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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Accelerated stress testing of amorphous silicon solar cells

A technique for performing accelerated stress tests of large-area thin a-Si solar cells is presented. A computer-controlled short-interval test system employing low-cost ac-powered ELH illumination and a simulated a-Si reference cell (seven individually bandpass-filtered zero-biased crystalline PIN photodiodes) calibrated to the response of an a-Si control cell is described and illustrated with flow diagrams, drawings, and graphs. Preliminary results indicate that while most tests of a program developed for c-Si cells are applicable to a-Si cells, spurious degradation may appear in a-Si cells tested at temperatures above 130 C.

Stoddard, W. G.↗
NASA NTRS2006

Stress Testing of Data-Communication Networks

NetStress is a computer program that stress-tests a data-communication network and components thereof. NetStress comprises two components running, respectively, in a transmitting system and a receiving system connected to a network under test

Leucht, Kurt↗
NASA NTRS1979

Transistor step stress testing program for JANTX2N2369A

The effect is reported of power/temperature step stress when applied to the transistor JANTX2N2369A manufactured by Raytheon and National Semiconductor. A total of 48 samples from each manufacturer was submitted to the process. In addition, two control sample units were maintained for verification of the electrical parametric testing. The power/thermal stress tests are described, and failure analyses are presented.

Source record↗
DOE OSTI2025

Stress Testing the Standard Model of Particle Physics at the Large Hadron Collider

Final technical report for the DOE grant "Stress Testing the Standard Model of Particle Physics at the Large Hadron Collider", awarded to Prof. Aram Apyan at Brandeis University. The work focused on the ATLAS experiment at LHC. During the award period the group worked on ATLAS physics analyses, all-silicon Inner Tracker (ITk) detector upgrade, and reconstruction and calibration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRSDate not supplied

Validation of Image-Based Neural Network Controllersthrough Adaptive Stress Testing

Neural networks have become state-of-the-art for computer vision problems because of their ability to efficiently model complex functions from large amounts of data. While neural networks can be shown to perform well empirically fora variety of tasks, their performance is difficult to guarantee.Neural network verification tools have been developed that can certify robustness with respect to a given input image; however,for neural network systems used in closed-loop controllers,robustness with respect to individual images does not address multi-step properties of the neural network controller and itsenvironment. Furthermore, neural network systems interacting in the physical world and using natural images are operating in a black-box environment, making formal verification in-tractable. This work combines the adaptive stress testing (AST)framework with neural network verification tools to search for the most likely sequence of image disturbances that cause the neural network controlled system to reach a failure. Anautonomous aircraft taxi application is presented, and results show that the AST method finds failures with more likely image disturbances than baseline methods. Further analysis of AST results revealed an explainable cause of the failure, giving insight into the problematic scenarios that should be addressed.

Adaptive Stress Testing, Marabou, Deep Neural Netw↗
NASA NTRS1993

Fixture For Hot Stress Tests Of Thin Specimens

Fixture designed to hold and heat thin, rectangular-cross-section specimen of composite material during hot lengthwise-stress test. Suitable for testing same specimen in either tension or compression. Clamps lightly onto specimen, providing both heat via thermal conduction and lateral support needed to prevent buckling during compression test.

Gates, Thomas S.↗
NASA NTRS1973

Use of the single-breath method of estimating cardiac output during exercise-stress testing.

The single-breath cardiac output measurement technique of Kim et al. (1966) has been modified for use in obtaining cardiac output measurements during exercise-stress tests on Apollo astronauts. The modifications involve the use of a respiratory mass spectrometer for data acquisition and a digital computer program for data analysis. The variation of the modified method for triplicate steady-state cardiac output measurements was plus or minus 1 liter/min. The combined physiological and methodological variation seen during a set of three exercise tests on a series of subjects was 1 to 2.5 liter/min. Comparison of the modified method with the direct Fick technique showed that although the single-breath values were consistently low, the scatter of data was small and the correlation between the two methods was high. Possible reasons for the low single-breath cardiac output values are discussed.

