Results for “machining processes” — Page 44

NASA NTRS1981

Multigrid solvers on parallel computers

Massively parallel computers, as considered in this investigation, are not yet available. However, a large-scale parallel computer cannot usefully be designed before the hypothetical algorithms which will employ it are studied. Most of the studies of parallel partial differential equations (PDE) solvers are based on solution techniques much slower (on sequential machines) than multigrid methods. Multigrid methods are highly parallelizable. Each of their processes can simultaneously be performed at all grid points. The present investigation is concerned with a preliminary exploration of the potential of multigrid, or, more generally, Multi-Level Adaptive Techniques (MLAT) on computers with many processors. Basic processes are considered, taking into account coarse-grid approximation, relaxation, coarse-grid corrections, full multigrid algorithms, nonlinear problems and eigenvalue problems, fine-to-coarse correction, and chains of problems. Details of parallel multigrid processing are also examined.

Brandt, A.↗

NASA NTRS1983

Lessons learned from the development and manufacture of ceramic reusable surface insulation materials for the space shuttle orbiters

Three ceramic, reusable surface insulation materials and two borosilicate glass coatings were used in the fabrication of tiles for the Space Shuttle orbiters. Approximately 77,000 tiles were made from these materials for the first three orbiters, Columbia, Challenger, and Discovery. Lessons learned in the development, scale up to production and manufacturing phases of these materials will benefit future production of ceramic reusable surface insulation materials. Processing of raw materials into tile blanks and coating slurries; programming and machining of tiles using numerical controlled milling machines; preparing and spraying tiles with the two coatings; and controlling material shrinkage during the high temperature (2100-2275 F) coating glazing cycles are among the topics discussed.

Banas, R. P.↗

NASA NTRS1986

First 3 years of operation of RIACS (Research Institute for Advanced Computer Science) (1983-1985)

The focus of the Research Institute for Advanced Computer Science (RIACS) is to explore matches between advanced computing architectures and the processes of scientific research. An architecture evaluation of the MIT static dataflow machine, specification of a graphical language for expressing distributed computations, and specification of an expert system for aiding in grid generation for two-dimensional flow problems was initiated. Research projects for 1984 and 1985 are summarized.

Denning, P. J.↗

NASA NTRS1989

Initial Ada components evaluation

The SAIC has the responsibility for independent test and validation of the SSE. They have been using a mathematical functions library package implemented in Ada to test the SSE IV and V process. The library package consists of elementary mathematical functions and is both machine and accuracy independent. The SSE Ada components evaluation includes code complexity metrics based on Halstead's software science metrics and McCabe's measure of cyclomatic complexity. Halstead's metrics are based on the number of operators and operands on a logical unit of code and are compiled from the number of distinct operators, distinct operands, and total number of occurrences of operators and operands. These metrics give an indication of the physical size of a program in terms of operators and operands and are used diagnostically to point to potential problems. McCabe's Cyclomatic Complexity Metrics (CCM) are compiled from flow charts transformed to equivalent directed graphs. The CCM is a measure of the total number of linearly independent paths through the code's control structure. These metrics were computed for the Ada mathematical functions library using Software Automated Verification and Validation (SAVVAS), the SSE IV and V tool. A table with selected results was shown, indicating that most of these routines are of good quality. Thresholds for the Halstead measures indicate poor quality if the length metric exceeds 260 or difficulty is greater than 190. The McCabe CCM indicated a high quality of software products.

Moebes, Travis↗

NASA NTRS1992

Validating a large geophysical data set: Experiences with satellite-derived cloud parameters

