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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Hybrid AI/ML and Computational Mechanics Based Approach for Time-Series State and Fatigue Life Estimation of Nuclear Reactor Components

Environmental fatigue modeling is a complex problem due to multiple failure modes and their intermixing. The failure modes are function of various underlying causes in addition to the corrosive effect of reactor coolant environment. Some of the major causes are time-dependence of material associated with cyclic loading, load sequence effect associated with random/variable amplitude loading, effect of strain amplitude and rates, effect of varying temperature (along both temporal and spatial directions) and the effect of mean strain and stress. The nonlinear intermixing of failure modes associated with above mentioned causing parameters makes the environmental fatigue modeling is a challenging task. Because of this challenge, fatigue is traditionally being modeled based on experimental data. However, test based empirical approach often requires hundreds of fatigue tests to model the above-mentioned intermixing failure causes even for a single material system. The problem is further exaggerated for reactor component made from multi-material systems such as made from both carbon and stainless-steel base metals and their similar and dissimilar metal welds. With the difficulty of conducting hundreds of fatigue tests to capture the above-mentioned intermixing failure causes, fatigue modeling approaches often depends on empirical models based on limited available test data such as available through ASME code and NUREG 6909. However, these limited test-data-based models may not be enough to accurately predict the life of reactor components. Accurate prediction of life of reactor component would become a necessity, particularly when the license of the reactors to be extended for long-term-operation (LTO) that is for well beyond its original design life of 40 years. The requirement of extending the license of reactor under LTO requires hundreds of fatigue tests to be conducted to understand the mechanism associated with the above-mentioned interdependent failure causes. However, conducting large number of fatigue tests is not a feasibility due to the cost involved. To address this issues Argonne National Laboratory (ANL) with the sponsorship of DOE Light Water Reactor Sustainability (LWRS) program trying to develop a hybrid predictive modeling approach. This is based on limited experiment-data, Artificial-intelligence (AI) – Machine-Learning (ML) - Deep-Learning (DL) based techniques and Multiphysics-computational-mechanics based modeling tools. The hybrid approach not-only can improve the accuracy of the existing stress analysis and fatigue modeling approach but also can reduce the over-dependency on test-based approach. Towards this goal following are some of the major contributions based on ANL’s FY-20 environmental fatigue modeling activities: 1) A cyclic plasticity material model database for 82/182 dissimilar metal weld, which can be readily shared with US nuclear industry and regulatory agency on request. 2) A well validated analytical modeling methodology to perform cycle-by-cycle stress prediction under both constant amplitude fatigue loading and variable amplitude fatigue loading (with load-sequence effect). 3) An AI/ML/DL based methodology to predict unmeasurable cyclic strain based on other available sensor signals. This type of approach can be used for estimating strain in real reactor components from other sensor readings. 4) An AI/ML based approach to improve the US capability on environmental fatigue testing. This is by improving ANL’s existing environmental fatigue testing capacity to conduct ASME required strain-controlled tests (by controlling strain amplitudes and its rate), while not measuring the strain (due to the difficulty of placing an extensometer in a narrow autoclave in a PWR-water-test system). 5) A simulation and experiment based probabilistic modeling methodology for time-series fatigue state and life estimation of reactor metal such as dissimilar metal weld.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Benefit-Cost Analysis for Utility-Facing Grid Modernization Investments: Trends, Challenges, and Considerations

In recent years, many electric utilities have submitted grid modernization plans for review by state public utility commissions. A central objective of these plans is to demonstrate that grid modernization investments will provide net benefits to customers, be reasonable and be in the public interest. The plans typically include some form of benefit-cost analysis, but the assumptions, methodologies and frameworks vary considerably between utilities. This report: -Describes utility-facing technologies and projects for modernizing distribution systems, including interdependencies of grid components -Highlights benefit-cost considerations related to grid modernization -Summarizes recent trends in benefit-cost analysis for grid modernization based on a review of 21 plans by U.S. electric utilities -Discusses challenges state public utility commissions face in reviewing utility plans and provides options for addressing challenges

