SEARCH · Engineering Papers

Results for “time to failure”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 415 records · Page 23

All sources NASA NTRS DOE OSTI

DOE OSTI2025

On the dynamics of the fluoroethylene carbonate generated solid electrolyte interphase on silicon anodes during calendar life aging

Here, the widespread use of silicon (Si)-rich anodes in lithium-ion batteries (LIBs) is impeded by an unstable solid electrolyte interphase (SEI) incurring insufficient cell life. Fluoroethylene carbonate (FEC) additive in the electrolyte significantly improves cycle life. However, the gains on calendar life remain unclear; the SEI structure still undergoes detrimental alterations at rest. Thus, elucidating the SEI dynamics during calendar aging is critical to mitigating time-dependent capacity degradation. ATR-FTIR, XPS, and ToF-SIMS are used herein to investigate the SEI structure before and after calendar aging. Si cycled without FEC exhibits no notable SEI chemistry changes Pre- and Post-aging, leaving poor passivation as the main failure pathway. Conversely, the FEC-SEI starts as short oligomeric species from FEC/EC electroreduction prior to aging; after calendar aging, polymerized carbonates become consistently more prominent. Unexpectedly, the deposition of self-polymerized FEC species results from time exposure to the delithiated Si specifically as opposed to the lithiated surface. This unexpected finding is supported by another recent Si calendar-aging research, which albeit not investigating FEC, finds global failure of the SEI upon delithiation resulting in ∼247 fold more reactive surface compared to the lithiated.

Batteries↗

DOE OSTI2023

Effects of root litter traits on soil organic matter dynamics depend on decay stage and root branching order

Decaying roots contribute disproportionately to soil organic carbon (SOC) stocks in many ecosystems, yet few studies have examined the afterlife effects of root trait variability on the formation, stability and mineralization of SOC. In order to assess how root functional class (absorptive vs. transport) and mycorrhizal association (ectomycorrhizal vs. arbuscular mycorrhizal fungi) affect both formation and loss of SOC, we decayed lower-order absorptive (orders 1–2) and higher-order transport (orders 3–4) roots from six arbuscular mycorrhizal (AM) and six ectomycorrhizal (EcM) associated hardwood tree species in an isotopically distinct soil under laboratory conditions. We found that root litter effects on SOC differed significantly among root functional classes and mycorrhizal types. AM absorptive and transport roots (high in nitrogen and soluble compounds) contributed more to the formation of new mineral-associated organic carbon (MAOC), but also contributed to higher mineralization of native SOC (via priming effects). Moreover, absorptive AM roots formed MAOC gradually and rates saturated, whereas ECM roots formed MAOC more quickly, despite slower decay (via greater formation efficiency). Altogether, these findings demonstrate how different combinations of root traits might contribute to soil C balance, and that failure to account for the chemical and morphological heterogeneity of roots, as well their interactions with microbes over time, may lead to incorrect projections of SOC stocks and turnover.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

srlife : A software tool for estimating the life of high temperature concentrating solar receivers. Part II – Ceramic receivers

As Concentrating Solar Power (CSP) technologies aim for higher operating temperatures to enhance efficiency and meet industrial process heat demands, high-temperature metallic materials, including nickel-based superalloys, face challenges in maintaining structural integrity. Advanced ceramics offer a promising alternative due to their superior high-temperature strength. However, accurately assessing the performance of ceramic components requires a fundamentally different approach from that used for metallic components. This Part II of a two-part paper describes the integration of ceramic statistical failure models within srlife – an open-source tool for predicting the life of high-temperature CSP receivers. These models account for the inherent variability in ceramic strength, as well as the effects of subcritical crack growth (SCG) under high temperature cyclic loads. Here, the paper includes an example problem that demonstrate the process of evaluating ceramic receivers using srlife. Part I details the life estimation process for metallic receivers (i.e. creep-fatigue life) along with input and output data structure, thermohydraulic analysis, and structural analysis. The complete tool is available as open-source software at https://github.com/srlife-project/srlife and can be installed via the PyPi package manager (https://pypi.org). By supporting both ceramic and metallic receiver analyses, srlife facilitates fair comparisons between competing metallic and ceramic designs, enabling accurate evaluations of plant efficiency and the economic benefits of ceramic solar receivers and other components.

