SEARCH · Engineering Papers

Results for “Reliability assessment”

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 631 records · Page 35

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Evaluation of the Simplified Assessment Peak Equivalent Stress Design Limit Probability of Failure

The ASME Boiler and Pressure Vessel Code Section III Division 5 Subsection HH Subpart A (HHA) outlines requirements and qualification methods for graphite core components in high temperature reactor environments. One such structural qualification method is the Simplified Assessment outlined in HHA-3220, which represents a comparison of service level specific equivalent stresses to allowable stress values derived from target probability of failures (POFs). The target POF is based on the structural reliability class (SRC) for the components and service condition of interest, and is used to establish design limits for combined membrane and peak equivalent stresses. Combined membrane stress limits are derived from two parameter Weibull distribution fits of the graphite grade specific tensile strength data and the target POF. The combined membrane stress limits are then scaled based on the ratio of flexural strength to tensile strength (referred hereinafter as Rtf) to establish the corresponding peak equivalent stress limits. It is desired that the target POF is at least maintained for both combined membrane and peak equivalent design limits, especially with the use of Rtf. The assessment presented herein examines tensile and flexural data for medium and fine grade graphites relative to the calculated combined membrane and peak equivalent stress limits per HHA-3220 and illustrates the simplified assessment method results in anticipated, or at least conservative, peak equivalent design stress limits.

36 - MATERIALS SCIENCE↗

DOE OSTI2024

Assessing decision boundaries under uncertainty

In order to make design decisions, engineers may seek to identify regions of the design domain that are acceptable in a computationally efficient manner. A design is typically considered acceptable if its reliability with respect to parametric uncertainty exceeds the designer’s desired level of confidence. Despite major advancements in reliability estimation and in design classification via decision boundary estimation, the current literature still lacks a design classification strategy that incorporates parametric uncertainty and desired design confidence. To address this gap, this paper offers a novel interpretation of the acceptance region by defining the decision boundary as the hypersurface which isolates the designs that exceed a user-defined level of confidence given parametric uncertainty. This work addresses the construction of this novel decision boundary using computationally efficient algorithms that were developed for reliability analysis and decision boundary estimation. The approach proposed in this paper is verified on two physical examples from structural and thermal analysis using Support Vector Machines and Efficient Global Optimization-based contour estimation.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Assessment of Process Modeling Tools for Determining Variability in Additively Manufactured Parts

The Advanced Materials and Manufacturing Technologies (AMMT) program aims to accelerate the development, qualification, demonstration, and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy However, the unique aspects of additive manufacturing (AM) materials in terms of their processing history, microstructure, and properties, are a major barrier for qualification and certification of nuclear components. Much of this challenge may be attributed to component scale variations in microstructure and properties that are driven by local influences of process conditions and geometry on thermal history, melt pool dynamics, and corresponding microstructure evolution. Computational modeling tools may be helpful in this regard to aid in predicting and controlling this level of variability. The purpose of this report is to review the current state-of-the-art for process modeling with regards to metal AM. For this purpose, we consider specifically the case study of laser powder bed fusion (LPBF) processing of SS316, a family of alloys that are both commonly used in nuclear energy applications and suitable for AM processing. The report first introduces the necessary components of a process modeling workflow, followed by a review of the current status of each. At the end, application of these modeling tools to understanding variability in AM process given their current state are considered, and recommendations for future development are proposed

36 MATERIALS SCIENCE↗

DOE OSTI2021

International collaboration framework for the calculation of performance loss rates: Data quality, benchmarks, and trends (towards a uniform methodology)

Abstract The IEA PVPS Task 13 group, experts who focus on photovoltaic performance, operation, and reliability from several leading R&D centers, universities, and industrial companies, is developing a framework for the calculation of performance loss rates of a large number of commercial and research photovoltaic (PV) power plants and their related weather data coming across various climatic zones. The general steps to calculate the performance loss rate are (i) input data cleaning and grading; (ii) data filtering; (iii) performance metric selection, corrections, and aggregation; and finally, (iv) application of a statistical modeling method to determine the performance loss rate value. In this study, several high‐quality power and irradiance datasets have been shared, and the participants of the study were asked to calculate the performance loss rate of each individual system using their preferred methodologies. The data are used for benchmarking activities and to define capabilities and uncertainties of all the various methods. The combination of data filtering, metrics (performance ratio or power based), and statistical modeling methods are benchmarked in terms of (i) their deviation from the average value and (ii) their uncertainty, standard error, and confidence intervals. It was observed that careful data filtering is an essential foundation for reliable performance loss rate calculations. Furthermore, the selection of the calculation steps filter/metric/statistical method is highly dependent on one another, and the steps should not be assessed individually.

