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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 OSTI2026

Evaluation of Howard A. Hanson Dam Juvenile Fish Passage and Survival Study Live Fish Injury Assessment, Sensor Fish, and BioPA Modeling Tasks

The live fish injury assessment, Sensor Fish, and BioPA modeling study tasks were conducted by researchers from Pacific Northwest National Laboratory (PNNL). The four tasks were part of the larger Evaluation of Howard A. Hanson Dam (HAHD) Juvenile Fish Passage and Survival study, which had six total tasks. To achieve study objectives for each of the four tasks, field work occurred at Green Peter Dam (GPR) to evaluate the highest elevation steep slope bypass pipe, at HAHD to evaluate baseline conditions of the horseshoe tunnel, and at PNNL’s Aquatic Research Laboratory (ARL) to evaluate simulated dam passage conditions (i.e., shear forces and collision). Each of these evaluations utilized live fish injury assessment, Sensor Fish, and BioPA modeling. Live fish injury assessment and survival (tagged with and without balloon or passive integrated transponder [PIT] tags) was correlated with Sensor Fish to determine thresholds. The CFD analyses were then performed, and the computed values were compared to the corresponding measured values of Sensor Fish data. The results of the overall injury and survival of fish was also used in the validation of the CFD modeling method. Collectively, the results will aid in future modeling of fish passage at HAHD. Results from these tasks can be used by biologists, engineers, resource managers, and regional decision-makers to inform baseline conditions under current operations and the engineering design of the new FPF at HAHD. This draft report contains initial data and results from the four tasks. Table 8 1, Table 8 2, and Table 8 3, and Figure 8 1, Figure 8 2, and Figure 8 3 depict the CFD modeling findings for the GPR steep slope bypass, HAHD horseshoe tunnel, and laboratory testing. Table 8 4, Table 8 5, and Table 8 6 depict the Sensor Fish findings for the GPR steep slope bypass and HAHD horseshoe tunnel testing. The Mv values observed in the HAHD were significantly lower compared to the laboratory experiments conducted at PNNL. Currently, investigations are underway to understand the reasons for this disparity and to establish an appropriate threshold value for Mv. Survival predictions presented in the tables below should be considered preliminary and should not be used until further analyses and adjustments are completed. The next steps for modeling will include the flow regime, (i.e., density of flow regimes due to water and air mixing ) to continue to improve on the threshold value for Mv.

13 HYDRO ENERGY↗
DOE OSTI2022

Addressing Market Issues in Electrical Power Systems with Large Shares of Variable Renewable Energy

This paper reports recent findings from IEA Wind TCP Task 25, which compiles international experiences and research related to large-scale integration of wind and other renewable energy. In the paper, we address the main challenges for market integration of variable renewable energy, relating to price formation, cost recovery, balancing and other grid services. The paper gives an overview of recent scenario studies on electricity price impacts of (1) various generation, energy storage and demand types in different markets, and (2) different market designs and energy/climate policies. Studying markets with very high shares of variable renewable energy requires an improved set of analysis tools for forecasting market outcomes, estimating flexibility needs and sources, and assessing resource adequacy. Key market features need to be investigated within these improved analytical capabilities for systems transitioning to high shares of variable renewable energy, storage and flexible demand. System services that can be supported by markets will likely need to be revisited. Finally, this paper identifies open questions and suggested future market design work for supporting systems with very high shares of variable renewable energy, which are to be addressed in follow-up work of Task 25 collaborative research.

