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Modeling Scientific Software Architecture from Regression Tests using Data Mining Techniques
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Quality Assurance Program Plan for SFR Metallic Fuel Data Qualification
This document contains an evaluation of the applicability of the current Quality Assurance Standards from the American Society of Mechanical Engineers Standard NQA-1 (NQA-1) criteria and identifies and describes the quality assurance process(es) by which attributes of historical, analytical, and other data associated with sodium-cooled fast reactor [SFR] metallic fuel will be evaluated. This process is being instituted to facilitate validation of data to the extent that such data may be used to support future licensing efforts associated with advanced reactor designs. The initial data to be evaluated under this program were generated during the US Integral Fast Reactor program between 1984-1994, where the data include, but are not limited to, research and development data and associated documents, test plans and associated protocols, operations and test data, technical reports, and information associated with past United States Nuclear Regulatory Commission reviews of SFR designs. It is recognized that managing the data generated by large research and development projects presents a significant challenge for retaining data integrity and availability. American Society of Mechanical Engineers Standard NQA-1 (NQA-1) 2008/2009a provides appropriate requirements for this plan.
Quality Assurance Program Plan for SFR Metallic Fuel Data Qualification
This document contains an evaluation of the applicability of the current Quality Assurance Standards from the American Society of Mechanical Engineers Standard NQA-1 (NQA-1) criteria and identifies and describes the quality assurance process(es) by which attributes of historical, analytical, and other data associated with sodium-cooled fast reactor [SFR] metallic fuel will be evaluated. This process is being instituted to facilitate validation of data to the extent that such data may be used to support future licensing efforts associated with advanced reactor designs. The initial data to be evaluated under this program were generated during the US Integral Fast Reactor program between 1984-1994, where the data include, but are not limited to, research and development data and associated documents, test plans and associated protocols, operations and test data, technical reports, and information associated with past United States Nuclear Regulatory Commission reviews of SFR designs. It is recognized that managing the data generated by large research and development projects presents a significant challenge for retaining data integrity and availability. American Society of Mechanical Engineers Standard NQA-1 (NQA-1) 2008/2009a provides appropriate requirements for this plan.
MSD CoP Webinar: AI and Extreme Events - Overcoming Data Challenges for Improved Characterization of Climate Extremes
Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Abstract: Artificial Intelligence (AI) models require large volumes of data for training and testing. Data requirements present challenges for using AI to explore extreme events with limited observational data. This webinar will showcase two innovative methods developed by part of the European Climate Intelligence (CLINT) project to overcome data challenges and harness AI to improve our understanding of climate extremes. Dr. Ascenso will present his research on data augmentation methods to improve estimates of tropical cyclones using satellite data. His presentation will review established methods for data augmentation and explore opportunities and challenges for using generative AI to generate images of extreme, life-threatening tropical cyclones. Next, Dr. Plesiat will present his research on deep learning techniques to overcome limited observational data sets. His presentation will illustrate deep learning methods to develop AI reconstructions of four climate indices across Europe. Presenters : Dr. Guido Ascenso (post-doctoral researcher, Politecnico di Milano); Dr. Étienne Plésiat (German Climate Computing Centre - DKRZ) Moderator(s): Stefano Galelli (MSD CoP WG Co-Lead), David Gold (MSD CoP WG Co-Lead), Jillian Sturtevant (MSD CoP WG Communications Officer), Matteo Giuliani (Politecnico di Milano, MSD CoP WG Member, Moderator and Organizer) This webinar was held on: October 11, 2024 from 11AM - 1PM ET
Study of Spacecraft On-board Test and Data Processing Techniques Final Summary Report
Bioinstrumentation and on-board data processing review for biological space mission requirements
An appraisal for use in reliability analysis of the test and data collection procedures in the manufacture of an inertial guidance system
Behavior of first gimbal stabilization loop for reliability analysis of inertial guidance system
Preliminary Low-Drag-Airfoil and Flap Data from Tests at Large Reynolds Numbers and Low Turbulence
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Ammonia Resistojet station keeping subsystem aboard applications technology satellite /ATS/ IV.
Ammonia resistojet stationkeeping subsystem onboard ATS 4 satellite, noting flight test data agreement with ground tests
Correlation of fixed-spacing thermionic converter performance with variable-spacing test vehicle data.
Performance prediction for planar and cylindrical electrode geometry fixed spacing thermionic converters
Explorer 22 electrostatic probe data analysis - Testing the results for accuracy
Accuracy of Explorer 32 probe electron density and temperature measurements
Aerospace systems pyrotechnic shock data - Ground test and flight. Volume 1 - Summary and analysis Final report, Jun. 1968 - Mar. 1970
Characteristics of shock loads on spacecraft structures produced by pyrotechnics and explosive devices - Vol. 1
Aerospace systems pyrotechnic shock data /ground test and flight/. Volume 6 - Pyrotechnic shock design guidelines manual, revision A Final report, Jun. 1968 - Mar. 1970
Design of structures and equipment to reduce shock loads induced by pyrotechnics and explosive devices - Vol. 6
Aerospace systems pyrotechnic shock data /ground test and flight/. Volume 7 - Investigation of mass loading effects Final report, 12 May - 12 Nov. 1970
Mass loading effects on pyrotechnic shock environment of aerospace systems
Test of data compilation procedures for the Fraunhofer line discriminator
Calculations and data correlation procedures for Fraunhofer line discriminator operating over open water
Multilayer Insulation Thermal Protection Systems Technology
A summary is presented of the work performed by Marshall Space Flight Center (MSFC) and industry toward the development of flight-type multilayer insulation(MLI) systems. The MSFC MLI program is divided into three large categories: (1) the generation and compilation of MLI composite test data; (2) the analysis, design, and testing of heat flow through MLI applied to ducting, seams, electrical feedthroughs, structural supports, and the tank sidewall; and (3) the development, modification, and utilization of new testing procedures, tanks, and the test facilities. Numerous data have been generated, analyzed, and documented on different MLI composites.
Evaluation of thermal network correction program using test temperature data
An evaluation process to determine the accuracy of a computer program for thermal network correction is discussed. The evaluation is required since factors such as inaccuracies of temperatures, insufficient number of temperature points over a specified time period, lack of one-to-one correlation between temperature sensor and nodal locations, and incomplete temperature measurements are not present in the computer-generated information. The mathematical models used in the evaluation are those that describe a physical system composed of both a conventional and a heat pipe platform. A description of the models used, the results of the evaluation of the thermal network correction, and input instructions for the thermal network correction program are presented.
Hypersonic research engine project. Phase 2: Aerothermodynamic integration model, test plan, data item no. 2-2.01
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