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Future of Water Infrastructure and Innovation Summit

Energy and water systems are interdependent, and the U.S. Department of Energy (DOE) has invested in energy and water for several years, including the Energy-Water Desalination Hub (led by the National Alliance for Water Innovation, NAWI), and research and development (R&D) in resource recovery from wastewater, among other areas. The Advanced Manufacturing Office (AMO) at the U.S. Department of Energy (DOE) held The Future of Water Infrastructure and Innovation Summit to inform the understanding of future opportunities in the water space. The virtual summit was held on October 27 and 28, 2020. The organizers gathered information from a diverse group of relevant water and wastewater stakeholders representing academia, industry, government, nongovernmental organizations, and local/regional utilities. Topics from Day 1 discussions included: desalination, water and wastewater treatment/recovery, produced water, industrial management of water, and hydropower, conveyance, and water systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Development of Standardized Property Requirements, Measurement Methods, and Reporting Guidance for Coatings

The diverse research programs presently in progress around the world have advanced a large number of coated cladding concepts to various stages of maturity. Industry teams have developed leading coating compositions and geometries, but significant disparity exists in the importance placed on different coating properties, as well as the applicability and standardization of the various methods used to measure these properties. This milestone report provides an initial assessment of the most important coating properties and the experimental methods available for their determination to lay the foundation for standardized reporting and development of comprehensive datasets for modeling efforts. This report has determined that the residual stress of the coating is the most crucial property to investigate, yet it has received minimal attention to date due to a knowledge gap about the growth and formation of the brittle Laves phase under reactor conditions. The significance of residual stress of the coating is further enhanced by its connection and interdependence with other important properties like creep and coating failure mechanisms. This milestone proposes an importance rating for residual stress properties and their associated measurement techniques to fill in knowledge. Furthermore, techniques to investigate the outlined properties are discussed, and their capabilities and limitations are illustrated to provide guidance on their use.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Critical Infrastructure Decision-Making under Long-Term Climate Hazard Uncertainty: The Need for an Integrated, Multidisciplinary Approach

U.S. critical infrastructure assets are often designed to operate for decades, and yet long-term planning practices have historically ignored climate change. With the current pace of changing operational conditions and severe weather hazards, research is needed to improve our ability to translate complex, uncertain risk assessment data into actionable inputs to improve decision-making for infrastructure planning. Decisions made today need to explicitly account for climate change – the chronic stressors, the evolution of severe weather events, and the wide-ranging uncertainties. If done well, decision making with climate in mind will result in increased resilience and decreased impacts to our lives, economies, and national security. We present a three-tier approach to create the research products needed in this space: bringing together climate projection data, severe weather event modeling, asset-level impacts, and contextspecific decision constraints and requirements. At each step, it is crucial to capture uncertainties and to communicate those uncertainties to decision-makers. While many components of the necessary research are mature (i.e., climate projection data), there has been little effort to develop proven tools for long-term planning in this space. The combination of chronic and acute stressors, spatial and temporal uncertainties, and interdependencies among infrastructure sectors coalesce into a complex decision space. By applying known methods from decision science and data analysis, we can work to demonstrate the value of an interdisciplinary approach to climate-hazard decision making for longterm infrastructure planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Causal Evaluations for Identifying Differences between Observations and Earth System Models

We use a nascent data-driven causal discovery method to find and compare causal relationships in observed data and climate model output. We consider ten different features in the Arctic climate collected from public databases on observational and Energy Exascale Earth System Model (E3SM) data. In identifying and analyzing the resulting causal networks, we make meaningful comparisons between observed and climate model interdependencies. This work demonstrates our ability to apply the PCMCI causal discovery algorithm to Arctic climate data, that there are noticeable similarities between observed and simulated Arctic climate dynamics, and that further work is needed to identify specific areas for improvement to better align models with natural observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

