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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 145 records · Page 8

Advanced Diagnosis and Accelerated Testing of Balance of System Components for Utility Scale PV Installations: October 1, 2022-September 30, 2024

A study of the durability of PV Balance of System components was performed. Specifically, wire cable jackets and cable connectors were examined within the direct current (DC) PV Power Transmission Chain (PTC). Degraded and failed samples have been obtained from utility PV installations to provide feedback on the degradation modes and the related damage-enabling considerations in today's PV systems. An industry interface group (including system owners, system inspectors, component manufacturers, and test labs) was used to help identify and obtain field-failed samples, for feedback (including samples and experimental design), and to facilitate the subsequent dissemination of the results of this study. Samples were empirically studied using accelerated stress testing with steady-state conditions (cable jackets) in addition to combined-accelerated stress testing (cable jackets, connectors and uncapped connectors). Steady-state accelerated testing has been performed using at least one applied stressor (e.g. UV light) to aid understanding of jacket durability relative to its application. Component- and material-focused failure analysis was conducted to develop an understanding and advise the PV industry. In-depth characterization will be applied selectively to field- and artificially aged-samples, to gain scientific understanding of the structural, chemical, electrical, mechanical, and thermal properties enabling degradation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Rover Attitude and Pointing System Simulation Testbed

The MER (Mars Exploration Rover) Attitude and Pointing System Simulation Testbed Environment (RAPSSTER) provides a simulation platform used for the development and test of GNC (guidance, navigation, and control) flight algorithm designs for the Mars rovers, which was specifically tailored to the MERs, but has since been used in the development of rover algorithms for the Mars Science Laboratory (MSL) as well. The software provides an integrated simulation and software testbed environment for the development of Mars rover attitude and pointing flight software. It provides an environment that is able to run the MER GNC flight software directly (as opposed to running an algorithmic model of the MER GNC flight code). This improves simulation fidelity and confidence in the results. Further more, the simulation environment allows the user to single step through its execution, pausing, and restarting at will. The system also provides for the introduction of simulated faults specific to Mars rover environments that cannot be replicated in other testbed platforms, to stress test the GNC flight algorithms under examination. The software provides facilities to do these stress tests in ways that cannot be done in the real-time flight system testbeds, such as time-jumping (both forwards and backwards), and introduction of simulated actuator faults that would be difficult, expensive, and/or destructive to implement in the real-time testbeds. Actual flight-quality codes can be incorporated back into the development-test suite of GNC developers, closing the loop between the GNC developers and the flight software developers. The software provides fully automated scripting, allowing multiple tests to be run with varying parameters, without human supervision.

Vanelli, Charles A.↗

High temperature ceramic interface study

Monolithic SiC and Si3N4 are susceptible to contact stress damage at static and sliding interfaces. Transformation-toughened zirconia (TTZ) was evaluated under sliding contact conditions to determine if the higher material fracture toughness would reduce the susceptibility to contact stress damage. Contact stress tests were conducted on four commercially available TTZ materials at normal loads ranging from 0.455 to 22.7 kg (1 to 50 pounds) at temperatures ranging from room temperature to 1204C (2200 F). Static and dynamic friction were measured as a function of temperature. Flexural strength measurements after these tests determined that the contact stress exposure did not reduce the strength of TTZ at contact loads of 0.455, 4.55, and 11.3 kg (1, 10, and 25 pounds). Prior testing with the lower toughness SiC and Si3N4 materials resulted in a substantial strength reduction at loads of only 4.55 and 11.3 kg (10 and 25 pounds). An increase in material toughness appears to improve ceramic material resistance to contact stress damage. Baseline material flexure strength was established and the stress rupture capability of TTZ was evaluated. Stress rupture tests determined that TTZ materials are susceptible to deformation due to creep and that aging of TTZ materials at elevated temperatures results in a reduction of material strength.

