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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

ACT University Collaboration Proposal: Role of manufacturing defects on material failure under dynamic loading for developing enhanced failure models and theories (Final Report)

Research on the tensile behavior of additively manufactured 316L stainless steel coupon specimens at increasing strain rates was conducted over the past year at Penn State. Dynamic loading rates into the 1000 1/s loading rates were performed on specimens with nearly 1.32” gage lengths. Stress-strain plots show ductile and plastic behavior well beyond 12% strain with necked specimens, having smaller effective gage lengths showing up to 56% ultimate strain. Additional tests performed on compact tension specimens helped with simulation work to understand the deformation behavior. Using finite elements, it was possible to determine the feasibility of a comprehensive experimental validation study towards an improved model for AM material failure – specifically, the Bai-Wierzbicki approach which accounts for lode angle and triaxiality. A non-significant number of tests are projected for eight specific failure nodes, with additional replicates to provide strain-rate capabilities to the existing formulation. One such correction factor is explored for quasi-static, notched specimens. Finally, stress intensity factor was explored using a set of compact-tension specimens which would also provide useful validation data for any simulation work.

36 MATERIALS SCIENCE↗
NASA NTRS1980

Cycles till failure of silver-zinc cells with completing failures modes: Preliminary data analysis

One hundred and twenty nine cells were run through charge-discharge cycles until failure. The experiment design was a variant of a central composite factorial in five factors. Preliminary data analysis consisted of response surface estimation of life. Batteries fail under two basic modes; a low voltage condition and an internal shorting condition. A competing failure modes analysis using maximum likelihood estimation for the extreme value life distribution was performed. Extensive diagnostics such as residual plotting and probability plotting were employed to verify data quality and choice of model.

Sidik, S. M.↗
NASA NTRS1990

Failure of the ERBE scanner instrument aboard NOAA 10 spacecraft and results of failure analysis

The Earth Radiation Budget Experiment (ERBE) scanner instrument on the NOAA 10 spacecraft malfunctioned on May 22, 1989, after more than 4 years of in-flight operation. After the failure, all instrument operational mode commands were tested and the resulting data analyzed. Details of the tests and analysis of output data are discussed therein. The radiometric and housekeeping data appear to be valid. However, the instrument will not correctly execute operational scan mode commands or the preprogrammed calibration sequences. The data indicate the problem is the result of a failure in the internal address decoding circuity in one of the ROM (read only memory) chips of the instrument computer.

Miller, J. B.↗
NASA NTRSDate not supplied

Synthetic Failure Mode Generation for Resilience Analysis and Failure Mechanism Discovery

Traditional risk-based design processes seek to mitigate operational hazards by manually identifying possible faults and corresponding mitigation strategies—a tedious process which critically relies on the designer’s limited knowledge. Resilience-based design, on the other hand, seeks to embody generic hazard-mitigating properties in the system to mitigate unknown hazards, often by modelling the system's response to potential hazardous events. This work adapts this approach to the traditional risk-based design process to synthetically generate hazardous modes, by representing them as a unique combination of internal component health-states which can then be injected and simulated in a model of the system failure dynamics. The design process may then reduce the risk of unknown internal hazards by iteratively mitigating the effects of these modes. The performance of this approach is evaluated in a model of an autonomous rover, where cluster analysis shows that elaborating the space of synthetic faults in the drive system using this approach uncovers a wider range of possible hazardous trajectories and failure consequences within each trajectory. However, this increase in hazard information comes at a high computational expense, highlighting the need for advanced, efficient methods to search and sample the hazard space.

Simulation↗
NASA NTRSDate not supplied

Synthetic Failure Mode Generation for Resilience Analysis and Failure Mechanism Discovery

Traditional risk-based design processes seek to mitigate operational hazards by manually identifying possible faults and corresponding mitigation strategies—a tedious process which critically relies on the designer’s limited knowledge. Resilience-based design, on the other hand, seeks to embody generic hazard-mitigating properties in the system to mitigate unknown hazards, often by modelling the system's response to potential hazardous events. This work adapts this approach to the traditional risk-based design process to synthetically generate hazardous modes, by representing them as a unique combination of internal component health-states which can then be injected and simulated in a model of the system failure dynamics. The design process may then reduce the risk of unknown internal hazards by iteratively mitigating the effects of these modes. The performance of this approach is evaluated in a model of an autonomous rover, where cluster analysis shows that elaborating the space of synthetic faults in the drive system using this approach uncovers a wider range of possible hazardous trajectories and failure consequences within each trajectory. However, this increase in hazard information comes at a high computational expense, highlighting the need for advanced, efficient methods to search and sample the hazard space.

