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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Inventory and Probabilistic Function of Natural Hazards in the United States: July 19, 2018 - September 18, 2018

The U.S. Department of Energy's National Renewable Energy Laboratory (NREL) developed a standardized risk assessment process that considers the location-specific vulnerabilities and threats (climate-related as well as human-caused) at a site to generate a ranked list of organizational risks and associated mitigation options for reducing those risks. To support this effort, the Southern Climate Impacts Planning Program (SCIPP), a National Oceanic and Atmospheric (NOAA) Regional Integrated Sciences and Assessments (RISA) team, was selected to provide climate science expertise to develop a comprehensive inventory and probabilistic function of natural hazards (e.g., hurricanes, tornadoes, flooding, and sea level rise) for the entire United States by region. The inventory of climate-related hazards and the associated likelihood scores are incorporated into a companion risk assessment tool enabling standardized comparisons of risk at sites across the country.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Risk-Informed Safety Analysis for Accident Tolerant Fuels

Accident Tolerant Fuels (ATF) are being tested by different nuclear vendors and research organization and their introduction in light water reactors fleet is planned for the second half of the 2020`s. In the framework of the US-DOE Light-Water Reactor Sustainability program, Risk-Informed Safety Analysis pathway (LWRS-RISA), research activities are being conducted at the Idaho National Laboratory (INL) for developing tools and methods that can help the industry in quantifying the ATF introduction benefits. In this paper we describe the developed risk-informed methodology, the codes improvements and we present some results for selected accidental conditions. The developed methodology combines INL state-of-the-art deterministic Best Estimate tools like RELAP5-3D code, and Probabilistic Risk Analysis tools like RAVEN and SAPHIRE codes. The analyses are performed on a three-loops pressurized water reactor (PWR) simulating accidental conditions like Station Blackout and LB-LOCA and considering near-term ATF (FeCrAl and Chromium-coated clads). Finally, we show, through our methodologies, how the delta-Core Damage Frequency can be assessed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Tools And Methods to Analyze Plant Outage Schedule and Assist Schedulers in Improving Outage Resilience

Refueling outages of nuclear power plants (NPPs) are considered one of the most critical phases throughout the plant lifetime. In such instances, tens of thousands of activities (e.g., maintenance, surveillance) are performed in a short amount of time (typically 2-3 weeks unless major backfitting or modernization projects are carried out) by a large number of crews (e.g., electricians, mechanics) that are hired as contractors. As a consequence, a plant outage can be expensive not only in terms of costs (e.g., contractor labor, material), but also in terms of loss generation since the plant is taken off the grid during the full outage duration (an indicative metric is about 1.2M$/day of loss of revenue). Thus, there is a continuous need to decrease the economic impact of outages on plant finances. This can be done by: decreasing the frequency of plant outages (e.g., from 18 to 24 months), reducing the time to complete the outage, and reducing the risk of outage delays. The Optimization of Outage Activities project under the Risk Informed Systems Analysis Pathway (RISA) sponsored by Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program focuses on developing tools and methods to support NPPs with outage schedule optimization. The developed tools and methods are designed to analyze plant outage schedule with the goal of identify critical elements in the schedule that might pose a high risk of delays. These methods and tools can be considered resource-centric in the sense that they address outage challenges as a resource optimization problem. In this context, resources are either time and crews; outage delays occurs when either (or both) resources are insufficient to complete the set of tasks assigned at a specific time instant of the outage. This report provides details on how plant resources (time and crews) can be allocated in such a way that delays are minimized. In this respect, two classes of methods have been developed: the first one focuses on the time resource and how variability of the time to complete outage tasks may impact outage delays. The second one integrates available resources to assess when dailies activities should be performed such that the risk of outage delays are minimized.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2016

Participatory Climate Research in a Dynamic Urban Context: Activities of the Consortium for Climate Risk in the Urban Northeast (CCRUN)

The Consortium for Climate Risk in the Urban Northeast (CCRUN), one of ten NOAA-RISAs, supports resilience efforts in the urban corridor stretching from Philadelphia to Boston. Challenges and opportunities include the diverse set of needs in broad urban contexts, as well as the integration of interdisciplinary perspectives. CCRUN is addressing these challenges through strategies including: 1) the development of an integrated project framework, 2) stakeholder surveys, 3) leveraging extreme weather events as focusing opportunities, and 4) a seminar series that enables scientists and stakeholders to partner. While recognizing that the most extreme weather events will always lead to surprises (even with sound planning), CCRUN endeavors to remain flexible by facilitating place-based research in an interdisciplinary context.

extreme events↗
DOE OSTI2021

Multicriterion Benefit Evaluation of Deploying New Battery Technology with Increased Capacity at a Generic Nuclear Power Plant

