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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Non-destructive electrochemical diagnosis of failure mechanisms in aqueous zinc batteries

The early detection of secondary reactions that affect the life and performance of zinc manganese oxide batteries requires a shift from conventional time-consuming and often destructive procedures to rapid lifetime-predictive techniques. In this work, an electrochemical approach is employed to elucidate independent signatures for four common types of failure mechanisms in zinc manganese dioxide (Zn||MnO2) batteries—namely, the loss of zinc inventory, the loss of active material at the cathode, electrolyte depletion, and increased cell impedance. Our findings, specific to coin cell configurations, reveal that each induced failure mechanism can be distinctively modeled and identified based on responses from the rest voltage and columbic-efficiency data for prompt detection. For instance, electrolyte depletion response manifests a distinctive abrupt (>80 %) decrease in columbic efficiency (CE) and charge-rest voltage (Vc) while the discharge-rest voltage remained constant at ~1.3 V. Furthermore, electrolyte rejuvenation of the cell increased the CE to >95 % and restored Vc from ~0.3 to >1.7 V. Recovery experiments and reference performance tests demonstrated consistency between electrochemical descriptors and their associated failure mechanisms. Further, the outcomes of this work provide valuable insights and data models for some of the dominant failure mechanisms present in zinc manganese battery chemistries, which are beneficial to accelerated early-lifetime diagnosis and advancement of Zn batteries development.

25 ENERGY STORAGE↗
DOE OSTI2025

Numerical and experimental analysis of mechanically induced failure in electric vehicle battery modules

Mitigating thermal runaway and cell-to-cell propagation is essential for improving the safety of electric and hybrid vehicles. Enhancing digital twin capabilities to predict battery mechanical abuse is particularly critical for automotive and aerospace applications, where crashworthiness is a key concern. Understanding failure conditions and propagation in battery modules during mechanical abuse is complex due to interactions between structural deformation, heat transfer, electrochemical processes, exothermic reactions and mechanical fracture. While prior studies have focused on modeling cell-level behavior, extending these models to module or pack level is necessary for a system level understating of electric vehicle safety. This study develops coupled large deformation finite element models that simultaneously solve for electrochemistry, material failure, internal short circuit and thermal runaway propagation. The models account for mechanical and thermal interactions between lithium-ion cells and other battery components while the contact interfaces are evolving with time. Model-predicted voltage, temperature and force responses are compared with experimental data for validation. The results demonstrate that the approach captures key failure mechanisms, including thermal propagation through heat transfer, electrical propagation from short circuits in parallel-connected cells, and mechanical propagation via penetration and crack formation. These findings show that computational models are valuable tools for understanding battery module failure and providing insight that can reduce the need for extensive experimental testing.

25 ENERGY STORAGE↗
DOE OSTI2025

Rapid characterization and failure analysis of 6276 rooftop-harvested photovoltaic connectors

Photovoltaic (PV) connectors, which link modules in series and connect PV strings in parallel, have increasingly been recognized as a primary contributor to PV system failures and a source of numerous fire incidents. However, publicly available data on the rates and types of connector failures are scarce, primarily due to the proprietary nature of the information and the need for comprehensive analysis. This study represents the first large-scale investigation of harvested PV connectors, drawing from a dataset of 6276 connectors from residential rooftop solar systems across the United States. The outcome of this work is twofold: 1) we have established a rapid characterization method for large populations of harvested connectors, incorporating visual inspection, resistance measurements, and X-ray imaging; and 2) the analysis made possible by our rapid-processing method has revealed, for a population of connector models provided by a single rooftop installer, failure statistics and insights for various connector makes and models, installation practices, operating currents, and internal component displacements. This research identifies common failure modes that could be considered in future connector designs standards, and operations and maintenance practices, to ultimately improve the reliability of this vital component of PV infrastructure.

