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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Photovoltaic research and development in Japan

The status of the Japanese photovoltaic (PV) R&D activities was surveyed through literature searches, private communications, and site visits in 1982. The results show that the Japanese photovoltaic technology is maturing rapidly, consistent with the steady government funding under the Sunshine Project. Two main thrusts of the Project are: (1) completion of the solar panel production pilot plants using cast ingot and sheet silicon materials, and (2) development of large area amorphous silicon solar cells with acceptable efficiency (10 to 12%). An experimental automated solar panel production plant rated at 500 kW/yr is currently under construction for the Sunshine Project for completion in March 1983. Efficiencies demonstrated by experimental large are amorphous silicon solar cells are approaching 8%. Small area amorphous silicon solar cells are, however, currently being mass produced and marketed by several companies at an equivalent annual rate of 2 MW/yr for consumer electronic applications. There is no evidence of an immediate move by the Japanese PV industry to enter extensively into the photovoltaic power market, domestic or otherwise. However, the photovoltaic technology itself could become ready for such an entry in the very near future, especially by making use of advanced process automation technologies.

Shimada, K.↗
NASA NTRS1999

Solar Microflare with BATSE

Our work on detecting and cataloging solar microflares using an automated method is illustrated in the accompanying figure. The figure represents the solar microflare distribution during the period of April 1991 to November 1992, the height of solar activity after the launch of The Compton Gamma Ray Observatory (CGRO). It also shows the distribution extending below the distribution obtained at Goddard Space Flight Center (GSFC) by manual means. We have implemented significant refinements in the search algorithm. The algorithm in its simplest form searches for transient events and based upon the distribution of the signal among the different Burst and Transient Source Experiment (BATSE) detectors, we can assign it to be of solar origin if the signal distribution conforms to what one expects from a burst or transient from that direction. One of the major problems in the earlier effort was to search for microflares and large flares simultaneously. The requirement for a dynamic range of almost 10 (exp 4) resulted in ambiguous identifications at the low side of the distribution. We have since restricted the search to events with peak count rates under 2000 s (exp -1). Larger events are easily identified in the manual search, so we have chosen not to duplicate that work. The second problem was that missing counts existed below channel 0 in the Burst and Transient Source Experiment Large Area Detector data (BATSE LAD). These have been recovered and are now included in the search process. This provides data below 20 keV, and as we get closer to the thermal part of the spectrum, it provides greater sensitivity. The third problem was that too many BATSE detector were used in the search. Detectors with pointing directions far from the Sun, although detecting the event, had poorly known responses. Detectors greater than approximately 60 deg. off the Sun are no longer included in the search process. By reducing the systematic errors with the large off-axis detectors we can conduct more rigorous statistical tests of a candidate event to ascertain whether it originated from the solar direction. We have reprocessed the period in the early mission that covers solar maximum and constructed the microflare distribution shown in the figure. The results of the automated search start to deviate from the manual search results below about 1000 s (exp -1). Not only do we now have this distribution but we have a database of solar microflares that was used to construct the distribution. This database contains the signal at higher energy channels as well as that in channel zero (and below). From this one can, using software at GSFC, construct a photon spectrum for some of the larger microflares. It can also be used in other solar studies, especially those that correlate the X-ray flux with emission at other wavelengths. With some additional effort we hope to integrate this database into the corresponding one residing at the Solar Data Analysis Center at GSFC. The entire CGRO mission's data can now be reprocessed to obtain the microflare distribution at all phases of the solar cycle. This work is in progress. The results of this work will be presented in forthcoming scientific workshops and conferences.

Ryan, James M.↗
NASA NTRS1987

Electronic prototyping

The potential benefits of automation in space are significant. The science base needed to support this automation not only will help control costs and reduce lead-time in the earth-based design and construction of space stations, but also will advance the nation's capability for computer design, simulation, testing, and debugging of sophisticated objects electronically. Progress in automation will require the ability to electronically represent, reason about, and manipulate objects. Discussed here is the development of representations, languages, editors, and model-driven simulation systems to support electronic prototyping. In particular, it identifies areas where basic research is needed before further progress can be made.

Hopcroft, J.↗
NASA NTRS1975

A fully automated digitally controlled 30-inch telescope

A fully automated 30-inch (75-cm) telescope has been successfully designed and constructed from a military surplus Nike-Ajax radar mount. Novel features include: closed-loop operation between mountain telescope and campus computer 30 km apart via microwave link, a TV-type sensor which is photon shot-noise limited, a special lightweight primary mirror, and a stepping motor drive capable of slewing and settling one degree in one second or a radian in fifteen seconds.