Lindberg, L. J.↗

Solar cell contacts

Two experimental contact systems were examined and compared to a baseline contact system consisting of evaporated layers of titanium, palladium, and silver and an electroplated layer of copper. The first experimental contact system consisted of evaporated layers of titanium, nickel, and copper and an electroplated layer of copper. This system performed as well as the baseline system in all respects, including its response to temperature stress tests, to a humidity test, and to an accelerated aging test. In addition, the cost of this system is estimated to be only 43 percent of the cost of the baseline system at a production level of 25 MW/year. The second experimental contact system consisted of evaporated layers of nickel and copper and an electroplated layer of copper. Cells with this system show serious degradation in a temperature stress test at 350 C for 30 minutes. Auger electron spectroscopy was used to show that the evaporated nickel layer is not an adequate barrier to copper diffusion even at temperatures as low as 250 C. This fact brings into question the long-term reliability of this contact system.

Meier, D. L.↗

Investigation of reliability attributes and accelerated stress factors on terrestrial solar cells

Three tasks were undertaken to investigate reliability attributes of terrestrial solar cells: (1) a study of the electrical behavior of cells in the second (reverse) quadrant; (2) the accelerated stress testing of three new state-of-the-art cells; and (3) the continued bias-temperature testing of four block 2 type silicon cells at 78 C and 135 C. Electrical characteristics measured in the second quadrant were determined to be a function of the cell's thermal behavior with breakdown depending on the initiation of localized heating. This implied that high breakdown cells may be more fault tolerant when forced to operate in the second quadrant, a result contrary to conventional thinking. The accelerated stress tests used in the first (power) quadrant were bias-temperature, bias-temperature-humidity, temperature-humidity, thermal shock, and thermal cycle. The new type cells measured included an EFG cell, a polycrystalline cell, and a Czochralski cell. Significant differences in the response to the various tests were observed between cell types. A microprocessed controlled, short interval solar cell tester was designed and construction initiated on a prototype.

Lathrop, J. W.↗

Discovery and Analysis of Rare High-Impact Failure Modes using Adversarial RL-Informed Sampling

Adaptive learning agents have tremendous potential to handle critical tasks currently performed by humans. Unfortunately, due to their complexity, it can be difficult to verify that these learning agents do not have critical failure modes. Standard verification and validation methods often do not apply directly to learning agents and Monte Carlo methods have difficulty covering even a small fraction of the state space, especially in multiagent systems or over long time horizons. To overcome this difficulty, we demonstrate an adaptive stress-testing method based on reinforcement learning of correlations that raise the probability of failure. This approach has three key properties: (1) it is able to find rare failure modes with far greater sample efficiency than Monte Carlo methods, (2) it can estimate the true probability of a failure mode despite the inherent bias in the learning method, and (3) it is capable of learning and resampling compact representations of multimodal failure spaces. These properties are important in practice as we need to find disparate failure modes while accounting for their actual relevance. This is a significant advantage over traditional adaptive stress testing methods that give abstract likelihoods of particular failure instances, but cannot estimate the probability of a broader failure mode. We test our algorithm on a simple problem from the aviation domain where an autonomous aircraft lands in gusty wind conditions. The results suggest that we can find failure modes with far fewer samples than the Monte Carlo approach and simultaneously estimate the probability of failure.

reinforcement learning↗

Discovery and Analysis of Rare High-Impact Failure Modes using Adversarial RL-Informed Sampling

Adaptive learning agents have tremendous potential to handle critical tasks currently performed by humans. Unfortunately, due to their complexity, it can be difficult to verify that these learning agents do not have critical failure modes. Standard verification and validation methods often do not apply directly to learning agents and Monte Carlo methods have difficulty covering even a small fraction of the state space, especially in multiagent systems or over long time horizons. To overcome this difficulty, we demonstrate an adaptive stress-testing method based on reinforcement learning of correlations that raise the probability of failure. This approach has three key properties: (1) it is able to find rare failure modes with far greater sample efficiency than Monte Carlo methods, (2) it can estimate the true probability of a failure mode despite the inherent bias in the learning method, and (3) it is capable of learning and resampling compact representations of multimodal failure spaces. These properties are important in practice as we need to find disparate failure modes while accounting for their actual relevance. This is a significant advantage over traditional adaptive stress testing methods that give abstract likelihoods of particular failure instances, but cannot estimate the probability of a broader failure mode. We test our algorithm on a simple problem from the aviation domain where an autonomous aircraft lands in gusty wind conditions. The results suggest that we can find failure modes with far fewer samples than the Monte Carlo approach and simultaneously estimate the probability of failure.

