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At least 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Identifying human failure events (HFEs) for external hazard probabilistic risk assessment

In recent years, several advancements in nuclear power plant (NPP) probabilistic risk assessment (PRA) have been driven by increased understanding of external hazards, plant response, and uncertainties. However, major sources of uncertainty associated with external hazard PRA remain. One important source is how risk-significant human actions that are carried out to enable plant response and recovery from natural hazards cause the close coupling of physical impacts on plants and overall plant risk during these hazard events. This makes human reliability and human-plant interactions important elements to consider in resolving PRA gaps in external hazards. One of the challenges in considering human response in external hazard probabilistic risk assessment (XHPRA) is that most existing human reliability analysis (HRA) models were not developed for assessing actions outside the control room (termed ex-control room actions) and hazard response. To support this new scope, HRA models will need to be developed or modified to support identification of human activities, causal factors, and uncertainties inherent in external hazard response, thereby providing insights regarding event timing and physical event conditions as they relate to human performance. In this study, there are two main objectives: (1) evaluate the applicability of an existing cognitive-based HRA method, Phoenix, to ex-control room actions, and (2) identify sources of uncertainty to be characterized or reduced in order to make this method suitable for XHPRA. The first step of such work is performed by assessing the suitability of existing HRA methods to support identifying human failure events (HFEs) for human response to flooding hazards. These HFEs are human actions or inactions that are involved in human responses to flooding hazards and could contribute to the loss of a critical function for the plant in the scenario being examined. Here, in this work, decomposition analyses using the cognitive-based Phoenix HRA model are used to identify HFEs. The Phoenix method was found to be suitable for analyzing ex-control room actions as well as identifying specific HFEs and underlying crew failure modes (CFMs). However, the method's suitability for use in ex-control room actions would benefit from expanding the available CFMs to accommodate a larger variety of physical and communication tasks.

42 ENGINEERING↗
DOE OSTI2012

Changes in expression of renal Oat1, Oat3 and Mrp2 in cisplatin-induced acute renal failure after treatment of JBP485 in rats

The purpose of this study is to investigate whether the effect of cyclo-trans-4-L-hydroxyprolyl-L-serine (JBP485) on acute renal failure (ARF) induced by cisplatin is related to change in expression of renal Oat1, Oat3 and Mrp2 in rats. JBP485 reduced creatinine, blood urea nitrogen (BUN) and indoxyl sulfate (IS) in plasma and malondialdehyde (MDA) in kidney, and recovered the glomerular filtration rate (GFR) and the activity of superoxide dismutase (SOD) in cisplatin-treated rats. The plasma concentration of PAH (para-aminohippurate) determined by LC–MS/MS was increased markedly after intravenous administration of cisplatin, whereas cumulative urinary excretion of PAH and the uptake of PAH in kidney slices were significantly decreased. qRT-PCR and Western-blot showed a decrease in mRNA and protein of Oat1 and Oat3, an increase in mRNA and protein of Mrp2 in cisplatin-treated rats, and an increase in IS (a uremic toxin) after co-treatment with JBP485. It indicated that JBP485 promoted urinary excretion of toxins by upregulating renal Mrp2. This therefore gives in part the explanation about the mechanism by which JBP485 improves ARF induced by cisplatin in rats. -- Highlights: ► Cisplatin induces acute renal failure (ARF). ► The expression of Oat1, Oat3 and Mrp2 were changed during ARF. ► The regulated expression of Oat1, Oat3 and Mrp2 is an adaptive protected response. ► JBP485 could facilitate the adaptive protective action.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Optimizing the location and configuration of disaster resilience hubs under transportation and electric power network failures

