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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Analysis of the weighted shifted boundary method for the Poisson and Stokes problems

The Shifted Boundary Method (SBM) belongs to the class of unfitted (or immersed, or embedded) finite element methods, and relies on reformulating the original boundary value problem over a surrogate (approximate) computational domain. Accuracy is maintained by properly shifting the location and values of the boundary conditions. This avoids integration over cut cells and the associated implementation issues. Recently, the Weighted SBM (WSBM) was proposed for the Navier-Stokes equations with free surfaces and the Stokes flow with moving boundaries. The attribute “weighted” in the name WSBM stems from the fact that its variational form is weighted with the elemental volume fraction of active fluid. The motivation for the development of the WSBM was the preservation of the volume of active fluid to a higher degree of accuracy, which in turn resulted in improved stability and robustness characteristics in moving-boundary, time-dependent simulations. In this article, we present the numerical analysis of the WSBM formulations for the Poisson and Stokes problems. We give mathematical conditions under which the bilinear forms defining the discrete variational formulations are uniformly coercive (Poisson problem) or inf-sup stable (Stokes problem). By these results, stability and optimal convergence is proven in the natural norm; L2-error estimates can also be derived.

Approximate domain boundaries↗
DOE OSTI2022

Determining the kinetic rate constants of Fe 3 O 4 -to-Fe and FeO-to-Fe reduction by H 2

Steel production using coal accounts for ~ 8% of global carbon emissions. “Green Steel” is a new grand concept proposed recently to make steel from iron ores using renewable derived “Green Hydrogen” to achieve zero carbon emission. The kinetics and rate-limiting steps of iron ore reduction into iron with H 2 as a reducing agent is critically important to the success of this new technology. While reduction of Fe 2 O 3 into Fe by H 2 follows multiple steps, the past research on this topic mainly deals with the overall averaged kinetics, giving little information on the elemental and rate-limiting steps. In this work, we report a kinetic study specifically design to attain kinetic rate constants of one-step reduction of Fe 3 O 4 -to-Fe and FeO-to-Fe. Guided by thermodynamics, we show first how to create in situ the desirable starting oxide phases, i.e., Fe 3 O 4 and FeO, with precisely controlled the ratio of partial pressures of H 2 O and H 2 . We then show time-dependent raw H 2 O content data collected by a mass spectrometer and the processed reduction data to extract kinetic rate constants. We found that the kinetics of the two one-step reduction reactions follows nicely the Johnson-Mehl-Avrami (JMA) phase transformation model. The one-step reduction mechanisms and activation energy are also discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Three-dimensional feature matching improves coverage for single-cell proteomics based on ion mobility filtering

Single-cell proteomics (scProteomics) promises to advance our understanding of cell functions within complex biological systems. However, a major challenge of current methods is their inability to identify and provide accurate quantitative information for low abundance proteins. Herein, we describe an ion mobility-enhanced mass spectrometry acquisition and peptide identification method, TIFF (Transferring Identification based on FAIMS Filtering), to improve the sensitivity and accuracy of label-free scProteomics. TIFF extends the ion accumulation times for peptide ions by filtering out singly charged ions. The peptide identities are assigned by a three-dimensional MS1 feature matching approach (retention time, accurate mass, and FAIMS compensation voltage). TIFF method enabled unbiased proteome analysis to a depth of >1,700 proteins in single HeLa cells with >1,100 proteins consistently identified. As a demonstration, we applied the TIFF method to obtain temporal proteome profiles of >150 single murine macrophage cells during lipopolysaccharide stimulation and identified time-dependent proteome changes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Smoothed boundary method for simulating incompressible flow in complex geometries

