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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Quantifying conditional probabilities of fish-turbine encounters and impacts

Tidal turbines are one source of marine renewable energy but development of tidal power is hampered by uncertainties in fish-turbine interaction impacts. Current knowledge gaps exist in efforts to quantify risks, as empirical data and modeling studies have characterized components of fish approach and interaction with turbines, but a comprehensive model that quantifies conditional occurrence probabilities of fish approaching and then interacting with a turbine in sequential steps is lacking. We combined empirical acoustic density measurements of Pacific herring ( Clupea pallasii ) and when data limited, published probabilities in an impact probability model that includes approach, entrainment, interactions, and avoidance of fish with axial or cross-flow tidal turbines. Interaction impacts include fish collisions with stationary turbine components, blade strikes by rotating blades, and/or a collision followed by a blade strike. Impact probabilities for collision followed by a blade strike were lowest with estimates ranging from 0.0000242 to 0.0678, and highest for blade strike ranging from 0.000261 to 0.40. Maximum probabilities occurred for a cross-flow turbine at night with no active or passive avoidance. Estimates were lowest when probabilities were conditional on sequential events, and when active and passive avoidance was included for an axial-flow turbine during the day. As expected, conditional probabilities were typically lower than analogous independent events and literature values. Estimating impact probabilities for Pacific herring in Admiralty Inlet, Washington, United States for two device types illustrates utilization of existing data and simultaneously identifies data gaps needed to fully calculate empirical-based probabilities for any site-species combination.

collision risk↗
DOE OSTI2025

High-Burnup BWR LOCA Burst Analysis Using High-Fidelity Multiphysics Simulations

The US nuclear industry is looking to improve on the operating economics of the current fleet of light-water reactors (LWRs). One way of achieving this is by operating fuel to higher burnup. In pressurized water reactors (PWRs), relaxing the current burnup limit will allow for cycle length extensions and power uprates; in boiling water reactors (BWRs) it may allow for improved fuel utilization and reduced feed assemblies, as well as more efficient power uprates and increased capacity factors that will support the Administration’s Executive Order to facilitate 5 GW of power uprates at existing nuclear facilities. However, one of the key limitations to operating fuel to higher burnup is the risk of fuel fragmentation, relocation, and dispersal (FFRD). Recognizing the high interest in extending burnup limits, the US Nuclear Regulatory Commission (NRC) has issued Draft Regulatory Guide DG-1434, which defines an approach that would be acceptable to the NRC for addressing FFRD risk. The approach defined will require better understanding of the phenomena leading to FFRD as well as best-estimate simulation methods to understand FFRD risk in high-burnup cores. The Nuclear Energy Advanced Modeling and Simulation program is supporting the FFRD industry challenge problem through development of state-of-the-art, high-fidelity modeling and simulation LWR analysis capabilities; namely, the BISON fuel performance code and the VERA core simulator software. These tools, along with the US NRC TRACE system analysis code, have been utilized for analysis of FFRD risk in both PWR and BWR cores in recent years. The work documented in this report addresses the lack of high-fidelity research for BWRs and builds on a previous activity where the framework has been applied to Cycles 16 through 18 of Limerick Unit 1, a BWR/4, with introduction of 8 high-burnup lead use assemblies (HBLUAs) that were representative of the 8 HBLUAs loaded into Limerick Unit 2 in 2021. VERA was used in this previous activity to model rod-by-rod depletion in these cycles, and its solution was used to initialize a TRACE simulation of a large-break loss-of-coolant accident (LBLOCA) at the end of Cycle 18. In the work documented in this report, the TRACE model was improved by refining the core mesh and utilizing a new feature that allows for capturing the full 3D VERA power distribution in the model. This allows for a more detailed solution for setting BISON boundary conditions. Furthermore, the solutions from VERA and TRACE were used to set up and perform BISON simulations of about 1,000 rods sampled from the core, including all burnup levels. Utilizing two cladding burst models, it was shown that no fuel rods were predicted to burst during the postulated LBLOCA transient. Additionally, a sensitivity study was performed by artificially increasing linear heat rate during the postulated LBLOCA to identify parameters that correlate with rod burst susceptibility. Burnup, fission gas release, and hoop strain were all found to be positively correlated with rod burst susceptibility. Small-break loss-of-coolant accident (SBLOCA) analyses were also performed; these analyses predicted cladding temperature increases that were bounded by the LBLOCA cladding temperatures for all small break sizes studied for this plant. However, future refinements to the plant response assumptions during the SBLOCA could impact the predicted cladding response. Finally, a benchmark study was performed between CTF and TRACE for LOCA conditions to better qualify CTF for BWR LOCA modeling.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Corrosion of 316 L stainless steel under the natural circulation of molten NaCl-MgCl 2 salt