Natural disasters often result in failures of transportation network components and blackouts that imperil the wellbeing of vulnerable populations. In response to these events, resilience hubs have been proposed as a pre-disaster planning strategy to improve access to critical services. This paper introduces an optimization-based approach to locate and configure electric power-generating resilience hubs considering the possibility of failures in transportation and electric power systems. The model's objective is to identify hub locations and configurations that maximize transportation accessibility to the hubs and maximize the satisfaction of basic energy needs through hub-generated electric power. Besides a budget constraint, the model accounts for limits on the levels of hub energy generation vis-à-vis community energy demands, and on the transportation network distance of communities to hubs. Three heuristics are presented for the proposed planning problem. The first heuristic is a genetic algorithm (GA) with problem-specific solution generation procedures. The other two heuristics implement greedy search techniques. Numerical experiments were conducted, using data from rural Puerto Rico, to illustrate the application of the proposed model and heuristics, and examine their performance. In the numerical experiments, the GA heuristic found better solutions than the greedy heuristics. Additionally, design solutions consisting of spatially dispersed hubs with low energy generation capacity were better than solutions with spatially concentrated high-capacity hubs. Lastly, across a wide range of hub demand scenarios, only a small number of candidate hub locations consistently ranked among the best locations for establishing a hub.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

Comparison of different procedures to stabilize biogas formation after process failure in a thermophilic waste digestion system: Influence of aggregate formation on process stability

Highlights: Black-Right-Pointing-Pointer Mechanism of process recovery with calcium oxide. Black-Right-Pointing-Pointer Formation of insoluble calcium salts with long chain fatty acids and phosphate. Black-Right-Pointing-Pointer Adsorption of VFAs by the precipitates resulting in the formation of aggregates. Black-Right-Pointing-Pointer Acid uptake and phosphate release by the phosphate-accumulating organisms. Black-Right-Pointing-Pointer Microbial degradation of volatile fatty acids in the aggregates. - Abstract: Following a process failure in a full-scale biogas reactor, different counter measures were undertaken to stabilize the process of biogas formation, including the reduction of the organic loading rate, the addition of sodium hydroxide (NaOH), and the introduction of calcium oxide (CaO). Corresponding to the results of the process recovery in the full-scale digester, laboratory experiments showed that CaO was more capable of stabilizing the process than NaOH. While both additives were able to raise the pH to a neutral milieu (pH > 7.0), the formation of aggregates was observed particularly when CaO was used as the additive. Scanning electron microscopy investigations revealed calcium phosphate compounds in the core of the aggregates. Phosphate seemed to be released by phosphorus-accumulating organisms, when volatile fatty acids accumulated. The calcium, which was charged by the CaO addition, formed insoluble salts with long chain fatty acids, and caused the precipitation of calcium phosphate compounds. These aggregates were surrounded by a white layer of carbon rich organic matter, probably consisting of volatile fatty acids. Thus, during the process recovery with CaO, the decrease in the amount of accumulated acids in the liquid phase was likely enabled by (1) the formation of insoluble calcium salts with long chain fatty acids, (2) the adsorption of volatile fatty acids by the precipitates, (3) the acid uptake by phosphorus-accumulating organisms and (4) the degradation of volatile fatty acids in the aggregates. Furthermore, this mechanism enabled a stable process performance after re-activation of biogas production. In contrast, during the counter measure with NaOH aggregate formation was only minor resulting in a rapid process failure subsequent the increase of the organic loading rate.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Risk management for outsourcing biomedical waste disposal – Using the failure mode and effects analysis

Highlights: • This study is based on a real case in hospital in Taiwan. • We use Failure Mode and Effects Analysis (FMEA) as the evaluation method. • We successfully identify the evaluation factors of bio-medical waste disposal risk. - Abstract: Using the failure mode and effects analysis, this study examined biomedical waste companies through risk assessment. Moreover, it evaluated the supervisors of biomedical waste units in hospitals, and factors relating to the outsourcing risk assessment of biomedical waste in hospitals by referring to waste disposal acts. An expert questionnaire survey was conducted on the personnel involved in waste disposal units in hospitals, in order to identify important factors relating to the outsourcing risk of biomedical waste in hospitals. This study calculated the risk priority number (RPN) and selected items with an RPN value higher than 80 for improvement. These items included “availability of freezing devices”, “availability of containers for sharp items”, “disposal frequency”, “disposal volume”, “disposal method”, “vehicles meeting the regulations”, and “declaration of three lists”. This study also aimed to identify important selection factors of biomedical waste disposal companies by hospitals in terms of risk. These findings can serve as references for hospitals in the selection of outsourcing companies for biomedical waste disposal.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

