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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Software Formal Inspections Standard

The purpose of this Standard is to define the requirements for a software inspection process aimed at detecting and eliminating defects as early as possible in the software life cycle. This process can be used for any documented product; however, this Standard focuses on its use for software products - i.e., software code, plans, manuals, etc. The process provides for the collection and analysis of inspection data to improve the inspection process as well as the quality of the software.

Wetherholt, Martha S.↗
NASA NTRS2011

Software Testing and Verification in Climate Model Development

Over the past 30 years most climate models have grown from relatively simple representations of a few atmospheric processes to a complex multi-disciplinary system. Computer infrastructure over that period has gone from punch card mainframes to modem parallel clusters. Model implementations have become complex, brittle, and increasingly difficult to extend and maintain. Existing verification processes for model implementations rely almost exclusively upon some combination of detailed analysis of output from full climate simulations and system-level regression tests. In additional to being quite costly in terms of developer time and computing resources, these testing methodologies are limited in terms of the types of defects that can be detected, isolated and diagnosed. Mitigating these weaknesses of coarse-grained testing with finer-grained "unit" tests has been perceived as cumbersome and counter-productive. In the commercial software sector, recent advances in tools and methodology have led to a renaissance for systematic fine-grained testing. We discuss the availability of analogous tools for scientific software and examine benefits that similar testing methodologies could bring to climate modeling software. We describe the unique challenges faced when testing complex numerical algorithms and suggest techniques to minimize and/or eliminate the difficulties.

Clune, Thomas L.↗
DOE OSTI2024

Characterizing structural features of two-dimensional particle systems through Voronoi topology

This paper introduces a new approach toward characterizing local structural features of two-dimensional particle systems. The approach can accurately identify and characterize defects in high-temperature crystals, distinguish a wide range of nominally disordered systems, and robustly describe complex structures such as grain boundaries. This paper also introduces two-dimensional functionality into the open-source software program VoroTop which automates this analysis. This software package is built on a recently-introduced multithreaded version of V ORO ++, enabling the analysis of systems with billions of particles on high-performance computer architectures.

36 MATERIALS SCIENCE↗
NASA NTRS2012

In-Situ Nondestructive Evaluation of Kevlar(Registered Trademark)and Carbon Fiber Reinforced Composite Micromechanics for Improved Composite Overwrapped Pressure Vessel Health Monitoring

NASA has been faced with recertification and life extension issues for epoxy-impregnated Kevlar 49 (K/Ep) and carbon (C/Ep) composite overwrapped pressure vessels (COPVs) used in various systems on the Space Shuttle and International Space Station, respectively. Each COPV has varying criticality, damage and repair histories, time at pressure, and pressure cycles. COPVs are of particular concern due to the insidious and catastrophic burst-before-leak failure mode caused by stress rupture (SR) of the composite overwrap. SR life has been defined [1] as the minimum time during which the composite maintains structural integrity considering the combined effects of stress level(s), time at stress level(s), and associated environment. SR has none of the features of predictability associated with metal pressure vessels, such as crack geometry, growth rate and size, or other features that lend themselves to nondestructive evaluation (NDE). In essence, the variability or surprise factor associated with SR cannot be eliminated. C/Ep COPVs are also susceptible to impact damage that can lead to reduced burst pressure even when the amount of damage to the COPV is below the visual detection threshold [2], thus necessitating implementation of a mechanical damage control plan [1]. Last, COPVs can also fail prematurely due to material or design noncompliance. In each case (SR, impact or noncompliance), out-of-family behavior is expected leading to a higher probability of failure at a given stress, hence, greater uncertainty in performance. For these reasons, NASA has been actively engaged in research to develop NDE methods that can be used during post-manufacture qualification, in-service inspection, and in-situ structural health monitoring. Acoustic emission (AE) is one of the more promising NDE techniques for detecting and monitoring, in real-time, the strain energy release and corresponding stress-wave propagation produced by actively growing flaws and defects in composite materials [3,4,5,6,7,8]. To gain further insight into the mechanisms responsible for composite rupture, broadband modal acoustic emission analysis was used. Also, since AE data reduction proved to be very time consuming, specialized data reduction software was written to automate the process.

