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tanks in military as well as civilian vehicles. REFERENCES: Due to the nature of the topic, most reports are either classified or of limited distribution. However, the following references are provided for general information and as background material. 1) Cook, M. D., P. J. Haskins, and H. R. James, ?Projectile Impact Initiation of Explosive Charges,? Ninth Symposium (International) on Detonation, Portland, OR, OCNR 113291-7, Office of Chief of Naval Research, Arlington, VA, 1989, pp. 1441-1449. 2) James, H. R. ?Critical Energy Criterion for the Shock Initiation of Explosives by Projectile Impact,? Propellants, Explosives, Pyrotechnics, Vol. 13, 1988, p. 35. 3) de Longueville, Y., C. Fauguignon, and H. Moulard, ?Initiation of Several Condensed Explosives by a Given Duration Shock Wave,? Sixth Symposium (International) on Detonation, San Diego, CA, 24-27 Aug 1976, pp. 105-114. 4) Bahl, K. L., H. C. Vantine, and R. C. Weingart, ?The Shock Initiation of Bare and Covered Explosives by Projectile Impact,? Seventh Symposium (International) on Detonation, Annapolis, MD, 15-19 June 1981, pp. 325-335. KEYWORDS: IAV vehicle, FCS vehicle, crew survivability, injury, ammunition protection, explosion, schock,fragments, heat A03-033 TITLE: Novel Hierarchical Hybrids for Transparent Armor
1) LeBaron, P. C., Wang, Z., Pinnavaia, T. J., Appl. Clay Sci. 15, 11, Sept. (1999). 2) Dietsche, F., Mulhaupt, R., Polym. Bull., 43, 395 (1999). 3) Kasuga, T.; Hiramatsu, M.; Hoson, A.; Sekino, T.; Niihara, K., Langmuir 14, 3160 (1998). 4) Siegel, R. W., Chang, S. K., Ash, B. J., Stone, J., Ajayan, P. M., Doremus, R. W., Schadler, L. S., Scripta Mater. 44, 2061 (2001). 5) Hernandez, B. A.; Chang, K. S.; Fisher, E. R.; Dorhout, P. K.; Chem. Mater. 14, 480 (2002). KEYWORDS: nanomaterials; hierarchical hybrids; multi-functionalities; EMI shielding; transparent armor; ballistic performance. A03-034 TITLE: Non-Imaging Disposable Sensor System TECHNOLOGY AREAS: Sensors OBJECTIVE: Develop a complete sensor system that includes several disposable sensor nodes that communicate with a hand-held display. Each disposable node should include one (or more) transducer(s) with suitable amplifier/filter(s), a signal processor, and a communication device, all in a single package for under $10 (projected unit price, quantities of 1-10 million/year). These sensor nodes should be extremely small (1-10 cm^3), lightweight (1-30 gm), and consume extremely low amounts of power (0.1-1 mW). It is anticipated that such sensors could be used by individual soldiers for surveillance and/or self-protection, by small groups of soldiers operating in an urban environment, and/or as "feelers" in a large sensor network. DESCRIPTION: The specific sensor modalities are not specified in this topic, but could include acoustic, seismic, magnetic, E-field, non-imaging passive infrared (PIR), passive RF, chem/bio, and/or any other transducer(s) that could be used to detect any targets or threats of military significance, and that could be built at a unit production cost that is on the order of $1/transducer. Individual sensors could be multi-modal, and/or a mix of individual sensors with different modalities could be used to detect a wide range of targets and/or threats on the battlefield, including: personnel (armed, unarmed); ground vehicles (wheeled, tracked); aircraft, including unattended arial vehicles (UAVs) and micro-air vehicles (MAVs); explosions, including gunfire, artillery, and rocket launches; chemical and/or biological threats, and/or monitoring of power lines, local communications, etc. Performance goals for individual disposable nodes are secondary to the size, power, weight, and cost objectives listed above. Examples of desired performance include the following: one month continuous operation using internal batteries and/or energy harvesting, low false-alarm rate (Pfa < 1 false alarm/hour in quiet military training environments, and Pfa < 3 false alarms/hour during normal military training operations), detection of personnel (Pd >0.9 @ 2 m, >0.7 @ 5 m, >0.3 @ 10 m, <0.01 @ >50 m), classification of soldiers (Pc > 0.5 @ 2 m), detection of large