9
Crosscutting Conclusions and Recommendations and Exceptional Accomplishments
CROSSCUTTING CONCLUSIONS AND RECOMMENDATIONS
The following crosscutting conclusions, recommendations, and exceptional accomplishments are based on the projects and programs presented, as a full spectrum of projects and programs within each Army Research Laboratory (ARL) campaign and the interrelating mapping across all campaigns’ projects and programs were not provided to the Army Research Laboratory Technical Assessment Board (ARLTAB).
Research Positioning
To be successful and productive, research needs to be properly positioned with respect to the broader scientific community including industry. Such positioning requires cognizance of the objectives of relevant research efforts, an analysis of the strengths and weaknesses relative to this broader scientific community, and a plan to develop the critical knowledge and expertise needed to best achieve program objectives.
Recommendation 1: Upon initiation, ARL research efforts should propose a positioning plan and schedule that includes
- Identification of key, core, and complementary research programs and relevant expertise;
- A statement of ARL’s intended role in the context of this expertise (lead, follow, support); and
- An appraisal of the need for external and internal technical support—for example, via external advisory boards, visiting researchers, workshops, or collaborations—and if needed a plan to develop such support.
Leveraging Scientific Talent
As research problems have evolved to include multidisciplinary interactions, there has been a concomitant growth in collaboration among researchers, both within ARL and with those from the larger external community. In this research environment, it is important to acknowledge that common foundational technical skills may exist in ARL in different campaign thrusts, where they are being applied in uniquely different ways. Knowledge of the existence of these technical skills would be highly beneficial, both from the perspective of bringing greater technical talent to bear on existing problems, as well as promoting synergy among campaign thrusts by bringing to light possible new areas of collaboration. There was some evidence, for example, that system intelligence and intelligent systems
(SIIS) researchers within ARL were not always aware of similar or parallel efforts in other campaigns. In looking at research related to human-machine or human-information interaction, it is clear that individual projects within campaign thrusts would benefit if collaborations with researchers with parallel or complementary skills in other campaigns could be facilitated. A systematic mapping of primary and secondary skill sets of the technical staff at ARL would be highly beneficial in this context.
Recommendation 2: ARL should bring about greater understanding of available technical expertise in critical subject areas across ARL, and leverage this expertise to build greater synergy across campaign thrusts.
Predictable Funding
Multiyear research projects that undergird the development of future Army capabilities rely on the development of experimental tools and modeling capabilities that require years to develop. Predictable funding levels are needed over the project lifetime (with, of course, milestones for continued support) in order to plan an effective strategy for acquisition of equipment and the hiring and training of personnel.
Recommendation 3: ARL should provide predictable long-term funding for multiyear projects.
Streamlining Research-Related Approvals
ARL staff reported that the time period for the approval process for conference attendance and for equipment purchases is often too long. Attendance and presentations at national and international conferences play an important role in bringing an awareness of the latest developments in a field into the purview of ARL. They also play a major role in making the outside world aware of the high-quality research at ARL, thereby enhancing the reputation of ARL and demonstrating to young scientists and engineers that a career at ARL would be attractive. It is important that procedures for attendance at such conferences should not make preparation for participation a chore and thereby discourage ARL staff from pursuing such opportunities.
Incidents occur in the course of carrying out research where an additional piece of equipment is needed or where computer software or hardware needs to be purchased to complete a project. In some cases, because of the time delay in acquiring what is needed, government employees need to use contractors and contractor facilities to get work done that they cannot do because of such delays or because of the lack of adequate computational support. Procedures need to be in place for reducing the time scale for justifying the need and then obtaining what is needed as well as providing timely computational support when needed. An expedited approval process for conference participation and equipment purchases would enhance staff productivity and ARL staff morale.
Recommendation 4: To facilitate research, ARL should streamline the approval process for conference participation and procurement of equipment.
Systems Approach
Effective research assessment processes require (1) clear articulation of the expected outcomes for each portfolio, including key technical milestones and metrics to be used for measuring progress and success; (2) definition of an appropriate set of outcomes and metrics for each project within a research portfolio; and (3) a closing of the loop that documents and describes the actions resulting from the assessment process. Beyond providing researchers the ability to gauge progress and make midcourse
adjustments (which may in some cases arise from an unanticipated discovery), including a refocusing of portfolios and projects determined to be too broad in scope, a well-structured assessment process provides greater visibility to collaborators and partners. This is especially needed for research that entails a systems engineering approach.
Every Army system is intended to serve, enable, and protect the soldier within the system. Army systems that do not interact with the soldier at some level do not exist.
Recommendation 5: ARL should place greater emphasis and focus on a systematic assessment of its research. The assessment should include measureable milestones, outcomes, and metrics for the portfolios and the projects within them. In all ARL campaigns, research efforts aimed at developing any system should endeavor to understand, incorporate, and accommodate the soldier within the system through the incorporation of human systems integration (HSI) principles. HSI should include the consideration of usability, sustainability, resilience, and survivability within the system.
