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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Sustainable Campus with PEV and Microgrid

Market penetration of electric vehicles (EVs) is gaining momentum, as is the move towards increasingly distributed, clean and renewable electricity sources. EV charging shifts a significant portion of transportation energy use onto building electricity meters. Hence, integration strategies for energy-efficiency in buildings and transport sectors are of increasing importance. This paper focuses on a portion of that integration: the analysis of an optimal interaction of EVs with a building-serving transformer, and coupling it to a microgrid that includes PV, a fuel cell and a natural gas micro-turbine. The test-case is the Nanyang Technological University (NTU), Singapore campus. The system under study is the Laboratory of Clean Energy Research (LaCER) Lab that houses the award winning Microgrid Energy Management System (MG-EMS) project. The paper analyses three different case scenarios to estimate the number of EVs that can be supported by the building transformer serving LaCER. An approximation of the actual load data collected for the building into different time intervals is performed for a transformer loss of life (LOL) calculation. The additional EV loads that can be supported by the transformer with and without the microgrid are analyzed. The numbers of possible EVs that can be charged at any given time under the three scenarios are also determined. The possibility of using EV fleet at NTU campus to achieve demand response capability and intermittent PV output leveling through vehicle to grid (V2G) technology and building energy management systems is also explored.

Singh, Reshma↗
DOE OSTI2022

Assessment of nuclear data needs for advanced reactor demonstrations: application to the molten chloride reactor experiment (MCRE)

A number of advanced reactor concepts are planned for near-term demonstrations including micro-reactors, larger demonstrations and space nuclear systems. These reactor concepts are based on a wide variety of reactor technologies, including sodium, gas, and salt cooling. An overlooked area in the development and ultimate startup of these reactors is addressing nuclear data needs that allow confident prediction of the criticality, safety requirements, and operation of the reactors. In this paper we try to address the problem of assessing nuclear data needs and possible remedies to reduce the existing uncertainties for advanced nuclear reactors. A methodology for defining these needs is described. The case of the Molten Chloride Reactor Experiment (MCRE) has been considered and the related investigation highlights the specific needs for reducing uncertainty on the {sup 235}U capture and {sup 35}Cl (n,p) reactions. Relatively inexpensive integral experiments are indicated as possible solutions for significantly reducing the current associated uncertainties. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Evaluating offshore legacy wells for geologic carbon storage: A case study from the Galveston and Brazos areas in the Gulf of Mexico

In this article, federal offshore waters in the Gulf of Mexico are of interest for large-scale geologic carbon storage (GCS). However, more than 80,000 offshore oil and gas wells exist in the region, which could impact the integrity of sealing intervals. In this study, we propose a screening methodology for ranking offshore legacy wells based on the challenge they may present to GCS. The methodology relies on the review of well regulatory records to 1) identify leakage pathways and assess the potential hazards that wells pose to planned GCS operations, 2) evaluate well features that impact the accessibility of wells to determine the feasibility of potential corrective actions, and 3) rank wells based on the overall challenge they may pose for GCS. We demonstrate our framework by evaluating the construction and abandonment of 156 wells across eight areas of interest (AOIs) in shallow federal waters along the Texas Gulf Coast. The majority (99.3 %) of wells considered were constructed and plugged in a manner that did not isolate prospective GCS targets in the Upper and Lower Miocene formations and may potentially require a challenging or uncertain corrective action prior to GCS. Dataset trends suggest that the observed well construction and plugging designs may be common in shallow offshore federal waters along the Texas Gulf Coast. Consequently, operators pursuing offshore GCS projects in the region may consider selecting areas that avoid challenging wells or performing robust evaluations of legacy well leakage risks to plan corrective action prior to CO 2 injection.