High temperature ceramic receivers↗

DOE OSTI2020

Experimentally Validated Computational Modeling of Creep and Creep-Cracking for Nuclear Concrete Structures

In a Nuclear Power Plant, one of the most important components is the concrete nuclear reactor cavity, which serves both a structural and protective function as the biological radiation shield. Given that creep has been identified as a major knowledge gap in the assessment of nuclear structures (NUREG/CR-7153), this work helps to further the understanding of creep behavior of massive concrete containment structures for decades to enable safe and long-term operation of these facilities. This project has developed a robust, experimentally validated model to predict creep in nuclear concrete structures for up 60 years using short-term creep data thereby enabling a longer service life of critical facilities and early detection of structural failure. The work presented in this report is a pairing of computational and experimental methods. For the first time, the time temperature superposition (TTS) principle was successfully used to generate a uniaxial creep compliance master curve to predict mortar creep response for up to 22,500 days (nearly 60 years) at a reference temperature of 20°C. These data were used as input into finite element analysis (FEA) codes that use highly realistic random, 3D concrete microstructures from reconstructed coarse limestone aggregates. Finite element analysis performed provides the ability to quickly upscale mortar viscoelastic behavior to long-term concrete creep/relaxation data. A master creep compliance curve, constructed from the TTS principle, spanning 27 years, was used to validate two and a half decades of simulated concrete creep. Concurrently, three different simulated wall specimens were designed to mimic the behavior of post-tensioned concrete nuclear containment facility vessel walls over time as a result of concrete creep. The specimens were designed with different thicknesses, transverse and longitudinal reinforcement ratios, and level of post-tensioning stress. Each specimen contained various instrumentation to measure internal concrete temperature, concrete strain, and post-tensioning strain hourly for over 3 years. The concrete creep model developed in this project, based on the FEA concrete simulations, was applied to simulate the structural-scale experiments of prestressed concrete walls conducted in this project using the Grizzly code. These models can represent the effects of reinforcing and prestressing. Although there are some discrepancies with the experimental data, the model can predict the overall trends of the creep response in these experiments. One of these experimental models was also applied to an extended time to demonstrate how the findings from this study can be used to predict the behavior of actual structures of interest that have been in service for extended periods of time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Characterization of Creep-fatigue Tested A709 with Precipitation Treatment

The fatigue and creep-fatigue microstructures of the solution-annealed (SA) and the precipitation-treated (PT) Alloy 709 in the ESR1150 condition were studied. It was discovered that while high densities of new precipitates were formed during the tests in the ESR1150-SA material, the precipitates in the ESR1150-PT after the tests resembled of those in the untested PT condition with new features associated with the additional time spent at high temperatures. The observations explained the higher peak stresses and the lower cycles-to-failure in the SA material compared to those in the PT material during the cyclic deformations.

25 ENERGY STORAGE↗

DOE OSTI2025

Unsupervised Process Anomaly Detection and Identification Using the Leave-One-Variable-Out Approach