Colgate, S. A.↗
NASA NTRS1984

Support structures for large infrared telescopes

An infrared telescope requires an accuracy of its reflecting surfaces of less than a micrometer. Future missions may require such accuracy from telescopes that are 20 meters or larger in diameter. The structure for supporting such a telescope will most probably take the form of a deep truss. Various approaches for constructing the primary mirror in space are illustrated. One that employs automated deployment of interconnected reflector-structure modules was described in detail. Estimates were made of the precision obtainable with properly configured truss structures and the required ability of active control systems for achieving the desired accuracy.

Hedgepeth, J. M.↗
NASA NTRS1991

Theoretical foundations for information representation and constraint specification

Research accomplished at the Knowledge Based Systems Laboratory of the Department of Industrial Engineering at Texas A&M University is described. Outlined here are the theoretical foundations necessary to construct a Neutral Information Representation Scheme (NIRS), which will allow for automated data transfer and translation between model languages, procedural programming languages, database languages, transaction and process languages, and knowledge representation and reasoning control languages for information system specification.

Menzel, Christopher P.↗
DOE OSTI2025

Accurate segmentation of localized corrosion in structural alloys via deep learning

This study presents a deep learning-based approach for the automated segmentation of corrosion damage in scanning electron microscopy (SEM) images. The proposed method enables rapid and accurate segmentation of corrosion features in these SEM images, making it highly suitable for real-time applications such as automated microscopy. Specifically, a dedicated corrosion segmentation database tailored for this task is constructed. The newly constructed dataset, alongside data from two public databases, are employed to jointly train a deep learning-based model modified with a texture refinement module. Compared to the same model without the texture refinement module, the refined model substantially enhances the efficacy and efficiency of corrosion segmentation. Furthermore, the methodology developed here is extendable to segmentation tasks for other materials with similar resolution, texture, and contrast characteristics, thereby paving the way for accelerated and automated analysis in corrosion science and beyond.

Artificial Intelligence↗
DOE OSTI2024

Maximizing Efficiency and Quality: Leveraging Automated Testing for Laboratory Commissioning

The traditional commissioning process uses sampling to select equipment for functional acceptance testing when large quantities of equipment are present. Although this approach is generally effective in identifying wide-spread issues, it has several shortcomings: it fails to evaluate equipment not included in the sample, provides only a one-time validation of equipment operation, and the standard documentation is a simple checklist of pass/fail questions. During the construction and commissioning process of the new Research and Innovation Laboratory (RAIL) in Golden, CO, the National Renewable Energy Laboratory team engaged Group14 Engineering to implement a Connected Commissioning process using fault detection and diagnostic software for automated functional acceptance testing. This presentation highlights the advantages offered by automated functional testing in this critical laboratory setting: (1) sampling 100% of BAS-connected equipment during functional testing, (2) testing results backed by data beyond the traditional pass/fail checklist, and (3) an automated test process that can be regularly executed by the building management team for ongoing commissioning throughout the life of the building. The presentation will also cover technical challenges associated with Connected Commissioning and the important conversations with key stakeholders that need to occur well before functional acceptance testing in order to successfully implement the automated testing processes.

automated testing↗
DOE OSTI2024

Automated Calibration for Rapid Optical Spectroscopy Sensor Development for Online Monitoring

An automated platform has been developed to assist researchers in the rapid development of optical spectroscopy sensors to quantify species from spectral data. This platform performs calibration and validation measurements simultaneously. Real-time, in situ monitoring of complex systems through optical spectroscopy has been shown to be a useful tool; however, building calibration models requires development time, which can be a limiting factor in the case of radiological or otherwise hazardous systems. While calibration time can be reduced through optimized design of experiments, this study approached the challenge differently through automation. The ATLAS (Automated Transient Learning for Applied Sensors) platform used pneumatic control of stock solutions to cycle flow profiles through desired calibration concentrations for multivariate model construction. Additionally, the transients between desired concentrations based on flow calculations were used as validation measurements to understand model predictive capabilities. This automated approach yielded an incredible 76% reduction in model development time and a 60% reduction in sample volume versus estimated manual sample preparation and static measurements. The ATLAS system was demonstrated on two systems: a three-lanthanide system with Pr/Nd/Ho representing a use case with significant overlap or interference between analyte signatures and an alternate system containing Pr/Nd/Ni to demonstrate a use case in which broad-band corrosion species signatures interfered with more distinct lanthanide absorbance profiles. Both systems resulted in strong model prediction performance (RMSEP < 9%). Lastly, ATLAS was demonstrated as a tool to simulate process monitoring scenarios (e.g., column separation) in which models can be further optimized to account for day-to-day changes as necessary (e.g., baseline correction). Ultimately, ATLAS offers a vital tool to rapidly screen monitoring methods, investigate sensor fusion, and explore more complex systems (i.e., larger numbers of species).