Simulating flow through porous media with explicit considerations of complex microstructures is very challenging using conventional sharp-interface methods because of the difficulties in generating meshes conformal to complex geometries. In this work, a diffuse interface embedded boundary method known as the Smoothed Boundary Method (SBM) is utilized to facilitate simulations of fluid dynamics involving complex geometries. In diffuse-interface methods, the geometry is described by a domain parameter. The SBM allows the straightforward reformulation of the time-dependent Navier-Stokes equations in terms of this domain parameter, using only algebraic identities. Thus, enforcing the appropriate boundary conditions at the irregular embedded boundary is greatly simplified. Adaptive mesh refinement is used to increase the accuracy of the diffuse interface method by allowing thinner interfacial thickness to be used in the domain parameter. Here, the SBM-formulated Navier-Stokes equations are solved with the Finite Difference Method on refined mesh systems. Sharp-interface Finite Element Method simulations using the commercial software COMSOL on body-conforming meshes are also provided for comparison. Favorable agreement between the two methods is observed. Since it is no longer necessary for the mesh to conform to the complex geometry, the grid system for the SBM simulations can be generated rapidly and without additional manual interventions, making the entire simulation process more expedient.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Bayesian operator inference for data-driven reduced-order modeling

This work proposes a Bayesian inference method for the reduced-order modeling of time-dependent systems. Informed by the structure of the governing equations, the task of learning a reduced-order model from data is posed as a Bayesian inverse problem with Gaussian prior and likelihood. The resulting posterior distribution characterizes the operators defining the reduced-order model, hence the predictions subsequently issued by the reduced-order model are endowed with uncertainty. The statistical moments of these predictions are estimated via a Monte Carlo sampling of the posterior distribution. Since the reduced models are fast to solve, this sampling is computationally efficient. Furthermore, the proposed Bayesian framework provides a statistical interpretation of the regularization term that is present in the deterministic operator inference problem, and the empirical Bayes approach of maximum marginal likelihood suggests a selection algorithm for the regularization hyperparameters. The proposed method is demonstrated on two examples: the compressible Euler equations with noise-corrupted observations, and a single-injector combustion process.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Simulation and analysis of small angle scattering (SAS) patterns of Ni-based superalloy microstructures generated by a phase-field model

This paper investigates the relationship between microstructural features and small-angle scattering (SAS) patterns in Ni-based superalloys using a combined phase-field and SAS simulation approach coupled with microstructure analyses. The simulated SAS patterns accurately capture key experimental observations previously reported in the literature, including the time-dependent transition from circular to square-shaped precipitates and the development of anisotropic SAS patterns. Importantly, our analysis reveals the correlations between characteristic length scales extracted from SAS profiles and microstructural descriptors, such as precipitate size and inter-precipitate distance. These findings provide a comprehensive understanding of the link between SAS profiles and microstructure evolution in Ni-based superalloys, offering valuable insights for materials characterization and design.

Microstructure↗
DOE OSTI2020

A reconstructed discontinuous Galerkin method for compressible flows in Lagrangian formulation

In this work, a high-order accurate reconstructed discontinuous Galerkin (rDG) method is developed for solving two-dimensional hydrodynamic problems in cell-centered updated Lagrangian formulation. This method is the Lagrangian limit of the unsplit rDG-ALE formulation, and is obtained by assuming the equality of the grid velocity to the fluid velocity only at cell boundaries. The conservative variables and the Taylor basis defined on the time-dependent moving mesh, provide the piece-wise polynomial expansion in the updated Lagrangian formulation. A multi-directional nodal Riemann solver is implemented for computing the grid velocity at the vertices and the numerical flux at the cell boundaries. A characteristic limiting procedure is extended from the primitive variable version to the conservative variable version, and its performance is compared with the limiter on physical variables. A number of benchmark test cases are conducted to assess the accuracy, robustness, and non-oscillatory property of the DG(P0), DG(P1) and rDG(P1P2) methods. The numerical experiments demonstrate that the developed rDG method is able to attain the designed order of accuracy and the characteristic limiting procedure outperforms the limiter on physical variables in terms of the monotonicity and symmetry preservation for shock problems.

