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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Analytical modeling and sensor monitoring for optimal processing of polymeric composite material systems

Process simulation models and cure monitoring sensors are discussed for use in optimal processing of fiber-reinforced composites. Analytical models relate the specified temperature and pressure cure cycle to the thermal, chemical, and physical processes occurring in the composite during consolidation and cure. Frequency-dependent electromagnetic sensing (FDEMS) is described as an in situ sensor for monitoring the composite curing process and for verification of process simulation models. A model for resin transfer molding of textile composites is used to illustrate the predictive capabilities of a process simulation model. The model is used to calculate the resin infiltration time, fiber volume fraction, resin viscosity, and resin degree of cure. Results of the model are compared with in situ FDEMS measurements.

Loos, Alfred C.↗
NASA NTRS1987

Spacelab Data Processing Facility (SLDPF) quality assurance expert systems development

Spacelab Data Processing Facility (SLDPF) expert system prototypes were developed to assist in the quality assurance of Spacelab and/or Attached Shuttle Payload (ASP) processed telemetry data. The SLDPF functions include the capturing, quality monitoring, processing, accounting, and forwarding of mission data to various user facilities. Prototypes for the two SLDPF functional elements, the Spacelab Output Processing System and the Spacelab Input Processing Element, are described. The prototypes have produced beneficial results including an increase in analyst productivity, a decrease in the burden of tedious analyses, the consistent evaluation of data, and the providing of concise historical records.

Kelly, Angelita C.↗
NASA NTRS1991

Development of silicon nitride rotors for the ATTAP program at Garrett Ceramic Components

The development and fabrication of reliable high temperature-high strength silicon nitride rotors by Garrett Ceramic Components (GCC) for the Advanced Turbine Technology Applications Project (ATTAP) is discussed. GCC's progress will be presented, including mechanical properties characterization, in-process monitoring development, and extensive NDE analysis. The current status of material, process, and part properties of the rotors being developed will be compared to properties required for implementation and successful operation of advanced gas turbine engines at 2500 F.

Busovne, B. J., Jr.↗
NASA NTRS2008

Gold Nanoparticle Labels Amplify Ellipsometric Signals

The ellipsometric method reported in the immediately preceding article was developed in conjunction with a method of using gold nanoparticles as labels on biomolecules that one seeks to detect. The purpose of the labeling is to exploit the optical properties of the gold nanoparticles in order to amplify the measurable ellipsometric effects and thereby to enable ultrasensitive detection of the labeled biomolecules without need to develop more-complex ellipsometric instrumentation. The colorimetric, polarization, light-scattering, and other optical properties of nanoparticles depend on their sizes and shapes. In the present method, these size-and-shape-dependent properties are used to magnify the polarization of scattered light and the diattenuation and retardance of signals derived from ellipsometry. The size-and-shape-dependent optical properties of the nanoparticles make it possible to interrogate the nanoparticles by use of light of various wavelengths, as appropriate, to optimally detect particles of a specific type at high sensitivity. Hence, by incorporating gold nanoparticles bound to biomolecules as primary or secondary labels, the performance of ellipsometry as a means of detecting the biomolecules can be improved. The use of gold nanoparticles as labels in ellipsometry has been found to afford sensitivity that equals or exceeds the sensitivity achieved by use of fluorescence-based methods. Potential applications for ellipsometric detection of gold nanoparticle-labeled biomolecules include monitoring molecules of interest in biological samples, in-vitro diagnostics, process monitoring, general environmental monitoring, and detection of biohazards.