Buderer, M. C.↗
NASA NTRS1985

Repeatable electrical measurement instrumentation for use in the accelerated stress testing of thin film solar cells

Attention is given to the construction, calibration, and performance of a repeatable measurement system for use in conjunction with the accelerated stress testing of a-Si:H cells. A filtered diode array is utilized to approximate the spectral response of any type of solar cell in discrete portions of the spectrum. It is noted that in order to achieve the necessary degree of overall repeatability, it is necessary to pay particular attention to methods of contacting and positioning the cells.

Davis, C. W.↗
NASA NTRS1989

A prototype gas exchange monitor for exercise stress testing aboard NASA Space Station

This paper describes an easy-to-use monitor developed to track the weightlessness deconditioning aboard the NASA Space Station, together with the results of testing of a prototype instrument. The monitor measures the O2 uptake and CO2 production, and calculates the maximum O2 uptake and anaerobic threshold during an exercise stress test. The system uses two flowmeters in series to achieve a completely automatic calibration, and uses breath-by-breath compensation for sample line-transport delay. The monitor was evaluated using two laboratory methods and was shown to be accurate. The system's block diagram and the bench test setup diagram are included.

Orr, Joseph A.↗
NASA NTRS1982

Accelerated stress testing of terrestrial solar cells

The development of an accelerated test schedule for terrestrial solar cells is described. This schedule, based on anticipated failure modes deduced from a consideration of IC failure mechanisms, involves bias-temperature testing, humidity testing (including both 85-85 and pressure cooker stress), and thermal-cycle thermal-shock testing. Results are described for 12 different unencapsulated cell types. Both gradual electrical degradation and sudden catastrophic mechanical change were observed. These effects can be used to discriminate between cell types and technologies relative to their reliability attributes. Consideration is given to identifying laboratory failure modes which might lead to severe degradation in the field through second quadrant operation. Test results indicate that the ability of most cell types to withstand accelerated stress testing depends more on the manufacturer's design, processing, and worksmanship than on the particular metallization system. Preliminary tests comparing accelerated test results on encapsulated and unencapsulated cells are described.

Lathrop, J. W.↗
DOE OSTI2026

Using Explainable Artificial Intelligence to Predict Perovskite Solar Cell Electrical Metastability from Operando Photoluminescence Images in Accelerated Stress Testing

Metal halide perovskite (MHP) solar cells exhibit a metastable response to bias governed by coupled ionic–electronic processes, complicating the conventional reciprocity relation between luminescence intensity and device open-circuit voltage (V oc ). This limits the use of luminescence as a diagnostic for device screening or accelerated stress testing, motivating new approaches that can interpret photoluminescence (PL) signals under nonequilibrium conditions. From the artificial intelligence perspective, we develop an explainable deep learning framework that integrates convolutional neural networks (CNN), long short-term memory (LSTM) layers, and an attention mechanism to learn spatiotemporal features from operando photoluminescence PL image sequences. The model achieves a mean absolute error of ±0.027 V in predicting open-circuit voltage transients and reduces extreme-tail errors by up to 78% compared to physics-based reciprocity calculations. Gradient-weighted Class Activation Mapping (Grad-CAM) provides interpretability by highlighting physically meaningful regions such as electrode edges and emergent defect features. From the engineering application perspective, this framework enables accurate, contactless prediction of device V oc and identification of degradation-relevant features during accelerated aging of perovskite solar cells. This approach demonstrates how explainable AI can enhance operando diagnostics and reliability analysis in photovoltaic devices under nonequilibrium conditions.

14 SOLAR ENERGY↗
NASA NTRS1998

High-Temperature Slow Crack Growth of Silicon Carbide Determined by Constant-Stress-Rate and Constant-Stress Testing

High-temperature slow-crack-growth behaviour of hot-pressed silicon carbide was determined using both constant-stress-rate ("dynamic fatigue") and constant-stress ("static fatigue") testing in flexure at 1300 C in air. Slow crack growth was found to be a governing mechanism associated with failure of the material. Four estimation methods such as the individual data, the Weibull median, the arithmetic mean and the median deviation methods were used to determine the slow crack growth parameters. The four estimation methods were in good agreement for the constant-stress-rate testing with a small variation in the slow-crack-growth parameter, n, ranging from 28 to 36. By contrast, the variation in n between the four estimation methods was significant in the constant-stress testing with a somewhat wide range of n= 16 to 32.

