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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 73 records · Page 4

Probing the Damage Zone at Parkfield

Rocks are heterogeneous materials that exhibit nonlinear elastic (anelastic) behavior at scales ranging from the laboratory to Earth. In the laboratory, typical, complex relationships exist between stress and strain that include hysteresis, finite relaxation times, strain rate, and history dependence. These behaviors are linked to important characteristics such as stress, porosity, permeability, material integrity, and material failure. In this work, we adopted a “pump-probe” type experiment common in laboratory studies, using solid earth tides as the low-frequency pump and empirical Green's function as the high-frequency probe. By probing the velocity at different points in the pump cycle, we constrained important information about the strain-modulus relationship. Near the San Andreas Fault, we observed strongly nonlinear elastic behavior that characterizes the damage zone. We also constrained important aspects of hysteretic behavior that are related to damage properties and possibly pore pressure. Away from the fault, the nonlinear behavior is diminished.

58 GEOSCIENCES↗

Shoulder fillet effects in strength distributions of microelectromechanical system components

The failure forces and fracture strengths of polysilicon microelectromechanical system (MEMS) components in the form of stepped tensile bars with shoulder fillets were measured using a sequential failure chain methodology. Approximately 150 specimens for each of four fillet geometries with different stress concentration factors were tested. The resulting failure force and strength distributions of the four geometries were related by a common sidewall flaw population existing within different effective stressed lengths. The failure forces, strengths, and flaw population were well described by a weakest-link based analytical framework. Finite element analysis was used to verify body-force based expressions for the stress concentration factors and to provide insight into the variation of specimen effective length with fillet geometry. Monte Carlo simulations of flaw size and location, based on the strength measurements, were also used to provide insight into fillet shape and size effects. The successful description of the shoulder fillet specimen strengths provides further empirical support for application of the strength and flaw framework in MEMS fabrication and design optimization.

36 MATERIALS SCIENCE↗

Uniform Mechanical Loading Can Test for Nonuniform Loading Durability

In this work, we present a method to evaluate the equivalency between any module mechanical loading conditions. The method is developed to address the specific failure mode of glass fracture and is based on Weibull analysis and weakest link theory. It considers the varying stress profile across the module to calculate the probability of glass fracture, which is used as the metric of equivalency. An idealized nonuniform loading scheme is employed to demonstrate the method and introduce the concept of the equivalent uniform load factor: a factor applied to the maximum pressure of the nonuniform load to obtain the equivalent uniform load value. It is demonstrated that this factor is less than unity for all nonuniform load cases considered, including snow and various characters of wind loading. These significant results suggest that uniform loading may be reliably, and practically, employed to evaluate photovoltaic module glass for nonuniform loading durability.

14 SOLAR ENERGY↗

Enhancing PV Inverter Reliability Through Predictive Maintenance: Insights from Retrofitting of PV Inverters

Photovoltaic (PV) systems represent a cornerstone in the global shift toward sustainable energy generation, with inverters serving as the crucial link between solar panels and the grid. Despite their pivotal role, inverters are susceptible to failures, contributing significantly to maintenance events and operational disruptions in large-scale PV plants. This white paper investigates the importance and methodologies of predictive maintenance strategies that monitor the component-level pre-failure signatures on PV inverters. Through a comprehensive survey of literature and industry professionals, insights on preventive maintenance and retrofitting practices have been gathered. The expert elicitation helps shed light on common challenges and opportunities for improving PV system reliability, particularly inverter reliability. By addressing these challenges, the white paper aims to enhance the long-term viability and effectiveness of solar PV plants in the renewable energy landscape, contributing to the global transition toward environmentally friendly energy generation.

14 SOLAR ENERGY↗

Redefining Design for Remanufacturing: A Practical Methodology for Prioritizing Remanufacturing Design Rules

Products are often discarded when they fail or no longer meet user needs. These outcomes are frequently shaped by early design decisions. While remanufacturing offers a sustainable alternative by restoring products to like‐new condition, its potential is often limited by designs that do not consider remanufacturing from the outset. This research addresses that challenge by introducing a structured Design for Remanufacturing (DfRem) methodology and a CAD‐integrated tool to support real‐time design decisions. The DfRem framework introduces a new primary design function focused on preserving product functionality across its life cycle. It is supported by a fault tree that identifies failure modes that limit remanufacturing potential and a hierarchy of design principles including Prevent, Minimize, Relocate, Restore, and others. Each principle is linked to actionable design rules that help engineers reduce the need for remanufacturing or improve its efficiency when necessary. To operationalize this framework, we developed CAD plugins for Autodesk Inventor and PTC Creo. These tools use a state machine model to present prioritized design rules based on selected failure modes and user input. By embedding DfRem logic directly into widely used CAD environments, the tool enables engineers to make sustainability‐informed decisions without disrupting existing workflows. Furthermore, this approach highlights the critical role of design in enabling circular and resource‐efficient product development, making remanufacturing a more practical and accessible strategy during the early stages of product design.