Venkatasubbarao, Srivatsa↗
DOE OSTI2024

AOI [1] Advanced Manufacturing of Ceramic Anchors with Embedded Sensors for Process and Health Monitoring of Coal Boilers

Researchers at West Virginia University (WVU) developed methods to fabricate and test ceramic anchors with an embedded sensor technology for monitoring the health and processing conditions within pulverized coal (PC) and fluidized-bed combustion (FBC) boiler systems. The technology included the development of advanced manufacturing processes for 2D/3D printing electroceramic (conductive ceramic) sensor designs within the ceramic anchor microstructure during the manufacturing process. This advanced manufacturing process would allow for the precise control of local microstructure and composition in order to engineer layer-by-layer any protective and electrically active materials within the refractory anchor. This 3D printing technology would permit the rapid and controlled design of the refractory microstructure and embedded sensor design throughout the volume of the ceramic anchor. The work also included a method to interconnect the sensors to boiler shell through the anchor clamp, where the sensor signals will be processed by low-power electronics and transmitted wirelessly to a central processing hub. The end-goal of the program was to produce a ceramic anchor sensor system which would be ready for implementation within a coal boiler, and/or other similar refractory liner systems (such as that in the glass and metal manufacturing areas). The project objectives were to: 1) Define the chemical and microstructural stability, in addition to the electrical properties, of oxide and non-oxide ceramic composites to be embedded within the ceramic anchor compositions that may operate up to 1400ºC; 2) Develop and implement the 2D/3D printing technology to pattern and control the microstructure of the ceramic anchor and embedded sensor circuits; 3) Develop an interconnect technology which will permit easy installation of the ceramic anchors and signal collection at the boiler shell; 4) Develop low power analog electronics and wireless communication hardware to efficiently collect the sensor signal at each processing unit and transmit data to a central hub for data analysis; 5) Demonstrate the smart ceramic anchor system for temperature and liner fracture within a high-temperature processing unit, such as a boiler furnace or glass melting furnace floor/wall liner.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS1989

SHARP: A multi-mission AI system for spacecraft telemetry monitoring and diagnosis

The Spacecraft Health Automated Reasoning Prototype (SHARP) is a system designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. Telecommunications link analysis of the Voyager II spacecraft is the initial focus for the SHARP system demonstration which will occur during Voyager's encounter with the planet Neptune in August, 1989, in parallel with real-time Voyager operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real-time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. A brief introduction is given to the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory. The current method of operation for monitoring the Voyager Telecommunications subsystem is described, and the difficulties associated with the existing technology are highlighted. The approach taken in the SHARP system to overcome the current limitations is also described, as well as both the conventional and artificial intelligence solutions developed in SHARP.

Lawson, Denise L.↗
NASA NTRS1989

SHARP: A multi-mission artificial intelligence system for spacecraft telemetry monitoring and diagnosis

The Spacecraft Health Automated Reasoning Prototype (SHARP) is a system designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. Telecommunications link analysis of the Voyager 2 spacecraft is the initial focus for the SHARP system demonstration which will occur during Voyager's encounter with the planet Neptune in August, 1989, in parallel with real time Voyager operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. A brief introduction is given to the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory. The current method of operation for monitoring the Voyager Telecommunications subsystem is described, and the difficulties associated with the existing technology are highlighted. The approach taken in the SHARP system to overcome the current limitations is also described, as well as both the conventional and artificial intelligence solutions developed in SHARP.

Lawson, Denise L.↗
NASA NTRS1989

SHARP - A multi-mission AI system for spacecraft telemetry monitoring and diagnosis

The Spacecraft Health Automated Reasoning Prototype (SHARP) is a system designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. Telecommunications link analysis of the Voyager II spacecraft is the initial focus for the SHARP system demonstration which will occur during Voyager's encounter with the planet Neptune in August, 1989, in parallel with real-time Voyager operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real-time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. A brief introduction is given to the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory. The current method of operation for monitoring the Voyager Telecommunications subsystem is described, and the difficulties associated with the existing technology are highlighted. The approach taken in the SHARP system to overcome the current limitations is also described, as well as both the conventional and artificial intelligence solutions developed in SHARP.

