Cross-Organizational Planning and Management
The Army Research Laboratory Technical Assessment Board (ARLTAB) was asked by the ARL Director to identify technical opportunities that ARL should be pursuing but is not doing at the present time. In some instances, examples of these opportunities are identified and discussed in the directorate-specific chapters in this report. There is, however, one generic response to this charge. It has long been agreed that many of the most exciting breakthroughs in science and technology (S&T) take place at the interfaces between disciplines. To identify and pursue such opportunities, laboratories must create a process, provide incentives and resources, and use evaluation metrics that measure progress. Consider, for example, the broad topic of “robotics and autonomous systems.” Most, if not all, ARL directorates have some effort in this area. The ARLTAB panels—one for each of ARL’s six directorates—reviewed many individual projects, but the panels came away with no sense of a collective vision across directorates guiding these efforts and encountered relatively few cross-organizational projects jointly managed and jointly monitored by several directorates. Yet this field of robotics and autonomous systems cries out for collaborative efforts that range from design, to materials development and/or selection, to communication, to sensing, to human-machine interfacing.
When this subject was subsequently explored with the ARL Director, it was revealed that a rich, diverse array of such collaborative efforts does exist in many technical areas throughout ARL. These efforts were not commonly being briefed in panel reviews, however. To encourage such briefings and the discussions that they would likely engender, ARLTAB recommends that an additional assessment criterion be added to those currently governing the ARLTAB statement of task—one focused on cross-organizational collaborative effort (Appendix C presents the complete set of current assessment criteria). Directorates, responding to such a charge, would be expected to clarify the planning, management, and
content of such cross-organizational endeavors. ARLTAB panels would continue to focus on one directorate in each review. Representatives from collaborating directorates might be invited to such cross-organizational briefings, and they might contribute to interactive discussions, but they would not normally be presenting the briefing itself. In addition, ARLTAB encourages ARL to continue to take advantage of the opportunity to use the Board to carry out additional reviews of specific cross-organizational programs as they are being developed and executed. Such reviews would encourage the gap analysis required to address properly the issue of what additional opportunities should be pursued by ARL.
Deficiencies in the Research Process
In most of the projects reviewed, the research problems and objectives were clearly and adequately defined; investigators showed their awareness of related research in the extramural community and had formed productive collaborations where available. The language-translation work in the Computational and Information Sciences Directorate (CISD) evinced a well-planned movement from speech recognition, to text translation, to the current focus on parsing large volumes of documents. The CISD program in network analysis proceeds according to a clear articulation of project goals and plans. Additional strengths of this program include the support of three new Small Business Innovation Research (SBIR) projects on source selection, a focus on interdisciplinary collaboration, and expanded interactions with the Office of the Secretary of Defense (OSD), the Multidisciplinary University Research Initiative (MURI), Collaborative technology Alliance (CTA) participants, and end users.
In the Sensors and Electron Devices Directorate (SEDD), as a general rule changes are guided by a clearly stated long-term vision for each of the major SEDD mission areas. For example, the vision for the area of extreme energy and power describes an objective to provide the individual soldier with access to two or three augmented energy sources on the mesoscale and microscale, and the vision for the area of heterogeneous electronics highlights intelligent systems built from multiple technologies integrated into clothing, vehicle surfaces, and other stuctures in the warfighter’s environment.
The emerging neuroscience group in the Human Research and Engineering Directorate (HRED) has clearly set goals as part of its management of in-house programs and CTA collaborations. In the Survivability and Lethality Analysis Directorate (SLAD), the development of the methodology for achieving an understanding of underbody blast effects is well thought out and combines appropriate physics and necessary codes for assessing damage to vehicles. There is a good understanding of the limitations of the various elements that are interconnected to form the overall methodology. SLAD’s Target Interaction Lethality/Vulnerability (TILV) programs demonstrate collaboration efforts with the Weapons and Materials Research Directorate (WMRD) as well as the U.S. Air Force Research Laboratory (AFRL). There was also collaboration in international data-collection efforts using facilities such as the test ranges at Aberdeen Proving Ground, Maryland; facilities at Adelphi, Maryland; and Eglin Air Force Base, Florida, as well as ARL’s computational facilities.