Validation↗

Discovery and Analysis of Rare High-Impact Failure Modes using Adversarial RL-Informed Sampling

Adaptive learning agents have tremendous potential to handle critical tasks currently performed by humans. Unfortunately, due to their complexity, it can be difficult to verify that these learning agents do not have critical failure modes. Standard verification and validation methods often do not apply directly to learning agents and Monte Carlo methods have difficulty covering even a small fraction of the state space, especially in multiagent systems or over long time horizons. To overcome this difficulty, we demonstrate an adaptive stress-testing method based on reinforcement learning of correlations that raise the probability of failure. This approach has three key properties: (1) it is able to find rare failure modes with far greater sample efficiency than Monte Carlo methods, (2) it can estimate the true probability of a failure mode despite the inherent bias in the learning method, and (3) it is capable of learning and resampling compact representations of multimodal failure spaces. These properties are important in practice as we need to find disparate failure modes while accounting for their actual relevance. This is a significant advantage over traditional adaptive stress testing methods that give abstract likelihoods of particular failure instances, but cannot estimate the probability of a broader failure mode. We test our algorithm on a simple problem from the aviation domain where an autonomous aircraft lands in gusty wind conditions. The results suggest that we can find failure modes with far fewer samples than the Monte Carlo approach and simultaneously estimate the probability of failure.

Validation↗

Drive Cycles, Battery Pack Scaling, and Usage Considerations for Long-Haul and Regional-Haul Electric Trucks

Electrifying Class-8 heavy-duty trucks presents a promising opportunity to enhance energy efficiency and reduce freight transport costs. Battery electric trucks (BETs), once considered niche, are gaining traction due to advancements in battery technology and cost reductions. However, accurately predicting battery lifespan under realistic usage conditions remains a key challenge. Understanding battery failure mechanisms and their links to design, operation, and management is essential for developers and fleet operators. This study introduces a method to develop simplified, lab-testable dynamic stress test (DST) cycles for regional and long-haul Class-8 BETs, derived from real-world diesel truck usage. These DSTs enable benchmarking of battery technologies, identification of aging stressors, and optimization of battery design, life, and cost. The approach supports evaluation of key metrics such as levelized cost of driving and total cost of ownership, aiding fair comparisons and adoption decisions. We also propose feasible battery pack sizes that meet current driving demands with strategic charging, and a method to scale pack-level DSTs to cell-level cycles for lab-based testing. These tools facilitate tradeoff analysis across battery chemistries, pack sizing, and charging strategies, while offering means to get insights into battery aging under realistic conditions-ultimately supporting informed BET deployment decisions.

25 ENERGY STORAGE↗

Automatic Blood Pressure Measurements During Exercise

Microprocessor circuits and a computer algorithm for automatically measuring blood pressure during ambulatory monitoring and exercise stress testing have been under development at SRI International. A system that records ECG, Korotkov sound, and arm cuff pressure for off-line calculation of blood pressure has been delivered to NASA, and an LSLE physiological monitoring system that performs the algorithm calculations in real-time is being constructed. The algorithm measures the time between the R-wave peaks and the corresponding Korotkov sound on-set (RK-interval). Since the curve of RK-interval versus cuff pressure during deflation is predictable and slowly varying, windows can be set around the curve to eliminate false Korotkov sound detections that result from noise. The slope of this curve, which will generally decrease during exercise, is the inverse of the systolic slope of the brachial artery pulse. In measurements taken during treadmill stress testing, the changes in slopes of subjects with coronary artery disease were markedly different from the changes in slopes of healthy subjects. Measurements of slope and O2 consumption were also made before and after ten days of bed rest during NASA/Ames Research Center bed rest studies. Typically, the maximum rate of O2 consumption during the post-bed rest test is less than the maximum rate during the pre-bed rest test. The post-bed rest slope changes differ from the pre-bed rest slope changes, and the differences are highly correlated with the drop in the maximum rate of O2 consumption. We speculate that the differences between pre- and post-bed rest slopes are due to a drop in heart contractility.