47 OTHER INSTRUMENTATION↗
NASA NTRS1992

Development of a machine vision system for automated structural assembly

Research is being conducted at the LaRC to develop a telerobotic assembly system designed to construct large space truss structures. This research program was initiated within the past several years, and a ground-based test-bed was developed to evaluate and expand the state of the art. Test-bed operations currently use predetermined ('taught') points for truss structural assembly. Total dependence on the use of taught points for joint receptacle capture and strut installation is neither robust nor reliable enough for space operations. Therefore, a machine vision sensor guidance system is being developed to locate and guide the robot to a passive target mounted on the truss joint receptacle. The vision system hardware includes a miniature video camera, passive targets mounted on the joint receptacles, target illumination hardware, and an image processing system. Discrimination of the target from background clutter is accomplished through standard digital processing techniques. Once the target is identified, a pose estimation algorithm is invoked to determine the location, in three-dimensional space, of the target relative to the robots end-effector. Preliminary test results of the vision system in the Automated Structural Assembly Laboratory with a range of lighting and background conditions indicate that it is fully capable of successfully identifying joint receptacle targets throughout the required operational range. Controlled optical bench test results indicate that the system can also provide the pose estimation accuracy to define the target position.

Sydow, P. Daniel↗
NASA NTRS1978

Application of the informational reference system OZhUR to the automated processing of data from satellites of the Kosmos series

The structure and potential of the information reference system OZhUR designed for the automated data processing systems of scientific space vehicles (SV) is considered. The system OZhUR ensures control of the extraction phase of processing with respect to a concrete SV and the exchange of data between phases.The practical application of the system OZhUR is exemplified in the construction of a data processing system for satellites of the Cosmos series. As a result of automating the operations of exchange and control, the volume of manual preparation of data is significantly reduced, and there is no longer any need for individual logs which fix the status of data processing. The system Ozhur is included in the automated data processing system Nauka which is realized in language PL-1 in a binary one-address system one-state (BOS OS) electronic computer.

Pokras, V. M.↗
NASA NTRS2003

Intelligent Machines in the 21st Century: Automating the Processes of Inference and Inquiry

The last century saw the application of Boolean algebra toward the construction of computing machines, which work by applying logical transformations to information contained in their memory. The development of information theory and the generalization of Boolean algebra to Bayesian inference have enabled these computing machines. in the last quarter of the twentieth century, to be endowed with the ability to learn by making inferences from data. This revolution is just beginning as new computational techniques continue to make difficult problems more accessible. However, modern intelligent machines work by inferring knowledge using only their pre-programmed prior knowledge and the data provided. They lack the ability to ask questions, or request data that would aid their inferences. Recent advances in understanding the foundations of probability theory have revealed implications for areas other than logic. Of relevance to intelligent machines, we identified the algebra of questions as the free distributive algebra, which now allows us to work with questions in a way analogous to that which Boolean algebra enables us to work with logical statements. In this paper we describe this logic of inference and inquiry using the mathematics of partially ordered sets and the scaffolding of lattice theory, discuss the far-reaching implications of the methodology, and demonstrate its application with current examples in machine learning. Automation of both inference and inquiry promises to allow robots to perform science in the far reaches of our solar system and in other star systems by enabling them to not only make inferences from data, but also decide which question to ask, experiment to perform, or measurement to take given what they have learned and what they are designed to understand.

Knuth, Kevin H.↗
NASA NTRS1992

Towards a theory of automated elliptic mesh generation

The theory of elliptic mesh generation is reviewed and the fundamental problem of constructing computational space is discussed. It is argued that the construction of computational space is an NP-Complete problem and therefore requires a nonstandard approach for its solution. This leads to the development of graph-theoretic, combinatorial optimization and integer programming algorithms. Methods for the construction of two dimensional computational space are presented.