The Vehicle Technology Directorate (VTD) has developed a capability concepts approach that allows VTD to connect research projects to specified objectives and to prioritize research and research areas so that work impacting several capability concepts can be moved forward, and research that does not apply to any capability concept might be redirected or stopped. At VTD, some high-quality technical work contributes significantly to the work of the overall technical community. For example, the compressor-tip-injection stall control work that couples experimental data and computational fluid mechanics is state of the art and will enable the industrial design community to improve gas turbine fuel economy and reduce compressor stall. In a similar manner, the windage work in high-speed gear systems is state of the art and promises to improve gearbox efficiency across a wide range of vehicles. The 3,000 to 10,000
shaft horsepower gas turbine (Versatile Affordable Advanced Turbine Engine [VAATE]) Program has well-defined metrics; leverages technology development across the Army, Air Force, Navy, NASA, and industry; and, if successful, will enable several classes of new Army vehicles. In all of these areas, VTD exhibits awareness of and is leveraging a wide range of government, industry, and university research to achieve the needs of the Army.
In most of the projects reviewed during the 2009-2010 period, appropriate scientific and engineering methodologies were applied, and an adequate mix of theory, modeling, and experimentation was in place. An example of CISD work showing good experimental design is a study of how better visualization techniques (i.e., how to cluster for display purposes large amounts of disparate data) aid in reducing the timing of decision making in high-tempo workloads. WMRD’s well-coordinated experimental and modeling efforts in the area of guidance, navigation, and control of flight bodies represent the state of the art in the Department of Defense (DoD). WMRD’s initiative in affordable precision munitions applies an appropriate technical approach that features a combination of analytical and computer modeling, laboratory/bench experiments, and full-scale field testing, including guide-to-hit tests.
Commonly, but to a lesser extent, verification and validation (V&V) efforts were appropriately applied to lend credibility to the models employed. At CISD there are research areas such as machine translation in which a V&V mind-set has become central to the research process. Also, both the early work in CISD on materials with complex microstructures that are hit with a shock of some kind and the modeling of antimicrobial peptides with bacteria membranes seem focused on a good formulation of their respective problems, with a solid initial approach; these projects have developed good collaborations with leading academic centers, and for at least early work included suitable checks on the potential limits of the models. The CISD Battlefield Environment Division (BED) has for a long time taken care to save the data sets that come out of V&V experiments, and that practice has provided a rich knowledge base for fueling future work.
Despite the strengths exemplified above, sufficient examples of deficiencies in the research process were observed to warrant notice. In some instances, the research problem and objectives were not clearly articulated. In SLAD, the problem context for system-of-systems analysis (SoSA) has not been clearly defined. There is a concern that the direction for the system-of-systems (SoS) framework and philosophy is to develop a platform for analysis and evaluation of survivability, lethality, and vulnerability (SLV) without a specific plan. The details that address the objectives, requirements, and operational level for SoSA model development are lacking. There is need for a concise plan that includes the rationale for the use of SoSA in SLAD, an explanation of how SoSA will contribute to the SLAD mission, and the identification the technical personnel support necessary to sustain the function. This plan needs to define how SoSA tools will be established and implemented, and it also needs to identify one or more specific applications that will prove the worthiness of this tool relative to the SLAD portfolio.
CISD work on managing very large databases was not sufficiently connected to the tactical needs of the Army or to other, related work in the broader intelligence community, and it needs to be put in that context. The project needs to have a clearly stated objective that is consistent with the mission of ARL. CISD work on networking will benefit from a more careful articulation of the key problems being attacked and how the research is being directed to address them. For example, the work reviewed in this cycle tended to divide between strong theory that is not crisply described in terms of its relationship to real Army problems, and work that has a good Army connection but loses the connection with networking.