58 GEOSCIENCES↗
DOE OSTI2025

Apomixis in Farmers’ Fields: Overview, Case Studies from Forage Grasses and Considerations for Future Apomictic Crops

Apomixis occurs naturally in several commercially important species from diverse plant families. While in some of these species apomixis is yet to be exploited in breeding schemes aimed at fixing heterosis, genetic progress and cultivar development, in other species apomixis has been integrated at different stages of breeding. Some of the most relevant examples come from the subfamily Panicoideae, the second largest subfamily of the Poaceae, and are the main focus of this review. The subfamily encompasses many tropical and sub-tropical grasses and grains of worldwide economic importance. Apomictic tropical forages are prime examples of how apomixis can be used and exploited in the development of marketable cultivars, which are essential to the meat and milk production industries globally. The main commercial forages used as grass pastures covering millions of hectares in tropical and sub-tropical regions are polyploids exhibiting gametophytic apomixis that belong to the genus Urochloa spp. (brachiariagrasses) and to the species Megathyrsus maximus (guineagrass). Buffel grass (Cenchrus ciliaris) and Paspalum spp. are other important apomictic forages bred and used in these regions. Breeding involves large germplasm collections from the centers of origin of the species, and for most of them, sexually reproducing diploid plants have been found. Chromosomically duplicated plants that maintain sexual reproduction are used in crosses with apomictic genotypes for the development and selection of cultivars to be marketed or used as progenitors in subsequent breeding cycles. The peculiarities of each genus/species breeding programs, the cultivars obtained from these programs, and the impact of use of marker assisted selection in cultivar development are presented. In addition, the test or implementation of new technologies such as high throughput phenotyping, and the use of machine learning methods for trait prediction and genomic selection are positively impacting the selection and speed of development of new polyploid apomictic cultivars. Furthermore, genetic transformation techniques, including genome editing, provide an additional layer for design of tailor-made, customer-oriented cultivars.

Cenchrus↗
DOE OSTI2024

Economically Viable Intermediate to Long Duration Hydrogen Energy Storage Solutions for Fossil Fueled Assets

This report was prepared as an account of work sponsored by the Office of Fossil Energy and Carbon Management of U.S. Department of Energy under Funding Opportunity Announcement Number DE-FOA-0002332 “Energy Storage for Fossil Power Generation”. The work aimed to explore and advance an innovative hydrogen energy storage system – the synergistically integrated hydrogen energy storage system (SIHES) – that has the following characteristics: • Compatible with existing or new coal and gas fuel electricity generation units, • best suited for intermediate to long duration energy storage, from 12 hours to weeks even months, and • capable of storing energy at the utility scale – hundreds of MWh to GWh energy storage with power output level in tens to hundreds of MW. Preliminary front-end engineering design (Pre-FEED) studies was carried out to develop and refine a site-specific SIHES as peaking power generation units (so named as HyPeaker) as the first market entry point, to demonstrate both the technical feasibility and the economic viability to integrate the HyPeaker “within the fence” of a fossil power plant. This specific site was TVA’s Johnsonville Combustion Turbine Plant. The HyPeaker was designed and engineered to integrate with a 60MW aeroderivative gas turbine unit already available at TVA’s Johnsonville site. This site-specific HyPeaker consists of an alkaline electrolyzer to produce hydrogen from CO 2 free electricity sources, an innovative low-cost high-pressure hydrogen storage system (Big-Ton) and the aero gas turbine to generate electricity using blend of hydrogen and natural gas. A holistic system level technoeconomic analysis tool specific to HyPeaker was developed to optimize the engineering design of the Johnsonville site-specific HyPeaker for cost and performance. The optimal design and specification of the Johnsonville site-specific HyPeaker are the following: • Alkaline electrolyzer: 3MW • Big-Ton storage vessel: 11,000kg H 2 at 3000psi. • 4-stage diaphragm hydrogen compressor: 55kg-H 2 /hr from 150psi to 3000psi. The HyPeaker is designed to provide sufficient hydrogen for 90% continuous operation of the HyPeaker. All major components have design life of 30 years. The capex of HyPeaker is estimated at $\$$7.1M. This included $\$$1.5M for the electrolyzer, $\$$5.6M for the storage vessel and compressor. The cost of aero gas turbine was included as it is already available at the site. Key findings are: • HyPeaker can be designed, manufactured, installed and integrated with the fossil power plants, with sub-systems and components commercially available on the market today, even when it is scaled up to an order of magnitude larger than the one at the Johnsonville site. HyPeaker is a technologically viable solution to cover a wide range of energy storage duration needs, from daily peaking operation to seasonal shifting for fossil fueled assets. • The cost advantage of SCCV based Big-Ton H 2 storage vessel made it possible to “oversize” the H 2 storage subsystem to achieve overall system level cost optimization. The benefits are two-fold. First, it allows to significantly reduce the capacity and cost of electrolyzer by spreading H 2 production over a much longer period of time when the fuel cost for electricity production is low. Second, it allows to balance the hydrogen production and usage shift over weeks to months to meet the peak demands. As such, the capital cost of HyPeaker system using the Big-Ton was less than half of the cost of a system with today’s steel tube based H 2 storage system. The HyPeaker has even better cost advantage Li-ion battery based energy storage system. The estimated capital cost of Li-Ion battery system would be at $\$$38M, under the same projected 20-year electricity generation profile of the Johnsonville site. This is over 5 times more expensive than the HyPeaker system. • Since industry scale energy storage systems do not have 100% energy conversion and storage efficiency, energy storage systems using fossil fuel generated electricity would increase the CO 2 emission. This is particularly the case for HyPeaker due to its low round trip efficiency. Therefore, a more sensible solution would be to the excessive or curtailed electricity from CO 2 emission free sources such as solar farms, wind farms or nuclear power plants, to produce hydrogen, and integrate them with the HyPeaker. Electricity from TVA’s nuclear power plants was used for the Johnsonville HyPeaker. • The economic viability of HyPeaker is expected to be further improved when global supply chains are taken into consideration. For the same Johnsonville site specific HyPeaker, the capex would be reduced to ~$\$$3.6M from ~$\$$7.1M, and the added LCOE is reduced to ~$\$$85/MWh. With the bipartisan Infrastructure Investment and Jobs Act, the cost of domestically produced HyPeaker sub-systems would be at the level of today’s global suppliers. Since the peaking units generally operate at peak usage period, thereby demanding higher price, the projected $\$$85/MWh LCOE would be within the realm of financial viability for utility operators.

