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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 109 records · Page 6

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↗

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↗

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]↗

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↗

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↗

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↗

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↗

Status Report on Fast Flux Test Facility Mechanistic Fuel Failure Experiment Analysis with BISON for Post Irradiation Examination Support

The renewed interest in metallic U-Zr nuclear fuel alloy has led to a drive for deeper understanding of the mechanisms driving the phenomena observed under irradiation conditions. The Department of Energy Advanced Fuel Campaign has developed infrastructure to support metallic fuel development, including Post Irradiation Examination (PIE) of legacy Fast Flux Test Facility (FFTF) Mechanistic Fuel Failure (MFF) experiments. The PIE performed on legacy FFTF MFF experiments gives insight on metallic fuel performance and can address the lack of knowledge and scarcity of reliable data identified in several studies over recent years. Unfortunately, PIE efforts can cost significant time and resources which can impede the progress of metallic U-Zr fuel development. Metallic U-Zr fuel performance modeling can be used to inform PIE efforts on regions of interest for relevant investigations and can help understand phenomena observed in PIE. This report demonstrates the current progress of FFTF MFF fuel performance simulations using the BISON fuel performance code and discusses the support provided by simulation to PIE efforts. Progress in temperature, profilometry, fission gas release, plenum pressure, and zirconium redistribution simulation results have been demonstrated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

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 ↗

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↗

Failure of the large-N expansion in a bosonic tensor model

We study the tensor model generalization of the quantum p-spherical model in the large-N limit. While the tensor model has the same large-N expansion as the disordered quantum p-spherical model, its ground state is superextensive, in contradiction with large-N perturbation theory. Therefore, the large-N expansion of this model catastrophically fails at arbitrarily large-N, without any obvious signal in perturbation theory.

1/N Expansion↗

Environmental barrier coatings on SiC without a silicon bond coating: oxidation resistance, failure modes, and future improvements

Environmental barrier coatings (EBCs) are used to mitigate chemical reactions between SiC ceramic matrix composite (CMC) components and the H 2 O in combustion gas in turbine hot sections. CMCs are currently temperature-limited by the Si-bond coating, which melts at ~ 1414 °C. This work explores EBCs where the bond coating was removed to achieve higher operating temperatures. Various versions of enhanced roughness SiC were utilized to improve EBC adhesion to the substrates prior to 1 h furnace cycle testing in steam at 1250–1425 °C. The enhanced SiC roughness resulted in short coating lifetimes as the roughness was oxidized away with SiO 2 formation. Further, isothermal furnace exposures at 1400–1600 °C showed Yb 2 Si 2 O 7 /Yb 2 SiO 5 EBC microstructural changes, resulting in premature debonding from the substrates. Finally, this work provides baseline requirements for the development of both next-generation EBCs and bond coating strategies to overcome the current limitation of the Si-bond coating melting temperature.

36 MATERIALS SCIENCE↗