Lawson, Denise L.↗
DOE OSTI2024

Performance Testing of a Moving-Bed Gasifier Using Coal, Biomass, and Waste Plastic Blends with Washed and Unwashed Legacy Coals and Other Waste Fuels to Generate White Hydrogen

The objective of this effort, primarily funded by the United States Department of Energy (DOE), and led by the Electric Power Research Institute, Inc. (EPRI), with support by Hamilton Maurer International (HMI) and Sotacarbo S.p.A. (Sotacarbo), has been to qualify coal, biomass, and plastic waste blends based on performance testing of selected fuel pellet compositions in a pilot-scale updraft moving-bed (UDMB) gasifier. The testing provided relevant data to advance the commercial-scale design of the moving-bed gasifier to be able to successfully use these feedstocks to produce hydrogen. In particular, the effects of waste plastics on feedstock development (i.e., blending and pelletizing) and the resulting products (i.e., syngas compositions, organic condensate production, and ash characteristics) are the focus. The gasifier used for testing is HMI’s moving-bed gasifier, which has been proven capable of gasifying nearly all coal ranks. It has also shown the ability in prior testing work to gasify wood chips (biomass). However, mixtures of these fuels with plastic wastes have not been prepared and gasified together. The three feedstocks were densified and pelletized by California Pellet Mill (CPM) to meet the feedstock size required by Sotacarbo’s 30mm ID UDMB gasifier, under contract to HMI. The technical tasks and results from this two-year research project included: (1) Feed Procurement and Preparation: Nine different tri-fuel pellets were prepared from varying compositions of fresh mined PRB coal, corn stover biomass, and car fluff waste plastics. Tri-fuel pellets were produced by CPM and shipped to Sotacarbo’s test facility in Carbonia, Sardinia, Italy. (2) Test Plan Development: A test plan was created to define the test runs to be performed. The test plan detailed the different UDMB gasification tests to be performed in Sotacarbo’s 12-inch ID pilot scale gasifier, the process monitoring instrumentation used, and the extractive samples recovered for analysis of the total gasification process mass and energy balance. (3) Gasifier Testing: Nine different gasification runs were performed in the pilot-scale gasifier at Sotacarbo using nine different fuel feedstock compositions generated from varying mixtures of PRB coal, biomass, and plastic wastes. The testing generated performance data on gasification reaction efficiency and performance, yielding relevant data for models used to scale up the gasifier design. This task also included work to refurbish and reassemble the pilot gasifier at Sotacarbo and perform a baseline 100% PRB coal run. (4) Data Analysis and Reporting: Review of the data, determination of figures of merit, and interpretation of the results are reported in the project’s final report, published in March 2024. The results show that all tri-fuel pellets gasified well and maintained structural integrity throughout the gasification process. The syngas generated can be shifted to hydrogen by using commercial syngas shifting technologies. (5) High Fidelity computational fluid dynamics (CFD) Simulation: The National Energy Technology Laboratory (NETL) team performed CFD simulations of the UDMB gasifier for two of the tri-fuel pellets gasified in Sotacarbo’s pilot scale gasifier. The kinetic mechanisms for the pyrolysis of each constituent, PRB coal, corn stover biomass, and waste plastics are based on thermogravimetric analysis performed by Sotacarbo. The gasification model was validated by comparing the predicted syngas composition at the exit of the gasifier with the measured syngas composition. In addition, the reactor’s measured internal temperature profile agreed well with the predicted internal reactor temperature profile. These results validate that the model can be used to predict the performance of the updraft moving bed gasifier for different feedstocks and operating conditions. This paper summarizes the results of the completed work in which the pelletizing procedure was validated to ensure the viability of the tri-fuel pellets for the gasification runs performed at Sotacarbo’s 30 mm UDMB gasifier. The gasification performance data from this series of nine runs will enable modeling of a full-scale HMI industrial scale gasifier supporting both combined heat and power, and Hydrogen production from coal (both fresh mined and legacy) combined with various biomass and waste plastics. Additionally, plans and progress on a follow-up project, being executed by the same project team, will be presented. In this project, a total of twenty (20) different feedstocks are being prepared from varying compositions of biomass (both woody biomass and corn stover) with a mixture of legacy coal waste, plastic waste, and refuse-derived fuel (RDF). The testing will provide information on gasification reaction efficiency/performance, yielding relevant data for models used to scale up the gasifier design to 50 megawatt electric (MWe) (equivalent hydrogen production). Tests will also be performed on a bench-scale fluidized-bed gasifier for comparison purposes. The results of this testing will be used to specify the range of feedstock blends that can be successfully gasified as well as quantify gasifier outputs based on specific blends.