The corrosion behavior of 316 L stainless steel (SS) was studied via the natural circulation of molten eutectic NaCl-MgCl 2 salt through a microloop. The post-corrosion tested 316 L SS microloop sections were characterized with microscopy techniques to determine the microstructural and microchemical changes that occurred at the alloy/salt interface. It was found that 316 L SS showed heterogeneous dissolution at the hot-leg, whereas deposition of corrosion products occurred at the cold-leg. For the first time, experimentally obtained molten salt flow-induced corrosion of 316 L SS results were combined with computational thermodynamic-kinetic models to validate the dissolution and deposition in terms of elemental compositional changes at the alloy/salt interface. The thermodynamic-kinetic modeling predicted that the heterogeneous dissolution of Cr and Fe from the hot-leg section of 316 L SS persisted throughout the salt circulation. The model also estimated that, despite Cr deposition starting earlier than Fe, the total redeposition of Fe is expected to be significantly greater than that of Cr over the circulation of salt. Furthermore, the modeling accurately predicted the subsurface enrichment of Mo which is attributed to the reduced Cr activity and the relatively higher diffusion rate of Mo within the alloy matrix. Here, the agreement between modeling and experimental results confirms that Fe chlorides dissolve at the hot-leg and subsequently deposit at the cold-leg due to activity changes driven by the thermal gradient. By contrast, Cr was not detected in the cold-leg deposits, which is attributed to its weaker temperature dependence on activity, limiting its redeposition under these conditions.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Catalytic hydrogenation of HMF to BHMF over copper catalysts

2,5-Bis(hydroxymethyl)furan (BHMF) is a bio-derived building block for polyester production, obtained via the hydrogenation of 5-hydroxymethylfurfural (HMF). First-principles thermodynamic equilibrium calculations indicate that this reaction is not thermodynamically limited under relevant conditions (e.g., 100 °C and high H 2 partial pressure). In this work, crude HMF was employed as the feedstock for BHMF synthesis. Initially, acidic impurities and humins were removed from unrefined HMF through filtration using a packed bed of γ-alumina. A comprehensive study of the filtration process is presented, including filtration kinetics, breakthrough curve analysis, and mathematical modeling. The purified HMF was subsequently hydrogenated over a 10 wt% CuZrO 2 catalyst, using ethanol as the reaction solvent. Batch reactions were first performed for collection of kinetic data to guide the transition to continuous flow operation. Kinetic data was collected in a fixed bed reactor at varying contact time, time on stream, temperature, and HMF concentration. This data was used to develop a kinetic model for HMF hydrogenation. Maximum BHMF production rates were achieved at 130 °C, accompanied by minor formation of byproducts from BHMF ring-opening reactions. The BHMF selectivity was 100 % at 100 °C although with lower reaction rates. Furthermore, catalyst stability tests revealed a loss of up to 50 % in catalytic activity within the first 24 h, likely due to the adsorption of HMF-derived oligomers that are not easily removed by filtration.

Crude HMF filtration↗
DOE OSTI2026

Searching for neutrino polarizability at DUNE

We perform an initial study of DUNE’s sensitivity to enhanced neutrino polarizability within models of light scalar mediators. We identify two possible signatures of polarizability due to neutrino scattering on electrons and due to coherent scattering on argon nuclei. These result in either one or two separated electromagnetic showers, respectively, with no associated hadronic activity. For each signature we compute the signal rates and the relevant backgrounds, obtaining the projected reach of the DUNE near detector. We then compare this with the current astrophysical and terrestrial bounds on light scalar models coupling to neutrinos and/or photons.

Carey, Sam [Wayne State U.] (ORCID:000900029607531↗
DOE OSTI2024

Modeling Europium (II/III) ion solvation in the LiCl-KCl eutectic mixture with polarizable force fields

Here, the solvation processes of Europium (II/III) ions within the molten salt eutectic mixture, 3LiCl-2KCl, are investigated over temperatures ranging from 673 K to 1173 K. New polarizable ion force fields are proposed to model Europium ions in a molten salt eutectic mixture with a goal of accurately capturing the underlying physics in the solutions. In contrast to rigid-ion models, the polarizable Drude model with an adjusted WBK (Wang-Buckingham) force field significantly improves predictions for diffusion coefficients, the average diffusion activation energy, and changes in excess ion chemical potential and partial molar entropy, producing good agreement with experimental measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Structure of the Sec14 domain of Kalirin reveals a distinct class of lipid-binding module in RhoGEFs

