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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Comprehensive Analysis of Streaming and Shutdown Dose Rate Experiments at JET with ORNL Fusion Neutronics Workflows

Current experimental fusion systems and conceptual designs of fusion pilot plants (FPPs) are growing in complexity and size. Several radiation metrics are crucial to the safe operation of fusion machines, including neutron flux streaming through openings and the shutdown dose rate (SDDR). Most current designs of advanced experimental fusion systems—and the most probable candidates for FPPs—are based on the tokamak concept, which is prone to neutron streaming through the myriad openings needed for diagnostic and support systems. SDDR is caused by decay gamma rays from radionuclides that become activated by neutrons during the operation of a fusion system that use deuterium-deuterium (DD), tritium-tritium, or deuterium-tritium plasma. Because computational tools have become essential for determining these radiation metrics, they must be validated against reliable and applicable experimental data. Experiments at the Joint European Torus (JET) provide a unique source of experimental data for validating computational tools and nuclear data used to determine SDDR and neutron fluxes in streaming-dominated geometries. Here, this paper presents the comprehensive analysis of the high-performance DD JET SDDR, and streaming experiments performed using Oak Ridge National Laboratory (ORNL) fusion workflows. The computational results were compared with experimental results that consist of online SDDR measurements with ionization chambers and neutron fluence streaming measurements using thermoluminescent detectors. The ratio of calculated-to-experimental SDDR values ranges from 0.6 to 2.5, and the streaming results range from 0.5 to 8.0. Future work will include analyzing the JET 2021 DTE2 campaign alongside the integration of the Shift Monte Carlo transport code into all ORNL fusion neutronics workflows.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Operations, maintenance, and cost considerations for PV+Storage in the United States

Battery storage systems are increasingly being installed at photovoltaic (PV) sites to address supply-demand balancing needs. Although there is some understanding of costs associated with PV operations and maintenance (O&M), costs associated with emerging technologies such as PV plus storage lack details about the specific systems and/or activities that contribute to the cost values. This study aims to address this gap by exploring the specific factors and drivers contributing to utility-scale PV plus storage systems (UPVS) O&M activities costs, including how technology selection, data collection, and related and ongoing challenges. Specifically, we used semi-structured interviews and questionnaires to collect information and insights from utility-scale owners and operators. Data was collected from 14 semi-structured interviews and questionnaires representing 51.1 MW with 64.1 MWh of installed battery storage capacity within the United States (U.S.). Differences in degradation rate, expected life cycle, and capital costs are observed across different storage technologies. Most O&M activities at UPVS related to correcting under-performance. Fires and venting issues are leading safety concerns, and owner operators have installed additional systems to mitigate these issues. There are ongoing O&M challenges due the lack of storage-specific performance metrics as well as poor vendor reliability and parts availability. Insights from this work will improve our understanding of O&M consideration at PV plus storage sites.

14 SOLAR ENERGY↗
DOE OSTI2023

The Current State of Light-Duty Electric Vehicle Supply Equipment Costs: An Assessment of Contemporary Understanding

This study uses a hybrid meta-analysis and literature-review approach to understand the current state of knowledge regarding the costs of electric vehicle supply equipment (EVSE). We present a novel way to consider, categorize, and label measures of cost and show cost measure estimates from a sample of 13 recent studies. We find that in general, there is too much variation and too few commonly represented EVSE cost measures to reasonably provide aggregate figures for these measures. We propose a convention for presenting EVSE cost measures that includes the application (commercial or residential), the power level (Level 1, Level 2, DCFC [with further distinction based on rated power capacity]), and the type of cost measure (hardware, installation, operation, and total cost). We contend that providing researchers with standard cost measures will help to advance our knowledge of EVSE costs by ensuring that future work will use common metrics. Establishing common metrics will enable conventional meta-analyses that will make assessments of EVSE costs even more accessible. Additionally, common metrics will make tracking costs more reliable as the technology continues to evolve and become more ubiquitous.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Functional protein mining with conformal guarantees