We are validating the global cloud parameters derived from the satellite-borne HIRS2 and MSU atmospheric sounding instrument measurements, and are using the analysis of these data as one prototype for studying large geophysical data sets in general. The HIRS2/MSU data set contains a total of 40 physical parameters, filling 25 MB/day; raw HIRS2/MSU data are available for a period exceeding 10 years. Validation involves developing a quantitative sense for the physical meaning of the derived parameters over the range of environmental conditions sampled. This is accomplished by comparing the spatial and temporal distributions of the derived quantities with similar measurements made using other techniques, and with model results. The data handling needed for this work is possible only with the help of a suite of interactive graphical and numerical analysis tools. Level 3 (gridded) data is the common form in which large data sets of this type are distributed for scientific analysis. We find that Level 3 data is inadequate for the data comparisons required for validation. Level 2 data (individual measurements in geophysical units) is needed. A sampling problem arises when individual measurements, which are not uniformly distributed in space or time, are used for the comparisons. Standard 'interpolation' methods involve fitting the measurements for each data set to surfaces, which are then compared. We are experimenting with formal criteria for selecting geographical regions, based upon the spatial frequency and variability of measurements, that allow us to quantify the uncertainty due to sampling. As part of this project, we are also dealing with ways to keep track of constraints placed on the output by assumptions made in the computer code. The need to work with Level 2 data introduces a number of other data handling issues, such as accessing data files across machine types, meeting large data storage requirements, accessing other validated data sets, processing speed and throughput for interactive graphical work, and problems relating to graphical interfaces.

Kahn, Ralph↗

NASA NTRS1999

Carbon-Carbon Piston Architectures

An improved structure for carbon-carbon composite piston architectures consists of replacing the knitted fiber, three-dimensional piston preform architecture described in U.S. Pat. No. 4.909,133 (Taylor et al.) with a two-dimensional lay-up or molding of carbon fiber fabric or tape. Initially. the carbon fabric or tape layers are prepregged with carbonaceous organic resins and/or pitches and are laid up or molded about a mandrel. to form a carbon-fiber reinforced organic-matrix composite part shaped like a "U" channel, a "T"-bar. or a combination of the two. The molded carbon-fiber reinforced organic-matrix composite part is then pyrolized in an inert atmosphere, to convert the organic matrix materials to carbon. At this point, cylindrical piston blanks are cored from the "U" channel, "T"-bar, or combination part. These blanks are then densified by reimpregnation with resins or pitches which are subsequently carbonized. Densification is also be accomplished by direct infiltration with carbon by vapor deposition processes. Once the desired density has been achieved, the piston billets are machined to final piston dimensions; coated with oxidation sealants; and/or coated with a catalyst. When compared to conventional steel or aluminum-alloy pistons, the use of carbon-carbon composite pistons reduces the overall weight of the engine; allows for operation at higher temperatures without a loss of strength; allows for quieter operation; reduces the heat loss; and reduces the level of hydrocarbon emissions.

Rivers, H. Kevin↗

NASA NTRS1999

Method of Fabricating Chopped-Fiber Composite Piston

A three-dimensional piston molding is fabricated from a mixture of chopped, carbon tow filaments of variable length, which are prepregged with carbonaceous organic resins and/or pitches and molded by conventional molding processes into a near net shape, to form a carbon-fiber reinforced organic-matrix composite part. Continuous reinforcement in the form of carbon-carbon composite tapes or pieces of fabric can be also laid in the mold before or during the charging of the mold with the chopped-fiber mixture, to enhance the strength in the crown and wrist-pin areas. The molded chopped-fiber reinforced organic-matrix composite parts are then pyrolized in an inert atmosphere, to convert the organic matrix materials to carbon. These pyrolized parts are then densified by reimpregnation with resins or pitches, which are subsequently carbonized. Densification is also accomplished by direct infiltration with carbon by vapor deposition processes. Once the desired density has been achieved, the piston molds are machined to final piston dimensions, and piston ring grooves are added. To prevent oxidation and/or to seal the piston surface or near surface, the chopped-fiber piston is coated with ceramic and/or metallic sealants: and/or coated with a catalyst.

Rivers, H. Kevin↗

NASA NTRS2000

Carbon-Carbon Piston Architectures

An improved structure for carbon-carbon composite piston architectures is disclosed. The improvement consists of replacing the knitted fiber, three-dimensional piston preform architecture described in U.S. Pat.No. 4,909,133 (Taylor et al.) with a two-dimensional lay-up or molding of carbon fiber fabric or tape. Initially, the carbon fabric of tape layers are prepregged with carbonaceous organic resins and/or pitches and are laid up or molded about a mandrel, to form a carbon-fiber reinforced organic-matrix composite part shaped like a "U" channel, a "T"-bar, or a combination of the two. The molded carbon-fiber reinforced organic-matrix composite part is then pyrolized in an inert atmosphere, to convert the organic matrix materials to carbon. At this point, cylindrical piston blanks are cored from the "U"-channel, "T"-bar, or combination part. These blanks are then densified by reimpregnation with resins or pitches which are subsequently carbonized. Densification is also accomplished by direct infiltration with carbon by vapor deposition processes. Once the desired density has been achieved, the piston billets are machined to final piston dimensions; coated with oxidation sealants; and/or coated with a catalyst. When compared to conventional steel or aluminum alloy pistons, the use of carbon-carbon composite pistons reduces the overall weight of the engine; allows for operation at higher temperatures without a loss of strength; allows for quieter operation; reduces the heat loss; and reduces the level of hydrocarbon emissions.