42 ENGINEERING↗
DOE OSTI2025

Exploring the impact of hydro-mechanical coupling on compaction localization

In deep subsurface environments, where porous rocks are saturated with fluids, hydromechanical coupling plays a critical role in the formation and propagation of localized deformation zones, such as compaction bands. In this study, we numerically investigate the influence of fluid-rock interactions on the development of compaction localization in fluid-saturated rocks. For this purpose, it uses a numerical framework that adapts the heat equation to model the diffusion of pore pressure caused by deformation. This is achieved with specialized subroutines for material behavior and heat transfer formulated within the ABAQUS platform and by allowing changes in rock permeability during strain localization. The results highlight that hydromechanical coupling significantly alters the compaction behavior compared to dry conditions. Under high confining stress, excess pore pressure inhibits the progression of compaction fronts, while in time-dependent processes like rock creep, pore pressure transients accelerate deformation by creating feedback loops between mechanical forces and fluid flow. These findings underscore the importance of saturation in controlling the dynamics of compaction localization and provide insights into the interplay between pore pressure, deformation, and permeability. The implications of this study extend to applications in geological storage, resource extraction, and subsurface geomechanics, offering a deeper understanding of coupled hydromechanical processes in porous rocks.

58 GEOSCIENCES↗
DOE OSTI2024

Poromechanical cohesive interface element with combined Mode I-II cohesive zone elastoplasticity for simulating fracture in fluid-saturated porous media

A combined Mode I-II cohesive zone (CZ) elasto-plastic constitutive model, and a two-dimensional (2D) cohesive interface element (CIE) are formulated and implemented at small strain within an ABAQUS User Element (UEL) for simulating 2D crack nucleation and propagation in fluid-saturated porous media. Here, the CZ model mitigates problems of convergence for the global Newton-Raphson solver within ABAQUS, which when combined with a viscous stabilization procedure allows for simulation of post-peak response under load control for coupled poromechanical finite element analysis, such as concrete gravity dam stability analysis. Verification examples are presented, along with a more complex ambient limestone-concrete wedge fracture experiment, water-pressurized concrete wedge experiment, and concrete gravity dam stability analyses. A calibration procedure for estimating the CZ parameters is demonstrated with the limestone-concrete wedge fracture process. For the water-pressurized concrete wedge fracture experiment it is shown that the inherent time-dependence of the poromechanical CIE analysis provides a good match with experimental force versus displacement results at various crack mouth opening rates, yet misses the pore water pressure evolution ahead of the crack tip propagation. This is likely a result of the concrete being partially-saturated in the experiment, whereas the finite element analysis assumes fully water saturated concrete. For the concrete gravity dam analysis, it is shown that base crack opening and associated water uplift pressure leads to a reduced Factor of Safety, which is confirmed by separate analytical calculations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

An Eulerian Vlasov-Fokker–Planck algorithm for spherical implosion simulations of inertial confinement fusion capsules

Here, we present a numerical algorithm that enables a phase-space adaptive Eulerian Vlasov–Fokker–Planck (VFP) simulation of inertial confinement fusion (ICF) capsule implosions. The approach relies on extending a recent mass, momentum, and energy conserving phase-space moving-mesh adaptivity strategy to spherical geometry. In configuration space, we employ a mesh motion partial differential equation (MMPDE) strategy while, in velocity space, the mesh is expanded/contracted and shifted with the plasma’s evolving temperature and drift velocity. The mesh motion is dealt with by transforming the underlying VFP equations into a computational (logical) coordinate, with the resulting inertial terms carefully discretized to ensure conservation. To deal with the spatial and temporally varying dynamics in a spherically imploding system, we have developed a novel nonlinear stabilization strategy for MMPDE in the configuration space. The strategy relies on a nonlinear optimization procedure that optimizes between mesh quality and the volumetric rate change of the mesh to ensure both accuracy and stability of the solution. Implosions of ICF capsules are driven by several boundary conditions: (1) an elastic moving wall boundary; (2) a time-dependent Maxwellian Dirichlet boundary; and (3) a pressure-driven Lagrangian boundary. Of these, the pressure-driven Lagrangian boundary driver is new to our knowledge. The implementation of our strategy is verified through a set of test problems, including the Guderley and Van-Dyke implosion problems — the first-ever reported using a Vlasov–Fokker–Planck model.