The role of cardiac energy metabolism in cardiac hypertrophy and failure

In mammalian heart, incessant production of cellular energy is vital for maintaining continuous mechanical pumping function providing the body for oxygen and nutrients. To ensure this essential function, cardiac muscle adapt to increased energy demand or compromised energy supply by reprogramming the network of genes whose products are necessary to match the production of energy to consumption. Failure in this regulation leads to severe cardiac dysfunction and has been associated with cardiac pathogenesis including cardiac hypertrophy, failure and diabetes. Metabolic adaptations are induced by network of transcriptional pathways that are activated by a variety of factors such as hormones, nutrients, second messengers and oxygen. The metabolic phenotype of the heart is maintained by pathways controlling transcriptional regulators, which include peroxisome proliferator-activated receptors, estrogen-related receptors and nuclear respiratory factors, as well as their common coactivator protein peroxisome proliferator-activated receptor γ coactivator 1. These central regulators of gene expression are complemented with factors such as hypoxia inducible factor 1, which is activated in insufficient oxygenation of the tissue. Here, we discuss how these pathways relate to the cardiac metabolism and how they interact with pathways controlling the contractile phenotype of the heart. - Highlights: • Energy metabolic changes are associated with cardiac adaptation and pathogenesis. • Cardiac energy substrate utilisation is controlled by complex transcriptional networks. • Transcriptional pathways controlling heart metabolic and contractile phenotype overlap.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Investigation of the Failure of Marcus Theory for Hydrated Electron Reactions

Reactions of the hydrated electron with a wide variety of substrates have been found to exhibit unusually similar activation energies in a manner incompatible with Marcus electron transfer theory. Given the fundamental linear response assumption of Marcus theory, one possible explanation for this apparent failure is that the underlying free energy surfaces governing the reactions are not harmonic, i.e., hydrated electron structural fluctuations exhibit non-Gaussian behavior. In this work, we test this hypothesis by using simulations to calculate the hydrated electron vertical detachment energy distribution. Furthermore, we consider both cavity and non-cavity models for the hydrated electron, between which the actual hydrated electron behavior is expected to lie. Our results identify a possible origin for non-Gaussian behavior of the hydrated electron, but show that it is not of sufficient magnitude to explain the failure of Marcus theory to describe its reactions. Thus, other explanations must be sought.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

From Filamentary Failure to Durable Halide Perovskite Memristors

Halide perovskites have emerged as promising materials for memristive devices. While their pronounced electrochemical reactivity and fast ionic mobility enable numerous advantages including low-voltage operation and fast switching, the same features also render perovskite-based memristors vulnerable to metallic shunts and poor endurance, limiting their practical applications. Here, we elucidate both the resistive switching and failure mechanisms in perovskite memristors with a fluorine-doped tin oxide (FTO)/methylammonium lead triiodide (MAPbI3)/Ag structure and demonstrate a strategy to substantially enhance device durability. As opposed to commonly invoked filamentary mechanisms, electrical, structural, and spectroscopic analyses reveal that resistive switching arises from interfacial barrier modulation by reversible Ag redox reactions that drive electrochemical doping/dedoping within the perovskite. Device failure, however, originates from metallic Ag0 filamentation that ultimately forms permanent conductive pathways. Introducing an ultrathin Al2O3 interlayer at the inert-electrode interface improves device endurance by more than 30-fold, exceeding 15,000 switching cycles, without compromising other performance metrics. Interfacial characterization indicates that the Al2O3 layer modifies wettability of Ag deposits, promoting planar island growth rather than through-film filamentation. These findings establish a clear link between interfacial electrochemistry, metal precipitation behavior, and memristor reliability, highlighting inert-electrode interfacial engineering as an effective pathway toward durable perovskite-based memristors.