cost recovery↗
DOE OSTI2018

Initial Site-Specific Studies for Removing SNF from Six Shutdown Sites - 18042

The US Department of Energy (DOE) is exploring options for developing a large-scale transportation system for the safe transport of spent nuclear fuel (SNF) and high-level radioactive waste to future storage or disposal facilities. This complex, large-scale transportation system will involve coordinated, integrated activities. Interfaces with various transportation and non-transportation activities must be defined, and systems must be developed to ensure successful integration when the system becomes operational. To provide an understanding of the tasks and interfaces required for the complete de-inventory of particular sites where SNF is stored, DOE solicited bids from integrating contractors to develop initial site-specific de-inventory reports. The reports were developed for several nuclear power plant sites selected to represent a range of geographic locations, existing on-site SNF storage systems, and expected transportation modal options. Each report is presented in a self-contained narrative describing a potential campaign for removing all SNF and greater-than-class-C low-level radioactive waste (GTCC waste) from each specified site. Each study narrative includes site information; an analysis of the near-site transportation infrastructure; a concept of operations for the de-inventory; an estimated budget and schedule for the duration of operations; and a safety and security plan with site-specific considerations, emergency response considerations, and recommendations for the next steps DOE could take to de-inventory the site. The reports provide cost estimates for analytical purposes only; they do not attempt to specify the party or parties responsible for the costs. These reports present a first look at how an integrating contractor might recommend removing SNF from particular sites. They are written from the perspective of the contractor and do not represent DOE's plans. At this writing, six sites have been studied: - Connecticut Yankee, - Big Rock Point, - Humboldt Bay, - Maine Yankee, - Trojan, - Kewaunee. DOE may develop de-inventory reports for all reactor sites, with an initial focus on shutdown reactor sites. The order in which sites have been selected for study should not be considered an indicator of the order used by DOE to remove SNF from the sites. Since the SNF's destination is not important for the purpose of this work, DOE tasked the contractor with planning transportation of the SNF from the site to a generic railroad location in the approximate geographical center of the United States. These reports represent an initial study of the specific sites. Per the terms of the contract, the contractor was not permitted to engage in dialogue with power plant site personnel; near-site railroad personnel; or any local, state, or regional stakeholders about the studies. DOE provided site-specific data. The contractor was tasked to rely on past corporate experience, data available from DOE, and publicly available data when making site-specific recommendations for removing all SNF from each site. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

DECOVALEX-2023: Task C Final Report

The Full-scale Emplacement (FE) heater experiment at the Mont Terri Underground Rock Laboratory (URL) was designed and conducted by Nagra to replicate an emplacement tunnel of Nagra’s reference repository design at 1:1 scale. Alongside testing the technical feasibility of constructing disposal tunnels, emplacing waste containers in the tunnels and then backfilling them, the main goals of the FE experiment are (1) to obtain a better understanding of the coupled effects of induced thermo-hydro-mechanical (THM) processes that may occur and (2) to validate existing coupled THM models (Müller et al., 2017). A key aspect of ensuring safety for repositories located in low-permeability rock involves minimizing any damage to the rock itself, thereby preserving its integrity and promoting a stable environment Amongst a number of processes that could damage the rock is the increase in pore pressure due to thermal loading caused by heat emitted from the waste. To reduce the potential damage of the rock, it is important to analyse the evolution of heat over time due to the heat load of the containers and assess possible consequences by coupled THM models. The aim of Task C of DECOVALEX-2023 was to build 3D numerical models of the FE experiment, focussing in particular on the heating induced pore pressure change in the Opalinus Clay. Data from a large number of sensors were available from the FE experiment for model comparison. These sensors measured temperature and relative humidity in the bentonite around the heaters, and temperature, pressure and displacement/strain in the surrounding Opalinus clay. Data were available from the start of excavation (April 2012) up to August 2020 for most sensors (more than 5 years from the start of heating in December 2014). To fulfil the overall aim of the task, the work was broken down into a number of steps, starting with simpler models to build confidence in each team’s approach and then moving to more complex models that better represent the FE experiment. Step 0 consisted of 2D benchmark models, gradually increasing the number of processes that are represented from thermal (T) only models in Step 0a, to coupled thermal hydraulic (TH) models in Step 0b with a representation of changing porosity, to coupled thermo-hydro-mechanical (THM) models in Step 0c, where porosity changes are calculated by the mechanical model. A detailed specification of processes, parameters, initial and boundary conditions was provided for this step, with the ambition that all teams would work towards close agreement in their model results, thus building confidence in the model implementations. vi It was not straightforward to achieve agreement between the teams, so additional steps (Step 0b2, 0b3, 0c2, 0c3) were added along with derivation of some analytical solutions against which the models could be compared. The reasons for the differences between teams were investigated and found to be caused primarily by different conceptual model assumptions (including temperature dependence of the thermal expansion of water), different model formulations (including porosity evolution) and differences in modelled domain sizes, boundary conditions and grid discretisation. This demonstrates that comparisons between multiple modelling teams and/or comparison with analytical results and experimental data are highly beneficial in providing an indication of uncertainty in model predictions. At the conclusion of Step 0, almost all teams had achieved a close agreement in model results and those that had not achieved an agreement knew the reason for this. Step 1 moved from 2D models to 3D models of the FE experiment without adding technical features like shotcrete or EDZ, and only considering the heating phase. Initially the 3D model was tightly specified to continue to build confidence in the model implementations (Step 1a). The results of Step 1a were compared to the data from the FE-experiment without the teams seeing the data. The teams were then provided with a sub-set of the data from the FE-experiment and invited to consider how best to use the large dataset for model comparison (Step 1b). Teams were then asked to use the data provided to calibrate their models, only changing material property values rather than adding features or processes to their models (Step 1c). In Step 1, teams were asked to only model the heating phase of the experiment, so pressure in the Opalinus Clay was reported as change in pressure since the initial conditions were specified rather than modelled. The change from 2D to 3D models was accompanied by an increase in the dispersion of results between the teams. Some of this was resolved during the task, but some remained and is potentially due to model discretisation. Calibration of parameters was useful in improving the fit of the models to the data but the remaining differences indicated that the models were missing features or processes. In Step 2, the teams were asked to update their models with additional features and processes as well as calibrating parameters to try and improve the fit of the models to the data. Teams were encouraged to represent ventilation of the open FE tunnel prior to backfilling with heaters and bentonite and in Step 2, the absolute pressure in the Opalinus Clay was compared between the teams. Teams took different approaches, but there was consideration of adding shotcrete and an EDZ into the model, representing stress change during excavation and different approaches to modelling ventilation of the FE tunnel. Overall, the documented results showed a very good agreement for temperature. The results for porewater pressure evolution showed a significant improvement for most teams compared to Step 1c with a good agreement to the measurements for several teams whereas some teams overpredicted the pressure increase and others overpredicted the drainage effect especially for the sensors close to the heater. Step 3 was an opportunity for teams to use the models developed in Step 1 and Step 2 to make predictions about the temperature and pressure changes that will be expected at the FE experiment over the next few years in light of the planned changes in thermal output of the heaters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Monte Carlo simulations for water adsorption in porous materials: Best practices and new insights

