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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Multiobjective optimization in structural design with uncertain parameters and stochastic processes

The application of multiobjective optimization techniques to structural design problems involving uncertain parameters and random processes is studied. The design of a cantilever beam with a tip mass subjected to a stochastic base excitation is considered for illustration. Several of the problem parameters are assumed to be random variables and the structural mass, fatigue damage, and negative of natural frequency of vibration are considered for minimization. The solution of this three-criteria design problem is found by using global criterion, utility function, game theory, goal programming, goal attainment, bounded objective function, and lexicographic methods. It is observed that the game theory approach is superior in finding a better optimum solution, assuming the proper balance of the various objective functions. The procedures used in the present investigation are expected to be useful in the design of general dynamic systems involving uncertain parameters, stochastic process, and multiple objectives.

Rao, S. S.↗
NASA NTRS1984

Design of vibration isolation systems using multiobjective optimization techniques

The design of vibration isolation systems is considered using multicriteria optimization techniques. The integrated values of the square of the force transmitted to the main mass and the square of the relative displacement between the main mass and the base are taken as the performance indices. The design of a three degrees-of-freedom isolation system with an exponentially decaying type of base disturbance is considered for illustration. Numerical results are obtained using the global criterion, utility function, bounded objective, lexicographic, goal programming, goal attainment and game theory methods. It is found that the game theory approach is superior in finding a better optimum solution with proper balance of the various objective functions.

Rao, S. S.↗
NASA NTRS1984

Multiobjective optimization techniques for structural design

The multiobjective programming techniques are important in the design of complex structural systems whose quality depends generally on a number of different and often conflicting objective functions which cannot be combined into a single design objective. The applicability of multiobjective optimization techniques is studied with reference to simple design problems. Specifically, the parameter optimization of a cantilever beam with a tip mass and a three-degree-of-freedom vabration isolation system and the trajectory optimization of a cantilever beam are considered. The solutions of these multicriteria design problems are attempted by using global criterion, utility function, game theory, goal programming, goal attainment, bounded objective function, and lexicographic methods. It has been observed that the game theory approach required the maximum computational effort, but it yielded better optimum solutions with proper balance of the various objective functions in all the cases.

Rao, S. S.↗
NASA NTRS1989

Simulation Of Combat With An Expert System

Proposed expert system predicts outcomes of combat situations. Called "COBRA", combat outcome based on rules for attrition, system selects rules for mathematical modeling of losses and discrete events in combat according to previous experiences. Used with another software module known as the "Game". Game/COBRA software system, consisting of Game and COBRA modules, provides for both quantitative aspects and qualitative aspects in simulations of battles. COBRA intended for simulation of large-scale military exercises, concepts embodied in it have much broader applicability. In industrial research, knowledge-based system enables qualitative as well as quantitative simulations.

Provenzano, J. P.↗
NASA NTRS1990

Optimal helicopter trajectory planning for terrain following flight

Helicopters operating in high threat areas have to fly close to the earth surface to minimize the risk of being detected by the adversaries. Techniques are presented for low altitude helicopter trajectory planning. These methods are based on optimal control theory and appear to be implementable onboard in realtime. Second order necessary conditions are obtained to provide a criterion for finding the optimal trajectory when more than one extremal passes through a given point. A second trajectory planning method incorporating a quadratic performance index is also discussed. Trajectory planning problem is formulated as a differential game. The objective is to synthesize optimal trajectories in the presence of an actively maneuvering adversary. Numerical methods for obtaining solutions to these problems are outlined. As an alternative to numerical method, feedback linearizing transformations are combined with the linear quadratic game results to synthesize explicit nonlinear feedback strategies for helicopter pursuit-evasion. Some of the trajectories generated from this research are evaluated on a six-degree-of-freedom helicopter simulation incorporating an advanced autopilot. The optimal trajectory planning methods presented are also useful for autonomous land vehicle guidance.

