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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 NTRS2007

Data Mining Methods Applied to Flight Operations Quality Assurance Data: A Comparison to Standard Statistical Methods

In a previous study, multiple regression techniques were applied to Flight Operations Quality Assurance-derived data to develop parsimonious model(s) for fuel consumption on the Boeing 757 airplane. The present study examined several data mining algorithms, including neural networks, on the fuel consumption problem and compared them to the multiple regression results obtained earlier. Using regression methods, parsimonious models were obtained that explained approximately 85% of the variation in fuel flow. In general data mining methods were more effective in predicting fuel consumption. Classification and Regression Tree methods reported correlation coefficients of .91 to .92, and General Linear Models and Multilayer Perceptron neural networks reported correlation coefficients of about .99. These data mining models show great promise for use in further examining large FOQA databases for operational and safety improvements.

Stolzer, Alan J.↗
NASA NTRS1995

Quality assurance and reliability in the Japanese electronics industry

Quality and reliability are two attributes required for all Japanese products, although the JTEC panel found these attributes to be secondary to customer cost requirements. While our Japanese hosts gave presentations on the challenges of technology, cost, and miniaturization, quality and reliability were infrequently the focus of our discussions. Quality and reliability were assumed to be sufficient to meet customer needs. Fujitsu's slogan, 'quality built-in, with cost and performance as prime consideration,' illustrates this point. Sony's definition of a next-generation product is 'one that is going to be half the size and half the price at the same performance of the existing one'. Quality and reliability are so integral to Japan's electronics industry that they need no new emphasis.

Pecht, Michael↗
NASA NTRS2019

Ozonesonde Quality Assurance: JOSIE-SHADOZ (2017) and SHALLOTS (2018)

Ozonesonde data constitute a mainstay of satellite calibration and are used for climatologies and analysis of trends, especially in the lower stratosphere where satellites are most uncertain. The electrochemical-concentration cell (ECC) ozonesonde has been deployed at ~100 stations worldwide since the 1960s, with changes over time in manufacture and procedures, including details of the cell chemical solution and data processing. As a consequence, there are biases among different stations and discontinuities in profile timeseries from individual site records. Since 1996 the Jülich [Germany] Ozone Sonde Intercomparison Experiment (JOSIE) has periodically tested ozonesondes in a simulation chamber designated the World Calibration Centre for Ozonesondes by WMO. In October- November 2017 a JOSIE campaign evaluated the sondes and procedures used in SHADOZ (Southern Hemisphere Additional Ozonesondes), a 14-station tropical and subtropical network. A distinctive feature of the 2017 JOSIE was that the tests were conducted by operators from eight SHADOZ stations; Nairobi, Natal, Irene, Costa Rica, Paramaribo, Reunion, Hanoi, Kuala Lumpur. Experimental protocols and preliminary results for the SHADOZ sonde configurations, which represent most of those in use today, are described. SHADOZ stations that follow WMO-recommended protocols record total ozone within 3% of the JOSIE reference instrument. Instrument biases noted in prior JOSIE and field tests like BESOS (2004) were noted in JOSIE-2017, with maximum effect in the stratosphere. In June 2018 we organized a series of dual launches during the OWLETS II campaign in the Maryland and Chesapeake Bay area (SHALLOTS = SHADOZ-OWLETS ParaLLel Ozonesonde Test Study). Instrument and solution types were varied as in JOSIE-2017 and three radiosonde-ozonesonde variants were tested. An example of a parallel sampling in SHALLOTS, from a Greenbelt EnSCI-iMet sonde combination flown with the Wallops SPCLMS package, is illustrated in the Figure. The result was a range of biases but in general the instrument combination (EnSCI-iMet) deployed at 11 SHADOZ stations recorded ~5-10% less ozone in the stratosphere than the SPC ECC sonde flown with a Vaisala or LMS system. These 2017 and 2018 results and prior JOSIEs demonstrate that regular testing is essential to maintain best practices in ozonesonde operations and to ensure high-quality data for the ozone assessment communities.

Quality assurance↗
NASA NTRS1991

Quality assurance planning for lunar Mars exploration

A review is presented of the tools and techniques required to meet the challenge of total quality in the goal of traveling to Mars and returning to the moon. One program used by NASA to ensure the integrity of baselined requirements documents is configuration management (CM). CM is defined as an integrated management process that documents and identifies the functional and physical characteristics of a facility's systems, structures, computer software, and components. It also ensures that changes to these characteristics are properly assessed, developed, approved, implemented, verified, recorded, and incorporated into the facility's documentation. Three principal areas are discussed that will realize significant efficiencies and enhanced effectiveness, change assessment, change avoidance, and requirements management.

