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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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A high quality spotlight SAR processing algorithm is presented. In this algorithm, subband images of the radar illuminated spot are pocessed using well known strip mode processing algorithms.
The quality of vibroacoustical surface polishing and the deviation formation process of the surfaces were studied using a polishing mill unit. Data cover spectral composition of vibration accelerations and vibration displacements of individual elements, precision rotation of the polishing circle spindle in static and dynamic operation modes, spectral composition of relative vibrations of polishing circle and the part being processed, statistical and dynamic rigidity of individual elements, and APFC of the elastic system of the mill stand. The effect of individual spindle parameters on vibroacoustical characteristics of the system was also discussed as well as the spectrum measurement of the disturbing force.
The Spacelab Data Processing Facility (SLDPF) is an integral part of the Space Shuttle data network for missions that involve attached scientific payloads. Expert system prototypes were developed to aid in the performance of the quality assurance function of the Spacelab and/or Attached Shuttle Payloads processed telemetry data. The Spacelab Input Processing System (SIPS) and the Spacelab Output Processing System (SOPS), two expert systems, were developed to determine their feasibility and potential in the quality assurance of processed telemetry data. The capabilities and performance of these systems are discussed.
This bibliography lists 606 references to reports and journal articles entered into the NASA Scientific and Technical Information Database during 1992 to 1993. Topics cover the philosophy and history of Continual Improvement (CI), basic approaches and strategies for implementation, and lessons learned from public and private sector models. Entries are arranged according to the following categories: Leadership for Quality, Information and Analysis, Strategic Planning for CI, Human Resources Utilization, Management of Process Quality, Supplier Quality, Assessing Results, Customer Focus and Satisfaction, TQM Tools and Philosophies, and Applications. Indexes include subject, personal author, corporate source, contract number, report number, and accession number.
This report summarizes the National Aeronautics and Space Administrations (NASA) state of the art of nondestructive evaluation (NDE) for additive manufacturing (AM), or "3-D printed", hardware. NASA's unique need for highly customized spacecraft and instrumentation is suited for AM, which offers a compelling alternative to traditional subtractive manufacturing approaches. The Agency has an opportunity to push the envelope on how this technology is used in zero gravity, an enable in-space manufacturing of flight spares and replacement hardware crucial for long-duration, manned missions to Mars. The Agency is leveraging AM technology developed internally and by industry, academia, and other government agencies for its unique needs. Recent technical interchange meetings and workshops attended by NASA have identified NDE as a universal need for all aspects of additive manufacturing. The impact of NDE on AM is cross cutting and spans materials, processing quality assurance, testing and modeling disciplines. Appropriate NDE methods are needed before, during, and after the AM production process.
Arc-spray "monotape" process automated, low in cost, and produces at high rate. Ideal for development of new metal-matrix composites. "Monotape" reproducible and of high quality. Process carried out in controlled gas environment with programmable matrix-deposition rates, resulting in significant cost saving
Moving software development into the engineering arena requires controllability, and to control a process, it must be measurable. Measuring the process does no good if the product is not also measured, i.e., being the best at producing an inferior product does not define a quality process. Also, not every number extracted from software development is a valid measurement. A valid measurement only results when we are able to verify that the number is representative of the attribute that we wish to measure. Many proposed software metrics are used by practitioners without these metrics ever having been validated, leading to costly but often useless calculations. Several researchers have bemoaned the lack of scientific precision in much of the published software measurement work and have called for validation of software metrics by measurement theory. This dissertation applies measurement theory to validate fifty proposed object-oriented software metrics (Li and Henry, 1993; Chidamber and Kemerrer, 1994; Lorenz and Kidd, 1994).
Moving software development into the engineering arena requires controllability, and to control a process, it must be measurable. Measuring the process does no good if the product is not also measured, i.e., being the best at producing an inferior product does not define a quality process. Also, not every number extracted from software development is a valid measurement. A valid measurement only results when we are able to verify that the number is representative of the attribute that we wish to measure. Many proposed software metrics are used by practitioners without these metrics ever having been validated, leading to costly but often useless calculations. Several researchers have bemoaned the lack of scientific precision in much of the published software measurement work and have called for validation of software metrics by measurement theory. This dissertation applies measurement theory to validate fifty proposed object-oriented software metrics.
Moving software development into the engineering arena requires controllability, and to control a process, it must be measurable. Measuring the process does no good if the product is not also measured, i.e., being the best at producing an inferior product does not define a quality process. Also, not every number extracted from software development is a valid measurement. A valid measurement only results when we are able to verify that the number is representative of the attribute that we wish to measure. Many proposed software metrics are used by practitioners without these metrics ever having been validated, leading to costly but often useless calculations. Several researchers have bemoaned the lack of scientific precision in much of the published software measurement work and have called for validation of software metrics by measurement theory. This dissertation applies measurement theory to validate fifty proposed object-oriented software metrics.