INS–Support for Formal Cyber Security Education in Brazil–After Action Report

The adoption of digital technology into Instrumentation and Control (I&C) systems in nuclear facilities fundamentally changes the nature of these systems. Greater interconnectivity of reprogrammable, and functionally interdependent control systems has given rise to the need for computer security consideration in digital I&C Systems. The cyber security of I&C systems presents a growing risk to nuclear facilities and requires the development of educational and research tools to ensure the safety of these facilities. Currently there is a major gap in formal educational offerings on cyber security for these Operational Technology (OT) systems. To provide formal cyber security education resources, DOE’s office of International Nuclear Security (INS) partnered with the University of São Paulo (USP) to develop a training course on the cyber security of nuclear facility I&C systems using the hypothetical Nuclear Power Plant, Asherah.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Cybersecurity Certification Recommendations for Interconnected Grid Edge Devices and Inverter Based Resources

Escalating deployment of PV and grid-edge devices on the distribution grid has increased the sustainability and efficiency of the electric grid. However, the increasing number of distributed energy resources (DERs) deployed creates a heightened cyber-physical interdependency on the distribution grid and thus creates more vectors for cyber-attacks to exploit through information and communication technology (ICT) systems and networks. For example, control signal packets can be modified, intercepted, or corrupted due to vulnerabilities in communication protocols used by microgrid controllers and grid edge devices for power control. Therefore, to mitigate and prevent cyber-attacks on grid edge devices and the inverter-based resources connected to the distribution grid, the U.S. Department of Solar Energy Technologies Office (SETO) awarded funding to the National Renewable Energy Laboratory and Sandia National Laboratory (SNL) to research, develop, and harmonize cybersecurity standards for Photovoltaic (PV) systems and for other kinds of DERs. To help develop a standard for DER cybersecurity, NREL established certification recommendations and test cases, in consensus with the solar industry and UL, for ensuring intrinsic design security for DERs. These recommendations were developed to bolster the cybersecure functionalities such as TLS, MAC, CRL, session resumption/renegotiation, and password, system, and service security management within the DER devices. The proposed test cases verify authentication, authorization, confidentiality, and data integrity for data and communications of DERs that use Transmission Control Protocol/Internet Protocol (TCP/IP). They were also developed to protect DER communications from eavesdropping, replay, man-in-the-middle, denial of service (DoS), spoofing through security certificates, least-privilege violation, and brute-force credentials. This report, which has been validated and reviewed by UL, expands upon those test cases to provide DER cybersecurity certification recommendations which increase DER resiliency and help to mitigate cyber-attacks. UL's collaboration with NREL and approval of this document will accelerate the adoption of a UL standard for DER cybersecurity.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Mapping the Opportunity Space to Model the Circular Economy Using Tools Funded by the DOE Office of Energy Efficiency and Renewable Energy

An increasing rate of material consumption and a growing population mean that the Earth's supply of natural resources is witnessing an unsustainable and unprecedented demand. This forces us to find solutions that ensure the availability of resources for sustenance of our society in the years to come. Actors from various backgrounds are addressing these challenges from their own perspectives: engineers are developing efficient manufacturing processes, designers are creating lightweight and durable products, educators are incorporating sustainable thinking in their curricula, policymakers are finding interdisciplinary solutions that benefit society at large, etc. Circular economy (CE) is one such approach to resource use that aims to move away from the linear material use framework of "take-make-waste" to a more circular and interdependent system where product, material and resource use is maximized to avoid unnecessary social, economic, and environmental costs. The purpose of this report is to explain how to approach evaluating the circular economy and to help researchers identify existing tools that can be used or that can serve as starting points for their research needs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Integration of Electric Power Infrastructure into the Drinking Water Shared Risk Framework: Prototype Development

An existing shared risk framework designed for assessing and comparing threat-based risks to water utilities is being extended to incorporate electric power. An important differentiating characteristic of this framework is the use of a system-centric rather than an asset-centric approach. This approach allows anonymous sharing of results and enables comparison of assessments across different utilities within an infrastructure sector. By allowing utility owners to compare their assessments with others, they can improve their self-assessments and identification of "unknown unknowns". This document provides an approach for extension of the framework to electric power, including treatment of dependencies and interdependencies. The systems, threats, and mathematical description of associated risks used in a prototype framework are provided. The method is extensible so that additional infrastructure sectors can be incorporated. Preliminary results for a proof of concept calculation are provided.