08 HYDROGEN↗
NASA NTRS1989

Digital imaging technology assessment: Digital document storage project

An ongoing technical assessment and requirements definition project is examining the potential role of digital imaging technology at NASA's STI facility. The focus is on the basic components of imaging technology in today's marketplace as well as the components anticipated in the near future. Presented is a requirement specification for a prototype project, an initial examination of current image processing at the STI facility, and an initial summary of image processing projects at other sites. Operational imaging systems incorporate scanners, optical storage, high resolution monitors, processing nodes, magnetic storage, jukeboxes, specialized boards, optical character recognition gear, pixel addressable printers, communications, and complex software processes.

Source record↗
NASA NTRS1994

Concept of using a benchmark part to evaluate rapid prototype processes

A conceptual benchmark part for guiding manufacturers and users of rapid prototyping technologies is proposed. This is based on a need to have some tool to evaluate the development of this technology and to assist the user in judiciously selecting a process. The benchmark part is designed to have unique product details and features. The extent to which a rapid prototyping process can reproduce these features becomes a measure of the capability of the process. Since rapid prototyping is a dynamic technology, this benchmark part should be used to continuously monitor process capability of existing and developing technologies. Development of this benchmark part is, therefore, based on an understanding of the properties required from prototypes and characteristics of various rapid prototyping processes and measuring equipment that is used for evaluation.

Cariapa, Vikram↗
NASA NTRS2015

Multiscale and Multiphysics Modeling of Additive Manufacturing of Advanced Materials

The objective of this proposed project is to research and develop a prediction tool for advanced additive manufacturing (AAM) processes for advanced materials and develop experimental methods to provide fundamental properties and establish validation data. Aircraft structures and engines demand materials that are stronger, useable at much higher temperatures, provide less acoustic transmission, and enable more aeroelastic tailoring than those currently used. Significant improvements in properties can only be achieved by processing the materials under nonequilibrium conditions, such as AAM processes. AAM processes encompass a class of processes that use a focused heat source to create a melt pool on a substrate. Examples include Electron Beam Freeform Fabrication and Direct Metal Deposition. These types of additive processes enable fabrication of parts directly from CAD drawings. To achieve the desired material properties and geometries of the final structure, assessing the impact of process parameters and predicting optimized conditions with numerical modeling as an effective prediction tool is necessary. The targets for the processing are multiple and at different spatial scales, and the physical phenomena associated occur in multiphysics and multiscale. In this project, the research work has been developed to model AAM processes in a multiscale and multiphysics approach. A macroscale model was developed to investigate the residual stresses and distortion in AAM processes. A sequentially coupled, thermomechanical, finite element model was developed and validated experimentally. The results showed the temperature distribution, residual stress, and deformation within the formed deposits and substrates. A mesoscale model was developed to include heat transfer, phase change with mushy zone, incompressible free surface flow, solute redistribution, and surface tension. Because of excessive computing time needed, a parallel computing approach was also tested. In addition, after investigating various methods, a Smoothed Particle Hydrodynamics Model (SPH Model) was developed to model wire feeding process. Its computational efficiency and simple architecture makes it more robust and flexible than other models. More research on material properties may be needed to realistically model the AAM processes. A microscale model was developed to investigate heterogeneous nucleation, dendritic grain growth, epitaxial growth of columnar grains, columnar-to-equiaxed transition, grain transport in melt, and other properties. The orientations of the columnar grains were almost perpendicular to the laser motion's direction. Compared to the similar studies in the literature, the multiple grain morphology modeling result is in the same order of magnitude as optical morphologies in the experiment. Experimental work was conducted to validate different models. An infrared camera was incorporated as a process monitoring and validating tool to identify the solidus and mushy zones during deposition. The images were successfully processed to identify these regions. This research project has investigated multiscale and multiphysics of the complex AAM processes thus leading to advanced understanding of these processes. The project has also developed several modeling tools and experimental validation tools that will be very critical in the future of AAM process qualification and certification.

