Search NASA⌕ Search

SEARCH · Search NASA

Results for “Compositional simulation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Assessment of CO 2 trapping mechanisms in partially depleted oil-bearing sands

The goal of this work is to evaluate various CO 2 sequestration mechanisms occurring in the Morrow B Sandstone in the Farnsworth Unit. A history-matched numerical simulation model was created using extensive geological, petrophysical, and operational data collected from the field. The numerical model is competent to investigate the impact of residual, structural-stratigraphic, solubility, and mineral trapping mechanisms on the fluid transportation dynamics and petrophysical property variations. The model forecasts the field response of 20 years of WAG injections. Afterward, all wells were shut-in, and the reservoir was allowed to evolve for 1000 years to investigate the fate of injected CO 2 . In this paper, we assess the impacts of various trapping mechanisms on oil recovery and CO 2 storage efficacy. By analyzing the results reported from the numerical simulation model, the in-situ fluid composition and mineralogy changes are also investigated. More importantly, we seek to confirm the petrophysical property variations due to the CO 2 injection with observations from laboratory measurements. The experiences gained from this study provide valuable insights regarding physiochemical storage induced by the CO 2 injection activities and serve as a benchmark case for future CO 2 enhanced oil recovery (EOR) projects involving reactive solute transport.

42 ENGINEERING↗
DOE OSTI2023

Multifidelity deep operator networks for data-driven and physics-informed problems

Operator learning for complex nonlinear systems is increasingly common in modeling multi-physics and multi-scale systems. However, training such high-dimensional operators requires a large amount of expensive, high-fidelity data, either from experiments or simulations. In this work, we present a composite Deep Operator Network (DeepONet) for learning using two datasets with different levels of fidelity to accurately learn complex operators when sufficient high-fidelity data is not available. Additionally, we demonstrate that the presence of low-fidelity data can improve the predictions of physics-informed learning with DeepONets. We demonstrate the new multi-fidelity training in diverse examples, including modeling of the ice-sheet dynamics of the Humboldt glacier, Greenland, using two different fidelity models and also using the same physical model at two different resolutions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Predicting the Phase Stability of Multicomponent High-Entropy Compounds

A generic method to estimate the relative feasibility of formation of high-entropy compounds in a single phase, directly from first principles, is developed. As a first step, the relative formation abilities of 56 multicomponent, AO, oxides were evaluated. These were constructed from five cation combinations chosen from A = {Ca, Co, Cu, Fe, Mg, Mn, Ni, Zn}. Candidates for multicomponent oxides are predicted from descriptors related to the enthalpy and configurational entropy obtained from the mixing enthalpies of two-component oxides. The utility of this approach is evaluated by comparing the predicted combinations with the experimentally realized entropy-stabilized oxide, (MgCoCuNiZn)O. In the second step, Monte Carlo simulations are utilized to investigate the phase composition and local ionic segregation as a function of temperature. This approach allows for the evaluation of potential secondary phases, thereby making realistic predictions of novel multicomponent compounds that can be synthesized.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Methanogenesis and Acetogenesis in Hydrogenotrophy with Carbonate Minerals: Dependence on Mineral Surface Area, Biofilm Growth, and Microbial Community

The production, storage, and use of hydrogen are anticipated to grow substantially to achieve energy and climate goals. Consequently, microbial communities in many terrestrial and subsurface Earth environments could be exposed to elevated hydrogen concentrations. Hydrogen stimulates metabolic processes that reduce aqueous chemical species, such as bicarbonate or sulfate, that can exchange with solid mineral phases, but the controls on microbial hydrogenotrophy with mineral sources of electron acceptors are not fully understood. Herein, we applied laboratory experiments and biogeochemical modeling to study the response of a natural microbial community to an elevated partial pressure of hydrogen in the presence of carbonate minerals of varying composition, solubility, and size. Experimental incubations and simulation results showed that hydrogen consumption by microbial communities was initially dominated by sulfate reduction and, subsequently, transitioned to acetogenesis and methanogenesis. The rates of acetogenesis and methanogenesis were not correlated with the solubility of carbonate minerals. Instead, we observed strong linear correlations between the rates and surface area of carbonate minerals. Methane and acetate production slowed down in all incubations after about 2 weeks of incubation, although biogeochemical modeling predicted that the metabolic processes were not thermodynamically limited. Electron microscopy and infrared spectroscopy showed that biofilms with diverse microorganisms grew on the carbonates during this period. The methane δ13C value significantly increased, consistent with slower growth at elevated pH. This work highlights that microbial communities form biofilm on carbonate mineral surfaces as a response to hydrogen and that biofilm formation could pose a strong kinetic limitation to hydrogenotrophic metabolism utilizing carbonate minerals.