Menon, P. K. A.↗
NASA NTRS1990

Time-optimal Aircraft Pursuit-evasion with a Weapon Envelope Constraint

The optimal pursuit-evasion problem between two aircraft including a realistic weapon envelope is analyzed using differential game theory. Six order nonlinear point mass vehicle models are employed and the inclusion of an arbitrary weapon envelope geometry is allowed. The performance index is a linear combination of flight time and the square of the vehicle acceleration. Closed form solution to this high-order differential game is then obtained using feedback linearization. The solution is in the form of a feedback guidance law together with a quartic polynomial for time-to-go. Due to its modest computational requirements, this nonlinear guidance law is useful for on-board real-time implementation.

Menon, P. K. A.↗
NASA NTRS1991

Extended attention span training system

Attention Deficit Disorder (ADD) is a behavioral disorder characterized by the inability to sustain attention long enough to perform activities such as schoolwork or organized play. Treatments for this disorder include medication and brainwave biofeedback training. Brainwave biofeedback training systems feed back information to the trainee showing him how well he is producing the brainwave pattern that indicates attention. The Extended Attention Span Training (EAST) system takes the concept a step further by making a video game more difficult as the player's brainwaves indicate that attention is waning. The trainee can succeed at the game only by maintaining an adequate level of attention. The EAST system is a modification of a biocybernetic system that is currently being used to assess the extent to which automated flight management systems maintain pilot engagement. This biocybernetic system is a product of a program aimed at developing methods to evaluate automated flight deck designs for compatibility with human capabilities. The EAST technology can make a contribution in the fields of medical neuropsychology and neurology, where the emphasis is on cautious, conservative treatment of youngsters with attention disorders.

Pope, Alan T.↗
NASA NTRS1995

Structural design using equilibrium programming formulations

Solutions to increasingly larger structural optimization problems are desired. However, computational resources are strained to meet this need. New methods will be required to solve increasingly larger problems. The present approaches to solving large-scale problems involve approximations for the constraints of structural optimization problems and/or decomposition of the problem into multiple subproblems that can be solved in parallel. An area of game theory, equilibrium programming (also known as noncooperative game theory), can be used to unify these existing approaches from a theoretical point of view (considering the existence and optimality of solutions), and be used as a framework for the development of new methods for solving large-scale optimization problems. Equilibrium programming theory is described, and existing design techniques such as fully stressed design and constraint approximations are shown to fit within its framework. Two new structural design formulations are also derived. The first new formulation is another approximation technique which is a general updating scheme for the sensitivity derivatives of design constraints. The second new formulation uses a substructure-based decomposition of the structure for analysis and sensitivity calculations. Significant computational benefits of the new formulations compared with a conventional method are demonstrated.

Scotti, Stephen J.↗
NASA NTRS1995

STS-73 Flight Day 6

On this sixth day of the STS-73 sixteen day mission, the crew Cmdr. Kenneth Bowersox, Pilot Kent Rominger, Payload Specialists Albert Sacco and Fred Leslie, and Mission Specialists Kathryn Thornton, Catherine 'Cady' Coleman, and Michael Lopez-Alegria are shown performing several of the spaceborne experiments onboard the United States Microgravity Lab-2 (USML-2). The experiments shown include the Protein Crystal Growth (PCG) experiment, the Astroculture(tm)(ASC) experiment, the Drop Physics Module (DPM) experiment, and the Surface Tension Driven Convection Experiment (STDCE). The High-Packed Digital Television (HI-PAC) system is further tested and an in-orbit interview with Lopez-Alegria by NBC Nightside is conducted. The entire flightcrew salutes the 5th game of the World Series between the Atlanta Braves and Cleveland Indians by pretending to throw out the first ball of the game through a downlink to the stadium. Earth views taken from the payload bay cameras include some cloud cover, oceans, land masses, and the Nile River and the Red Sea.