Within the work in WMRD on theoretical predictions and modeling of energetics material properties, the objectives of the force field modeling were not clearly stated. Are the force fields to be used to model the shock wave in a decomposing energetics material, or are the goals more reasonable—for
example, to predict mesostructure parameters? Also, there was no evidence of a carefully constructed experimental program to look at energetics materials beyond the atomic level. WMRD should clearly articulate the goals for force field modeling of energetics and provide an experimental method to verify the results. An appropriate effort might be to predict the elastic constants of a crystal of energetics material and, when successful, study the effects of shear on molecular conformation.
At HRED there is a noteworthy absence of advancement in articulating the content and structure of the social and cognitive network science domain as envisioned in program research; there appears to be no strategic plan or logical narrative guiding the program. HRED’s Environment for Auditory Research (EAR) is a world-class auditory facility. However, it remains unclear if there is a utilization plan that will produce world-class results at this facility.
Researchers on several significant projects would benefit from a greater awareness of the research performed by others; that is, the work does not seem to take into account related research that is being conducted elsewhere or does not evince state-of-the-art methods, techniques, or technologies. HRED researchers need to improve their contact with contemporary research in the area of human-robot interaction. HRED researchers seem somewhat isolated from closely related research being done at universities and at other DoD facilities. Contact with this work is important, in part because there are technical advances that can be of use to HRED. More broadly, contact helps shape the research questions that actually serve to advance the field. Additionally, as this research moves into areas that involve traditional studies of human-computer interactions, it is important that HRED personnel learn techniques and methodologies from that area rather than trying to apply methods that they already know are inappropriate for the research problems that they face. Furthermore, it is not at all clear that HRED is positioned appropriately to conduct research in some of the areas in which it is engaged (e.g., cognitive robotics). Although engaging with these problems reveals vision and foresight, it is not clear that the full range of required technical knowledge is present in the HRED staff or that the limited resources applied are adequate to make meaningful progress. Finally, it would be useful to have a centralized mechanism to facilitate information sharing, research review, and discussion across the widely distributed HRED robotics-related researchers. Individuals with limited robotics experience would benefit from interaction with others who have more extensive, ecologically valid robotics evaluation experience. Similarly, in the case of the sensor fusion work in vision at HRED, the project does not seem to evince adequate contact with the very substantial work on this topic that occurs elsewhere in DoD and other domains (e.g., in medical imaging).
At CISD there is potential within the area of network research to accumulate unique, world-class data sets from experimental and/or modeling efforts and to document them in ways that will allow them to be useful both to future ARL efforts and to the larger research and development (R&D) community. WMRD’s work in the multiscale modeling of lethality materials would likely benefit from interactions and collaboration with other groups studying interfacial cohesion and from a more thorough review of the literature. ARL’s recently initiated program Materials in Extreme Dynamic Environments (MEDE) is a very promising approach to creating a collaborative team to address multiscale modeling to contribute to the achievement of significant Army materials applications.
SLAD has the opportunity to develop additional knowledge and expertise by expanding its awareness of non-Army programs, capabilities, and advanced concepts. For example, SLAD was not aware of an AFRL program called Laser IRCM Flyout Experiment (LIFE) that developed and tested a prototype of a closed-loop infrared countermeasures (IRCM) capability for large, fixed-wing aircraft. This technology could have application for Army platforms and should be considered. All of this information has been openly discussed at conferences and is readily available on the Internet, yet SLAD personnel were not aware of it. SLAD would benefit from becoming more involved in and aware of non-Army electro-optic
countermeasure (EOCM) programs and the lessons learned from those programs. Attending conferences is an obvious means of expanding this awareness. SLAD should also seek out information on advanced concepts and roadmaps from its DoD colleagues.