Automated anomaly detection and identification can signal equipment issues and pinpoint causes in large-scale industrial systems. For systems with limited failure history, unsupervised machine learning methods can be utilized as they do not require past failures. This study introduces the leave-one-variable-out (LOVO) model, which masks one variable at a time to predict the others, learning underlying process correlations. Detection performance was assessed with synthetic and experimental data, while identification performance used only synthetic data due to its ability to generate labeled anomaly types. For detection using synthetic data, the LOVO model generally outperformed comparative models; while using experimental data, the comparative methods outperformed the LOVO model. However, the comparative methods required selecting a latent size, and these conclusions pertain to using the optimal size. In practice, it would not be feasible to always select the optimal value, and incorrect selections impacted performance. In contrast, the LOVO model does not require a latent space. For identification using synthetic data, the LOVO model was slightly outperformed in interpretability and repeatability but still demonstrated impressive results. These outcomes suggest that the LOVO model is an effective model and may be more easily implemented without the challenging tuning process of selecting a latent size.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Low Peripheral Blood Counts and Elevated Proinflammatory Cytokines Signal a Poor CD19 Chimeric Antigen Receptor T-cell Response in Acute Lymphoblastic Leukemia

CD19 chimeric antigen receptor T-cell (CAR-T) therapy has significantly improved outcomes for patients with relapsed/refractory B-cell acute lymphoblastic leukemia (R/R B-ALL). However, approximately 20% of patients fail to achieve a complete remission (CR), and some develop severe, life-threatening toxicities. Understanding the biological mechanisms underlying both dysfunctional responses and severe toxicity is essential for optimizing patient management and improving therapeutic efficacy. This study aimed to (1) characterize cytokine profiles associated with dysfunctional responses and severe toxicity following CAR-T infusion, (2) examine the timing and trajectory of cytokine changes in relation to treatment outcomes, and evaluate potential strategies for mitigating toxicity and treatment failure. We conducted a comprehensive analysis of serum cytokine profiles in 86 adult and pediatric patients undergoing autologous CD19 CAR-T therapy for B-ALL. Patients were categorized into three groups: (1) Dysfunctional response—Patients who failed to achieve a minimal residual disease-negative CR (MRD-CR) by Day 63 or who experienced recurrence of CD19+ disease in the setting ongoing CAR-T cell detection before Day 63. (2) Functional response with severe cytokine release syndrome (CRS) and/or neurotoxicity (NTX)—Patients with best response of MRD-CR by Day 63 who experienced grade 3 or higher CRS or NTX. (3) Functional response without severe CRS or NTX—Patients with best response of MRD-CR by Day 63 who did not experience grade =3 CRS or NTX. Cytokine levels were measured during the first-week postinfusion and correlated with treatment efficacy, toxicity outcomes, complete blood counts, and CAR-T expansion dynamics. This analysis aimed to better understand how cytokine profiles relate to patient outcomes and immune responses in CAR-T therapy. Patients with dysfunctional response exhibited decreased neutrophils, platelets, and levels of granulocytic cytokines (suggestive of low bone marrow reserve) alongside elevated pro-inflammatory cytokines by Day 1. Functional response with severe toxicity patients showed a progressive rise in proinflammatory cytokines, reaching similar levels to dysfunctional response patients by Day 7. We observed that high cytokines at both the Day 1 and Day 7 time points were associated with poor survival. These findings remained significant when adjusting for high disease burden, a known predictor of severe inflammatory toxicity and lack of response. Early post-CAR-T infusion inflammation is associated with both dysfunctional response and severe toxicity—even after adjusting for disease burden. This suggests that inflammation, in addition to disease burden, plays a role in determining patient outcome. Therefore, strategies aimed at reducing the pro-inflammatory state prior to or early after CAR-T cell infusion may improve outcomes for R/R B-ALL patients.

Serum cytokines↗

DOE OSTI2024

DuraMAT: Building a Consortium to Accelerate the Photovoltaic Module Reliability Learning Cycle

Durable and reliable photovoltaic (PV) modules are critical to enabling an efficient transition to sustainable energy generation. The rate at which new module designs and materials are developed and deployed currently outpaces the rate at which we can identify failure mechanisms and understand degradation rates. Increasing the service life of PV modules, and our ability to predict performance over time, requires more durable materials and designs, better durability testing, more extensive material characterization, robust modeling, and methods to cross-examine historical performance data to extract meaningful results. This is a multidisciplinary challenge that requires expertise from a broad range of fields and, therefore, benefits significantly from a collaborative approach. In this Perspective, we outline the approach taken by the Durable Module Materials Consortium (DuraMAT), present a few case studies where our approach was successful, and provide an outlook on where this approach might be applied as the PV technology landscape continues to rapidly evolve. Published by the American Physical Society 2024