1D2V↗
DOE OSTI2023

Hermes-3: Multi-component plasma simulations with BOUT++

A new open source tool for fluid simulation of multi-component plasmas is presented, based on a flexible software design that is applicable to scientific simulations in a wide range of fields. Hermes-3 is built on plasma simulation framework BOUT++, consolidating earlier SD1D and Hermes models into a single code that can be configured at run-time to solve plasma models in 1D, 2D or 3D, either for transport (steady-state) or turbulent (time-evolving) problems, with an arbitrary number of ion and neutral species. Here, we describe the improved numerical algorithms and software design that have been implemented in Hermes-3. To demonstrate the capabilities of this tool, applications relevant to the boundary of tokamak plasmas are presented: 1D simulations of diveror plasmas evolving equations for all charge states of neon and deuterium; 2D transport simulations of tokamak equilibria in single-null X-point geometry with plasma ion and neutral atom species; and simulations of the time-dependent propagation of plasma filaments (blobs). Hermes-3 is publicly available on Github under the GPL-3 open source license. The repository includes documentation and a suite of unit, integrated and convergence tests.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

An improved methodology for modeling short pulse buried layer x-ray emission spectra

Radiation-hydrodynamic and spectroscopic modeling are important aspects of high energy density experimental design. In this paper, we improve the performance and capabilities over those obtainable with a previous methodology used for simulating x-ray emission spectra from buried layer targets heated by short pulse lasers. The improvement incorporates post-processing HYDRA radiation-hydrodynamic output with a non-local thermodynamic equilibrium atomic-kinetics radiation transport code, Cretin. Each code uses an independent radiation field which allows decoupling HYDRA's radiation group structure from Cretin's spectral output to improve the speed and flexibility of the design methodology. The execution time decreases from 2–3 days to a few hours while the flexibility of the improved methodology allows for performing sensitivity studies including a comparison of steady-state and time-dependent atomic kinetics and differences in the radiation group structure.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

The TDHF code Sky3D version 1.2

The Sky3D code has been widely used to describe nuclear ground states, collective vibrational excitations, and heavy-ion collisions. The approach is based on Skyrme forces or related energy density functionals. The static and dynamic equations are solved on a three-dimensional grid, and pairing is been implemented in the BCS approximation. This updated version of the code aims to facilitate the calculation of nuclear strength functions in the regime of linear response theory, while retaining all existing functionality and use cases. The strength functions are benchmarked against available RPA codes, and the user has the freedom of choice when selecting the nature of external excitation (from monopole to hexadecapole and more). Some utility programs are also provided that calculate the strength function from the time-dependent output of the dynamic calculations of the Sky3D code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Test of model of equivalence of tree height growth and transpiration rates in percolation-based phenomenology for root-soil interaction

We recently introduced a phenomenological model to represent root-soil interactions that accounts for variability in tree growth on local scales and within species (Hunt et al., 2020). Here, using publicly available datasets, we examine the developed model to provide additional empirical evidence, which also gives novel insight into two particular tree species, Eucalyptus regnans and Eucalyptus sieberri. In particular, we discovered two novel aspects of the model: a power-law time dependence with a different power-law exponent than usually heretofore applied, and apparently a direct equivalence of results for transpiration and growth rates. Also, although our original expectation was that growth and transpiration were merely proportional, comparison of the entire BAAD data set (Falster et al., 2015) for tree height with our model (Hunt et al., 2020; Fig. 1) already suggested approximate equality of these disparate measurements (volume/area, height). In this present manuscript we find further evidence for equivalence of the two measurements and provide additional theoretical basis for a model assumption regarding constancy of sap flow rates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Physics-informed State-space Neural Networks for transport phenomena