Waller, Jess↗
NASA NTRSDate not supplied

Degradation of Carbon Fiber Microstructures Due to Oxidative Etch Pitting

In order to understand the influence of etch pits on the material properties of carbon fiber microstructures, we use the Porous Microstructure Analysis (PuMA) software to create realistic pitted structures from virgin fiber structures and then analyze their degradation as the degree of pitting increases. For that purpose, we developed a pitting module within PuMA that creates pits with user-defined geometry (shape, size) and distribution (defect density) on the surface of arbitrary microstructures. In this work, we consider FiberForm microstructures, which are commonly used as the base material for ablative thermal protection systems (TPS). Using the new pitting module, we mimic the evolution of etch pits on FiberForm as it occurs from oxidation in ablative heating environments, by first importing the virgin FiberForm structure from a micrograph scan and then imposing different pitting conditions by varying pit radii and defect densities. We then leverage PuMA’s capabilities to calculate material properties for each structure. The results clearly show the degradation of thermal conductivity and structural integrity as etch pits grow, and furthermore highlight the complex evolution of the surface topology, which results in significant changes of the flowgeometry and chemical gas-surface interactions. Furthermore, a comparison of these changes with the case of shrinking fibers, which has heretofore been the standard for modelling ablation of carbon structures, yields significant differences. For example, we observe the formation of small chunks of fibers as pits grow in size, which could be released into the surrounding flow environment as spallation particles. This motivates us to continue our efforts of modelling pitting as an integral part of the structural degradation of carbon fiber structures in oxidation environments, which will ultimately improve our understanding of failure mechanisms in those materials.

PuMA↗
NASA NTRSDate not supplied

Degradation of Carbon Fiber Microstructures Due to Oxidative Etch Pitting

In order to understand the influence of etch pits on the material properties of carbon fiber microstructures, we use the Porous Microstructure Analysis (PuMA) software to create realistic pitted structures from virgin fiber structures and then analyze their degradation as the degree of pitting increases. For that purpose, we developed a pitting module within PuMA that creates pits with user-defined geometry (shape, size) and distribution (defect density) on the surface of arbitrary microstructures. In this work, we consider FiberForm microstructures, which are commonly used as the base material for ablative thermal protection systems (TPS). Using the new pitting module, we mimic the evolution of etch pits on FiberForm as it occurs from oxidation in ablative heating environments, by first importing the virgin FiberForm structure from a micrograph scan and then imposing different pitting conditions by varying pit radii and defect densities. We then leverage PuMA’s capabilities to calculate material properties for each structure. The results clearly show the degradation of thermal conductivity and structural integrity as etch pits grow, and furthermore highlight the complex evolution of the surface topology, which results in significant changes of the flowgeometry and chemical gas-surface interactions. Furthermore, a comparison of these changes with the case of shrinking fibers, which has heretofore been the standard for modelling ablation of carbon structures, yields significant differences. For example, we observe the formation of small chunks of fibers as pits grow in size, which could be released into the surrounding flow environment as spallation particles. This motivates us to continue our efforts of modelling pitting as an integral part of the structural degradation of carbon fiber structures in oxidation environments, which will ultimately improve our understanding of failure mechanisms in those materials.

PuMA↗
NASA NTRS1994

Robotic NDE inspection of advanced solid rocket motor casings

The Advanced Solid Rocket Motor program determined the need to inspect ASRM forgings and segments for potentially catastrophic defects. To minimize costs, an automated eddy current inspection system was designed and manufactured for inspection of ASRM forgings in the initial phases of production. This system utilizes custom manipulators and motion control algorithms and integrated six channel eddy current data acquisition and analysis hardware and software. Total system integration is through a personal computer based workcell controller. Segment inspection demands the use of a gantry robot for the EMAT/ET inspection system. The EMAT/ET system utilized similar mechanical compliancy and software logic to accommodate complex part geometries. EMAT provides volumetric inspection capability while eddy current is limited to surface and near surface inspection. Each aspect of the systems are applicable to other industries, such as, inspection of pressure vessels, weld inspection, and traditional ultrasonic inspection applications.