vehicles (Pd >0.9 @ 20 m, >0.7 @ 50 m, >0.3 @ 100 m, <0.01 @ >500 m), classification of wheeled/tracked/airborne vehicles (Pc > 0.5 @ 20 m). Other desirable performance goals include detection and/or classification of other targets and/or threats, including: unattended air vehicles (UAVs), micro-air vehicles (MAVs), and other robotic or autonomous vehicles; gunshots, mortar/artillery/rocket launches, and/or explosions; power line activity, telephone activity (wired, cell phone, satellite phone, tactical radio, etc.); chemical and/or biological threats; node tampering, etc. Target and/or threat reports should be on the order of 100 bits long (excluding communications overhead), and should include a timestamp, sensor node ID, target/threat detection/classification code; it is desirable to also include a confidence level estimate. The type of signal processor is also not specified in this topic, but must consume exceptionally low amounts of power (e.g., 100 uW average). This may be achieved through a combination of power-efficient processor design, low clock rate or asynchronous computing, efficient algorithm(s), and/or low duty cycle(s). The processor output should include a sensor ID, timestamp, target type (simple classification), and confidence level. To process disparate signals from an extremely wide range of sources, multi-modal, or "orthogonal" sensor fusion is anticipated at some level. If possible, the processor/algorithm should be adaptable (to environment) and/or programmable (for a particular mission). The communications mode is not specified, although very low bit rates (<1 bps average), duty cycles (<1%), and ranges (<100 m ground-to-ground, <1000 m ground-to-air) are anticipated. The communications source may be acoustic/ultrasonic, RF, or IR, or it may resonate or reflect "on command" from an external receiver. One-way communication is presumed to exfiltrate data to end-users and/or more capable sensors, gateways, etc. Knowledge of the sensor location and/or orientation is often necessary; however, this topic does NOT address this issue. Under this topic, it can be assumed that such knowledge is available or can otherwise be determined during emplacement of the low-cost sensors. This topic also does NOT address issues related to information assurance (i.e., encryption, authentication, non-repudiation, etc.). It may be desirable to assimilate reports from multiple sensors over time, correlate this target and/or threat information with topographic and/or tactical features, and build one or more user interface(s) that provide(s) real-time situational awareness to individual soldiers and/or other C4I (command, control, computers, communications, and intelligence) assets; however, this topic does NOT address issues related to network-level information fusion, communications, and/or displays. PHASE I: Develop an overall system design that includes specification of low-cost, low-power sensors (modalities, transducers, amplifiers, filters), signal processors (sampling issues, processing mode(s), sensor fusion), and communications (type, duty cycle). Particular attention should be placed on unit production cost; other important issues include: power and energy consumption; size and weight; and robust operation (detection of a wide variety of targets under a wide variety of operating conditions). PHASE II: Develop and demonstrate a prototype system in a realistic environment. Conduct testing to prove feasibility over extended operating conditions. The "system" should include at least 10-20 low-cost, low-power sensor/processor/transmitter nodes, and at least one hand-held interrogator/receiver/display unit. PHASE III DUAL USE APPLICATIONS: This system could be used in a broad range of military and civilian security applications where automatic surveillance and tracking are necessary – for example, in overseas peacekeeping operations or in enhancing security in industrial facilities. REFERENCES: 1) Larry B. Stotts, "Unattended ground sensor related technologies; an Army perspective", Proceedings of SPIE, Vol. 4040, pp. 2-10, April, 2000. 2) John Eicke, "Disposable sensors: a vision of the world ahead", Proceedings of SPIE, Vol. 5090, April, 2003.