14 SOLAR ENERGY↗

DOE OSTI2020

Solar Energy Research Institute for India and the United States (SERIIUS): Lessons and Results from a Binational Consortium

This book describes the development, functioning, and results of a successful binational program to promote significant scientific advances in Earth-abundant photovoltaics (PV) and concentrated solar power (CSP), advanced process/manufacturing technologies, multiscale modeling and reliability testing, and analysis of integrated solar energy systems. SERIIUS is a consortium between India and the United States dedicated to developing new solar technologies and assessing their potential impact in the two countries. The consortium consists of nearly 50 institutions including academia, national laboratories, and industry, with the goal of developing significant new technologies in all areas of solar deployment. In addition, the program focused on workforce development through graduate students, post-doctoral students, and an international exchange program. Particular emphasis was placed on the following efforts: creating disruptive technologies in PV and CSP through high-impact fundamental and applied research and development (R&D); identifying and quantifying the critical technical, economic, and policy issues for solar energy development and deployment in India; overcoming barriers to technology transfer by teaming research institutions and industry in an effective project structure; building a new platform for binational collaboration using a formalized R&D project structure, along with effective management, coordination, and decision processes; creating a sustainable network and workforce development program from which to build large collaborations and fostering a collaborative culture and outreach programs. This includes using existing and new methodologies for collaboration based on advanced electronic and web-based communication to facilitate functional international teams. The book summarizes the general lessons learned from these experiences.

14 SOLAR ENERGY↗

DOE OSTI2021

Bond dissociation energies of low-valent lanthanide hydroxides: lower limits from ion–molecule reactions and comparisons with fluorides

Despite that bond dissociation energies (BDEs) are among the most fundamental and relevant chemical properties they remain poorly characterized for most elementary lanthanide hydroxides and halides. Lanthanide ions Ln + = Eu + , Tm + and Yb + are here shown to react with H 2 O to yield hydroxides LnOH + . Additionally, under low-energy conditions such reactions must be exothermic, which implies a lower limit of 499 kJ mol -1 for the Ln + –OH BDEs. This limit is significantly higher than previously reported for YbOH + and is unexpectedly similar to the BDE for Yb + –F. To explain this apparent anomaly, it is considered feasible that the inefficient hydrolysis reactions observed here in a quadrupole ion trap mass spectrometer may actually be endothermic. More definitive and broad-based evaluations and comparisons require additional and more reliable BDEs and ionization energies for key lanthanide molecules, and/or energies for ligand-exchange reactions like LnF + OH ↔ LnOH + F. The hydroxide results motivated an assessment of currently available lanthanide monohalide BDEs. Among several intriguing relationships is the distinctively higher BDE for neutral LuF versus cationic LuF + , though quantifying this comparison awaits a more accurate value for the anomalously high ionization energy of LuF.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

PyTUQ: Python Toolkit for Uncertainty Quantification

SAND2025-03661O PyTUQ is a user-friendly software toolkit designed to help researchers and professionals understand and manage uncertainty in several scientific fields. By providing tools for analyzing how uncertainties affect outcomes, PyTUQ can be applied in areas such as energy production, and biology. Its unique approach allows users to make more informed decisions by assessing risks and improving predictions. Whether you're studying combustion processes or exploring complex biological systems, PyTUQ empowers you to gain deeper insights and enhance the reliability of your results. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗

DOE OSTI2025

Irradiation Vehicles for Evaluating SiC/SiC Cladding Bowing Under Neutron Flux Gradients

