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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Coastal Acoustic Buoy for Offshore Wind: Project Synthesis

The population of North Atlantic right whales is critically endangered and their habitat overlaps with offshore windfarm leases. It is therefore imperative that effective mitigation strategies be used to avoid impacts on right whales during the construction of offshore windfarms. The Department of Energy issued FOA Number DE-FOA-0001924 to encourage the development of technology that could monitor large exclusion zones for right whales in order to mitigate potential impact of construction noise on right whales. This report summarizes the past two years of the development and evaluation of the Coastal Acoustic Buoy for Offshore Wind (CABOW) project which aimed to develop technology to monitor large exclusion zones for North Atlantic right whales. Over the course of the project SMRU Consulting have implemented a rigorous design process including comparison of different approaches (e.g., single sensor vs multiple sensors), as well as consideration of placement and timing of acoustic monitoring. We have evaluated critical components of the CABOW system including, reliability, detection range, and bearing accuracy in areas adjacent to offshore windfarm leases in Maryland by conducting 3,536 playbacks of simulated right whale upcalls. The maximum call detection range was 7.5 km when noise was 99 dB re 1µPa rms (50-225 Hz), but this reduced to < 1 km when ambient noise levels were high. Our detection probability in the field was measured as a function of range as well as the source-to-noise level ratio allowing us to build a model to predict the probability of detection under various scenarios (sample size: 3,536 calls x 5 buoys = 17,680). The median bearing error was -0.25° but this is likely an underestimate of error due to experimental design. Using the published recall and precision of the two detectors we implemented in the CABOW system, we estimate that at a recall of 80%, our precision was > 80%, within the range of what we were aiming for in this project. To estimate our exclusion zone false negative and false positive rates, we built a simulation model using the empirical data from our field trial. We modelled three to nine CABOW units placed on the 10 km exclusion zone and estimated our false negative rate to be 1% or less (which was our project goal) and our false positive rate to be between seven and nine percent, slightly above our goal of 5%. However, we also modelled an equivalent PAM system that does not have bearing capabilities and found the false positive rates for that system to be six to eight times higher than the CABOW rate. This higher false positive rate of PAM systems with low spatial information could have significant cost repercussions for offshore wind developers by adding work shutdowns or delays without providing additional protection for right whales. The model we built allows us to explore the placement of PAM systems under various scenarios and will thus help facilitate planning of PAM mitigation systems to meet NOAA Incidental Harassment Authorizations for specific windfarms. We achieved an average system uptime of 98.3%, just below our goal of 99%. The issues that caused these short losses of data have been identified and fixed. Right whale detections and audio clips were typically transferred via radio from the buoys to the base station in two to four seconds. We therefore believe we have developed a highly robust real-time PAM system. Based on the above, we feel we have achieved the stated funding goal of developing a cost-effective and robust real-time PAM system that enables the monitoring of large exclusion zones for right whales during the constructions of offshore windfarms. This should lead to decreased costs and risks for the offshore wind sector while providing robust mitigation for right whales. It is important to state that PAM mitigation will need to be implemented with other mitigation strategies (e.g., visual observers) to provide a complete mitigation strategy to ensure that any effects on right whales from offshore windfarm construction is minimized.

17 WIND ENERGY↗
DOE OSTI2024

Strategies for mitigating residual magnetic field effect on pre-production PIP-II SSR2 cryomodule performance

This paper outlines the strategy aimed at mitigating the adverse effects of residual magnetic fields on the performance of pre-production SSR2 superconducting cavities within the context of the PIP-II project at Fermilab. Residual magnetic fields can significantly impact cavity performance, leading to reduced quality factor. To address this challenge, our strategy integrates various approaches including magnetic shielding, careful selection of materials, quality controls aimed at measuring magnetic permeability, magnetic hygiene to reduce residual magnetic field at the installation phase. Additionally, experimental studies are being planned to analyze the behavior of the cavities under different magnetic field conditions, and the effectiveness of advanced demagnetization procedures.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Forecasting super-sample covariance in future weak lensing surveys with SuperSCRAM