Liou, Frank↗
NASA NTRS1994

Innovation and application of ANN in Europe demonstrated by Kohonen maps

One of the most important contributions to neural networks comes from Kohonen, Helsinki/Espoo, Finland, who had the idea of self-organizating maps in 1981. He verified his idea by an algorithm of which many applications make use of. The impetus for this idea came from biology, a field where the Europeans have always been very active at several research laboratories. The challenge was to model the self-organization found in the brain. Today one goal is the development of more sophisticated neurons which model the biological neurons more exactly. They should come to a better performance of neural nets with only a few complex neurons instead of many simple ones. A lot of application concepts arise from this idea: Kohonen himself applied it to speech recognition, but the project did not overcome much more than the recognition of the numerals one to ten at that time. A more promising application for self-organizing maps is process control and process monitoring. Several proposals were made which concern parameter classification of semiconductor technologies, design of integrated circuits, and control of chemical processes. Self-organizing maps were applied to robotics. The neural concept was introduced into electric power systems. At Dortmund we are working on a system which has to monitor the quality and the reliability of gears and electrical motors in equipment installed in coal mines. The results are promising and the probability to apply the system in the field is very high. A special feature of the system is that linguistic rules which are embedded in a fuzzy controller analyze the data of the self-organizing map in regard to life expectation of the gears. It seems that the fuzzy technique will introduce the technology of neural networks in a tandem mode. These technologies together with the genetic algorithms start to form the attractive field of computational intelligence.

Goser, Karl↗
NASA NTRS1988

Spacelab data processing facility (SLDPF) Quality Assurance (QA)/Data Accounting (DA) expert systems: Transition from prototypes to operational systems

The SLDPF is responsible for the capture, quality monitoring processing, accounting, and shipment of Spacelab and/or Attached Shuttle Payloads (ASP) telemetry data to various user facilities. Expert systems will aid in the performance of the quality assurance and data accounting functions of the two SLDPF functional elements: the Spacelab Input Processing System (SIPS) and the Spacelab Output Processing System (SOPS). Prototypes were developed for each as independent efforts. The SIPS Knowledge System Prototype (KSP) used the commercial shell OPS5+ on an IBM PC/AT; the SOPS Expert System Prototype used the expert system shell CLIPS implemented on a Macintosh personal computer. Both prototypes emulate the duties of the respective QA/DA analysts based upon analyst input and predetermined mission criteria parameters, and recommended instructions and decisions governing the reprocessing, release, or holding for further analysis of data. These prototypes demonstrated feasibility and high potential for operational systems. Increase in productivity, decrease of tedium, consistency, concise historial records, and a training tool for new analyses were the principal advantages. An operational configuration, taking advantage of the SLDPF network capabilities, is under development with the expert systems being installed on SUN workstations. This new configuration in conjunction with the potential of the expert systems will enhance the efficiency, in both time and quality, of the SLDPF's release of Spacelab/AST data products.

