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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Remaining Life Prediction of SNF Storage Canisters Exposed to CISCC Environments

• DOE Standardized SNF Storage Canisters o DOE designed standard spent nuclear fuel (SNF) storage canisters for storage of DOE SNF. o DOE canisters are significantly different from commercial MultiPurpose Canisters (MPC) in size. o MPC canisters are large, a height = 15.8 ft, OD = 68”, WT = 0.5”. o DOE canisters are small with 18” / 24” diameter, 10’ / 15’ length. • Integrity Evaluation of DOE versus MPC Canisters o Many investigations have been performed for MPC canisters. o Limit investigations were performed for DOE standard canisters. Most were done at Idaho National Lab (INL). o DOE has sponsored integrity studies to evaluate weld integrity using drop tests and FEA simulations. o No evaluation on CISCC/service life of DOE canister in literature. o MPC canister: 4 axial welds, 1 center girth weld, 2 closing welds.

ZHU, Xiankui↗
DOE OSTI2023

NREL Planning Resources for States

This presentation summarizes some NREL resources and capabilities that states might want to access to help with decarbonization planning. It describes three types of resources: already-available, public datasets describing technology costs and future grid evolution; jurisdiction-specific integration studies that require directly partnering with NREL; and an envisioned new data product comprising state-specific standard scenarios that could be collaboratively funded by the states.

annual technology baseline↗
DOE OSTI2024

Improving the National Solar Radiation Database (NSRDB) Using a Physics-Based Direct Normal Irradiance (DNI) Model

The National Solar Radiation Database (NSRDB) is a widely used resource providing satellite-derived solar data across the United States and globally. While the NSRDB employs a physical model for computing global horizontal irradiance (GHI), its current method for estimating cloudy-sky direct normal irradiance (DNI) relies on surface observations and empirical models. Recently, a novel physics-based approach, the Fast All-Sky Radiation Model for Solar applications with DNI (FARMS-DNI), was developed to enhance the DNI forecasting. FARMS-DNI incorporates both direct and scattered solar radiation within the circumsolar region, resulting in improved day-ahead DNI predictions when integrated into the Weather Research and Forecasting model with Solar extensions (WRF-Solar). This study integrates FARMS-DNI into the NSRDB algorithm to generate high-resolution DNI data from satellite resources. Our findings reveal that FARMS-DNI effectively mitigates the substantial DNI overestimation present in the conventional NSRDB across surface sites, particularly in conditions categorized as cloudy overcast. Consequently, this innovative model substantially enhances the overall accuracy of the NSRDB.

Xie, Yu↗
DOE OSTI2024

Improving the National Solar Radiation Database (NSRDB) Using a Physics-Based Direct Normal Irradiance (DNI) Model: Preprint

The National Solar Radiation Database (NSRDB) is a widely used resource providing satellite-derived solar data across the United States and globally. While the NSRDB employs a physical model for computing global horizontal irradiance (GHI), its current method for estimating cloudy-sky direct normal irradiance (DNI) relies on surface observations and empirical models. Recently, a novel physics-based approach, the Fast All-Sky Radiation Model for Solar applications with DNI (FARMS-DNI), was developed to enhance the DNI forecasting. FARMS-DNI incorporates both direct and scattered solar radiation within the circumsolar region, resulting in improved day-ahead DNI predictions when integrated into the Weather Research and Forecasting model with Solar extensions (WRF-Solar). This study integrates FARMS-DNI into the NSRDB algorithm to generate high-resolution DNI data from satellite resources. Our findings reveal that FARMS-DNI effectively mitigates the substantial DNI overestimation present in the conventional NSRDB across surface sites, particularly in conditions categorized as cloudy overcast. Consequently, this innovative model substantially enhances the overall accuracy of the NSRDB.