Molecular structure prediction and homology detection offer promising paths to discovering protein function and evolutionary relationships. However, current approaches lack statistical reliability assurances, limiting their practical utility for selecting proteins for further experimental and in-silico characterization. To address this challenge, we introduce a statistically principled approach to protein search leveraging principles from conformal prediction, offering a framework that ensures statistical guarantees with user-specified risk and provides calibrated probabilities (rather than raw ML scores) for any protein search model. Our method (1) lets users select many biologically-relevant loss metrics (i.e. false discovery rate) and assigns reliable functional probabilities for annotating genes of unknown function; (2) achieves state-of-the-art performance in enzyme classification without training new models; and (3) robustly and rapidly pre-filters proteins for computationally intensive structural alignment algorithms. Our framework enhances the reliability of protein homology detection and enables the discovery of uncharacterized proteins with likely desirable functional properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

PV Evolution in the Light of Circular Economy

As photovoltaic (PV) deployments increase, the increasing material volume presents challenges throughout the supply chain and eventual end-of-life waste management. Quantifying the value of lifetime, reliability, repair, reuse, recycling, and other options to increase circularity can help identify and prioritize research and technical solutions required to integrate PV into the circular economy. In this work, we capture the evolution of PV module technology, such as improved reliability and increasing market share of glass/glass modules. We discuss material circularity, lifetime and reliability, and energy return on investment as quantitative metrics to define and evaluate circularity and sustainability.

bifacial↗
DOE OSTI2024

Establishing performance metrics for quantitative non-targeted analysis: a demonstration using per- and polyfluoroalkyl substances

Abstract Non-targeted analysis (NTA) is an increasingly popular technique for characterizing undefined chemical analytes. Generating quantitative NTA (qNTA) concentration estimates requires the use of training data from calibration “surrogates,” which can yield diminished predictive performance relative to targeted analysis. To evaluate performance differences between targeted and qNTA approaches, we defined new metrics that convey predictive accuracy, uncertainty (using 95% inverse confidence intervals), and reliability (the extent to which confidence intervals contain true values). We calculated and examined these newly defined metrics across five quantitative approaches applied to a mixture of 29 per- and polyfluoroalkyl substances (PFAS). The quantitative approaches spanned a traditional targeted design using chemical-specific calibration curves to a generalizable qNTA design using bootstrap-sampled calibration values from “global” chemical surrogates. As expected, the targeted approaches performed best, with major benefits realized from matched calibration curves and internal standard correction. In comparison to the benchmark targeted approach, the most generalizable qNTA approach (using “global” surrogates) showed a decrease in accuracy by a factor of ~4, an increase in uncertainty by a factor of ~1000, and a decrease in reliability by ~5%, on average. Using “expert-selected” surrogates ( n = 3) instead of “global” surrogates ( n = 25) for qNTA yielded improvements in predictive accuracy (by ~1.5×) and uncertainty (by ~70×) but at the cost of further-reduced reliability (by ~5%). Overall, our results illustrate the utility of qNTA approaches for a subclass of emerging contaminants and present a framework on which to develop new approaches for more complex use cases. Graphical Abstract

Pu, Shirley (ORCID:0000000201223797)↗
DOE OSTI2022

Temporal complementarity of marine renewables with wind and solar generation: Implications for GB system benefits

Wave and tidal energy have the potential to provide benefits to power systems with high proportions of stochastic renewable generation. This is particularly applicable with wind and solar photovoltaics, as the offsetting of these renewable resources results in more reliable renewable generation. This study utilises ten metrics to quantify the temporal complementarity and supply-demand balancing requirements of the energy mix in Great Britain, to investigate the potential magnitude of these system benefits. Wave and tidal generation profiles are created using historical resource data and hydrodynamic models. The results show that the inclusion of wave and tidal generation creates a renewable energy mix which is more available under multiple conditions: throughout a year of operation; at times of peak demand; for multiple consecutive hourly time periods; and at times when wind and solar generation are not available. Three regional case studies also show that the inclusion of marine energy allows for improved regional supply-demand matching, reducing instances of energy shortage and excess and potentially relieving transmission congestion at particularly constrained locations within GB. Finally, the implications of these findings are discussed in terms of GB wholesale market operation, system balancing and system security.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Building water resilience in the face of cascading wildfire risks

