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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Electrodialysis and nitrate reduction (EDNR) to enable distributed ammonia manufacturing from wastewaters

Underutilized wastewaters containing dilute levels of reactive nitrogen (Nr) can help rebalance the nitrogen cycle. This study describes electrodialysis and nitrate reduction (EDNR), a reactive electrochemical separation architecture that combines catalysis and separations to remediate nitrate and ammonium-polluted wastewaters while recovering ammonia. By engineering operating parameters (e.g., background electrolyte, applied potential, electrolyte flow rate), we achieved high recovery and conversion of Nr in both simulated and real wastewaters. The EDNR process demonstrated long-term robustness and up-concentration that recovered >100 mM ammonium fertilizer solution from agricultural runoff that contained 8.2 mM Nr. EDNR is the first reported process to our knowledge that remediates dilute real wastewater and recovers ammonia from multiple Nr pollutants, with an energy consumption (245 MJ per kg NH 3 –N in simulated wastewater, 920 MJ per kg NH 3 –N in agricultural runoff) on par with the state-of-the-art. Demonstrated first at proof-of-concept and engineered to technology readiness level (TRL) 4–5, EDNR shows great promise for distributed wastewater treatment and sustainable ammonia manufacturing.

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

Effects of Rolling Reduction on Critical Current Density and Microstructure of Bi-2212 Wires

Bi-2212 Rutherford cables have been fabricated into flat racetrack coils and canted-cosine-theta dipole magnets. The performance gap between the magnets made with Rutherford cables and the “short-sample-limit” is about 30%. To better understand the influence of Rutherford cable processing on the strand performance, we studied three Bi-2212 wires with filament architectures of 37 × 18 and 55 × 18 and diameters of 0.8 and 1.0 mm. To simulate the deformation caused by cabling process, the three wires were rolled with thickness reductions ranging from 10% to 30%. The aspect ratios of rolled strands are between 1.29 and 2.05. The low aspect-ratio wire is also an interesting form for fabricating solenoid coils with higher packing density. The round and rolled strands were heat-treated under 50 bar and with maximum heat treatment temperatures of 885.5 °C and 890.5 °C. The rolling deformation reduced filament size uniformity, resulting in filament merging in fully heat-treated wires. It was found that rolling reduction reduced wire critical current density (JE) by 16 to 18%, but the JE decrease saturated at 15 to 20% of the thickness reduction. It is believed that the reduced JE results from the filament merging caused by rolling and non-uniform shrinking during overpressure heat treatment.

Bi-2212 wire↗
DOE OSTI2024

How Well Does the DOE Global Storm Resolving Model Simulate Clouds and Precipitation Over the Amazon?

This study assesses a 40-day 3.25-km global simulation of the Simple Cloud-Resolving E3SM Model (SCREAMv0) using high-resolution ground-based observations from the Atmospheric Radiation Measurement (ARM) Green Ocean Amazon (GoAmazon) field campaign. SCREAMv0 reasonably captures the diurnal timing of boundary layer clouds yet underestimates the boundary layer cloud fraction and mid-level congestus. SCREAMv0 well replicates the precipitation diurnal cycle, however it exhibits biases in the precipitation cluster size distribution compared to scanning radar observations. Specifically, SCREAMv0 overproduces clusters smaller than 128 km, and does not form enough large clusters. Such biases suggest an inhibition of convective upscale growth, preventing isolated deep convective clusters from evolving into larger mesoscale systems. This model bias is partially attributed to the misrepresentation of land-atmosphere coupling. This study highlights the potential use of high-resolution ground-based observations to diagnose convective processes in global storm resolving model simulations, identify key model deficiencies, and guide future process-oriented model sensitivity tests and detailed analyses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Surrogate modeling and optimization of the leaching process in a rare earth elements recovery plant

Critical minerals (CMs) and Rare Earth Elements (REEs) play a vital role in crucial infrastructure technologies such as renewable energy generation and batteries. Recovering them from waste materials has recently been found to significantly reduce environmental impact and supply chain costs related to these materials. In this work, we investigate surrogate modeling techniques aimed to simplify the modeling, simulation, and optimization of the leaching processes involved in CM and REE recovery flowsheets. As there is currently a lack of systematic studies on this topic, we perform extensive computational testing to ascertain which surrogate models are easier to construct and offer high predictive accuracy. Further, our results suggest that sparse quadratic models balance predictive accuracy and computational efficiency. Training and using these surrogates for global optimization of the leaching process requires two orders of magnitude fewer measurements and is up to four orders of magnitude faster than optimizing the original simulation using equation-oriented optimization or derivative-free optimization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Low-Pressure Diffusion Bonding of Vanadium to Commercially Pure Titanium and Ti-6Al-4V