CAD↗

Evidence Theory Representations for Properties Associated With Weak Link/Strong Link Systems, Part 1: Loss of Assured Safety

The use of evidence theory in the analysis of loss of assured safety (LOAS) for weak link (WL)/strong link (SL) systems is introduced and illustrated. Furthermore, article content includes (i) an introduction to evidence theory, (ii) definition of two WLs and two SLs used for illustration, (iii) belief and plausibility for the occurrence of LOAS for a one WL/two SL system, and (iv) a sampling-based procedure for the verification of belief and plausibility calculations. The presented results can be generalized to systems with more than one WL and two SLs.

42 ENGINEERING↗

Toward quantifying capacity losses due to solid electrolyte interphase evolution in silicon thin film batteries

To understand the origins of failure and limited cycle life in lithium-ion batteries (LIBs), it is imperative to quantitatively link capacity-fading mechanisms to electrochemical and chemical processes. This is extremely challenging in real systems where capacity is lost during each cycle to both active material loss and solid electrolyte interphase (SEI) evolution, two indistinguishable contributions in traditional electrochemical measurements. Here, we have used a model system in combination with (1) precision measurements of the overall Coulombic efficiency via electrochemical experiments and (2) x-ray reflectivity measurements of the active material losses. The model system consisted of a 515 Å thick amorphous silicon (a-Si) thin film on silicon carbide in half-cell geometry using a carbonate electrolyte with LiPF6 salt. This approach allowed us to quantify the capacity lost during each cycle due to SEI evolution. Combined with electrochemical analysis, we identify SEI growth as the major contribution to capacity fading. Specifically, the continued SEI growth results in increasing overpotentials due to increased SEI resistance, and this leads to lower extent of lithiation when the cutoff voltage is reached during lithiation. Our results suggest that SEI grows more with increased time spent at low voltages where electrolyte decomposition is favored. Finally, we extracted a proportionality constant for SEI growth following a parabolic growth law. Our methodology allows for the quantitative determination of lithium-ion loss mechanisms in LIBs by separately tracking lithium ions within the active materials and the SEI and offers a powerful method of quantitatively understanding LIB loss mechanisms.

25 ENERGY STORAGE↗

Investigation of Multiple Data Streams for Gearbox Bearing Fault Prediction Through Machine-Learning Models

Operations and maintenance (O&M) cost of wind plant accounts up to 30% of total energy cost, which can be reduced through continuous monitoring and successfully detecting incipient wind turbine failures. To accomplish this, condition monitoring and predictive maintenance systems are being implemented in wind industry to support O&M decision making. A wide range of approaches for condition monitoring and fault prediction have been developed. These approaches generally use historical data of wind turbines collected by Supervisory Control and Data Acquisition (SCADA) system to identify patterns that lead to failure. These SCADA data show the overall condition of a wind turbine and can be leveraged to detect when the turbine's performance is degrading and to identify if a fault is developing. However, it becomes challenging to predict the failure of a specific wind turbine gearbox bearing, because the SCADA data are often not directly linked to the component. To bridge the gap, we have investigated features calculated from SCADA data using physics-based models and the gearbox design over the years. The damaged metric we used in the physics domain is frictional energy. Combining these physics domain variables with SCADA data as inputs to various machine learning models for gearbox bearing fault prediction, we have demonstrated the benefits of leveraging both physics and data domain models. It was an attempt to improve frictional-energy-based damage metric by adding data domain inputs, as we had learned that the frictional-energy-based damage metric alone is not sufficient to single out failed bearings from healthy. As condition monitoring data (either vibration or oil debris data) has become available at more and more wind plants, we would like to evaluate whether by adding the condition monitoring data can help further improve the performance of frictional-energy-based damage metric for gearbox bearing fault prediction. Both cases by modeling through various machine learning algorithms are discussed in this study along with some observations.

fault prediction↗

Finite Element Modeling of the Phase Change in Thermally-Grown SiO 2 in SiC Systems for Gas Turbines