In several cases, a project’s researchers would benefit by collaborating with researchers in other fields or at other organizations, extramural and/or within ARL. At CISD, without care in performing human-computer network experiments, the actual value to the Army could be limited. In particular, using just delay and loss measures in the data network models seems limiting, especially in terms of parameters that are relevant to how humans interact with such networks. Better coordination with HRED and the Communications-Electronics Research, Development, and Engineering Center may be able to help with realistic assumptions. CISD should consider introducing Training and Doctrine Command-validated behaviors into research, and interacting with the Joint Experimentation Directorate. In other areas, such as data mining, in which there is no history of internal projects or collaborations with others outside ARL, there is little understanding of other work or awareness of the availability of existing program packages.
In some instances, the scientific approach, plan, or method applied did not seem appropriate, adequate, or clear. At HRED, questions have arisen in the area of statistical analysis and interpretation. In some cases, the analysis did not seem to be correctly performed. In other cases, the distinction between statistical significance and scientific or practical significance was lost. At VTD, testing and field demonstrations of autonomous vehicles and their interaction with terrain and humans are very important. VTD’s Fort Indiantown Gap facility is well equipped to conduct this type research; however, some of the results from recent tests of experiments suggest that the design of the tests and analysis of data gathered is a challenge for VTD. VTD personnel should develop expertise in the design and conduct of robotics experiments.
Some projects lack an adequate mix of theory, modeling, and experimentation; and at times insufficient analytic and theoretical research is provided to support models, simulations, and experiments. At WMRD, the Gun Liner Emplacement by Elastomeric Materials (GLEEM) Processing project seems to involve very applied engineering with little evidence of systematic R&D or modeling to guide the effort. WMRD should examine whether this development project can be designed to incorporate a more coupled experimental-modeling emphasis. At VTD, there is a need for the modeling of vehicle systems. The results of good models, such as performance prediction and scalability studies, seemed absent in the many of the VTD projects presented. Research on robotic platforms and air vehicles needs modeling to improve the understanding of performance limits and optimization of platform parameters. Modeling is also critical to system design; good models are the key to insight into the underlying physics, from which meaningful metrics can be developed and understood.
In some instances, models and simulations did not demonstrate valid predictive capabilities, and there was an apparent lack of verification and validation of data and results, from a model or experiment or both, to connect the approach and underlying assumptions to real-world applications. In cases where data have not been validated, explicit plans to do so were not always explained or did not seem appropriate, clear, or adequate. In some cases, metrics and technical features of models or simulations were not explained in sufficient detail to permit their detailed assessment. At CISD, there is still not enough effort being made to ensure that mobile network models, especially when run in a multiscale, multilevel, end-to-end mode, are in fact reliable predictors of reality. In new areas of research at CISD, such as aerosol dispersion or ultrasonics in more complex environments (such as urban settings, with turbulence), researchers appeared to have some difficulty articulating what it takes to validate a new model. At CISD, particularly in projects involving complex computations, there remains a tendency to develop stand-alone codes, without any clear approach articulated for ensuring that both the algorithm modeling the physics and the implementation of that algorithm are correct.
WMRD is conducting work that applies modeling at different length scales (quantum through continuum) to describe the fracture behavior of AlON, and work that uses the optical response to ballistic impact in AlON and other transparent materials to understand stress, strain, and defects ahead of the actual fracture front, particularly the phenomenon described as “effective plasticity.” With respect to descriptions of these projects, numerous references were made by the panel to the lack of crisp success criteria, which makes it hard to know what properties or structures should be optimized. For example, what are the desired fragmentation size distributions for ceramic armor? Also, what is the desired mixture of static and dynamic failure prevention in ceramic armor? Without crisp success criteria, it remains difficult to understand the real goals of the substantial modeling and experimental efforts that are underway, or how they will be leveraged by the more applied engineering groups. ARL’s new MEDE Program is a promising approach to clarifying the goals and contributions of modeling and experimental efforts toward the achievement of application goals.
