAF and the ability for the user to easily adjust parameters of interest; the S&T community can perform mission effectiveness analysis without the need for CS SME support.

The development of a set of analysis community approved scenarios will allow the mission effectiveness analysis to capture the full scope of environments in which the emerging technologies will be utilized. Having an approved set of scenarios will ensure results obtained have credibility and do not bias the analysis.

OneSAF produces an extensive amount of data into multiple files, which require CS expertise to analyze. A simplified tool to process the OneSAF output files and present results for user selected metrics removes the need for a CS SME to be involved in the backend data analytics.

Support to DAC Research Competencies:

Title: Support to DAC Research Competencies

Announcement ID: DAC BAA-026

TPOC: DACBAA@army.mil.

DAC Office: Any

Domain: Any

DAC Foundational Research Competencies: Aligns to DAC’s core mission

Army Modernization Priorities: Any



Under this research topic, DAC will consider whitepapers and proposals that may not directly align to a topic published by a DAC TPOC, but can demonstrate a strong alignment to DAC’s mission. DAC’s research mission is executed within identified applied scientific research competencies that provide the Army foundational expertise and specialized capabilities grounded in scientific excellence and driven by unique Army challenges. DAC is always interested in considering innovative research whitepapers and proposals outside of the published topics on the DAC website that demonstrate a strong alignment to DAC’s foundational research competencies and have the potential to create discovery, innovation, and transition of technologies for Army transformational overmatch. To learn more about DAC’s Applied Scientific research competencies see Appendix A.

Appendix A: DEVCOM Analysis Center Mission, Domain Competencies and Core Competencies


I.              Mission

The DEVCOM Analysis Center’s mission is to: Inform Army modernization and readiness decisions with objective Analysis enabled through Tool development and Data curation.

II.           Domain Descriptions

Domains: Set of enduring competencies required to execute the DEVCOM mission. Six (6) DEVCOM domains exist including: Lifecycle Engineering, Science & Technology (S&T), Foundational Research, Data & Analysis.

1.0 Lifecycle Engineering Domain: Set of enduring competencies required to execute DEVCOM mission of systems engineering and programmatic support to current and emerging Army capability development and sustainment, to include engineering support to S&T Projects. Supports an established program of record, focuses on prototyping of a soon-to-be fielded (0-~3 years) program of record, or provides support of fielded end items. Provides engineering support with an emphasis on informing concepts and advancing capabilities

2.0 Science & Technology Domain: Set of enduring competencies required to execute DEVCOM mission of applied research to advance capabilities and inform concepts/requirements. Applied research focused on translating underlying phenomena into specific application domains for mid and long-term mission impacts (1 to ~15 years out). Project meets a recognized need or has launched initial field experiments

3.0 Foundational Research Domain: Set of enduring competencies required to execute DEVCOM mission of foundation research. Farsighted high payoff research related to long-term (15-20 years out) national security needs (e.g. Priority Research Areas) Research that is not tied to any specific process or products.

4.0 Data & Analysis Domain: Set of enduring competencies required to execute DEVCOM mission of providing data and analytical support and recommendations. Developing data from assessments, experiments, Soldier touchpoints, and modeling and simulation. Creating tools to automate or standardize repeatable decisions based on data. Inform decisions related to the acquisition lifecycle or business functions.

III.         DEVCOM Analysis Domain Competencies and Core Competencies


1.1 Cyber Resilience Competency: This competency in the DEVCOM Analysis Domain leverages highly skilled and certified cyber experts with degrees and/or backgrounds in the fields of science, technology, engineering, and mathematics (STEM), threat intelligence, human systems understanding and military operations to enable the design, development, integration, convergence and operation of resilient warfighting capability. Performs experimentation, analysis and assesses capability to enable continuous and effective warfighting operations in contested multi-domain threat environments.  Delivers analytics and soldier-driven experimentation supported by research and the development of models, tools, exploits and simulations, leveraging cyber ranges to facilitate objective life cycle threat experimentation and analysis & assessment in support of readiness today and a more lethal future force operating in a Multi-Domain Operations environment tomorrow.