Acetobacterium↗
DOE OSTI2021

Comparison of Current and Future PM2.5 Air Quality in China Under CMIP6 and DPEC Emission Scenarios

The latest scenarios for the sixth Coupled Model Intercomparison Project (CMIP6) provide opportunities to explore future climate and air pollution mitigation pathways with socioeconomic features. However, to what extent inadequate consideration of region-specific policies in the CMIP6 scenarios would affect regional air quality projections is still not clear. Here, we simulated China’s future PM2.5 concentrations and compositions with local policy-based scenarios and the original CMIP6 datasets, for the first time estimating future air quality differences induced by the lack of local pollution control policies in the CMIP6 scenarios. We found that the CMIP6-driven projections overestimate major chemical aerosols by 10% – 70% in 2015 and fail to capture the rapid PM2.5 concentration decline during 2015–2019. Near-term differences further lead to 43% – 49% (5 – 9 µg/m3) PM2.5 overpredictions in 2050 in CMIP6 scenarios compared with policy-based mitigation scenarios. Our study demonstrates the indispensable influences of local policies on regional analyses and suggests that the research community should incorporate more region-specific information in future scenario designs.

Cheng, Jing↗
DOE OSTI2026

Regularization via f -Divergence: An Application to Multi-Oxide Spectroscopic Analysis

In this paper, we explore the application of convolutional neural networks (CNNs) for predicting the chemical composition of complex geologic samples in a simulated Martian atmospheric environment. Specifically, we aim to characterize oxide weight percentages (wt.%) of rock samples analyzed by remote Laser-Induced Breakdown Spectroscopy (LIBS), framing the problem as a multi-target regression task . Neural networks trained on LIBS spectra are prone to overfitting due to high spectral complexity, limited labeled data, and measurement noise. While regularization is critical for improving generalization, common methods (e.g., ℓ 2 regularization) impose constraints not directly tied to data distribution properties. We propose a novel regularization method based on a specific ƒ-divergence induced by a graph-based estimator, designed to constrain the distributional discrepancy between predictions and targets. This regularizer serves a dual purpose: (a) mitigating overfitting by enforcing a constraint on the distributional difference between predictions and noisy targets, and (b) acting as an auxiliary loss that penalizes large divergences. To enable backpropagation, we develop a differentiable approximation of this particular ƒ-divergence, making the method feasible for neural networks. Experiments on ChemCam and SuperCam LIBS calibration spectra show that mathematical equation-divergence regularization outperforms or matches standard regularization methods (ℓ 1 , ℓ 2 , dropout) and the classical baseline, partial least squares (PLS). Combining ƒ-divergence regularization with standard regularization yields further performance gains, indicating that distributional regularization is useful in this context giving a promising direction for robust model training in planetary science applications. Source code is publicly available at Klein and Li (2025), https://doi.org/10.11578/dc.20250530.7.