Severe wildfire is altering the natural and the built environment and posing risks to environmental and societal health and well-being, including cascading impacts to water systems and built water infrastructure. Research on wildfire-resilient water systems is growing but not keeping pace with the scale and severity of wildfire impacts, despite their intensifying threat. In this study, we evaluate the state of knowledge regarding wildfire-related hazards to water systems. We propose a holistic framework to assess interactions and feedback loops between water quality, quantity, and infrastructure hazards as determinants of post-fire water availability and access. Efforts to address the evolving threat of wildfires to water systems will require more interdisciplinary research on the complex relationships shaping wildfire’s threat to water availability and access. To support this, we need reliable long-term data availability, consistent metrics, greater research in shared contexts, more extensive research beyond the burn area, and multistakeholder collaboration on wildfire risks to water systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A Hot‐Swappable, Fault‐Tolerant, Modular Power Converter System for Solar Photovoltaic Plants

The performance metrics of the state-of-the-art commercial solar inverters, such as system cost, operation and maintenance (O&M) cost, service life, reliability, maintainability, and power density are much lower than the target metrics needed to achieve SunShot’s 2030 levelized cost of energy (LCOE) goals. To overcome the shortcomings of the existing solar inverters, this project proposed a novel Hot-Swappable, Fault-Tolerant, Modular Power Converter (HSFT-MPC) concept for solar photovoltaic (PV) plants and proved the concept through the design, fabrication, and laboratory test validation of a single-phase HSFT-MPC prototype. The HSFT-MPC has the following distinct advantages over the state-of-the-art: 1) elimination of harmonic/ electromagnetic interference (EMI) filter in the inverter stage due to the novel topology, 2) lower system cost and higher power density due to the modular design, elimination of harmonic/EMI filter, and lower cooling requirement, 3) higher efficiency due to lower switching frequencies, 4) higher reliability and longer (50 years) service life due to simpler cooling and fault tolerance capability, 5) easier installation, lower O&M cost, and improved maintainability due to the modular design and hot-swappable power electronic building blocks (PEBBs), and 6) improved manufacturability due to the modular design. This project developed a single-phase HSFT-MPC prototype with 25kW nominal output power, 2.4kV, 60Hz nominal AC output, lower than 5% AC output voltage total harmonic distortion, over 5 kW/L inverter power density, and 99.4% inverter peak efficiency, being tolerant to failure of single and multiple PEBBs, and capable of hot swapping of the failed PEBB(s). The HSFT-MPC enables uninterruptable operation of the solar PV plant when failure of single or multiple PEBBs or PV modules occurs. Compared with the existing solar inverters in the market, the HSFT-MPC is expected to reduce the inverter failure-caused downtime and energy losses of solar PV plants by more than 60% and 50%, respectively. Project findings have been presented at major conferences in the field and published in peer-reviewed papers, which added new knowledge to the field of power electronics for solar PV systems. A minicourse on Solar PV Systems was developed for outreach activities. The minicourse will help attract young individuals to the renewable energy profession which has a significant talent shortage. The HSFT-MPC is expected to overcome all of the shortcomings of the state-of-the-art solar inverters in terms of cost, efficiency, service life, reliability, maintainability, and manufacturability targets needed to achieve SunShot’s 2030 LCOE goals. Therefore, the proposed HSFT-MPC concept has the great potential to disrupt the current solar inverter market. This project created a pathway towards industry adoption of the HSFT-MPC to help achieve 50-year service life solar PV systems. Since the solar PV plants using the HSFT-MPC will feature with higher reliability, longer service life, and easier maintenance, they are particularly useful for the rural areas with underserved populations that demand reliable and affordable clean electricity. The outcomes of the project have the strong potential to address national needs in the field of renewable energy to reduce CO 2 emissions from the electricity sector, reduce imports of energy from foreign sources, and improve energy security, efficiency, and sustainability. Since electricity is used in almost all of society’s sectors, the outcomes of the project will benefit various sectors of society and economy.

