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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Discovering the Most Severe K-Point Failure Based on Reinforcement Learning: Preprint

Smart devices are essential to ensure the stability of the power grid and resilience to intermittent energy production. However, smart devices can also be the target of cyber adversaries that may exploit false data injection attacks (FDIAs) to induce unstable grid conditions. A practical consideration of FDIA mitigation approaches is addressed here: given a finite available budget, for which smart device should cyber-threat mitigation be deployed first? In this work, this question is answered by identifying the so-called most-sensitive devices, i.e., the devices that, if compromised, can let an adversary induce the most serious grid instabilities. The method proposed utilizes an adversarial reinforcement learning (RL) framework to identify the k-mostsensitive smart devices (here, smart inverters). The adversarial agent can tamper with the compromised inverters' active and reactive operating power setup points, with the goal of maximizing voltage deviations. Numerical results show that the proposed RL method finds the optimal attack scenarios for 1-point failure and the near-optimal solution for the 2-point case. Additionally, the proposed RL method achieves an 8.8 speed-up ratio in running time compared to the brute force method for the 2-point case.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Pore-Filling Induced Solid Electrolyte Failure of Ti-Doped Na 3 Zr 2 Si 2 PO 12 Characterized by Operando Synchrotron X-Ray Tomography

Solid-state batteries (SSBs), particularly those utilizing sodium metal, are emerging as a promising technology due to their potential for enhanced safety, higher energy density, and longer cycle life. NASICON (Na superionic conductor) materials, known for their robust crystalline structure and high ionic conductivity, are pivotal in the development of efficient sodium all-solid-state batteries. These materials exhibit high room-temperature ionic conductivity and electrochemical stability, making them ideal for various applications. Research has focused on improving NASICON's ionic conductivity and stability through doping, interface regulation, and composite anode design. Recent advancements include Ti-doped Na 3 Zr 2 Si 2 PO 12 (Ti-NZSP), which demonstrates improved surface stability, higher ionic conductivity, and increased critical current density. However, challenges such as Na dendrite formation and mechanical integrity under operational conditions persist. Advanced imaging techniques like operando synchrotron X-ray tomography have provided insights into failure mechanisms, revealing that pore-filling and dendrite growth are significant issues. Understanding these processes is essential for enhancing the performance and safety of Na-based SSBs. Here, this study underscores the need for continued research to address these challenges and develop reliable, high-performance solid-state electrolytes for future energy storage solutions.

25 ENERGY STORAGE↗
DOE OSTI2025

Damage progression and failure of SiC/SiC composite tubes under hard-contact radial expansion

The response of silicon carbide (SiC) fiber-reinforced SiC matrix (SiC/SiC) composite cladding to mechanical interaction with fissile fuel is a knowledge gap that must be overcome to design and assess SiC-based cladding systems for advanced nuclear applications. This study developed the relevant mechanical testing capability and identified the failure behavior and the critical microstructural features and processing defects. Sections of SiC composite tube were subjected to a modified expansion-due-to-compression (EDC) test in an X-ray computed tomography microscope: a polyurethane plug pressed surrogate Al 2 O 3 into the inner walls of the SiC/SiC composite tubes to achieve hard contact. A pure EDC test with just a polyurethane plug was also performed as a reference. Through the use of displacement fields, digital volume correlation revealed inhomogeneous deformation fields in the tubes, even for pure EDC, which was related to the inherent defects in the structure. Deep learning–aided segmentation and systematic data analysis revealed that the presence of inhomogeneous deformation applied by the hard contact was exaggerated by the presence of inner surface imperfections left behind from the matrix densification process. In conclusion, the findings provide insights into the applications, highlighting the necessity for improvements in inner surface roughness and the incorporation of localized contacts in pellet–cladding mechanical interaction computational models.