1.1.1     Certified Red Team Cyber Vulnerability Analysis, Experimentation and Remediation Core Competency:  This core competency within the DEVCOM Analysis Domain Cyber Resilience Competency focuses on the early understanding of cyber resilience associated with the design, development and integration of Army warfighting technologies. The objective is to conduct early analysis, modeling and simulation (M&S), and experimentation on Army warfighting technologies to better understand cyber-attack surfaces and potential high impact or highly likely cyber-attack vectors through early collaboration between cyber professionals, government researchers and technology developers, industry technology development partners, and Soldier operators. The data includes critical Soldier touch point input which will influence design and development of cyber-resilient warfighting technologies which can be operated efficiently and effectively in a Multi-Domain Operational (MDO) environment. This core competency combines cyber threat research, experimentation, analysis, and test & evaluation of Army warfighting technologies including Soldier operators through the conduct of Red Team certified cyber vulnerability assessments on critical Army modernization and readiness technologies being developed, integrated and/or fielded. This core competency also leverages DAC’s Red Team certified cyber experts to work with technology developers and/or users/Soldiers to identify remediation recommendations and reassess remediation via verification of fixes (VoF) cyber assessments. Additionally, this core competency collects, and leverages data generated from cyber threat M&S, experimentation, and testing to analyze and understand the cyber resilience of the system (technology + Soldier) to effectively complete the mission when exposed to near-peer CEMA threats deployed in a MDO environment. Lastly, this core competency leverages its Rapid Acquisition Risk Management Framework (RMF) authority given by HQDA CIO/G6 to execute Cyber Vulnerability Assessments (VAs) on Army rapid capability technologies destined for expedited deployment to support the Warfighter.

1.1.2     Threat Tools/Exploits and Advanced Analytical Systems Development Core Competency: This core competency within the DEVCOM Analysis Domain Cyber Resilience Competency is focused on data analytics and the requisite analysis to understand the interaction and impact of cyber threats on Army modernization and readiness warfighting technologies that include the Soldier operators. The core competency uses the multi-disciplinary fields of computer science, engineering, artificial intelligence, threat intelligence and mathematics. These individuals understand the tactical and operational implications on Army warfighting operations introduced by the cyber threat and are able to assess risk and provide valuable remediation recommendations across doctrine, organization, training, materiel, leadership, personnel, facilities, and policy (DOTMLP-F) to mitigate critical cyber vulnerabilities and their associated risks which would prevent or impact mission success. To do this, these experts conduct research and develop cyber threat representative tools, cyber resiliency analysis tools, methodologies, exploits, and M&S. These events are necessary to assess the security posture of Army warfighting technologies operating in multi-Domain threat environments as well as to assess Warfighter resilience. The research and development of tools, methodologies and exploits is then applied to analyze and assess critical warfighting technologies, e.g., Internet Protocol (IP) based and non-IP based wired and wireless networks, Controller Area Network (CAN) bus, industrial control systems (ICS), artificial intelligence (AI), cloud computing, augmented reality, and novel futuristic architectures and technologies that are in the design phases for incorporation into future Multi-Domain battlefields.

1.2 Electronics Warfare (EW) Threat Defense Competency: This competency in the DEVCOM Analysis Domain uses the multi-disciplinary fields of computer science, engineering, artificial intelligence, threat intelligence and human systems understanding to enable the design, development, integration, convergence and operation of secure and resilient warfighting capabilities. Performs experimentation, analysis and assesses capability to enable continuous and effective warfighting operations in contested multi-domain threat environments. Delivers analytics and experimentation supported by the development of models, tools, exploits and simulations, leveraging cyber ranges to facilitate objective life cycle threat experimentation and analysis & assessment in support of readiness today and a more lethal future force operating in a Multi-Domain Operations environment tomorrow.