Modern technology increasingly requires components to be made from specific high-performance materials. To support complex multi-metal structures, a variety of techniques are required to join dissimilar metal parts with precise shapes. This study evaluates vacuum diffusion bonding as a method for joining titanium and vanadium, focusing on both pure titanium and the common alloy Ti-6Al-4V. We employ modest pressure provided by a weight and simple surface preparation to simulate the most commercially applicable process. Here, we show that Ti-6Al-4V alloy bonds readily to V, forming a continuous, clearly defined interdiffusion layer with predictable kinetics. Conversely, commercially pure Ti forms a crack-prone bond with V that fails to improve at higher bonding temperatures or longer times. We attribute this failure to the concentration of stress caused by the ß-to-α phase transformation in Ti. The contrasting bonding efficacy between pure Ti and the alloy provides insight into the crystallographic interactions that occur at the interface during bonding and cooling. These results provide surprising insight into a new method for bonding Ti alloys to V and possibly other metals that share the body-centered cubic crystal structure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Location-Specific Microstructure Characterization Within AM Bench 2022 Nickel Alloy 718 3D Builds

Abstract The Additive Manufacturing Benchmark Test Series (AM Bench) is a broad effort to produce rigorous measurement datasets for validating AM computer simulations across the range of processing, structure, and properties, for many additive manufacturing (AM) build methods and material classes. Here, the microstructures of nickel alloy 718 AM Bench 2022 test artifacts produced using laser-based powder bed fusion (PBF-LB), in both as-built and fully heat-treated conditions, are examined. Cross sections are primarily characterized using large area scanning electron microscopy (SEM) electron backscatter diffraction (EBSD) and example analyses of the crystallographic textures are described. These data are part of a large set of in situ and ex situ measurements from both three-dimensional builds and laser tracks on bare plates. All the measurement data are available online with download links at www.nist.gov/ambench .

Levine, L. E. (ORCID:0000000334484229)↗
DOE OSTI2025

MOOSE ProbML: Parallelized probabilistic machine learning and uncertainty quantification for computational energy applications

Here, this paper presents the development and demonstration of massively parallel probabilistic machine learning (ML) and uncertainty quantification (UQ) capabilities within the Multiphysics Object-Oriented Simulation Environment (MOOSE), an open-source computational platform for parallel finite element and finite volume analyses. In addressing the computational expense and uncertainties inherent in complex multiphysics simulations, this paper integrates Gaussian process (GP) variants, active learning, Bayesian inverse UQ, adaptive forward UQ, Bayesian optimization, evolutionary optimization, and Markov chain Monte Carlo (MCMC) within MOOSE. It also elaborates on the interaction among key MOOSE systems — Sampler, MultiApp, Reporter, and Surrogate — in enabling these capabilities. The modularity offered by these systems enables development of a multitude of probabilistic ML and UQ algorithms in MOOSE. Example code demonstrations include parallel active learning and parallel Bayesian inference via active learning. The impact of these developments is illustrated through five applications relevant to computational energy applications: UQ of nuclear fuel fission product release, using parallel active learning Bayesian inference; very rare events analysis in nuclear microreactors using active learning; advanced manufacturing process modeling using multi-output GPs (MOGPs) and dimensionality reduction; fluid flow using deep GPs (DGPs); and tritium transport model parameter optimization for fusion energy, using batch Bayesian optimization. These capabilities are part of the MOOSE framework.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Development of a high-temperature Inconel 625 heat exchanger by model design and binder jetting additive manufacturing

A nickel-based Inconel 625 superalloy heat exchanger for high-temperature applications was developed via binder jetting additive manufacturing. The material properties were characterized first on printed and sintered parts. Two sintering temperatures were used to investigate the effects of the temperature on densification and microstructure. For channel geometry design, the heat transfer capabilities of the heat exchanger were optimized for the cross-section geometry of fluid flow channels in a counterflow configuration, and a stress analysis was conducted to investigate the effects of channel geometry. After headers were incorporated into the heat exchanger as a one-piece component, a prototype was printed. A complete depowdering was achieved via compressed air blowing, and sintering was performed with the developed profile. Ultimately, a one-piece heat exchanger with a nearly full density was obtained. Heat transfer tests were performed on this unit, and the results were compared with those from the simulations. In this study, systematic processes were developed for an additively manufactured Inconel-based heat exchanger for high-pressure, high-temperature heat transfer applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Chromium versus Aluminum: Impact of Nickel Alloy Composition and Interfacial Kinetics on High-Temperature Passivating Oxide Formation

