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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 397 records · Page 22

Impact of Irradiation on Corrosion Performance of Hybrid Organic/Inorganic Coatings on Austenitic Stainless Steel

The effects of gamma radiation on the performance of two corrosion-resistant coatings applied to stainless-steel 304L (SS304L) surfaces are presented. Specifically, the ability of the coatings to mitigate corrosion of SS304L surfaces as a function of the dose received (0–1300 Mrad) and dose rate (176 compared to 1054 rad/s) is evaluated using electrochemical methods, spectroscopy, and microscopy. Coating A, an organic/inorganic hybrid coating consisting of a two-part silica ceramic component and a polymer linker was evaluated in comparison to Coating B, which utilized Coating A as a topcoat for a commercial, off-the-shelf, Zn-rich primer. Post irradiation, Coating A demonstrated some corrosion protection following exposure to low levels of gamma radiation, but coating degradation occurred with an increased exposure dose and resulted in isolated regions of corrosion initiation. For Coating B, greater corrosion resistance was observed compared to Coating A due to the sacrificial nature of the Zn at elevated doses of gamma radiation. No effect of the dose rate (for the single dose examined) was observed for either coating. It is proposed for Coating B that as the polymer coating thermally degrades above 250 °C (bond scission of the polymer occurs), the remaining Zinc layer adhered to the SS304L post-irradiation enables enhanced corrosion resistance as compared to Coating A, which displays solely polymer degradation. The results presented herein establish an understanding of coating behavior with radiation exposure, specifically the relationship between corrosion coating performance and radiation dose, and can inform ageing and lifetime management for various applications.

degradation↗

Demand response event simulator and risk-aware bidding tool for industrial customers

Incentive Based Demand Response (IBDR) program participation delivers financial benefits to the consumers and resiliency benefits to the electricity grid. Effectively participating in these programs as an industrial consumer requires bidding strategies that balance financial risk with operational constraints. Existing bidding tools tend not to fully incorporate stochastic IBDR event modeling, program specific baseline and payment/penalty calculations, or demand reduction process control schemes that account for the cascading impacts of shutdown in complex facilities. Here, this work presents an IBDR event simulator and risk-aware bidding framework tool integrating three key components: a flexible, parameterized demand response event generator that rigorously accounts for program structures and stochasticity, a demand response operational simulation model that generates explicit control strategies for load reduction, and a Monte Carlo simulator to evaluate financial risk for varied capacity bids. A case study at a wastewater treatment plant participating in PG&E's Capacity Bidding Program demonstrates the framework's utility. In the peak capacity price month of August, optimal bidding by the wastewater treatment plant nets a mean IBDR benefit of $101,000 (67% of the August electricity bill) with 0.4% probability of a financial loss. This framework enables industrial operators to make informed bidding decisions, negotiate better program terms with demand response load aggregators, and analyze energy flexibility investments at their facilities. Ultimately, this work reduces participation barriers in IBDR programs and supports the broader goal of enhancing grid reliability and renewable energy integration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Automatic detection of impact craters on Al foils from the Stardust interstellar dust collector using convolutional neural networks

NASA's Stardust mission utilized a sample collector composed of aerogel and aluminum foil to return cometary and interstellar particles to Earth. Analysis of the aluminum foil begins with locating craters produced by hypervelocity impacts of cometary and interstellar dust. Interstellar dust craters are typically less than one micrometer in size and are sparsely distributed, making them difficult to find. In this paper, we describe a convolutional neural network based on the VGG16 architecture that achieves high specificity and sensitivity in locating impact craters in the Stardust interstellar collector foils. Finally, we evaluate its implications for current and future analyses of Stardust samples.