08 HYDROGEN↗
DOE OSTI2024

Prognostic model and failure mechanisms of steam generators in Sodium-Cooled fast reactors

This paper presents a prognostic model for sodium-cooled fast reactor (SFR) steam generators (SGs). Here, the purpose of the model is to estimate the remaining useful life of SFR SGs and thus to support the decision-making of autonomous control. SFR SGs are of great interest for plant integrity due to their harsh operation environment. They operate at higher temperatures and higher coolant-to-steam pressure differences than those of current light water reactors (LWR). The severity of the SFR SG failure consequences, which include water-sodium contact, is another reason. Understanding its failure mechanisms is important for the development of its prognostic model. Based on our literature review and physics-based analysis, we concluded that creep would be a dominant degradation mode of SFR SGs due to SFR’s high-temperature and high-pressure environment. Thus, creep is the focus of the prognostic model. Various other failure modes were also investigated in this study. The mechanical fatigue due to flow-induced vibration is usually observed in early developmental phases and would not be an important issue during normal operation. The thermal fatigue due to thermal stripping is occasionally observed in other components in SFRs but does not affect SG integrity. Pure water stress corrosive crack, fretting, and so on are commonly observed in LWR SGs but are significantly less important in SFR SGs because of the high temperatures, high pressure differences, and chemical properties of liquid sodium. Based on these investigations, a prognostic model focusing on creep failures was developed. It estimates the failure probability profile by sampling the Larson-Miller parameter (LMP) and temperature and associated uncertainties through Monte Carlo methods. Two case studies were presented. The first one demonstrated the model’s capability to calculate the failure probability for a new specimen within a given time. If the tube is working under temperatures of 500C ± 3 and pressures of 15.2 MPa, which leads to LMP of 20,100 ± 50, the failure probabilities within 50, 70, and 90 years are approximately 0.1 %, 3.2 %, and 17.5 %. The second demonstrated how adjusting the workload can help to protect the integrity of the component. For an old tube reaching 99 % of its lifespan, continuing to run at temperatures of 500C ± 3 and LMP of 20,100 ± 50 leads to a failure probability of about 29.0 % within a year. If the temperature is reduced by 5C, the failure probability can be reduced to 2.5 %, and, if the pressure is also reduced such that the LMP is increased by 100, the failure probability can further be reduced to 0.12 %.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Seismic response of vertical dry storage casks under three-dimensional earthquake motions