The operating lifetimes of SiC-based components in combustion environments are directly linked to the adhesion of the protective environmental barrier coating (EBC) layer. One of the major known failure modes for EBCs is the formation of a thick SiO 2 thermally grown oxide (TGO), which decreases coating adhesion and encourages eventual coating spallation. The effect of the TGO thickness under Yb 2 Si 2 O 7 EBCs on silicon carbide was investigated using finite element models (FEMs) with various interfacial architectures and SiO 2 TGO thicknesses. Further, the FEMs incorporated a user-defined material to simulate the volume contraction of the TGO during the silica phase transformation from β-cristobalite to α-cristobalite upon cooling from the stress-free state at 1350°C to room temperature. Systems with and without a silicon bond coating intermediary layer were assessed. It was shown that the TGO phase transformation stress (1.6–1.7 GPa) dominated the increase in stress in the TGO and EBC layers. Furthermore, it was found that stress increase in the TGO was independent of TGO thickness and interface geometry. These results indicate that stabilization of the TGO to mitigate the phase transformation could dramatically improve the performance of SiC-base components with EBCs.

36 MATERIALS SCIENCE↗

The influence of preexisting host rock damage on fault network localization

The transition from stable to unstable fracture propagation occurs when fractures begin to interact and link. Thus, fracture network coalescence controls how rocks and engineered structures fail. Here, to constrain the factors that influence localization in shear zones under brittle conditions, we build discrete element method models with a rough fault embedded in a shear zone. We add varying numbers of diffuse, randomly-placed weaknesses to examine the influence of diffuse damage on fracture network localization. The number of weaknesses controls the localization behavior of the fault network and the final fault geometry. We quantify localization using the Gini coefficient of the fracture volume, which measures the nonuniformity in a population. Each model generally increases in localization toward failure. However, models with more diffuse damage experience delocalization phases that are superimposed on the overall trend of increasing localization. The observed link between delocalization and host rock damage may help explain the varying localization of low magnitude seismicity in southern California. Models with more diffuse damage produce more complex fault geometries comprised of several parallel strands of wing cracks. The propagation of these wing cracks reduces the shear stress acting on the model boundaries, indicating that this fracture development increases the mechanical efficiency of the system.

58 GEOSCIENCES↗

Subdiffusive High-Pressure Hydrogen Gas Dynamics in Elastomers

We report elastomeric rubber materials serve a vital role as sealing materials in the hydrogen storage and transport infrastructure. With applications including O-rings and hose liners, these components are exposed to pressurized hydrogen at a range of temperatures, cycling rates, and pressure extremes. High-pressure exposure and subsequent rapid decompression often lead to cavitation and stress-induced damage of the elastomer due to localization of the hydrogen gas. Here, we use all-atom classical molecular dynamics simulations to assess the impact of compositional variations on gas diffusion within the commonly used elastomer ethylene–propylene–diene monomer (EPDM). With the aim to build a predictive understanding of precursors to cavitation and to motivate material formulations that are less sensitive to hydrogen-induced failure, we perform systematic simulations of gas dynamics in EPDM as a function of temperature, gas concentration, and cross-link density. Our simulations reveal anomalous, subdiffusive hydrogen motion at pressure and intermediate times. We identify two groups of gas with different mobilities: one group exhibiting high mobility and one group exhibiting low mobility due to their motion being impeded by the polymer. With decreasing temperatures, the low-mobility group shows increased gas localization, the necessary precursor for cavitation damage in these materials. At lower temperatures, increasing cross-link density led to greater hydrogen gas mobility and a lower fraction of caged hydrogen, indicating that increasing cross-link density may reduce precursors to cavitation. Finally, we use a two-state kinetic model to determine the energetics associated with transitions between these two mobility states.

36 MATERIALS SCIENCE↗

Trust-Based Detection and Mitigation of Cyber Attacks in Distributed Cooperative Control of Islanded AC Microgrids

In this study, we address the challenge of detecting and mitigating cyber attacks in the distributed cooperative control of islanded AC microgrids, with a particular focus on detecting False Data Injection Attacks (FDIAs), a significant threat to the Smart Grid (SG). The SG integrates traditional power systems with communication networks, creating a complex system with numerous vulnerable links, making it a prime target for cyber attacks. These attacks can lead to the disclosure of private data, control network failures, and even blackouts. Unlike machine learning-based approaches that require extensive datasets and mathematical models dependent on accurate system modeling, our method is free from such dependencies. To enhance the microgrid’s resilience against these threats, we propose a resilient control algorithm by introducing a novel trustworthiness parameter into the traditional cooperative control algorithm. Our method evaluates the trustworthiness of distributed energy resources (DERs) based on their voltage measurements and exchanged information, using Kullback-Leibler (KL) divergence to dynamically adjust control actions. We validated our approach through simulations on both the IEEE-34 bus feeder system with eight DERs and a larger microgrid with twenty-two DERs. The results demonstrated a detection accuracy of around 100%, with millisecond range mitigation time, ensuring rapid system recovery. Additionally, our method improved system stability by up to almost 100% under attack scenarios, showcasing its effectiveness in promptly detecting attacks and maintaining system resilience. These findings highlight the potential of our approach to enhance the security and stability of microgrid systems in the face of cyber threats.