Silicon carbide fiber–reinforced silicon carbide matrix (SiC/SiC) composites are among the most promising candidates for long term accident-tolerant nuclear fuel cladding. A key challenge related to their deployment is lateral bowing caused by differential radiation-induced swelling under dose or temperature gradients, which could obstruct coolant flow or interfere with control rod/blade movements. Although previous modeling efforts have predicted bowing behavior in light-water reactor (LWR) environments, experimental validation remains limited, especially at prototypic LWR temperatures. This study addresses that gap by irradiating six reduced-length SiC/SiC cladding tubes (~600 mm) in the High Flux Isotope Reactor (HFIR) at ~300°C, which is representative of LWR conditions. The tubes will be housed in a sealed vessel with an inert gas gap to maintain target temperatures and prevent direct coolant contact. Arranged in three pairs, each set will receive a different radiation dose (low, medium, high), with the central pair receiving ~0.1 displacements per atom (dpa)—the expected dose for peak bowing. The experiment will determine the dose-dependent bowing behavior and validate predictive finite element models. In this work, the tubes are freely suspended from pins to allow for unconstrained bowing; however, we present a concept for introducing localized constraints to represent grid spacer effects. Post-irradiation examination will include swelling measurements and profilometry to assess bowing and compare the results with model predictions. This work aims to confirm the conditions under which maximum bowing occurs so as to improve the reliability of SiC/SiC performance models in nuclear applications.

Russell, Nick [ORNL] (ORCID:0000000296099820)↗

DOE OSTI2024

Major Drivers of Long-Term Distribution Transformer Demand

Distribution transformers, used to step-down medium voltage to service-voltage level for end-use electrical consumption, are currently experiencing major shortages. Utilities are experiencing extended lead times for transformers of up to 2 years (a 4x increase on lead times pre-2022) and prices have gone up by as much as 5-6 times in the past 2 years. Current shortages have been attributed to pent-up post-pandemic demand, workforce shortages and low retention rates, component supply chain challenges, and materials shortages (grain-oriented electrical steel, aluminum, and copper). The supply of this equipment is critical for the reliability and growth of the power system, and in meeting administration climate goals in terms of electrification of demand and the growth of renewable energy. This report details some of the initial analysis conducted by the National Renewable Energy Laboratory (NREL), supported by the Department of Energy's Office of Electricity and Office of Policy, in assessing the long-term demand trends for distribution transformers. Expected increased demand is due to a confluence of not only electrification and renewable energy growth, but also in the context of aging electric infrastructure, increased frequency and severity of extreme weather events, and utility-driven investments in reliability and resiliency of the electricity distribution system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Dynamic Model Agnostic Reliability Evaluation of Machine-Learning Models Integrated in Instrumentation & Control Systems

In recent years, the field of data-driven neural network-based machine learning (ML) algorithms has grown significantly and spurred research in its applicability to instrumentation and control systems. While they are promising in operational contexts, the trustworthiness of such algorithms is not adequately assessed. Failures of ML-integrated systems are poorly understood; the lack of comprehensive risk modeling can degrade the trustworthiness of these systems. In recent reports by the National Institute for Standards and Technology, trustworthiness in ML is a critical barrier to adoption and will play a vital role in intelligent systems' safe and accountable operation. Thus, in this work, we demonstrate a real-time model-agnostic method to evaluate the relative reliability of ML predictions by incorporating out-of-distribution detection on the training dataset. It is well documented that ML algorithms excel at interpolation (or near-interpolation) tasks but significantly degrade at extrapolation. This occurs when new samples are "far" from training samples. The method, referred to as the Laplacian distributed decay for reliability (LADDR), determines the difference between the operational and training datasets, which is used to calculate a prediction's relative reliability. LADDR is demonstrated on a feedforward neural network-based model used to predict safety significant factors during different loss-of-flow transients. LADDR is intended as a "data supervisor" and determines the appropriateness of well-trained ML models in the context of operational conditions. Ultimately, LADDR illustrates how training data can be used as evidence to support the trustworthiness of ML predictions when utilized for conventional interpolation tasks.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Assessment of Nuclear Sensors and Instrumentation Maturity in Advanced Nuclear Reactors