79 ASTRONOMY AND ASTROPHYSICS↗

Direct Air Capture-Based Carbon Dioxide Removal with United States Low-Carbon Energy and Sinks

The overall objective of this project was to complete an initial design of a commercial-scale, Carbon Capture and Storage system for Direct Air Capture (CCS-DAC) that separates and stores a minimum of 100,000 tonnes/year (t/yr.) net CO 2 from air. Three geographically diverse host sites will be used to determine the impact of different climates on the design and cost of the CCS-DAC systems; California (dry-hot), Louisiana (humid-hot), and Wyoming (mid-continental). In addition, the impact of using different low-carbon energy sources was also examined. The focus of this project was to geologically store the CO 2 , rather than the utilization of CO 2 . This Final Scientific/Technical Report is a collection of the deliverables for the project. The project team was able to successfully complete all the necessary tasks needed to determine the feasibility of the designs and operational needs of the DAC systems for each location. The data created by this allowed the project team to conduct the required evaluations to meet the requirements of the deliverables. The following deliverables were drafted and submitted to DOE prior to the conclusion of the project: (1) Initial Engineering Design; (2) Costing Estimate; (3) Techno-Economic Analysis (TEA); (4) Life Cycle Analysis (LCA); (5) Business Case Assessment; and (6) Technology EH&S Risk Assessment.

42 ENGINEERING↗

Performance Metrics to Evaluate Utility Resilience Investments

In 2019, Sandia National Laboratories (Sandia) contracted Synapse Energy Economics (Synapse) to research the integration of community and electric grid resilience investment planning as part of the Designing Resilient Communities (DRC): A Consequence-Based Approach for Grid Investment project. Synapse produced a series of reports to explore the challenges and opportunities in several key areas, including benefit-cost analysis (BCA), performance metrics, microgrids, and regulatory mechanisms. This report focuses on BCA. BCA is an approach that electric utilities, electric utility regulators, and communities can use to evaluate the costs and benefits of a wide range of grid resilience investments in a comprehensive and consistent way. While BCA is regularly applied to some types of grid investments, application of BCA to grid resilience investments is in the early stages of development. Though resilience is increasingly cited in connection with grid investment proposals and plans, the resilience- related costs and benefits of grid resilience investments are typically not fully identified, infrequently quantified, and almost never monetized. Without complete assessments of costs and benefits, regulators can be hesitant to approve some types of grid resilience investments. This report provides the first application of the framework developed in the 2020 National Standard Practice Manual for Benefit-Cost Analysis of Distributed Energy Resources (NSPM for DERs) to grid resilience investments. We provide guidance on next steps for implementation to enable grid resilience investments to receive due consideration. We suggest developing BCA principles and standards for jurisdiction-specific BCA tests. We also recommend identifying the resilience impacts of the investments and quantification of these impacts by establishing utility performance metrics for resilience. Proactive integration of grid resilience investments into existing regulatory processes and practices can increase the capacity of jurisdictions to respond to and recover from the consequences of extreme events. 1 National Energy Screening Project. 2020. National Standard Practice Manual for Benefit-Cost Analysis of Distributed Energy Resources.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Silver Sulfide and Silver Sulfate as Aging Byproducts and Adsorbents for Gaseous Iodine Capture in Spent Nuclear Fuel Reprocessing

While it is considered a promising adsorbent for radioiodine capture in spent nuclear fuel reprocessing off-gas, silver functionalized silica aerogel (Ag 0 -aerogel) experiences a capacity loss when exposed to other off-gas components (O 2 , H 2 O, NO, and NO 2 ) through a process known as aging. Ag 2 S and Ag 2 SO 4 were identified as major byproducts of aging, but their impact on iodine adsorption remains unclear. Thus, to further investigate aging, we loaded Ag 2 S and Ag 2 SO 4 powders with molecular iodine (I 2 ) at 150 °C and characterized their properties. The I 2 adsorption capacity of Ag 2 SO 4 was 0.12 wt % after 72 h, suggesting its formation directly reduces the capacity of the Ag 0 -aerogel. Conversely, Ag 2 S had an iodine capacity of 86.8 wt % and near total Ag utilization after 240 h. Given its high capacity and availability, we evaluated the feasibility of Ag 2 S as an I 2 adsorbent in future applications. Finally, several drawbacks need to be overcome, including the relatively slow uptake rate, potential emission of another hazardous byproduct (SO 2 ), and potential aging effects (e.g., Ag 2 S conversion to Ag 2 SO 4 ) before Ag 2 S can be applied for the radioiodine capture process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analysis and design of fast flow liquid Li divertor for fusion nuclear science facility (FNSF) using coupled plasma boundary and LM MHD/heat transfer codes *