Ensuring the long-term seismic safety of dry storage casks (DSCs) is becoming increasingly critical as these systems evolve from temporary to de facto permanent repositories for spent nuclear fuels. Traditional seismic soil–structure interaction (SSI) assessment methods use one-dimensional deconvolution or simplified boundary conditions to model incident waves. Although computationally appealing, simplifying assumptions may alter the seismic risk by neglecting the full complexity of three-dimensional (3D) wave propagation effects. To address this challenge, this paper introduces a novel high-fidelity computational framework that leverages the Domain Reduction Method (DRM) with perfectly matched layers (PML) to accurately transfer complex, 3D seismic wavefields from regional-scale fault-rupture simulations into local-scale finite element models of DSCs. Using broadband, physics-based ground motions from a generic M w 7.0 strike-slip event, both single-cask and multi-cask configurations were investigated under near- and far-field conditions. Emphasis is placed on capturing complex SSI, spatial variability in the ground motion, and nonlinear phenomena such as cask rocking and sliding. Numerical results demonstrate that near-field conditions, where forward directivity and fling-step effects dominate, lead to significantly higher DSC rocking and sliding. Far-field cases, by contrast, generally exhibit modest responses. Incorporating SSI tends to amplify or alter DSC response spectra and introduce response variability, which underscores the need for site-specific evaluations and robust modeling approaches to ensure the seismic integrity of DSCs in interim spent fuel storage installations.

Das, Tonmoy↗
DOE OSTI2025

Developing machine learning for heterogeneous catalysis with experimental and computational data

Machine learning techniques have emerged as a useful tool for identifying complex patterns and correlations in large datasets, such as associating catalyst performance to its physicochemical properties. In the heterogeneous catalysis communities, machine learning models have mostly been developed using high-throughput quantum chemistry calculations, with only a few case studies resulting in experimentally validated catalyst improvements. This limited success may be due to the use of simplified catalyst structures in computational studies and the lack of comprehensive experimental datasets. In this Review, we bring together studies integrating high-throughput approaches and machine learning for the advancement of solid heterogeneous catalysis, leveraging both experimental and computational data. We systematically analyze trends in the field, based on the descriptors used as model input and output; the materials, devices, or reactions investigated; the dataset size; and the overall achievements. Furthermore, for models reporting unitless R 2 values, we compare the performances based on these mentioned trends.

Computational chemistry↗
DOE OSTI2020

ddcMD: A fully GPU-accelerated molecular dynamics program for the Martini force field

We have implemented the Martini force field within Lawrence Livermore National Laboratory’s molecular dynamics program, ddcMD. The program is extended to a heterogeneous programming model so that it can exploit graphics processing unit (GPU) accelerators. In addition to the Martini force field being ported to the GPU, the entire integration step, including thermostat, barostat, and constraint solver, is ported as well, which speeds up the simulations to 278-fold using one GPU vs one central processing unit (CPU) core. A benchmark study is performed with several test cases, comparing ddcMD and GROMACS Martini simulations. The average performance of ddcMD for a protein–lipid simulation system of 136k particles achieves 1.04 µs/day on one NVIDIA V100 GPU and aggregates 6.19 µs/day on one Summit node with six GPUs. The GPU implementation in ddcMD offloads all computations to the GPU and only requires one CPU core per simulation to manage the inputs and outputs, freeing up remaining CPU resources on the compute node for alternative tasks often required in complex simulation campaigns.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Phase-field modeling of stored-energy-driven grain growth with intra-granular variation in dislocation density