The observable universe contains density perturbations on scales larger than any finite volume survey. Perturbations on scales larger than a survey can measure degrade its power to constrain cosmological parameters. The dependence of survey observables such as the weak lensing power spectrum on these long-wavelength modes results in super-sample covariance. Accurately forecasting parameter constraints for future surveys requires accurately accounting for the super-sample effects. If super-sample covariance is in fact a major component of the survey error budget, it may be necessary to investigate mitigation strategies that constrain the specific realization of the long-wavelength modes. We present a Fisher matrix based formalism for approximating the magnitude of super-sample covariance and the effectiveness of mitigation strategies for realistic survey geometries. We implement our formalism in the public code SuperSCRAM: Super-Sample Covariance Reduction and Mitigation. We illustrate SuperSCRAM with an example application, where the modes contributing to supersample covariance in the WFIRST weak lensing survey are constrained by the low-redshift galaxy number counts in the wider LSST footprint. We find that super-sample covariance increases the volume of the error ellipsoid in 7D cosmological parameter space by a factor of 4.5 relative to Gaussian statistical errors only, but our simple mitigation strategy more than halves the contamination, to a factor of 2.0.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Securing The Future: 2026 Manufacturing & Critical Infrastructure Threat Landscape

This report outlines the current state of manufacturing weaknesses introduced by the complexities of modern environments, including cloud services and Internet of Things (IoT) devices, with particular attention paid to the unique vulnerabilities encountered by SMMs. It also highlights CyManII’s strategic initiatives and collaborative solutions to mitigate these risks and strengthen the cybersecurity posture of the manufacturing ecosystem. Utilizing data from 2025 to inform forward-looking mitigation strategies, this report provides manufacturers with a clear understanding of both current and emerging cybersecurity threats, as well as practical opportunities to strengthen their cyber ecosystems. The following sections detail key vulnerabilities and threat vectors, along with actionable mitigation strategies, many of which have been developed or piloted through CyManII-led efforts. A thorough understanding of these risks and mitigation strategies is essential for manufacturers seeking to strengthen the security and resilience of their manufacturing operations.

3D Printing↗
NASA NTRS2012

Influence of Natural Environments in Spacecraft Design, Development, and Operation

The natural environment has a great influence on the ability of spacecraft to perform according to mission design specification. Compatibility with the natural environment is a primary factor in determining the functional lifetime of the spacecraft. The spacecraft being designed and developed today are growing in complexity. In many instances, the increased complexity also increases its sensitivity to environmental effects. Sensitivities to the natural environment can be tempered through appropriate design measures, mitigation strategies, and/or the acceptance of known risk. The design engineer must understand the effects of the natural environment on the spacecraft and its components; while having an in-depth knowledge of mitigation strategies. Too much protection incurs unnecessary expense, and often times excessive mass; while too little protection can easily lead to premature mission loss. This presentation will provide a brief overview of both the natural environment and its effects and provide some insight into mitigation strategies.

Edwards, David L.↗
NASA NTRSDate not supplied

ISS EVA80 EMU Water in the Helmet Failure and Associated Analytical Response

On March 23rd, 2022, during Extra-Vehicular Activity (EVA) 80 aboard the International Space Station (ISS) crew identified an 8-10-inch diameter thin film of water in the pressure bubble of the suit during repress. This launched an investigation to determine the cause of the water in the helmet as well as short- and long-term mitigation efforts to enable return to EVA as quickly as possible. The investigation analysis efforts in combination with hardware inspection and testing determined the most likely cause of the water in the helmet to be sublimator carryover as a result of high latent loading put on the system. In parallel with this investigation, efforts were being made to mitigate any future water in the helmet events. The short-term mitigation strategy developed is to install absorbent material in the pressure bubble to capture water as it enters the helmet before it can impact the astronauts. This hardware is referred to as the Helmet Absorption Band (HAB) and Helmet Absorption Pad – Extender (HAP-E). Longer-term mitigation strategies include a device to capture small water events before entering the helmet by installing a water capture system in the vent loop of the Extravehicular Mobility Unit (EMU). This effort is coined the T2 Water Capture System. Additionally, developing an on-orbit sublimator challenge test which will be able to verify sublimator performance before and after EVAs. The sublimator is the hardware which condenses water vapor and removes it from the vent loop, and this hardware is referred to as the EMU Moisture Injection Test System (EMITS). Based on the investigation and short-term water capture solutions the ISS Program decided to return to nominal EVAs on October 7, 2022. With the addition of the long-term mitigation strategies, the team hopes to be able to prevent any future water in the helmet events.