The SOLPS-ITER code is utilized to analyze the boundary plasma associated with a fast-flow lithium (Li) divertor configuration in the fusion nuclear science facility (FNSF) tokamak and identify operational regimes with acceptable divertor and core conditions. Plasma transport from the SOLPS-ITER code has been coupled with a liquid metal (LM) MHD/heat transfer code to model a Li open-surface divertor design and assess its impact on the scrape-off-layer (SOL) and core plasma performance. Simulations with only Neon (Ne) impurity seeding have been conducted to evaluate its impact on meeting FNSF design demands for the divertor and upstream plasma parameters. Simulation results indicate that Ne seeding significantly mitigates divertor heat flux but potentially reduces both upstream electron and main ion density due to fuel dilution. The combined application of Ne seeding and deuterium (D 2 ) puffing is required to satisfy the FNSF design requirements on upstream density ($n^{OMP}_{e,sep}$~1× 10 20 m -3 ) and divertor energy flux ($q^{Odiv}_{\bot,max}$<10 MW m -2 ). D 2 puffing plays a role in counteracting upstream density drops and augmenting energy and momentum losses through atomic and molecular processes. The inlet Li flow velocity is systematically varied across a wide range to identify acceptable flows and corresponding LM surface temperatures. This comprehensive analysis identifies the acceptable Li flow parameters, LM surface temperature, and emitted Li fluxes necessary to meet the major design constraints. The emitted Li fluxes exhibit minimal impact on the main plasma at surface temperatures up to approximately ~525 °C, corresponding emitted Li fluxes of up to φ Li ~2X10 23 atoms s -1 . Uncertainties in the Li emission processes from the surface are also investigated, primarily influencing Li loss in the lower surface temperature range (<525 °C), with simulation results indicating a minor impact on the divertor and upstream plasma. Conversely, evaporation predominantly drives the Li loss processes at higher surface temperature ranges (>525 °C), contaminating both the divertor and upstream plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Intra-canopy leaf trait variation facilitates high leaf area index and compensatory growth in a clonal woody encroaching shrub

Leaf trait variation enables plants to utilize large gradients of light availability that exist across canopies of high leaf area index (LAI), allowing for greater net carbon gain while reducing light availability for understory competitors. While these canopy dynamics are well understood in forest ecosystems, studies of canopy structure of woody shrubs in grasslands are lacking. To evaluate the investment strategy used by these shrubs, we investigated the vertical distribution of leaf traits and physiology across canopies of Cornus drummondii, the predominant woody encroaching shrub in the Kansas tallgrass prairie. We also examined the impact of disturbance by browsing and grazing on these factors. Our results reveal that leaf mass per area (LMA) and leaf nitrogen per area (Na) varied approximately threefold across canopies of C. drummondii, resulting in major differences in the physiological functioning of leaves. High LMA leaves had high photosynthetic capacity, while low LMA leaves had a novel strategy for maintaining light compensation points below ambient light levels. The vertical allocation of leaf traits in C. drummondii canopies was also modified in response to browsing, which increased light availability at deeper canopy depths. As a result, LMA and Na increased at lower canopy depths, leading to a greater photosynthetic capacity deeper in browsed canopies compared to control canopies. This response, along with increased light availability, facilitated greater photosynthesis and resource-use efficiency deeper in browsed canopies compared to control canopies. Furthermore, our results illustrate how C. drummondii facilitates high LAI canopies and a compensatory growth response to browsing—both of which are key factors contributing to the success of C. drummondii and other species responsible for grassland woody encroachment.

