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Results for “Reliability analysis”

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 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Higher order mode analysis of a 915 MHz 2-cell cavity for a prototype industrial accelerator

A possible solution to reduce the complexity posed by the cryogenic systems in a superconducting RF accelerator for industrial applications, is to capitalize on the advances achieved by the Nb3Sn superconducting RF technology, as well as the feasibility of a reliable 4 K cooling system, based on commercial cryocoolers. Following this philosophy, the conceptual design for a prototype, conduction-cooled, 4 MeV, 20 kW SRF electron linac, is being developed at Jefferson Lab. Such design is based on a 915 MHz two-cell Nb3Sn cavity. In this contribution, we present the proposed cavity design, including the fundamental power coupler, and the analysis of the Higher Order Modes, using numerical simulations to estimate the potentially dangerous modes and to provide the requirements for damping for reliable operations with a cryocooler.

Rimmer, Robert↗
DOE OSTI2025

Model-driven prediction for accelerator magnet diagnostics to improve operation reliability

Reliability is one of the most critical metrics for accelerator operation, especially in user facilities. To reduce costly facility downtime and provide an operational environment where system performance can be reliably predicted in support of scientific studies, we are developing a model-driven approach for prediction and anomaly detection. Here, in this study, we present the application of a model-driven method that employs a linear regression model to predict the future temperature, in real time, of accelerator magnets at the NSLS-II light source. This approach enables proactive identification of magnet-heating issues, facilitating magnet flushing prior to the occurrence of permanent damage without interrupting machine operation. The implementation of this method in the NSLS-II control room is described and the analysis of the online results is presented. The results demonstrate the model’s effectiveness in providing early alerts to engineers and improving the reliability of accelerator operations.

36 MATERIALS SCIENCE↗
DOE OSTI2019

SONET: a semantic ontological network graph for managing points of interest data heterogeneity

Scalability, standardization, and management are important issues when working with very large Volunteered Geographic Information (VGI). VGI is a rich and valuable source of Points of Interest (POI) information, but its inherent heterogeneity in content, structure, and scale across sources present major challenges for interlinking data sources for analysis. To be useful at scale, the raw information needs to be transformed into a standardized schema that can be easily and reliably used by data analysts. In this work, we tackle the problem of unifying POI categories (e.g. restaurants, temple, and hotel) across multiple data sources to aid in improving land use maps and population distribution estimation as well as support data analysts wishing to fuse multiple data sources with the OpenStreetMap (OSM) mapping platform or working with projects that are already configured in the OSM schema and wish to add additional sources of information. Graph theory and its implementation through the SONET graph database, provides a programmatic way to organize, store, and retrieve standardized POI categories at multiple levels of abstraction. Additionally, it addresses category heterogeneity across data sources by standardizing and managing categories in a way that makes cross-domain analysis possible.

Palumbo, Rachel↗
DOE OSTI2025

Nuclear Reactor Heat Extraction for Synthetic Fuel Plants

This report looks at the viability and best approach when producing synthetic fuels using heat and power supplied by advanced nuclear energy systems. The report looks at a low temperature integration pathway with four types of advanced reactors: a pressurized water reactor (PWR), an advanced light water reactor (A-LWR), a sodium fast reactor (SFR), and a high-temperature gas-cooled reactor (HTGR). A failure modes and effects analysis (FMEA) of the coupling system between the nuclear plant and the synthetic fuel systems is performed with the goal of identifying the reliability of such a thermal delivery system. Furthermore, a high temperature pathway is investigated for synfuel coupling to determine if this is more efficient and more cost effective as a coupling approach.