Veronica Lee Pizor↗
DOE OSTI2015

Identification of Modeling Approaches To Support Common-Cause Failure Analysis

Experience with applying current guidance and practices for common-cause failure (CCF) mitigation to digital instrumentation and control (I&C) systems has proven problematic, and the regulatory environment has been unpredictable. The impact of CCF vulnerability is to inhibit I&C modernization and, thereby, challenge the long-term sustainability of existing plants. For new plants and advanced reactor concepts, the issue of CCF vulnerability for highly integrated digital I&C systems imposes a design burden resulting in higher costs and increased complexity. The regulatory uncertainty regarding which mitigation strategies are acceptable (e.g., what diversity is needed and how much is sufficient) drives designers to adopt complicated, costly solutions devised for existing plants. The conditions that constrain the transition to digital I&C technology by the U.S. nuclear industry require crosscutting research to resolve uncertainty, demonstrate necessary characteristics, and establish an objective basis for qualification of digital technology for usage in Nuclear Power Plant (NPP) I&C applications. To fulfill this research need, Oak Ridge National Laboratory is conducting an investigation into mitigation of CCF vulnerability for nuclear-qualified applications. The outcome of this research is expected to contribute to a fundamentally sound, comprehensive technical basis for establishing the qualification of digital technology for nuclear power applications. This report documents the investigation of modeling approaches for representing failure of I&C systems. Failure models are used when there is a need to analyze how the probability of success (or failure) of a system depends on the success (or failure) of individual elements. If these failure models are extensible to represent CCF, then they can be employed to support analysis of CCF vulnerabilities and mitigation strategies. Specifically, the research findings documented in this report identify modeling approaches that can be adapted to contribute to the basis for developing systematic methods, quantifiable measures, and objective criteria for evaluating CCF vulnerabilities and mitigation strategies.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2011

The Use of the Integrated Medical Model for Forecasting and Mitigating Medical Risks for a Near-Earth Asteroid Mission

Introduction The Integrated Medical Model (IMM) is a decision support tool that is useful to space flight mission managers and medical system designers in assessing risks and optimizing medical systems. The IMM employs an evidence-based, probabilistic risk assessment (PRA) approach within the operational constraints of space flight. Methods Stochastic computational methods are used to forecast probability distributions of medical events, crew health metrics, medical resource utilization, and probability estimates of medical evacuation and loss of crew life. The IMM can also optimize medical kits within the constraints of mass and volume for specified missions. The IMM was used to forecast medical evacuation and loss of crew life probabilities, as well as crew health metrics for a near-earth asteroid (NEA) mission. An optimized medical kit for this mission was proposed based on the IMM simulation. Discussion The IMM can provide information to the space program regarding medical risks, including crew medical impairment, medical evacuation and loss of crew life. This information is valuable to mission managers and the space medicine community in assessing risk and developing mitigation strategies. Exploration missions such as NEA missions will have significant mass and volume constraints applied to the medical system. Appropriate allocation of medical resources will be critical to mission success. The IMM capability of optimizing medical systems based on specific crew and mission profiles will be advantageous to medical system designers. Conclusion The IMM is a decision support tool that can provide estimates of the impact of medical events on human space flight missions, such as crew impairment, evacuation, and loss of crew life. It can be used to support the development of mitigation strategies and to propose optimized medical systems for specified space flight missions. Learning Objectives The audience will learn how an evidence-based decision support tool can be used to help assess risk, develop mitigation strategies, and optimize medical systems for exploration space flight missions.