58 GEOSCIENCES↗
DOE OSTI2024

Methylation enables the use of fluorine-free ether electrolytes in high-voltage lithium metal batteries

Lithium metal batteries represent a promising technology for next-generation energy storage, but they still suffer from poor cycle life due to lithium dendrite formation and cathode cracking. Fluorinated solvents can improve battery longevity by improving LiF content in the solid-electrolyte interphase; however, the high cost and environmental concerns of fluorinated solvents limit battery viability. Here, for this work, we designed a series of fluorine-free solvents through the methylation of 1,2-dimethoxyethane, which promotes inorganic LiF-rich interphase formation through anion reduction and achieves high oxidation stability. The anion-derived LiF interphases suppress lithium dendrite growth on the lithium anode and minimize cathode cracking under high-voltage operation. The Li + -solvent structure is investigated through in situ techniques and simulations to draw correlations between the interphase compositions and electrochemical performances. The methylation strategy provides an alternative pathway for electrolyte engineering towards high-voltage electrolytes while reducing dependence on expensive fluorinated solvents.

25 ENERGY STORAGE↗
DOE OSTI2014

Energy resolved actinometry for simultaneous measurement of atomic oxygen densities and local mean electron energies in radio-frequency driven plasmas

A diagnostic method for the simultaneous determination of atomic oxygen densities and mean electron energies is demonstrated for an atmospheric pressure radio-frequency plasma jet. The proposed method is based on phase resolved optical emission measurements of the direct and dissociative electron-impact excitation dynamics of three distinct emission lines, namely, Ar 750.4 nm, O 777.4 nm, and O 844.6 nm. The energy dependence of these lines serves as basis for analysis by taking into account two line ratios. In this frame, the method is highly adaptable with regard to pressure and gas composition. Results are benchmarked against independent numerical simulations and two-photon absorption laser-induced fluorescence experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Functionally graded magnetic materials: a perspective to advance charged particle optics through compositional engineering

Additive manufacturing has ushered in a new paradigm of bottom-up materials-by-design of spatially non-uniform materials. Functionally graded materials have locally tailored compositions to provide optimized global properties and performance. In this letter, we propose an opportunity for the application of graded magnetic materials as lens elements for charged particle optics. A Hiperco50/Hymu80 (FeCo-2 V/Fe-80Ni-5Mo) graded magnetic alloy was successfully additively manufactured via Laser Directed Energy Deposition with spatially varying magnetic properties. The compositional gradient is then applied using computational simulations to demonstrate how a tailored material can enhance the magnetic performance of a critical, image-forming component of a transmission electron microscope.

36 MATERIALS SCIENCE↗
DOE OSTI2014

SU-E-T-578: MCEBRT, A Monte Carlo Code for External Beam Treatment Plan Verifications

Purpose: Present a new Monte Carlo code (MCEBRT) for patient-specific dose calculations in external beam radiotherapy. The code MLC model is benchmarked and real patient plans are re-calculated using MCEBRT and compared with commercial TPS. Methods: MCEBRT is based on the GEPTS system (Med. Phys. 29 (2002) 835–846). Phase space data generated for Varian linac photon beams (6 – 15 MV) are used as source term. MCEBRT uses a realistic MLC model (tongue and groove, rounded ends). Patient CT and DICOM RT files are used to generate a 3D patient phantom and simulate the treatment configuration (gantry, collimator and couch angles; jaw positions; MLC sequences; MUs). MCEBRT dose distributions and DVHs are compared with those from TPS in absolute way (Gy). Results: Calculations based on the developed MLC model closely matches transmission measurements (pin-point ionization chamber at selected positions and film for lateral dose profile). See Fig.1. Dose calculations for two clinical cases (whole brain irradiation with opposed beams and lung case with eight fields) are carried out and outcomes are compared with the Eclipse AAA algorithm. Good agreement is observed for the brain case (Figs 2-3) except at the surface where MCEBRT dose can be higher by 20%. This is due to better modeling of electron contamination by MCEBRT. For the lung case an overall good agreement (91% gamma index passing rate with 3%/3mm DTA criterion) is observed (Fig.4) but dose in lung can be over-estimated by up to 10% by AAA (Fig.5). CTV and PTV DVHs from TPS and MCEBRT are nevertheless close (Fig.6). Conclusion: A new Monte Carlo code is developed for plan verification. Contrary to phantombased QA measurements, MCEBRT simulate the exact patient geometry and tissue composition. MCEBRT can be used as extra verification layer for plans where surface dose and tissue heterogeneity are an issue.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