Rivers, H. Kevin↗

NASA NTRS1998

Automated Generation of Message-Passing Programs: An Evaluation Using CAPTools

Scientists at NASA Ames Research Center have been developing computational aeroscience applications on highly parallel architectures over the past ten years. During that same time period, a steady transition of hardware and system software also occurred, forcing us to expend great efforts into migrating and re-coding our applications. As applications and machine architectures become increasingly complex, the cost and time required for this process will become prohibitive. In this paper, we present the first set of results in our evaluation of interactive parallelization tools. In particular, we evaluate CAPTool's ability to parallelize computational aeroscience applications. CAPTools was tested on serial versions of the NAS Parallel Benchmarks and ARC3D, a computational fluid dynamics application, on two platforms: the SGI Origin 2000 and the Cray T3E. This evaluation includes performance, amount of user interaction required, limitations and portability. Based on these results, a discussion on the feasibility of computer aided parallelization of aerospace applications is presented along with suggestions for future work.

Hribar, Michelle R.↗

NASA NTRS2002

Automated Generation of Message-Passing Programs: An Evaluation Using CAPTools

Scientists at NASA Ames Research Center have been developing computational aeroscience applications on highly parallel architectures over the past ten years. During that same time period, a steady transition of hardware and system software also occurred, forcing us to expend great efforts into migrating and re-coding our applications. As applications and machine architectures become increasingly complex, the cost and time required for this process will become prohibitive. In this paper, we present the first set of results in our evaluation of interactive parallelization tools. In particular, we evaluate CAPTool's ability to parallelize computational aeroscience applications. CAPTools was tested on serial versions of the NAS Parallel Benchmarks and ARC3D, a computational fluid dynamics application, on two platforms: the SGI Origin 2000 and the Cray T3E. This evaluation includes performance, amount of user interaction required, limitations and portability. Based on these results, a discussion on the feasibility of computer aided parallelization of aerospace applications is presented along with suggestions for future work.

Hribar, Michelle R.↗

NASA NTRS2018

Knowledge Discovery Process: Case Study of RNAV Adherence of Radar Track Data

This talk is an introduction to the knowledge discovery process, beginning with: identifying the problem, choosing data sources, matching the appropriate machine learning tools, and reviewing the results. The overview will be given in the context of an ongoing study that is assessing RNAV adherence of commercial aircraft in the national airspace.

Machine Learning↗

NASA NTRSDate not supplied

Polar Resources Ice Mining Experiment-1 (PRIME-1) NASA’s First Polar Drilling and Volatiles Detection Mission

The US Administration announced in 2019 that NASA would return to the Moon where it would seek to establish a sustainable lunar presence. In Situ Resource Utilization (ISRU) is needed to sustain and grow hu-man surface exploration and it is therefore a vital part of ensuring this bold endeavor. ISRU requires ground-truth on physical, mineral, and volatile characteristics of the resources. Water, a key and game-changing resource, exists in the polar regions of the Moon. Learning to harvest and use this resource first requires understanding where the resource is abundantly located and on what scales. Harvested water, which is usable for life support and fuel, must be identified, quantified, and assessed for its mining feasibility. The project goal for PRIME-1 is to develop a flight-ready instrumentation package that can assess the volatiles at a polar lunar landing location. PRIME-1 is the combination of two instruments; Mass Spectrometer observing lunar operations (MSolo) and The Regolith and Ice Drill for Exploring New Terrain (TRIDENT). TRIDENT is an 1-meter augering drill capable of bringing incremental lunar regolith samples to the surface for volatile analysis. MSolo is a modified, commercial-off-the-shelf (COTS) mass spectrometer capable of qualifying and quantifying atomic species in the 1-100 amu range, including isotopic differentiation. These two lunar flight instruments operating together make up the PRIME-1 instrument suite. PRIME-1 intends to fly on and operate from a static lunar lander acquired by the NASA Commercial Lunar Payload Services (CLPS) acquisition process. The PRIME-1 payload suite was selected to fly on Intuitive Machines Nova-C lander, and is currently targeting a late Fall 2023 landing attempt.