DNI↗
DOE OSTI2023

Fine-scale evaluation of two standard 16S rRNA gene amplicon primer pairs for analysis of total prokaryotes and archaeal nitrifiers in differently managed soils

The advance of high-throughput molecular biology tools allows in-depth profiling of microbial communities in soils, which possess a high diversity of prokaryotic microorganisms. Amplicon-based sequencing of 16S rRNA genes is the most common approach to studying the richness and composition of soil prokaryotes. To reliably detect different taxonomic lineages of microorganisms in a single soil sample, an adequate pipeline including DNA isolation, primer selection, PCR amplification, library preparation, DNA sequencing, and bioinformatic post-processing is required. Besides DNA sequencing quality and depth, the selection of PCR primers and PCR amplification reactions arguably have the largest influence on the results. This study tested the performance and potential bias of two primer pairs, i.e., 515F (Parada)-806R (Apprill) and 515F (Parada)-926R (Quince) in the standard pipelines of 16S rRNA gene Illumina amplicon sequencing protocol developed by the Earth Microbiome Project (EMP), against shotgun metagenome-based 16S rRNA gene reads. The evaluation was conducted using five differently managed soils. We observed a higher richness of soil total prokaryotes by using reverse primer 806R compared to 926R, contradicting to in silico evaluation results. Both primer pairs revealed various degrees of taxon-specific bias compared to metagenome-derived 16S rRNA gene reads. Nonetheless, we found consistent patterns of microbial community variation associated with different land uses, irrespective of primers used. Total microbial communities, as well as ammonia oxidizing archaea (AOA), the predominant ammonia oxidizers in these soils, shifted along with increased soil pH due to agricultural management. In the unmanaged low pH plot abundance of AOA was dominated by the acid-tolerant NS-Gamma clade, whereas limed agricultural plots were dominated by neutral-alkaliphilic NS-Delta/NS-Alpha clades. This study stresses how primer selection influences community composition and highlights the importance of primer selection for comparative and integrative studies, and that conclusions must be drawn with caution if data from different sequencing pipelines are to be compared.

16S rRNA gene amplicon Illumina sequencing↗
DOE OSTI2022

Time-dependent THMC properties and microstructural evolution of damaged rocks in excavation damage zone

Modeling coupled thermo-hydro-mechanical-chemical (THMC) processes in host rocks near high-level nuclear waste (HLW) repositories at various time scales is an extremely challenging task. The current study integrates experimental, theoretical, and numerical methods in assessing the evolution of excavation damage zone (EDZ) over time and its implication on the long-term migration of hazardous species. Argillite and rock salt and are the focus of this study. The first part of the report presents a novel time-dependent directional microcrack damage theory for generic brittle rocks. It features detailed statistical description of the microcracks within a damaged solid, permitting a direct upscaling of microscale processes such as crack growth kinetics, crack closure/opening, sliding friction to explain the macroscopic creep, nonlinear elasticity, shear dilation, and loading-unloading hysteresis. This provides a basic platform for describing the anisotropic mechanical and transport properties of damaged rocks during excavation and subsequent THMC loadings. The model is validated and numerically implemented to Finite Element (FE) package ABAQUS through the user-defined material (UMAT) interface and have demonstrated great potential in resolving the time-dependent and anisotropic evolution of damage in the EDZ. The second part of the report presents a multi-scale experimental effort in characterizing the thermal, hydraulic, and mechanical properties of Mancos shale and Avery Island salt. For the Mancos shale, triaxial compression tests are performed at different confining pressures and temperatures to probe its thermomechanical properties relevant to HLW repositories. The obtained stress-strain data are interpreted using the proposed directional damage theory. Post-test specimens are subjected to gas permeability tests to reveal the correlation between permeability and the degree of microcracking. At microscale, temperature-controlled nanoindentation tests are performed and found a linear correlation between fracture toughness and elastic modulus from 25°C to 300°C. For Avery Island salt, we have designed and manufactured a novel relative-humidity controlled uniaxial creep device. Long-term creep tests at low stresses (< 5 MPa) are performed at different levels of relative humidity (RH). Besides confirming the much higher creep rates as one would expect through extrapolating the high-stress creep data, the results reveal that the steady-state creep rate of rock salt is strongly dependent on the ambient RH, an aspect that is often neglected in the literature. Both behaviors can be attributed to the pressure-solution creep mechanism which dominates at low stress and high RH levels. The third part of the report explores a set of numerical strategies in modeling the THMC behavior of porous geomaterials. A fully implicit, monolithic FE solution that can flexibly interface with different material models and coupling mechanisms for THMC problems is developed and verified through the ABAQUS user-defined element (UEL) interface. The scheme is used to study the THM response of a hypothetical HLW storage site with reference to an existing in-situ heater test. Strategies for integrating the UEL and the microcrack UMAT are suggested. Another numerical endeavor of this study is to implement a higher-order asymptotic homogenization method to account for the heterogeneous porous structures. The same method is then extended to perform microstructure-informed thermo-mechanical modeling of generalized continua. The above outcomes of this project provide a strong thrust towards enhancing the fundamental understanding and modeling capability of the long-term evolution of host rocks in EDZ, thus helping achieve the design goal of 1-million-year isolation of high-level nuclear wastes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Hybrid data-driven cement-stabilized soil design: An integration of machine learning, multi-objective optimization, and life cycle assessment