A03-035 TITLE: Cross-Layer Designs for Energy-Efficient Sensor Networking TECHNOLOGY AREAS: Information Systems ACQUISITION PROGRAM: Intell., EW and Sensors; Command, Cntrl., and Comm OBJECTIVE: To develop cross-layer approaches to radio design for energy-efficient ad hoc sensor networking. DESCRIPTION: Traditional designs of random access protocols and the physical layer radio have been separate, with each viewing the other component as a black box. Advances in signal processing at the physical layer dictate that the medium access control (MAC) layer take these advances into account. Benefits of a cross-layer design are evident in some recent designs such as the 802.11 standard. The Army vision for Future Combat Systems (FCS) envisages the deployment of large scale sensor networks to provide timely and reliable information to the soldier. Designing peer-to-peer communication systems for these radios faces several challenges such as mobility, uncertain terrain/channel conditions, scalability issues, and severe constraints on bandwidth and energy. The communication link will be asymmetric, and the users will be asynchronous, the sensors may be duty-cycled, and the load on the network may vary from quiescent to heavy loads. Thus the traditional single TDMA or CSMA/CA protocol, and the traditional barriers leading to separate design of networking, medium access and physical layer functions will not be adequate. A successful cross-layer design should lead to a robust low-complexity radio transceiver that can cope with potentially time- and frequency-selective channels, undesired interference, as well as thermal noise. The cross-layer design should be amenable to implementation and should be robust to reasonable variations in the environment (channel, users, interferers, etc.). The protocols should be energy-efficient and scalable. PHASE I: Propose, and analyze, novel cross-layer design techniques leading to robust scalable architectures for sensor networks, operating under varying system loads. Analyze the computation and implementation complexity of the joint design vs. traditional separate designs. Conduct robustness analyses. Demonstrate feasibility via limited software simulations. PHASE II: Develop working prototype radios based on the cross-layer protocols developed; demonstrate performance in a real-time environment. PHASE III DUAL USE APPLICATIONS: The wireless medium is continually challenged by demands for new services. It is expected that emerging technologies will lead to significant decrease in the size, weight, and power (SWAP) requirements of sensors, as well as their cost. Hence, systems with possibly large numbers of embedded sensors will be developed and will play significantly increased roles in applications ranging from monitoring (traffic, habitats, factory floors), telemedicine, ensuring infrastructure integrity (roads, bridges, power plants), as well as in tactical battlefield communications (sensor networks are envisaged to have a key role in FCS). Constraints on bandwidth and power will become more severe as the demand from applications increases. Successful cross-layer radio designs should lead to efficient usage of bandwidth and power. Radio architectures with energy efficient medium access protocols coupled with low-complexity signal processing at the physical layer will thus be in demand in many commercial situations. Thus the development of novel cross-layer protocols for radios will have significant commercial potential. OPERATING AND SUPPORT COST (OSCR) REDUCTION: Successful development of cross-layer protocols should lead to efficient use of bandwidth, and thus savings in cost. REFERENCES: 1) NSF/ONR/ARO-CTA Workshop on Future Challenges to Signal Processing and Communications in Wireless Networks, 5-6 September 2002, Cornell University, Ithaca, NY. 2) NSF/ONR Workshop on Cross-Layer Design in Adaptive Ad Hoc Networks: From Signal Processing to Global Networking. 31 May - 1 June 2001, Cornell University, Ithaca, NY. 3) Special Session on Cross-Layer Issues, Asilomar Conference on Signals, Systems and Computers, 3-6 November 2002, Pacific Grove, CA. 4) A. Swami and B. M. Sadler, "Issues in military communications", IEEE Signal Processing Magazine, 16(3), 31-33, March 1999.