10 - SYNTHETIC FUELS↗
DOE OSTI2015

Experimental spectra analysis in THM with the help of simulation based on the Geant4 framework

The Coulomb barrier and electron screening cause difficulties in directly measuring nuclear reaction cross sections of charged particles in astrophysical energies. The Trojan-horse method has been introduced to solve the difficulties as a powerful indirect tool. In order to understand experimental spectra better, Geant4 is employed to simulate the method for the first time. Validity and reliability of the simulation are examined by comparing the experimental data with simulated results. Lastly, the Geant4 simulation can give useful information to understand the experimental spectra better in data analysis and is beneficial to the design for future related experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

CSP Plant Optimization Study for the California Power Market (“CalCSP”) (Final Technical Report)

Concentrating Solar Power (CSP) with thermal energy storage offers a unique and strategic opportunity to support California’s clean energy transition. Unlike photovoltaic (PV) systems, CSP with thermal storage can generate electricity after sunset and during periods of high demand, making it a valuable complement to intermittent renewable resources. CSP also provides synchronous, inertia-contributing generation, long-duration storage, and flexible dispatch—capabilities increasingly important as thermal plants retire. This report summarizes the findings of the CSP Plant Optimization Study for the California Power Market or “CalCSP study,” which evaluated the technical, economic, environmental, and policy factors that influence the deployment of CSP technologies in California. The CalCSP study was conducted to assess how CSP can contribute to California’s long-term decarbonization goals while enhancing grid reliability, supporting local economic development, and making efficient use of land and transmission resources. It draws on detailed modeling of CSP performance and costs, site suitability analysis, policy reviews, and stakeholder engagement across utilities, regulators, developers, and community organizations. The analysis focuses on mature molten-salt tower technology and incorporates lessons learned from the global CSP fleet, distinguishing today’s CSP from earlier first-of-a-kind projects in the U.S. The findings support a more prominent role for CSP in California’s evolving clean energy landscape. With strategic planning, targeted policy support, and continued cost improvements, CSP can complement PV and batteries to deliver reliable, around-the-clock clean electricity—especially in areas with high solar resource and constrained grid capacity.

14 SOLAR ENERGY↗
DOE OSTI2024

Experimental and modeling study of the effect of confinement on the thermal decomposition of organic materials

Simultaneous Thermal Analysis is widely used to study thermal decomposition of a variety of organic materials, and the choice of experimental conditions is very important to obtain reliable mass loss and heat flow curves. Here in this work we investigate the effect of confinement on the thermal decomposition of organic materials. As an example, we explore high-density polyethylene (HDPE) and one of its pyrolysis products, namely eicosane (C 20 H 42 ), through experiments and modeling in open crucibles and crucibles closed with a pierced lid. A new model is developed for evaporation and sublimation from open and pinhole thermal-analysis pans. It considers the kinetic resistance of evaporation at the liquid-vapor interface, inhibition of evaporation by buildup of vapor inside the pan, thermal expansion of vapor inside the pan, and diffusion of vapor from the pan. The model is validated using simultaneous heat-flow and mass-loss measurements of n-eicosane evaporation for various pinhole sizes, down to 50 µm. The importance of product evaporation inhibition for measuring polymer decomposition was demonstrated using HDPE. This study sheds light on the effect of confinement on the mass loss rate of organic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

In situ liquid SEM imaging analysis revealing particle dispersity in aqueous solutions

A quantitative description on dispersity of boehmite (γ-AlOOH) particles, a key component for waste slurry at Hanford sites, can provide useful knowledge for understanding various physicochemical nature of the waste. In this work, in situ liquid scanning electron microscopy (SEM) was used to evaluate the dispersity of particles in aqueous conditions using a microfluidic sample holder, System for Analysis at Liquid Vacuum Interface (SALVI). Secondary electron (SE) images and image analyses were performed to determine particle centroid locations and the distance to the nearest neighbour particle centroid, providing reliable rescaled interparticle distances as a function of ionic strength in acidic and basic conditions. Our finding of the particle dispersity is consistent with physical insights from corresponding particle interactions under physicochemical conditions, demonstrating delicate changes in dispersity of boehmite particles based on novel in situ liquid SEM imaging and analysis.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Learning and Fast Adaptation for Grid Emergency Control via Deep Meta Reinforcement Learning