Abstract We present a phase-field (PF) model to simulate the microstructure evolution occurring in polycrystalline materials with a variation in the intra-granular dislocation density. The model accounts for two mechanisms that lead to the grain boundary migration: the driving force due to capillarity and that due to the stored energy arising from a spatially varying dislocation density. In addition to the order parameters that distinguish regions occupied by different grains, we introduce dislocation density fields that describe spatial variation of the dislocation density. We assume that the dislocation density decays as a function of the distance the grain boundary has migrated. To demonstrate and parameterize the model, we simulate microstructure evolution in two dimensions, for which the initial microstructure is based on real-time experimental data. Additionally, we applied the model to study the effect of a cyclic heat treatment (CHT) on the microstructure evolution. Specifically, we simulated stored-energy-driven grain growth during three thermal cycles, as well as grain growth without stored energy that serves as a baseline for comparison. We showed that the microstructure evolution proceeded much faster when the stored energy was considered. A non-self-similar evolution was observed in this case, while a nearly self-similar evolution was found when the microstructure evolution is driven solely by capillarity. These results suggest a possible mechanism for the initiation of abnormal grain growth during CHT. Finally, we demonstrate an integrated experimental-computational workflow that utilizes the experimental measurements to inform the PF model and its parameterization, which provides a foundation for the development of future simulation tools capable of quantitative prediction of microstructure evolution during non-isothermal heat treatment.

Materials Science↗
DOE OSTI2025

Finite-volume formalism for physical processes with an electroweak loop integral

This study investigates finite-volume effects in physical processes that involve the combination of long-range hadronic matrix elements with electroweak loop integrals. We adopt the approach of implementing the electroweak part as the infinite-volume version, which is denoted as the EW ∞ method in this work. A general approach is established for correcting finite-volume effects in cases where the hadronic intermediate states are dominated by either a single particle or two particles. For the single-particle case, this work derives the infinite volume reconstruction method from a new perspective. For the two-particle case, we provide the correction formulas for power-law finite-volume effects and unphysical terms with exponentially divergent time dependence. The finite-volume formalism developed in this study has broad applications, including the QED corrections in various processes and the two-photon exchange contribution in 𝐾 𝐿 → 𝜇 + ⁢𝜇 − or 𝜂 → 𝜇 + ⁢𝜇 − decays.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Stability and Convergence of Solutions to Stochastic Inverse Problems Using Approximate Probability Densities

Data-consistent inversion is designed to solve a class of stochastic inverse problems where the solution is a pullback of a probability measure specified on the outputs of a quantities of interest (QoI) map. Here, this work presents stability and convergence results for the case where finite QoI data result in an approximation of the solution as a density. Given their popularity in the literature, separate results are proven for three different approaches to measuring discrepancies between probability measures: f-divergences, integral probability metrics, and L p metrics. In the context of integral probability metrics, we also introduce a pullback probability metric that is well-suited for data-consistent inversion. This fills a theoretical gap in the convergence and stability results for data-consistent inversion that have mostly focused on convergence of solutions associated with approximate maps. Numerical results are included to illustrate key theoretical results with intuitive and reproducible test problems that include a demonstration of convergence in the measure-theoretic "almost" sense.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A Data-driven Phytotechnology Framework for Identification and Remediation of Leached-Metals-Contaminated Soil Near Coal Ash Impoundments

This project developed and evaluated advanced remote sensing and machine learning approaches to identify, monitor, and address environmental contamination associated with coal combustion residual (CCR) impoundments and landfills at coal-fired power plants. In Phase I, historical and multi-temporal Sentinel-2 satellite imagery, groundwater monitoring data, and environmental variables were integrated to detect vegetation stress potentially caused by toxic metal leaching from coal ash disposal sites. Multiple vegetation and biophysical indices were analyzed to determine their effectiveness in identifying abnormal vegetation growth patterns linked to contamination. Results from case studies conducted at coal ash–impacted power plant sites in North Carolina and Virginia demonstrated that satellite-based vegetation monitoring can serve as an effective early indicator of environmental stress associated with metals such as arsenic, cadmium, cobalt, lead, lithium, radium, and thallium.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