Source record↗
NASA NTRS1994

Demonstration of high sensitivity laser ranging system

We report on a high sensitivity semiconductor laser ranging system developed for the Gravity and Magnetic Earth Surveyor (GAMES) for measuring variations in the planet's gravity field. The GAMES laser ranging instrument (LRI) consists of a pair of co-orbiting satellites, one which contains the laser transmitter and receiver and one with a passive retro-reflector mounted in an drag-stabilized housing. The LRI will range up to 200 km in space to the retro-reflector satellite. As the spacecraft pair pass over the spatial variations in the gravity field, they experience along-track accelerations which change their relative velocity. These time displaced velocity changes are sensed by the LRI with a resolution of 20-50 microns/sec. In addition, the pair may at any given time be drifting together or apart at a rate of up to 1 m/sec, introducing a Doppler shift into the ranging signals. An AlGaAs laser transmitter intensity modulated at 2 GHz and 10 MHz is used as fine and medium ranging channels. Range is measured by comparing phase difference between the transmit and received signals at each frequency. A separate laser modulated with a digital code, not reported in this paper, will be used for coarse ranging to unambiguously determine the distance up to 200 km.

Millar, Pamela S.↗
NASA NTRS1999

Practical Application of Model Checking in Software Verification

This paper presents our experiences in applying the JAVA PATHFINDER (J(sub PF)), a recently developed JAVA to SPIN translator, in the finding of synchronization bugs in a Chinese Chess game server application written in JAVA. We give an overview of J(sub PF) and the subset of JAVA that it supports and describe the abstraction and verification of the game server. Finally, we analyze the results of the effort. We argue that abstraction by under-approximation is necessary for abstracting sufficiently smaller models for verification purposes; that user guidance is crucial for effective abstraction; and that current model checkers do not conveniently support the computational models of software in general and JAVA in particular.

Havelund, Klaus↗
NASA NTRS2000

Landsat TM as a Tool for Locating Habitat for Cerulean Warblers

I believe that I made significant strides in three areas between fall of 1997 and fall of 2000 when I concluded my participation in the JOVE program. First, I acquired skill in digital remote sensing. This was significant to me because it had been 20 years since I had done any work utilizing remote sensing. I used my new skills in two classroom settings (forest ecology and GIS). In addition, I will participate as an instructor of digital remote sensing in a workshop for secondary educators this coming spring. Second, I received funding from the Arkansas Game and Fish Commission and the U.S. Forest Service to supplement JOVE funds. Third, and most importantly, a students and I developed a technique using LandSAT TM for identifying habitat for cerulean warblers. We developed a habitat model using logistic regression to discriminate between pixels that had a high probability of representing good cerulean warbler habitat and pixels that had a low probability of representing cerulean warbler habitat. Using this model, we located five significant populations of cerulean warblers in the Ozark National Forest of Arkansas. These populations were unknown before the initiation of this research and further represent a significant proportion of the known cerulean warblers in Arkansas. Preliminary findings were presented at the Ornithological Societies of America meeting in August of 1999. I also presented findings at the Arkansas Game and Fish Commission Research Symposium held in June of 2000. Finally, one paper is in press: James, D. A., C.J. Kellner, J. Self, and J. Davis., 'Breeding season distribution of cerulean warblers in Arkansas in the 1990's'. In addition, one paper is under construction: 'Population fluctuation and habitat selection by cerulean warblers in upland forests of Arkansas,' and one paper is under consideration: 'LandSAT TM and Logistic regression for identification of cerulean warbler habitat in upland forests of Arkansas.'

Kellner, Chris↗
NASA NTRS2000

Optimal Wonderful Life Utility Functions in Multi-Agent Systems

The mathematics of Collective Intelligence (COINs) is concerned with the design of multi-agent systems so as to optimize an overall global utility function when those systems lack centralized communication and control. Typically in COINs each agent runs a distinct Reinforcement Learning (RL) algorithm, so that much of the design problem reduces to how best to initialize/update each agent's private utility function, as far as the ensuing value of the global utility is concerned. Traditional team game solutions to this problem assign to each agent the global utility as its private utility function. In previous work we used the COIN framework to derive the alternative Wonderful Life Utility (WLU), and experimentally established that having the agents use it induces global utility performance up to orders of magnitude superior to that induced by use of the team game utility. The WLU has a free parameter (the clamping parameter) which we simply set to zero in that previous work. Here we derive the optimal value of the clamping parameter, and demonstrate experimentally that using that optimal value can result in significantly improved performance over that of clamping to zero, over and above the improvement beyond traditional approaches.