In the last decade, 97% of the worldwide commercial nuclear reactors connected to the grid were Light Water Reactors (LWRs). LWRs are expected to stay the dominant type of nuclear reactors for the next few decades. Reliable and redundant safety systems are required in nuclear reactors to ensure safe operation and shutdown in abnormal conditions. These safety systems are actuated by the signals obtained from several sensors and instrumentation in and out of the reactor core. Research and Development (R&D) in advanced sensors and instrumentation has gained extra attention, particularly following the accident at the Three Mile Island Unit-2 (TMI-2). In LWRs, these sensors and instrumentation have shown a high level of maturity with long operating experience. Ensuring the compatibility of these sensors and instrumentation with advanced nuclear reactors (Generation IV) is necessary, particularly with the expected expansion of the nuclear industry in the next few decades. Nuclear Sensor and instrumentation technologies used in the current generation of LWRs were investigated. The compatibility of these technologies with advanced reactors was assessed by comparing the advanced reactors' environments with those of the currently operating reactors. In addition to that, the needed R&D for such technologies was highlighted. In comparison with the LWRs environment, it was shown that advanced reactor environments are expected to experience elevated temperatures, a fast neutron spectrum, and a harsh corrosion environment. It was demonstrated that R&D is required mainly for fixed in-core nuclear sensors and instrumentation, while it is not a priority for ex-core nuclear sensors and instrumentation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Common practices for quantifying methane emissions from plumes detected by remote sensing

This document provides a set of community-accepted practices for quantifying methane emissions based on plumes detected via spectroscopic remote sensing. Its primary goal is to promote consistency in the generation, validation, reporting, and quality assessment of methane emission estimates derived from remote sensing radiances. Developed by subject matter experts with deep experience across all stages of the measurement process, this guidance reflects a critical evaluation of current methodologies and highlights key practices needed to produce reliable, interoperable, and traceable products. The focus is specifically on methane emissions quantified from distinct plumes originating from localized sources, rather than diffuse emissions spread over large regions, which are beyond the scope of this work. This document is intended to serve both data producers and users. For producers, it offers a framework for aligning with field-recognized standards to ensure their outputs meet rigorous quality and transparency criteria. For users, it provides a reference to assess dataset fitness-for-purpose by highlighting essential metadata, assumptions, and methodological choices that underpin emission estimates. By fostering a shared understanding of best practices, this work aims to enhance comparability, confidence, and utility of remotely sensed methane emission products.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Benefits and Challenges of California Offshore Wind Electricity: An Updated Assessment

Offshore wind (OSW) technology has recently been included in California’s plans to achieve 100% carbon-free electricity by 2045. As an emerging technology, many features of OSW are changing more rapidly than established renewable options and are shaped by local circumstances in unique ways that limit transferrable experiences globally. This paper fills a gap in the literature by providing an updated technological assessment of OSW in California to determine its viability and competitiveness in the state’s electricity generation mix to achieve its near-term energy and environmental goals. Through a critical synthesis and extrapolation of technical, social, and economic analyses, we identify several major improvements in its potential. First, we note that while estimates of OSW’s costs per MWh of installed capacity have generally documented and projected a long-term decline, recent technical, microeconomic, and macroeconomic factors have caused significant backsliding of this momentum. Second, we project that the potential dollar value benefits of OSW’s greenhouse gas reduction capabilities have increased by one to two orders of magnitude, primarily due to major upward revisions of the social cost of carbon. Several co-benefits, including enhanced reliability, economic growth, and environmental justice, look to be increasingly promising due to a combination of technological advances and policy initiatives. Despite these advancements, OSW continues to face several engineering and broader challenges. We assess the current status of these challenges, as well as current and future strategies to address them. We conclude that OSW is now overall an even more attractive electricity-generating option than at the beginning of this decade.

Rose, Adam (ORCID:0000000333477684)↗

DOE OSTI2023

Skillful Multi‐Month Predictions of Ecosystem Stressors in the Surface and Subsurface Ocean

Abstract Anthropogenic carbon emissions and associated climate change are driving rapid warming, acidification, and deoxygenation in the ocean, which increasingly stress marine ecosystems. On top of long‐term trends, short term variability of marine stressors can have major implications for marine ecosystems and their management. As such, there is a growing need for predictions of marine ecosystem stressors on monthly, seasonal, and multi‐month timescales. Previous studies have demonstrated the ability to make reliable predictions of the surface ocean physical and biogeochemical state months to years in advance, but few studies have investigated forecast skill of multiple stressors simultaneously or assessed the forecast skill below the surface. Here, we use the Community Earth System Model (CESM) Seasonal to Multiyear Large Ensemble (SMYLE) along with novel observation‐based biogeochemical and physical products to quantify the predictive skill of dissolved inorganic carbon (DIC), dissolved oxygen, and temperature in the surface and subsurface ocean. CESM SMYLE demonstrates high physical and biogeochemical predictive skill multiple months in advance in key oceanic regions and frequently outperforms persistence forecasts. We find up to 10 months of skillful forecasts, with particularly high skill in the Northeast Pacific (Gulf of Alaska and California Current Large Marine Ecosystems) for temperature, surface DIC, and subsurface oxygen. Our findings suggest that dynamical marine ecosystem prediction could support actionable advice for decision making.