42 ENGINEERING↗
DOE OSTI2022

Software Deployment Process at NERSC: Deploying the Extreme-scale Scientific Software Stack (E4S) Using Spack at the National Energy Research Scientific Computing Center (NERSC)

One of the many benefits of using a high-performance computing (HPC) system at a Department of Energy (DOE) Office of Science (SC) HPC facility is the large number of software products, built and optimized for the system. The HPC center staff and HPC vendors provide optimized software such as libraries and even full scientific applications, ready to be used by users as building blocks to accelerate scientific discovery. Behind each provided packaged software module are a large number of decisions - which compiler, optimizations, variants/options - to build the software on the target system. And, even before the software gets deployed, the software must be developed, tested, and maintained, including deprecating old versions and ensuring compatibility across versions. The software lifecycle is complex and is further convoluted by a web of interdependencies on other software.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Electrical-Discharge-Machining Contamination Removal from Metal Additively Manufactured Components

The use of an electrochemical dissolution process is shown to remove the recast layer contamination from the surfaces of electrical-discharge-machining cut components, as well as the interior exposed surfaces of the structure. The solution chemistry, cell potential, and exposure time are all relevant interdependent variables. Optimization of the electrode geometry should be made for each type of component. For the case of Cu-Zn recast contamination of 300-series alloy components, surface composition analysis indicates that complete electrochemical dissolution is achieved using a dilute solution of nitric acid (HNO 3 ). For example, electrochemical dissolution of the Cu-Zn recast is accomplished at 1.2 V cell potential using a 20% nitric solution and an exposure time of 4 h. The use of a nitric acid bath was specifically chosen since it’s chemically compatible and will not degrade the host alloy or the component. In sum, an electrochemically driven dissolution process can be tailored to remove of the recast contamination without affecting the integrity of the host component structure and its dimensional tolerances.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

SolSmart Technical Assistance Provider (Final Technical Report)

The SolSmart program was established in late 2015 to “establish a prominent national recognition and technical assistance program for local governments that will signal to installers and the public that a community is receptive to solar businesses and has established a supportive solar market environment. This, in turn, will reduce market barriers and lower soft costs, thus contributing to SunShot goals. The program will also assist communities who are just beginning to improve their solar markets.” By March 31, 2022 (the grant end date), the SolSmart Team designated 460 communities, more than 50% more than the initial program objective of 300 communities. The designated communities represent 42 states, the District of Columbia, the U.S. Virgin Islands, and Puerto Rico. The SolSmart team developed and revised criteria representing best practices for local governments; recruited, trained, evaluated, and mentored communities to incorporate these best practices; and disseminated resources about solar and solar-related technologies as well as the newest best practices on a regular basis. 98% of local government officials who participated in the program said that SolSmart increased their knowledge of solar energy. The SolSmart program had both real and perceived tangible impacts on barriers to solar adoption in designated communities. Significantly, the time to permit a solar installation decreased by 7.5 days on average. This reduced the soft costs for both the solar installer (and therefore the customer) and the local government. The result is that solar installations in SolSmart communities increased by 17% per month compared with similar non-SolSmart communities. Larger and wealthier communities were more likely to pursue SolSmart designation and earn more points within SolSmart. As a result, IREC/TSF developed strategies to reach underserved communities and created new resources to help them more easily achieve designation, as described below. In the last year of the Award, 44% of designated communities were underserved, compared with 31% in the earlier years of the program. DOE issued two awards for SolSmart: the SolSmart Technical Assistance Provider (TAP), led by The Solar Foundation (TSF) which has since merged with the Interstate Renewable Energy Council (IREC), and the Designation Program Administrator (DPA), led by the International City/County Management Association (ICMA). IREC was lead for the TAP project and, until the time of TSF/IREC merger, was a subrecipient on the DPA project. These two projects were interdependent; one could not exist without the other. While this report will focus on the work performed by the TAP, it will be impossible to speak of this without talking about the successes, impacts, and benefits of the overall SolSmart program.