This presentation is prepared for the DOE LWRS RISA Pathway Stakeholder Engagement Meeting on October 13-14, 2021. Nuclear power plant (NPP) safety improvements are routinely made by plant licensees and regulators. Examples of plant improvements include accident-tolerant fuel, diverse and flexible coping strategies, passive cooling systems, and increased battery capacity. A combined use of these plant improvements could lead to plant designs with enhanced resilience, allowing NPPs to better cope with both internal and external hazards and keep the plant operating safely, efficiently, and economically. This presentation focuses on increased battery capacity and evaluates the potential costs and benefits of deploying batteries with increased capacities at a generic boiling water reactor (BWR) NPP. A multicriterion benefit evaluation methodology is used for the cost-benefit analysis. Ten alternatives for extending battery capacity are developed, including eight alternatives to provide additional direct-current power and one alternative to provide additional alternating-current power. Potential benefits of reducing plant risk are quantified through incorporating the alternatives into loss-of-offsite-power scenarios of the generic BWR probabilistic risk assessment model. Potential costs of implementing the alternatives are qualitatively discussed and ranked. The alternatives are then compared based on their impacts on plant risk and economics.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Pressurized-Water Reactor Core Design using Multi-Objective Plant Fuel Reload Optimization Platform

The United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program Risk-Informed Systems Analysis (RISA) Pathway Plant Reload Optimization Project aims to develop an integrated, comprehensive framework offering an all-in-one solution for reload evaluations with a special focus on optimization of core design. The optimization of the fuel loading pattern is one of the most important considerations in reducing the amount of new fuel used in the core. Due to thousands of possible options of core configuration, finding optimal solutions is an unachievable task for a human. The Plant ReLoad Optimization (PRLO) platform which supports artificial-intelligence-based reactor core designing is now fully capable of handling realistic problems. The PRLO Platform development project aims to build a reactor core design tool that includes reactor safety and fuel performance analyses and uses artificial intelligence to support the optimization of core design solutions. The NSGA-II (Non-dominated Sorting Genetic Algorithm-II) optimizer was developed and tested within RAVEN (Risk Analysis and Virtual Environment) to handle many constraints by using an augmented objectives methodology. The demonstration was performed with constrained multi-objective optimization of a 17 × 17 pressurized-water reactor core loading patterns to minimize fuel cost and maximize fuel cycle length.

42 ENGINEERING↗
DOE OSTI2021

Combination of cluster number counts and two-point correlations: validation on mock Dark Energy Survey

ABSTRACT We present a method of combining cluster abundances and large-scale two-point correlations, namely galaxy clustering, galaxy–cluster cross-correlations, cluster autocorrelations, and cluster lensing. This data vector yields comparable cosmological constraints to traditional analyses that rely on small-scale cluster lensing for mass calibration. We use cosmological survey simulations designed to resemble the Dark Energy Survey Year 1 (DES-Y1) data to validate the analytical covariance matrix and the parameter inferences. The posterior distribution from the analysis of simulations is statistically consistent with the absence of systematic biases detectable at the precision of the DES-Y1 experiment. We compare the χ2 values in simulations to their expectation and find no significant difference. The robustness of our results against a variety of systematic effects is verified using a simulated likelihood analysis of DES-Y1-like data vectors. This work presents the first-ever end-to-end validation of a cluster abundance cosmological analysis on galaxy catalogue level simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A non-fueled nuclear-heated rod for in-pile transient boiling studies

Separate-effects boiling experiments have recently been conducted in the Transient Reactor Test Facility at Idaho National Laboratory to investigate transient heating and irradiation effects on cladding-to-coolant heat transfer. Specifically, transient critical heat flux (CHF) remains an important area of research, and better understanding of this phenomenon has potential for improving predictive models related to operational and safety limits. Consequently, this knowledge is expected to improve efficiency of light-water reactor operations. A novel borated nuclear-heated rodlet (BNHR) was designed to enable observation of transient cladding-to-coolant heat transfer phenomena. The final BNHR design takes a surrogate approach, wherein nuclear heating is induced by 10 B(n, α) reactions rather than derived from fissions in a fueled specimen. The structure of the BNHR consists of a hollowed out borated (B nat ~ 2.05 wt %) stainless steel tube with an hourglass-shaped outer surface, capped at both ends with non-borated stainless steel. This geometry allows for inner-rodlet instrumentation and generation of the highest nuclear heating rates near the center of the rodlet to ensure onset of boiling near instrumentation for real-time observation. A novel approach to measuring the nuclear energy deposition rate in the BNHR separate and apart from the influence of the coolant, termed the n-a thermometer, is also detailed in this paper. This device has demonstrated excellent repeatability, and measurements indicate predictive modeling results for energy deposition in the BNHR rod agree within a 10% margin of the experiment measurements. In conclusion, these results give confidence that the BNHR design has successfully met experiment objectives.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Zwitterion Moieties in Polypeptides Synergistically Enhance the Release of Cellulose and Amorphous Polysaccharides from Plant Cell Walls