Modeling the PV System Level Economic Impact of PV Connector Failure Modes

Photovoltaic (PV) connectors must maintain mechanical integrity for over 25 years while operating under UV exposure, elevated temperature, and mechanical loading. Connector degradation increases with electrical resistance, leading to energy losses, unplanned downtime, and higher operation and maintenance (O&M) costs and in severe cases, safety risks from overhearing or arcing. Connector related failures remain among the most frequent causes of disruption in utility-scale PV (UPV) systems, yet their lifetime economic impacts are poorly quantified. This work presents a techno-economic analysis (TEA) framework that links identified connector failure modes to system level energy losses and lifetime cost impacts using identified resistance measurements and failure rates from 6,2761 PV connectors inspected. Connector failures increase system level O&M costs, raising LCOE by roughly 5%. Downtime driven availability losses dominate economic impact. Resistance-driven I2R and IV-curve losses are secondary, but remain non-negligible. Thermal damage, bend-radius violations, and loose connections drive the majority of LCOE uplift Improving connector reliability through better installation quality, inspection, and design can meaningfully reduce lost energy, O&M costs, and LCOE.

14 SOLAR ENERGY↗
DOE OSTI2025

Greenhouse gas emissions reduction strategies that maximize portfolio-wide life cycle cost reduction, resilience, and environmental justice benefits

While strategies to achieve net-zero emissions at an individual site are well understood, new analysis methods are required for organizations seeking to achieve net-zero across multiple facilities, each with concurrent priority goals. At a portfolio level, distinct locations present varied challenges that cannot be addressed through singular solutions, and competing goals can take precedence with the assumption that net-zero emissions strategies deter from energy resilience and cost savings, therefore negatively impacting nearby communities. This study tests these assumptions by analyzing 16 diverse sites (varying in size, climate, and energy use) to identify strategies that reduce emissions and assess the impact these strategies have on life cycle costs, resilience, and communities with environmental justice concerns. Methods were developed to approximate missing information essential to net-zero evaluation. Established methods were augmented to evaluate life cycle costs, resilience, and environmental justice impacts across a set of strategies and accommodate the multi-criteria analyses. Potential benefits from identified strategies were quantified using site characteristics and a set of corresponding metrics. The net-zero analysis found that 11 sites could use on-site strategies to eliminate all but 2% of emissions generated. The remaining emissions can be offset, for instance through sequestration, executed at the portfolio scale. On-site carbon-free energy was found to reduce 51% of emissions across all sites; efficiency reduced 19% of emissions; sequestration 16%; procured carbon-free energy 15%; fuel switching 1.6%; and fleet electrification 1.3%. Building electrification, however, increased emissions by 4.4%. Different strategies also provide cost, resilience, and/or environmental justice benefits—the degree to which varies with individual site conditions. The findings indicate an advantage to considering the strategies as a comprehensive set, which leads to co-benefits, both in the ability to achieve net-zero goals and in advancing other goals. The results present the case for comprehensive advanced planning at the portfolio level to prioritize investments that will balance the minimization of emissions and life cycle cost with the maximization of resilience and environmental justice benefits. The novel methods for evaluation and integration, valuation of benefits, and consideration at the portfolio scale allow organizations to select investments that simultaneously address multiple key priorities.

Net-Zero Emissions↗
DOE OSTI2026

Integrated Transmission-Distribution Multi-Period Switching for Wildfire Risk Mitigation: Improving Speed and Scalability with Distributed Optimization: Preprint

With increasingly severe wildfire conditions driven by climate change, utilities must manage the risk of wildfire ignitions from electric power lines. During "public safety power shutoff'" events, utilities de-energize power lines to reduce wildfire ignition risk, which may result in load shedding. Distributed energy resources provide flexibility that can help support the system to reduce load shedding when lines are de-energized. We investigate a coordinated transmission-distribution optimization problem that balances wildfire risk mitigation and load shedding. We model distribution systems that include battery energy storage systems which may support loads when transmission lines are de-energized. This multi-period integrated transmission-distribution optimal switching problem jointly optimizes line switching decisions, the generators' setpoints, load shedding, and the batteries' states of charge, resulting in significant computational challenges. To improve scalability, we decompose the problem over both space and time and apply a distributed optimization algorithm. Using a large-scale synthetic California test case with realistic distribution models and real wildfire risk data, we show that distributed optimization can solve large-scale multi-period switching problems that are otherwise intractable for centralized solvers. We also discuss challenges and future directions for improving the distributed algorithm's convergence performance as the number of time periods increases.

24 POWER TRANSMISSION AND DISTRIBUTION↗