Computer Science↗

Reliability metrics and their management implications for open pond algae cultivation

The prevalence of contaminating organisms in outdoor algae cultivation, with the often-associated dramatic crop failures, necessitates the need for metrics describing production system reliability. Standard metrics for algae cultivation reliability are critically needed to be able to map improvements in operational parameters, but do not currently exist. In this work, we present a set of standard metrics including mean time to failure (MTTF) and mean time between failures (MTBF) as the basis for the calculation of pond failure rate (FR) and reliability coefficient (RC). Metrics associated with the numbers of contaminating organisms such as abundance ratio (AR), prevalence of infection (PI), and mean intensity of infection (MII) are also relevant. These metrics, based on measured experimental values of outdoor pond performance during the Algae Testbed Public-Private Partnership (ATP3) Unified Field Studies (UFS), provide a basis for quantifying pond failure and provide insight into potential pond management and contaminant mitigation strategies. From these reliability metrics applied to this dataset, we are able to link operational parameters, such as harvest frequency and inoculum source, to pond reliability for different algae strains and seasons, and from an assessment of AR, provide contamination thresholds beyond which a culture may be unrecoverable. Ultimately, the implementation of widely-practiced and simple-to-calculate algae pond reliability metrics calculated from rapid and easy to collect data or observations will reduce risk and uncertainty in large-scale algae deployment and aid in the development of integrated pest management (IPM) strategies.

09 BIOMASS FUELS↗

Full core LOCA safety analysis for a PWR containing high burnup fuel

For economic reasons, the US nuclear industry is renewing efforts to build a technical basis to extend peak rod average burnup limits above the current regulatory burnup limit of 62 GWd/MTU. The primary driver of these efforts is to economically increase pressurized water reactor (PWR) cycle lengths to 24 months, reduce the number of fresh fuel assemblies, increase time online, thereby reducing number of outages and their associated cost, higher fuel utilization, and possibly reduce core design constraints. In order for US nuclear utilities to leverage these economic efficiencies, the US Nuclear Regulatory Commission (NRC) will likely require nuclear power plants (NPPs) to analyze a number of potential operational occurrences and their potential consequences with each new core design prior to resuming normal operation. Potential operational occurrences can be divided into three primary regimes: (1) normal operation, (2) anticipated operation occurrences (AOOs), and (3) design basis accidents (DBAs). Normal plant operation is an operating regime in which the plant operates within specified operational limits until the end of the cycle, whereas AOOs are events that result in the NPP deviating outside the normal operating regime. A key attribute of an AOO is that the occurrence should be expected. However, by definition, the occurrence of an AOO does not result in significant impact to critical safety functions. The last potential operational occurrence is a DBA. From the fuel performance point-of-view, DBAs can be subdivided into two bounding categories: (1) loss of coolant accidents (LOCAs), and (2) reactivity insertion accidents (RIAs). Unlike AOOs, DBAs may result in fuel rod failure. The NRC imposes fundamental acceptance criteria to minimize radiological consequences to the public and onsite staff. Furthermore, safety criteria are typically linked to the fulfillment of other acceptance criteria related to reactor safety equipment designed to mitigate DBAs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Mechanistic modeling of lifetime distribution of SiC/SiC composite claddings

Silicon carbide (SiC) fiber-reinforced SiC matrix (SiC/SiC) composites have emerged as a new material candidate for fuel claddings in light water reactors. Recent studies showed that the load capacity of SiC/SiC materials exhibits a considerable statistical variation. Therefore, reliability analysis plays a critical role in design of SiC/SiC composite claddings. Here, this paper presents a probabilistic model for the lifetime distribution of SiC/SiC composites. The model is anchored by a multiaxial stress-based failure criterion and subcritical damage accumulation mechanism. Based on the kinetics of subcritical damage growth, the lifetime distribution of a laboratory test specimen for any given loading history can be calculated. A finite weakest-link model is used to extrapolate the lifetime distribution of test specimens to full-length claddings. It is shown that the damage accumulation mechanism has a strong influence on the lifetime distribution of the cladding. This finding highlights the importance of understanding the static fatigue behavior of SiC/SiC composites. The present analysis also demonstrates an intricate length effect on the failure probability of the cladding, which is expected to play a crucial role in design extrapolation.