54 ENVIRONMENTAL SCIENCES↗

Field Evaluation of the High Efficiency Dehumidification System (HEDS) at the Timken Museum of Art - Summary of Measurement and Verification (M&V) Results from Summer 2023

The National Renewable Energy Laboratory (NREL) is performing a measurement and verification (M&V) assessment of the Conservant High Efficiency Dehumidification System (HEDS) at the Timken Museum of Art in San Diego, California. The HEDS was selected for evaluation by the U.S. Department of Energy (DOE) High Impact Technology Catalyst (HIT) evaluation program in 2022. This report documents recently completed analysis of data collected as an initial assessment of the HEDS system performance. Data was collected for the summer M&V during several weeks in August and September 2023 while operating the Timken Museum's HVAC system in several operating modes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Airports as Energy Nodes (ÆNodes) Project Report

Aviation is experiencing an influx of electrified aircraft in the advanced air mobility (AAM) space. The goal of Airports as Energy Nodes (ÆNodes) is to evaluate the impact of AAM and other advanced aircraft adoption growth on the electrical system of existing small to medium hub regional airports to better prepare them for the future while also enhancing resiliency and helping surrounding communities. AAM small passenger air service encompasses vertical takeoff and landing (VTOL), general aviation (GA) and flight training, and nine to thirty passenger conventional aircraft for regional air mobility (RAM) applications all of which include electrical, hybrid, or hydrogen powered varieties. Some challenges that ÆNodes is trying to address include how to utilize existing airport infrastructure to meet the energy needs of AAM growth in a way that is robust to aid in the growth of AAM while also leveraging any airport-hosted energy assets for the surrounding community in emergency situations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Policy and Regulatory Environment for Utility-Scale Energy Storage: India

This report is part of a series investigating the potential for utility-scale energy storage in South Asia. The first part of the work is focused on opportunities and barriers for energy storage within existing policy and regulatory frameworks in the region. This report applies the previously-developed Energy Storage Readiness Assessment to evaluate the policy and regulatory environment for energy storage in India. Forthcoming reports will expand this analysis to other countries in South Asia. These evaluations are designed to provide insights on the opportunities and barriers for energy storage growth and deployment in each country. The second part of this work consists of techno-economic analysis to understand the drivers of energy storage investments in South Asia. Using NREL’s power system planning and operational models of South Asia, this analysis will identify potential storage applications and growth under various cost, policy, and demand growth scenarios. In addition, the regulatory and policy barriers and incentive mechanisms identified in the first task will be incorporated into the modeling task to understand their impact on energy storage deployment and operation. Together these studies will inform the applications and value of energy storage on South Asia power systems and policy and regulatory pathways to realize this value.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Exploring the Potential of Rainwater Harvesting for Cooling Towers: A Systematic Review and Regional Feasibility Assessment

Water scarcity has driven interest in rainwater harvesting, especially for U.S. industries like power and manufacturing, which dedicate a large percentage of their water needs to cooling towers. This paper provides a comprehensive systematic review of studies on the use of rainwater in cooling tower applications, along with an assessment of the regional feasibility of integrating RWH in U.S. manufacturing cooling towers. The systematic review examines the technical, economic, environmental, and policy feasibility of utilizing harvested rainwater, and the regional feasibility analysis evaluates the practical implementation of RWH in manufacturing cooling towers, considering factors such as regional RWH potential, water costs, state policies, and the industrial water use of manufacturing facilities per state. This study supports the hypothesis that RWH for cooling towers is technically feasible, economically viable, and environmentally beneficial. Harvested rainwater is naturally less conductive and soft, and rainwater reuse minimizes the ecological footprint. Supportive state policies, regional RWH potential, and rising water costs across the U.S. are important variables that may impact RWH adoption. The review highlights rooftop RWH as the most studied method and notes that implementing RWH requires infrastructure changes and filtration techniques. While initial investment costs may be high, operational and maintenance costs are low, making RWHS economically feasible over time. Regions with higher water costs and supportive policies are more likely to benefit from RWH adoption. The study provides a foundation for understanding the potential for using RWH in industrial cooling towers.

