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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

ArcjetCV: Automating Recession Tracking

Arc jet Computer Vision (arcjetCV) is a software application built to automate time-resolved recession tracking of edges in test videos, specifically for tracking material recession and the shock-material standoff. This provides a new capability to resolve and validate new physics associated with non-linear processes and an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcticCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials and characterizing certain failure modes.

Recession tracking↗
NASA NTRSDate not supplied

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben D Phillips↗
NASA NTRSDate not supplied

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben Phillips↗
NASA NTRS1978

MBASIC batch processor architectural overview

The MBASIC (TM) batch processor, a language translator designed to operate in the MBASIC (TM) environment is described. Features include: (1) a CONVERT TO BATCH command, usable from the ready mode; and (2) translation of the users program in stages through several levels of intermediate language and optimization. The processor is to be designed and implemented in both machine-independent and machine-dependent sections. The architecture is planned so that optimization processes are transparent to the rest of the system and need not be included in the first design implementation cycle.

Reynolds, S. M.↗
NASA NTRS1988

Programming the Navier-Stokes computer: An abstract machine model and a visual editor

The Navier-Stokes computer is a parallel computer designed to solve Computational Fluid Dynamics problems. Each processor contains several floating point units which can be configured under program control to implement a vector pipeline with several inputs and outputs. Since the development of an effective compiler for this computer appears to be very difficult, machine level programming seems necessary and support tools for this process have been studied. These support tools are organized into a graphical program editor. A programming process is described by which appropriate computations may be efficiently implemented on the Navier-Stokes computer. The graphical editor would support this programming process, verifying various programmer choices for correctness and deducing values such as pipeline delays and network configurations. Step by step details are provided and demonstrated with two example programs.

Middleton, David↗
NASA NTRS1990

General method of pattern classification using the two-domain theory

Human beings judge patterns (such as images) by complex mental processes, some of which may not be known, while computing machines extract features. By representing the human judgements with simple measurements and reducing them and the machine extracted features to a common metric space and fitting them by regression, the judgements of human experts rendered on a sample of patterns may be imposed on a pattern population to provide automatic classification.

Rorvig, Mark E.↗
NASA NTRS1993

Electrical-Discharge Machining Of Curved Passages

Electrical-discharge machining (EDM) used to cut deep hole with bends. EDM process done with articulating segmented electrode. Originally straight, electrode curved as it penetrates part, forming long, smoothly curving hole. After hole cut, honed with slurry to remove thin layer of recast metal created by EDM. Breakage of tools, hand deburring, and drilling debris eliminated.

Guirguis, Kamal S.↗
NASA NTRS1993

General method of pattern classification using the two-domain theory

Human beings judge patterns (such as images) by complex mental processes, some of which may not be known, while computing machines extract features. By representing the human judgements with simple measurements and reducing them and the machine extracted features to a common metric space and fitting them by regression, the judgements of human experts rendered on a sample of patterns may be imposed on a pattern population to provide automatic classification.

Rorvig, Mark E.↗
NASA NTRS1995

Basic space payload fastener

A new basic space fastener has been developed and tested by the GSFC. The purposes of this fastener are to permit assembly and servicing in space by astronauts and/or robots and to facilitate qualification of payloads on Earth prior to launch by saving time and money during the systems integration and component testing and qualification processes. The space fastener is a rework of the basic machine screw such that crossthreading is impossible; it is self-locking and will not work its way out during launch (vibration proof); it will not wear out despite repeated use; it occupies a small foot print which is comparable to its machine screw equivalent, and it provides force and exhibits strength comparable to its machine screw equivalent. Construction is ultra-simple and cost effective and the principle is applicable across the full range of screw sizes ranging from a #10 screw to 2.5 cm (1 in) or more. In this paper, the fastener principles of operation will be discussed along with test results and construction details. The new fastener also has considerable potential in the commercial sector. A few promising applications will be presented.

Vranish, J. M.↗
NASA NTRS1995

Program Helps Decompose Complex Design Systems

DeMAID (Design Manager's Aid for Intelligent Decomposition) computer program is knowledge-based software system for ordering sequence of modules and identifying possible multilevel structure for design problems such as large platforms in outer space. Groups modular subsystems on basis of interactions among them. Saves considerable amount of money and time in total design process, particularly in new design problem in which order of modules has not been defined. Originally written for design problems, also applicable to problems containing modules (processes) that take inputs and generate outputs. Available in three machine versions: Macintosh written in Symantec's Think C 3.01, Sun, and SGI IRIS in C language.

Rogers, James L., Jr.↗
NASA NTRS1997

Precision Casting via Advanced Simulation and Manufacturing

A two-year program was conducted to develop and commercially implement selected casting manufacturing technologies to enable significant reductions in the costs of castings, increase the complexity and dimensional accuracy of castings, and reduce the development times for delivery of high quality castings. The industry-led R&D project was cost shared with NASA's Aerospace Industry Technology Program (AITP). The Rocketdyne Division of Boeing North American, Inc. served as the team lead with participation from Lockheed Martin, Ford Motor Company, Howmet Corporation, PCC Airfoils, General Electric, UES, Inc., University of Alabama, Auburn University, Robinson, Inc., Aracor, and NASA-LeRC. The technical effort was organized into four distinct tasks. The accomplishments reported herein. Task 1.0 developed advanced simulation technology for core molding. Ford headed up this task. On this program, a specialized core machine was designed and built. Task 2.0 focused on intelligent process control for precision core molding. Howmet led this effort. The primary focus of these experimental efforts was to characterize the process parameters that have a strong impact on dimensional control issues of injection molded cores during their fabrication. Task 3.0 developed and applied rapid prototyping to produce near net shape castings. Rocketdyne was responsible for this task. CAD files were generated using reverse engineering, rapid prototype patterns were fabricated using SLS and SLA, and castings produced and evaluated. Task 4.0 was aimed at developing technology transfer. Rocketdyne coordinated this task. Casting related technology, explored and evaluated in the first three tasks of this program, was implemented into manufacturing processes.