Gated entry of lipophilic ligands into the enclosed hydrophobic pocket in stand-alone Sec14 domain proteins often links lipid metabolism to membrane trafficking. Similar domains occur in multidomain mammalian proteins that activate small GTPases and regulate actin dynamics. The neuronal RhoGEF Kalirin, a central regulator of cytoskeletal dynamics, contains a Sec14 domain (Kal bSec14 ) followed by multiple spectrin-like repeats and catalytic domains. Previous studies demonstrated that Kalirin lacking its Sec14 domain fails to maintain cell morphology or dendritic spine length, yet whether and how Kal bSec14 interacts with lipids remain unknown. Here, we report the structural and biochemical characterization of Kal bSec14 . Kal bSec14 adopts a closed conformation, sealing off the canonical ligand entry site, and instead employs a surface groove to bind a limited set of lysophospholipids. The low-affinity interactions of Kal bSec14 with lysolipids are expected to serve as a general model for the regulation of Rho signaling by other Sec14-containing Rho activators.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Quantitative stable isotope probing (qSIP)-informed metagenomics identifies viruses infecting chemoautotrophs

Aquatic environments absorb ~2.5 gigatonnes of atmospheric carbon each year1, more than the carbon stored in the atmosphere, soils, and all biomass combined. Primary producers transform this dissolved inorganic carbon into biomass that can subsequently flow into other trophic levels, or be released back into the environment through viral lysis. While there is substantial knowledge about the diversity and activity of viruses infecting photoautotrophic primary producers and the ecosystem impact, little is known about viruses infecting chemoautotrophs, representing a gap in our understanding of key processes driving microbial carbon cycling. Here, we combine metagenomics with quantitative 12/13C stable isotopic probing (qSIP) mesocosm experiments in a marine-derived meromictic pond to quantify population-specific isotopic enrichment, identify key chemoautotrophic primary producers, and virus-host dynamics. Isotopically enriched carbon is tracked from the genomes of chemoautotrophs to putative viruses, showing that active populations of hydrogen/sulfur-oxidizing chemoautotrophs (Thiomicrorhabdus, Hydrogenovibrio, Sulfurimonas, Sulfurovum) are targeted by viruses. This work provides the foundation for revealing the diversity and activity of viruses infecting globally-widespread chemoautotrophs. Our study sheds light on trophic interactions that impact microbial carbon cycling in aphotic environments and builds toward biogeochemical models that incorporate viral impacts on chemoautotrophic microbial communities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

REDOTHERM (Redox Countercurrent Thermodynamic Limits Model) [SWR-24-88]

REDOTHERM is an open-source, MATLAB-based thermodynamic modeling framework developed to evaluate the performance of redox-active materials for water (H2O) and carbon dioxide (CO2) splitting. It includes models of all major unit operations and supports comparative analysis of different redox-active material candidates. The model is tailored for systems of moving oxide under a parallel/cocurrent flow (PF) and countercurrent flow (CF) configurations. Unvalidated mixed flow reactor (MFR, also known as CSTR) model is also included as an optional addition.

Lidor, Alon [National Renewable Energy Laboratory ↗
DOE OSTI2024

Machine Learning Accelerated First-Principles Study of the Hydrodeoxygenation of Propanoic Acid

The complex reaction network of catalytic biomass conversions often involves hundreds of surface intermediates and thousands of reaction steps, greatly hindering the rational design of metal catalysts for these conversions. Here, we present a framework of machine learning (ML)-accelerated first-principles studies for the hydrodeoxygenation (HDO) of propanoic acid over transition metal surfaces. The microkinetic model (MKM) is initially parametrized by ML-predicted energies and iteratively improved by identifying the rate-determining species and steps (RDS), computing their energies by density functional theory (DFT), and reparameterizing the MKM until all the RDS are computed by DFT. The Gaussian process (GP) model performs significantly better than the linear ridge regression model for predicting both the adsorption free energies and transition state free energies. Parameterized with energies from the GP model, only 5–20% of the full reaction network has to be computed by DFT for the MKM to possess DFT-level accuracy for the TOF and dominant reaction pathway. While the linear ridge regression model performs worse than the GP model, its performance is greatly improved when only transition states are predicted by the regression model and adsorption energies are computed by DFT. Overall, we find that a high accuracy in adsorption free energies is more important for a reliable MKM than a high accuracy in TS free energies. Lastly, based on the GP model with GOH and GCHCHCO as catalyst descriptors, we build two-dimensional volcano plots in activity and selectivity that can help design promising alloy catalysts for HDO reactions of organic acids.