A novel approach to background subtraction in contrast-enhanced dual-energy digital mammography with commercially available mammography devices: Noise minimization

Purpose: Dual-energy image subtraction represents a useful tool to improve the detectability of small lesions, especially in dense breasts. A feature it shares with all x-ray imaging techniques is the appearance of fluctuations in the texture of the background, which can obscure the visibility of interesting details. The aim of the work is to investigate the main noise sources, in order to create a better performing subtraction mechanism. In particular, the structural noise cancellation was achieved by means of a suitable extension of the dual-energy algorithm. Methods: The effect of the cancellation procedure was tested on an analytical simulation of a target with varying structural composition. Subsequently, the subtraction algorithm was also applied to a set of actual radiographs of a breast phantom exhibiting a nonuniform background pattern. The background power spectra of the outcomes were computed and compared to the ones obtained from a standard subtraction algorithm. Results: The comparison between the standard and the proposed cancellations showed an overall suppression of the magnitudes of the spectra, as well as a flattening of the frequency dependence of the structural component of the noise. Conclusions: The proposed subtraction procedure provides an effective cancellation of the residual background fluctuations. When combined with the polychromatic correction already described in a companion publication, it results in a high performing dual-energy subtraction scheme for commercial mammography units.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Investigation of LSM-YSZ Composite Cathode Performance Degradation with a Multistep Charge Transfer Model

The long-term performance degradation of LSM/YSZ composite cathodes is investigated via calibrated multiphysics simulation with a multistep oxygen reduction reaction (ORR) model and structural coarsening data from a phase field study. Multiphysics simulations, including a multistep ORR mechanism, are first developed for better understanding of the limiting processes in solid oxide fuel cells. The multistep ORR mechanism includes two parallel pathways, surface pathway and bulk pathway, which consist of elementary reaction steps. The multiphysics model is simultaneously calibrated with experimental polarization curves and impedance behavior for various air/fuel supply conditions. To our knowledge, this is the first time that a multistep ORR model is calibrated with such datasets. Next, the calibrated simulations are utilized to simulate a 2D half-cell constructed with measured microstructural data and random heterogeneity. Finally, the long-term performance degradation of the half-cell is predicted by the calibrated multiphysics model coupled with structural coarsening trends simulated using a phase field-based coarsening model. Degradation of both polarization curves and impedance behavior is investigated. Thorough analyses, including changes of contributions from different pathways, the resistance components, and overall reaction order, are performed to provide more insights into cathode performance degradation due to grain coarsening phenomena.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Sulfur Solubility Testing and Characterization of LAW Phase 1 Matrix Glasses

In this report, the Savannah River National Laboratory (SRNL) provides chemical analysis results for a series of simulated low-activity waste (LAW) glass compositions. These data will be used in the development of improved sulfur solubility models for LAW glass. A procedure developed at Pacific Northwest National Laboratory (PNNL) for producing sulfur saturated melts (SSMs) was carried out at both SRNL and PNNL to fabricate the glasses characterized in this report. This method includes triplicate melting steps with excess sodium sulfate, followed by grinding and washing to remove unincorporated sulfur salts. The wash solutions were also analyzed as part of this study.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Percheron Power – Small Business Vouchers Pilot Program Technology Assistance Report

Battelle Memorial Institute, under U.S. Department of Energy Contract No. DE-AC05-76RL01830 to operate the Pacific Northwest National Laboratory (PNNL), agreed to provide technology assistance to Percheron Power in accordance with Small Business Vouchers Pilot Program Agreement project number 68798. This agreement w as designed to provide assistance to Percheron Power in performing modeling and simulations for the design and optimization of composite Archimedes hydrodynamic screw (AHS) turbines.