As power systems are undergoing a significant transformation with more uncertainties, less inertia and closer to operation limits, there is increasing risk of large outages. Thus, there is an imperative need to enhance grid emergency control to maintain system reliability and security. Towards this end, great progress has been made in developing deep reinforcement learning (DRL) based grid control solutions in recent years. However, existing DRL-based solutions have two main limitations: 1) they cannot handle well with a wide range of grid operation conditions, system parameters, and contingencies; 2) they generally lack the ability to fast adapt to new grid operation conditions, system parameters, and contingencies, limiting their applicability for real-world applications. Here, in this paper, we mitigate these limitations by developing a novel deep meta-reinforcement learning (DMRL) algorithm. The DMRL combines the meta strategy optimization together with DRL, and trains policies modulated by a latent space that can quickly adapt to new scenarios. We test the developed DMRL algorithm on the IEEE 300-bus system. We demonstrate fast adaptation of the meta-trained DRL polices with latent variables to new operating conditions and scenarios using the proposed method, which achieves superior performance compared to the state-of-the-art DRL and model predictive control (MPC) methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Modeling and Control of Cascaded Bridgeless Multilevel Rectifier Under Unbalanced Load Conditions

The goal of this project is to model and control a novel unidirectional cascaded multilevel bridgeless rectifier as an active front end in medium and high voltage applications. This topology has many advantages over a conventional cascaded H-bridge rectifier, such as lower implementation cost, higher reliability, and greater flexibility with similar power quality.The steady-state mathematical model is used to develop a method for the voltage balancing of dc cells. Power factor analysis is discussed to achieve unity power factor using fully controlled hbridge cells. Power loss, efficiency, and cost comparison studies between the traditional cascaded H-Bridge converter and the proposed bridgeless converter demonstrate the advantages. A novel control strategy is proposed to achieve dc voltage balancing, fast and robust grid synchronization and power factor correction under unbalanced load conditions. Simulation and experimental results validate the models and control method.

Cascaded Bridgeless Rectifier, Power factor analys↗
DOE OSTI2022

Towards Z-Next: The Integration of Theory, Experiments, and Computational Simulation in a Bayesian Data Assimilation Framework

Making reliable predictions in the presence of uncertainty is critical to high-consequence modeling and simulation activities, such as those encountered at Sandia National Laboratories. Surrogate or reduced-order models are often used to mitigate the expense of performing quality uncertainty analyses with high-fidelity, physics-based codes. However, phenomenological surrogate models do not always adhere to important physics and system properties. This project develops surrogate models that integrate physical theory with experimental data through a maximally-informative framework that accounts for the many uncertainties present in computational modeling problems. Correlations between relevant outputs are preserved through the use of multi-output or co-predictive surrogate models; known physical properties (specifically monotoncity) are also preserved; and unknown physics and phenomena are detected using a causal analysis. By endowing surrogate models with key properties of the physical system being studied, their predictive power is arguably enhanced, allowing for reliable simulations and analyses at a reduced computational cost.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Towards automated and real-time multi-object detection of anguilliform fishes from sonar data using YOLOv8 deep learning algorithm

Eels (Anguilla spp.), including American eels (Anguilla rostrata), European eels (Anguilla anguilla), and Japanese eels (Anguilla japonica), are species of critical management and regulatory concern due to their vulnerability to various stressors during downstream migrations. Accurate and efficient detection of migrating eels can improve our understanding of fish behaviors and fish-hydraulic structure interactions, thereby facilitating the design, operation, and optimization of more effective downstream passage facilities from both biological and economic perspectives. However, a real-time, automated framework for detecting migrating eels in real-world applications is currently lacking. Leveraging imaging sonar as a reliable technology for fish passage monitoring, field data are acquired using imaging sonar and then converted to single sonar frames/images for subsequent analysis. In this study, a framework based on the You Only Look Once Version 8 (YOLOv8)-based convolutional neural network is proposed for multi-object detection of eels and non-eel fish using the sonar images after image subtraction and additional wavelet denoising. The results from both training and testing phases demonstrate that the framework's ability can successfully detect both eels and non-eel fish in preprocessed sonar images, achieving F1-scores and mAP@0.50 exceeding 0.84. Additionally, the incorporation of wavelet denoising during preprocessing slightly improve detection performance. Furthermore, the transferability of this framework from eel to lamprey detection is demonstrated to be feasible given the similar morphological characteristics of these two species. Overall, the proposed framework achieves accurate and efficient detection of migrating eels, providing reliable and real-time information that can help conserve vulnerable eel and eel-like populations.