Robotics and Autonomous Systems
The invention and use of robots on the battlefield will bring about the most profound change in warfare since the development of gunpowder. News stories now recount daily the results of drones piloted from Arizona and hitting targets of opportunity in the Afghanistan theater. As amazing as that may seem, we stand only at the threshold of change with respect to the impact that robots will have in future wars. Consistent with the importance of robots, the Army Research Laboratory has a large body of ongoing robotic research. During the past 2 years, the Board, through its various panels, has reviewed some of this research. While much interesting work is underway, several structural challenges should be addressed if these research programs are to achieve their potential.
A central concern is the limited contact of ARL researchers with the broader robotics community: ARL research projects generally seem to involve too little contact and collaboration with existing robot manufacturers, academics conducting robotic research, and other Army users of robots. This leads to the possibility of work that is duplicative or behind the state of the art. It is important that ARL researchers attend meetings at which they are exposed to the best of current external work in areas of interest and that they strive to publish their open research in the top-tier peer-reviewed journals in the field.
ARL should lead an effort with robot manufacturers, academia, and Army users to define the robotic capabilities that might be desired in a 2020 time frame. After 2020 capabilities are defined, ARL then needs to review its portfolio of research to ensure that its efforts are directed to areas in which it can make unique and important contributions. A benefit of such a review would be to foster cross-directorate interactions in the robotics area. Although it may be an artifact of the manner in which the panels are briefed, robotics work in one directorate often does not appear to make contact with relevant work elsewhere in ARL.
As ARL seeks to define areas in which it can have the most impact, two crosscutting areas seem promising: human-robotic interaction and robotic propulsion power density. Human-robotic interaction deals with how the robots will be deployed and controlled and how they will react to different battlefield challenges. At one end of the human-robotic interaction spectrum would be a single human in complete control of the robot; at the other end of the spectrum would be a completely autonomous robot. ARL has access to unique resources and data in this area and can contribute insights that would not be available from studies of interactions with robots that are cleaning house or building automobiles.
Robotic propulsion power determines the range, the time on station, and the payload of a robot. In particular, the combustion of Jet Propellant 8 fuel (JP-8) produces approximately two orders-of-
magnitude-higher energy density than that of battery electric-type propulsion; therefore, ARL should concentrate on the combustion of JP-8 in very small, high-pressure-ratio systems.
Computation and Modeling
Computational science involves the construction of mathematical models and quantitative analysis techniques of, generally, physical phenomena, followed by the use of computers to apply these models to explore a design space—often one that cannot be easily duplicated in reality. Challenges in computational science often occur in terms of scale: how the model or its implementation as a computer program changes as the problem changes. This scale can change in two ways. First, in a physics sense, multiscale models reflecting the conjoining of different models represent different levels of, usually, the physical world, such as a low-level atomic model for situations in which there are few atoms and/or in which small changes need to be tracked, whereas more bulk models are characterized by less accuracy but lower computational complexity. The second type of scale change reflects the relationship between problem size and the amount of computational resources used to solve it: in strong scaling, one keeps the problem size constant and increases the amount of computational resources in hopes of shortening the total solution time; in weak scaling, one wishes to increase the problem size as the computational resources increase, so that execution time remains constant. In terms of challenges to ARL, it is increasingly important that new models be designed from the start to be composable to multiscale, and that the right level of programming expertise in high-performance computing (HPC) be used to ensure that the resulting codes can scale either strongly or weakly as the application requires. ARL is addressing this challenge through two newly initiated programs in the evolving area of multiscale modeling and associated experimentation: the MEDE Program and the Multiscale Multidisciplinary Modeling of Electronic Materials Program. Each of these programs will involve cooperative research alliances that foster collaborative efforts among external institutions and with ARL researchers.