Mcneelege, Glenn E.↗
DOE OSTI2022

FY22 Progress Report: SRNL Analysis of ICCWR LCM and WAMS Data for Corrosion and Cracking

Algorithms for machine learning and data analysis for the 3013 Surveillance Program are being developed in an ongoing collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). To detect the presence of corrosion and cracking, data is collected from large binary files generated by a Laser Confocal Microscope (LCM) or Wide Area 3D Measurement System (WAMS). Software is being developed to use the physical attributes in the data files (e.g., height, color, and grayscale values; all as functions of a location in a plane projection) to detect the presence of surface corrosion and cracking. A user-friendly Matlab Graphical User Interface (GUI) that reads data from either LCM or WAMS files was developed to integrate input data with software developed for processing and evaluation. The GUI can selectively download binary data, interrogate data attributes, label data for training ML algorithms, flag significant features, execute Machine Learning (ML) algorithms, output parameters from trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. Surface defects can be called out by setting user-specified thresholds, feature based analysis or machine learning algorithms. Enhancements to data labeling capability have been developed to address this essential precursor to application of ML routines. Efficient labeling is particularly important in view of the very large volume of data required to train ML algorithms.

3013 Corrosion↗
NASA NTRS2003

Experimental Evaluation of Verification and Validation Tools on Martian Rover Software

To achieve its science objectives in deep space exploration, NASA has a need for science platform vehicles to autonomously make control decisions in a time frame that excludes intervention from Earth-based controllers. Round-trip light-time is one significant factor motivating autonomy capability, another factor is the need to reduce ground support operations cost. An unsolved problem potentially impeding the adoption of autonomy capability is the verification and validation of such software systems, which exhibit far more behaviors (and hence distinct execution paths in the software) than is typical in current deepspace platforms. Hence the need for a study to benchmark advanced Verification and Validation (V&V) tools on representative autonomy software. The objective of the study was to access the maturity of different technologies, to provide data indicative of potential synergies between them, and to identify gaps in the technologies with respect to the challenge of autonomy V&V. The study consisted of two parts: first, a set of relatively independent case studies of different tools on the same autonomy code, second a carefully controlled experiment with human participants on a subset of these technologies. This paper describes the second part of the study. Overall, nearly four hundred hours of data on human use of three different advanced V&V tools were accumulated, with a control group that used conventional testing methods. The experiment simulated four independent V&V teams debugging three successive versions of an executive controller for a Martian Rover. Defects were carefully seeded into the three versions based on a profile of defects from CVS logs that occurred in the actual development of the executive controller. The rest of the document is structured a s follows. In section 2 and 3, we respectively describe the tools used in the study and the rover software that was analyzed. In section 4 the methodology for the experiment is described; this includes the code preparation, seeding of defects, participant training and experimental setup. Next we give a qualitative overview of how the experiment went from the point of view of each technology; model checking (section 5), static analysis (section 6), runtime analysis (section 7) and testing (section 8). The find section gives some preliminary quantitative results on how the tools compared.

Brat, Guillaume↗
NASA NTRS1993

Applying formal methods and object-oriented analysis to existing flight software

Correctness is paramount for safety-critical software control systems. Critical software failures in medical radiation treatment, communications, and defense are familiar to the public. The significant quantity of software malfunctions regularly reported to the software engineering community, the laws concerning liability, and a recent NRC Aeronautics and Space Engineering Board report additionally motivate the use of error-reducing and defect detection software development techniques. The benefits of formal methods in requirements driven software development ('forward engineering') is well documented. One advantage of rigorously engineering software is that formal notations are precise, verifiable, and facilitate automated processing. This paper describes the application of formal methods to reverse engineering, where formal specifications are developed for a portion of the shuttle on-orbit digital autopilot (DAP). Three objectives of the project were to: demonstrate the use of formal methods on a shuttle application, facilitate the incorporation and validation of new requirements for the system, and verify the safety-critical properties to be exhibited by the software.

Cheng, Betty H. C.↗
NASA NTRS2016

Microarray Data Analysis of Space Grown Arabidopsis Leaves for Genes Important in Vascular Patterning

Venation patterning in leaves is a major determinant of photosynthesis efficiency because of its dependency on vascular transport of photoassimilates, water, and minerals. Arabidopsis thaliana grown in microgravity show delayed growth and leaf maturation. Gene expression data from the roots, hypocotyl, and leaves of A. thaliana grown during spaceflight vs. ground control analyzed by Affymetrix microarray are available through NASAs GeneLab (GLDS-7). We analyzed the data for differential expression of genes in leaves resulting from the effects of spaceflight on vascular patterning. Two genes were found by preliminary analysis to be upregulated during spaceflight that may be related to vascular formation. The genes are responsible for coding an ARGOS like protein (potentially affecting cell elongation in the leaves), and an F-boxkelch-repeat protein (possibly contributing to protoxylem specification). Further analysis that will focus on raw data quality assessment and a moderated t-test may further confirm upregulation of the two genes and/or identify other gene candidates. Plants defective in these genes will then be assessed for phenotype by the mapping and quantification of leaf vascular patterning by NASAs VESsel GENeration (VESGEN) software to model specific vascular differences of plants grown in spaceflight.

