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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 55 records · Page 3
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NASA NTRS2021

A Quality Assurance Framework for Satellite Earth Observation Missions

Presented is a new quality assurance (QA) framework for Earth Observation missions that has been developed as a joint initiative between ESA and NASA. It aims ensure the rigorous assessment of all aspects of relevant aspects of mission quality, verifying claimed mission performance and, where applicable, reviewing the extent to which the mission follows community best practice in a manner that is “fit for purpose”. The QA framework has potential for more general use in both institutional and commercial Earth Observation – helping mission providers to understand the information their users' needs and empowering users to make informed decisions about which data is fit for their purpose.

Samuel E Hunt↗
NASA NTRS2008

Guidance and Control Software Project Data - Volume 4: Configuration Management and Quality Assurance Documents

The Guidance and Control Software (GCS) project was the last in a series of software reliability studies conducted at Langley Research Center between 1977 and 1994. The technical results of the GCS project were recorded after the experiment was completed. Some of the support documentation produced as part of the experiment, however, is serving an unexpected role far beyond its original project context. Some of the software used as part of the GCS project was developed to conform to the RTCA/DO-178B software standard, "Software Considerations in Airborne Systems and Equipment Certification," used in the civil aviation industry. That standard requires extensive documentation throughout the software development life cycle, including plans, software requirements, design and source code, verification cases and results, and configuration management and quality control data. The project documentation that includes this information is open for public scrutiny without the legal or safety implications associated with comparable data from an avionics manufacturer. This public availability has afforded an opportunity to use the GCS project documents for DO-178B training. This report provides a brief overview of the GCS project, describes the 4-volume set of documents and the role they are playing in training, and includes configuration management and quality assurance documents from the GCS project. Volume 4 contains six appendices: A. Software Accomplishment Summary for the Guidance and Control Software Project; B. Software Configuration Index for the Guidance and Control Software Project; C. Configuration Management Records for the Guidance and Control Software Project; D. Software Quality Assurance Records for the Guidance and Control Software Project; E. Problem Report for the Pluto Implementation of the Guidance and Control Software Project; and F. Support Documentation Change Reports for the Guidance and Control Software Project.

Hayhurst, Kelly J.↗
NASA NTRS1973

Apollo experience report: Reliability and quality assurance

The reliability of the Apollo spacecraft resulted from the application of proven reliability and quality techniques and from sound management, engineering, and manufacturing practices. Continual assessment of these techniques and practices was made during the program, and, when deficiencies were detected, adjustments were made and the deficiencies were effectively corrected. The most significant practices, deficiencies, adjustments, and experiences during the Apollo Program are described in this report. These experiences can be helpful in establishing an effective base on which to structure an efficient reliability and quality assurance effort for future space-flight programs.

Sperber, K. P.↗
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 NTRS1987

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

Spacelab Data Processing Facility (SLDPF) expert system prototypes have been developed to assist in the quality assurance of Spacelab and/or Attached Shuttle Payload (ASP) processed telemetry data. 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 NTRS1985

Quality assurance procedures for V378A matrix resin

A characterization methodology has been developed on which to base quality assurance procedures for U.S. Polymeric V378A bismaleimide matrix resin. Chemical composition is established by partition reverse phase and size exclusion liquid chromatography. Cure rheology behavior is quantitatively characterized by dynamic viscoelastic analysis using the parallel plate technique. The overall cure process is characterized by differential scanning calorimetry. The sensitivity of the procedures is evaluated by studying the effects of ambient out time on the chemical end behaviorial properties of the resin.

Hamermesh, C. L.↗
NASA NTRS2014

A Systems Engineering Approach to Quality Assurance for Aerospace Testing

On the surface, it appears that AS9100 has little to say about how to apply a Quality Management System (QMS) to major aerospace test programs (or even smaller ones). It also appears that there is little in the quality engineering Body of Knowledge (BOK) that applies to testing, unless it is nondestructive examination (NDE), or some type of lab or bench testing associated with the manufacturing process. However, if one examines: a) how the systems engineering (SE) processes are implemented throughout a test program; and b) how these SE processes can be mapped to the requirements of AS9100, a number of areas for involvement of the quality professional are revealed. What often happens is that quality assurance during a test program is limited to inspections of the test article; what could be considered a manufacturing al fresco approach. This limits the quality professional and is a disservice to the programs and projects, since there are a number of ways that quality can enhance critical processes, and support efforts to improve risk reduction, efficiency and effectiveness. The Systems Engineering (SE) discipline is widely used in aerospace to ensure the progress from Stakeholder Expectations (the President, Congress, the taxpayers) to a successful, delivered product or service. Although this is well known, what is not well known is that these same SE processes are implemented in varying complexity, to prepare for and implement test projects that support research, development, verification and validation, qualification, and acceptance test projects. Although the test organization's terminology may vary from the SE terminology, and from one test service provider to another, the basic process is followed by successful, reliable testing organizations. For this analysis, NASA Procedural Requirements (NPR) 7123.1, NASA Systems Engineering Processes and Requirements is used to illustrate the SE processes that are used for major aerospace testing. Many of these processes are also implemented for smaller test projects, and this set of processes will also look familiar to those who have participated in launch site activation and flight demonstrations.