MC4↗
DOE OSTI2022

Failure Probability Constrained AC Optimal Power Flow

Despite cascading failures being the central cause of blackouts in power transmission systems, existing operational and planning decisions are made largely by ignoring their underlying cascade potential. This paper posits a reliability-aware AC Optimal Power Flow formulation that seeks to design a dispatch point which has a low operator-specified likelihood of triggering a cascade starting from any single component outage. By exploiting a recently developed analytical model of the probability of component failure, our Failure Probability-constrained ACOPF (FP-ACOPF) utilizes the system's expected first failure time as a smoothly tunable and interpretable signature of cascade risk. Here, we use techniques from bilevel optimization and numerical linear algebra to efficiently formulate and solve the FP-ACOPF using off-the-shelf solvers. Extensive simulations on the IEEE 118-bus case show that, when compared to the unconstrained and N-1 security-constrained ACOPF, our probability-constrained dispatch points can significantly lower the probabilities of long severe cascades and of large demand losses, while incurring only minor increases in total generation costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Hoop Tensile Failure Stress of 500 µm-Diameter Ceramic Spheres

The tensile failure stress of a brittle-material sphere is important to the survival of the sphere itself but is particularly relevant to systems that employ such spheres for applications in which the sphere exterior is subjected to tension during system fabrication or operation. That maximum hoop or tangential stress can be measured by diametrally compressing a C-sphere specimen directly machined from such spheres. This combination of specimen geometry and test method was conceived at Oak Ridge National Laboratory around 20 years ago. Although the C-sphere geometry has been tested with larger spheres, the ease and efficacy of its testing are unknown for submillimeter sphere diameters. To consider this, C-sphere specimens were machined from yttria-stabilized zirconia (YSZ) spheres of ∼500 µm diameter. The maximum (hoop or tangential) tensile stress was determined as a function of compressive failure force and specimen dimensions using finite element analysis. Companion effective area and volume as a function of Weibull modulus were computed. Hoop tensile failure stresses were then measured and fractography conducted to examine flaw type and location and to estimate the mirror constant of this YSZ grade. This novel study demonstrates that hoop tensile failure stress can be determined with sub-millimeter brittle-material spheres.

Delia, Daniel [ORNL] (ORCID:0000000209023239)↗
DOE OSTI2022

Mechanics-Driven Anode Material Failure in Battery Safety and Capacity Deterioration Issues: A Review

Abstract High-capacity anodes, such as Si, have attracted tremendous research interest over the last two decades because of the requirement for the high energy density of next-generation lithium-ion batteries (LIBs). The mechanical integrity and stability of such materials during cycling are critical because their volume considerably changes. The volume changes/deformation result in mechanical stresses, which lead to mechanical failures, including cracks, fragmentation, and debonding. These phenomena accelerate capacity fading during electrochemical cycling and thus limit the application of high-capacity anodes. Experimental studies have been performed to characterize the deformation and failure behavior of these high-capacity materials directly, providing fundamental insights into the degradation processes. Modeling works have focused on elucidating the underlying mechanisms and providing design tools for next-generation battery design. This review presents an overview of the fundamental understanding and theoretical analysis of the electrochemical degradation and safety issues of LIBs where mechanics dominates. We first introduce the stress generation and failure behavior of high-capacity anodes from the experimental and computational aspects, respectively. Then, we summarize and discuss the strategies of stress mitigation and failure suppression. Finally, we conclude the significant points and outlook critical bottlenecks in further developing and spreading high-capacity materials of LIBs.

Mechanics↗
DOE OSTI2021

Artificial Reasoning System for Symptom-Based Conditional Failure Probability Estimation Using Bayesian Network

Advances in nuclear power technologies require enhanced capabilities for operator advice and autonomous control. One of the first tasks in the development of such capabilities is the formulation of symptom-based conditional failure probabilities for structures, systems, and components (SSCs) of interest, for which the primary goal is to aid plant personnel in deducing the probabilistic performance status of the monitored SSCs and in detecting impending faults/failure. The task of conditional failure probability estimation is a bidirectional inference problem and shall be logically tackled by the Bayesian network (BN) approach. As a knowledge-based artificial intelligence tool and a probabilistic graphical model, BN offers the capability of reasoning under uncertainty and graphical representation emulating the physical behavior of the target SSC. This paper provides a systematic overview of the BN technique and the software tools for handling implementation of BN models, along with the associated knowledge representation and reasoning paradigm. Both operational data and expert judgement can be readily incorporated into the knowledge base of a BN model. The challenges with data availability are highlighted, and the general approach to target SSC identification is presented. Our focus is upon failure-prone and risk-important balance of plant assets, especially cases having strong operator involvement. An exemplary case study on the failure of a motor-driven centrifugal pump is also conducted to demonstrate the usefulness and technical feasibility of the proposed artificial reasoning system using an expert system shell.