High-temperature corrosion resistance depends critically on the formation of a passivating surface oxide, which is highly sensitive to alloy composition and structure. Such details often elude experimental investigation, and simplified analytical models fail to provide a truly chemical view of passivating oxide evolution. Here, we explicitly compare the fundamental chemistry of Cr and Al as prototypical passivating elements in Ni alloys by directly simulating competing reaction and diffusion processes within the oxide film using kinetic Monte Carlo and density functional theory. We find that the origin and expression of passivating behavior during early-stage thermal oxidation are qualitatively different between the two alloy systems. Ni–Cr alloys feature a sudden onset of passivation associated with a sharp phase transition upon Cr enrichment that directly couples oxidation kinetics to phase transformation behavior. In contrast, Ni–Al alloys display more continuous oxide phase variation with Al enrichment, ultimately resulting in a lower composition threshold for passivation and a thinner passivating layer. In addition, we elucidate the nonobvious role of metal exchange within the alloy near the oxide boundary, which fundamentally alters film composition and passivating behavior. Furthermore, our results have key implications for engineering improved corrosion-resistant alloys, both in terms of compositional variation and processing.

Alloys↗
DOE OSTI2024

Estimating the CO 2 Fertilization Effect on Extratropical Forest Productivity From Flux‐Tower Observations

Abstract The land sink of anthropogenic carbon emissions, a crucial component of mitigating climate change, is primarily attributed to the CO 2 fertilization effect on global gross primary productivity (GPP). However, direct observational evidence of this effect remains scarce, hampered by challenges in disentangling the CO 2 fertilization effect from other long‐term confounding drivers, particularly climatic changes. Here, we introduce a novel statistical approach to separate the CO 2 fertilization effect on photosynthetic carbon uptake using eddy covariance (EC) records across 38 extratropical forest sites. We find the median stimulation rate of GPP to be 3.2 ± 0.9 gC m −2 yr −1 ppm −1 (or 16.4 ± 4.2% per 100 ppm) under increasing atmospheric CO 2 across these sites, respectively. To validate the robustness of our findings, we test our statistical method using factorial simulations of an ensemble of process‐based land surface models. We address additional factors, including nitrogen deposition and land management, that may impact plant productivity, potentially confounding the attribution to the CO 2 fertilization effect. Assuming these site‐specific effects offset to some extent across sites as random factors, the estimated median value still reflects the strength of the CO 2 fertilization effect. However, disentanglement of these long‐term effects, often inseparable by timescale, requires further causal research. Our study provides direct evidence that the photosynthetic stimulation is maintained under long‐term CO 2 fertilization across multiple EC sites. Such observation‐based quantification is key to constraining the long‐standing uncertainties in the land carbon cycle under rising CO 2 concentrations.

Environmental Sciences & Ecology↗
DOE OSTI2024

Summertime Continental Shallow Cumulus Cloud Detection Using GOES‐16 Satellite and Ground‐Based Ceilometer at North Alabama

Abstract Accurate simulations of boundary layer cloud processes remain challenging in Earth system modeling. Observations are essential to evaluate and improve models of such processes. This study introduces a comprehensive validation framework for a satellite‐based detection algorithm of continental shallow cumulus (ShCu) clouds during the daytime, which was initially developed using ground‐based observations of stereo cameras at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains site (J. Tian et al., 2021, https://doi.org/10.3390/rs13122309 , 2022, https://doi.org/10.1029/2021gl097070 ). To validate this algorithm, the framework employs ground‐based ceilometer measurements from North Alabama (NA) where ShCu populations are prevalent. This study first generates clear‐sky surface reflectance maps at NA and identifies ShCu pixels with a detection threshold using Geostationary Operational Environmental Satellite (GOES) reflectance data. The obtained cloud fractions (CFs) are then compared against CFs from a ground‐based ceilometer, considering factors such as observed area differences, satellite parallax issue, and systematic biases. We found that with a detection threshold (∆R) of 0.05, the ShCu detection algorithm is effective for NA, enabling the reproduction of hourly ShCu CFs using GOES. Our framework is straightforward and easily repeatable to evaluate the effectiveness of a ∆R threshold for detecting ShCu clouds in various geographic regions where ceilometers are deployed. This satellite detection of ShCu provides a crucial regional context for ground‐based measurements, facilitating the tracking of convection initiation and its coupling with land surface conditions. Integrating localized ground‐based and regional satellite data will enhance our ability to conduct thorough studies of cloud morphology and land‐atmosphere interactions in North Alabama.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Accelerating detector simulations with Celeritas: Profiling and performance optimizations