“Network science” is a term that covers a great deal of territory, and that territory has been growing. The networking efforts in ARL encompass two different concepts of a network. The first is the traditional view of a network as a collection of interconnected computing devices, and the questions asked are about the speeds or latency of transmission, perhaps versus the power expended to do the transmission. The second concept of networking involves a human (social) network, and it is the linkages between individuals revealing information about their intents that are important. Described in this way, these would seem to be two quite different domains making use of the same label. However, there is also a substantial area of overlap in which networks of humans are interacting through networks of devices. For an example of a topic that covers both domains, consider decision making by a distributed group, communicating over a network that introduces perceptible delays in the transmission of information. The behavior of the system is an interaction of the two types of networks.
ARL needs to provide strong scientific leadership in order to manage these different types of network science. ARL must decide where it can make an impact in the network sciences. Some topics will fall clearly within either CISD or HRED (see the individual directorate chapters for a discussion of those topics). Other topics bridge the directorates, and it will be important to coordinate the efforts across organizational boundaries. The Network Sciences Division of CISD, and its CTA, International Technology Alliance, and Mobile Network Modeling Institute were all formed with a primary focus on networks of computing devices. They appear to be moving to include issues involving networks of
humans. Careful coordination between HRED, CISD, and other interested groups will be needed in order to provide appropriate financial and scientific resources for these different forms of network science.
A great deal is being said in the greater power community about the future of smart grids and micropower. Stripped down to its fundamentals, micropower research is based on two related ideas:
Power at the point of application is the real issue. Power conversion, distribution, and consumption management are now included in every aspect of a system design, which can no longer be isolated in a single module interfaced at a power connector. For example, in modern microelectronics design, power and energy distribution and management primitives cut across every level of the design, from distribution networks in the physical design to energy and clock management in software. This multiscale design strategy for power and energy management is the future for almost all military systems.
Power is an integral part of every aspect of a system design. Such a system design is much more than a traditional load analysis. Designs for power conversion and distribution must include considerations of weight and thermal loading both locally and cumulatively. When considered in this way, priorities and practicalities are easier to identify, and solutions often become apparent.
With power and energy an integral part of an entire system design, successful systems will result from a collaborative effort that includes the designers of the power and energy systems and the designers of the systems that consume power and energy resources. Power management that is tightly integrated with information technologies has already been demonstrated to be a winning concept. This approach must be expanded to take in sensing, actuation, and communication systems as well as control systems, armor, and weapons systems. ARL must identify and support early and ongoing collaborations among individuals with power and energy expertise within SEDD and system designers in all of the other directorates. This will ensure that for future systems, power and energy issues are identified and solved early in the design process. One significant relevant approach underway at ARL is the Multiscale Multidisciplinary Modeling of Electronic Materials Program mentioned above.
Materials by Design
In past eras, materials have been principally selected almost exclusively on the basis of hands-on experience with a material’s characteristics—that is, the material was found or manufactured and then, based on its performance compared to that of other materials, was selected as the preferred material for a given application. This approach to materials selection applies to industrial practice in general and also to defense applications such as those in the Army. Engineering the response of metals and alloys to the desired end performance or application is an age-old trade, extending from the famous 5th-century steels of Damascus to the aluminum alloys that enabled the modern era of civilian aviation. This historical approach to materials and alloy development, sometimes crudely referred to as “cook and look,” has been reflected in the mainstream Edisonian approach to developing new materials classes. Under this approach, a strong closed-loop linkage between processing and performance was established. The optimization of a material to meet the performance needs of a given application was most often, therefore, an iterative process of varying the processing, and accordingly the material’s microstructure and its properties, to achieve the desired results in terms of performance.
Manufacturing recipes were typically developed through trial and error, but during the years leading up to World War II, scientists and engineers conducted the first systematic materials studies. As one example, significant research was focused on how the relationship between the applied stress, or force over area, and the resulting strain, or change in length, varied with temperature, strain rate, and stress state. Knowledge from that research was quickly applied to critical wartime needs: high-speed manufacturing of metal parts (including high-speed wire drawing and the cold rolling of metal parts) and advances in ballistics, avionics, and armor. Spin-offs from those early studies led to increasingly sophisticated materials of relevance to defense, transportation, and communications. Further, in this mode of materials development, the detailed quantification of the microstructure and properties of a material as a function of a diverse set of variables was developed as scientific understanding, and engineering predictive linkages were sought in order to accelerate materials development.