Cooling towers↗

Metal additive manufacturing simulation across length, time, and computing scales

Metal additive manufacturing (AM) offers a unique opportunity for production of advanced materials and complex geometries. However, variability in microstructure and properties challenges conventional approaches to design, process optimization, qualification, and materials selection. Modeling and simulation can improve understanding of AM processing and materials, but also poses major challenges for existing computational methods. Simultaneously, modern scientific computing hardware has become increasingly complex, most notably with the adoption of hybrid architectures such as Graphical Processing Units (GPUs). If appropriately utilized, emerging computational capabilities provide an opportunity to reveal new insight into AM processing and the resulting material structure and properties. In this review we describe the computational AM landscape, identify critical gaps, and highlight opportunities to impact the development and application of AM. First, the requirements and challenges of representative AM problem statements will be defined. Here, these problems range from scientific studies to industrial applications and are designed to capture the breadth of challenges facing the AM community. Next, the current state of AM modeling and simulation is evaluated, broken down by enabling hardware and software, process simulation, microstructure simulation, and property simulation. Each section describes the diversity of simulation approaches and associated trade-offs in physical fidelity and computational expense. Each area is then assessed based on their suitability and readiness for current and developing computational architectures. Lastly, the greatest opportunities for future research and application are highlighted, including gaps in modeling capabilities, opportunities for near-term application, and key scientific challenges.

additive manufacturing↗

Measuring the Conditional Luminosity and Stellar Mass Functions of Galaxies by Combining the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys Data Release 9, Survey Validation 3, and Year 1 Data

In this investigation, we leverage the combination of the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 9, Survey Validation 3, and Year 1 data sets to estimate the conditional luminosity functions and conditional stellar mass functions (CLFs and CSMFs) of galaxies across various halo mass bins and redshift ranges. To support our analysis, we utilize a realistic DESI mock galaxy redshift survey (MGRS) generated from a high-resolution Jiutian simulation. An extended halo-based group finder is applied to both MGRS catalogs and DESI observation. By comparing the r- and z-band luminosity functions (LFs) and stellar mass functions (SMFs) derived using both photometric and spectroscopic data, we quantified the impact of photometric redshift (photo-z) errors on the galaxy LFs and SMFs, especially in the low-redshift bin at the low-luminosity/mass end. By conducting prior evaluations of the group finder using MGRS, we successfully obtain a set of CLF and CSMF measurements from observational data. We find that at low redshift, the faint-end slopes of CLFs and CSMFs below ~10 9 h –2 L ⊙ (or h –2 M ⊙ ) evince a compelling concordance with the subhalo mass functions. After correcting the cosmic variance effect of our local Universe following Chen et al., the faint-end slopes of the LFs/SMFs turn out to also be in good agreement with the slope of the halo mass function.

79 ASTRONOMY AND ASTROPHYSICS↗

EVALUATION OF HRA METHODOLOGIES FOR APPLICATION IN SDP WORK

This study critically evaluates human reliability analysis (HRA) methodologies applicable to regulatory probabilistic safety assessment (PSA) model, with a particular focus on their role in supporting the significance determination process (SDP) in nuclear safety assessment. Firstly, three widely utilized HRA methods – IDHEAS-ECA, SPAR-H, and ASEP/THERP – were qualitatively and quantitatively assessed. Qualitative assessments were conducted using attributes from the NEA/CSNI/R(2015)1 report, while quantitative evaluations employed regression and correlation analyses to compare predicted human error probabilities (HEPs) against empirical data. Results reveal distinct strengths, for example, IDHEAS-ECA’s robust predictive accuracy and K-HRA’s alignment with operational practices. In addition, dependency analysis and recovery analysis were critically evaluated. For dependency analysis, the methods’ handling of inter-task dependencies and their impact on HEPs were examined, while recovery analysis highlighted strategies for mitigating failure events. Furthermore, strategies were proposed to evaluate performance-shaping factors under conditions of reduced human performance, such as stress, fatigue, or cognitive overload, addressing specific challenges faced in SDP evaluations. Human errors from KINS’s operational performance information system event reports were evaluated as a case study. This study identifies gaps and provides actionable insights to ensure their validity and applicability in SDP HRA applications. This paper is a part of research conducted by KINS, and it should be noted that this result does not represent the regulatory position of KINS.