Soil stabilization is crucial in geotechnical engineering, yet conventional methods are often time-consuming, resource-intensive, and environmentally unsustainable. Despite growing interest in Machine Learning (ML) and optimization tools for mix design, few studies integrate these methods with decision-making techniques and environmental assessment to support practical implementation. This study proposes a hybrid data-driven framework for predicting strength, optimizing mix compositions, and evaluating environmental impacts via life cycle assessment of cement-stabilized soft soils. Six ML models were evaluated, and the top-performing eXtreme Gradient Boosting (XGB) model was further improved using the Grey Wolf Optimizer (GWO). The optimized XGB-GWO model, integrated with a polynomial cost function, served as the objective function in a multi-objective optimization problem solved via the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), with final mix selection guided by the entropy-weighted TOPSIS method. Validation through a case study produced mix designs offering superior strength-cost trade-offs, with the optimal mix achieving 2243.2 kPa unconfined compressive strength and a 16.07 % reduction in carbon emissions compared to the highest-cost design. In conclusion, this study offers a sustainable, scalable approach to soil stabilization and supports informed decision-making in construction.

Life cycle assessment↗
DOE OSTI2023

Integration of discrete-event dynamics and machining dynamics for machine tool: Modeling, analysis and algorithms

Machining dynamics research lays a solid foundation for machining operations by providing stable combinations of spindle speed and depth of cut. Furthermore, machine learning has been applied to predict tool life as a function of cutting speed. However, the existing research does not consider the discrete-event dynamics in machine shop, i.e., the machine tool needs to process a series of parts in queue under various practical production requirements. This paper addresses the integration of discrete-event dynamics and machining dynamics to achieve cost savings in machining. A learning-based cost function is first proposed for the studied integrated optimization problem of machine tool. The proposed cost function utilizes the predicted tool life under different stable cutting speeds for further optimizing speed selection of machine tool to deal with the discrete-event dynamics in machine shop. Then, according to the practical production requirements, effective mathematical optimization models are developed for the related integrated optimization problems with the consideration of cost, makespan and due date, respectively. Numerical results show the effectiveness of our proposed methods and also the potential to be used in practice.

Ma, Mason↗
DOE OSTI2023

Exploiting electricity market dynamics using flexible electrolysis units for retrofitting methanol synthesis

Here we investigate the economic viability of integrating flexible electrolysis units to produce hydrogen in methanol synthesis processes. Specifically, we investigate whether this approach can help reduce methanol production costs by strategically exploiting dynamics of electricity markets. Our study integrates high-fidelity process simulations, optimization tools, and microkinetic modeling (informed by density functional theory) to conduct detailed techno-economic analyses and to compare performance against traditional processes that use hydrogen produced via steam-methane reforming (SMR). We also use this approach to estimate the levelized cost of hydrogen (LCOH) as a function of time-varying electricity prices (from day-ahead and real-time prices) and of key techno-economic parameters. Our results show that the proposed electrification framework is cost-competitive under certain electricity market conditions. Specifically, we find that, when the electrolysis system is operated in flexible mode (and can respond to dynamics of electricity markets), the associated electricity cost nearly collapses to zero. Conversely, when the unit is not flexible (and cannot respond to markets), the electricity cost comprises 60% of the total cost. Our results also reveal that the LCOH of the flexible electrolysis system participating in real-time electricity markets is 31% lower than the LCOH obtained from SMR. Overall, this indicates that exploiting the dynamics of electricity markets can make hydrogen production cost-competitive and this can lead to viable alternatives to electrify methanol production and other hydrogen-based processes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Broad range material-to-system screening of metal–organic frameworks for hydrogen storage using machine learning