Technologies based on water adsorption such as water harvesting from air have tremendous potential in mitigating important global crises such as water scarcity. An important challenge to the deployment of such technologies is finding optimal adsorbent materials. Given the large materials space of available adsorbents, large-scale computational screening can be extremely helpful for this task. This work explores the methods and details associated with such screening procedures and recommends best practices. We also shed light on the limitations of traditionally used and inexpensive to compute prescreening approaches involving geometric and energetic features to predict water adsorption behavior of porous materials. Such approaches can provide general trends to predict adsorption behavior but may lead to the overlook of potentially important structures due to the complex nature of water adsorption. Finally, this study offers insights for future water adsorption simulations to facilitate the development of optimal water adsorbents.

42 ENGINEERING↗
DOE OSTI2018

Excess lung cancer occurrence in poultry plants. Occupational risk factors: Findings for oncogenic viruses exposure and other occupational exposures

Highlights: • Exposure to poultry oncogenic virus was associated with increased lung cancer risk. • Exposure to chemical carcinogens was associated with increased lung cancer risk. • Each of these tobacco smoking-adjusted findings was independent of the other. Certain viruses naturally infect and cause cancer in chickens and turkeys. Humans are widely exposed. The viruses cause cancer in primates, and transform human cells in vitro, but it is not known if they cause cancer in humans, mainly because of the lack of epidemiologic evidence. We conducted cohort mortality studies of workers in poultry slaughtering/processing plants across the United States, because they have the highest human exposures. An excess of lung cancer and other deaths was recorded in the poultry workers. Here, we report on a case-cohort study of the lung cancer deaths nested within these cohorts, that was conducted to provide epidemiologic evidence linking these viruses with human cancer occurrence, while adjusting for possible confounders, including workplace chemical carcinogens. We obtained interviews for 339 lung cancer deaths and 457 controls, selected from our combined cohorts of 30,411 poultry plant workers and 16,405 non-poultry workers, belonging to United Food & Commercial Workers unions. Data was analyzed by both logistic regression and Cox regression, adjusting for smoking and other confounders. Lung cancer risk was independently associated with tasks or work areas indicative of exposure to both poultry oncogenic viruses and to workplace chemical carcinogens. The study provides an incremental piece of evidence (epidemiologic), indirectly linking the oncogenic viruses of poultry with the occurrence of cancer in humans, and thus may have public health implications, but the limitations highlighted must be considered. Confirmatory studies, particularly molecular studies providing definitive proof of poultry oncogenic retrovirus integration in human DNA are needed, before the findings observed in this study can be put into proper perspective.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Accelerating Multivariate Functional Approximation Computation with Domain Decomposition Techniques⋆