Weaver, Charles S.↗

SITCOMTN-162: Testing the implementation of Metadetection and Cell-Based Coadds on Abell 360 LSSTComCam data

The purpose of this technote is to test the technical quality of LSSTComCam commissioning data, specifically the Rubin_SV_38_7 field, by utilizing cell-based coadds and Metadetection by measuring the tangential and cross weak lensing shear profiles of the massive cluster Abell 360 (called A360 throughout the technote). The process entails generating the cell-based coadds for Metadetection to run on, identifying and removing cluster member galaxies, applying quality cuts, calibrating the shear measurements, and validation. Cell-based coadds and Metadetection are both currently in the process of being implemented within the LSST Science Pipelines at the time of this technote. There is substantial technical value in attempting a difficult measurement prior to full implementation. Measuring the tangential shear around A360 will showcase the current abilities of these algorithms, as well as highlight where work is still needed. As seen from the resulting shear profile of A360, the cell-based coadds and Metadetection are able to work in tandem to produce a shear catalog and resulting reduced shear profile. This technote is one part of a series studying A360 in order to both stress test the commissioning camera and demonstrate the technical capabilities of the Vera Rubin Observatory. We study the quality of the PSF modeling and impact it can have on cluster WL in [Combet et al., 2025], implementation of cell-based coadds and subsequent use for Metadetect [Sheldon et al., 2023] in this technote, photometric calibration in (in prep), source selection and photometric redshifts in [Adari et al., 2025], use of Anacal [Li et al., 2024] to produce a cluster shear profile in [Li et al., 2025], and background subtraction in this field and Fornax in [Zhou et al., 2025].

79 ASTRONOMY AND ASTROPHYSICS↗

Synthetic seawater as stress-corrosion test medium

Seawater minimizes pitting corrosion of aluminum-alloy test samples. Of three corrosion-inhibiting methods evaluated using (a) chromate inhibitors in saltwater, (b) surface treating sample via anodizing or alodine treatment, and (c) synthetic seawater, synthetic seawater was most effective test medium, since it is more uniform than fresh seawater.

Humphries, T. S.↗

Development of an unsteady aerodynamics model to improve correlation of computed blade stresses with test data

A reliable rotor aeroelastic analysis operational that correctly predicts the vibration levels for a helicopter is utilized to test various unsteady aerodynamics models with the objective of improving the correlation between test and theory. This analysis called Rotor Aeroelastic Vibration (RAVIB) computer program is based on a frequency domain forced response analysis which utilizes the transfer matrix techniques to model helicopter/rotor dynamic systems of varying degrees of complexity. The results for the AH-1G helicopter rotor were compared with the flight test data during high speed operation and they indicated a reasonably good correlation for the beamwise and chordwise blade bending moments, but for torsional moments the correlation was poor. As a result, a new aerodynamics model based on unstalled synthesized data derived from the large amplitude oscillating airfoil experiments was developed and tested.

Gangwani, S. T.↗

Evaluating Solid-Lubricant Films

Report describes experimental techniques for measuring properties of solid-lubricant films. Discusses experimental parameters. Reviews basic pin-on-disk configurations and methods of preparing disks and applying solid lubricants. Techniques for constant-temperature testing, low-contact-stress testing, and temperature-versus-time testing presented. Suggests methods of measuring pin-wear volume and recommends ways of presenting data.

Fusaro, Robert L.↗

Bearing-bypass loading in composite joints - Testing and stress analysis

A combined experimental and analytical study of bearing and bypass loading on single-fastener specimens of a 16-ply, quasi-isotropic T300/5208 graphite/epoxy laminate with a centrally located hole is reported. The specimens were loaded in either tension or compression, and onset damage, ultimate strengths, and corresponding failure modes were determined. The tension data showed the expected linear interaction for combined bearing-bypass loading with damage developing in the net-section tension mode. However, the bearing-onset strengths showed an unexpected interaction of the bearing and compressive bypass loads in which the latter reduced the bearing-onset strength. A linear finite element analysis showed that bearing-bypass loading had a marked influence on the bolt-hole contact which in turn had a significant effect on local stresses.

Crews, John H., Jr.↗