Celeritas is a GPU-optimized Monte Carlo (MC) particle transport code designed to meet the growing computational demands of next-generation high energy physics (HEP) experiments. It provides efficient simulation of electromagnetic (EM) physics processes in complex geometries with magnetic fields, detector hit scoring, and seamless integration into Geant4-driven applications to offload EM physics to GPUs. Recent efforts have focused on performance optimizations and expanding profiling capabilities. This paper presents some key advancements, including the integration of the Perfetto system profiling tool for detailed performance analysis and the development of track-sorting methods to improve computational efficiency.

Lund, Amanda [Argonne National Laboratory (ANL)]↗
DOE OSTI2024

An octahedral Mach B-dot probe for 3D flows and magnetic fields in the edge of reversed field pinches

Measurements and simulations show that plasma relaxation processes in the reversed field pinch drive and redistribute both magnetic flux and momentum. To examine this relaxation process, a new 3D Mach B-dot probe has been constructed. This probe collects ion saturation currents through six molybdenum electrodes arranged on the flattened vertices of an octahedron made of boron nitride (BN). The ion saturation current flows through configurable voltage dividers for measurement and returns through one of six selectable return electrodes equally spaced along the 12 cm BN probe arm. In addition, the probe arm houses three B-dot magnetic pickup coils in the BN stalk immediately below to the octahedron, to measure the local magnetic field. Inserted in the Madison Symmetric Torus (MST) during deuterium discharges with 220 kA plasma current, density of 0.8 × 10 13 cm –3 , the probe collects ion saturation currents with sawtooth-like peaks correlated with relaxation events. This compact octahedral design fitting six Mach electrode surfaces within a 1 cm3 cube will enable future multi-point, multi-field probes compatible with the 1.5 in. ports of MST. Such probes will allow for flow circulation, current, and canonical vorticity to be calculated in the center of the finite difference stencil formed by the measurement locations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Calibrating a finite-strain phase-field model of fracture for bonded granular materials with uncertainty quantification

To study the mechanical behavior of mock high explosives, an experimental and simulation program was developed to calibrate, with quantified uncertainty, a material model of the bonded granular material Idoxuridine and nitroplasticized Estane-5703. This paper reports on the efficacy of such a framework as a generalizable methodology for calibrating material models against experimental data with uncertainty quantification. Additionally, this paper studies the effect of two manufacturing temperatures and three initial granular configurations on the unconfined compressive behavior of the resulting bonded granular materials. In each of these cases, the same calibration framework was used; in that, hundreds of high-fidelity direct numerical simulations using a new, graphics processing unit-enabled, high-performance finite element method software, Ratel, were run to calibrate a finite-strain phase-field fracture model against experimental data. It was found that manufacturing temperature influenced the elastic response of the mock high explosives, with higher temperatures yielding a stiffer response. By contrast, it was found that the initial configuration of the grains had a negligible impact on the overall behavior of the mock high explosives though it remains possible that local damage accumulation within the specimens could be altered by the initial configurations. Overall, the calibration framework was successful at creating well-calibrated models, showing its usefulness as an engineering and scientific tool.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Bayesian Neural Network Variational Autoencoder Inverse Mapper (BNN-VAIM) and its application in Compton Form Factors extraction

Abstract We extend the Variational Autoencoder Inverse Mapper (VAIM) framework for the inverse problem of extracting Compton Form Factors (CFFs) from deeply virtual exclusive reactions, such as the unpolarized Deeply virtual exclusive scattering (DVCS) cross section. VAIM is an end-to-end deep learning framework to address the solution ambiguity issue in ill-posed inverse problems, which comprises of a forward mapper and a backward mapper to simulate the forward and inverse processes, respectively. In particular, we incorporate Bayesian Neural Network (BNN) into the VAIM architecture (BNN-VAIM) for uncertainty quantification. By sampling the weights and biases distributions of the BNN in the backward mapper of the VAIM, BNN-VAIM is able to estimate prediction uncertainty associated with each individual solution obtained for an ill-posed inverse problem. We first demonstrate the uncertainty quantification capability of BNN-VAIM in a toy inverse problem. Then, we apply BNN-VAIM to the inverse problem of extracting 8 CFFs from the unpolarized DVCS cross section.