Stewardship of Data
The explosive growth of data—observational, experimental, and computational—and the rapid and concurrent development of new machine learning techniques is opening new opportunities to extract insights and patterns and create predictive models of natural phenomena and human behavior, while also preserving unique or historical context and experiences. Following theory, experiment, and computational modeling, big data analytics and deep learning have been called the “fourth paradigm” of scientific discovery. ARL is well positioned to host unique Army-relevant data and metadata and to engage the research and industry communities in collaborative partnerships. Equally importantly, such hosting and engagement can accelerate ARL research by applying data analytics and machine learning across disciplinary and multidisciplinary contexts, while also attracting new talent and ideas.
Recommendation 6: ARL should develop and host a curated data repository of select Army-relevant data, targeting domains and contexts relevant to its strategic objectives and preserving data and contexts that may otherwise be lost. In conjunction with development of the data repository, ARL should develop a set of Army-specific data analytics questions and sponsor competitions to accelerate progress on ARL problems and attract new talent and expertise.
Enhancement of Approaches to Inform Theory
In order for ARL research to accelerate and to produce useful and meaningful findings, the research needs to be approached in a systematic manner that includes the consideration of environmental conditions, an understanding of system response to expected stimuli, and an understanding of the overall behavior of the system under consideration. Given this context, ARL research efforts need to consider this broad systems research approach to develop and enhance research efforts. The ARL observational and experimental research endeavors seem generally adequate, but there appears to be a weakness in the theoretical underpinning of the research in some areas. Such weakness in underlying theory has been addressed by modeling.
ARL researchers demonstrated general awareness of the facts that in the conception, design, implementation, and assessment of scientific solutions of technical problems, the use of models commands a central and critical position in the development of technology, and that considering the complexity of phenomena of interest to ARL, useful modeling provides a means of advancing the development of technology. In some cases, however, there appeared to be incomplete appreciation of the fact that useful models incorporate complexity, scalability, robustness, uncertainty, and operations in
noise and interference. The uncertainty in such modeling may be large. Applying state-of-the-art tools to analyze uncertainty, ARL can develop and use models to advance technology.
Recommendation 7: The ARL research efforts within a particular campaign should comprise four components: (1) real-world observations (for example, surveillance, field research, and naturalistic observations); (2) laboratory testing; (3) theoretical underpinning of the science (for example, modeling and simulation); and (4) assessment, verification and validation, and uncertainty quantification of the models. All research should endeavor to contribute to one or more of these research components in such a way that each component’s findings serve to inform the other research components. In addition, a balance should be met between the contributions to these various components so that an overall systems appreciation is achieved. ARL should further enhance the use of appropriate models to better understand the phenomena of interest and develop technology.
Enriching Open Campus
Research software is rapidly developing, and qualification of software for use on internal ARL networks takes time. Staff members reported that this situation forces them to choose between delaying using software that facilitates their research or, if they can, going to contractor (or other) offsite computer facilities to carry out their work. This delays or in extreme cases can preclude, carrying out promising research projects.
Recommendation 8: To enrich the ARL open campus, ARL should consider developing an ARL on-site open network that research staff can use to readily access research software that has not yet received qualification for use on the internal network.
EXCEPTIONAL ACCOMPLISHMENTS
The following are the exceptional accomplishments for each campaign area.
Materials Research
The work on high-voltage aqueous electrolytes could be revolutionary for battery technology for the Army and elsewhere. Work on radioisotope-based power sources is also noteworthy, having progressed very rapidly from concept to implementation. This work is considered by the ARLTAB to have significant upward potential.
In just a few years, the quantum sciences program has attracted outstanding investigators, driven in part by their membership with the University of Maryland and the National Institute of Standards and Technology (NIST) in the Joint Quantum Institute. The quantum sciences group has done an outstanding job of bringing in a strong team of a well-established mid-career leader with extensive knowledge, service laboratory experience, and connections of military systems and needs, and a second, well-established academic who is a recognized quantum sciences leader. In the past two years under their leadership, an excellent research team of six experimentalists and one theoretician has been established. In addition, the group has built impressive research facilities. Among the applications addressed by the quantum sciences program is absolutely secure communications, a major challenge for a highly mobile and ever-changing battle scene where your opponent very likely will be able to receive your communications and thus unbreakable encryption is essential. The ARL team has made a significant effort on different approaches for a “quantum repeater” to extend the range over which secure communications can be assured.
The quantum sciences program is an outstanding example of vision for a future Army need: defining specific areas that are Army unique, and are not well covered by universities or national laboratories, and hiring recognized leadership and creating a well-funded, exciting program that has attracted an outstanding group of early-career scientists and postdoctoral researchers.
Sciences for Lethality and Protection
In the battlefield injury mechanisms area, the management is complimented for having created a comprehensive program, with talented, energetic scientists who provide the skills needed to define this area. This is an excellent start, and ARL is to be commended and encouraged to continue to grow this area.
