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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Machine learning in motion control

The existing methodologies for robot programming originate primarily from robotic applications to manufacturing, where uncertainties of the robots and their task environment may be minimized by repeated off-line modeling and identification. In space application of robots, however, a higher degree of automation is required for robot programming because of the desire of minimizing the human intervention. We discuss a new paradigm of robotic programming which is based on the concept of machine learning. The goal is to let robots practice tasks by themselves and the operational data are used to automatically improve their motion performance. The underlying mathematical problem is to solve the problem of dynamical inverse by iterative methods. One of the key questions is how to ensure the convergence of the iterative process. There have been a few small steps taken into this important approach to robot programming. We give a representative result on the convergence problem.

Su, Renjeng↗
NASA NTRS2019

Using Machine Learning to Predict Core Sizes of High-Efficiency Turbofan Engines

With the rise in big data and analytics, machine learning is transforming many industries. It is being increasingly employed to solve a wide range of complex problems, producing autonomous systems that support human decision-making. For the aircraft engine industry, machine learning of historical and existing engine data could provide insights that help drive for better engine design. This work explored the application of machine learning to engine preliminary design. Engine core-size prediction was chosen for the first study because of its relative simplicity in terms of number of input variables required (only three). Specifically, machine-learning predictive tools were developed for turbofan engine core-size prediction, using publicly available data of two hundred manufactured engines and engines that were studied previously in NASA aeronautics projects. The prediction results of these models show that, by bringing together big data, robust machine-learning algorithms and automation, a machine learning-based predictive model can be an effective tool for turbofan engine core-size prediction. The promising results of this first study paves the way for further exploration of the use of machine learning for aircraft engine preliminary design.

Tong, Michael T.↗
DOE OSTI2024

L-PBF High-Throughput Data Pipeline Approach for Multi-modal Integration

Abstract Metal-based additive manufacturing requires active monitoring solutions for assessing part quality. Multiple sensors and data streams, however, generate large heterogeneous data sets that are impractical for manual assessment and characterization. In this work, an automated pipeline is developed that enables feature extraction from high-speed camera video and multi-modal data analysis. The framework removes the need for manual assessment through the utilization of deep learning techniques and training models in a weakly supervised paradigm. We demonstrate this pipeline’s capability over 700,000 high-speed camera frames. The pipeline successfully extracts melt pool and spatter geometries and links them to corresponding pyrometry, radiography, and processparameter information. 715 individual prints are examined to reveal melt pool areas that exceeds 0.07 mm 2 and pyrometry signal over a threshold (375 pyrometry units) were more likely to have defects. These automated processes enable massive throughput of characterization techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Building Energy Analysis of Manufactured and Multifamily Housing Types in Juneau, Alaska

This report details the results of building energy modeling analysis evaluating the potential energy savings, economic outcomes, and grid-level electricity reduction associated with cold climate air source heat pump (ccASHP) adoption across multifamily and manufactured housing (MMFH) building typologies in the City and Borough of Juneau (CBJ). Three building archetypes were evaluated: multifamily 4-plex apartments, multifamily 8-plex apartments, and manufactured housing units. Building energy models were developed using OpenStudio-HPXML and calibrated to actual utility consumption data and local meteorological data from the Juneau International Airport weather station using an automated calibration tool following the BPI-2400-S-2015 v.2 standard for model calibration. Occupant behaviors present the greatest variability in successful calibrations. Calibrated models were benchmarked against a baseline electric resistance heating condition, with the selected ccASHP modeled as the retrofit condition and typical meteorological year weather data for all results generation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1975

Sikorsky interactive graphics surface design/manufacturing system

An interactive graphics system conceived to be used in the design, analysis, and manufacturing of aircraft components with free form surfaces was described. In addition to the basic surface definition and viewing capabilities inherent in such a system, numerous other features are present: surface editing, automated smoothing of control curves, variable milling patch boundary definitions, surface intersection definition and viewing, automatic creation of true offset surfaces, digitizer and drafting machine interfaces, and cutter path optimization. Documented costs and time savings of better than six to one are being realized with this system. The system was written in FORTRAN and GSP for use on IBM 2250 CRT's in conjunction with an IBM 370/158 computer.

Robbins, R.↗
NASA NTRS1977

Solar photovoltaics - An aerospace technology

Specific problems affecting the development of low-cost silicon solar array power sources are discussed, taking into account the potential of realizing less than $0.50/per peak watt of silicon solar array technology. A utilization of less expensive processes for the manufacture of pure silicon and more economical procedures of silicon crystal and wafer production appear desirable. Attention is given to a sheet growth process example and a concept of pulsed processing for automated cell production.