14 SOLAR ENERGY↗
DOE OSTI2026

High-Sensitivity DNA Aptasensors for Detecting Salivary Biomarker S100A7 in Heart Failure

Early detection of heart failure (HF) is vital for improving patient outcomes, lowering hospital readmission rates, and enabling prompt treatment. We present the first high-affinity DNA aptamer for the salivary HF biomarker S100A7 and its application in highly sensitive, noninvasive diagnostic tests. Iterative truncation of the initial 82-nt aptamer (17–82) produced a 43-nt core (17–43) with a binding affinity of 27 nM, which was further enhanced to 5.5 nM through dimerization. Biochemical and mutational studies confirmed that 17–43 adopts a G-quadruplex structure, which is essential for S100A7 recognition and resistance to enzymatic degradation in human saliva. Incorporating 17–43 into sandwich aptamer-ELISA and hybrid aptamer–antibody ELISA assays allowed detection of recombinant S100A7 in human saliva with limits of detection (LOD) of 7.4 ng mL–1 (0.6 nM) and 29 pg/mL (2.2 pM), respectively-outperforming commercial immunoassays in both sensitivity and dynamic range. The hybrid assay maintained its full performance after 2.5 months of room temperature storage. Additionally, a biolayer interferometry (BLI) sensor with 17–43 quantified S100A7 in patient saliva (n = 3), achieving a LOD of 3.2 ng mL–1 (0.3 nM) with a total assay time of less than 20 min. The aptamer’s stability, high specificity, and versatility across biosensing platforms establish it as a promising tool for noninvasive heart failure diagnostics, laying the groundwork for portable aptamer-based biosensors for multiplexed monitoring of HF biomarkers.

DNA aptamer↗
DOE OSTI2020

Preseismic Fault Creep and Elastic Wave Amplitude Precursors Scale With Lab Earthquake Magnitude for the Continuum of Tectonic Failure Modes

Tectonic faults fail in a continuum of modes from slow earthquakes to elastodynamic rupture. Precursory variations in elastic wavespeed and amplitude, interpreted as indicators of imminent failure, have been observed in limited natural settings and lab experiments where they are thought to arise from contact rejuvenation and microcracking within and around the fault zone. However, the physical mechanisms and connections to fault creep are poorly understood. Here we vary loading stiffness during frictional shear to generate a range of slip modes and measure fault zone properties using transmitted elastic waves. We find that elastic wave amplitudes show clear changes before fault failure. The temporal onset of amplitude reduction scales with lab earthquake magnitude and the magnitude of this reduction varies with fault slip. Our data provide clear evidence of precursors to lab earthquakes and suggest that continuous seismic monitoring could be useful for assessing fault state and seismic hazard potential.