Shepherd, Christena C.↗
NASA NTRS2015

A Systems Engineering Approach to Quality Assurance for Aerospace Testing

On the surface, it appears that AS91001 has little to say about how to apply a Quality Management System (QMS) to major aerospace test programs (or even smaller ones). It also appears that there is little in the quality engineering Body of Knowledge (BOK)2 that applies to testing, unless it is nondestructive examination (NDE), or some type of lab or bench testing associated with the manufacturing process. However, if one examines: a) how the systems engineering (SE) processes are implemented throughout a test program; and b) how these SE processes can be mapped to the requirements of AS9100, a number of areas for involvement of the quality professional are revealed. What often happens is that quality assurance during a test program is limited to inspections of the test article; what could be considered a manufacturing al fresco approach. This limits the quality professional and is a disservice to the programs and projects, since there are a number of ways that quality can enhance critical processes, and support efforts to improve risk reduction, efficiency and effectiveness.

Shepherd, Christena C.↗
NASA NTRS1991

Safety, Reliability, and Quality Assurance Provisions for the Office of Aeronautics, Exploration and Technology Centers

This Handbook establishes general safety, reliability, and quality assurance (SR&QA) guidelines for use on flight and ground-based projects conducted at the Ames, Langley, and Lewis Research Centers, hereafter identified as the Office of Aeronautics, Exploration and Technology (OAET) Centers. This document is applicable to all projects and operations conducted at these Centers except for those projects covered by more restrictive provisions such as the Space Shuttle, Space Station, and unmanned spacecraft programs. This Handbook is divided into two parts. The first (Chapters 1 and 2) establishes the SR&QA guidelines applicable to the OAET Centers, and the second (Appendices A, B, C, and D) provides examples and definitions for the total SR&QA program. Each center should implement SR&QA programs using these guidelines with tailoring appropriate to the special projects conducted by each Center. This Handbook is issued in loose-leaf form and will be revised by page changes.

Source record↗
NASA NTRS2010

A Discussion of the Software Quality Assurance Role

The basic idea underlying this paper is that the conventional understanding of the role of a Software Quality Assurance (SQA) engineer is unduly limited. This is because few have asked who the customers of a SQA engineer are. Once you do this, you can better define what tasks a SQA engineer should perform, as well as identify the knowledge and skills that such a person should have. The consequence of doing this is that a SQA engineer can provide greater value to his or her customers. It is the position of this paper that a SQA engineer providing significant value to his or her customers must not only assume the role of an auditor, but also that of a software and systems engineer. This is because software engineers and their managers particularly value contributions that directly impact products and their development. These ideas are summarized as lessons learned, based on my experience at Jet Propulsion Laboratory (JPL).

experience↗
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 NTRS2020

NASA quality assurance in an MBSE world

We explore the impact and consequences of the MBSE Value items discussed above and how they impact the disciplines of quality assurance, reliability and maintainability, system safety, and software assurance. We provide insight into how the MBSE modeling tools can be used to define S&MA processes (ideally as a result of Use Case [1] elaboration of processes represented in MagicDraw®), produce S&MA products (ViewEditor output of various items), and represent S&MA disciplines (S&MA inside of MagicDraw). We also provide insight into the degree to which some elements can be directly integrated into a SysML® model and when, as often happens, an interface to some external source must be provided.

Evans, John W.↗
NASA NTRS1996

Development and status of data quality assurance program at NASA Langley research center: Toward national standards

As part of a continuing effort to re-engineer the wind tunnel testing process, a comprehensive data quality assurance program is being established at NASA Langley Research Center (LaRC). The ultimate goal of the program is routing provision of tunnel-to-tunnel reproducibility with total uncertainty levels acceptable for test and evaluation of civilian transports. The operational elements for reaching such levels of reproducibility are: (1) statistical control, which provides long term measurement uncertainty predictability and a base for continuous improvement, (2) measurement uncertainty prediction, which provides test designs that can meet data quality expectations with the system's predictable variation, and (3) national standards, which provide a means for resolving tunnel-to-tunnel differences. The paper presents the LaRC design for the program and discusses the process of implementation.

Hemsch, Michael J.↗