Deep learning↗
DOE OSTI2012

Preliminary structural design conceptualization for composite rotor for verdant power water current turbine

Sandia National Laboratories (SNL) and Verdant Power Inc. (VPI) have partnered under a Cooperative Research and Development Agreement (CRADA) to develop a new kinetic hydropower rotor. The rotor features an improved hydrodynamic and structural design which features state-of-the-art technology developed for the wind industry. The new rotor will have higher energy capture, increased system reliability, and reduction of overall cost of energy. This project was divided into six tasks: (1) Composite Rotor Project Planning and Design Specification; (2) Baseline Fatigue Testing and Failure analysis; (3) Develop Blade/Rotor Performance Model; (4) Hydrofoil Survey and Selection; (5) FEM Structural Design; and (6) Develop Candidate Rotor Designs and Prepare Final Report.

13 HYDRO ENERGY↗
DOE OSTI2017

Generation of an Activation Map for Decommissioning Planning of the Berlin Experimental Reactor-II

The BER-II is an experimental facility with 10 MW that was operated since 1974. Its operation will end in 2019. To support the decommissioning planning, a map with the overall distribution of relevant radionuclides has to be created according to the state of the art. The activation analysis comprises all load periods until the planned shutdown. A procedure for an activation calculation of the pool structure of the BER-II research reactor including the concrete shielding is presented. With the combination of the options offered by MCNP6 and PARTISN, an effective method to compute the neutron flux for a reactor geometry model with 2,790,000 cells could be achieved. The fact that for calculations with PARTISN some extra effort to generate the XS is needed is more than compensated by the fact that for all volumes of the model, neutron fluxes are produced that can be subsequently used for the activation calculation. With the power history provided together with the material compositions, an activation map was created for the whole structure, even for the most remote parts. The activity can be calculated for all nuclides of the FISPACT library. Depending on material and irradiation history, however, only a limited number of nuclides must be regarded to reduce the size of activation data base. The results for the activation at calibration points give an example that the use of detailed calculation methods allows reliable estimation of the activity of relevant nuclides. The mean and the maximum activity can be determined. For a more detailed analysis, it is desirable to provide some more calibration points and realistic material specifications including impurities where the results of the activation can be validated, especially for more remote regions of the concrete structures.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

In-situ TEM analysis of the phase transformation mechanism of a Cu–Al–Ni shape memory alloy

We report that minimizing phase transformation (PT) hysteresis is of crucial importance for reliability of shape memory alloy (SMA)-based devices, where the lattice strain/stress caused by thermal hysteresis leads to functional degradation. As a result, understanding structural factors that control PT pathway is critical for development of materials with high reversibility. In this study, two distinct PT mechanisms (from γ$'\atop{1}$ martensite to β 1 austenite phase) in Cu–Al–Ni SMAs were revealed by in-situ TEM observation. A growth-dominant conventional PT mechanism shows in the fast quench sample, whereas a nucleation-dominant PT mechanism that suppresses interface propagation and induces high thermal hysteresis displays in the slow quench sample. By characterizing the atomic scale composition and microstructure we discover that slow quenching induces nanoprecipitation that changes chemistry of the matrix alloy, which in turn causes the higher PT hysteresis and temperature, while fast quenching avoids the formation of these nanoprecipitates. Lastly, our finding provides valuable insights into the fabrication of SMAs with better reliability.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Security by Design Economics Analysis for Advanced Reactors and Small Modular Reactors Project Interim Report for FY2021