14 SOLAR ENERGY↗
DOE OSTI2020

Scalable and Actionable Performance Measures for Traffic Signal Systems using Probe Vehicle Trajectory Data

Scalable and actionable performance measures for traffic signal systems provide opportunities for practitioners to measure and improve the transportation network. Historically, traffic signal improvements have relied on scheduled signal retiming based on limited data collection, or on the public to call and alert engineers of an issue. This inefficient method of improving signal timing led to the creation of automated traffic signal performance measures (ATSPMs). These metrics rely on expensive infrastructure, including detection and communications, which has produced barriers for numerous agencies to fully adopt. Recently, third-party data providers have begun to release vehicle trajectory data, which allows for enhanced signal metrics with no investment in physical equipment. The purpose of this study is to demonstrate the use of these data and summarize the scalability of the created metrics. This work builds on previous efforts to quantify signal performance on nine intersections in Michigan, U.S. Ten signalized corridors in Columbus, Ohio, were chosen to scale a performance assessment using crowdsourced trajectory data. A total of 136 intersections were assessed in 2-h intervals using data from all weekdays in 2017. High-level corridor summary metrics including average percent of vehicles stopping (18%–32%), average delay (9.4–20.5 s), and level of travel time reliability (1.23–2.73) were calculated for each corridor direction. Intersection-level metrics were also introduced, which can be used by practitioners to identify problems, improve signal timings, and prioritize future infrastructure investments.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

How different power plant types contribute to electric grid reliability, resilience, and vulnerability: a comparative analytical framework

Abstract This work explores the dependability tradeoffs provided by the most common types of central power plants in the United States. Historically, the electricity sector has lacked consensus on how reliability , resilience , and vulnerability differ and how those metrics change depending on the power plant fleet composition. We propose distinct definitions for these metrics and an analytical framework to evaluate power plant fleet dependability. Using data analysis and literature review, we identify fifteen dependability attributes across which we rank eleven power plant types relative to natural gas combined-cycle (NGCC) plants. We use NGCC as the benchmark because it is common to many locations and is of relatively recent vintage. The framework shows that each power plant type has unique dependability benefits and drawbacks. We provide examples of how researchers may use the framework to evaluate grid dependability qualitatively under different scenarios. We find that assuming all attributes that contribute to grid dependability are equally important and additive, electric grid dependability is best supported when power plant fleets include a mixture of power generation technologies. Then, we discuss scenario characteristics that could alter the prioritization and relationships of attributes. We also find that if current capacity installation trends continue to favor low- and zero-carbon power plants, US power grids may benefit from increased resilience and reduced vulnerability at the cost of decreased reliability. We conclude by recommending methods for adapting the framework and quantifying relationships between attributes in individual scenarios.

Ramirez-Meyers, K. (ORCID:0000000291216952)↗
DOE OSTI2026

“One Table to Rule Them All”: How a Single Table can Enable Extensive Insights, Analytics and Assessment on Human Mobility Data

