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At least 613 records · Page 34

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DOE OSTI2025

A nonhydrostatic formulation for MPAS-Ocean

The Model for Prediction Across Scales-Ocean (MPAS-Ocean) is an open-source, global ocean model and is one component of a family of climate models within the MPAS framework, including atmosphere, sea-ice, and land-ice models. Here, in this work, a new formulation for the ocean model is presented that solves the nonhydrostatic, incompressible Boussinesq equations on an unstructured, staggered, z-level grid. The introduction of this nonhydrostatic capability is necessary for the resolution of internal wave dynamics and large eddy simulations. Compared to the standard, hydrostatic formulation, a nonhydrostatic pressure solver and a vertical momentum equation are added, where the PETSc (Portable Extensible Toolkit for Scientific Computation) library is used for the inversion of a large sparse system for the nonhydrostatic pressure. Numerical results on a stratified seiche, internal solitary wave, overflow and lock-exchange test cases are presented, and the parallel efficiency of the code is evaluated using up to 1024 processors.

3D Poisson equation↗

DOE OSTI2025

A nonhydrostatic formulation for MPAS-Ocean

3D Poisson equation↗

DOE OSTI2025

Lowering entry barriers to developing custom simulators of distributed applications and platforms with SimGrid

Researchers in parallel and distributed computing (PDC) often resort to simulation because experiments conducted using a simulator can be for arbitrary experimental scenarios, are less resource-, labor-, and time-consuming than their real-world counterparts, and are perfectly repeatable and observable. Many frameworks have been developed to ease the development of PDC simulators, and these frameworks provide different levels of accuracy, scalability, versatility, extensibility, and usability. Further, the SimGrid framework has been used by many PDC researchers to produce a wide range of simulators for over two decades. Its popularity is due to a large emphasis placed on accuracy, scalability, and versatility, and is in spite of shortcomings in terms of extensibility and usability. Although SimGrid provides sensible simulation models for the common case, it was difficult for users to extend these models to meet domain-specific needs. Furthermore, SimGrid only provided relatively low-level simulation abstractions, making the implementation of a simulator of a complex system a labor-intensive undertaking. In this work we describe developments in the last decade that have contributed to vastly improving extensibility and usability, thus lowering or removing entry barriers for users to develop custom SimGrid simulators.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Quasielastic $\overrightarrow{^{3}He}$ $(\overrightarrow{e},e′)$ asymmetry in the threshold region with a longitudinally polarized target

We report on the measurements of the double-spin asymmetry from electron- 3 He scattering in the threshold region of two- and three-body breakup of 3 He for 4-momentum transfer values of 0.1 and 0.2 (GeV/c) 2 . The measurement was done at Jefferson Lab using a polarized 3 He target with its spin aligned parallel to the beam direction. This asymmetry is sensitive to a combination of spin-dependent response functions not previously measured and may highlight differences in two body forces, meson-exchange currents and final-state interactions. The results of this measurement serve as a test of our understanding of few-body systems. When compared with calculations from plane wave impulse approximation and Faddeev calculations, we found that the latter, which use modern nuclear potentials and prescriptions for meson-exchange currents, demonstrate an overall good agreement with data.

Few-body nuclei↗

DOE OSTI2024

A High-Performance Discrete-Element Framework for Simulating Flow and Jamming of Moisture Bearing Biomass Feedstocks

We developed and verified a high-performance open-source discrete element method (DEM) solver with simultaneously-supported feedstock-specific interaction models, including bonded-sphere, liquid bridge, cohesion, and non-linear contact models. Our solver uses parallel data structures on hybrid central and graphics processing unit (CPU/GPU) architectures, with favorable strong scaling performance observed for large problem sizes comprised of (100 M particles), and 4X single-node GPU speedup. The particles for corn stover feedstock were conceptualized and calibrated based on experimental measurements and results. Sensitivity analyses demonstrate that the mass flow rate from a wedge hopper is governed primarily by moisture content, friction coefficient, and cohesion energy density. The model is used to reproduce experimentally observed hopper jamming results, highlighting that the experimental no-flow trends can only be achieved by using non-spherical particles, liquid bridge and cohesion models, highlighting the importance of using concurrent feedstock specialized models for the effective representation of biomass material handling problems.

bioenergy↗

DOE OSTI2025

Multi-GPU porting of a phase-change cascaded lattice Boltzmann method for three-dimensional pool boiling simulations

The Lattice Boltzmann method (LBM) has proven effective in simulating phase-change phenomena, such as melting, solidification, evaporation, and boiling. In this work, we develop a highly parallelized multi-GPU implementation of LBM for three-dimensional pool boiling simulations. The code is based on the OpenACC programming model, which enables the code to be deployed efficiently on multi-core CPUs, GPUs, and potentially other accelerators, without the need for architecture-specific rewrites. To support large-scale simulations, the domain is decomposed and distributed across multiple compute nodes using MPI. We demonstrate that the code exhibits excellent scaling properties, with ideal strong-scaling running with up to 256 GPUs on the MareNostrum5 cluster.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Bayesian Optimized Deep Ensemble for Uncertainty Quantification of Deep Neural Networks: a System Safety Case Study on Sodium Fast Reactor Thermal Stratification Modeling