14 SOLAR ENERGY↗

DOE OSTI2022

Long-Term and Low-Level Envelope C2V3 Stimulation by Highly Diverse Virus Isolates Leads to Frequent Development of Broad and Elite Antibody Neutralization in HIV-1-Infected Individuals

A minority of HIV-1-infected patients produce broadly neutralizing antibodies (bNAbs). Identification of viral and host correlates of bNAb production may help develop vaccines. We aimed to characterize the neutralizing response and viral and host-associated factors in Angola, which has one of the oldest, most dynamic, and most diverse HIV-1 epidemics in the world. Three hundred twenty-two HIV-1-infected adults from Angola were included in this retrospective study. Phylogenetic analysis of C2V3C3 env gene sequences was used for virus subtyping. Env-binding antibody reactivity was tested against polypeptides comprising the C2, V3, and C3 regions. Neutralizing-antibody responses were determined against a reference panel of tier 2 Env pseudoviruses in TZM-bl cells; neutralizing epitope specificities were predicted using ClustVis. All subtypes were found, along with untypeable strains and recombinant forms. Notably, 56% of the patients developed cross neutralizing, broadly neutralizing, or elite neutralizing responses. Broad and elite neutralization was associated with longer infection time, subtype C, lower CD4 + T cell counts, higher age, and higher titer of C2V3C3-specific antibodies relative to failure to develop bNAbs. Neutralizing antibodies targeted the V3-glycan supersite in most patients. V3 and C3 regions were significantly less variable in elite neutralizers than in weak neutralizers and nonneutralizers, suggesting an active role of V3C3-directed bNAbs in controlling HIV-1 replication and diversification. In conclusion, prolonged and low-level envelope V3C3 stimulation by highly diverse and ancestral HIV-1 isolates promotes the frequent elicitation of bNAbs. These results provide important clues for the development of an effective HIV-1 vaccine. Studies on neutralization by antibodies and their determinants in HIV-1-infected individuals have mostly been conducted in relatively recent epidemics caused by subtype B and C viruses. Results have suggested that elicitation of broadly neutralizing antibodies (bNAbs) is uncommon. The mechanisms underlying the elicitation of bNAbs are still largely unknown. We performed the first characterization of the plasma neutralizing response in a cohort of HIV-1-infected patients from Angola. Angola is characterized by an old and dynamic epidemic caused by highly diverse HIV-1 variants. Remarkably, more than half of the patients produced bNAbs, mostly targeting the V3-glycan supersite in HIV-1. This was associated with higher age, longer infection time, lower CD4 + T cell counts, subtype C infection, or higher titer of C2V3C3-specific antibodies relative to patients that did not develop bNAbs. These results may help develop the next generation of vaccine candidates for HIV-1.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Spatiotemporal Variability in Wind Turbine Blade Leading Edge Erosion

Wind turbine blade leading edge erosion (LEE) reduces energy production and increases wind energy operation and maintenance costs. Degradation of the blade coating and ultimately damage to the underlying blade structure are caused by collisions of falling hydrometeors with rotating blades. The selection of optimal methods to mitigate/reduce LEE are critically dependent on the rates of coating fatigue accumulation at a given location and the time variance in the accumulation of material stresses. However, no such assessment currently exists for the United States of America (USA). To address this research gap, blade coating lifetimes at 883 sites across the USA are generated based on high-frequency (5-min) estimates of material fatigue derived using a mechanistic model and robust meteorological measurements. Results indicate blade coating failure at some sites in as few as 4 years, and that the frequency and intensity of material stresses are both highly episodic and spatially varying. Time series analyses indicate that up to one-third of blade coating lifetime is exhausted in just 360 5-min periods in the Southern Great Plains (SGP). Conversely, sites in the Pacific Northwest (PNW) exhibit the same level of coating lifetime depletion in over three times as many time periods. Thus, it may be more cost-effective to use wind turbine deregulation (erosion-safe mode) for damage reduction and blade lifetime extension in the SGP, while the application of blade leading edge protective measures may be more appropriate in the PNW. Annual total precipitation and mean wind speed are shown to be poor predictors of blade coating lifetime, re-emphasizing the need for detailed modeling studies such as that presented herein.