While much research has been conducted in Human Mobility Science, most studies on the analytics/insights part generally focus on one of the following: processing and analytics on human stop-trip behavior, design of individual mobility metrics (often in silos), calculation and characterization of only a handful (typically 5-6) of human mobility metrics on geospatial-temporal human mobility data of interest. Although human mobility research offers a vast and diverse array of available metrics, most individual studies typically compute only a small subset of five or six metrics at a time when analyzing trajectory datasets of human mobility across different areas of interest. This paper is motivated by the critical need to repeatedly compute an extensive array of human mobility metrics across several trajectory datasets and perform individual metric-level benchmarking to establish a new, standardized Test and Evaluation (T&E) suite for the field of Human Mobility Science. We first present our findings on the minimal yet sufficient pre-processing required to reliably and efficiently compute a wide range of human mobility metrics. The key findings are specifically related to the proposed Composite Stop Locations table, which serves as a core pre-processing data layer. Subsequently, we present a case study demonstrating how the Composite Stop Locations table facilitates computation of at least 14 distinct human mobility metrics (unlike 5-6 different set of metrics used for studies in the literature) using the popular and open-source OpenPFLOW dataset. Finally, we have also presented an example of our benchmarking methodology to evaluate the quality and performance of the trajectory dataset of interest, assessed across multiple human mobility metrics.

De, Debraj [ORNL] (ORCID:0000000233630020)↗
DOE OSTI2026

Uncertainty-Aware Machine Learning for Small-Angle X-ray Scattering Analysis in Autonomous Experimentation

Small-angle X-ray scattering (SAXS) is a powerful high-throughput characterization tool for probing nanoscale structure in native sample environments, providing real-time morphological information such as nanoparticle size and shape during synthesis. However, automated SAXS data analysis for extracting meaningful structural parameters is non-trivial and remains a bottleneck in closed-loop experimentation towards autonomous materials discovery, which demands fast, reliable, and uncertainty-aware data analysis. Here, we develop a machine-learning approach for automated SAXS analysis tailored to closed-loop nanoparticle synthesis. A Random Forest (RF) regression model is trained on 100,000 synthetic SAXS curves generated from polydisperse spherical nanoparticles with realistic background contributions. Using normalized one-dimensional SAXS intensity profiles as input, the RF model directly predicts nanoparticle radius, size polydispersity, and background parameters, while the ensemble standard deviation across trees provides built-in uncertainty quantification (UQ). On synthetic data, we show that combining fit-quality metrics (R 2 , MAE) with thresholds on prediction uncertainty reliably identifies accurate parameter estimates without access to ground truth. We then apply the trained model to 365 experimental SAXS profiles of citrate-reduced gold nanoparticles synthesized using an automated droplet-flow microreactor with in situ SAXS at a synchrotron beamline, classifying the results into high- and low-confidence subsets based on UQ metrics. Finally, we integrate RF-based SAXS analysis into a simulated closed-loop optimization campaign using Gaussian process Bayesian optimization to minimize nanoparticle polydispersity, benchmarking against conventional automated Levenberg–Marquardt fitting. The RF-guided campaign exhibits substantially faster convergence and lower relative opportunity cost (∼0.07 vs ∼0.3), demonstrating that uncertainty-aware machine-learning SAXS analysis significantly enhances the efficiency and robustness of autonomous nanomaterials synthesis workflows.

Bayesian optimization↗
DOE OSTI2025

High-heat transfer lithium-ion batteries: A new era in battery thermal management

Despite advances in lithium-ion battery technology, critical challenges remain that must be addressed to accelerate electric vehicle (EV) adoption and global energy transformation. Significantly improved battery thermal management (BTM) is key to overcoming these challenges. BTM approaches focus on increasing heat transfer coefficients via air, liquid, or refrigerant cooling, but less attention is given to reducing the battery's thermal resistance, a major bottleneck for heat transfer. This work introduces a novel approach to reduce battery thermal resistance by integrating in-plane heat transfer with optimized cell geometry, minimized thermal resistances, and reduced interfacial resistances, representing a departure from previous methods. The standard prismatic can cell incorporating this technology is referred to as the high heat transfer (HHT) battery. An equivalent resistance battery thermal model is developed for speed and accuracy, validated against experimental data in the literature, demonstrating strong correlation and ensuring reliable predictions for real-world performance. Thermal performance metrics of the conventional and HHT batteries are compared using a parametric study with air, liquid, and refrigerant boundary conditions across a range of aspect ratios. The HHT battery shows a heat removal rate up to 20 times higher than a conventional battery. These findings suggest that HHT technology could be transformative for EV battery performance, enabling fast charging, mitigating thermal runaway, extending battery life, reducing cold-weather power loss, increasing reliability, lowering costs, and enabling higher energy density, all critical for EV adoption and energy transformation. Future work will focus on prototyping and real-world testing to refine these findings for commercial-scale applications.