14 SOLAR ENERGY↗
DOE OSTI2022

Dynamics Informed Optimization for Resilient Energy Systems

Optimal mitigation planning for highly disruptive contingencies to a transmission-level power system requires optimization with dynamic power system constraints, due to the key role of dynamics in system stability to major perturbations. We formulate a generalized disjunctive program to determine optimal grid component hardening choices for protecting against major failures, with differential algebraic constraints representing system dynamics (specifically, differential equations representing generator and load behavior and algebraic equations representing instantaneous power balance over the transmission system). We optionally allow stochastic optimal pre-positioning across all considered failure scenarios, and optimal emergency control within each scenario. This novel formulation allows, for the first time, analyzing the resilience interdependencies of mitigation planning, preventive control, and emergency control. Using all three strategies in concert is particularly effective at maintaining robust power system operation under severe contingencies, as we demonstrate on the Western System Coordinating Council (WSCC) 9-bus test system using synthetic multi-device outage scenarios. Towards integrating our modeling framework with real threats and more realistic power systems, we explore applying hybrid dynamics to power systems. Our work is applied to basic RL circuits with the ultimate goal of using the methodology to model protective tripping schemes in the grid. Finally, we survey mitigation techniques for HEMP threats and describe a GIS application developed to create threat scenarios in a grid with geographic detail.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

WISP: Watching grid Infrastructure Stealthily through Proxies (Final Technical Report)

The complex interdependencies of cyber systems (sensors and communications), physical grids and associated electricity market operations make protecting electric power grids a significant challenge. The energy sector is constantly under new, targeted, advanced and dangerous cyber-attacks that have the potential to result in the loss of human life. These threats are further exacerbated by our need to modernize the grid. One focus of cyber security research in smart grids is the securing of the SCADA system through advanced intrusion detection systems (IDS) and bad data detection algorithms in state estimation. These methods either require full knowledge of the system topology and parameters or fail to understand the physical behaviors under attack. WISP (Watching grid Infrastructure Stealthily through Proxies) is designed to provide additional protection to the power grid using only publicly available data. In particular, WISP exploits the spatio-temporal nature of the real time locational marginal prices (LMPs), in conjunction with other information such as bids, weather, outages and load data to analyze anomalous power pricing behaviors and then correlate those observations to localize regions of interest and identify potential cyber events. WISP is non-intrusive as the tool is deployed as a service in the Cloud or on premise and provides reliable information to system operators for enhanced situational awareness, without impeding energy delivery functions. The WISP technology comprises three modules: the data-driven anomaly detection core, the vulnerability and risk analysis and the root cause analysis. The data-driven anomaly detection core performs the tasks of feature selection, anomaly detection and attack region localization. The vulnerability and risk analysis module provides system level information of the vulnerable variables and times, assisting the operators in selecting monitoring and protection nodes. The root cause analysis module takes the detection results and identifies potential operational conditions that contribute to the detected anomalies. In Phase I, we have demonstrated the feasibility and effectiveness of WISP. We developed a realistic electricity market simulator capable of generating normal and attack market data under various operational conditions. We developed a series of cyber-attack detection and analysis algorithms and evaluated them under multiple data sources. Finally, we integrated all modules into an end-to-end software, providing functions for data management, data analytics and visualization. Specifically, we have achieved: (i) real-time data acceptance from external utility interfaces with >99% acceptance rate; (ii) high performance anomaly detection algorithms with >98% detection accuracy and <0.1% false alarm rate; and (iii) ultra-low computing delay <50 milliseconds. Additionally, our team developed algorithms to identify the vulnerable variables in electricity market operations and root cause analysis functions to identify major contributors to the price spikes. These ancillary modules are necessary when deploying WISP in real world industry environment. In Phase II, we have demonstrated the effectiveness of WISP software on realistic largescale power systems. We performed red team testing for the Phase I WISP software and identified software vulnerabilities and implemented corresponding mitigation solutions. We adapted the electricity market simulator for the Texas synthetic 2000-bus system and generated datasets for the false data injection attacks. We created database and visualization interfaces for the Texas system and the ISO New England system. We performed software optimization in terms of operation efficiency, computing speed and detection accuracy. Finally, we tested the software on the Texas system and the ISO New England system and evaluated the detection performance. Overall, we achieved above 89% detection rate, below 3% false alarm rate and below 37 seconds of end-to-end detection delay.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Near-Term Reliability and Resilience (NTRR) (Final Report)