Pryor, Sara C. (ORCID:0000000348473440)↗

DOE OSTI2024

MODELING AND METHOD FOR OPTICAL PERFORMANCE OF A RECEIVER COATING AND ITS DEGRADATION DUE TO OPERATION

The optical properties of the coating used on a concentrated solar power (CSP)’s receiver directly impact the performance of the power plant. Receiver coatings are designed to absorb as much heat as possible and transfer it to the circulating fluid. Over time, the absorptivity of the receiver coating degrades due to environmental and operational conditions. This project aims to (1) create a test apparatus that allows coatings to undergo accelerated lifetime testing under conditions that mimic what the coating will experience on-tower; and (2) develop a mathematical model that based on the test data predicts absorptivity over time. To create the mathematical model, samples of BrightSource Energy’s Gen1 and Gen2 coatings were tested first looking at individual failure modes (such as high temperature cycling) and then for combined failure modes in the newly developed apparatus. In addition to taking optical measurements, the samples were destroyed to allow for metalogical evaluation to understand what was happening on a microscopic level. Pre-existing models from the literature that describe accelerated testing as well as individual phenomena observed in the coating were then combined to create the model. Additionally, the Gen2 and Gen3 coatings are being testing at the Plataforma Solar de Almería (PSA) facility in Almeria, Spain to confirm that the apparatus test results are similar to those received on-sun. (PSA’s facility closely mimics on-tower conditions). The goal is to enable industry players to test coatings using the new apparatus, gather absorptivity measurements (without needing to destroy samples), and input the information into the model to determine how the coating will perform over time, thus allowing the optical performance of coatings to be compared even before they are used on-tower. The model will be publicly available by the end of the project (currently projected as December 2024).

14 SOLAR ENERGY↗

DOE OSTI2023

Artificial neural network potentials for mechanics and fracture dynamics of two-dimensional crystals **

Understanding the mechanics and failure of materials at the nanoscale is critical for their engineering and applications. The accurate atomistic modeling of brittle failure with crack propagation in covalent crystals requires a quantum mechanics-based description of individual bond-breaking events. Artificial neural network potentials (NNPs) have emerged to overcome the traditional, physics-based modeling tradeoff between accuracy and accessible time and length scales. Previous studies have shown successful applications of NNPs for describing the structure and dynamics of molecular systems and amorphous or liquid phases of materials. However, their application to deformation and failure processes in materials is still uncommon. In this study, we discuss the apparent limitations of NNPs for the description of deformation and fracture under loadings and propose a way to generate and select training data for their employment in simulations of deformation and fracture simulations of crystals. We applied the proposed approach to 2D crystalline graphene, utilizing the density-functional tight-binding method for more efficient and extensive data generation in place of density functional theory. Then, we explored how the data selection affects the accuracy of the developed artificial NNPs. It revealed that NNP’s reliability should not only be measured based on the total energy and atomic force comparisons for reference structures but also utilize comparisons for physical properties, e.g. stress–strain curves and geometric deformation. In sharp contrast to popular reactive bond order potentials, our optimized NNP predicts straight crack propagation in graphene along both armchair and zigzag (ZZ) lattice directions, as well as higher fracture toughness of ZZ edge direction. Our study provides significant insight into crack propagation mechanisms on atomic scales and highlights strategies for NNP developments of broader materials.