Composites↗
DOE OSTI2026

Acute wood smoke exposure is associated with cell-specific hippocampal transcriptomic responses in an accelerated ovarian failure mouse model

Background Wildfire events are increasing in frequency and intensity, and aging individuals demonstrate heightened biological susceptibility to air pollution exposures including increased risk of neurological sequelae. Declining ovarian hormones levels that occur with aging in females along with associated systemic physiological and inflammatory changes may contribute to increased cerebral vulnerability to air pollution, representing a potential but underexplored mechanism. Menopause and the menopausal transition represent a period of profound physiological change that affects cardiovascular, neurological, and immune health. Methods We tested whether peri-menopausal–like hormonal status amplifies hippocampal responses to acute wood smoke (WS) using an ovary-intact, 4-vinylcyclohexene diepoxide (VCD) model of moderate accelerated ovarian failure (AOF) in female C57BL/6 mice. Animals were exposed to HEPA-filtered air (FA) or WS for 4 h/day over 2 consecutive days (∼0.5 mg/m³). Exposure characterization confirmed a complex mixture of combustion products with significant levels of both trace metals and gas release during WS exposure. Results Spatial transcriptomics (10x Visium; n = 4 sections/group) with automated cell-type annotation identified astrocytes, GABAergic and glutamatergic neurons, oligodendrocytes, revealed cell type-specific transcriptional alterations following WS exposure. Distinct transcriptional patterns were observed across all identified neuronal and glial cell populations. Conclusion Together, these findings define a cell-type specific transcriptomic framework describing how WS exposure and ovarian hormone decline interact to influence hippocampal responses and identify potential cellular pathways relevant to hippocampal vulnerability.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2025

Effect of reversible dislocation-based deformation on nanoparticle strain at failure

Molecular dynamics simulations are used to isolate and quantify the reversible and irreversible mechanisms that contribute to deformation in platinum nanoparticles under compression. Quantitative analysis reveals how the nucleation and entanglement of dislocations can lead to reversible dislocation-based deformation. Simulations run at different temperatures and loading conditions show that the formation of entangled dislocations is more likely at higher temperatures and is facilitated by loading orientations where dislocations nucleate on intersecting slip planes. The presence of entangled dislocations increases the strain at failure due to the ability of those dislocations to accommodate strain reversibly. The results are corroborated by the observation of similar entangled dislocation loops during in situ compression experiments on nanoparticles of the same material. Altogether, these findings provide insight into the role of dislocations in both reversible and irreversible deformation and their implications for nanoparticle stability and properties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Modelling the brittle failure of graphite induced by the controlled impact of runaway electrons in DIII-D

The thermo-mechanical response of an ATJ graphite sample to controlled runaway electron (RE) dissipation, realized in DIII-D, is modelled with a novel work-flow that features the RE orbit code KORC, the Monte Carlo particle transport code Geant4 and the finite element multiphysics software COMSOL. KORC provides the RE striking positions and momenta, Geant4 calculates the volumetric energy deposition and COMSOL simulates the thermoelastic response. Brittle failure is predicted according to the maximum normal stress criterion, which is suitable for ATJ graphite owing to its linear elastic behavior up to fracture and its isotropic mechanical properties. Measurements of the conducted energy, damage topology, explosion timing and blown-off material volume, impose a number of empirical constraints that suffice to distinguish between different RE impact scenarios and to identify RE parameters which provide the best match to the observations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Exploring Failure of Adhesively-Bonded Joints with Different Void Sizes at the Same Void Volume Fraction through A Micro-scale Numerical Modeling

This paper studied the effects of void sizes on the failure behavior of adhesively-bonded materials under global shear via micro-scale computational modeling. The numerical results indicate that large void sizes with increased distances between them at the same void volume fraction can alleviate the reduced joint strength of a weaker adherend-adhesive interface caused by interfacial voids. However, this is not the case for an adherend-adhesive interface with the interfacial tensile strength being sufficiently higher than the adhesive strength, showing the negligible effect on the joint strength due to various void sizes and the amount of interfacial voids. This preliminary investigation provides insightful information for scaling up the void size in the macro-scale computational modeling of joints, and enhances the understanding of the micro-mechanical adhesion in adherend-adhesive interfaces with different levels of bonding.