Advanced Reactor and Small Modular Reactor (AR/SMR) designs have the potential to provide clean, reliable baseload energy. Ensuring the capability to deploy these reactors in an economically viable fashion is of interest to industry. A large portion of the expected operating costs of AR/SMRs involves the security of the plant. Security by Design (SeBD) is the practice of including features in the design and construction of the site, with the intent to decrease the operating costs related to security. Quantifying the increase or decrease in the overall lifetime cost to the plant as a result of SeBD is of paramount importance in understanding the disadvantages and benefits of such activities. The National Nuclear Security Administration’s (NNSA) Office of International Nuclear Security (INS) is funding the development of a methodology whereby the capital expenses and operating expenses, as well as the physical security effectiveness, of SeBD can be quantified for AR/SMRs. This report is an interim report on the progress of the work performed by Sandia National Laboratories (SNL), Idaho National Laboratory, and Oak Ridge National Laboratory (ORNL). It is the second annual report on this work.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Governing in Time: Temporal Capacity and the Feasibility of Energy Transitions

Energy systems function as both technological systems and temporal institutions that shape how societies coordinate, justify, and support collective choices over time. This paper introduces the concept of governance horizons to explain why energy transitions can remain morally supported yet become institutionally weak under increasing pressure. We argue that governability depends on institutions' capacity to synchronize across multiple timeframes - aligning short-term decisions with intermediate coordination and long-term commitments. When this synchronization fails, transitions struggle not because their goals are dismissed, but because governance lacks sufficient time to justify, coordinate, and uphold decisions. Comparative analysis of San Antonio, Texas, and Interior Alaska reveals how energy system pressures generate distinct temporal configurations: San Antonio exhibits governance horizon stretching, where institutions must simultaneously meet near-term reliability demands and long-term transformation goals, while Interior Alaska exhibits horizon compression, where extreme environmental constraints force decision-making into short stabilization cycles. In both contexts, public support for sustainability goals coexists with institutional strain because evaluative judgments are unevenly distributed over time. A temporal configuration analysis is introduced as a diagnostic analytic stance for identifying these patterns. By treating temporal alignment as an explanatory variable rather than a background condition, this approach clarifies how feasibility, sequencing, and legitimacy are shaped by constraints on institutional time. The analysis demonstrates that successful energy transitions depend not only on technological innovation or institutional support, but on governance systems’ ability to sustain credible coordination across multiple time horizons.

Comparative case study↗
DOE OSTI2024

Automated Gold Nanorod Spectral Morphology Analysis Pipeline

The development of a colloidal synthesis procedure to produce nanomaterials with high shape and size purity is often a time-consuming, iterative process. This is often due to quantitative uncertainties in the required reaction conditions and the time, resources, and expertise intensive characterization methods required for quantitative determination of nanomaterial size and shape. Absorption spectroscopy is often the easiest method for colloidal nanomaterial characterization. However, due to the lack of a reliable method to extract nanoparticle shapes from absorption spectroscopy, it is generally treated as a more qualitative measure for metal nanoparticles. This work demonstrates a gold nanorod (AuNR) spectral morphology analysis tool, called AuNR-SMA, which is a fast and accurate method to extract quantitative structural information from colloidal AuNR absorption spectra. To demonstrate the practical utility of this model, we apply it to three distinct applications. First, we demonstrate this model's utility as an automated analysis tool in a high-throughput AuNR synthesis procedure by generating quantitative size information from optical spectra. Second, we use the predictions generated by this model to train a machine learning model to predict the resulting AuNR size distributions under specified reaction conditions. Third, we apply this model to spectra extracted from the literature where no size distributions are reported and impute unreported quantitative information on AuNR synthesis. This approach can potentially be extended to any other nanocrystal system where absorption spectra are size dependent, and accurate numerical simulation of absorption spectra is possible. In addition, this pipeline could be integrated into automated synthesis apparatuses to provide interpretable data from simple measurements, help explore the synthesis science of nanoparticles in a rational manner, or facilitate closed-loop workflows.

36 MATERIALS SCIENCE↗