Zhao, Xingang↗
DOE OSTI2020

Low-temperature failure mechanism of [001] niobium micropillars under uniaxial tension

The plasticity of body-centered cubic (bcc) metals is dependent of temperature as well as sample dimension at the micrometer scale, but the effects of cryogenic temperature on the plasticity and the related failure process in micron-sized bcc metals have not been studied under uniaxial tension. In this work, we utilized in situ cryogenic micro-tensile tests, transmission electron microscopy, and dislocation dynamic simulations to examine the plasticity and failure processes of [001]-oriented bcc niobium micropillars. Our study reveals that a strong suppression of cross-slip at low temperatures prevents dislocation multiplication and leads to a dislocation starvation state, at which no mobile dislocation exists due to the rapid annihilation of dislocations at free surfaces. New dislocations are then nucleated until stress concentration at a slip step creates a micro-crack, the propagation of which leads to catastrophic failure. As a result, this unique failure process results from the combined effects of sample dimension and temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Thermal-Mechanical Elastic-Plastic and Ductile Failure Model Calibrations for 6061-T651 Aluminum Alloy from Plate

Numerical simulations of metallic structures undergoing rapid loading into the plastic range require material models that accurately represent the response. In general, the material response can be seen as having four interrelated parts: the baseline response under slow loading, the effect of strain rate, the conversion of plastic work into heat and the effect of temperature. In essence, the material behaves in a thermal-mechanical manner if the loading is fast enough so when heat is generated by plastic deformation it raises the temperature and therefore influences the mechanical response. In these cases, appropriate models that can capture the aspects listed above are necessary. The matters of interest here are the elastic-plastic response and ductile failure behavior of 6061-T651 aluminum alloy under the conditions described above. The work was accomplished by first designing and conducting a material test program to provide data for the calibration of a modular $J_2$ plasticity model with isotropic hardening as well as a ductile failure model. Both included modules that accounted for temperature and strain rate dependence. The models were coupled with an adiabatic heating module to calculate the temperature rise due to the conversion of plastic work to heat. The test program included uniaxial tension tests conducted at room temperature, 150 and 300 C and at strain rates between 10 –4 and 10 3 1/s as well as four geometries of notched tension specimens and two tests on specimens with shear-dominated deformations. The test data collected allowed the calibration of both the plasticity and the ductile failure models. Most test specimens were extracted from a single piece of plate to maintain consistency. Notched tension tests came from a possibly different plate, but from the same lot. When using the model in structural finite element calculations, element formulations and sizes different from those used to model the test specimens in the calibration are likely to be used. A brief investigation demonstrated that the failure model can be particularly sensitive to the element selection and provided an initial guide to compensate in a specific example.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Tearing parameter failure integration with the multilevel solver.

The tearing parameter criterion and material softening failure method currently used in the multilinear elastic-plastic constitutive model was added as an option to modular failure capabilities. The modular failure implementation was integrated with the multilevel solver for multi-element simulations. Currently, this implementation is only available to the J 2 plasticity model due to the formulation of the material softening approach. The implementation compared well with multilinear elastic-plastic model results for a uniaxial tension test, a simple shear test, and a representative structural problem. Necessary generalizations of the failure method to extend it as a modular option for all plasticity models are highlighted.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Synthetic Sling Failure: Evaluations and Recommendations

The information and evaluations provided in this report were compiled to address the recurring problem of synthetic sling failure. As safety is the number one priority in all work aspects, a solution must be devised to prevent accidents from occurring. In revision 0, a total of thirteen cases regarding synthetic sling failure were evaluated in order to determine their causes, effects, and preventative measures. From the collected data, it was found that all cases in which the synthetic sling contacted the edge of its load resulted in sling failure. Revision 1 provides updated synthetic fling failures between the years of 2009 revision 0 and 2021 revision 1.

42 ENGINEERING↗
DOE OSTI2025

Preliminary System Interface Failure Mode Analysis for Two Advanced Reactors

This study explores two distinct Balance of Plant (BOP) configurations: the Rankine cycle for a sodium-cooled fast reactor (SFR) and the Brayton cycle for a gas-cooled reactor (GCR). As representative designs, the Power Reactor Innovative Small Module (PRISM) by GE Hitachi Nuclear Energy was selected for the SFR, while the Gas Turbine Modular Helium Reactor (GT MHR) by General Atomics was chosen for the gas-cooled reactor. Both configurations were adapted to deliver high-quality heat for industrial applications. A Failure Modes and Effects Analysis (FMEA) was conducted for each system to identify critical failure modes affecting key components. This study marks the first phase of a two-step design optimization approach, integrating FMEA into the design process. Based on the analysis, design modifications and mitigation strategies were proposed to enhance system resilience. The second phase, to be detailed in a subsequent report, will focus on the role of the control system in mitigating these failures. The FMEA serves as a foundation for defining the control topology, ensuring system resilience against component failures that could compromise essential functions, such as electricity and heat production.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Modeling the PV System Level Economic Impact of PV Connector Failure Modes