Over the past five decades, this initial coupling of processing know-how and experience with rules of thumb has given way, first, to an increasing level of scientific and engineering insight into the dominant mechanisms that control microstructure development linked to process modeling and, thereafter, to the predictive modeling of the correlations between microstructure, properties, and performance. This evolution in the process flow paradigm governing materials development to a rapidly accelerated level of using materials modeling to link processing to structure to properties to performance has seen great strides in recent years. Thus, researchers are now heralding a transition from the observation and validation of materials performance to the designing of materials to achieve tailored functionality through the utilization of multiscale materials modeling in order to predict accurately and to control performance.
In this evolving, new materials-design paradigm, the focus becomes geared to identifying new materials and microstructures that are theoretically predicted to meet a set of designer-specified performance criteria. This methodology encompasses two salient steps: (1) the identification of a set of microstructures that are theoretically predicted to meet or exceed a combination of the desired properties or performance goals, and (2) the identification of processing routes that are theoretically predicted to realize the desired optimized microstructures. This represents a decadal Grand Challenge to engineers and scientists: to develop tailored materials based on a body of knowledge founded on scientific mechanisms and the governing physics as opposed to empirical relationships fitted to experimental observations and testing. This turnaround in the design paradigm to the prediction and control of performance through the process-aware design of materials using predictive multiscale tools has been variously termed computational materials design, inverse materials design, materials by design, and integrated computational materials engineering.
In the new capability of predicting material behavior and designing and engineering custom materials with predetermined characteristics, materials are viewed as multiscale hierarchical systems. A critical aspect for achieving success in materials design is the availability of validated models that predict the processing-microstructure-property relationships in materials systems of interest. Given that the materials phenomena of relevance to research at ARL span a wide range of temporal and spatial scales, it is imperative that a linked multiscale modeling framework that passes information both to higher-length scales and to lower-length scales be developed. Meeting this need is particularly challenging in DoD, given the complexities in understanding and modeling processes such as armor penetration and munitions performance, which encompass complex physical and chemical processes. It is essential that the system of predictive models developed be tightly coupled throughout the design process to an efficient experimental system of model calibration, validation, and databases linking materials microstructures to properties and performance. Only through this linkage can the materials community, and the Army and its contractors in particular, hope to define accuracy through the quantification of model uncertainty and incorporate material statistics and heterogeneity. It is expected that the ARL Materials in Extreme
Dynamic Environments Program and Multiscale Multidisciplinary Modeling of Electronic Materials Program mentioned above will encourage intellectual and programmatic elements that will foster collaborative work for the integration of modeling, experimentation, and design in order to produce materials that address Army application needs.
LINKAGE BETWEEN THE ARMY RESEARCH LABORATORY AND THE ARMY RESEARCH OFFICE
The Board is not charged to review the work funded by the Army Research Office (ARO), which is an organizational entity within ARL. ARO is a significant basic research asset with a significant fraction of the total ARL basic research (6.1) budget. Considering the important role that basic research has had in the development of Army-relevant technologies and the similar high-payoff role that it could have in the future, the Board requested an opportunity to learn how the work portfolio of ARO is integrated into the activities normally reviewed by the Board. In response, ARO presented to each panel summaries of those 6.1 programs that ARO sponsors which are relevant to the ARL work reviewed by the given panel and/or presented a summary of the organizational mechanisms by which ARO interacts with staff at the directorates. The level of ARO collaboration varies across the directorates. In general, ARO demonstrated increasing attention to such collaboration, and the Board looks forward to continuing improvements in ARO’s cognizance and support of the missions of the directorates.