adsorption↗
DOE OSTI2024

Weathering Incongruence in Mountainous Mediterranean Climates Recorded by Stream Lithium Isotope Ratios

Lithium isotope ratios (δ 7 Li) of rivers are increasingly serving as a diagnostic of the balance between chemical and physical weathering contributions to overall landscape denudation rates. Here, we show that intermediate weathering intensities and highly enriched stream δ 7 Li values typically associated with lowland floodplains can also describe small upland watersheds subject to cool, wet climates. This behavior is revealed by stream δ 7 Li between +22.4 and +23.5‰ within a Critical Zone observatory located in the Cévennes region of southern France, where dilute stream solute concentrations and significant atmospheric deposition otherwise mask evidence of incongruence. The water-rock reaction pathways underlying this behavior are quantified through a multicomponent, isotope-enabled reactive transport model. Using geochemical characterization of soil profiles, bedrock, and long-term stream samples as constraints, we evolve the simulation from an initially unweathered granite to a steady state weathering profile which reflects the balance between (a) fluid infiltration and drainage and (b) bedrock uplift and soil erosion. Enriched stream δ 7 Li occurs because Li is strongly incorporated into actively precipitating secondary clay phases beyond what prior laboratory experiments have suggested. Chemical weathering incongruence is maintained despite relatively slow reaction rates and moderate clay accumulation due to a combination of two factors. First, reactive primary mineral phases persist across the weathering profile and effectively “shield” the secondary clays from resolubilization due to their greater solubility. Second, the clays accumulating in the near-surface profile are relatively mature weathering byproducts. These factors promote characteristically low total dissolved solute export from the catchment despite significant input of exogenous dust.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Theoretical insights into the surface physics and chemistry of redox-active oxides

Redox active oxides are ubiquitous in materials applications, including catalysis, photovoltaics, self-cleaning glasses, chemical sensors, and electronic components. Their utility derives from their unique ability to access multiple metal charge states within a finite energy window. However, this property also confounds our ability to study reducible oxides, because it leads to structural, compositional, and electronic complexities that elude simplistic models of materials structure and function. Oxygen vacancies play a critical role in shaping the functional properties of such oxides; most notably, they lead to mobile charge imbalances that impact surface processes at significant distances from the originating defect. Atomistic simulations are inherently equipped to illuminate these phenomena at a fundamental level; however, reducible oxides pose great challenges due to the high level of electron correlation needed to correctly describe them. Knowing how defects form, couple, propagate, agglomerate, or repel each other and influence the surface properties of reducible oxides is only now coming into the grasp of modern theory and simulation capabilities. This knowledge is also key to discovering and controlling emergent materials processes at nanometer scale and beyond. The manuscript was written with support of all three authors from U.S. Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences. Work by RR and VG was performed at Pacific Northwest National Laboratory (PNNL), which is a multi-program laboratory operated by Battelle for DOE under Contract DE AC05 76RL01830. AS was supported under Award DE-SC0007347.

Rousseau, Roger J.↗
DOE OSTI2023

Mechanistic insights into the conversion of polyalcohols over Brønsted acid sites

Multi-layered plastic (MLP) films provide excellent properties for food packaging; however, because of the complicated chemistry of the hydrophobic substrates and tightly laminated hydrophilic layers, it is challenging to recycle the MLP films. The selective conversion of polar functional groups in hydrophilic layers with a minimal destruction of the carbon backbone of constituted polymers is considered a promising approach to improve the recyclability of MLP films. Here, in this study, we combine computational and experimental studies to investigate the acid-catalyzed conversion of functional groups in polyalcohols, through which we report potential reaction pathways involved in the conversion of ethylene vinyl alcohol (EVOH), a common copolymer used in MLP films as an oxygen barrier. Using 2,4-pentanediol as a model compound, we show that its conversion proceeds primarily through the dehydration of a hydroxyl group via either a stepwise or a concerted mechanism to form an unsaturated alcohol that can be further converted into a conjugated diene or a saturated ketone; this secondary reaction determines the product selectivity. The rate determining intermediates and transition states are identified, and the activation barriers are calculated, in agreement with experimentally observed product selectivities. This study thus provides insights for the selective conversion of EVOH.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Experimentally Driven Automated Machine-Learned Interatomic Potential for a Refractory Oxide