Goldsmith, J. V.↗
NASA NTRS1978

Phase 1 of the automated array assembly task of the low cost silicon solar array project

The results of a study of process variables and solar cell variables are presented. Interactions between variables and their effects upon control ranges of the variables are identified. The results of a cost analysis for manufacturing solar cells are discussed. The cost analysis includes a sensitivity analysis of a number of cost factors.

Pryor, R. A.↗
NASA NTRS1982

Technology assessment of advanced automation for space missions

Six general classes of technology requirements derived during the mission definition phase of the study were identified as having maximum importance and urgency, including autonomous world model based information systems, learning and hypothesis formation, natural language and other man-machine communication, space manufacturing, teleoperators and robot systems, and computer science and technology.

Source record↗
DOE OSTI2022

Design optimization of integrated cooling inserts in modular Fischer-Tropsch reactors

Sustainable production of liquid fuels and feedstocks from atmospheric CO 2 through carbon recycling technologies is necessary to broaden decarbonization efforts and further reduce global emissions. Fischer–Tropsch (FT) reactors can address this challenge by providing storable, high-value liquid hydrocarbon fuels and feedstocks from syngas generated through reductive CO 2 utilization. FT technology, however, is most cost effective at large-scale, fixed-site plants and does not effectively address the smaller, globally distributed CO 2 point sources. Alternatively, smaller, modular reactors can be composed together to the specific scale of the emission source, yielding a flexible solution that enables more widespread deployment. In these modular reactors, thermal management using a finned cooling insert embedded within the catalyst matrix is critical to maintaining the performance and viability. Thus, in this work, topology optimization is used to determine the cooling insert geometry that maximizes reactor productivity while preventing auto-thermal runaway. Optimal designs are generated for varying number of constituent fins and over a range of maximum operating temperatures. Constraints including minimum feature length-scales and prescribed cooling insert material are imposed on the designs to enhance manufacturability. The impact of design features such as insert tapering and increased length scale hierarchy is automatically revealed by the systematic design framework employed. Here, this approach thus generates novel optimal geometries while automating, accelerating, and enhancing the design process compared to traditional heuristic approaches for cooling insert design in modular FT reactors.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Rapid Construction of Validated Chemistry Models for Advanced Biofuels (Co-Optima Final Report)

Computer methods were developed and demonstrated that make it possible to predict the combustion and pyrolysis chemistry of proposed biofuels, even before the biofuels are ever manufactured or experimentally tested. The methods are based on first-principles calculations of reaction rates and equilibria. A large number of complicated calculations are required, so we developed a computer workflow that automates many of the steps. With the chemical structure of the biofuel and the system conditions (temperature, pressure, compositions, etc.) as the input, the computer methods can construct a detailed kinetic model with refined parameters without intense human intervention. The automation of model construction makes it practical for a single engineer to make the predictions in a reasonable time period. The accuracy of the computer predictions was tested by measuring the time-profiles of various reaction intermediates (carbon monoxide, carbon dioxide, water, formaldehyde, methane, and ethylene) formed as the biofuels pyrolyze or ignite using sophisticated laser shock tube methods. Several biofuels, including methyl propyl ether, cyclopentanone, butyl acetate isomers, etc., were carefully studied to demonstrate the validity of the proposed computational and experimental methodology. This research project opens up the possibility for assessing some proposed biofuels on the computer without expensive experimental campaigns. The new computer methods are open source and well-documented, allowing a knowledgeable modeler to easily access the developed methods and implement them in their work routine. Moreover, they are also convenient and powerful, promising for developing the fuel chemistry models needed for use in engine simulators, facilitating co-optimization of new engine designs with new fuels.

09 BIOMASS FUELS↗
NASA NTRS1992

Test and analysis results for composite transport fuselage and wing structures

Automated tow placement (ATP) and stitching of dry textile composite preforms followed by resin transfer molding (RTM) are being investigated by researchers at NASA LaRC and Douglas Aircraft Company as cost-effective manufacturing processes for obtaining damage tolerant fuselage and wing structures for transport aircraft. The Douglas work is being performed under a NASA contract entitled 'Innovative Composites Aircraft Primary Structures (ICAPS)'. Data are presented in this paper to assess the damage tolerance of ATP and RTM fuselage elements with stitched-on stiffeners from compression tests of impacted three-J-stiffened panels and from stiffener pull-off tests. Data are also presented to assess the damage tolerance of RTM wing elements which had stitched skin and stiffeners from impacted single stiffener and three blade-stiffened compression tests and stiffener pull-off tests.