Kerstman, Eric↗
DOE OSTI2021

Gas hydrate deposit formation in transient flowloop tests and mitigation with a surface treatment

Thermodynamic and thermal mitigation strategies are traditionally utilized to prevent gas hydrate formation but may be rendered ineffective for certain unplanned, extended shut-in scenarios. Unfortunately, the current knowledge regarding transient gas hydrate formation has been extremely limited to only a few studies and unable to address this complex issue adequately. This work, conducted in a lab-scale flowloop, aims to add to the understanding of this area by delving into the implications of transient conditions on gas hydrate formation mechanisms, while also exploring a possible mitigation strategy of a surface treatment. Specifically, the effects of phase separation on gas hydrate formation locations, transportability, and plugging are presented for an oil-dominated system. An omniphobic surface treatment is shown to affect initial gas hydrate deposition and its wall adherence strength, as well as the overall plugging outcome. Overall, this work combines observational information with process data measurements to provide a better understanding of phase separated gas hydrate systems and passive deposition mitigation strategies. This can further aid advanced gas hydrate modeling efforts, which currently do not adequately address transient flow effects on phase separation/dispersion. Here, it offers representative gas hydrate testing for coatings, which have exclusively been limited to non-flowing and/or bench-scale analysis, to give confidence in their potential application as advanced deposition prevention tools.

03 NATURAL GAS↗
NASA NTRS2018

Estimating Mangrove Aboveground Biomass from Airborne LiDAR Data: a Case Study from the Zambezi River Delta

Mangroves are ecologically and economically important forested wetlands with the highest carbon (C) density of all terrestrial ecosystems. Because of their exceptionally large C stocks and importance as a coastal buffer, their protection and restoration has been proposed as an effective mitigation strategy for climate change. The inclusion of mangroves in mitigation strategies requires the quantification of C stocks (both above and belowground) and changes to accurately calculate emissions and sequestration. A growing number of countries are becoming interested in using mitigation initiatives, such as REDD+ (reducing emissions from deforestation and forest degradation), in these unique coastal forests. However, it is not yet clear how methods to measure C traditionally used for other ecosystems can be modified to estimate biomass in mangroves with the precision and accuracy needed for these initiatives. Airborne Lidar (ALS) data has often been proposed as the most accurate way for larger scale assessments but the application of ALS for coastal wetlands is scarce, primarily due to a lack of contemporaneous ALS and field measurements. Here, we evaluated the variability in field and Lidar-based estimates of aboveground biomass (AGB) through the combination of different local and regional allometric models and standardized height metrics that are comparable across spatial resolutions and sensor types, the end result being a simplified approach for accurately estimating mangrove AGB at large scales and determining the uncertainty by combining multiple allometric models.We then quantified wall-to-wall AGB stocks of a tall mangrove forest in the Zambezi Delta, Mozambique. Our results indicate that the Lidar H100 height metric correlates well with AGB estimates, with R(exp 2) between 0.80 and 0.88 and RMSE of 33% or less. When comparing Lidar H100 AGB derived from three allometric models, mean AGB values range from 192 Mg ha(exp −1) up to 252 Mg ha(exp −1).We suggest the best model to predict AGB was based on the East Africa specific allometry and a power-based regression that used Lidar H100 as the height input with an R(exp 2) of 0.85 and an RMSE of 122 Mg ha(exp −1) or 33%. The total AGB of the Lidar inventoried mangrove area (6654 ha) was 1 350 902 Mg with a mean AGB of 203 Mg ha(exp −1) +/-166 Mg ha(exp −1). Because the allometry suggested here was developed using standardized height metrics, it is recommended that the models can generate AGB estimates using other remote sensing instruments that are more readily accessible over other mangrove ecosystems on a large scale, and as part of future carbon monitoring efforts in mangroves.