A03-036 TITLE: Human Behavior Architecture Interface for Integrated Cognitive and Task Performance Model Development TECHNOLOGY AREAS: Information Systems, Human Systems ACQUISITION PROGRAM: Future Combat System OBJECTIVE: In order to account for the full range of soldier performance expected under the Army's Objective Force vision, a single interface must be developed for modeling both cognitive and task behaviors. The Future Combat System and the Objective Force Warrior acquisition programs are relying heavily on simulation-based acquisition and "Human Systems" are listed as a key enabling technology for those programs. It follows, then, that human behaviors as diverse as commander decision making, the monitoring of robotic devices, soldier situation awareness, and the performance of combat tasks must be represented in Army models and simulations. The most urgent need is for models and simulations used in force design and system acquisition although testing and training models also share this requirement. So that behaviors are considered in appropriate combinations, it is critical that a unified framework and a single software interface exist for model development. Consideration of task-level behaviors separate from the underlying cognitive processes can lead to inadequate organizational and design solutions and also duplication of effort. What is required by the rapid pace of the Army Transformation is that new, efficient, and cost-effective technical solutions be developed for the representation of human performance in models and simulations. The type of innovative solutions sought would increase the accessibility of tools and techniques for military force development and system design, and, therefore, also increase design effectiveness resulting in better system solutions for the Objective Force. DESCRIPTION: As noted in the National Research Council review (Pew & Mavor, 1998), the state-of-the-art of modeling human and organizational behavior is lacking. Currently there are reasonable approaches for representing task performance, which are used broadly today for human engineering (e.g., Allender, 2001); however, they require further maturation to adequately support representation of highly cognitive activities. Also, the application of cognitive modeling architectures to Army issues is becoming more prevalent and their value for representing cognition and for predicting human error performance, and thus, for system design has been demonstrated (e.g., Kelley, Patton, & Allender, 2001). However, cognitive architectures are notoriously difficult development environments, requiring expertise in both computer and cognitive science. Technology solutions must be developed that combine the detailed and theoretically-driven power of cognitive architectures with the broad descriptive and explanatory power of task network modeling (e.g., Lebiere, Biefeld, Archer, Archer, Allender, & Kelley, 2002). Such solutions must be applicable to both standalone modeling and human behavior representations federated with other models and simulations. There are multiple challenges to creating an interface for a human behavior architecture for integrated model development. First, selection of reasonable, robust, and validated available cognitive and task architectures for further development and/or integration is required given that development of an entirely new architecture is likely to be prohibitively costly and result in unnecessary duplication of efforts. Interface development must meet criteria of sound programming, efficient as well as psychologically plausible model-to-model communications, and, most importantly, inherent portrayal of a common foundation for representing both human cognitive and task-level behavior. In particular, this single, unified interface for accessing the cognitive and task architectures must meet standard usability guidelines for consistency, but it also must guide and compel users to develop unified models that use both the cognitive and task modeling functionality in appropriate and balanced combinations (e.g., Avraamides & Ritter, 2002; Taylor, Jones, Goldstein, Frederiksen, & Wray, 2002). PHASE I: The Phase I product will include the identification of task performance and cognitive architectures suitable to serve as the foundations for a unified interface. The documented rationale will be theoretically-grounded in accepted psychological principles including, but not limited to learning, memory, recall, recognition, decision making, and performance under a variety of stressors and individual difference parameters. A concept will be developed and application to an Army Objective Force-relevant case will be shown to be feasible. Within these requirements, there is considerable room for innovation and scientific advancement. PHASE II: At the conclusion of Phase II, a fully-capable unified interface for accessing task performance and cognitive architectures and for developing a