58 GEOSCIENCES↗
DOE OSTI2021

Attention Network Forecasts Time-to-Failure in Laboratory Shear Experiments

Rocks under stress deform by creep mechanisms that include formation and slip on small-scale internal cracks. Intragranular cracks and slip along grain contacts release energy as elastic waves termed acoustic emissions (AE). AEs are thought to contain predictive information that can be used for fault failure forecasting. Here, we present a method using unsupervised classification and an attention network to forecast labquakes using AE waveform features. Our data were generated in a laboratory setting using a biaxial shearing device with granular fault gouge intended to mimic the conditions of tectonic faults. Here, we analyzed the temporal evolution of AEs generated throughout several hundred laboratory earthquake cycles. We used a Conscience Self-Organizing Map (CSOM) to perform topologically ordered vector quantization based on waveform properties. The resulting map was used to interactively cluster AEs. We examined the clusters over time to identify those with predictive ability. Finally, we used a variety of LSTM and attention-based networks to test the predictive power of the AE clusters. By tracking cumulative waveform features over the seismic cycle, the network is able to forecast the time-to-failure (TTF) of lab earthquakes. Our results show that analyzing the data to isolate predictive signals and using a more sophisticated network architecture are key to robustly forecasting labquakes. In the future, this method could be applied on tectonic faults to monitor earthquakes and augment early warning systems.

58 GEOSCIENCES↗
DOE OSTI2022

Distributed Fiber Optics Measurements of Rock Deformation and Failure in Triaxial Tests

The implementation of distributed strain measurement methods in triaxial and uniaxial tests have demonstrated the development of strain localization, even at early stages. This implies that single point measurement methods are location dependent. The use of distributed methods is required not only to improve the interpreted constitutive parameters obtained from triaxial tests, but also to understand the implications of strain localization in the failure process. Here, this work uses optical fibers in triaxial tests. The developed distributed measurement method was implemented on granite, gabbro, and sandstone samples and tested under different confining pressures, reaching 200 MPa on the granite sample. Using a temporal resolution of 0.25 Hz and 5 mm of spatial resolution, the strain evolution at over 300 locations at the sample surface was measured during testing. When compared to point sensing methods, the use of optical fiber greatly increases the number of measurements at the surface of the sample, and their interpolation provides the entire deformation of the sample surface. In all the tests performed, strain localizations were revealed before failure. A three-dimensional interpretation of a test, combining an optical scan of the sample and the distributed measurements, show good correlation between the fractures and the strain localization.

58 GEOSCIENCES↗
DOE OSTI2019

Unraveling the mysterious failure of Cu/SAPO-34 selective catalytic reduction catalysts

Commercial Cu/SAPO-34 selective catalytic reduction (SCR) catalysts have experienced unexpected and quite perplexing failure. Understanding the causes at an atomic level is vital for the synthesis of more robust Cu/SAPO-34 catalysts. Here we show, via application of model catalysts with homogeneously dispersed isolated Cu ions, that Cu transformations resulting from low-temperature hydrothermal aging and ambient temperature storage can be semi-quantitatively probed with 2-dimensional pulsed electron paramagnetic resonance. Coupled with kinetics, additional material characterizations and DFT simulations, we propose the following catalyst deactivation steps: (1) detachment of Cu(II) ions from cationic positions in the form of Cu(OH)2; (2) irreversible hydrolysis of the SAPO-34 framework forming terminal Al species; and (3) interaction between Cu(OH)2 and terminal Al species forming SCR inactive, Cu-aluminate like species. Especially significant is that these reactions are greatly facilitated by condensed water molecules under wet ambient conditions, causing low temperature failure of the commercial Cu/SAPO-34 catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Effect of solid-electrolyte pellet density on failure of solid-state batteries

Abstract Despite the potentially higher energy density and improved safety of solid-state batteries (SSBs) relative to Li-ion batteries, failure due to Li-filament penetration of the solid electrolyte and subsequent short circuit remains a critical issue. Herein, we show that Li-filament growth is suppressed in solid-electrolyte pellets with a relative density beyond ~95%. Below this threshold value, however, the battery shorts more easily as the density increases due to faster Li-filament growth within the percolating pores in the pellet. The microstructural properties (e.g., pore size, connectivity, porosity, and tortuosity) of $$75\%{{{{{\rm{L}}}}}}{{{{{{\rm{i}}}}}}}_{2}{{{{{\rm{S}}}}}}-25\%{{{{{{\rm{P}}}}}}}_{2}{{{{{{\rm{S}}}}}}}_{5}$$ 75 % L i 2 S − 25 % P 2 S 5 with various relative densities are quantified using focused ion beam–scanning electron microscopy tomography and permeability tests. Furthermore, modeling results provide details on the Li-filament growth inside pores ranging from 0.2 to 2 μm in size. Our findings improve the understanding of the failure modes of SSBs and provide guidelines for the design of dendrite-free SSBs.