Hydrogen is pivotal in the transition to sustainable energy systems, playing major roles in power generation and industrial applications. Metal–organic frameworks (MOFs) have emerged as promising mediums for efficient hydrogen storage. However, identifying potential candidates for deployment is challenging due to the vast number of currently available synthesized MOFs. This study integrates molecular simulations, machine learning, and techno-economic analysis to evaluate the performance of MOFs across broad operation conditions for hydrogen storage applications. While previous screenings of MOF databases have predominantly emphasized high hydrogen capacities under cryogenic conditions, this study reveals that optimal temperatures and pressures for cost minimization depend on the raw price of the MOF. Specifically, when MOFs are priced at $15/kg, among the 9720 MOFs tested, 9692 MOFs achieve the lowest cost at temperatures between 170 K and 250 K and a pressure of 150 bar. Under these optimal conditions, 362 MOFs deliver a lower levelized cost of storage than 350 bar compressed gas hydrogen storage. Furthermore, this study reveals key material properties that result in low system cost, such as high surface areas (>3000 m2/g), large void fractions (>0.78), and large pore volumes (>1.1 cm3/g).

Hydrogen storage↗
DOE OSTI2023

Synchronous Wind: Evaluating the Grid Impact of Inverterless Grid-Forming Wind Power Plants: Preprint

Grid-forming (GFM) control of Type-3 and Type-4 wind turbine generators have attracted substantial attention in power system research. However, the limited over-current capability of power electronics converters continues to deteriorate the grid strength of the evolving power systems. This paper developed the generic model of synchronous wind power generators, also known as Type-5 wind turbines, for the power system integration studies. The Type-5 wind turbine interface to the grid through a synchronous generator; hence, its operation and consequent grid impacts are similar to a conventional power plant. Based on the developed model, a Type-5 wind power plant is integrated into IEEE 14-bus testbed to evaluate its control and operation with a bulk power system. Finally, the stability properties of Type-5 wind turbine generators are compared with Type-3 wind turbines in GFM control mode through impedance characterization.

grid strength↗
DOE OSTI2023

Synchronous Wind: Evaluating the Grid Impact of Inverterless Grid-Forming Wind Power Plants

Grid-forming (GFM) control of Type-3 and Type-4 wind turbine generators has attracted substantial attention in power systems research; however, the limited over-current capability of power electronics converters continues to deteriorate the grid strength of the evolving power systems. This paper develops the generic model of synchronous wind power generators, also known as Type-5 wind turbines, for power system integration studies. The Type-5 wind turbine interfaces with the electric grid through a synchronous generator; hence, its operation and consequent grid impacts are similar to a conventional power plant. Based on the developed model, a Type-5 wind power plant is integrated into the IEEE 14-bus test bed to evaluate its control and operation with a bulk power system. Finally, the stability properties of Type-5 wind turbine generators are compared with Type-3 wind turbines in GFM control mode through impedance characterization.

grid strength↗
DOE OSTI2025

Atmospheric methane consumption in arid ecosystems acts as a reverse chimney and is accelerated by plant-methanotroph biomes