42 ENGINEERING↗
DOE OSTI2018

Sulfur Solubility Testing and Characterization of Hanford LAW Phase 2, Outer Layer Matrix Glasses

In this report, the Savannah River National Laboratory (SRNL) provides chemical analyses and Product Consistency Test (PCT) results for a series of simulated Low-Activity Waste (LAW) glass compositions. A procedure developed at the Pacific Northwest National Laboratory (PNNL) for producing sulfur saturated melts (SSMs) was carried out at both SRNL and PNNL to fabricate the glasses characterized in this report. This method includes triplicate melting steps with excess sodium sulfate, followed by grinding and washing to remove unincorporated sulfur salts. The wash solutions were also analyzed as part of this study. These data will be used in the development of improved property/composition models for LAW glass.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Sulfur Solubility Testing and Characterization of Hanford LAW Phase 2, Outer Layer Matrix Glasses

In this report, the Savannah River National Laboratory (SRNL) provides chemical analyses and Product Consistency Test (PCT) results for a series of simulated Low-Activity Waste (LAW) glass compositions. A procedure developed at the Pacific Northwest National Laboratory (PNNL) for producing sulfur saturated melts (SSMs) was carried out at both SRNL and PNNL to fabricate the glasses characterized in this report. This method inclu des triplicate melting steps with excess sodium sulfate, followed by grinding and washing to remove unincorporated sulfur salts. The wash solutions were also analyzed as part of this study. These data will be used in the development of improved property/composition models for LAW glass.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

High Temperature Silicon Carbide Receiver Tubes for Concentrating Solar Power

In order for Concentrating Solar Power plants (CSP) to achieve the desired cost breakpoint, significant improvement in performance is required resulting in the need to increase temperatures of fluid systems. A US DOE Small Business Voucher project was established at Sandia to explore the performance characteristics of Ceramic Tubular Products (CTP) silicon carbide TRIPLEX tubes in key categories relating to its performance as a solar receiver in next generation CSP plants. Along these lines, the following research tasks were completed : (1) Solar Spectrum Testing, (2) Corrosion Testing in Molten Chloride Salt, (3) Mechanical Shock Testing, and (4) Thermal Shock Testing. Through the completion of these four tasks, it has been found that the performance of CTP's material across all of these categories is promising, and merits further investigation beyond this initial investigation. Through 50 solar aging cycles, the CTP material exhibited excellent stability to high temperatures in air, exhibited at or above 0.95 absorptance, and had measured emittances within the range of 0.88-0.90. Through molten salt corrosion testing at 750°C it was found that SiC exhibits significantly lower mass change (— 90 times lower) than Haynes 230 during 108 hours of salt exposure. The CTP TRIPLEX material performed significantly better than the SiC monolithic tube material in mechanical shock testing, breaking at an average height of 3 times that for the monolithic tubes. Through simulated rain thermal shock testing of CTP composite tubes at 800°C it was found that CTP's SiC composite tubes were able to survive thermal shock, while the SiC monolithic tubes did not.

14 SOLAR ENERGY↗
DOE OSTI2019

NEAMS Workbench and Bison Fuel Performance Remote Application Configuration

The mission of the US Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program is to develop, apply, deploy, and support state-of-the-art predictive modeling and simulation tools for the design and analysis of current and future nuclear energy systems. This is accomplished using computing architectures that range from laptops to leadership class facilities. The NEAMS Workbench [1,2,3] initiative will facilitate the transition from conventional computer codes to high-fidelity ones by providing a common analysis environment and interface for model creation, review, execution, output review, and visualization for integrated codes. The BISON fuel performance code [4] is a finite element method (FEM)-based software being developed by multiple organizations led by the Idaho National Laboratory for the US Department of Energy Office of Nuclear Energy. BISON can simulate a variety of fuel and cladding compositions and geometries in varying dimensionalities, depending upon the problem type and complexity, including one-dimensional (1D), 1.5D, 2D axially symmetric (2D-rz), 2D radial-azimuthal (2D-rθ), or 3D models. The NEAMS Workbench allows execution of the BISON fuel performance code on local and remote compute resources. In this report, the detailed instructions of configuring the NEAMS Workbench for remote execution of the BISON fuel performance code on a portable batch system (PBS)-scheduled compute resource, as well the transfer of associated Bison files, is illustrated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