36 MATERIALS SCIENCE↗

O-GlcNAc transferase regulates collagen deposition and fibrosis resolution in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a chronic pulmonary disease that is characterized by an excessive accumulation of extracellular matrix (ECM) proteins (e.g. collagens) in the parenchyma, which ultimately leads to respiratory failure and death. While current therapies exist to slow the progression, no therapies are available to resolve fibrosis. We characterized the O-linked N-Acetylglucosamine (O-GlcNAc) transferase (OGT)/O-GlcNAc axis in IPF using single-cell RNA-sequencing (scRNA-seq) data and human lung sections and isolated fibroblasts from IPF and non-IPF donors. The underlying mechanism(s) of IPF were further investigated using multiple experimental models to modulate collagen expression and accumulation by genetically and pharmacologically targeting OGT. Furthermore, we hone in on the transforming growth factor-beta (TGF-β) effector molecule, Smad3, by co-expressing it with OGT to determine if it is modified and its subsequent effect on Smad3 activation. We found that OGT and O-GlcNAc levels are upregulated in patients with IPF compared to non-IPF. We report that the OGT regulates collagen deposition and fibrosis resolution, which is an evolutionarily conserved process demonstrated across multiple species. Co-expression of OGT and Smad3 showed that Smad3 is O-GlcNAc modified. Blocking OGT activity resulted in decreased phosphorylation at Ser-423/425 of Smad3 attenuating the effects of TGF-β1 induced collagen expression/deposition. OGT inhibition or knockdown successfully blocked and reversed collagen expression and accumulation, respectively. Smad3 is discovered to be a substrate of OGT and its O-GlcNAc modification(s) directly affects its phosphorylation state. These data identify OGT as a potential target in pulmonary fibrosis resolution, as well as other diseases that might have aberrant ECM/collagen accumulation.

59 BASIC BIOLOGICAL SCIENCES↗

Lossless Phonon Transition Through GaN‐Diamond and Si‐Diamond Interfaces

Abstract Advancing Silicon (Si) technology beyond Moore's law through 3D architectures requires highly efficient heat management methods compatible with foundry processes. While continued increases in transistor density can be achieved through 3D architectures, self‐heating in the upper tiers degrades the performance. Self‐heating is a critical problem for high‐power, high‐frequency, wide bandgap, and ultra‐wide bandgap devices as well. Diamond, known for its exceptional thermal conductivity, offers a viable solution in both these cases. Since thermal boundary resistance (between the channel/junction and diamond plays a crucial role in overall thermal resistance, this study investigates various dielectrics for interface engineering, such as Silicon dioxide (SiO 2 ), amorphous‐ Silicon Carbide (a‐SiC), and Silicon Nitride (SiN x ), to make a phonon bridge at gallium nitride (GaN)‐diamond and Si‐diamond interfaces. The a‐SiC interlayer reduces diamond/GaN (<5 m 2 K per GW) and diamond/Si (<2 m 2 K per GW) thermal boundary resistances by linking low‐ and high‐frequency phonons, boosting phonon transport through the interface. Engineered interfaces enhance heat spreading from the channel/junction and rule out premature failure.

Malakoutian, Mohamadali↗

Elastic Properties and Deformation Mechanisms in the van der Waals Single-Crystalline Indium Selenide

The bulk van der Waals (vdW) single-crystalline indium selenide (β-InSe) displays exceptional plasticity in a layered crystalline form at both micro- and macroscale. However, the nanoscale origin of plasticity remains unclear. Herein, an atomic-level study on the deformation mechanisms of InSe by using first-principles calculations is reported. Remarkable anisotropic elasticity is observed in the vdW InSe layered crystal, and the stiffness is dramatically softened because of the vdW gap in the layered structure. The simulations capture the distinct fracture modes in the uniaxial tensile deformation, depending on the loading directions—brittle fracture in the [100] and [110] directions while ductile failure in the [001] direction. The InSe layered crystal structure exhibits superplastic deformability under uniaxial compression. Different transition pathways, including interlayer tangling, amorphization, and cross-linking, are tracked along respective deformation directions. The unprecedented plasticity of InSe layered crystals can be attributed to the phase transition coupled with interlayer gliding and cross-layer dislocation slipping. Here, this study deepens our understanding of the deformation mechanisms of layered materials at the atomistic level and provides insights into tailoring material properties for low-dimensional material design based on its deformation mechanisms.

2D materials↗