Deep neural networks (DNNs) are increasingly important to scientific computing and engineering system simulations. Accurate uncertainty quantification (UQ) for DNNs is critical in safety-sensitive engineering domains. Traditional Deep Ensemble (DE) methods, while easy to implement, frequently suffer from poorly calibrated uncertainty estimates and limited predictive accuracy due to reliance on fixed architectures with varied weight initializations. To address these issues, we introduce a workflow that combines Bayesian Optimization (BO) and DE. The workflow is modular, scalable, and integrates parallel BO initialized with Sobol sequences to individually optimize the hyperparameters of each ensemble member. This method enhances ensemble diversity, improves predictive accuracy, and provides reliable uncertainty estimates. We evaluate the proposed BODE approach in a sodium fast reactor thermal stratification modeling case study, where we used a densely connected convolutional neural network to predict turbulent viscosity during the reactor transient with consideration of data noise. We benchmark its performance against several optimization approaches, including baseline deep ensemble, evolutionary algorithm-optimized ensemble, ensemble formed via random search combined with greedy selection, and a BO ensemble using random initialization. Here, our results demonstrate superior performance of the developed BODE approach. In noise-free scenarios, BODE notably reduces incorrect aleatoric uncertainty and significantly enhances predictive accuracy. Under conditions of 5% and 10% Gaussian noise, BODE adaptively quantifies uncertainty proportional to data noise, achieving up to an 80% reduction in root mean square error compared to baseline methods and producing well-calibrated prediction intervals.

Bayesian optimization↗

DOE OSTI2026

PyHydroGeophysX: An extensible open-source platform for integrating hydrological models with geophysical measurements

Hydrological models and geophysical measurements are widely used tools for understanding subsurface hydrological processes relevant to water resource management, yet they typically remain disconnected due to technical barriers. We present PyHydroGeophysX, an open-source Python platform bridging this gap by providing standardized interfaces between hydrological modeling software (MODFLOW, ParFlow) and geophysical simulation tools (PyGIMLi, SimPEG). The platform implements bidirectional workflows: translating hydrological outputs into simulated geophysical responses through petrophysical models, and extracting hydrological information from geophysical inversions. Key features include bidirectional workflow modules, configurable petrophysical models, time-lapse inversion with temporal regularization, parallel computing, and mesh utilities for property transfer between geophysical and hydrological grids. The modular architecture of PyHydroGeophysX enables researchers to incorporate additional models and methods, fostering broader adoption of integrated hydrogeophysical approaches. The software is freely available on GitHub and is intended for researchers and practitioners working at the intersection of hydrology and geophysics.

Hydrogeophysics↗

DOE OSTI2025

AquaMEND: Reconciling multiple impacts of salinization on soil carbon biogeochemistry

Soil salinization, exacerbated by climate change, poses a global threat to coastal ecosystem function and soil quality. Salinity influences carbon cycling through direct effects on microbial activity and indirect alterations to soil physicochemical properties including cation exchange, pH, and soil organic carbon availability. Current models inadequately represent these complexities, relying on linear reduction functions that overlook specific physicochemical changes induced by salinity. To address this gap, we propose an integrated model framework, AquaMEND, that combines microbial-explicit carbon decomposition and geochemical models. This model allows cation exchange and surface complexation processes to capture solute chemistry and nutrient availability in soils upon saltwater intrusion. Using response functions that capture salinity impacts on both salt-sensitive and salt-resistant microbial processes, AquaMEND simulates how the abiotic and biotic mechanisms work individually and collectively to regulate organic and inorganic pools and fluxes. Here, the parallel structure of aqueous and non-aqueous phases, together with microbial functions, result in a versatile model for solving dynamic coupling of organics, minerals and microbes under various environmental settings.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Heat transfer coefficients of moving particle beds from flow-dependent thermal conductivity and near-wall resistance