99 - GENERAL AND MISCELLANEOUS↗

One Year In: Tracking the Impacts of NEM 3.0 on California’s Residential Solar Market

On December 15, 2022, the California Public Utilities Commission passed an overhaul of the net metering program for the state’s investor-owned utilities. The changes replaced the long-standing net energy metering (NEM) tariffs with a net billing tariff (NBT) structure—colloquially known as “NEM 3.0”—which significantly reduces the compensation for behind-the-meter solar photovoltaic (PV) systems. The NEM tariffs remained open for new interconnection applications until April 15, 2023, but after that date, all new interconnection applications were submitted under NBT. Now, one year later, we have an opportunity to evaluate how the California solar market has evolved under this new compensation regime. As a precursor to its annual Tracking the Sun report, Berkeley Lab has released a short technical brief describing key trends in the California residential solar market since the roll-out of the new NBT structure. The purpose of this analysis is to provide empirical insights into how the market has evolved over the past year, confirming some expectations while also revealing several striking surprises.

14 SOLAR ENERGY↗

An agent-based approach to study the diffusion rate and the effect of policies on joint placement of photovoltaic panels and green roof under climate change uncertainty

As two of the highest trending green technologies, photovoltaic panels and green roofs are proven to be effective practices for energy generation and energy saving. The achievable impact from the widespread installation of such technologies is, however, not clearly established. This is mainly because the degree of this impact highly depends on the inherently uncertain environmental and climate factors, as well as the unknown adoption rates of these technologies, which in turn depend on different characteristics of decision makers and interactions among them. To that end, this study aims to investigate the diffusion rate of these green technologies under uncertainties caused by climate change, characteristics of adopters, and their interactions. An integrated framework is developed to capture the interplay between financial and attitudinal aspects, as well as the uncertainties due to both the stochastic nature of system parameters and the interactions among agents involving human beings. Specifically, this framework consists of a integer programming model to optimize the green roof and/or photovoltaic panel installation settings for a given building under climate change uncertainty, and an agent-based model to factor in the role of human behavior and interactions. A case study for the city of Knoxville, TN, is presented to evaluate the effects of different policies on the diffusion rate of the green technologies of interest. The results show that the affordability of green technologies and public awareness are the key drivers of the adoption of these technologies, which highlight the important role of the decision makers in impacting the diffusion rate.

14 SOLAR ENERGY↗

Comparative Techno-Economic Analysis of Available Feedstocks for High-Temperature Conversion: Whole Tree Thinnings and Mature Pine Residues

The TEA and LCA impacts of utilizing low-cost feedstocks in a high-temperature conversion process are of great interest. Here, we investigate the conversion cost impacts of two underutilized feedstocks from the commercial pine industry; 13-year-old whole trees, representing trees removed for the purpose of pre-commercial thinning, and 23-year-old pine residues, representing a waste stream produced from the deconstruction of mature trees for other purposes. Experimental fast pyrolysis data for each feedstock was used in tandem with results from supply and preprocessing analyses in order to evaluate the field-to-fuel economics. A low difference in MFSP was found between the conversion costs for the two feedstocks, with residues demonstrating a net benefit of $0.27/GGE compared to the whole tree thinnings, driven primarily by feedstock supply costs. This suggests that both whole tree thinnings and pine residues may be viable feedstock options for CFP conversion. Life cycle inventories were also generated for each case, enabling a field-to-fuel quantification of the cost and carbon cycle associated with each feedstock.

09 BIOMASS FUELS↗