Basile, Lisa↗
NASA NTRS1988

Spacelab data processing facility (SLDPF) quality assurance (QA)/data accounting (DA) expert systems - Transition from prototypes to operational systems

The SLDPF is responsible for the capture, quality monitoring processing, accounting, and shipment of Spacelab and/or Attached Shuttle Payloads (ASP) telemetry data to various user facilities. Expert systems will aid in the performance of the quality assurance and data accounting functions of the two SLDPF functional elements: the Spacelab Input Processing System (SIPS) and the Spacelab Output Processing System (SOPS). Prototypes were developed for each as independent efforts. The SIPS Knowledge System Prototype (KSP) used the commercial shell OPS5+ on an IBM PC/AT; the SOPS Expert System Prototype used the expert system shell CLIPS implemented on a Macintosh personal computer. Both prototypes emulate the duties of the respective QA/DA analysts based upon analyst input and predetermined mission criteria parameters, and recommended instructions and decisions governing the reprocessing, release, or holding for further analysis of data. These prototypes demonstrated feasibility and high potential for operational systems. Increase in productivity, decrease of tedium, consistency, concise historical records, and a training tool for new analyses were the principal advantages. An operational configuration, taking advantage of the SLDPF network capabilities, is under development with the expert systems being installed on SUN workstations. This new configuration in conjunction with the potential of the expert systems will enhance the efficiency, in both time and quality, of the SLDPF's release of Spacelab/AST data products.

Basile, Lisa↗
NASA NTRS1989

Vacuum mechatronics

The discipline of vacuum mechatronics is defined as the design and development of vacuum-compatible computer-controlled mechanisms for manipulating, sensing and testing in a vacuum environment. The importance of vacuum mechatronics is growing with an increased application of vacuum in space studies and in manufacturing for material processing, medicine, microelectronics, emission studies, lyophylisation, freeze drying and packaging. The quickly developing field of vacuum mechatronics will also be the driving force for the realization of an advanced era of totally enclosed clean manufacturing cells. High technology manufacturing has increasingly demanding requirements for precision manipulation, in situ process monitoring and contamination-free environments. To remove the contamination problems associated with human workers, the tendency in many manufacturing processes is to move towards total automation. This will become a requirement in the near future for e.g., microelectronics manufacturing. Automation in ultra-clean manufacturing environments is evolving into the concept of self-contained and fully enclosed manufacturing. A Self Contained Automated Robotic Factory (SCARF) is being developed as a flexible research facility for totally enclosed manufacturing. The construction and successful operation of a SCARF will provide a novel, flexible, self-contained, clean, vacuum manufacturing environment. SCARF also requires very high reliability and intelligent control. The trends in vacuum mechatronics and some of the key research issues are reviewed.

Hackwood, Susan↗
NASA NTRS1987

Performance analysis of a generalized upset detection procedure

A general procedure for upset detection in complex systems, called the data block capture and analysis upset monitoring process is described and analyzed. The process consists of repeatedly recording a fixed amount of data from a set of predetermined observation lines of the system being monitored (i.e., capturing a block of data), and then analyzing the captured block in an attempt to determine whether the system is functioning correctly. The algorithm which analyzes the data blocks can be characterized in terms of the amount of time it requires to examine a given length data block to ascertain the existence of features/conditions that have been predetermined to characterize the upset-free behavior of the system. The performance of linear, quadratic, and logarithmic data analysis algorithms is rigorously characterized in terms of three performance measures: (1) the probability of correctly detecting an upset; (2) the expected number of false alarms; and (3) the expected latency in detecting upsets.

Blough, Douglas M.↗
NASA NTRS1996

Interdisciplinary Investigations in Support of Project DI-MOD

Various concepts from time series analysis are used as the basis for the development of algorithms to assist in the analysis and interpretation of remote sensed imagery. An approach to trend detection that is based upon the fractal analysis of power spectrum estimates is presented. Additionally, research was conducted toward the development of a software architecture to support processing tasks associated with databases housing a variety of data. An algorithmic approach which provides for the automation of the state monitoring process is presented.

Starks, Scott A.↗