1.2.1     EO/IR Experimentation and Analysis Core Competency: This core competency within the DEVCOM Analysis Domain, Electronic Warfare Threat Defense Competency provides theoretical, laboratory, and field evaluation and analysis of threat and friendly laser detection/countermeasure systems. Conducts laser jamming/damage analysis of sensors & eye damage and optical augmentation (OA) signature/detectability of US Army optical systems and threat optical targets. Utilizes state-of-the-art software and hardware to provide accurate EO/IR signature and battlefield obscurant characterizations used for sensor performance assessments. EO/IR physic-based modeling tools allow for the evaluation of sensors spectral response to signatures at various ranges and obscurant environments. Uses modeling/simulation tools to conduct tactical/system/mission effectiveness and assessment/characterization/analysis and experimentation for current, emerging, and potential EO/IR technologies. Includes general scientist, physicist and electrical engineering positions specializing in photonics and electromagnetic spectrum optical wavelength bands. Includes analyst positions specializing in modeling/simulation, data science, and mathematics/statistics supporting analysis in photonics and electromagnetic spectrum optical wavelength bands.

1.2.2     Radio Frequency Experimentation and Analysis Core Competency: This core competency within the DEVCOM Analysis Domain, Electronic Warfare Threat Defense Competency provides Electronic Attack (EA), Electronic Protect (EP) and Electronic Support (ES) vulnerability/survivability modeling and simulation, and tactical/system/mission effectiveness and assessment/characterization/analysis and experimentation for current, emerging, and potential technologies utilized by the US Army. Includes engineering positions specializing in electromagnetics, signal processing, and circuits/microelectronics. Includes analyst positions specializing in modeling/simulation, data science, and mathematics/statistics.

1.3 Human Engineering and Performance Competency: This competency within the DEVCOM Analysis Domain involves the characterization of warfighter strengths and limitations related to physical and mental demands in the design, development and test and evaluation of Army systems.

1.3.1     Army Human Systems Integration (HSI) Analysis and Experimentation Core Competency: This core competency within the DEVCOM Analysis Domain, Human Engineering and Performance Competency, includes positions specializing in human factors engineering (HFE) analysis, experimentation and applied research for warfighter centric design, and human physical, physiological, and cognitive attributes.

1.3.2     HSI Applied Advanced Systems Development Core Competency: This core competency within the DEVCOM Analysis Domain, Human Engineering and Performance Competency, includes positions specializing in human science research theory and innovative techniques for operational design, training, and advanced systems development for military application.


1.3.3     HSI Methodology, Models, Tools, and Simulations Core Competency: This core competency within the DEVCOM Analysis Domain, Human Engineering and Performance Competency, includes positions specializing in human performance behaviors and characteristics for implementation in HSI methods, models, tools, and simulations to quantitatively predict the impact of human systems integration variables (manpower, personnel, training, and human factors) in Multi-Domain Operations. Additional knowledge includes advanced programming languages, applied statistics, machine learning, artificial intelligence, data mining, and data visualization.

1.4 Integrated Materiel Performance Competency: This competency in the DEVCOM Analysis Domain involves: the conduct of decision-focused analyses and experiments on components, systems, and systems-of-systems to determine lethality, vulnerability, performance, effectiveness, reliability and mobility and to determine the relative utility of alternative solutions to combat capability gaps; the determination of residual capabilities that Soldiers and their weapon systems have after damage-inducing events (combat or test) and the development of recommendations to mitigate damage; the development of performance and operational effects data for use in combat models; the development, verification and validation (V&V) of methodologies and empirical and physics-based models and tools necessary to perform such analyses; and the determination of the adequacy of experimentation and test programs to provide data for model V&V and acquisition program decisions.

1.4.1     Ballistics Analysis Core Competency: This core competency within the DEVCOM Analysis Domain, Integrated Materiel Performance competency includes positions specializing in applying expertise in ballistics and other kinetic damage-inducing mechanisms to the analysis of system and personnel vulnerability and lethality (V/L). It requires expertise in penetration, damage mechanisms and behind-armor effects for various threat types in order to predict damage, injuries and residual capabilities prior to ballistics tests; assess damage from tests; and analyze V/L for a wide range of engagement conditions that cannot be tested. Experts in the Ballistics Analysis Core Competency identify vulnerabilities and recommend mitigation approaches as well as develop weaponeering data for use by operational forces. They collaborate with subject-matter experts across the defense test and evaluation enterprise in developing and executing live-fire test and evaluation programs for major acquisition programs.