This study demonstrated that covalently localized zwitterionic moieties in zwitterionic polypeptides (ZIPs) effectively disrupt hydrogen bonds in cellulosic substrates, including filter paper and plant cell wall materials, without significant cytotoxicity. ZIPs with varying densities of zwitterionic side chains were synthesized via the postpolymerization modification of histidinecontaining oligopeptides. The newly developed ZIPs predominantly comprised repeating units with zwitterionically converted side chains. Such ZIPs can cleave multiple hydrogen bonds by anchoring the zwitterionic structure at specific sites, thereby partially dissociating the polysaccharide chains in the cell wall. They are especially effective in dissolving amorphous cellulose, even at low concentrations in aqueous solutions. Importantly, this effect was achieved with minimal cellular toxicity, harnessing the advantages of ionic liquid-like properties while mitigating their high-toxicity limitations. This biofriendly approach to cell wall denaturation highlights a novel method for controlling hydrogen bond networks in polysaccharides and cell walls. These findings indicate a new approach for reducing biomass recalcitrance and developing next-generation biobased materials and fuels derived from plant cell walls.

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

Database of pharmacokinetic time-series data and parameters for 144 environmental chemicals

Time courses of compound concentrations in plasma are used in chemical safety analysis to evaluate the relationship between external administered doses and internal tissue exposures. This type of experimental data is rarely available for the thousands of non-pharmaceutical chemicals to which people may potentially be unknowingly exposed but is necessary to properly assess the risk of such exposures. In vitro assays and in silico models are often used to craft an understanding of a chemical’s pharmacokinetics; however, the certainty of the quantitative application of these estimates for chemical safety evaluations cannot be determined without in vivo data for external validation. To address this need, we present a public database of chemical time-series concentration data from 567 studies in humans or test animals for 144 environmentally-relevant chemicals and their metabolites (187 analytes total). All major administration routes are incorporated, with concentrations measured in blood/plasma, tissues, and excreta. We also include calculated pharmacokinetic parameters for some studies, and a bibliography of additional source documents to support future extraction of time-series. In addition to pharmacokinetic model calibration and validation, these data may be used for analyses of diferential chemical distribution across chemicals, species, doses, or routes, and for meta-analyses on pharmacokinetic studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Aemulus $\nu$: precise predictions for matter and biased tracer power spectra in the presence of neutrinos

Here we present the Aemulusν simulations: a suite of 150 (1.05 h -1 Gpc) 3 N-body simulations with a mass resolution of 3.51 × 10 10 Ω cb /0.3 h -1 M ⊙ in a wνCDM cosmological parameter space. The simulations have been explicitly designed to span a broad range in σ8 to facilitate investigations of tension between large scale structure and cosmic microwave background cosmological probes. Neutrinos are treated as a second particle species to ensure accuracy to 0.5 eV, the maximum neutrino mass that we have simulated. By employing Zel'dovich control variates, we increase the effective volume of our simulations by factors of 10-10 5 depending on the statistic in question. As a first application of these simulations, we build new hybrid effective field theory and matter power spectrum surrogate models, demonstrating that they achieve ≤ 1% accuracy for k ≤ 1 hMpc -1 and 0 ≤ z ≤ 3, and ≤ 2% accuracy for k ≤ 4 hMpc -1 for the matter power spectrum. We publicly release the trained surrogate models, and estimates of the surrogate model errors in the hope that they will be broadly applicable to a range of cosmological analyses for many years to come.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Aemulus ν: precision halo mass functions in wνCDM cosmologies

Precise and accurate predictions of the halo mass function for cluster mass scales in wνCDM cosmologies are crucial for extracting robust and unbiased cosmological information from upcoming galaxy cluster surveys. Here, we present a halo mass function emulator for cluster mass scales (≳ 1013 M ⊙/h) up to redshift z = 2 with comprehensive support for the parameter space of wνCDM cosmologies allowed by current data. Based on the Aemulus ν suite of simulations, the emulator marks a significant improvement in the precision of halo mass function predictions by incorporating both massive neutrinos and non-standard dark energy equation of state models. This allows for accurate modeling of the cosmology dependence in large-scale structure and galaxy cluster studies. We show that the emulator, designed using Gaussian Process Regression, has negligible theoretical uncertainties compared to dominant sources of error in future cluster abundance studies. Our emulator is publicly available (https://github.com/DelonShen/aemulusnu_hmf), providing the community with a crucial tool for upcoming cosmological surveys such as LSST and Euclid.

cluster counts↗