Simulation↗
NASA NTRS2004

Genesis failure investigation report : JPL Failure Review Board, Avionics Sub-Team

On January 7, 2001, the Genesis spacecraft lifted off from Cape Canaveral. Its mission was to collect solar wind samples and return those samples to Earth for detailed analysis by scientists. The mission proceeded successfully for three-and-a-half years. On September 8, 2004, the spacecraft approached Earth, pointed the Sample Return Capsule (SRC) at its entry target, and then fired pyros that jettisoned the SRC. The SRC carried the valuable samples collected over the prior 29 months. The SRC also contained the requisite hardware (mechanisms, parachutes, and electronics) to manage the process of entry, descent, and landing (EDL). After entering Earthas atmosphere, the SRC was expected to open a drogue parachute. This should have been followed by a pyro event to release the drogue chute, and then by a pyro event to deploy the main parachute at an approximate elevation of 6.7 kilometers. As the SRC descended to the Utah landing site, helicopters were in position to capture the SRC before the capsule touched down. On September 8, 2004, observers of the SRCas triumphant return became concerned as the NASA announcer fell silent, and then became even more alarmed as they watched the spacecraft tumble as it streaked across the sky. Long-distance cameras clearly showed that the drogue parachute had not deployed properly. On September 9, 2004, General Eugene Tattini, Deputy Director of the Jet Propulsion Laboratory formed a Failure Review Board (FRB). This board was charged with investigating the cause of the Genesis mishap in close concert with the NASA Mishap Investigation Board (MIB). The JPL-FRB was populated with experts from within and external to the Jet Propulsion Laboratory. The JPL-FRB participated with the NASA-MIB through all phases of the investigation, working jointly and concurrently as one team to discover the facts of the mishap.

solar wind↗
DOE OSTI2021

Characterizing possible failure modes in physics-informed neural networks (characterizing-pinns-failure-modes) v0.1.0

This software provides an implementation of the physics-informed neural network setup for different differential equations. It provides a way to solve differential equations using machine learning, via a physical constraint term in the loss function. Physics-informed neural networks are a popular approach, but here, the failures of such an approach are characterized and better solutions and training procedures are provided.

Krishnapriyan, Aditi↗
NASA NTRS2005

Learning from Failures: Archiving and Designing with Failure and Risk

Identifying and mitigating risks during conceptual design remains an ongoing challenge. This work presents the results of collaborative efforts between The University of Missouri-Rolla and NASA Ames Research Center to examine how an early stage mission design team at NASA addresses risk, and, how a computational support tool can assist these designers in their tasks. Results of our observations are given in addition to a brief example of our implementation of a repository based computational tool that allows users to browse and search through archived failure and risk data as related to either physical artifacts or functionality.

VanWie, Michael↗
DOE OSTI2021

Evidence Theory Representations for Properties Associated With Weak Link/Strong Link Systems, Part 2: Failure Time and Failure Temperature

The use of evidence theory and associated cumulative plausibility functions (CPFs), cumulative belief functions (CBFs), cumulative distribution functions (CDFs), complementary cumulative plausibility functions (CCPFs), complementary cumulative belief functions (CCBFs), and complementary cumulative distribution functions (CCDFs) in the analysis of loss of assured safety (LOAS) for weak link (WL)/strong link (SL) systems is introduced and illustrated. Article content includes cumulative and complementary cumulative belief, plausibility, and probability for (i) time at which LOAS occurs for a one WL/two SL system, (ii) time at which a two-link system fails, (iii) temperature at which a two-link system fails, and (iv) temperature at which LOAS occurs for a one WL/two SL system. The presented results can be generalized to systems with more than one WL and two SLs.

42 ENGINEERING↗