1.4.2     Engineering Analysis Core Competency: This core competency within the DEVCOM Analysis Domain, Integrated Materiel Performance competency includes positions specializing in applying scientific and engineering expertise in the conduct of analyses to determine the performance, effectiveness, vulnerability, mobility and relative utility of existing and conceptual systems and systems-of-systems, to include Analyses of Alternatives. It requires expertise in system design, functionality and operation in order to develop and apply solid-geometry, finite-element computer representations, and other engineering models in analyzing the ability of systems to achieve performance specifications and requirements. Experts in the Engineering Analysis Core Competency work with subject matter experts in combat modeling to be able to understand data requirements and generate the performance and effectiveness input data for combat models.

1.4.3     Methodology/Model/Instrumentation Development Core Competency: This core competency within the DEVCOM Analysis Domain, Integrated Materiel Performance competency includes positions specializing in developing and implementing methodology in models, simulations and instrumentation that represent Soldier survivability or system performance, effectiveness, vulnerability, reliability or mobility. It requires detailed knowledge in one or more scientific or engineering fields such as statistical theory, design of experiments, advanced programming languages, simulation techniques, verification and validation (V&V) techniques, injury biomechanics, signal processing, vehicle dynamics, etc. Experts in the Methodology/Model/Instrumentation Development Core Competency work with subject-matter experts in various technologies, engineering analysis and ballistics analysis to understand the nature of the phenomena to be modeled then develop methodology at the appropriate fidelity that can be underpinned by credible experimental data, implement the methodology in models or instrumentation, and conduct V&V to ensure credibility.

1.4.4     Operational Power and Energy Analysis Core Competency: This core competency within the DEVCOM Analysis Domain includes positions specializing in developing methodologies and conducting item-level energy analyses to elucidate the performance and sustainment characteristics of systems. This competency requires knowledge regarding the generation, storage, transport and application of mechanical, chemical, electrical, renewable and nuclear sources of energy. Experts in Operational Power and Energy work with subject matter experts in military operations, logistics, technology development and system design to understand how the technologies will be employed. Experts in Operational Power and Energy then model these systems within an operational context to provide a foundation for senior Army leadership acquisition and sustainment decisions.

1.4.5     Reliability, Availability, and Maintainability Core Competency: This core competency within the DEVCOM Analysis Domain includes highly qualified personnel developing and applying analytic approaches and tools to assess reliability of materiel and recommend ways to reduce life cycle costs. Specific skills required to assess the reliability growth of a materiel system from the incorporation of corrective actions during test programs and the application of the Reliability Scorecard to examine a program’s use of reliability best practices, as well as planned and completed reliability tasks in order to evaluate a program’s reliability progress. Application of Physics of Failure (PoF) design and analysis tools to predict reliability and minimize potential redesign at the component level based on the ability to understand how things can fail under the intended operational environments. Routine use of dynamics models for conducting real-time reliability and fatigue analyses for key program trades and schedule acceleration. Products ultimately lead to Army systems with enhanced mission effectiveness and reduced costs. 

1.5 Mission Effectiveness Analysis Competency: This competency in the DEVCOM Analysis Domain involves analyzing the impact of system performance, vulnerabilities, human interaction, and/or system interdependencies on mission success in military operations. The goal is to assess system-level effects in the context of how well they enable a unit to accomplish the mission.