Understanding the structure and properties of refractory oxides is critical for high temperature applications. In this work, a combined experimental and simulation approach uses an automated closed loop via an active learner, which is initialized by x-ray and neutron diffraction measurements, and sequentially improves a machine-learning model until the experimentally predetermined phase space is covered. Furthermore, a multiphase potential is generated for a canonical example of the archetypal refractory oxide, HfO 2 , by drawing a minimum number of training configurations from room temperature to the liquid state at similar to 2900 degrees C. The method significantly reduces model development time and human effort.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Data-Driven Exploration of Climate Attractor Manifolds For Long-Term Predictability

Focal Area: This white paper responds to Focal Area 3. We seek to gain insight into decadal-scale climate predictability by applying novel manifold-finding probabilistic AI techniques to the complex data produced by Earth System models (ESMs) such as E3SM. The associated portfolio of research activities leverages DOE’s asset mix of HPC platforms, climate expertise, climate simulation codes, and AI expertise. Science Challenge: Climate and climate models are dynamical systems exhibiting properties that are interpretable through chaos theory. The theory contains an important concept that is relevant to multi-decade-scale climate prediction: a chaotic attractor. While the space containing all the possible states of the Earth’s atmosphere and ocean, the possible weather, is large, the realized states tend to stay near the smaller-dimensioned attractor. This behavior is responsible for the “order behind the irregularity” [1] of climate phenomena. Climate change can be thought of as a change in the properties of the attractor, and predicting the climate over years to decades is equivalent to predicting how those properties will change. To date, the attractor has been a useful conceptual tool, but has not been amenable to direct characterization. A new development is the advent of efficient high-dimensional manifold-finding probabilistic AI techniques, which permit a data-driven characterization of the ESM attractor and its probability distribution over weather states. Such a characterization would result in a natural dimensional reduction — a “non-linear Principal Components Analysis (PCA) adapted to climate simulation data” — leading to important advances in scenario-based long-term climate prediction, long-term prediction of water cycle extremes, ESM verification, inter-model comparison, and process model development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

North Atlantic Oscillation response in GeoMIP experiments G6solar and G6sulfur: why detailed modelling is needed for understanding regional implications of solar radiation management

The realization of the difficulty of limiting global-mean temperatures to within 1.5 or 2.0°C above pre-industrial levels stipulated by the 21st Conference of Parties in Paris has led to increased interest in solar radiation management (SRM) techniques. Proposed SRM schemes aim to increase planetary albedo to reflect more sunlight back to space and induce a cooling that acts to partially offset global warming. Under the auspices of the Geoengineering Model Intercomparison Project, we have performed model experiments whereby global temperature under the high-forcing SSP5-8.5 scenario is reduced to follow that of the medium-forcing SSP2-4.5 scenario. Two different mechanisms to achieve this are employed: the first via a reduction in the solar constant (experiment G6solar) and the second via modelling injections of sulfur dioxide (experiment G6sulfur) which forms sulfate aerosol in the stratosphere. Results from two state-of-the-art coupled Earth system models (UKESM1 and CESM2-WACCM6) both show an impact on the North Atlantic Oscillation (NAO) in G6sulfur but not in G6solar. Both models show a persistent positive anomaly in the NAO during the Northern Hemisphere winter season in G6sulfur, suggesting an increase in zonal flow and an increase in North Atlantic storm track activity impacting the Eurasian continent and leading to high-latitude warming over Europe and Asia. These results are broadly consistent with previous findings which show similar impacts from stratospheric volcanic aerosol on the NAO and emphasize that detailed modelling of geoengineering processes is required if accurate impacts of SRM effects are to be simulated. Differences remain between the two models in predicting regional changes over the continental USA and Africa, suggesting that more models need to perform such simulations before attempting to draw any conclusions regarding potential continental-scale climate change under SRM.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Material flows and GHG emissions from housing stock evolution in US counties, 2020–60

The evolution of housing stocks determines demand for construction materials and energy, and associated emissions of greenhouse gasses (GHGs). The contribution of construction to building life-cycle emissions is growing as buildings become more energy efficient and the energy supply decarbonizes. A housing stock model is developed for counties in the United States using dynamic vacancy rates which endogenously influence stock out- and inflows. Stocks of three house types and 10 construction cohorts are projected for all contiguous US counties for the period 2020–60. Inflows and outflows of construction materials are then estimated along with GHG emissions associated with material production and construction activities in scenarios defined by stock turnover rates, population share by house type, and floor area characteristics of new houses. The results provide new insights into the drivers of construction-related emissions at local and national levels, and identify opportunities for their reduction. Demolition material flows grow in relation to construction material flows over the analysis period. Increasing the stock turnover rate increases future floor area per person, material requirements, and emissions from construction. Scenarios with reduced floor area and more multifamily homes in new construction have lower floor area growth, material requirements, and emissions from construction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