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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Collection Efficiency and Ice Accretion Calculations for a Boeing 737-300 Inlet

Collection efficiency and ice accretion calculations have been made for a Boeing 737-300 inlet using a three-dimensional panel code, an adaptive grid code, the NASA Lewis LEWICE3D grid based ice accretion code. Flow solutions for the inlet were generated using the VSAERO panel code. Grids used in the ice accretion calculations were generated using the newly developed adaptive grid code ICEGRID3D. The LEWICE3D grid based ice accretion program was used to calculate impingement efficiency and ice shapes. Ice shapes typifying rime and mixed icing conditions were generated for a 30 minute hold condition. All calculations were performed on an SGI Power Challenge computer. The results have been compared to experimental flow and impingement data. In general, the calculated flow and collection efficiencies compared well with experiment, and the ice shapes looked reasonable and appeared representative of the rime and mixed icing conditions for which they were calculated.

Bidwell, Colin S.↗
NASA NTRS1997

Current Collection in a Magnetic Field

It is found that the upper-bound limit for current collection in the case of strong magnetic field from the current is close to that given by the Parker-Murphy formula. This conclusion is consistent with the results obtained in laboratory experiments. This limit weakly depends on the shape of the wire. The adiabatic limit in this case will be easily surpassed due to strong magnetic field gradients near the separatrix. The calculations can be done using the kinetic equation in the drift approximation. Analytical results are obtained for the region where the Earth's magnetic field is dominant. The current collection can be calculated (neglecting scattering) using a particle simulation code. Dr. Singh has agreed to collaborate, allowing the use of his particle code. The code can be adapted for the case when the current magnetic field is strong. The needed dm for these modifications is 3-4 months. The analytical description and essential part of the program is prepared for the calculation of the current in the region where the adiabatic description can be used. This was completed with the collaboration of Drs. Khazanov and Liemohn. A scheme of measuring the end body position is also proposed. The scheme was discussed in the laboratory (with Dr. Stone) and it was concluded that it can be proposed for engineering analysis.

Krivorutsky, E. N.↗
NASA NTRS1997

Current Collection in a Magnetic Field

In accordance with the contract, two problem were studied: the upper-bound limit of current collection taking into account the current's magnetic field and preparation toward numerical computation of current collection. Also investigated was a proposed scheme of measuring the location of the end body.

Krivorutsky, E. N.↗
NASA NTRS1999

Collection and Analysis of Aircraft Emitted Particles

The University of Denver Aerosol Group proposed to adapt an impactor system for the collection of particles emitted by aircraft. The collection substrates were electron microscope grids which were analyzed by Dr. Pat Sheridan using a transmission electron microscope. The impactor was flown in the SNIFF behind aircraft and engine emissions were sampled. This report details the results of that work.

Wilson, James Charles↗
NASA NTRS2000

The Abacus/Reflector and Integrated Symmetrical Concentrator: Concepts for Space Solar Power Collection and Transmission

New energy sources are vital for the development of emerging nations, and the growth of industry in developed economies. Also vital is the need for these energy sources to be clean and renewable. For the past several years, NASA has been taking a new look at collecting solar energy in space and transmitting it to Earth, to planetary surfaces, and to orbiting spacecraft. Several innovative concepts are being studied for the space segment component of solar power beaming. One is the Abacus/Reflector, a large sun-oriented array structure fixed to the transmitter, and a rotating RF reflector that tracks a receiving rectenna on Earth. This concept eliminates the need for power-conducting slip rings in rotating joints between the solar collectors and the transmitter. Another concept is the Integrated Symmetrical Concentrator (ISC), composed of two very large segmented reflectors which rotate to collect and reflect the incident sunlight onto two centrally-located photovoltaic arrays. Adjacent to the PV arrays is the RF transmitter, which as a unit track the receiving rectenna, again eliminating power-conducting joints, and in addition reducing the cable lengths between the arrays and transmitter. The metering structure to maintain the position of the reflectors is a long mast, oriented perpendicular to the equatorial orbit plane. This paper presents a status of ongoing systems studies and configurations for the Abacus/Reflector and the ISC concepts, and a top-level study of packaging for launch and assembly.