Fatoyinbo, Temilola↗
DOE OSTI2019

Experimental and modeling study of chemical-based strategies for mitigating dust formation in fusion reactors [Plasma Flow Reactor Chemical Kinetics: A Method Toward Optimizing Nano-Manufacturing and Laser Inertial Fusion Energy Strategies]

We studied carbon/hydrogen/oxygen chemical kinetics at time scales and thermal conditions relevant to fusion energy applications using a custom-built plasma flow reactor to investigate chemical-based strategies for eliminating carbon dust formation in fusion reactors. Acetylene and oxygen gases under varying conditions of initial concentrations are injected into an inductively coupled argon plasma where complete molecular dissociation occurs. The evolution of chemical species is investigated along the plasma flow reactor as a function of temperature and residence time. Atomized species of C, H, and O cool from 5000 K to 1000 K within 30 ms at atmospheric pressures. We employed optical emission and infrared absorption spectroscopy to measure the reaction intermediates (e.g. C 2 ) and products (e.g. C 2 H 2 ). Chemical equilibrium models are inadequate to describe the evolution of carbon molecular products, and thus a chemical kinetics model is developed. In both experiments and kinetic modelling, we find that the addition of oxygen in 1:1 proportion to carbon strongly favors the formation of CO, preventing the formation of acetylene (an important soot precursor) in less than 10 milliseconds. The kinetics model is also used to perform a reaction sensitivity and a rate of production analyses to identify the rate determining steps and the major chemical pathways that control the acetylene production/consumption. The results demonstrate the feasibility of chemical-based strategies for eliminating the formation of carbonaceous particles in fusion energy reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Systems Theory Principles and Complex Systems Engineering Concepts for Protection and Resilience in Critical Infrastructure: Lessons from the Nuclear Sector

Part of the Presidential Policy Directive 21 (PPD-21) (PPD 2013) mandate includes evaluating safety, security, and safeguards (or nonproliferation) mechanisms traditionally implemented within the nuclear reactors, materials, and waste sector of critical infrastructure—including a complex, dynamic set of risks and threats within an all-hazards approach. In response, research out of Sandia National Laboratories (Sandia) explores the ability of systems theory principles (hierarchy and emergence) and complex systems engineering concepts (multidomain interdependence) to better understand and address these risks and threats. Herein, this Sandia research explores the safety, safeguards, and security risks of three different nuclear sector-related activities—spent nuclear fuel transportation, small modular reactors, and portable nuclear power reactors—to investigate the complex and dynamic risk related to the PPD-21-mandated all-hazards approach. This research showed that a systems-theoretic approach can better identify inter-dependencies, conflicts, gaps, and leverage points across traditional safety, security, and safeguards hazard mitigation strategies in the nuclear reactors, materials, and waste sector. Resulting from this, mitigation strategies from applying systems theoretic principles and complex systems engineering concepts can be (1) designed to better capture interdependencies, (2) implemented to better align with real-world operational uncertainties, and (3) evaluated as a systems-level whole to better identify, characterize, and manage PPD-21's all hazards strategies.