25 ENERGY STORAGE↗
DOE OSTI2021

Sub-pixel high-resolution imaging of high-energy x-rays inspired by sub-wavelength optical imaging

We have developed and demonstrated an image super-resolution method—XR-UNLOC: X-Ray UNsupervised particle LOCalization—for hard x-rays measured with fast-frame-rate detectors that is an adaptation of the principle of photo-activated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM), which enabled biological fluorescence imaging at sub-optical-wavelength scales. We demonstrate the approach on experimental coherent Bragg diffraction data measured with 52 keV x-rays from a nanocrystalline sample. From this sample, we resolve the fine fringe detail of a high-energy x-ray Bragg coherent diffraction pattern to an upsampling factor of 16 of the native pixel pitch of 30 μ m of a charge-integrating fastCCD detector. This was accomplished by analysis of individual photon locations in a series of “nearly-dark” instances of the diffraction pattern that each contain only a handful of photons. Central to our approach was the adaptation of the UNLOC photon fitting routine for PALM/STORM to the hard x-ray regime to handle much smaller point spread functions, which required a different statistical test for photon detection and for sub-pixel localization. A comparison to a photon-localization strategy used in the x-ray community (“droplet analysis”) showed that XR-UNLOC provides significant improvement in super-resolution. We also developed a metric by which to estimate the limit of reliable upsampling with XR-UNLOC under a given set of experimental conditions in terms of the signal-to-noise ratio of a photon detection event and the size of the point spread function for guiding future x-ray experiments in many disciplines where detector pixelation limits must be overcome.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

National Ignition Facility. Facility and Infrastructure Systems Maintenance Plan

Ensuring the reliability of the NIF, including its support systems, laser systems, target diagnostic systems, and utilities, is essential to the availability of the NIF in its support of NNSA missions. NIF is a key capability in the DOE Stockpile Stewardship Program and supports high energy physics experiments for nuclear weapons, energy, and astrophysics applications. High system reliability provides opportunities for shots and scientific discoveries with opportunities to enhance and upgrade capabilities. This Maintenance Plan (MP) identifies the policies and procedures used to perform and support asset management of the NIF Facility and Infrastructure Systems (FInS), NIF Lasers & Alignment (LASE), NIF Target Experimental Operations (TOPS), NIF Target Area Science and Engineering (TASE), and NIF&PS Control Systems (NCS). The FInS systems include the facility, HVAC, contamination control, beampath, and Line Replaceable Units (LRUs) as well as utilities which create the beampath environments, such as vacuum, argon, or clean dry air. The LASE systems are Programmatic systems which include laser diagnostics, alignment, power conditioning, pulsed power, and input laser systems. The TOPS and TASE systems are also Programmatic systems which include target and diagnostic delivery systems and positioners, many different insertable and fixed target diagnostics, and cryogenic and target gas fill systems. Finally, the NCS systems include both software and hardware for industrial and shot operation control systems. Policies governing administrative and operational practices related to maintenance of FInS, LASE, TOPS, TASE, and NCS systems are described in this plan. In addition, the plan provides processes and procedures for managing, tracking, and documenting the work. This document, the NIF Operations Management Plan, NIF-5020544 (Ref. 1), and NIF Shot Operations Plan, NIF-5018506 (Ref. 2), together satisfy the requirements of the Conduct of Operations. Duties, responsibilities, and reporting requirements of the various positions associated with FInS, LASE, and TOPS maintenance are detailed in this plan. The FInS systems include both Real Property systems with asset management requirements specified in DOE Order 430.1C (Ref. 3) and Programmatic systems. In addition, for FInS, there is a list of the System Level Maintenance Plans (SLMPs) in NIF-1007419198 (Ref. 4) which provide the system descriptions and maintenance plan and schedule. In addition, the list includes the Reliability Centered Maintenance (RCM) and Experience Centered Maintenance (ECM) evaluations that have been performed for applicable FInS systems as well as reliability criticality per Section 3.5. The -AM version of the NIF Maintenance Plan focuses on the reliability program for FInS, LASE, TOPS, TASE, and NCS within the context of the overall NIF Reliability, Availability, and Maintainability (RAM) program and incorporates changes since the -AL version from August 2011 and has been updated to be fully consistent with the updates to Ref. 1. It also includes asset management considerations, updates to the Work Order (WO) process within the NIF Computerized Maintenance Management System (CMMS) which is EAM infor® System Maintenance and Reliability Tracking (SMaRT) (Ref. 5), and updates to metrics and key performance indicators (KPIs).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Resilience Metrics for Solar Photovoltaics