Modeling large datasets through Multivariate Functional Approximations (MFA) provide an elegant way to handle many visualization and scientific analysis workflows. The process necessitates scalable data partitioning methods to compute MFA representations efficiently without compromising the accuracy or continuity of the reconstructed solution. We propose a domain -decomposed method for computing the MFA with B -spline bases, which reduces the total work per task and uses a restricted Additive Schwarz (RAS) method to converge the control point data degrees -of -freedom along subdomain boundaries. We provide an in-depth analysis of the parallel approach with domain decomposition solvers, aiming to minimize local subdomain error residuals and recover high -order continuity at subdomain interfaces with appropriate choices of knot overlaps. The communication cost, determined by the overlap regions in the RAS implementation, is optimized to recover the numerical error profile of the single subdomain case. Our proposed method stands in contrast to previous methods, which typically only recover either C 0 or at best C 1 continuity for arbitrary B -spline degree expansions, or those that require post -processing to blend discontinuities in the reconstructed data. We demonstrate the effectiveness of our approach using analytical and real -world datasets in 1D, 2D, and 3D through both strong and weak scaling studies. The performance results indicate that the overall cost of computing the approximation is directly proportional to the underlying nearest -neighbor communication implementation, and is only weakly dependent on the overlap region size that determines the size of the messages. This finding underscores the efficiency and scalability of our proposed method, making it a promising solution for handling large datasets in scientific workflows.

additive Schwarz solvers↗
DOE OSTI2021

Uranium corrosion characterization by handheld laser-induced breakdown spectroscopy

In this study, a commercial-off-the-shelf handheld laser-induced breakdown spectroscopy system was modified, calibrated and tested for discrimination between uranium oxide and uranium hydride when assessing uranium corrosion products. Operating parameters, system modifications, and onboard data analysis were developed to accomplish the analytical task. This work represents the first laser-induced breakdown spectroscopy analysis of bulk uranium hydride, a pyrophoric material, within an inert glovebox. Finally, the work shown here illustrates a rapid identification technique for uranium corrosion types from pure UO 2 or U 3 O 8 to pure UH 3 .

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

International assessment of priority environmental issues for land-based and offshore wind energy development

Non-technical summary A substantial increase in wind energy deployment worldwide is required to help achieve international targets for decreasing global carbon emissions and limiting the impacts of climate change. In response to global concerns regarding the environmental effects of wind energy, the International Energy Agency Wind Technical Collaborative Program initiated Task 34 – Working Together to Resolve Environmental Effects of Wind Energy or WREN. As part of WREN, this study performed an international assessment with the global wind energy and environmental community to determine priority environmental issues over the next 5‒10 years and help support collaborative interactions among researchers, developers, regulators, and stakeholders. Technical summary A systematic assessment was performed using feedback from the international community to identify priority environmental issues for land-based and offshore wind energy development. Given the global nature of wind energy development, feedback was of interest from all countries where such development is underway or planned to help meet United Nations Intergovernmental Panel on Climate Change targets. The assessment prioritized environmental issues over the next 5–10 years associated with wind energy development and received a total of 294 responses from 28 countries. For land-based wind, the highest-ranked issues included turbine collision risk for volant species (birds and bats), cumulative effects on species and ecosystems, and indirect effects such as avoidance and displacement. For offshore wind, the highest-ranked issues included cumulative effects, turbine collision risk, underwater noise (e.g. marine mammals and fish), and displacement. Emerging considerations for these priorities include potential application to future technologies (e.g. larger turbines and floating turbines), new stressors and species in frontier regions, and cumulative effects for multiple projects at a regional scale. For both land-based and offshore wind, effectiveness of minimization measures (e.g. detection and deterrence technologies) and costs for monitoring, minimization, and mitigation were identified as overarching challenges. Social media summary Turbine collisions and cumulative effects among the international environmental priorities for wind energy development.

17 WIND ENERGY↗
DOE OSTI2024

Multi-level, forming and filament free, bulk switching trilayer RRAM for neuromorphic computing at the edge

CMOS-RRAM integration holds great promise for low energy and high throughput neuromorphic computing. However, most RRAM technologies relying on filamentary switching suffer from variations and noise, leading to computational accuracy loss, increased energy consumption, and overhead by expensive program and verify schemes. We developed a filament-free, bulk switching RRAM technology to address these challenges. We systematically engineered a trilayer metal-oxide stack and investigated the switching characteristics of RRAM with varying thicknesses and oxygen vacancy distributions to achieve reliable bulk switching without any filament formation. We demonstrated bulk switching at megaohm regime with high current nonlinearity, up to 100 levels without compliance current. We developed a neuromorphic compute-in-memory platform and showcased edge computing by implementing a spiking neural network for an autonomous navigation/racing task. Our work addresses challenges posed by existing RRAM technologies and paves the way for neuromorphic computing at the edge under strict size, weight, and power constraints.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Theoretical guarantees for permutation-equivariant quantum neural networks