Instruments & Instrumentation↗
DOE OSTI2025

Hydrology controls thermokarst and alters carbon cycling and methane emissions in peatlands near the southern limit of permafrost

Permafrost peatlands store vast amounts of frozen carbon across northern landscapes. When ground ice melts, surface subsidence produces thermokarst landforms that expand wetlands at the edges of permafrost plateaus. Thermokarst represents an accelerating climate feedback, but uncertainties remain about how ground ice, hydrology, and vegetation interact to shape landscape change and carbon fluxes. We extended the process-based model ecosys to simulate thermokarst dynamics in laterally coupled 2D transects at a well-characterized boreal peatland site in Canada’s Northwest Territories. After benchmarking against site observations, we varied ground ice content and hydrologic boundary conditions across ranges typical near the southern permafrost limit. Simulations revealed distinct degradation regimes governed by the elevation difference between the frost table and the external water table. Rates of lateral retreat, the thaw-driven encroachment of wetlands into adjacent plateaus, ranged from 0 to >2 m yr −1 under identical weather forcing, consistent with observations and highlighting the strong role of WT and ground ice. Simulated vegetation dynamics indicate that black spruce mortality cannot be explained by anoxia alone, pointing to additional stressors such as root damage, pathogens, or physical destabilization. Despite large hydrologic shifts, net ecosystem CO 2 exchange remained a slight sink after collapse, while methane (CH 4 ) emissions rose by one to two orders of magnitude. As a result, lateral retreat substantially increases the greenhouse warming potential of permafrost peatlands (1.7 million km 2 in area), with simulated emissions of 0.1–10 Mt CO 2 -eq decade −1 depending on hydrology and retreat rates. These results underscore the need to account for both ground ice and hydrologic dynamics when assessing thermokarst-driven climate feedbacks.

carbon cycling↗
DOE OSTI2024

Computational prediction of dielectric breakdown strength of a transformer paper in oil with uncertainty quantification

The determination of the dielectric breakdown strengths of microstructurally heterogeneous materials has been a primarily experimental endeavor. We report the development of a microstructure-level model for computationally predicting the breakdown strength and analyzing the interactions between electromagnetic pulses (EMP) and the constituents in a composite of cellulose-based paper and mineral oil found in electrical transformers. The model allows explicit simulation of the material breakdown process by tracking the transition of dielectric constituents from non-conductive to conductive states. The focus is on the electric fields induced in the materials and the overall conditions for dielectric breakdown (defined as the onset of avalanche) caused by the electric field induced in the composite. Responses to three distinct pulse shapes, i.e., Steep Front (SF), Lightning (L), and AC with spectra spanning 60–9 × 105 Hz are considered. It is found that the breakdown strength of the material is significantly affected by microstructure heterogeneities, the spatial variations of the constituent properties, and the pulse shapes. A probabilistic characterization of the breakdown strength is computationally obtained and compared with experimental measurements. Although one particular material is analyzed, the model and approach are applicable to other heterogeneous materials as well.

breakdowns↗
DOE OSTI2024

Weak lensing combined with the kinetic Sunyaev–Zel’dovich effect: a study of baryonic feedback

ABSTRACT Extracting precise cosmology from weak lensing surveys requires modelling the non-linear matter power spectrum, which is suppressed at small scales due to baryonic feedback processes. However, hydrodynamical galaxy formation simulations make widely varying predictions for the amplitude and extent of this effect. We use measurements of Dark Energy Survey Year 3 weak lensing (WL) and Atacama Cosmology Telescope DR5 kinematic Sunyaev–Zel’dovich (kSZ) to jointly constrain cosmological and astrophysical baryonic feedback parameters using a flexible analytical model, ‘baryonification’. First, using WL only, we compare the $S_8$ constraints using baryonification to a simulation-calibrated halo model, a simulation-based emulator model, and the approach of discarding WL measurements on small angular scales. We find that model flexibility can shift the value of $S_8$ and degrade the uncertainty. The kSZ provides additional constraints on the astrophysical parameters, with the joint WL + kSZ analysis constraining $S_8=0.823^{+0.019}_{-0.020}$. We measure the suppression of the non-linear matter power spectrum using WL + kSZ and constrain a mean feedback scenario that is more extreme than the predictions from most hydrodynamical simulations. We constrain the baryon fractions and the gas mass fractions and find them to be generally lower than inferred from X-ray observations and simulation predictions. We conclude that the WL + kSZ measurements provide a new and complementary benchmark for building a coherent picture of the impact of gas around galaxies across observations.

79 ASTRONOMY AND ASTROPHYSICS↗