The Near-Term Reliability and Resiliency (NTRR) was awarded in December 2020 as an inter-lab project to examine the reliability and resilience of the electricity grid and natural gas transportation availability. The project builds on studies conducted by The North American Electric Reliability Corporation (NERC), the U.S. Department of Energy (DOE), and other non-governmental research and operational focused on reliability and resilience analyses challenges. The research was conceived to address near-term scenarios (within 10 years), when many local and regional policy transitions could begin to impact grid reliability, resilience, and supporting infrastructure availability. To integrate the natural gas interdependency, the team began with the generating capacity and demand projections from the 2020 NERC Long-Term Reliability Assessment and the Bulk Electric System (BES) transmission topologies defined in the Western Electricity Coordinating Council (WECC) Anchor Data Set, Eastern Interconnection Reliability Assessment Group Multi-Regional Modeling Working Group (ERAG/MMWG) Data Set, the team calculated baseline regional power sector gas demands from present electricity delivery year through the end of delivery year 2030/31 by applying security constrained economic dispatch. This demand was compiled along with demand projections for regional residential, commercial, and industrial natural gas demands from the most recent Energy Information Administration (EIA) Annual Energy Outlook Reference Case into Deloitte’s MarketBuilder® North American Gas Model. Through the application of these demands, MarketBuilder® was projected the topology of natural gas flows in the natural gas pipeline network across the interconnected North American system along with regional natural gas prices that may be seen by market participants in future years Additionally, contingencies and sensitivities focused on the built models of the Eastern Interconnection (EI) and Western Interconnection (WI). They address challenges from the following with the outcomes being an identification of performance under the extreme conditions and an identification of potential grid weaknesses that should be addressed to mitigate the reduced performance and improve the resilience and reliability of the specific regions as well as the National Grid: • Weather events including extreme heat, extreme cold, high wind, no wind, wind and solar forecasting errors, and wildfires. • Gas availability, factoring in supply disruption (contractual and physical), seasonal availability constraints, and infrastructure limitations; and • Transmission availability and congestion.

03 NATURAL GAS↗
DOE OSTI2023

Ecosystems and Networks Integrated with Genes and Molecular Assemblies (ENIGMA): Integrating Metabolomics into Environmental Systems Biology

Our research endeavors entail ambitious objectives to explore the communities of microorganisms and quantify their chemical input and output to determine specific biochemical activity. To achieve these scientific aims, we are creating advanced algorithms to scrutinize extensive experimental data produced through high-throughput technologies, enabling us to elucidate how biological functions are influenced by environmental factors on various scales, and how microbial systems alter their surroundings. By studying the metabolic interdependence of bacterial communities for their survival and reproductive prosperity, we can gain insights into their biochemical capabilities. To accomplish this, we employed cutting-edge mass spectrometry-based techniques and metabolic fingerprinting methods, which offer high chemical specificity and sensitivity. As our efforts progressed, the project evolved into ENIGMA, encompassing a broader range of technology development, including untargeted metabolomics and its implementation for system-level organism analysis.

54 ENVIRONMENTAL SCIENCES↗