Weitzeal, A. J.↗
NASA NTRS2016

Microarray Data Analysis of Space Grown Arabidopsis Leaves for Genes Important in Vascular Patterning

Venation patterning in leaves is a major determinant of photosynthesis efficiency because of its dependency on vascular transport of photoassimilates, water, and minerals. Arabidopsis thaliana grown in microgravity show delayed growth and leaf maturation. Gene expression data from the roots, hypocotyl, and leaves of A. thaliana grown during spaceflight vs. ground control analyzed by Affymetrix microarray are available through NASA's GeneLab (GLDS-7). We analyzed the data for differential expression of genes in leaves resulting from the effects of spaceflight on vascular patterning. Two genes were found by preliminary analysis to be upregulated during spaceflight that may be related to vascular formation. The genes are responsible for coding an ARGOS like protein (potentially affecting cell elongation in the leaves), and an F-box/kelch-repeat protein (possibly contributing to protoxylem specification). Further analysis that will focus on raw data quality assessment and a moderated t-test may further confirm upregulation of the two genes and/or identify other gene candidates. Plants defective in these genes will then be assessed for phenotype by the mapping and quantification of leaf vascular patterning by NASA's VESsel GENeration (VESGEN) software to model specific vascular differences of plants grown in spaceflight.

Weitzeal, A. J.↗
NASA NTRS2009

Fully Employing Software Inspections Data

Software inspections provide a proven approach to quality assurance for software products of all kinds, including requirements, design, code, test plans, among others. Common to all inspections is the aim of finding and fixing defects as early as possible, and thereby providing cost savings by minimizing the amount of rework necessary later in the lifecycle. Measurement data, such as the number and type of found defects and the effort spent by the inspection team, provide not only direct feedback about the software product to the project team but are also valuable for process improvement activities. In this paper, we discuss NASA's use of software inspections and the rich set of data that has resulted. In particular, we present results from analysis of inspection data that illustrate the benefits of fully utilizing that data for process improvement at several levels. Examining such data across multiple inspections or projects allows team members to monitor and trigger cross project improvements. Such improvements may focus on the software development processes of the whole organization as well as improvements to the applied inspection process itself.

Shull, Forrest↗
NASA NTRS2016

Microarray Data Analysis of Space Grown Arabidopsis Leaves for Genes Important in Vascular Patterning

Venation patterning in leaves is a major determinant of photosynthesis efficiency because of its dependency on vascular transport of photo-assimilates, water, and minerals. Arabidopsis thaliana grown in microgravity show delayed growth and leaf maturation. Gene expression data from the roots, hypocotyl, and leaves of A. thaliana grown during spaceflight vs. ground control analyzed by Affymetrix microarray are available through NASA's GeneLab (GLDS-7). We analyzed the data for differential expression of genes in leaves resulting from the effects of spaceflight on vascular patterning. Two genes were found by preliminary analysis to be up-regulated during spaceflight that may be related to vascular formation. The genes are responsible for coding an ARGOS (Auxin-Regulated Gene Involved in Organ Size)-like protein (potentially affecting cell elongation in the leaves), and an F-box/kelch-repeat protein (possibly contributing to protoxylem specification). Further analysis that will focus on raw data quality assessment and a moderated t-test may further confirm up-regulation of the two genes and/or identify other gene candidates. Plants defective in these genes will then be assessed for phenotype by the mapping and quantification of leaf vascular patterning by NASA's VESsel GENeration (VESGEN) software to model specific vascular differences of plants grown in spaceflight.

venation↗
DOE OSTI2023

Automated Energy-Dispersive X-ray Spectroscopy Analysis for Multi-Modal Few-Shot Learning