This workshop presentation proposes the development of solar photovoltaic (PV) system resilience metrics and a methodology and framework for evaluation of PV resilience metrics. PV resilience metrics are needed to establish a consistent basis for reporting, evaluation, and data collection by industry, evaluate performance of PV systems that have been subject to natural hazards, correlating resilience to system attributes, and predicting resilience for any PV system. PV resilience metrics can guide improved system design, standards, and insurance coverage. Establishing consistent metrics can foster data collection on impacts of natural hazards on PV systems.

14 SOLAR ENERGY↗
DOE OSTI2020

System Health and Status Reporting is Used to Improve Infrastructure Systems at the Hanford Site - 20449

Reliable physical infrastructure systems are vital to completing the clean-up mission and the start-up and commissioning of new nuclear waste processing facilities at the Hanford Site. Key infrastructure systems at Hanford include water, sewer, and electrical utilities, roads, telecommunications/network systems, and fire systems. All of the infrastructure systems are non-nuclear, General Service systems that are being maintained under formal engineering configuration control and none are specifically credited in any documented safety analysis (DSA). Starting in calendar year 2017, the Hanford Site's infrastructure and services contractor started producing system health and status reports for a total of 15 critical infrastructure systems as means to get a better understanding of each system's health and how it could be improved to ensure better and more reliable service delivery. As the reporting, tracking, and use of the metrics has matured, the number of systems for which reports are being developed has been expanded to a total of 23. Each of the critical infrastructure systems are assigned primary and alternate design authorities that complete qualifications on each assigned system. The design authorities actively manage and maintain configuration control on each of their systems and track metrics associated with availability, maintenance (corrective and preventive), and configuration of the technical baseline. The metrics are based on the principles established in Chapter V of DOE O 420.1C, Facility Safety, [1] and have been tailored as appropriate to each of the key infrastructure systems. An overall assessment of system health is performed and documented on a routine basis (e.g., quarterly). Included in this documentation is a quantitative score for each of the metrics (i.e., availability, maintenance, configuration management) along with results of system walk-downs, description of any permanent design modifications, identification of new or emerging issues and vulnerabilities affecting the system, and an assessment by the design authority of actions necessary to improve the system health score. The overall status scores are calculated using a formula and based on a pre-determined grading scale, a color is assigned for simple presentation. The information gained from developing the reports is being used to (1) assist with making timely and better informed decisions through the use of solid technical bases that are increasing the overall reliability and capabilities of the Site's infrastructure systems as new expense and capital projects in the Reliability Projects Investment Portfolio (RPIP) are prioritized and executed; (2) feed the risk management program, and (3) integrate the technical content of Master Plans that describe the Site's needs for the system and the system's capabilities to meet those future needs. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