Quality Assurance Processes on KSC and ER Meteorological Tower Data Archived at MSFC
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Eddy current sensors and sensor arrays are used for process quality and material condition assessment of conducting materials. In an embodiment, changes in spatially registered high resolution images taken before and after cold work processing reflect the quality of the process, such as intensity and coverage. These images also permit the suppression or removal of local outlier variations. Anisotropy in a material property, such as magnetic permeability or electrical conductivity, can be intentionally introduced and used to assess material condition resulting from an operation, such as a cold work or heat treatment. The anisotropy is determined by sensors that provide directional property measurements. The sensor directionality arises from constructs that use a linear conducting drive segment to impose the magnetic field in a test material. Maintaining the orientation of this drive segment, and associated sense elements, relative to a material edge provides enhanced sensitivity for crack detection at edges.
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.
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.
Quality control in processing of telemetry data
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.
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.