This work introduces Physics -informed State -space neural network Models (PSMs), a novel solution to achieving real-time optimization, flexibility, and fault tolerance in autonomous systems, particularly in transportdominated systems such as chemical, biomedical, and power plants. Traditional data -driven methods fall short due to a lack of physical constraints like mass conservation; PSMs address this issue by training deep neural networks with sensor data and physics -informing using components' Partial Differential Equations (PDEs), resulting in a physics -constrained, end -to -end differentiable forward dynamics model. Further, through two in silico experiments - a heated channel and a cooling system loop - we demonstrate that PSMs offer a more accurate approach than a purely data -driven model. In the former experiment, PSMs demonstrated significantly lower average root -mean -square errors across test datasets compared to a purely data -driven neural network, with reductions of 44 %, 48 %, and 94 % in predicting pressure, velocity, and temperature, respectively. Beyond accuracy, PSMs demonstrate a compelling multitask capability, making them highly versatile. In this work, we showcase two: supervisory control of a nonlinear system through a sequentially updated state -space representation and the proposal of a diagnostic algorithm using residuals from each of the PDEs. The former demonstrates PSMs' ability to handle constant and time -dependent constraints, while the latter illustrates their value in system diagnostics and fault detection.

42 ENGINEERING↗
DOE OSTI2021

A tool for assessing demand side management and operating strategies for isolated microgrids

Globally, power system operators are exploring ways to leverage the capabilities of smart meters to implement fine-grained demand side management (DSM). Here this paper presents a new simulation tool to evaluate operating strategies for smart-meter-enabled (SME) islanded microgrids being advanced for sustainable rural electrification in emerging economies. Based on MATLAB/Simulink, the tool's component-level models of small microgrids can be easily configured. Alternative rule-based operating strategies are implemented with controllable supply and storage components as well as other components driven by external factors (e.g., weather and time of day). To account for the wide range of possible operating conditions in real-world applications, statistical metrics can be evaluated using Monte Carlo (MC) methods based on user-defined, time-dependent probability distributions for demands, supplies, and environmental variables. Features of the tool are demonstrated with case studies for a representative microgrid in rural Rwanda.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Total cost of ownership of vehicle electrification and fuel switching options for light-duty and heavy-duty vehicles

Projecting the transition from combustion engines to battery-based powertrains is complex becuase it involves numerous interdependent decisions. This study estimates total cost of ownership (TCO) to assess the economic viability of powertrain electrification, focusing exclusively on advances in vehicle and fuel technologies. Under two bounding technology-progress scenarios, we develop vehicle designs and fuel cost trajectories, which serve as inputs to TCO projections for selected classes from 2021 to 2050. We analyzed a small sport utility vehicle (SUV) to represent the light-duty vehicle (LDV) sector, and four medium- and heavy-duty vehicle (MHDV) classes: Class 6 box delivery, Class 8 drayage, Class 8 long-haul, and Class 8 transit bus. For each class, we compared the TCO of battery electric vehicles (BEVs) and fuel cell hybrid electric vehicles (FCHEVs) against conventional internal combustion engine vehicles (ICEVs). The results show that modern ICEVs generally have lower TCO; however, BEVs and FCHEVs could match or have lower TCOs than ICEVs over time, depending on technological progress. In LDVs, BEV300 is projected to deliver the lowest TCO by 2050, particularly under the high-progress scenario. In MHDVs, both BEVs and FCHEVs could become more cost-competitive than ICEVs by 2050 in the high-progress case. Beyond these results, the findings suggest further investigation is warranted for BEV charging infrastructure, FCHEV hydrogen refueling infrastructure, and MHDV charging strategies. In conclusion, these factors could reduce the fuel-cost share of TCO and enhance the competitiveness of BEVs and FCHEVs relative to ICEVs.

Battery electric vehicle↗