Wolpert, David H.↗
NASA NTRS1998

Sense of Touch

Logitech Inc., has advanced a digital game controller originally developed for a NASA space mission. CyberMan 2 offers players the experience of being "inside" the game. The product is commercially available for $99 to anyone with a personal computer.

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NASA NTRS2002

The Design of Collectives of Agents to Control Non-Markovian Systems

The 'Collective Intelligence' (COIN) framework concerns the design of collectives of reinforcement-learning agents such that their interaction causes a provided 'world' utility function concerning the entire collective to be maximized. Previously, we applied that framework to scenarios involving Markovian dynamics where no re-evolution of the system from counter-factual initial conditions (an often expensive calculation) is permitted. This approach sets the individual utility function of each agent to be both aligned with the world utility, and at the same time, easy for the associated agents to optimize. Here we extend that approach to systems involving non-Markovian dynamics. In computer simulations, we compare our techniques with each other and with conventional-'team games'. We show whereas in team games performance often degrades badly with time, it steadily improves when our techniques are used. We also investigate situations where the system's dimensionality is effectively reduced. We show that this leads to difficulties in the agents' ability to learn. The implication is that 'learning' is a property only of high-enough dimensional systems.

Lawson, John W.↗
NASA NTRS2003

Collectives for Multiple Resource Job Scheduling Across Heterogeneous Servers

Efficient management of large-scale, distributed data storage and processing systems is a major challenge for many computational applications. Many of these systems are characterized by multi-resource tasks processed across a heterogeneous network. Conventional approaches, such as load balancing, work well for centralized, single resource problems, but breakdown in the more general case. In addition, most approaches are often based on heuristics which do not directly attempt to optimize the world utility. In this paper, we propose an agent based control system using the theory of collectives. We configure the servers of our network with agents who make local job scheduling decisions. These decisions are based on local goals which are constructed to be aligned with the objective of optimizing the overall efficiency of the system. We demonstrate that multi-agent systems in which all the agents attempt to optimize the same global utility function (team game) only marginally outperform conventional load balancing. On the other hand, agents configured using collectives outperform both team games and load balancing (by up to four times for the latter), despite their distributed nature and their limited access to information.

Tumer, K.↗
NASA NTRS2003

A Real Attention-Getter

While most parents would agree that playing videos games is the antithesis of time well spent for their children, recent advances involving NASA biofeedback technology are proving otherwise. The same techniques used to measure brain activity in NASA pilots during flight simulation exercises are now a part of a revolutionary video game system that is helping to improve overall mental awareness for Americans of all ages, including those who suffer from Attention Deficit Hyperactivity Disorder (ADHD).

Source record↗
NASA NTRS2002

Time-Extended Payoffs for Collectives of Autonomous Agents

A collective is a set of self-interested agents which try to maximize their own utilities, along with a a well-defined, time-extended world utility function which rates the performance of the entire system. In this paper, we use theory of collectives to design time-extended payoff utilities for agents that are both aligned with the world utility, and are "learnable", i.e., the agents can readily see how their behavior affects their utility. We show that in systems where each agent aims to optimize such payoff functions, coordination arises as a byproduct of the agents selfishly pursuing their own goals. A game theoretic analysis shows that such payoff functions have the net effect of aligning the Nash equilibrium, Pareto optimal solution and world utility optimum, thus eliminating undesirable behavior such as agents working at cross-purposes. We then apply collective-based payoff functions to the token collection in a gridworld problem where agents need to optimize the aggregate value of tokens collected across an episode of finite duration (i.e., an abstracted version of rovers on Mars collecting scientifically interesting rock samples, subject to power limitations). We show that, regardless of the initial token distribution, reinforcement learning agents using collective-based payoff functions significantly outperform both natural extensions of single agent algorithms and global reinforcement learning solutions based on "team games".

Tumer, Kagan↗