42 ENGINEERING↗
DOE OSTI2021

Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results

Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells - increasing or decreasing the fluid flow rates across the wells - and drilling new wells at appropriate locations. The latter is expensive, time-consuming, and subject to many engineering constraints, but the former is a viable mechanism for periodic adjustment of the available fluid allocations. Data and supporting literature from a study describing a new approach combining reservoir modeling and machine learning to produce models that enable strategies for the mitigation of decreased heat and power production rates over time for geothermal power plants. The computational approach used enables translation of sets of potential flow rates for the active wells into reservoir-wide estimates of produced energy and discovery of optimal flow allocations among the studied sets. In our computational experiments, we utilize collections of simulations for a specific reservoir (which capture subsurface characterization and realize history matching) along with machine learning models that predict temperature and pressure timeseries for production wells. We evaluate this approach using an "open-source" reservoir we have constructed that captures many of the characteristics of Brady Hot Springs, a commercially operational geothermal field in Nevada, USA. Selected results from a reservoir model of Brady Hot Springs itself are presented to show successful application to an existing system. In both cases, energy predictions prove to be highly accurate: all observed prediction errors do not exceed 3.68% for temperatures and 4.75% for pressures. In a cumulative energy estimation, we observe prediction errors that are less than 4.04%. A typical reservoir simulation for Brady Hot Springs completes in approximately 4 hours, whereas our machine learning models yield accurate 20-year predictions for temperatures, pressures, and produced energy in 0.9 seconds. This paper aims to demonstrate how the models and techniques from our study can be applied to achieve rapid exploration of controlled parameters and optimization of other geothermal reservoirs. Includes a synthetic, yet realistic, model of a geothermal reservoir, referred to as open-source reservoir (OSR). OSR is a 10-well (4 injection wells and 6 production wells) system that resembles Brady Hot Springs (a commercially operational geothermal field in Nevada, USA) at a high level but has a number of sufficiently modified characteristics (which renders any possible similarity between specific characteristics like temperatures and pressures as purely random). We study OSR through CMG simulations with a wide range of flow allocation scenarios. Includes a dataset with 101 simulated scenarios that cover the period of time between 2020 and 2040 and a link to the published paper about this project, where we focus on the Machine Learning work for predicting OSR's energy production based on the simulation data, as well as a link to the GitHub repository where we have published the code we have developed (please refer to the repository's readme file to see instructions on how to run the code). Additional links are included to associated work led by the USGS to identify geologic factors associated with well productivity in geothermal fields. Below are the high-level steps for applying the same modeling + ML process to other geothermal reservoirs: 1. Develop a geologic model of the geothermal field. The location of faults, upflow zones, aquifers, etc. need to be accounted for as accurately as possible 2. The geologic model needs to be converted to a reservoir model that can be used in a reservoir simulator, such as, for instance, CMG STARS, TETRAD, or FALCON 3. Using native state modeling, the initial temperature and pressure distributions are evaluated, and they become the initial conditions for dynamic reservoir simulations 4....

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Spatially resolved degradation during startup and shutdown in polymer electrolyte membrane fuel cell operation

Polymer electrolyte membrane fuel cells have durability limitations associated with the startup and shutdown of the fuel cell, which is critical for real-world vehicle commercialization. During startup or shutdown, there exists an active region (hydrogen/air) and a passive region (air/air) between the cell inlet and outlet. Internal currents are generated in the passive region causing high-potential excursion in the cathode leading to accelerated carbon corrosion. In this study, a segmented cathode hardware is used to evaluate the effect of platinum loading on both cathode and anode, and carbon support material on degradation due to repeated series of startups or shutdowns. Here, in situ losses in the performance and electrochemical surface area were measured spatially, and ex situ analysis of the catalyst layer thickness and platinum particle size was performed to understand the effect of startup or shutdown on different membrane electrode assembly materials. Startup degrades the region near anode outlet more, while shutdown degrades the region near anode inlet more compared to the rest of the electrode. While various system mitigation strategies have been reported in the literature to limit this degradation, one materials mitigation strategy is to limit the anode's ability to reduce oxygen to water through increasing the ratio of platinum loading in the cathode to the anode, or by using a bi-functional catalyst.

25 ENERGY STORAGE↗
DOE OSTI2017

Improved Safety Injection Flow Map Associated with Target RCS Depressurization to Maintain Core Coolability of OPR1000