Carrington, Connie↗
NASA NTRS1999

Managing Personal and Group Collections of Information

The internet revolution has dramatically increased the amount of information available to users. Various tools such as search engines have been developed to help users find the information they need from this vast repository. Users often also need tools to help manipulate the growing amount of useful information they have discovered. Current tools available for this purpose are typically local components of web browsers designed to manage URL bookmarks. They provide limited functionalities to handle high information complexities. To tackle this have created DIAMS, an agent-based tool to help users or groups manage their information collections and share their collections with other. the main features of DIAMS are described here.

Wolfe, Shawn R.↗
NASA NTRS2000

Meteorites and Microbes: Meteorite Collection and Ice Sampling at Patriot Hills, Thiel Mountains, and South Pole, Antarctica

During the Antarctica 2000 Expedition, sponsored by the Planetary Studies Foundation, meteorites and ice microbiota were collected from the Patriot Hills, and Thiel Mountains of Antarctica and snow samples were at the South Pole. Psychrophilic and psychrotrophic microbiota were obtained from blue ice, cryoconite and ice-bubble systems. Twenty frozen meteorites were collected using aseptic techniques from the blue ice fields near the Moulton Escarpment of the Thiel Mountains (85 S, 94 W) and from the Morris Moraine of the Patriot Hills (80 S, 81 W) Ellsworth Mountains. These ice and meteorite samples are of potential significance to Astrobiology. They may help refine chemical and morphological biomarkers and refine characteristics of microbial life in one of the harshest environments on Earth. We discuss the Antarctica 2000 Expedition and provide preliminary results of the investigation of the meteorites and ice microbiota recovered.

Sipiera, Paul P.↗
NASA NTRS2001

Collection of LAI and FPAR Data Over The Terra Core Sites

The objective of our effort was to collect and archive data on LAI (leaf area index) and FPAR (Fraction of Photosynthetically active Radiation absorbed by vegetation) at the EOS Core validation sites as well as to validate and evaluate global fields of LAI and FPAR derived from atmospherically corrected MODIS (Moderate Resolution Imaging Spectrometer) surface reflectance data by comparing these fields with the EOS Core validation data set. The above has been accomplished by: (a) the participation in selected field campaigns within the EOS Validation Program; (b) the processing of the collected data so that suitable comparison between field measurements and the MODIS LAI/FPAR fields can be made; (c) the comparison of the MODAS LAI/FRAM fields with the EOS Terra Core validation data set.

Myneni, Ranga B.↗
NASA NTRS2001

Learning Sequences of Actions in Collectives of Autonomous Agents

In this paper we focus on the problem of designing a collective of autonomous agents that individually learn sequences of actions such that the resultant sequence of joint actions achieves a predetermined global objective. We are particularly interested in instances of this problem where centralized control is either impossible or impractical. For single agent systems in similar domains, machine learning methods (e.g., reinforcement learners) have been successfully used. However, applying such solutions directly to multi-agent systems often proves problematic, as agents may work at cross-purposes, or have difficulty in evaluating their contribution to achievement of the global objective, or both. Accordingly, the crucial design step in multiagent systems centers on determining the private objectives of each agent so that as the agents strive for those objectives, the system reaches a good global solution. In this work we consider a version of this problem involving multiple autonomous agents in a grid world. We use concepts from collective intelligence to design goals for the agents that are 'aligned' with the global goal, and are 'learnable' in that agents can readily see how their behavior affects their utility. We show that reinforcement learning agents using those goals outperform both 'natural' extensions of single agent algorithms and global reinforcement, learning solutions based on 'team games'.

Turner, Kagan↗
NASA NTRS2003

Collectives for the Optimal Combination of Imperfect Objects

In this letter we summarize some recent theoretical work on the design of collectives, i.e., of systems containing many agents, each of which can be viewed as trying to maximize an associated private utility, where there is also a world utility rating the behavior of that overall system that the designer of the collective wishes to optimize. We then apply algorithms based on that work on a recently suggested testbed for such optimization problems. This is the problem of finding the combination of imperfect nano-scale objects that results in the best aggregate object. We present experimental results showing that these algorithms outperform conventional methods by more than an order of magnitude in this domain.