Source record↗
NASA NTRS2003

Processing at the Speed of Light

Spatial Light Modulators (SLMs) are critical elements in optical processing systems used for imaging, displaying, data storage, communications, and other applications. By taking advantage of the natural properties of light beams, the devices process information at speeds unattainable by human operators and most machines, with high-resolution results.Boulder Nonlinear Systems, Inc., is one of the world s foremost SLM manufacturers. Applications of this technology are briefly described.

Source record↗
NASA NTRS2004

Detailed Microstructural Characterization of the Disk Alloy ME3

The advanced powder metallurgy disk alloy ME3 was designed using statistical screening and optimization of composition and processing variables in the NASA/General Electric/Pratt & Whitney HSR/EPM disk program to have extended durability for large disks at maximum temperatures of 600 to 700 C. Scaled-up disks of this alloy were then produced at the conclusion of that program to demonstrate these properties in realistic disk shapes. The objective of the present study was to assess the microstructural characteristics of these ME3 disks at two consistent locations, in order to enable estimation of the variations in microstructure across each disk and across several disks of this advanced alloy. Scaled-up disks processed in the HSR/EPM Compressor/Turbine Disk program had been sectioned, machined into specimens, and tested in tensile, creep, fatigue, and fatigue crack growth tests by NASA Glenn Research Center, in cooperation with General Electric Engine Company and Pratt & Whitney Aircraft Engines. For this study, microstructures of grip sections from tensile specimens in the bore and rim were evaluated from these disks. The major and minor phases were identified and quantified using transmission electron microscopy (TEM). Particular attention was directed to the .' precipitates, which along with grain size can predominantly control the mechanical properties of superalloy disks.

Gabb, Timothy P.↗
NASA NTRS2005

A VHDL Core for Intrinsic Evolution of Discrete Time Filters with Signal Feedback

The design of an Evolvable Machine VHDL Core is presented, representing a discrete-time processing structure capable of supporting control system applications. This VHDL Core is implemented in an FPGA and is interfaced with an evolutionary algorithm implemented in firmware on a Digital Signal Processor (DSP) to create an evolvable system platform. The salient features of this architecture are presented. The capability to implement IIR filter structures is presented along with the results of the intrinsic evolution of a filter. The robustness of the evolved filter design is tested and its unique characteristics are described.

Gwaltney, David A.↗
NASA NTRS2004

Compact Microscope Imaging System With Intelligent Controls Improved

The Compact Microscope Imaging System (CMIS) with intelligent controls is a diagnostic microscope analysis tool with intelligent controls for use in space, industrial, medical, and security applications. This compact miniature microscope, which can perform tasks usually reserved for conventional microscopes, has unique advantages in the fields of microscopy, biomedical research, inline process inspection, and space science. Its unique approach integrates a machine vision technique with an instrumentation and control technique that provides intelligence via the use of adaptive neural networks. The CMIS system was developed at the NASA Glenn Research Center specifically for interface detection used for colloid hard spheres experiments; biological cell detection for patch clamping, cell movement, and tracking; and detection of anode and cathode defects for laboratory samples using microscope technology.

McDowell, Mark↗
NASA NTRS2005

Effects of High-Temperature Exposures on the Fatigue Life of Disk Superalloys Examined

Tests used to characterize the low-cycle-fatigue resistance of disk superalloys are usually performed at cyclic frequencies of 0.33 Hz or faster. However, service conditions for disks in some aerospace and land-based gas turbine engines can produce major cycle periods extending from minutes to hours and days. Over a service life, this can produce total service times near the maximum temperature that exceed 100 hr for aerospace applications and 100,000 hr for land-based applications. Such time-dependent effects of realistic mission cycles on fatigue resistance can be significant in superalloy disks, and need to be considered for accurate disk life prediction. The purpose of this study at the NASA Glenn Research Center was to examine the effects of extended exposures and extended cycle periods on the fatigue resistance of two disk superalloys. Current alloy Udimet 720 (Special Metals Corporation, Huntington, WV) disk material was provided by Solar Turbines/Caterpillar Co., and advanced alloy ME3 was provided by the NASA Ultra-Efficient Engine Technologies (UEET) Project, in powder-metallurgy-processed, supersolvus heat-treated form. Fatigue specimens were fully machined and exposed in air at temperatures of 650 to 704 C for extended times. Then, they were tested using conventional fatigue tests with a total strain range of 0.70 percent and a minimum-to-maximum strain ratio of zero to determine the effects of prior exposure on fatigue resistance. Subsequent tests with extended dwells at minimum strain in each fatigue cycle were performed to determine cyclic exposure effects.

Gabb, Timothy P.↗