Myers, Kay↗
NASA NTRS1986

Quality assurance procedures for environmental control and monitoring in plant growth facilities. Report of the North Central Regional 101 Committee on Growth Chamber Use

This report includes procedures for ensuring the quality of the environment provided for plant growth in controlled environment facilities. Biologists and engineers may use these procedures for ensuring quality control during experiments or for ensuring quality control in the design of plant growth facilities. Environmental monitoring prior to and during experiments is included in these procedures. Specific recommendations cover control, acquisition, and calibration for sensor types for the separate parameters of radiation (light), temperature, humidity, carbon dioxide, and air movement.

NASA Discipline Number 61-10↗
NASA NTRS1979

Quality assurance and control in the production and static tests of the solid rocket boosters for the Space Shuttle

The paper surveys the various aspects of design and overhaul of the solid rocket boosters. It is noted that quality control is an integral part of the design specifications. Attention is given to the production process which is optimized towards highest quality. Also discussed is the role of the DCA (Defense Contract Administration) in inspecting the products of subcontractors, noting that the USAF performs this role for prime contractors. Fabrication and construction of the booster is detailed with attention given to the lining of the booster cylinder and the mixing of the propellant and the subsequent X-ray inspection.

Cerny, O. F.↗
NASA NTRS2010

Data Quality Assurance for Supersonic Jet Noise Measurements

The noise created by a supersonic aircraft is a primary concern in the design of future high-speed planes. The jet noise reduction technologies required on these aircraft will be developed using scale-models mounted to experimental jet rigs designed to simulate the exhaust gases from a full-scale jet engine. The jet noise data collected in these experiments must accurately predict the noise levels produced by the full-scale hardware in order to be a useful development tool. A methodology has been adopted at the NASA Glenn Research Center s Aero-Acoustic Propulsion Laboratory to insure the quality of the supersonic jet noise data acquired from the facility s High Flow Jet Exit Rig so that it can be used to develop future nozzle technologies that reduce supersonic jet noise. The methodology relies on mitigating extraneous noise sources, examining the impact of measurement location on the acoustic results, and investigating the facility independence of the measurements. The methodology is documented here as a basis for validating future improvements and its limitations are noted so that they do not affect the data analysis. Maintaining a high quality jet noise laboratory is an ongoing process. By carefully examining the data produced and continually following this methodology, data quality can be maintained and improved over time.

Brown, Clifford A.↗
DOE OSTI2025

The AMACStar ASIC for the HL-LHC ATLAS ITk Strip detector: design, verification, testing, and quality assurance

For the high-luminosity upgrade to the LHC (HL-LHC), the ATLAS detector at CERN requires an all-new inner detector, the Inner Tracker (ITk). The ITk Strip subdetector is made up of silicon modules, which include three types of radiation-hard ASICs. One of these is the Autonomous Monitor and Control (AMAC). The AMAC is manufactured by Global Foundries using 130 nm CMOS8RF DM technology and is approximately 3 by 5 mm in size. This ASIC autonomously monitors the temperatures, voltages, and currents in the module components while controlling critical values in order to prevent these quantities from reaching dangerous levels. The final design, AMACStar, was verified, tested, and ensured to perform all necessary functions. A quality control procedure using an in-house probe station set-up was developed in order to ensure that every individual chip on each wafer of AMACStars required by the ITk Strip project met performance requirements. The average per wafer yield of usable AMACStars is 92.33%, exceeding the design-specific 90% yield estimated for project costing. This estimate was based on actual yields for similar designs in this process.