Deaton, Jerry W.↗
NASA NTRS1993

Third NASA Advanced Composites Technology Conference, volume 1, part 2

This document is a compilation of papers presented at the Third NASA Advanced Composites Technology (ACT) Conference held at Long Beach, California, 8-11 June 1992. The ACT Program is a major multi-year research initiative to achieve a national goal of technology readiness before the end of the decade. Conference papers recorded results of research in the ACT Program in the specific areas of automated fiber placement, resin transfer molding, textile preforms, and stitching as these processes influence design, performance, and cost of composites in aircraft structures. Papers sponsored by the Department of Defense on the Design and Manufacturing of Low Cost Composites (DMLCC) are also included in Volume 2 of this document.

Davis, John G., Jr.↗
NASA NTRS1993

Third NASA Advanced Composites Technology Conference, volume 1, part 1

This document is a compilation of papers presented at the Third NASA Advanced Composites Technology (ACT) Conference. The ACT Program is a major multi-year research initiative to achieve a national goal of technology readiness before the end of the decade. Conference papers recorded results of research in the ACT Program in the specific areas of automated fiber placement, resin transfer molding, textile preforms, and stitching as these processes influence design, performance, and cost of composites in aircraft structures. Papers sponsored by the Department of Defense on the Design and Manufacturing of Low Cost Composites (DMLCC) are also included in Volume 2 of this document.

Davis, John G., Jr.↗
DOE OSTI2025

Machine Learning for Automated Weld Quality Monitoring and Control

Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Machine Learning for Automated Weld Quality Monitoring and Control

Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.

42 ENGINEERING↗
NASA NTRS1982

Glasses for Solar-Cell Arrays

Report presents data on glass for encapsulation of solar-cell arrays, with special emphasis on materials and processes for automated high-volume production of low-cost arrays. Commercial suppliers of glass are listed. Factors that affect the cost of glass are examined: type (sheet, float, or plate), formulation, and energy consumed in manufacturing.

Bouquet, F. L.↗
NASA NTRS1993

A widely adaptable habitat construction system utilizing space resources

This study suggests that the cost of providing accommodations for various manned activities in space may be reduced by the extensive use of resources that are commonly found throughout the solar system. Several concepts are proposed for converting these resources into simple products with many uses. Concrete is already being considered as a possible moonbase material. Manufacturing equipment should be as small and simple as possible, which leads to the idea of molding it into miniature modules that can be produced and assembled in large numbers to create any conceivable shape. Automated equipment could build up complex structures by laying down layer after layer in a process resembling stereolithography. These tiny concrete blocks handle compression loads and provide a barrier to harmful radiation. They are joined by a web of tension members that could be made of wire or fiber-reinforced plastic. The finished structure becomes air-tight with the addition of a flexible liner. Wire can be made from the iron modules found in lunar soil. In addition to its structural role, a relatively simple apparatus can bend and weld it into countless products like chairs and shelving that would otherwise need to be supplied from Earth. Wire woven into a loose blanket could be an effective micrometeoroid shield, tiny wire compression beams could be assembled into larger beams which in turn form larger beams to create very large space-frame structures. A technology developed with lunar materials could be applied to the moons of Mars or the asteroids. To illustrate its usefulness several designs for free-flying habitats are presented. They begin with a minimal self-contained living unit called the Cubicle. It may be multiplied into clusters called Condos. These are shown in a rotating tether configuration that provides a substitute for gravity. The miniature block proposal is compared with an alternate design based on larger triangular components and a tetrahedral geometry. The overall concept may be expanded to envision city-sized self-sufficient environments where humans could confortably live their entire lives. One such proposal is the Hive. It is configured around a unique sunlight collection system that could provide all its energy needs and that could be scaled up to compensate for the reduced solar intensity at greater distances from the sun. Its outer perimeter consists of a cylindrical section mated to two conical end walls that taper inwards toward a small aperture at the center of rotation. Light collected by two huge mirrors of unusual design enters the aperture and is redirected to the inside of the cylinder. The conical end walls are shielded from direct sunlight and are designed to radiate heat into space. They are lined with air ducts that passively recirculate the atmosphere while extracting moisture by condensation. Although there is no immediate demand for spacecraft on this scale, their consideration can influence even the earliest stages of the development process.

Wykes, Harry B.↗
NASA NTRS1984

Robotic System

A complicated design project, successfully carried out by New York manufacturing consultant with help from NERAC, Inc., resulted in new type robotic system being marketed for industrial use. Consultant Robert Price, operating at E.S.I, Inc. in Albany, NY, sought help from NERAC to develop an automated tool for deburring the inside of 8 inch breech ring assemblies for howitzers produced by Watervliet Arsenal. NERAC conducted a search of the NASA data base and six others. From information supplied, Price designed a system consisting of a standard industrial robot arm, with a specially engineered six-axis deburring tool fitted to it. A microcomputer and computer program direct the tool on its path through the breech ring. E.S.I. markets the system to aerospace and metal cutting industries for deburring, drilling, routing and refining machined parts.

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