Facilities and equipment are defined for refining processes to commercial grade of lunar material that is delivered to a 'space manufacturing facility' in beneficiated, primary processed quality. The manufacturing facilities and the equipment for producing elements of large space systems from these materials and providing programmatic assessments of the concepts are also defined. In-space production processes of solar cells (by vapor deposition) and arrays, structures and joints, conduits, waveguides, RF equipment radiators, wire cables, converters, and others are described.
The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to fabricate nuclear components to be assembled into a fully functional microreactor core. Compared with traditional manufacturing technologies, AM technologies allow (1) observation of the manufacturing process at a much higher resolution in real-time using in situ monitoring technologies to capture the sensor signature that scientifically describes each event occurring over time and space and (2) validation of the manufacturing process quality using domain-informed data analytics techniques as a potential qualification and certification methodology for the final component. This report provides an update on the program work on binder jetting in situ process monitoring and associated data analytics results, as well as sample placement and tracking for the subsequent chemical vapor infiltration (CVI) process. Examples are provided to illustrate the progress. Elements of the Digital Thread and data management are discussed in the main document, and an extensive supplemental material section is provided detailing the Digital Platform, as well as its implementation and components. In conclusion the path forward for the next fiscal year is discussed.
Concentrations of atmospheric trace species in the United States have changed dramatically over the past several decades in response to pollution control strategies, shifts in domestic energy policy and economics, and economic development (and resulting emission changes) elsewhere in the world. Reliable projections of the future atmosphere require models to not only accurately describe current atmospheric concentrations, but to do so by representing chemical, physical and biological processes with conceptual and quantitative fidelity. Only through incorporation of the processes controlling emissions and chemical mechanisms that represent the key transformations among reactive molecules can models reliably project the impacts of future policy, energy and climate scenarios. Efforts to properly identify and implement the fundamental and controlling mechanisms in atmospheric models benefit from intensive observation periods, during which collocated measurements of diverse, speciated chemicals in both the gas and condensed phases are obtained. The Southeast Atmosphere Studies (SAS, including SENEX, SOAS, NOMADSS and SEAC4RS) conducted during the summer of 2013 provided an unprecedented opportunity for the atmospheric modeling community to come together to evaluate, diagnose and improve the representation of fundamental climate and air quality processes in models of varying temporal and spatial scales. This paper is aimed at discussing progress in evaluating, diagnosing and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models. The effort focused primarily on model representation of fundamental atmospheric processes that are essential to the formation of ozone, secondary organic aerosol (SOA) and other trace species in the troposphere, with the ultimate goal of understanding the radiative impacts of these species in the southeast and elsewhere. Here we address questions surrounding four key themes: gas-phase chemistry, aerosol chemistry, regional climate and chemistry interactions, and natural and anthropogenic emissions. We expect this review to serve as a guidance for future modeling efforts.
The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to fabricate nuclear grade components to be assembled into a fully functional microreactor core. Compared to traditional manufacturing technologies, additive manufacturing technologies allow (1) observation of the manufacturing process at a much higher resolution in real time using in situ monitoring technologies to capture the sensor signature that scientifically describes each event occurring over time and space, and (2) validation of the manufacturing process quality using domain-informed data analytics techniques as a potential qualification and certification methodology for the final component. This report provides an update on the program work on laser powder bed fusion in-situ process monitoring and associated data analytics results. Examples are provided to illustrate the progress. Elements of the Digital Thread and data management are discussed in the main document, and an extensive supplemental material section is provided detailing the Digital Platform, as well as its implementation and components. In conclusion the path forward for the next fiscal year is discussed.
Fabricating primary aircraft and spacecraft structures using advanced composite materials entail both benefits and risks. The benefits come from much improved strength-to-weight ratios and stiffness-to-weight ratios, potential for less part count, ability to tailor properties, chemical and solvent resistance, and superior thermal properties. On the other hand, the risks involved include high material costs, lack of processing experience, expensive labor, poor reproducibility, high toxicity for some composites, and a variety of space induced risks. The purpose of this project is to generate a manufacturing database for a selected number of materials with potential for space applications, and to rely on this database to develop quantitative approaches to screen candidate materials and processes for space applications on the basis of their manufacturing risks including costs. So far, the following materials have been included in the database: epoxies, polycyanates, bismalemides, PMR-15, polyphenylene sulfides, polyetherimides, polyetheretherketone, and aluminum lithium. The first four materials are thermoset composites; the next three are thermoplastic composites, and the last one is is a metal. The emphasis of this database is on factors affecting manufacturing such as cost of raw material, handling aspects which include working life and shelf life of resins, process temperature, chemical/solvent resistance, moisture resistance, damage tolerance, toxicity, outgassing, thermal cycling, and void content, nature or type of process, associate tooling, and in-process quality assurance. Based on industry experience and published literature, a relative ranking was established for each of the factors affecting manufacturing as listed above. Potential applications of this database include the determination of a delta cost factor for specific structures with a given process plan and a general methodology to screen materials and processes for incorporation into the current conceptual design optimization of future spacecrafts as being coordinated by the Vehicle Analysis Branch where this research is being conducted.