Scanning transmission electron microscopy (STEM) is a powerful tool that allows for the atomic-scale analysis of a materials’ structure, chemistry, and defect domains (Akers et al. 2021). The current generation of microscopes generate vast amounts of data, surpassing the limits of effective manual analysis traditionally performed by domain experts (Spurgeon et al. 2021). While recent strides in machine learning have significantly enhanced the processing of large and intricate datasets acquired through electron microscopy, the prevalent use of proprietary software packages for initial data collection poses a challenge. In many cases, these software packages act as a ‘black box’, constraining user functionality and hindering the output of data in a format that is conducive to seamless integration into machine learning models. This work addresses these challenges by adapting HyperSpy, an open-source Python library, for the analysis and quantification of raw energy dispersive spectroscopy (EDS) data acquired through STEM. The modified HyperSpy code successfully facilitates user-defined segmentation of the data, enabling the integration of atomic %, weight %, and raw EDS spectra for each segmented region into an existing few-shot machine learning model. While initial results reveal discrepancies in quantified atomic and weight percentages when compared to proprietary software, ongoing efforts aim to rectify this issue by refining the fit of the HyperSpy model to the EDS spectra. Overall, this research underscores the potential of open-source tools like HyperSpy to enhance the accessibility of analytical tools, fostering a transparent and user-friendly environment for seamlessly incorporating electron microscopy data into machine learning models.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Combining machine-learned and empirical force fields with the parareal algorithm: application to the diffusion of atomistic defects

We numerically investigate an adaptive version of the parareal algorithm in the context of molecular dynamics. This adaptive variant has been originally introduced in [1]. We focus here on test cases of physical interest where the dynamics of the system is modelled by the Langevin equation and is simulated using the molecular dynamics software LAMMPS. In this work, the parareal algorithm uses a family of machine-learning spectral neighbor analysis potentials (SNAP) as fine, reference, potentials and embedded-atom method potentials (EAM) as coarse potentials. We consider a self-interstitial atom in a tungsten lattice and compute the average residence time of the system in metastable states. Our numerical results demonstrate significant computational gains using the adaptive parareal algorithm in comparison to a sequential integration of the Langevin dynamics. We also identify a large regime of numerical parameters for which statistical accuracy is reached without being a consequence of trajectorial accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Extrusion parameter control optimization for DIW 3D printing using image analysis techniques

Material extrusion is a well-recognized facet of additive manufacturing that involves the fabrication of parts through the deposition of structural material from an extrusion head from a bulk supply. In the subdivision of Direct Ink Writing (DIW) additive manufacturing, challenges arise when the structural material is flowable, synchronous extrusion control and tool movement becomes critical for achieving high-quality parts with low defect populations. DIW techniques are most used in laboratory settings using expensive custom instruments and may require specialized 3D slicing software. Here, in this study, the fabrication of an inexpensive, consumer-friendly progressive cavity pump dispensing system is detailed, in which can create high-quality parts by executing G-code commands produced from a commercial slicing software. The precision and repeatability of the movement-synchronized material extrusion is demonstrated through a series of optimization schemes, entailing the alteration of various control parameters, which directly affect the extrusion properties demonstrated during a print. In situ diagnostics were implemented to evaluate the results of the established optimization experiment. Using a machine vision technique, images of the optimization prints are processed. Following this, a supervised machine learning model was trained to autonomously judge whether or not the extrusion parameters produced a passing or failing result. The machine learning scheme serves as a preliminary benchmark for future layer-by-layer evaluation of more complex DIW parts. The construction of the printer and development of in situ characterization capabilities demonstrates the ability for this printer to create high-fidelity DIW parts for a fraction of the price of other systems.

42 ENGINEERING↗
NASA NTRS1992

Fracture mechanics expert system

Attention is given to fracture mechanics, an analytical method used extensively in the National Space Transportation System to conservatively predict the remaining service life of an article when a flaw or a material defect is detected. These analyses are performed on hardware containing material defects that have been detected by various nondestructive inspection techniques. An expert system being developed to streamline the process so that hardware dispositions may be obtained in a timely and consistent manner is discussed. The expert system reduces the potential for errors due to the manual transcription between the various software programs involved in completing a fracture mechanics analysis. NEXPERT Object, the expert system development shell selected for this purpose, allows the various software programs used in fracture mechanics analyses to be accessed and manipulated from the same platform.

Powers, E.↗