In the directed energy area, the work on exploiting Raman laser to greatly improve fiber power output is exceptional and is an archetype for research at ARL that compliments other Department of Defense (DOD) laboratories while not duplicating academic or industrial research. Another exceptional work is the nonlinear optical materials and coatings that are frequency agile in the visible spectrum to passively protect Army optical sensors from directed energy laser threats such as that from straight damage, jamming, dazzling, and so on.
In the weapons-target interactions area, the advanced penetrator work is a potential game-changer and is viewed as exceptional.
Information Sciences
Of the reviewed projects, some are deserving of special mention. The research program in electric and magnetic field sensing is a strong program overall. This is a comprehensive and strongly interconnected program with projects in sensor development, validation, calibration, algorithm design, and field deployment. Strong mentorship by senior scientists has effectively grown an impressive cohort of next-generation scientists to sustain this effort. The private sector partnerships and commercialization activities are also notable.
Another project related to the detection and characterization of chemical aerosols is worthy of special attention. This project has successfully demonstrated a laser-based technique for isolating, detecting, and identifying the chemical compositions of micron-size particles of multiple phases with unprecedented speed and accuracy. The work is exceptional and novel, and has the ability to revolutionize the aerosol science field as well as all industries and technologies that rely on aerosol science.
Ongoing work related to the meteorological sensor array (MSA) will enable unprecedented continuous examination of atmospheric phenomena crucial to our understanding of atmospheric flows over complex terrain at high horizontal resolution. The unique data that will result from the full deployment of MSA and its instruments as well as the opportunity to engage multiple partners are factors that contribute to the high impact of the project.
The planned sensor information test-bed collaborative research environment (SITCORE) facility appears to be a significant enabler for impactful, multidisciplinary research that expands the scope of many information sciences projects. The plan to place this facility next to the Network Science Research Laboratory and to be included as part of the open campus are expected to facilitate collaborative research and promote innovative solutions to challenge problems.
Computational Sciences
The work presented in the predictive sciences combines machine learning within large simulations to optimize multiscale model computations with the hierarchical multiscale (HMS) work, with positive
results and a promising future. The data-intensive sciences work on neuromorphic processing and cooperative reinforcement learning was excellent. The panel congratulates the data-intensive sciences team on its strong start in the new research thrust in machine learning. Alongside operating and managing high-performance computing (HPC) systems to serve the processing needs of the broader DOD community, the advanced architecture group has evolved to focus on tactical high-performance computing at the edge, having made significant progress in evaluating the role of neuromorphic computing to enable high-fidelity computation using many low-precision elements and very low energy.
Sciences for Maneuver
Several research programs were observed to be outstanding. Three such research programs stand out—research on low-ranked representation learning of action attributes (flexibility and extensibility) in focusing on human action attributes; research on autonomous mobile information collection using a value of information-enriched belief approach (projected functional stochastic gradient-based approach with teams of robots); and research and simulation work on the Wingman Software Integration Laboratory, which has a clear path to Army-relevant static and dynamic scenarios and multiple-machine and multiple-human interactions.
Human Sciences
The real-world behavior (RWB) program now has state-of-the-art expertise in electroencephalogram (EEG) systems and source localization; it has developed in-house EEG technology and compared it with commercial EEG systems. Of particular note is a head phantom for EEG, a device approximating the human skull conduction used to re-create electrical signals on the scalp that will enable the modeling and exclusion of noise sources, with the goal of identifying measurable neural signals recorded in complex environments. The group has developed a cutting-edge facility for integrating EEG and other related neural and physiological sensor data.
The Human Cyber Performance group within the Humans in Multiagent Systems program has demonstrated foresight into effective collaboration by its initiation of promising work in human aspects of cybersecurity utilizing the Cyber Human Integrated Modeling and Experimentation Range Army (CHIMERA) laboratory, jointly developed by ARL’s Human Research and Engineering Computational and Information Sciences Directorate (CISD).
Analysis and Assessments
The BSVL group has historically led the way in modeling ballistic survivability, lethality, and vulnerability for the Army, DOD, and international allied community. There is no competition for leadership in this area—it is ARL’s mission. The movements to embrace HPC to speed computations and support the Army community needs for analysis and assessment (A&A) are commendable efforts. The emerging methodology for underbody blast and multihit survivability analyses will be exceptional contributions to Army A&A.
The finite element modeling of underbody events on vehicles is top-notch work. The finite element modeling team has a clear understanding of the fidelity required and is advancing state-of-the-art tools and contributing to their validation.
The approach for the physiological experimental work combining high-speed X-ray imaging with state-of-the-art and exploratory sensor technologies is an example of outstanding work that is leading this field. It is the best high-speed X-ray capability that has been observed in this area.
In human systems integration (HSI), the human physical accommodation models and soldier performance and workload modeling and simulation tools developed and employed by ARL are first rate and have provided the Army and industry with an excellent capability to assess soldier integration into complex systems. Current tools, including the Improved Performance Research Integration Tool (IMPRINT) and digital clothing and equipment models, provide analytical capabilities that can be cost-effectively applied early in the acquisition cycle as well as later during system development.