In Korea, Severe Accident Management Guidance (SAMG) for Optimized Power Reactor (OPR1000) has been developed through the research results related to the WOG SAMG, in which the operation phase shifts from the Emergency Operation Procedure (EOP) to the SAMG when the Core Exit Temperature (CET) reaches 923 K. Among 7 mitigation strategies envisioned, the third management strategy, injecting coolant into Reactor Coolant System (RCS) by depressurizing the RCS is one of the key strategies to fortify the in-vessel retention capability. As an aid to such mitigation strategy, a safety injection (SI) flow map has been developed by Lee et al. for predicting required flow rate associated with target RCS depressurization to recover in-vessel coolability. The mechanistic SI flow map used the CET increase rate and core water level decrease rate obtained from MELCOR code simulation. It should be noted that during the severe accident, the total heat generated is sum of the decay heat and the oxidation heat. Thus, it is necessary to consider additional heat sources by oxidation reaction between cladding, structure, control rod, and hot steam prior to the injection of coolant. It was believed that the SI model estimated required flow rate rather conservatively by considering the expected amount decay heat and the accumulated heat in the core based on the RCS pressure. However, it was confirmed that the SI model developed by Lee et al. could not represent the total heat removal especially since start of oxidation. Under transient conditions, the heat sources accumulated in the heat structures (fuel, cladding, supporting structures) should be embarked in the model for accurate contribution of the total heat source to the required flow rate. Therefore, the objective of this study is to improve the previous SI flow map predicting the injection flow rate associated with target RCS depressurization to satisfy the in-vessel coolability during severe accidents. Additional terms were developed to reflect accurate heat accumulating and included in the existing model. Resulting SI flow map includes the target RCS depressurization, which enables discharge of the required flow rate by utilizing the flow rate-pressure curve with operation of two high pressure safety injections (HPSIs). Also recent MELCOR simulation result of a postulated steam generator tube rupture (SGTR) accident verified the accuracy of the improved map.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Multizonal modeling of SARS-CoV-2 aerosol dispersion in a virtual office building

The dispersion of indoor airborne contaminants across different zones within a mechanically ventilated building is a complex phenomenon driven by multiple factors. In this study, we modeled the indoor dispersion of airborne SARS-CoV-2 aerosols within a US Department of Energy detailed medium office prototype building using CONTAM software. The aim of this study is to improve our understanding about how different parts of a building can experience varying concentrations of the airborne viruses under different circumstances of release and mitigation strategies. Results indicate that unventilated stairwells can have significantly higher concentrations of airborne viruses. The mitigation strategies of morning and evening flushing of conditioned zones were not found to be very effective. Instead, a constant high percentage of outdoor air in the supply mix, and the use of masks, portable HEPA air cleaners, MERV 13 or higher HVAC air filters, and ultraviolet germicidal irradiation disinfection were effective strategies to prevent airborne viral contamination in the majority of the simulated office building.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

After the hurricane: Validating a resilience assessment methodology

With increasing utility grid outages in the United States, there is growing interest in assessing risk and developing mitigation strategies to reduce the impact of grid outages. Working with the U.S. Air Force, the U.S. Department of Energy's National Renewable Energy Laboratory (NREL) developed a replicable energy resilience assessment methodology and investment decision tool to: (1) identify and score hazards and vulnerabilities at the site level; (2) analyze risks to energy infrastructure; and (3) identify and prioritize energy resilience investments. This work improves on existing resilience assessment methodologies and tools by combining a bottom-up, all-hazards assessment methodology with top-down geographic information system mapping capabilities to provide an innovative, dynamic tool for identifying and prioritizing actionable solutions. This process combines probabilistic forecasting with an iterative approach for continuously updating and reassessing risks to address temporal dynamism. Relationships among systems are modeled and visualized to estimate the effectiveness of resilience actions across multiple interdependent systems and inform financial priorities through cost-difficulty-impact trade-offs. The approach is validated in a case study at Tyndall Air Force Base (AFB) in Florida, which experienced a Category 5 hurricane in 2018. The risks and mitigation strategies identified pre-hurricane are compared with post-hurricane, realized impacts. The assessment effectively identifies risks and actions to increase site energy resilience, but the methodology can be enhanced though greater consideration of the interdependencies between the energy system and related systems like transportation, communication, and food/water systems, which impact the recovery of the energy system and the base.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

CalWave Design for PacWave - Preliminary Design Phase - Risk Management Plan

The project objectives for CalWave's deployment at PacWave are distinguished by the Preliminary Design Phase and the Detailed Design Phase. During the Preliminary Design Phase, the Risk Register was established to identify risks and mitigation strategies. The Risk Management Plan assesses potential risks of CalWave's technology and accompanying processes and describes the risk mitigation strategies for the project.

16 TIDAL AND WAVE POWER↗