MSolo↗

NASA NTRSDate not supplied

Polar Resources Ice Mining Experiment-1 (PRIME-1) NASA’s First Polar Drilling and Volatiles Detection Mission

The US Administration announced in 2019 that NASA would return to the Moon where it would seek to establish a sustainable lunar presence. In Situ Resource Utilization (ISRU) is needed to sustain and grow hu-man surface exploration and it is therefore a vital part of ensuring this bold endeavor. ISRU requires ground-truth on physical, mineral, and volatile characteristics of the resources. Water, a key and game-changing resource, exists in the polar regions of the Moon. Learning to harvest and use this resource first requires understanding where the resource is abundantly located and on what scales. Harvested water, which is usable for life support and fuel, must be identified, quantified, and assessed for its mining feasibility. The project goal for PRIME-1 is to develop a flight-ready instrumentation package that can assess the volatiles at a polar lunar landing location. PRIME-1 is the combination of two instruments; Mass Spectrometer observing lunar operations (MSolo) and The Regolith and Ice Drill for Exploring New Terrain (TRIDENT). TRIDENT is an 1-meter augering drill capable of bringing incremental lunar regolith samples to the surface for volatile analysis. MSolo is a modified, commercial-off-the-shelf (COTS) mass spectrometer capable of qualifying and quantifying atomic species in the 1-100 amu range, including isotopic differentiation. These two lunar flight instruments operating together make up the PRIME-1 instrument suite. PRIME-1 intends to fly on and operate from a static lunar lander acquired by the NASA Commercial Lunar Payload Services (CLPS) acquisition process. The PRIME-1 payload suite was selected to fly on Intuitive Machines Nova-C lander, and is currently targeting a late Fall 2023 landing attempt.

MSolo↗

NASA NTRSDate not supplied

Statistical Classification of Biosignature Information using Multiple Instrument Observations

The accurate identification of biosignatures (indications of life) from data taken from remote or in situ planetary exploration is one of the most important challenges in astrobiology, the interdisciplinary field examining habitability and the potential for extraterrestrial life. This study employs machine learning algorithms to optimize the identification of biosignatures, with an emphasis on those which are agnostic to a specific biochemical basis. We exploit the wealth of terrestrial data available from biogenic and abiogenic systems to enhance efficient feature prioritization. Our dataset, pulled from public databases and laboratory recorded measurements, includes elemental abundance, isotopic fractionation, and VNIR/Raman spectra The data curation process included standardization for detection limits and ranges. Subsequent feature extraction yielded detailed inputs for machine learning, including combinations of elemental content, isotopic ratios, and parameters of spectral peaks and troughs. Feature significance was evaluated across diverse machine learning methodologies, such as k-nearest neighbors, logistic regression, Random Forest, support vector machines, and Gaussian Naïve Bayes, along with a combined voting classifier. We utilized Receiver Operating Characteristic Area Under the Curve (ROC AUC) across 2,000 50% test-train splits as a robust metric of model performance. Results revealed a promising ROC AUC of 0.853 for the combined voting classifier. Removing elemental abundance data notably reduced model accuracy (13% decrease in AUC), highlighting its critical role in biosignature detection. Several other individual data features exhibited significance within their respective data types, offering additional granularity. This research fortifies the relevance of machine learning to astrobiology, potentially enhancing life detection missions by allowing algorithmic prioritization of high-interest samples for further investigation. Future work will refine data standardization, expand the dataset to include more terrestrial systems, and incorporate convolutional neural networks for spectral feature extraction. The potential for public data sharing is also under exploration, reinforcing our commitment to collective scientific advancement.