25 ENERGY STORAGE↗
DOE OSTI2025

Material Fracturing and Failure Simulation Datasets

Fracturing is a fundamental physics phenomena with broad relevance across multiple domains, ranging from infrastructure integrity, aerospace durability, reservoir production, and seismic events. We present a diverse dataset of simulated fracture evolution and material failure generated from two numerical solvers: the phase-field method and the combined finite-discrete element method (FDEM). These solvers differ in formulation, physical fidelity, and computational efficiency. The dataset includes five materials: PBX, anisotropic shale, tungsten, aluminum, and steel. For each, phase-field simulations span 400,000 cases: 200,000 under uniaxial tension and 200,000 under biaxial tension. The computationally expensive FDEM simulations include 90,000 split evenly among PBX, shale, and tungsten under uniaxial loading. All simulations begin with randomized initial fracture patterns. Each entry includes temporal data capturing fracture propagation dynamics. This comprehensive dataset is designed to support the development of foundational or surrogate machine learning approaches for predicting material failure. While no such models are introduced here, the dataset lays a robust foundation for advancing future research and innovation in these areas.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Self-heating and failure in scalable graphene devices

Self-heating induced failure of graphene devices synthesized from both chemical vapor deposition (CVD) and epitaxial means is compared using a combination of infrared thermography and Raman imaging. Despite a larger thermal resistance, CVD devices dissipate >3x the amount of power before failure than their epitaxial counterparts. The discrepancy arises due to morphological irregularities implicit to the graphene synthesis method that induce localized heating. As a result, morphology, rather than thermal resistance, therefore dictates power handling limits in graphene devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Evaluating Resilience of Water Distribution Networks to Operational Failures from Cyber-Physical Attacks

Water cyber-physical systems (CPSs) have gained increasing interest to improve operational efficiency and reliability. However, due to growing exposure to cyber-physical attacks, cybersecurity and resilience against the attacks have become significant concerns. There have been efforts to improve cybersecurity in water CPSs, yet few attempts to investigate resilience against cyber-physical attacks. This study contributes to characterizing resilience of a water CPS and investigating potential resilience strategies. An advanced resilience measure integrating withstanding, absorptive, adaptive, and restorative capability of a system is proposed and applied to the C-town water distribution network (WDN) for 15 failure set scenarios with a pressure-driven hydraulic simulation. The results provide identification of failure sets and unfavorable operational conditions that make the system more vulnerable to the cyber-physical attacks and in turn produce low resilience and capabilities. It is also found that, after recovery of a disrupted component, adjustment of overall operational interactions across system components is needed for complete restoration of disrupted functionality. The findings provide insights on infrastructure investment with resilience strategies in cyber and physical water system domains.

Shin, Sangmin↗
DOE OSTI2014

Modeling of microstructural effects on electromigration failure

Current electromigration models used for simulation and analysis of interconnect reliability lack the appropriate description of metal microstructure and consequently have a very limited predictive capability. Therefore, the main objective of our work was obtaining more sophisticated electromigration tools. The problem is addressed through a combination of different levels of atomistic modeling and already available, continuum level macroscopic models. A novel method for an ab initio calculation of the effective valence for electromigration is presented and its application on the analysis of EM behavior is demonstrated. Additionally, a simple analytical model for the early electromigration lifetime is obtained. We have shown that its application provides a reasonable estimate for the early electromigration failures including the effect of microstructure. A simulation study is also applied on electromigration failure in tin solder bumps, where it contributed the understanding of the role of tin crystal anisotropy in the degradation mechanism of solder bumps.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