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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

CO2 Removal Onboard the International Space Station – Material Selection and System Design

The previous three years of efforts have focused on the study of the sorbent materials available for use in a 4-bed molecular sieve system. The accumulation of knowledge has been invaluable for further decisions and for reflecting on the conclusions of past decisions. The goal of the next system is perfect uptime for nearly 20,000 hours of operation, but no complex life support system has yet reached this lofty goal. In addition to reliability, CO2 removal performance improvements have been intensively studied. The achievements toward this end include highly detailed isotherm measurements which drive system simulations as well as testing physical design improvements. Looking back on the successes and failures of past systems, correlating tests with long-duration data, and carefully projecting the future are all needed for the success of the next system. This work intends to reveal the path we have taken and illuminate the steps to come for CO2 removal life support with the 4BCO2 flight demonstration.

Cmarik, Gregory E.↗
NASA NTRS2004

Spaceborne Doppler Precipitation Radar: System Configurations and Performance Analysis

Knowledge of the global distribution of the vertical velocity of precipitation is important in in the study of energy transportation in the atmosphere, the climate and weather. Such knowledge can only be directly acquired with the use of spaceborne Doppler precipitation radars. Although the high relative speed of the radar with respect to the rainfall particles introduces significant broadening in the Doppler spectrum, recent studies have shown that the average vertical velocity can be measured to acceptable accuracy levels by appropriate selection of radar parameters. Furthermore, methods to correct for specific errors arising from NUBF effects and pointing uncertainties have recently been developed. In this paper we will present the results of the trade studies on the performances of a spaceborne Doppler radar with different system parameters configurations.

spaceborne radar↗
DOE OSTI2022

MIONet: Learning Multiple-Input Operators via Tensor Product

As an emerging paradigm in scientific machine learning, neural operators aim to learn operators, via neural networks, that map between infinite-dimensional function spaces. Several neural operators have been recently developed. However, all the existing neural operators are only designed to learn operators defined on a single Banach space; i.e., the input of the operator is a single function. Here, for the first time, we study the operator regression via neural networks for multiple-input operators defined on the product of Banach spaces. We first prove a universal approximation theorem of continuous multiple-input operators. We also provide a detailed theoretical analysis including the approximation error, which provides guidance for the design of the network architecture. Based on our theory and a low-rank approximation, we propose a novel neural operator, MIONet, to learn multiple-input operators. MIONet consists of several branch nets for encoding the input functions and a trunk net for encoding the domain of the output function. Here, we demonstrate that MIONet can learn solution operators involving systems governed by ordinary and partial differential equations. In our computational examples, we also show that we can endow MIONet with prior knowledge of the underlying system, such as linearity and periodicity, to further improve accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Survey of spatio-temporal couplings throughout high-power ultrashort lasers

The investigation of spatio-temporal couplings (STCs) of broadband light beams is becoming a key topic for the optimization as well as applications of ultrashort laser systems. This calls for accurate measurements of STCs. Yet, it is only recently that such complete spatio-temporal or spatio-spectral characterization has become possible, and it has so far mostly been implemented at the output of the laser systems, where experiments take place. In this survey, we present for the first time STC measurements at different stages of a collection of high-power ultrashort laser systems, all based on the chirped-pulse amplification (CPA) technique, but with very different output characteristics. This measurement campaign reveals spatio-temporal effects with various sources, and motivates the expanded use of STC characterization throughout CPA laser chains, as well as in a wider range of types of ultrafast laser systems. In this way knowledge will be gained not only about potential defects, but also about the fundamental dynamics and operating regimes of advanced ultrashort laser systems.

Jeandet, Antoine (ORCID:0000000345493067)↗
NASA NTRS1977

Robot learning and error correction

A model of robot learning is described that associates previously unknown perceptions with the sensed known consequences of robot actions. For these actions, both the categories of outcomes and the corresponding sensory patterns are incorporated in a knowledge base by the system designer. Thus the robot is able to predict the outcome of an action and compare the expectation with the experience. New knowledge about what to expect in the world may then be incorporated by the robot in a pre-existing structure whether it detects accordance or discrepancy between a predicted consequence and experience. Errors committed during plan execution are detected by the same type of comparison process and learning may be applied to avoiding the errors.

Friedman, L.↗
NASA NTRS1993

Telerobotic control of a mobile coordinated robotic server, executive summary

This interim report continues with the research effort on advanced adaptive controls for space robotics systems. In particular, previous results developed by the principle investigator and his research team centered around fuzzy logic control (FLC) in which the lack of knowledge of the robotic system as well as the uncertainties of the environment are compensated for by a rule base structure which interacts with varying degrees of belief of control action using system measurements. An on-line adaptive algorithm was developed using a single parameter tuning scheme. In the effort presented, the methodology is further developed to include on-line scaling factor tuning and self-learning control as well as extended to the multi-input, multi-output (MIMO) case. Classical fuzzy logic control requires tuning input scale factors off-line through trial and error techniques. This is time-consuming and cannot adapt to new changes in the process. The new adaptive FLC includes a self-tuning scheme for choosing the scaling factors on-line. Further the rule base in classical FLC is usually produced by soliciting knowledge from human operators as to what is good control action for given circumstances. This usually requires full knowledge and experience of the process and operating conditions, which limits applicability. A self-learning scheme is developed which adaptively forms the rule base with very limited knowledge of the process. Finally, a MIMO method is presented employing optimization techniques. This is required for application to space robotics in which several degrees-of-freedom links are commonly used. Simulation examples are presented for terminal control - typical of robotic problems in which a desired terminal point is to be reached for each link. Future activities will be to implement the MIMO adaptive FLC on an INTEL microcontroller-based circuit and to test the algorithm on a robotic system at the Mars Mission Research Center at North Carolina State University.