1.5.1     Combat Simulation Development and Analysis Core Competency: This core competency within the DEVCOM Analysis Domain, Mission Effectiveness Analysis Competency includes positions specializing in developing and implementing methodology in simulations that represent force-on-force or small-unit engagements. It requires knowledge of advanced programming languages, simulation techniques, verification and validation (V&V) techniques, and battlefield phenomena. Experts in the Combat Simulation Development and Analysis Core Competency work with subject matter experts in military tactics and various technologies to understand the nature of the phenomena to be modeled, then develop methodology at the appropriate fidelity that can be underpinned by credible performance data, implement the methodology in combat simulations, and conduct V&V of the model to ensure credibility. This core competency within the DEVCOM Analysis Domain, Mission Effectiveness Analysis Competency includes positions specializing in using combat simulations to conduct analysis of the impact of system performance on force-on-force or small-unit operational effectiveness. It requires knowledge of operational scenarios, simulation techniques, system performance, and applied statistics. Experts in the Combat Simulation Development and Analysis Core Competency work with subject matter experts in military operations and tactics, techniques and procedures to develop operationally-sound scenarios, then develop an appropriate run matrix to address critical study issues, run the simulation, analyze the output to understand trends and results, and provide decision makers with insights to enable them to make well-informed, data-driven decisions.

1.5.2     Geospatial Analysis Core Competency: This core competency within the DEVCOM Analysis Domain, Mission Effectiveness Analysis Competency includes positions specializing in developing methodologies and conducting analysis to examine system performance in the context of an operational environment. It requires knowledge of terrain data standards and development, interaction of combat systems with terrain, and the application of geospatial tools and analysis techniques. Experts in the Geospatial Analysis Competency work with subject matter experts in military operations and various technologies to understand how technologies will be employed in various terrains, then develop tailored digital terrain to model relevant features, conduct analysis of technology with terrain, and provide decision makers with geospatial results to enable them to make well-informed, data-driven decisions.


IV.         DEVCOM Lifecycle Engineering Domain Competencies and Core Competencies


2.1 Decision Support Competency: This competency, in the Lifecycle Engineering Domain, involves the application of mathematical methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data. This competency also includes the development and application of a wide range of problem-solving techniques and advanced analytic methods to inform sustainment and risk-related decisions to enable affordable current and future Readiness. Positions within this competency encompass the multi-disciplinary field of data science, which includes components from statistics, computer science, data visualization, and database management, and data syndication, which includes aggregating and cleansing internal and external data in structured formats for use in analysis and the development of models and simulations that drive analytic results to support better investment and acquisition decisions, improved performance, effectiveness, and system reliability. In addition, this competency comprises business intelligence initiatives to create dashboards and visualizations to understand performance and effectiveness measures. The goal is to inform Army decisions by gaining sound insight from all available data sources and deliver predictions and recommendations based on analytic products that increase Readiness, optimize costs, and lower risks. Decision support to establish precision logistics that provides a reliable, agile, and responsive sustainment capability necessary to support rapid power projection, Multi-Domain Operations, and independent maneuver from the Strategic Support Area to the Deep Maneuver Area. Precision logistics is enabled by: a sustainment enterprise resource planning decision support system with predictive analysis tools and the ability to resupply without request and/or redirect supplies based on priority; a real-time common operating picture viewable by commanders and logisticians at echelon; and significant demand reduction across the Total Force to lessen delivery requirements by as much as 50% and extend the operational time and reach of formations.

2.1.1     Data Analytics and Computing Core Competency: This core competency, within the Lifecycle Engineering Competency, includes positions specializing in implementing and applying descriptive, diagnostic, predictive, and prescriptive analytical techniques to provide Army decision makers with insight from structured and unstructured data sets. It requires knowledge of programming languages, applied statistics, machine learning, data mining, and data visualization. Experts, in the Data Analytics and Computing Core Competency, use a broad knowledge of data analytic methods to gain insight from data, implement tools to automate understanding of data sets, and provide decision makers with intuitive visual displays to enable them to make well-informed, data-driven decisions.