Tumer, Kagan↗
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 NTRS2001

Design and Control of Large Collections of Learning Agents

The intelligent control of multiple autonomous agents is an important yet difficult task. Previous methods used to address this problem have proved to be either too brittle, too hard to use, or not scalable to large systems. The 'Collective Intelligence' project at NASA/Ames provides an elegant, machine-learning approach to address these problems. This approach mathematically defines some essential properties that a reward system should have to promote coordinated behavior among reinforcement learners. This work has focused on creating additional key properties and algorithms within the mathematics of the Collective Intelligence framework. One of the additions will allow agents to learn more quickly, in a more coordinated manner. The other will let agents learn with less knowledge of their environment. These additions will allow the framework to be applied more easily, to a much larger domain of multi-agent problems.

Agogino, Adrian↗
NASA NTRS2003

Team Formation and Communication Restrictions in Collectives

A collective of agents often needs to maximize a "world utility" function which rates the performance of an entire system, while subject to communication restrictions among the agents. Such communication restrictions make it difficult for agents which try to pursue their own "private" utilities to take actions that also help optimize the world utility. Team formation presents a solution to this problem, where by joining other agents, an agent can significantly increase its knowledge about the environment and improve its chances of both optimizing its own utility and that its doing so will contribute to the world utility. In this article we show how utilities that have been previously shown to be effective in collectives can be modified to be more effective in domains with moderate communication restrictions resulting in performance improvements of up to 75%. Additionally we show that even severe communication constraints can be overcome by forming teams where each agent of a team shares the same utility, increasing performance an additional 25%. We show that utilities and team sizes can be manipulated to form the best compromise between how "aligned" an agent s utility is with the world utility and how easily an agent can learn that utility.

Agogino, Adrian K.↗
NASA NTRS2003

The Genesis Solar Wind Collection Mission: Current Status

The NASA Genesis spacecraft was launched August 8, 2001 on a mission to collect samples of solar wind for greater than or equal to 2 years and then return them to Earth in 2004. Detailed analyses of the solar wind ions implanted into high-purity collection substrates will subsequently be carried out in earth-based laboratories using various mass spectrometry techniques. These analyses are expected to determine key isotopic ratios and elemental abundances in the solar wind and, by extension, in the solar photosphere. Further, the photospheric composition is thought to be representative of the solar nebula with a few exceptions so that the Genesis mission will provide a baseline for the average solar nebula composition with which to compare present-day compositions of planets, meteorites, and asteroids. The implications of the solar oxygen isotopic composition have been discussed. A list of other isotopic and elemental measurement objectives, and some of the rationale behind them, is given.

Barraclough, B. L.↗
NASA NTRS1998

Distributed Control with Collective Intelligence

We consider systems of interacting reinforcement learning (RL) algorithms that do not work at cross purposes , in that their collective behavior maximizes a global utility function. We call such systems COllective INtelligences (COINs). We present the theory of designing COINs. Then we present experiments validating that theory in the context of two distributed control problems: We show that COINs perform near-optimally in a difficult variant of Arthur's bar problem [Arthur] (and in particular avoid the tragedy of the commons for that problem), and we also illustrate optimal performance in the master-slave problem.

Wolpert, David H.↗
NASA NTRS1998

Using Collective Intelligence to Route Internet Traffic

A Collective Intelligence (COIN) is a community of interacting reinforcement learning (RL) algorithms designed so that their collective behavior maximizes a global utility function. We introduce the theory of COINs, then present experiments using that theory to design COINs to control internet traffic routing. These experiments indicate that COINs outperform previous RL-based systems for such routing that have previously been investigated.

Wolpert, David H.↗
NASA NTRS2004

Overcoming Communication Restrictions in Collectives

Many large distributed system are characterized by having a large number of components (eg., agents, neurons) whose actions and interactions determine a %orld utility which rates the performance of the overall system. Such collectives are often subject to communication restrictions, making it difficult for components which try to optimize their own private utilities, to take actions that also help optimize the world utility. In this article we address that coordination problem and derive four utility functions which present different compromises between how aligned a component s private utility is with the world utility and how readily that component can determine the actions that optimize its utility. The results show that the utility functions specifically derived to operate under communication restrictions outperform both traditional methods and previous collective-based methods by up to 75%.

Tumer, Kagan↗