Lee, Gordon↗
DOE OSTI2022

Phase Stability Through Machine Learning

Understanding the phase stability of a chemical system constitutes the foundation of materials science. Knowledge of the equilibrium state of a system under arbitrary thermodynamic conditions provides valuable information about the types of phases that are likely to be synthesized and how to get there. Accessing the phase diagram in a materials system provides one with the information necessary to design materials and microstructures with optimal properties. While the materials science community has long been focused on exploiting this knowledge to navigate the materials space, recent advances in machine learning (ML) and artificial intelligence (AI) have provided the community with novel ways of interrogating the materials thermodynamics space. Furthermore, this work presents some of the most recent advances in ML/AI applied to phase stability and thermodynamics of materials. Prof. John Morral always had a passion for understanding and teaching the fundamental characteristics of phase diagrams. This review is written to honor his memory.

36 MATERIALS SCIENCE↗
NASA NTRS1988

Automated knowledge generation

The general objectives of the NASA/UCF Automated Knowledge Generation Project were the development of an intelligent software system that could access CAD design data bases, interpret them, and generate a diagnostic knowledge base in the form of a system model. The initial area of concentration is in the diagnosis of the process control system using the Knowledge-based Autonomous Test Engineer (KATE) diagnostic system. A secondary objective was the study of general problems of automated knowledge generation. A prototype was developed, based on object-oriented language (Flavors).

Myler, Harley R.↗
NASA NTRS1982

An overview of expert systems

An expert system is defined and its basic structure is discussed. The knowledge base, the inference engine, and uses of expert systems are discussed. Architecture is considered, including choice of solution direction, reasoning in the presence of uncertainty, searching small and large search spaces, handling large search spaces by transforming them and by developing alternative or additional spaces, and dealing with time. Existing expert systems are reviewed. Tools for building such systems, construction, and knowledge acquisition and learning are discussed. Centers of research and funding sources are listed. The state-of-the-art, current problems, required research, and future trends are summarized.

Gevarter, W. B.↗
NASA NTRS2009

Towards a Framework for Evaluating and Comparing Diagnosis Algorithms

Diagnostic inference involves the detection of anomalous system behavior and the identification of its cause, possibly down to a failed unit or to a parameter of a failed unit. Traditional approaches to solving this problem include expert/rule-based, model-based, and data-driven methods. Each approach (and various techniques within each approach) use different representations of the knowledge required to perform the diagnosis. The sensor data is expected to be combined with these internal representations to produce the diagnosis result. In spite of the availability of various diagnosis technologies, there have been only minimal efforts to develop a standardized software framework to run, evaluate, and compare different diagnosis technologies on the same system. This paper presents a framework that defines a standardized representation of the system knowledge, the sensor data, and the form of the diagnosis results and provides a run-time architecture that can execute diagnosis algorithms, send sensor data to the algorithms at appropriate time steps from a variety of sources (including the actual physical system), and collect resulting diagnoses. We also define a set of metrics that can be used to evaluate and compare the performance of the algorithms, and provide software to calculate the metrics.

Kurtoglu, Tolga↗
NASA NTRS1991

A knowledge based application of the extended aircraft interrogation and display system

A family of multiple-processor ground support test equipment was used to test digital flight-control systems on high-performance research aircraft. A unit recently built for the F-18 high alpha research vehicle project is the latest model in a series called the extended aircraft interrogation and display system. The primary feature emphasized monitors the aircraft MIL-STD-1553B data buses and provides real-time engineering units displays of flight-control parameters. A customized software package was developed to provide real-time data interpretation based on rules embodied in a highly structured knowledge database. The configuration of this extended aircraft interrogation and display system is briefly described, and the evolution of the rule based package and its application to failure modes and effects testing on the F-18 high alpha research vehicle is discussed.

Glover, Richard D.↗
NASA NTRS1999

Earth Science Enterprise Technology Strategy

NASA's Earth Science Enterprise (ESE) is dedicated to understanding the total Earth system and the effects of natural and human-induced changes on the global environment. The goals of ESE are: (1) Expand scientific knowledge of the Earth system using NASA's unique vantage points of space, aircraft, and in situ platforms; (2) Disseminate information about the Earth system; and (3) Enable the productive use of ESE science and technology in the public and private sectors. ESE has embraced the NASA Administrator's better, faster, cheaper paradigm for Earth observing missions. We are committed to launch the next generation of Earth Observing System (EOS) missions at a substantially lower cost than the EOS first series. Strategic investment in advanced instrument, spacecraft, and information system technologies is essential to accomplishing ESE's research goals in the coming decades. Advanced technology will play a major role in shaping the ESE fundamental and applied research program of the future. ESE has established an Earth science technology development program with the following objectives: (1) To accomplish ESE space-based and land-based program elements effectively and efficiently; and (2) To enable ESE's fundamental and applied research programs goals as stated in the NASA Strategic Plan.