Choi, Sung H.↗
DOE OSTI2024

Photovoltaic Cable Jackets: A Comparison of Representative Products Using Combined-Accelerated Stress Testing [Slides]

Photovoltaic (PV) cables facilitate the distribution of electricity collected from modules to the energy grid. Durable cabling enables continuous operation of PV installations, whereas cables with a lifetime less than the modules must be replaced - reducing electricity generation and adding to the operating expense. This study primarily focusses on the aging of the key cable types using the combined-accelerated stress testing (C-AST) protocol. Representative cables for utility, building, and control/auxiliary applications were examined. Cable jacket materials examined include: polyolefin, polyethylene, polyamide, poly(vinyl chloride), chlorinated polyethylene, thermoplastic elastomer, and ethylene propylene diene monomer rubber. Specimen characterizations applied include: optical microscopy, mechanical profilometry, instrumented indentation, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), Fourier-transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC). A variety of performance and durability characteristics were observed, depending on the base material, polymer formulation, and jacket color. The results from C-AST are analyzed and discussed relative to a recent industry survey on electronic balance of system components in addition to a recent study where similar cables were aged using steady state ultraviolet weathering (International Electrotechnical Commission Technical Specification 62788-7-2). Recommendations are made for the screening, industry qualification, and service life prediction of PV cable jackets.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRSDate not supplied

Adaptive Stress Testing of Collision Avoidance Systems for Small UASs with Deep Reinforcement Learning

The next-generation Airborne Collision Avoidance System for smaller UASs (ACAS sXu) is currently being developed and tested by the Federal Aviation Administration (FAA) to provide detect-and-avoid capability for small unmanned aircraft operating beyond line-of-sight. Due to the complexity and safety-critical nature of the system, safety validation is important not only for the certification of the final system, but also for informing changes during the iterative development process. In this paper, we analyze a prototype of ACAS sXu in simulated aircraft encounters to discover scenarios of small near mid-air collisions (sNMACs), an important safety event in which two aircraft come closer than 50 feet horizontally and 15 feet vertically. Due to the size and complexity of the system as well as rarity of sNMAC events, traditional methods such as Monte Carlo testing often require informed setup and targeting to elicit failures. However, such a dependence on domain knowledge can be incompatible with the independent verification and validation (IV&V) process, the aim of which is to discover unforeseen issues. To address these challenges, we apply an accelerated validation method called adaptive stress testing (AST) to find the most likely sNMAC scenarios without reliance on system introspection. AST uses reinforcement learning to adapt the search towards the most promising areas of the search space as it progresses. We use a state-of-the-art deep reinforcement learning algorithm, proximate policy optimization, to more efficiently search the large and continuous state space. We find that this approach significantly improves the performance of AST compared to a prior approach based on Monte Carlo tree search. We perform experiments using AST to find sNMAC events under various encounter configurations, varying parameters pertaining to dynamics and coordination. Our experiments show AST to be very effective at finding sNMAC scenarios. We summarize our findings, presenting high-level categories of discovered sNMACs and specific examples of encounters in each category.

aircraft collision avoidance↗
NASA NTRS2015

Adaptive Stress Testing of Airborne Collision Avoidance Systems

This paper presents a scalable method to efficiently search for the most likely state trajectory leading to an event given only a simulator of a system. Our approach uses a reinforcement learning formulation and solves it using Monte Carlo Tree Search (MCTS). The approach places very few requirements on the underlying system, requiring only that the simulator provide some basic controls, the ability to evaluate certain conditions, and a mechanism to control the stochasticity in the system. Access to the system state is not required, allowing the method to support systems with hidden state. The method is applied to stress test a prototype aircraft collision avoidance system to identify trajectories that are likely to lead to near mid-air collisions. We present results for both single and multi-threat encounters and discuss their relevance. Compared with direct Monte Carlo search, this MCTS method performs significantly better both in finding events and in maximizing their likelihood.

Verification and Validation↗