Statistical↗

NASA NTRS1999

Volatiles Evolved from Soybean Products Intended for Use in Long Duration Space Missions

Soybeans have been baselined to be grown in a habitat (Advanced Life Support Systems Integration Test Bed, ALSSITB) intended for evaluating advanced life support systems developed for long duration missions to the Moon or Mars. The ALSSITB is being constructed at NASA-Johnson Space Center and is composed of 5 chambers (4.6 m x 11.3 m each) and an airlock joined by an interconnecting tunnel (3.7 m x 19.2 m). Processed soy products such as soy milk and soy bread are planned to be incorporated into a nutritionally sound, plant-based food system. Since all consumables will be recycled and reused, volatile compounds evolved during the manufacturing of these food products need to be quantified to assess their impact on this closed loop system. Soy milk was made in a prototype machine and bread in a commercial bread baking machine. These machines were each placed in a tightly closed chamber and, at the completion of the process, air volatiles were identified and quantified by GC/MS. For soy milk, ethanol, acetaldehyde, methanol, hexanal, propanal and acetone and for soybread, acetaldehyde, ethanol, N-propanol and ethyl acetate were detected in significant quantities. The crew members will spend an average of 180 days in the ALSSITB and it was estimated that 138 batches of soy milk will be processed in the tunnel and 130 loaves of soybread would be baked in the habitat chamber during their stay. The aforementioned volatiles would surpass the 180 day Spacecraft Maximum Allowable Concentrations (SMACs) if no means of scrubbing are adapted which would lead to toxic levels of these compounds. Therefore, sufficient means for eliminating the contribution of volatiles evolved from food processing and preparation equipment needs to be provided in the ALSSITB.

Vodovotz, Yael↗

NASA NTRS2022

(Preliminary) Effects of Ball Milling Zeolite Powders for Use in Additively Manufactured Solid Sorbents

Zeolite 13X is favorable to be used as an adsorbent in carbon dioxide (CO2) removal from the spacecraft cabin air. Reducing the size of the zeolite particles and particle size distribution is thought to increase the capacity of CO2 adsorption of the zeolite 13X powder, and potentially increase its manufacturability as a paste for additive manufacturing or slip casting. This paper will go into detail on the process of using ball milling in order to reduce particle size and particle size distribution of commercial zeolite 13X powder, as well as to characterize CO2 adsorption and manufacturability of the milled powder. Both dry and wet ball milling was analyzed during the experiment. Studies were also ran on the amount of time the powder was milled, rotational speed of the milling machine, ball to powder ratio, ball to jar ratio, and ethanol to powder ratio. The processed powder was then characterized through laser diffraction, SEM, and surface measurement techniques to show that particle size and particle size distribution could be reduced, and to show the effect of the reduced particle size and particle size distribution on CO2 adsorption and manufacturability.

zeolite↗

NASA NTRS1984

The Multimission Image Processing Laboratory's virtual frame buffer interface

Large image processing systems use multiple frame buffers with differing architectures and vendor supplied interfaces. This variety of architectures and interfaces creates software development, maintenance and portability problems for application programs. Several machine-dependent graphics standards such as ANSI Core and GKS are available, but none of them are adequate for image processing. Therefore, the Multimission Image Processing laboratory project has implemented a programmer level virtual frame buffer interface. This interface makes all frame buffers appear as a generic frame buffer with a specified set of characteristics. This document defines the virtual frame uffer interface and provides information such as FORTRAN subroutine definitions, frame buffer characteristics, sample programs, etc. It is intended to be used by application programmers and system programmers who are adding new frame buffers to a system.

Wolfe, T.↗

NASA NTRS2020

Data Accountability and Uncertainty Analysis for the Mars Science Laboratory

This paper presents machine learning-based approaches to automate and optimize the detection of volume loss for the downlink process of telemetry data from the Mars Curiosity Rover. The Curiosity observes volume loss and data corruption, requiring re-transmits from the rover and Ground Data System Analysts (GDSA) to monitor the data flow. To resolve this issue, we created a data pipeline to accumulate data from various data sources in the downlink process and detect where the data is missed. In this paper, we benchmarked different methodologies based on the accuracy and excitability of them to identify whether a downlink data that is received to the ground system is complete or incomplete. Our results show that machine learning methods can improve the performance of the GDSA by 55% while the user can diagnose why data is missed and provide an explanation for the data accountability problem.

Chowdhury, Ameera↗