Drylands cover one-third of the Earth’s surface and are one of the largest terrestrial sinks for methane. Understanding the structure–function interplay between members of arid biomes can provide critical insights into mechanisms of resilience toward anthropogenic and climate-change-driven environmental stressors—water scarcity, heatwaves, and increased atmospheric greenhouse gases. This study integrates in situ measurements with culture-independent and enrichment-based investigations of methane-consuming microbiomes inhabiting soil in the Anza-Borrego Desert, a model arid ecosystem in Southern California, United States. The atmospheric methane consumption ranged between 2.26 and 12.73 μmol m 2 h −1 , peaking during the daytime at vegetated sites. Metagenomic studies revealed similar soil-microbiome compositions at vegetated and unvegetated sites, with Methylocaldum being the major methanotrophic clade. Eighty-four metagenome-assembled genomes were recovered, six represented by methanotrophic bacteria (three Methylocaldum , two Methylobacter , and uncultivated Methylococcaceae ). The prevalence of copper-containing methane monooxygenases in metagenomic datasets suggests a diverse potential for methane oxidation in canonical methanotrophs and uncultivated Gammaproteobacteria. Five pure cultures of methanotrophic bacteria were obtained, including four Methylocaldum . Genomic analysis of Methylocaldum isolates and metagenome-assembled genomes revealed the presence of multiple stand-alone methane monooxygenase subunit C paralogs, which may have functions beyond methane oxidation. Furthermore, these methanotrophs have genetic signatures typically linked to symbiotic interactions with plants, including tryptophan synthesis and indole-3-acetic acid production. Based on in situ fluxes and soil microbiome compositions, we propose the existence of arid-soil reverse chimneys, an empowered methane sink represented by yet-to-be-defined cooperation between desert vegetation and methane-consuming microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Study on Electrostatic Separation of Quinoline Insolubles from Coal Tar Pitch

The feasibility of electrical separation in the removal of quinoline insoluble (QI) particles from coal tar pitch (CTP) was experimentally investigated. QI particle involvement prohibits the effective fabrication of high-quality value-added products, such as carbon fibers, from CTP. A substantial and sustainable CTP market exists around the world; therefore, a strong incentive exists to develop a viable technical approach to effectively and economically remove QI particles from CTP. The electrical separation method shows promise to achieve this technical goal (Cao et al., 2012). Even with the given setup (wire- cylinder adapted), critical issues remain to be addressed for this method to be applicable to the CTP: (1) identifying the wash oil used in the original QI separation, (2) understanding the mechanism of QI separation, (3) characterizing the deposit, and (4) identifying the QI. This study integrated a set of experimental and analysis techniques into the electrical separation tests to address the aforementioned issues. Key findings are as follows: 1. Electric current responses: • The electric current level of the CTP–wash oil solution reported by Cao et al. (2012) can be attained by using a mixture of 25% quinoline and 75% toluene for the CTPs examined in this study under the same electrical load condition. • The electric current tends to decrease during the test period because of the decreasing number of charged particles. • The reversed field corresponded to the configuration of electrostatic precipitation for positive corona discharge. The high electric field can result in dielectric breakdown and lead to an abrupt current surge. 2 Deposit response and solvent candidates: • Deposit of particles in CTP mixture can be effectively implemented in a wire-cylinder configuration as proposed and examined in this study. • Deposit depends on the solvents. Among the solvents tested, two- and three-part solvents that included quinoline and ethanol (i.e., 25% quinoline and 75% toluene; 50% quinoline and 50% toluene; and 33% wash oil, 33% BTX, and 34% ethanol) produced the highest deposit weight. • The deposit process examined in this study is derived from the charged particles. An appreciable relation exists between deposit weight and electric charge. 3. QI removal efficiency (RE): • The RE of the electrostatic separation can reach as high as 76.2% for Carbores, and 61.6% for Koppers. • The RE can be further enhanced if the field level increases from 0.16 kV/mm that was used in the current study to 0.23 kV/mm, according to the relation established between the RE and the electric field. 4. Testing of the modeling system: • The motion of particles is originally driven by the charge-based electric force in the cases tested. The solid particle separation mechanism is similar to that of QI deposition in CTP. • The mechanical movement of solid particles can be strongly affected by the gravitational and viscous forces in the electric field. 5. EDS analysis and chemical compositions: • The main chemical composition of deposit QI matches that of as-prepared CTP QI. The deposit QI is derived from the same group of the CTP QI. • In addition to carbon, the QI contains oxygen, sodium, aluminum, silicon, iron, and sulfur. The work for the near future is also discussed.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Energy Requirements for Integration of Nuclear Reactors with Iron and Steel Plants