2D materials↗

DOE OSTI2023

Performance of Windows in Walls With Continuous Insulation

Window openings in walls are a significant contributor to poor thermal performance because of thermal bridging through the framing members (e.g., studs, joists, plates, bracing) and because windows lack the thermal properties of insulation. Window installation guidance for walls with continuous insulation (CI) is critical for continued market growth of this energy efficiency technology. This research project offers window manufacturers a starting point and a potential path toward developing installation instructions for windows over CI. The objectives of the research include evaluating the common method for installing windows in walls with CI, as well as establishing acceptance criteria for evaluating the performance of windows installed in walls with and without CI. The research measures: 1. The performance characteristics (e.g., water management, structural integrity) of windows in walls without CI. 2. The performance of different thicknesses and types of CI used in walls. 3. The performance of different types of window assemblies (e.g., double-hung windows, mulled double-hung windows, mulled casement windows, and slider windows) installed over CI. 4. The performance of window flange types (e.g., rigid mounting and less robust flanges) installed over CI. 5. Installing windows over CI using baseline installation instructions versus window manufacturer installation instructions. The project’s sequential testing protocol consists of the following: • A water penetration resistance testing adapted from two ASTM standards: E331 (uniform static air pressure in four steps) and E547 (cyclic static air pressure) • A temperature cycling adapted from ASTM E2264 Method B (convective hot air) • A service condition wind loading test adapted from ASTM E330 • A six-month vertical displacement observation phase prior to the structural performance testing • A final water penetration resistance test after vertical displacement observation • A structural performance test adapted from ASTM E330. Key research findings include: • The criterion for passing a water penetration resistance test is that there is no water overflowing at the interior face of the studs. If there is any bubbling or slight pooling of water at the sill, then it must recede after the pressure is removed. Excessive leakage and/or water leaking to the interior face of the framing around the window constitutes a failure. • All single double-hung windows installed directly to lumber or over oriented strand board passed all test protocols. • For most wall specimens, the test results showed that the use of foam sheathing did not affect the performance of the window for water leakage. • All wall specimens underwent temperature cycling. The results indicated that temperature cycling had little to no effect on windows installed over foam sheathing. • For wall specimens that underwent six-month vertical displacement monitoring, the results showed that windows installed over foam sheathing do not sag over time. • The single-hung and double-hung windows installed using window manufacturer installation instructions passed the structural performance test, compared to failures observed in windows that were installed using generic installation instructions. The generic and manufacturer installation methods differed on the following construction details: type of fasteners, fastening patterns on the flanges, and window shimming details. • Additional testing is required to determine methods to improve structural pressure performance of slider windows. Potential solutions that would require additional testing may include fastener spacing, different types of fasteners, masonry window clips, construction adhesive, foam sealant, stronger window flange material, and/or straps.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Evaluation of Component Reliability in Photovoltaic Systems using Field Failure Statistics

Ongoing operations and maintenance (O&M) are needed to ensure photovoltaic (PV) systems continue to operate and meet production targets over the lifecycle of the system. Although average costs to operate and maintain PV systems have been decreasing over time, reported costs can vary significantly at the plant level. Estimating O&M costs accurately is important for informing financial planning and tracking activities, and subsequently lowering the levelized cost of electricity (LCOE) of PV systems. This report describes a methodology for improving O&M planning estimates by using empirically-derived failure statistics to capture component reliability in the field. The report also summarizes failure patterns observed for specific PV components and local environmental conditions observed in Sandia's PV Reliability, Operations & Maintenance (PVROM) database, a collection of field records across 800+ systems in the U.S. Where system-specific or fleet-specific data are lacking, PVROM-derived failure distribution values can be used to inform cost modeling and other reliability analyses to evaluate opportunities for performance improvements.