Cordova, J. Q.↗
NASA NTRS2014

Aviation Safety Risk Modeling: Lessons Learned From Multiple Knowledge Elicitation Sessions

Aviation safety risk modeling has elements of both art and science. In a complex domain, such as the National Airspace System (NAS), it is essential that knowledge elicitation (KE) sessions with domain experts be performed to facilitate the making of plausible inferences about the possible impacts of future technologies and procedures. This study discusses lessons learned throughout the multiple KE sessions held with domain experts to construct probabilistic safety risk models for a Loss of Control Accident Framework (LOCAF), FLightdeck Automation Problems (FLAP), and Runway Incursion (RI) mishap scenarios. The intent of these safety risk models is to support a portfolio analysis of NASA's Aviation Safety Program (AvSP). These models use the flexible, probabilistic approach of Bayesian Belief Networks (BBNs) and influence diagrams to model the complex interactions of aviation system risk factors. Each KE session had a different set of experts with diverse expertise, such as pilot, air traffic controller, certification, and/or human factors knowledge that was elicited to construct a composite, systems-level risk model. There were numerous "lessons learned" from these KE sessions that deal with behavioral aggregation, conditional probability modeling, object-oriented construction, interpretation of the safety risk results, and model verification/validation that are presented in this paper.

Luxhoj, J. T.↗
DOE OSTI2024

Development and Validation of Home Comfort System for Total Performance Deficiency/Fault Detection and Optimal Comfort Control

In this project, we developed and tested a learning-based home thermal model that facilitates the operation of a model predictive control (MPC)-based optimization agent and an automated fault detection and diagnosis (AFDD) agent. The home thermal model was constructed using a two-node resistor-capacitor model. Moreover, two accompanying parameter identification methods were introduced, least-squares and optimization. Based on the home thermal model, the MPC-based optimization agent was developed to optimize residential HVAC operation. Using two FDD methods, the AFDD agent was constructed to detect and diagnose two prevalent residential AC faults, airflow reduction and refrigerant undercharge. The home thermal model, along with the MPC-based optimization agent and AFDD agent, were tested at the Norman Test House, Miami Test House, Pacific Northwest National Laboratory (PNNL) Test House A, and PNNL Test House B. Finally, they were also field tested in nine demonstration homes with real occupants.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1972

SLAR image interpretation keys for geographic analysis

A means for side-looking airborne radar (SLAR) imagery to become a more widely used data source in geoscience and agriculture is suggested by providing interpretation keys as an easily implemented interpretation model. Interpretation problems faced by the researcher wishing to employ SLAR are specifically described, and the use of various types of image interpretation keys to overcome these problems is suggested. With examples drawn from agriculture and vegetation mapping, direct and associate dichotomous image interpretation keys are discussed and methods of constructing keys are outlined. Initial testing of the keys, key-based automated decision rules, and the role of the keys in an information system for agriculture are developed.

Coiner, J. C.↗
NASA NTRS1989

OFMTutor: An operator function model intelligent tutoring system

The design, implementation, and evaluation of an Operator Function Model intelligent tutoring system (OFMTutor) is presented. OFMTutor is intended to provide intelligent tutoring in the context of complex dynamic systems for which an operator function model (OFM) can be constructed. The human operator's role in such complex, dynamic, and highly automated systems is that of a supervisory controller whose primary responsibilities are routine monitoring and fine-tuning of system parameters and occasional compensation for system abnormalities. The automated systems must support the human operator. One potentially useful form of support is the use of intelligent tutoring systems to teach the operator about the system and how to function within that system. Previous research on intelligent tutoring systems (ITS) is considered. The proposed design for OFMTutor is presented, and an experimental evaluation is described.

Jones, Patricia M.↗
NASA NTRS1991

Building the Scientific Modeling Assistant: An interactive environment for specialized software design

The construction of scientific software models is an integral part of doing science, both within NASA and within the scientific community at large. Typically, model-building is a time-intensive and painstaking process, involving the design of very large, complex computer programs. Despite the considerable expenditure of resources involved, completed scientific models cannot easily be distributed and shared with the larger scientific community due to the low-level, idiosyncratic nature of the implemented code. To address this problem, we have initiated a research project aimed at constructing a software tool called the Scientific Modeling Assistant. This tool provides automated assistance to the scientist in developing, using, and sharing software models. We describe the Scientific Modeling Assistant, and also touch on some human-machine interaction issues relevant to building a successful tool of this type.

Keller, Richard M.↗