Qiao, Yao↗
DOE OSTI2025

Cracking the failure of lithium batteries

Lithium batteries that use a solid electrolyte have the potential to improve safety and increase the amount of stored energy . This makes solid-state electrochemical cells a promising option for electric vehicles and wearable devices. However, nonuniform plating or stripping of lithium at the interface between an anode (negative electrode) and the electrolyte during charging and discharging leads to growth of detrimental lithium filaments (dendrites) that short-circuit the battery cell. This problem even occurs when the battery operates at small currents. The underlying mechanism of this failure is not well understood. On page 311 of this issue, Wang et al. (1) report that structural defects accumulate in the lithium metal anode under repeated charging and discharging at a small current. This is similar to mechanical fatigue that is observed over longer periods of intermittent straining of a material. Here, the observation could guide the design of lithium batteries with increased life span.

25 ENERGY STORAGE↗
DOE OSTI2025

Influence of gradation on failure mode of saturated sand at particle scale

Extensive research has been reported in the literature to characterize the failure mode of dry sand using various experimental techniques such as surface optical imaging, photo-elastic materials, three-dimensional (3D) computed tomography (CT), and 3D synchrotron micro-computed tomography (SMT). However, there is a limited literature about the behavior of saturated sand. This paper presents the results of axisymmetric triaxial compression (ATC) experiments that were conducted on saturated sand specimens. The behavior of specimens composed of a uniform sand with grain size between US sieves #40 and #50 is compared to specimens conducted on the same sand that has a wider gradation. 3D SMT technique was used to acquire 3D scans while shearing the specimens to probe localized events that are completely missed or misinterpreted when analyzing ATC measurements based on global standard measurements. The results show a higher effective principal stress ratio (EPSR) for the non-uniform specimen and a thicker shear band when compared to uniform specimen.

Elnur, Mohammed [University of Tennessee]↗
DOE OSTI2025

Anomaly Detection in Seismic Data with Deep Learning: Application for Instrument Failure Detection and Forecasting

Seismic data quality assessment (QA) is the first and one of the most important steps before conducting any further data analysis. Traditional methods involve checking various metrics, such as spike detection and power spectral density, by setting strict thresholds or comparing data against synthetic benchmarks. However, these approaches often rely on pre-existing knowledge and assumptions about data anomalies, leading to potential misclassification of unusual cases. Here, in this study, we propose a deep autoencoder model, an unsupervised learning approach that evaluates data quality without making assumptions about normal and anomalous data, which can be used to identify deviations in recorded data that may indicate nascent instrument failure. We test the model with the U.S. International Monitoring System (IMS) seismic stations and demonstrate the capability of detecting anomalies on a monthly scale. This could prompt station operators to examine potential problems early, allowing sufficient time for instrument maintenance to prevent data outages. In addition, we use a new manually selected testing dataset to compare our model performance against two supervised machine learning (ML) approaches and a standard QA package, as baseline models. When applied to the dataset containing known data anomalies, performance of the supervised and unsupervised ML approaches is similar, with an accuracy of 88.1% for our model compared to ∼90% for the supervised ML approach and 78.2% for the standard QA package. Our model outperforms the baseline models when applied to new stations, where new types of data anomalies can be station-specific and not included in the training dataset. Finally, we show model transferability by training the model with data from the Global Seismograph Network only and applying it to the IMS network data. The results suggest that our model is generalizable and can be applied to new stations with good accuracy.