Despite the great promise of quantum machine learning models, there are several challenges one must overcome before unlocking their full potential. For instance, models based on quantum neural networks (QNNs) can suffer from excessive local minima and barren plateaus in their training landscapes. Recently, the nascent field of geometric quantum machine learning (GQML) has emerged as a potential solution to some of those issues. The key insight of GQML is that one should design architectures, such as equivariant QNNs, encoding the symmetries of the problem at hand. Here, we focus on problems with permutation symmetry (i.e., symmetry group $S_n$), and show how to build $S_n$-equivariant QNNs We provide an analytical study of their performance, proving that they do not suffer from barren plateaus, quickly reach overparametrization, and generalize well from small amounts of data. To verify our results, we perform numerical simulations for a graph state classification task. Our work provides theoretical guarantees for equivariant QNNs, thus indicating the power and potential of GQML.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Anomalously enhanced ion transport and uptake in functionalized angstrom-scale two-dimensional channels

Emulating angstrom-scale dynamics of the highly selective biological ion channels is a challenging task. Recent work on angstrom-scale artificial channels has expanded our understanding of ion transport and uptake mechanisms under confinement. However, the role of chemical environment in such channels is still not well understood. Here, we report the anomalously enhanced transport and uptake of ions under confined MoS2-based channels that are ~five angstroms in size. The ion uptake preference in the MoS2-based channels can be changed by the selection of surface functional groups and ion uptake sequence due to the interplay between kinetic and thermodynamic factors that depend on whether the ions are mixed or not prior to uptake. Our work offers a holistic picture of ion transport in 2D confinement and highlights ion interplay in this regime.

2D channels↗
DOE OSTI2024

Transforming the bootstrap: using Transformers to compute scattering amplitudes in planar N = 4 Super Yang-Mills theory

Abstract We pursue the use of deep learning methods to improve state-of-the-art computations in theoretical high-energy physics. Planar N = 4 Super Yang-Mills theory is a close cousin to the theory that describes Higgs boson production at the Large Hadron Collider; its scattering amplitudes are large mathematical expressions containing integer coefficients. In this paper, we apply Transformers to predict these coefficients. The problem can be formulated in a language-like representation amenable to standard cross-entropy training objectives. We design two related experiments and show that the model achieves high accuracy (> 98%) on both tasks. Our work shows that Transformers can be applied successfully to problems in theoretical physics that require exact solutions.

Cai, Tianji (ORCID:0000000232359486)↗
DOE OSTI2021

TriGORank: A Gene Ontology Enriched Learning-to-Rank Framework for Trigenic Fitness Prediction

Machine learning (ML) has been gaining interest in the metabolic engineering community as a means to automate prediction tasks. In this work, we introduce and study the task of using ML to recommend high-fitness triplet mutants as candidates for wet-lab experiments. We first utilize individual fitness and digenic fitness scores as features and train machine learning models that produce a ranked list, from high to low fitness scores, for triplet gene mutants of S. cerevisiae. Then, we incorporate prior metabolic knowledge from an existing gene ontology, by designing a novel graph representation and deducing features that can capture gene similarity and gene interactions. Lastly, experimental results show that our proposed gene ontology enriched model, termed TriGORank, improves both performance and explainability.

Labhishetty, Sahiti↗
DOE OSTI2017

Initial Site-Specific De-Inventory Report for Kewaunee

This report has been developed to satisfy the Statement of Work for Task Order #3 for the Department of Energy (DOE) – Office of Nuclear Energy under contract number DE-NE0008491 issued to AREVA Federal Services (AFS). The purpose of this report is to assist the United States (U.S.) DOE in laying the groundwork for implementing an integrated nuclear waste management system. This includes preparing for future large-scale transport of Spent Nuclear Fuel (SNF), High-Level Radioactive Waste (HLW), and Greater Than Class C (GTCC) Low Level Radioactive Waste (LLW). This report addresses the tasks, equipment, and interfaces necessary for the complete de-inventory of the Kewaunee Power Station (KPS) independent spent fuel storage installation (ISFSI) site located in the town of Carlton, WI (but with a Kewaunee mailing address), approximately 30 miles southeast of Green Bay, WI and 90 miles north of Milwaukee, WI. As such, this report is intended to provide information useful for planning options within an integrated nuclear waste management system.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

PV Performance Modeling and Stakeholder Engagement (Q3 FY2020 Project Report)

The objectives of this project are as follows: 1. Reduce uncertainty in PV performance models by developing and validating new and improved models and submodes. 2. Create and manage an open source repository of modeling functions and data. 3. Build and grow the PV Performance Modeling Collaborative; and, 4. Represent the US in the IEA PVPS Task 13 Working group.

14 SOLAR ENERGY↗