14 SOLAR ENERGY↗

DOE OSTI2025

Risk-informed Graded Approach for Reliability and Performance Assessment of Machine Learning and Artificial Intelligence for Advanced Condition Monitoring Techniques

With the shift away from time-based maintenance and toward condition-based maintenance, and to reduce overall maintenance costs, there has been an upsurge in the usage and development of advanced condition monitoring (ACM) techniques for real-time monitoring of nuclear power plant (NPP) components. ACM is particularly useful in the development of digital twins, which are designed to predict the failure or degradation of plant components. Successful implementation of ACM requires an assessment to inform the development of a risk-informed approach to evaluate the use of ACM to meet Nuclear Regulatory Committee (NRC) regulations for in-service testing (IST) programs. This includes the monitoring and diagnostics of reactor components and systems in current, new, and advanced reactors. A key component in ACM is the usage of machine learning (ML) and artificial intelligence (AI) algorithms that can employ real-time data from instrumentation and sensors to detect and predict reactor component degradations. Such predictive capabilities enable early detection of component degradation so as to help plant personnel plan and execute necessary maintenance. For successful implementation of ML/AI in ACM such that regulatory requirements are met, a risk-informed graded approach is needed to assess the reliability and performance of ML/AI for ACM. The American Society for Mechanical Engineers (ASME) developed their Operations and Maintenance (O&M) Code to provide guidance on safe, reliable O&M of NPPs. The IST section of the O&M Code specifically establishes requirements for IST and examination to gauge operational readiness of components in water-cooled NPPs. This paper presents a state-of-the-art review of how reliability and risk assessment can be integrated with ACM to assess component performance by non-nuclear industries. This is followed by different methodologies and approaches for conducting performance and reliability assessments so as to meet IST requirements for NPP components.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Risk-informed Graded Approach for Reliability and Performance Assessment for Advanced Condition Monitoring Techniques

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Use of Rig Parameter Data in Bit Constraint Models for Improved Drilling Performance at The Geysers

Surface parameter measurements are routinely used during deep well construction to monitor and guide drilling conditions for improved performance and reduced costs. However, these measurements are of reduced value without a standard to aid in evaluation and decision making. A method is demonstrated whereby drill bit constraint models are used to interpret drilling response parameters. Drill rig parameter data for well GDC-36 at the Geysers Geothermal Field Power were acquired by Geysers Power Company and drilling contractor Kenai Drilling using Pason US DataHub and evaluated. Drilling parameters are evaluated using laboratory-validated rock reduction models for predicting the phenomenological response of drag bits (Detournay and Defourny, 1992) along with other model constraints in computational algorithms. The method is used to evaluate overall bit performance, monitor bit integrity, and detect the presence of drillstring vibrations and other conditions contributing to bit failure; comparisons are made to observations of bit wear and damage. The method will be applied in real-time to improve decision-making on subsequent wells and has applicability to development of advanced analytics on future geothermal wells using real-time electronic drilling recorder (EDR) data for improved performance and reduced drilling costs.

15 GEOTHERMAL ENERGY↗

DOE OSTI2021

Development of a Vibration Technique Based on Geometric Optimization for Fatigue Life Evaluation of Sandwich Composite Structures

A major obstacle to obtaining cost-effective experimental data on the fatigue life of sandwich panels is the prohibitive amount of time and cost required to carry out millions of cycles. On the other hand, vibration techniques applied to sandwich geometries fail to match the stress patterns that are obtained from standard flexural fatigue tests. To overcome such limitations, a vibration-based fatigue technique is proposed, which entails the use of sandwich specimens whose geometries are optimized to reproduce the stress distribution observed during three point bend loading while vibrating at the first resonant frequency. The proposed vibration technique was experimentally validated. The results, compared with the average number of cycles to failure at different stress ratios obtained via the Three-Point Bending test, showed high levels of accuracy. The proposed method is robust and time effective and indicates the possibility of attaining fatigue lifetime prediction of a wide class of composite elements, such as sandwich panels.

36 MATERIALS SCIENCE↗