Environmental Sciences & Ecology↗

DOE OSTI2025

Spurious solar-wind effects on acceleration noise in LISA Pathfinder

Spurious solar-wind effects are a potential noise source in future Laser Interferometer Space Antenna (LISA) measurements. One noise coupling mechanism is constrained by estimating solar-wind effects on acceleration noise in LISA Pathfinder (LPF). While LISA is designed for drag-free differential measurement, predicting the realistic impact both bounds the operational environment and assesses whether LISA could provide serendipitous space-weather observations. Data from NASA's Advanced Composition Explorer (ACE), situated at the L1 Lagrange point, serves as a reliable source of solar-wind data. The data sets are compared over the 114 d time period from 1 March 2016 to 23 June 2016. This period gives the longest readily-available open data set, without interference from other commissioning activities. To evaluate space weather effects, the data from both satellites are formatted, gap-filled/interpolated, and fast-Fourier transformed for amplitude spectral density and coherence comparisons. Solar wind effects are not seen in a coherence plot between LPF and ACE; modest coherence in the planned LISA observational frequency band can be attributed to chance. This result indicates that measurable correlation due to solar-wind acceleration noise over 3 month timescales will be a negligible noise source. LISA is unlikely to inform solar wind measurements routinely. Another source of noise from the Sun, solar radiation pressure, is estimated to impart greater acceleration noise, but has yet to be analyzed.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

805 Stepped Plan Project Description

The 805 MHz system utilizes 1.25 MW class klystron amplifiers. The Solid-State Amplifier (SSA) technology has been utilized in the SC accelerator technology, but more powerful sources are needed for use in the NC accelerator facilities such as LASNCE. The SSA topologies that are widely used need to be scaled and tested for reliability and operation in a high impact accelerator facility, such as the 805 MHz SCCL in Los Alamos. Operational experience with high power SSA needs to be assessed prior to installation of an SSA unit at LANSCE. The RFE group at LANSCE is looking for collaboration in the development of the Solid-State Amplifier.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

Kivalina Biomass Reactor

This report summarizes work performed under DOE Award DE-EE00010149 to support the reliable operation of a community-scale biochar reactor system in Kivalina, Alaska. The project focused on improving sanitation and waste management in a remote community by assessing the installed system, identifying spare parts, defining key performance indicators (KPIs), preparing operator and maintenance manuals, and developing mobile reporting tools for operational data and KPI tracking. The team also produced training materials and recorded videos to support operator onboarding and continuity. The project demonstrated progress in system readiness, documentation, and digital reporting, while also identifying challenges common to remote deployments, including travel constraints, upstream system failures, and local resource limitations. This work provides a practical framework for improving the operation, monitoring, and future replication of biomass reactor systems in remote communities.

09 BIOMASS FUELS↗

DOE OSTI2024

Application of printed strain gauges in prototypical nuclear reactor conditions

This report discusses the current development and testing of additively manufactured temperature sensors and resistive/ capacitive strain gauges. This has potential to improve the sensor design and manufacturing techniques to meet the requirements of in-pile monitoring of mechanical properties and structural health of materials and specimens in current and advanced nuclear test reactors (i.e., in terms of environment conditions, sample geometry, and materials compatibility). The developmental additively manufactured strain gauges are exposed to separate effects testing (i.e., mechanical strain (up to 1000 µe), high temperature (up to 700 °C)) to determine environmental factors that affect the performance of the strain gauge. The robustness and integrity of a printed strain gauge layer exposed to a molten salt environment for up to 500 hours was evaluated, with the goal of assessing material compatibility of printed strain sensors for instrumented surveillance test articles in molten salt reactors. In addition, sensor qualification methodologies are further developed for determining the reliability and robustness at the interface of the additively manufactured strain gauge materials.

36 - MATERIALS SCIENCE↗