Analogue electronic circuits↗
DOE OSTI2024

Software Quality Assurance Plan ANSYS LSDYNA Version 2023R1

ANSYS Inc. develops and markets engineering simulation software and services used in the aerospace, automotive, manufacturing, electronics, biomedical, energy, defense, and many other industries. ANSYS is dedicated to engineering simulation and is the world’s leading software provider. ANSYS was founded in 1970 and is headquartered in Canonsburg, Pennsylvania. ANSYS provides an engineering analysis tool combining structural, thermal, computational fluid dynamics, acoustic and electromagnetic simulation capabilities. ANSYS LS-DYNA is the most used explicit simulation program capable of simulating the response of materials to short periods of severe loading. Its many elements, contact formulations, material models, and other controls can be used to simulate complex models with control over all the details of the problem. ANSYS LS-DYNA has a vast array of capabilities to simulate extreme deformation problems using its explicit solver. Engineers can tackle simulations involving material failure and look at how the failure progresses through a part or through a system. Models with large amounts of parts or surfaces interacting with each other are also easily handled, and the interactions and load passing between complex behaviors are modeled accurately. Using computers with higher numbers of CPU cores can drastically reduce solution times. In addition, many consulting firms and hundreds of universities use ANSYS for analysis, research, and educational purposes. ANSYS is recognized worldwide as one of the most widely used and capable programs of its type. ANSYS has successfully passed over 100 customer quality system audits against American Society of Mechanical Engineers (ASME) NQA-1 and 10 CFR Part 50, Appendix B, since the company was founded, over 60 of which have been since 1997. ANSYS has successfully passed over 100 International Organization for Standardization (ISO) 9001 assessments. ANSYS design analysis software is the first created within a quality system with ISO 9001 certification, which is the internationally accepted quality standard. Product development, testing, maintenance, and support processes also meet the US Nuclear Regulatory Commission’s (NRC’s) quality requirements, as they have for nearly four decades. ANSYS staff perform more than 60,000 software verification tests before releasing each new product. ASME NQA-1-2012 (Subpart 2.7 is specific to software) is the industry- and NRC-accepted approach (consensus standard) for meeting 10 CFR Part 50, Appendix B, requirements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1997

Application of Domain Knowledge to Software Quality Assurance

This work focused on capturing, using, and evolving a qualitative decision support structure across the life cycle of a project. The particular application of this study was towards business process reengineering and the representation of the business process in a set of Business Rules (BR). In this work, we defined a decision model which captured the qualitative decision deliberation process. It represented arguments both for and against proposed alternatives to a problem. It was felt that the subjective nature of many critical business policy decisions required a qualitative modeling approach similar to that of Lee and Mylopoulos. While previous work was limited almost exclusively to the decision capture phase, which occurs early in the project life cycle, we investigated the use of such a model during the later stages as well. One of our significant developments was the use of the decision model during the operational phase of a project. By operational phase, we mean the phase in which the system or set of policies which were earlier decided are deployed and put into practice. By making the decision model available to operational decision makers, they would have access to the arguments pro and con for a variety of actions and can thus make a more informed decision which balances the often conflicting criteria by which the value of action is measured. We also developed the concept of a 'monitored decision' in which metrics of performance were identified during the decision making process and used to evaluate the quality of that decision. It is important to monitor those decision which seem at highest risk of not meeting their stated objectives. Operational decisions are also potentially high risk decisions. Finally, we investigated the use of performance metrics for monitored decisions and audit logs of operational decisions in order to feed an evolutionary phase of the the life cycle. During evolution, decisions are revisisted, assumptions verified or refuted, and possible reassessments resulting in new policy are made. In this regard we implemented a machine learning algorithm which automatically defined business rules based on expert assessment of the quality of operational decisions as recorded during deployment.

Wild, Christian W.↗
DOE OSTI2025

Quality Assurance of the Irradiated EBR-II Metallic Fuels Data

The U.S. DOE-NE’s Advanced Reactor Technologies (ART) Fast Reactor Program (FRP) and the NE-4 Advanced Fuels Campaign (AFC) have jointly undertaken efforts to qualify post-irradiation examination (PIE) data for Experimental Breeder Reactor II (EBR-II) and Fast Flux Test Facility (FFTF) metallic fuels. Among the thousands of PIE datasets in the Metallic Fuels Irradiation & Physics Database (FIPD), data from selected EBR-II experiments have been prioritized as the most valuable to the U.S. nuclear industry for licensing activities related to metallic fuel-based advanced fast reactors. This report summarizes the general data qualification progress of the EBR-II and FFTF experiments, with focus on the selected EBR-II experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Quality Assurance of Legacy Post-Irradiation Examination Data for Metallic Fuels

The U.S. DOE-NE’s Advanced Reactor Technologies (ART) Fast Reactor Program (FRP) and the NE-4 Advanced Fuels Campaign (AFC) have jointly undertaken the qualification of the legacy post-irradiation examination (PIE) data held in the Fuels Irradiation & Physics Database (FIPD), covering metallic fuel experiments conducted in the Experimental Breeder Reactor II (EBR-II) and the Fast Flux Test Facility (FFTF). In FY26 this effort reached a milestone: six major types of PIE data—contact profilometry, isotopic gamma scan, fission gas chemistry, fission gas release, laser profilometry, and neutron radiography—have been qualified for all available experiments in FIPD, and the U.S. nuclear industry can now draw on them with confidence in licensing activities for metallic fuel-based advanced fast reactors. This report documents the qualification process and the resulting status of the PIE data.

Mo, Kun↗