seamless human behavior representation will be developed. Supporting experimental and field-practical findings will be provided showing that modelers are able to develop behavior representations of appropriate combinations of cognitive and task performance. Applications to both standalone and model federations are required. PHASE III: Prospects for Phase III applications are numerous: equally as well as in the military, and, for the first time, cost-effective tools and techniques for representing cognitive and task performance will be available to other government, industry, and even academia. The National Aeronautics and Space Administration, the Nuclear Regulatory Commission, the Federal Aviation Administration, and the Department of Transportation could take apply the resulting innovations to their own research, development, and regulatory efforts. Applications to the information systems, telecommunications businesses, and medical equipment industry also could be immediate as could implementation as a research tool in universities and colleges. REFERENCES: 1) Richard W. Pew & Anne S. Mavor, Eds. Modeling Human and Organizational Behavior. Applications to Military Simulations. National Academy Press: Washington, D.C., 1998. 2) Laurel Allender. Modeling human performance: Impacting system design, performance, and cost. In Proceedings of the Military, Government and Aerospace Simulation Symposium, 2000 Advanced Simulation Technologies Conference, M. Chinni, Ed., Washington, D.C., 2000, pp. 139-144. 3) Troy D. Kelley, Debra J. Patton, & Laurel Allender. Predicting situation awareness errors using cognitive modeling. In Proceedings of Human-Computer Interaction International 2001 Conference: (Vol. 1) Usability Evaluation and Interface Design: Cognitive Engineering, Intelligent Agents and Virtual Reality, Eds. M. J. Smith, G. Salvendy, D. Harris, R. J. Koubek. Mahwah, NJ: Lawrence Erlbaum Associates, 2001, pp. 1455-1459. 4) Christian Lebiere, Eric Biefeld, Rick Archer, Sue Archer, Laurel Allender, & Troy D. Kelley. IMPRINT/ACT-R: Integration of a task network modeling architecture with a cognitive architecture and its application to human error modeling. Proceedings of the 2002 Advanced Simulation Technologies Conference, Simulation Series Vol. 34 (3). San Diego, CA: SCS, April 2002, pp. 13-18. 5) Marios N. Avraamides & Frank E. Ritter. Using multidisciplinary expert evaluations to test and improve cognitive model interfaces. Proceedings of the Eleventh Conference on Computer Generated Forces and Behavior Representation, May 7-9, 2002, Orlando, FL, pp. 553-561. 6) Glen Taylor, Randolph M. Jones, Michael Goldstein, Richard Frederiksen, & Robert E. Wray, III. VISTA: A Generic Toolkit for Visualizing Agent Behavior. Proceedings of the Eleventh Conference on Computer Generated Forces and Behavior Representation, May 7-9, 2002, Orlando, FL, pp. 157-167.
A03-037 TITLE: Non-Fuel-Cell, Ultra-Low Emission/Signature Engine Capable of Exhaust Water Extraction TECHNOLOGY AREAS: Ground/Sea Vehicles ACQUISITION PROGRAM: NASA OBJECTIVE: Develop non-fuel-cell propulsion engines/concepts with ultra-low emissions (both pollutants and heat), that are amenable to exhaust water extraction. DESCRIPTION: The propulsion engine for advanced versions of the FCS (Future Combat System) must have many diverse attributes. Besides compactness, high power density and high efficiency, the engine must have the lowest possible pollutant and thermal signatures (both of which can be detected on the battlefield). In addition, in remote areas of the world, the ability to extract water from the engine exhaust is very desirable. Since (in an ideal combustion process) every gallon of fuel produces approximately an equal quantity of water, the ability to extract water from the exhaust would greatly reduce the logistics burden of delivering large quantities of water to the battlefield. Directory: osbp -> sbir -> solicitations solicitations -> Army sbir 09. 1 Proposal submission instructions dod small Business Innovation (sbir) Program solicitations -> Navy sbir fy09. 1 Proposal submission instructions solicitations -> Army 16. 3 Small Business Innovation Research (sbir) Proposal Submission Instructions solicitations -> Air force 12. 1 Small Business Innovation Research (sbir) Proposal Submission Instructions solicitations -> Army 14. 1 Small Business Innovation Research (sbir) Proposal Submission Instructions solicitations -> Navy small business innovation research program submitting Proposals on Navy Topics solicitations -> Navy small business innovation research program solicitations -> Armament research, development and engineering center solicitations -> Army 17. 1 Small Business Innovation Research (sbir) Proposal Submission Instructions solicitations -> Navy 11. 3 Small Business Innovation Research (sbir) Proposal Submission Instructions Download 1.85 Mb. Share with your friends:
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