Photovoltaic (PV) connectors must maintain mechanical integrity for over 25 years while operating under UV exposure, elevated temperature, and mechanical loading. Connector degradation increases with electrical resistance, leading to energy losses, unplanned downtime, and higher operation and maintenance (O&M) costs and in severe cases, safety risks from overhearing or arcing. Connector related failures remain among the most frequent causes of disruption in utility-scale PV (UPV) systems, yet their lifetime economic impacts are poorly quantified. This work presents a techno-economic analysis (TEA) framework that links identified connector failure modes to system level energy losses and lifetime cost impacts using identified resistance measurements and failure rates from 6,2761 PV connectors inspected. Connector failures increase system level O&M costs, raising LCOE by roughly 5%. Downtime driven availability losses dominate economic impact. Resistance-driven I2R and IV-curve losses are secondary, but remain non-negligible. Thermal damage, bend-radius violations, and loose connections drive the majority of LCOE uplift Improving connector reliability through better installation quality, inspection, and design can meaningfully reduce lost energy, O&M costs, and LCOE.

14 SOLAR ENERGY↗
DOE OSTI2021

Fracture Network Localization Preceding Catastrophic Failure in Triaxial Compression Experiments on Rocks

We quantify the spatial distribution of fracture networks throughout six in situ X-ray tomography triaxial compression experiments on crystalline rocks at confining stresses of 5–35 MPa in order to quantify how fracture development controls the final macroscopic failure of the rock, a process analogous to those that control geohazards such as earthquakes and landslides. Tracking the proportion of the cumulative volume of fractures with volumes >90th percentile to the total fracture volume, ∑ v 90 / v t o t indicates that the fracture networks tend to increase in localization toward these largest fractures for up to 80% of the applied differential stress. The evolution of this metric also matches the evolution of the Gini coefficient, which measures the deviation of a population from uniformity. These results are consistent with observations of localizing low magnitude seismicity before large earthquakes in southern California. In both this analysis and the present work, phases of delocalization interrupt the general increase in localization preceding catastrophic failure, indicating that delocalization does not necessarily indicate a reduction of seismic hazard. However, the proportion of the maximum fracture volume to the total fracture volume does not increase monotonically. Experiments with higher confining stress tend to experience greater localization. To further quantify localization, we compare the geometry of the largest fractures, with volumes >90th percentile, to the best fit plane through these fractures immediately preceding failure. The r 2 scores and the mean distance of the fractures to the plane indicate greater localization in monzonite than in granite. The smaller mean mineral diameter and lower confining stress in the granite experiments may contribute to this result. Tracking these various metrics of localization reveals a close association between macroscopic yielding and the acceleration of fracture network localization. Near yielding, ∑ v 90 / v t o t and the Gini coefficient increase while the mean distance to the final failure plane decreases. Macroscopic yielding thus occurs when the rate of fracture network localization increases.

58 GEOSCIENCES↗
DOE OSTI2024

Combined ambient vibration and surface displacement measurements for improved progressive failure monitoring at a toppling rock slab in Utah, USA

Seismic resonance and surface displacement measurements can be implemented in tandem to improve landslide characterization and progressive failure monitoring. Crack aperture data are frequently used in rock slope stability monitoring and often exhibit recognizable trends prior to failure, such as accelerated crack opening. Alternatively, ambient resonance data offer multiple parameters including modal frequencies, damping, and polarization that can be monitored alongside crack aperture and may respond differently to environmental forcings and complex failure evolution. We analyzed data from continuous ambient vibration monitoring and concomitant crack aperture measurements at the Courthouse Mesa instability, a large toppling sandstone slab in Utah, USA. Three years of data revealed crack aperture increases of 2–4 mm/year with no clearly detectable irreversible changes in modal parameters, including frequency. Annually, frequency and displacement varied by 29% and 19% of the mean, respectively, with average and maximum daily frequency fluctuations of 6.5% and 16%, respectively. These reversible cyclic changes were primarily temperature-driven, but annually, frequency was in-phase with temperature whereas crack aperture lagged temperature changes by ~37 days. Polarization and damping also varied seasonally but were less strongly correlated with temperature. Conceptual 3D finite element modeling demonstrated consistent frequency decreases associated with crack propagation but variable changes in crack aperture measured at a single point; i.e., crack propagation did not always result in increased crack opening but always generated a resonance frequency decrease. Taken together, our data suggest a possible thermal wedging-ratcheting mechanism at the Courthouse Mesa instability, where annual thermoelastic crack closure is impeded by debris infill but the absence of downward crack propagation during the monitoring period is evidenced by no permanent resonance frequency changes. Our study demonstrates that combined seismic resonance and crack aperture data provide an improved description of rock slope instability behavior, supporting refined characterization and monitoring of changes accompanying progressive failure.