2.1.2     Database Engineering Core Competency: This core competency, within the Lifecycle Engineering Competency, includes positions specializing in designing, developing, and maintaining databases to manage data from analysis, experimentation, testing, and operational sources. It requires knowledge of data storage solutions, data and metadata standards, data access and security, query languages, and database development tools. Experts in the Database Engineering Core Competency work with subject matter experts, in specific military commodity areas, to understand the nature of the data to be studied, then develop and implement solutions to enable storage, access, automation, and the use of data analytics techniques to study the data.

2.1.3     Logistics Footprint and Cost Analysis Core Competency: This core competency within the Lifecycle Engineering Domain, Operations Research Competency includes specializing in developing methodologies and conducting analysis to examine the size of logistics support needed to move and sustain a warfighting force, and skills in cost analysis and estimating. The footprint includes all the necessary support needed to maintain the force such as fuel, spare parts, support equipment, personnel, etc. Advanced analytic models and simulations are used to conduct early life cycle sustainment plan development, materiel system level of repair analyses, operational and materiel availability determination, initial and replenishment spare part provisioning determination, etc. Detailed estimates of acquisition and Total Ownership Costs (TOC) for materiel systems are supported and utilized during materiel system trade-off analyses throughout the acquisition cycle. Accurate cost estimates are critical for effective and efficient acquisition programs. A broad range of Cost Benefit Analyses (CBA) are conducted to assess costs, benefits, risks, and return on investment of alternative choices and identify the most advantageous course of action. Analysis of product support alternatives to inform Materiel Developer of costs and benefits associated with specific support strategies being considered. Analytic products allow for cost effective decision making across the full spectrum of materiel and across the acquisition life cycle. These analytic products are critical to shape Multi-Domain Operations precision logistics requirement to significantly reduce the across the Total Force to lessen delivery requirements by as much as 50% and extend operational time and reach of formations.

2.1.4     Prescriptive Sustainment Analysis Core Competency: This core competency within the Lifecycle Engineering Domain, Operations Research Competency includes positions specializing in service to sustainment customers supported by a broad range of specific skills and knowledge in the areas such as Applied Statistics, Machine Learning, Signal processing, Natural Language Processing, and computational sciences. Ability to continually take in new data and be able to automatically improve data accuracy, thereby, prescribing better recommendations. Be able to ingest hybrid data, a combination of structured (numbers, categories) and unstructured data (videos, images, sounds, texts), and business rules to anticipate what lies ahead and to prescribe how to take advantage of the future without compromising other priorities. Leverage Army logistics data sources, hands-on sustainment reviews, and discussions with tactical through strategic level sustainment personnel to uncover materiel failures and issues arising from inefficient sustainment processes or policies. Identify optimized system design, trades, engineering change proposals, and improved sustainment technologies. Provide analytic support that highlights the most impactful sustainment areas of concern and produces recommendations and potential solutions impacting readiness, cost and safety of Army systems.

2.1.5     Risk Analysis Core Competency: This core competency within the Lifecycle Engineering Domain, Operations Research Competency includes positions specializing in the development, implementation, and application of mathematical and statistical methods to conduct schedule and technical risk analysis. It requires knowledge of applied statistics, schedule modeling, simulation techniques, DoD acquisition pathways, and Readiness Levels (Technology, Integration, and Manufacturing). Experts in this competency work with Subject Matter Experts (SMEs) from the Science and Technology, Program Management, testing, and requirements communities to identify current estimated readiness levels, technology maturation and program tasks required for completion, risks and opportunities that may delay or accelerate tasks, activity linkages, and uncertainty time estimates for each task. Experts then apply schedule modeling and statistical techniques to develop forecasts of projected milestones, identify major schedule and technical drivers, and determine the impacts of available risk mitigations, which thereby allow Senior Leaders to make sound, risk-informed decisions.

2.1.6     Supply Chain Analysis Core Competency: This core competency within the Lifecycle Engineering Domain, Operations Research Competency includes positions specializing in developing methodologies and conducting analysis to examine logistics performance and its impact on readiness and/or costs in the Army. It requires knowledge of applied mathematics, optimization, simulation, and an understanding of the Enterprise Resource Planning (ERP).