This report identifies energy needs of heavy energy users within the domestic iron and steel industry and suggests solutions for integrating nuclear energy. The iron and steel industry, composed of several types of plants which perform different processes with varied energy demands and vectors, is a heavy consumer of electric power and fossil fuels including coke and natural gas. Almost all major process temperatures exceed the temperatures of direct heat available from advanced reactors, and so electricity and hydrogen were considered instead. Reference units were adopted and estimated energy demands computed for the blast furnace (BF), direct reduced iron (DRI) unit, electric arc furnace (EAF), and reheat furnaces. By utilizing production capacity data from industry reports, the ranges of power demands were estimated, including for hydrogen production by high temperature steam electrolysis (HTSE). For the EAF and DRI unit, more detailed integration studies with thermodynamic modeling were also conducted and determined a possible solution with a specific reactor design and number of modules. Furthermore, because many unit processes are co-located, entire plants were considered by adding the energy demands of the unit processes to form four hypothetical reference plants. The range of power needs for the reference plants is compatible with multi-unit banks of microreactors at the low end, and would create a need for multiple larger-capacity SMRs at the high end (1 GWe plus 0.14 GWt). Although the overall power need at the high end is well-matched with one present-day large reactor offering (1.1 GWe), redundancy considerations may require a minimum of two reactors, potentially eliminating the single large reactor from consideration. Auxiliary or house loads would increase the reference plant estimates. Finally, the report provides total estimated energy needs under integration of all U.S. units of each process (BF, DRI, EAF, and reheat furnaces), representing a national potential for nuclear energy in the industry. U.S. iron and steel plants may be candidates for integration with nuclear reactors via electricity and hydrogen, and many sites have energy requirements that correspond well to the capacities of several advanced nuclear power designs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Framework for assessment of magnetic equilibrium controller performance on the MAST upgrade spherical tokamak

Here, in this work we present the assessment framework for magnetic equilibrium controllers on MAST Upgrade spherical tokamak (MAST-U) spherical tokamak. Such controllers are essential for the MAST-U since exhaust physics and core-edge integration studies require advanced divertor plasma configurations. The developed framework is based on the TokSys suite of plasma control codes, which was adapted and upgraded for MAST-U. However, extra capabilities were added on top of TokSys to support the development of new control algorithms, deployment of controllers to the plasma control system (PCS) and evaluation of their performance. The controller assessment was realized via closed-loop integrated control simulations with the actual MAST-U PCS and different physics-based plasma models. Since all components of the assessment chain were experimentally validated, these simulations provide qualified controllers applicable for direct use in the experiment. This resulted in the successful experimental demonstration of advanced plasma shape control on MAST-U with minimal on-machine development time. A similar methodology would be beneficial to other tokamaks, both existing and future.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Rewiring the unfolded protein response for plant growth recovery after stress

The unfolded protein response (UPR) is a highly coordinated signaling network that alleviates endoplasmic reticulum (ER) stress, a condition induced by diverse environmental challenges in plants. Over the past two decades, substantial progress has been made in elucidating the genetic and molecular mechanisms of ER stress sensing and signal transduction in plants, largely through studies in the model plant Arabidopsis thaliana . These advances have established the UPR as a central regulator of proteostasis and underscored its broader relevance to plant growth and development and crop productivity under stress conditions. Despite this progress, critical knowledge gaps remain, particularly concerning the downstream biological processes required for growth recovery once ER stress has subsided and how these processes are coordinated by UPR regulators. Recent systems-level and integrative studies have begun to reveal critical roles of UPR signaling in pathways governing growth re-establishment and homeostasis of nutrient allocation and energy metabolism. In this review, we highlight recent findings on the functional roles of the plant UPR in recovery from ER stress, with a focus on mechanisms mediated by UPR regulators and downstream biological pathways that enable the transition from stress mitigation to growth restoration. Although this research area is still emerging, accumulating evidence supports a model in which the UPR functions as a dynamic regulatory network that actively coordinates post-stress physiological recovery to support plant fitness.

ER stress↗