This slide presentation reviews the process for implementation and qualification of space flight photonic components. It discusses the causes for most common anomalies for the space flight components, design compatibility, a specific failure analysis of optical fiber that occurred in a cable in 1999-2000, and another ExPCA connector anomaly involving pins that broke off. It reviews issues around material selection, quality processes and documentation, and current projects that the Photonics group is involved in. The importance of good documentation is stressed.
Abstract In the interest of continued industrialization of metal additive manufacturing in modern production environments, cost is often referenced as a primary deterrent to new adopters. Conventional economic models for additive systems, processes, and supply chains often focus on specific process applications with little generalizability, or they neglect significant costs associated with production such as machine maintenance and consumable part replacement. Compounding the latter issue are substantial knowledge gaps in consumable part wear characterization for additive and other convergent manufacturing systems. In coaxial blown powder directed energy deposition systems, gas atomized metal powder is wasted during material deposition at a rate that is partly dependent on present wear phenomena in a consumable nozzle housed in the cladding head assembly. The price and lead time required to replace the nozzle incentivizes its reuse even when visibly worn. Often this initiates a process quality decline in the form of underbuilt geometry and internal defects due to losses in powder catchment efficiency. While depositing H13 steel using a hybrid manufacturing machine tool equipped with such a deposition system, a unique partial clog with a bridge-like structure formed at the consumable nozzle exit when supporting argon gas flows failed mid-process. To further understand coaxial multi-phase powder flow in the event of support gas failure, a computational fluid dynamics simulation is tailored to relevant process parameters, H13 powder material profile, and machine operator observations collected after the incident. The resulting differences in powder flow compared to control gas flow parameters is presented and discussed. The powder flowability and performance of the clogged nozzle is then assessed by using an optical profilometer to extract the profile of the clog and recreate the clog geometry within the simulation environment. In past work this simulation has been experimentally validated for a 316L steel powder material profile and used specifically for analyzing powder stream geometry and catchment efficiency. After the initial powder flow characterization, the clog is removed, and the nozzle is reprofiled. After removing the obstructing clog, the newly unobstructed nozzle geometry, the original off the shelf nozzle geometry, and additional nozzle profiles exploring different consumable refurbishment strategies are reevaluated in the simulation. Powder catchment efficiency for all variant nozzle geometries and relevant flow variables are compared and discussed, along with potential mitigation strategies for optimizing powder flowability with worn consumables. This work expands on the known morphology of blown powder obstructions and wear defects present in consumable coaxial nozzles while discussing pragmatic simulation driven responses to unanticipated subsystem failure in hybrid manufacturing machining platforms.
This viewgraph presentation provides an overview of land surface process and air quality research at MSFC including atmospheric modeling and ongoing research whose objective is to undertake a comprehensive spatiotemporal analysis of the effects of accurate land surface characterization on atmospheric modeling results, and public health applications. Land use maps as well as 10 meter air temperature, surface wind, PBL mean difference heights, NOx, ozone, and O3+NO2 plots as well as spatial growth model outputs are included. Emissions and general air quality modeling are also discussed.
As an effective dimension reduction and feature extraction technique, manifold learning has been successfully applied to high-dimensional data analysis. With the rapid development of sensor technology, a large amount of high-dimensional data such as image streams can be easily available. Thus, a promising application of manifold learning is in the field of sensor signal analysis, particular for the applications of online process monitoring and control using high-dimensional data. The objective of this study is to develop a manifold learning-based feature extraction method for process monitoring of Additive Manufacturing (AM) using online sensor data. Due to the non-parametric nature of most existing manifold learning methods, their performance in terms of computational efficiency, as well as noise resistance has yet to be improved. To address this issue, this study proposes an integrated manifold learning approach termed multi-kernel metric learning embedded isometric feature mapping (MKML-ISOMAP) for dimension reduction and feature extraction of online high-dimensional sensor data such as images. Based on the extracted features with the utilization of supervised classification and regression methods, an online process monitoring methodology for AM is implemented to identify the actual process quality status. Finally, in the numerical simulation and real-world case studies, the proposed method demonstrates excellent performance in both prediction accuracy and computational efficiency.