Source record↗
NASA NTRS1987

Clips as a knowledge based language

CLIPS is a language for writing expert systems applications on a personal or small computer. Here, the CLIPS programming language is described and compared to three other artificial intelligence (AI) languages (LISP, Prolog, and OPS5) with regard to the processing they provide for the implementation of a knowledge based system (KBS). A discussion is given on how CLIPS would be used in a control system.

Harrington, James B.↗
NASA NTRS1983

HDM/PASCAL Verification System User's Manual

The HDM/Pascal verification system is a tool for proving the correctness of programs written in PASCAL and specified in the Hierarchical Development Methodology (HDM). This document assumes an understanding of PASCAL, HDM, program verification, and the STP system. The steps toward verification which this tool provides are parsing programs and specifications, checking the static semantics, and generating verification conditions. Some support functions are provided such as maintaining a data base, status management, and editing. The system runs under the TOPS-20 and TENEX operating systems and is written in INTERLISP. However, no knowledge is assumed of these operating systems or of INTERLISP. The system requires three executable files, HDMVCG, PARSE, and STP. Optionally, the editor EMACS should be on the system in order for the editor to work. The file HDMVCG is invoked to run the system. The files PARSE and STP are used as lower forks to perform the functions of parsing and proving.

Hare, D.↗
NASA NTRS1990

Results of the Systems Autonomy Demonstration Project

The Systems Autonomy Demonstration Project (SADP) produced a knowledge-based real-time control system for real-time control and fault detection, isolation and recovery (FDIR) of a prototype two-phase Space Station Freedom external control system (TCS). The Thermal Expert System (TEXSYS) was demonstrated in recent tests to be capable of reliable fault anticipation and detection, as well as nominal control of the thermal bus. Performance requirements were addressed by adopting a hierarchical symbolic control approach, layering model-based expert system software on a conventional numerical data acquisition and control system. The model-based capabilities of TEXSYS were shown to be advantageous, particularly for detection of unforeseen faults and sensor failures.

Glass, B. J.↗
NASA NTRS1992

Survey of Intelligent Computer-Aided Training

Intelligent Computer-Aided Training (ICAT) systems integrate artificial intelligence and simulation technologies to deliver training for complex, procedural tasks in a distributed, workstation-based environment. Such systems embody both the knowledge of how to perform a task and how to train someone to perform that task. This paper briefly reviews the antecedents of ICAT systems and describes the approach to their creation developed at the NASA Lyndon B. Johnson Space Center. In addition to the general ICAT architecture, specific ICAT applications that have been or are currently under development are discussed. ICAT systems can offer effective solutions to a number of training problems of interest to the aerospace community.

Loftin, R. B.↗
NASA NTRS1990

Real time data acquisition for expert systems in Unix workstations at Space Shuttle Mission Control

A distributed system of proprietary engineering-class workstations is incorporated into NASA's Space Shuttle Mission-Control Center to increase the automation of mission control. The Real-Time Data System (RTDS) allows the operator to utilize expert knowledge in the display program for system modeling and evaluation. RTDS applications are reviewed including: (1) telemetry-animated communications schematics; (2) workstation displays of systems such as the Space Shuttle remote manipulator; and (3) a workstation emulation of shuttle flight instrumentation. The hard and soft real-time constraints are described including computer data acquisition, and the support techniques for the real-time expert systems include major frame buffers for logging and distribution as well as noise filtering. The incorporation of the workstations allows smaller programming teams to implement real-time telemetry systems that can improve operations and flight testing.

Muratore, John F.↗
NASA NTRS1991

The role of smart systems in rendezvous, close proximity operations and docking maneuvers

Various missions scenarios (Space Station logistics, LEO and GEO services, and SEI operation) will involve flexibility in mission management. This means operations will be one or a combination of the following: autonomous, supervised autonomous, and machine aided manual control. Smart Systems will likely play a significant role in making these missions successful from a safety/reliability perspective and less costly from an operations perspective. This does not imply that Smart Systems need to be super sophisticated. On the contrary, Smart Systems have been described as automated intelligence that if a person had done it wrong, it would be considered stupid. The first part of this paper will describe the types of Smart System techniques involved in AR and CC, their specifications, duties, and interactions. Next will be a discussion of the work performed under the auspice of the ALS Program to further Expert Systems applications imbedded in the control process, NASA/JSC CRAD, and other related IRAD projects. This will include issues pertaining to the following: integration, speed, knowledge encapsulation, and cooperative systems. Finally, a brief description will be offered to outline the major obstacles for the acceptance of Smart Systems in critical applications.

Szatkowski, Gerard P.↗