58 GEOSCIENCES↗
DOE OSTI2022

Wind Turbine Gearbox Failure Detection Through Cumulative Sum of Multivariate Time Series Data

The wind energy industry is continuously improving their operational and maintenance practice for reducing the levelized costs of energy. Anticipating failures in wind turbines enables early warnings and timely intervention, so that the costly corrective maintenance can be prevented to the largest extent possible. It also avoids production loss owing to prolonged unavailability. One critical element allowing early warning is the ability to accumulate small-magnitude symptoms resulting from the gradual degradation of wind turbine systems. Inspired by the cumulative sum control chart method, this study reports the development of a wind turbine failure detection method with such early warning capability. Specifically, the following key questions are addressed: what fault signals to accumulate, how long to accumulate, what offset to use, and how to set the alarm-triggering control limit. We apply the proposed approach to 2 years’ worth of Supervisory Control and Data Acquisition data recorded from five wind turbines. We focus our analysis on gearbox failure detection, in which the proposed approach demonstrates its ability to anticipate failure events with a good lead time.

17 WIND ENERGY↗
DOE OSTI2020

Prognosis of Wind Turbine Gearbox Bearing Failures Using SCADA and Modeled Data

Predictive maintenance and condition monitoring systems for wind turbines have seen increased adoption to minimize downtime, reducing operation and maintenance costs. On today’s wind power plants, the integrated supervisory control and data acquisition (SCADA) system provides low- frequency operational data that can be leveraged to quantify a wind turbine’s health. The aim of this study is to utilize machine-learning techniques to predict axial cracking failures in wind turbine gearbox bearings up to 1 month ahead of time. The failures are assumed to have occurred when the investigated bearing was replaced. While current SCADA systems show the overall condition of a wind turbine, often they do not allow for the investigation of specific gearbox bearings’ health. To enrich bearing fault signatures, additional data are computed through physics-based models using gearbox design information. Based on SCADA data, modeled data, and bearing failure log data from an actual wind plant, the performances of different machine-learning models on unseen data are then evaluated using industry-standard metrics such as precision, recall, and F1 score. Results show the overall system performance enhancement in predicting bearing failure when modeled data are included with SCADA data. The reduction in terms of false alarms is about 50%, and improvement in terms of precision and F1 score is about 33% and 12% respectively, based on the best modeling case in this study.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
NASA NTRS1972

Multimaterial lamination as a means of retarding penetration and spallation failures in plates

Experimental data are presented which show that hypervelocity impact spallation and penetration failures of a single solid aluminum plate and of a solid aluminum plate spaced a distance behind a Whipple meteor bumper may be retarded by replacing the solid aluminum plate with a laminated plate. Four sets of experiments were conducted. The first set of experiments was conducted with projectile mass and velocity held constant and with polycarbonate cylinders impacted into single plates of different construction. The second set of experiments was done with single plates of various construction and aluminum spherical projectiles of similar mass but different velocities. These two experiments showed that a laminated plate of aluminum and polycarbonate or aluminum and methyl methacrylate could prevent spallation and penetration failures with a lower areal density than either an all-aluminum laminated plate or a solid aluminum plate. The aluminum laminated plate was in turn superior to the solid aluminum plate in resisting spallation and penetration failures. In addition, through an example of 6061-T6 aluminum and methyl methacrylate, it is shown that a laminated structure ballistically superior to its parent materials may be built. The last two sets of experiments were conducted using bumper-protected main walls of solid aluminum and of laminated aluminum and polycarbonate. Again, under hypervelocity impact conditions, the laminated main walls were superior to the solid aluminum main walls in retarding spallation and penetration failures.

Dibattista, J. D.↗