Lin, Jiun-Ting [Lawrence Livermore National Labora↗
DOE OSTI2024

Multiphysics Simulations of Nanofibrous High Power Targets for the Inference of Failure Modes

Fermilab s High Power Targetry Research and Development (HPT R&D) group have been developing and studying an electrospun nanofiber target concept to support the need for robust targets in future fixed target facilities. These nanofiber mats have demonstrated resistance to radiation damage, and the free motion of the individual fibers is expected to mitigate the cyclic stresses induced by a pulsed, high-power beam. To evaluate the efficacy of this concept, nanofiber mat samples have been sent by the HPT R&D group to the HiRadMat facility at CERN for prototypic thermal shock testing; the outcomes of these experiments show that the survivability of a nanofiber target depends on its construction parameters, in particular the packing density of the fibers. Samples with higher packing densities have consistently been destroyed by exposure to the HiRadMat beam, with a hole at the beam center visible, and layers of nanofibers peeled away from the center hole, whereas samples with lower densities have survived with limited damage. The exact reason for the failure of the higher density targets was unclear at the time of the original experiments, but the results of our recent multiphysics simulations which recreate the experiments support the hypothesis that the expansion and pressurization of the air inside the target after being heated by the pulsed beam is the cause; in a high density nanofiber mat, the motion of air through the pores of the mat is much more restricted, and induces a larger pressure on the fibers, blowing the mat apart. In this talk, we ll share the results of these simulations and discuss how they support this hypothesis.

Asztalos, Will↗
DOE OSTI2024

Failure Criteria and Temperature Dependent Elastic Constants in the 3-D Elastic Orthotropic Model

Recent points of emphasis in the Library of Advanced Materials for Engineering (LAMÉ) have been to enable flexibility in formulations via the adoption of a variety of modular frameworks. While more established phenomenologies such as plasticity and viscoelasticity have been considered, elastically orthotropic models (e.g. elastic_3D_orthotropic) have not. For the elasticity component, not much can be modularized. However, a potential feature of interest would be the evaluation of failure criteria to consider the possibility of damage. Many such forms exist in the literature providing a good basis for modularity.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Assessment of Potential Failure Modes and Effects for On-Board Components for Hydrogen-Powered Locomotives

Hydrogen fuel sources offer alternatives to conventional fuels in the rail transportation industry. Hydrogen powered locomotive designs utilizing either a fuel cell or an internal combustion engine can make migration to alternative fuels possible for rail transportation. Codes and standards are still in development for rail application of hydrogen and safety risks must be assessed for hydrogen locomotive applications. This report utilizes a failure mode & effects analysis framework to help qualitatively understand possible risks from a hydrogen locomotive system. Findings illustrate how a combination of three mitigations greatly reduces the risks from a hydrogen locomotive system.

08 HYDROGEN↗
DOE OSTI2024

An outbreak of renal failure in asian dogs due to s-triazine adulteration of pet food raw material: Analysis of unique, green kidney stones formed as a result

Renoliths were removed at necropsy from dogs that had died from acute kidney injury in Asia in 2004 and submitted to our laboratories for analysis including elemental composition, mass spectrometry, and microprobe analysis. The presence of a mixed s-triazine matrix comprising melamine, cyanuric acid, and ammelide, but no detectable ammeline, was found in the stone samples we analyzed. The unusual and unique green coloration of these stones was determined to be due to the presence of biliverdin. The occurrence of these green stones distinguished the 2004 incident from another incident in 2007 in the USA and other reported cases. The presence of crystals was reported in renal tubules and collecting ducts in both outbreaks, but no stones were reported in the 2007 incident. Here, this difference suggested a variation in the disease process caused by mixed s- triazine ingestion. Careful monitoring of food additives is warranted to prevent future problems in animals and humans.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Physics of Failure Analysis of Nuclear Fusion Divertor Monoblock: An Analytical Approach

Original - A slide package that summarizes research progress of 2025 summer high school internship. To be presented at an internal group presentation to all the high school interns and mentors within C200, plus potential more interested audience from INL. Revision - Based on the original LRS-approved slide package, an updated slide package and a poster were prepared with slight changes (e.g., adjusting the layout of slides and reproducing some plots for better clarity) for the interns' final showcase on August 13. The showcase will be public-facing (i.e., not limited to INL attendees).

99 - GENERAL AND MISCELLANEOUS↗