Accurate determination of heat transfer coefficients for flowing packed particle beds is essential to the design of particle heat exchangers and other thermal and thermochemical equipment. While such dense granular flows mostly fall into the well-known plug-flow regime, the discrete nature of granular materials alters the thermal transport processes in both the near-wall and bulk regions of flowing particle beds from their stationary counterparts. As a result, heat transfer correlations based on the stationary particle bed thermal conductivity could be inadequate for flowing particles in a heat exchanger. Most earlier works have achieved a reasonable agreement with experiments by treating granular heat transfer media as a plug-flow continuum with a near-wall thermal resistance in series. However, the thermal conductivity values of the continuum were often obtained from measurements on stationary beds owing to the difficulty of flowing bed measurements. In this work, it was found that the properties of a stationary bed are highly sensitive to the method of particle packing and there is a decrease in the particle bed thermal conductivity and increase in the near-wall thermal resistance, measured as an effective air gap thickness, on the onset of particle flow. These variations in thermal conductivity of stationary and flowing particle beds can lead to errors in heat transfer coefficient calculations. Therefore, the heat transfer coefficients for granular flows were calculated using experimentally determined flowing particle bed thermal conductivity and near-wall air gap for ceramic particles – CARBO CP 40/100 (mean diameter = 275 µm), HSP 40/70 (404 µm) and HSP 16/30 (956 µm); at velocities of 5–15 mm·s –1 ; and temperatures of 300–650 °C. The thermal conductivity and air gap values for CP 40/100 and HSP 40/70 were further used to calculate heat transfer coefficients across different particle bed temperatures and velocities for different parallel-plate heat exchanger dimensions. Furthermore, these calculations, which show good agreement with measured HTC values reported in literature, can be used as a guide for heat exchanger designs. Graphical abstract

14 SOLAR ENERGY↗

DOE OSTI2025

Rapid characterization and failure analysis of 6276 rooftop-harvested photovoltaic connectors

Photovoltaic (PV) connectors, which link modules in series and connect PV strings in parallel, have increasingly been recognized as a primary contributor to PV system failures and a source of numerous fire incidents. However, publicly available data on the rates and types of connector failures are scarce, primarily due to the proprietary nature of the information and the need for comprehensive analysis. This study represents the first large-scale investigation of harvested PV connectors, drawing from a dataset of 6276 connectors from residential rooftop solar systems across the United States. The outcome of this work is twofold: 1) we have established a rapid characterization method for large populations of harvested connectors, incorporating visual inspection, resistance measurements, and X-ray imaging; and 2) the analysis made possible by our rapid-processing method has revealed, for a population of connector models provided by a single rooftop installer, failure statistics and insights for various connector makes and models, installation practices, operating currents, and internal component displacements. This research identifies common failure modes that could be considered in future connector designs standards, and operations and maintenance practices, to ultimately improve the reliability of this vital component of PV infrastructure.

MC4↗

DOE OSTI2024

Insights into the interaction of nitrobenzene and the Ag(111) surface: A DFT study

Here, this study explores the potential of nitrobenzene as an anolyte material for nonaqueous redox flow batteries (RFBs) by theoretically examining its low-coverage adsorption behavior on neutral and charged Ag(111) model electrode surfaces. At the low coverage limit, DFT calculations show a preference for nitrobenzene to adsorb parallel to the surface, with the benzene ring and nitro group centered over HCP sites. Interactions between nitrobenzene and the surface were analyzed using induced charge density analysis, Bader charge analysis, and projected density of states (PDOS). It was found that nitrobenzene adsorbs primarily through van der Waals interactions with the surface. As nitrobenzene accumulates negative charge, the strength of adsorption diminishes. Understanding the electrode-electrolyte interface is crucial for enhancing RFB electrochemical performance, and this study sheds light on nitrobenzene's interaction with a model Ag electrode.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

The evolution of model Rh/Fe 3 O 4 (001) catalysts in hydrogen environments

Single metal atoms dispersed on oxides are a new emerging class of catalysts owing to their unique electronic and chemical properties. Here, in this study, we have prepared a series of model single-atom catalysts possessing well-characterized Rh sites that include Rh adatoms (Rh ad ), mixed surface layers with octahedrally-coordinated Rh (Rh oct ), as well as metallic Rh clusters and nanoparticles (Rh met ) on Fe 3 O 4 (001). Using X-ray photoelectron spectroscopy (XPS) and scanning tunneling microscopy (STM), we investigated the activity of such model systems towards H2 and their stability in reducing environments. Our results show that the atomically dispersed Rhad and Rhoct species do not activate H 2 , which would result in the formation of surface hydroxyls on Fe 3 O 4 (001). In contrast, the presence of Rh met in H 2 results in the formation of hydroxyls and subsequent etching of the Fe 3 O 4 (001) at higher temperatures (≥ 500 K) due to water formation via the Mars-van Krevelen mechanism. Additionally, such surface etching leads to the release of the Rh oct from the surface lattice and their sintering to Rh met . To bridge the material gap between the surface science models and high surface area catalysts, we perform parallel studies on powder Rh/Fe 3 O 4 catalysts. The XPS characterization shows remarkable similarities between these systems. Further, our surface science studies provide an atomistic picture of the behavior of high surface area catalysts in the H 2 atmosphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Effects of co-adsorbed water on different bond cleavages involved in acetic acid decomposition on Pt (111)

Acetic acid decomposition on Pt (111) in the presence of co-adsorbed water is a good model system for oxygenate decomposition on Pt (111) in aqueous phase, with application in hydrogen production and biomass conversion. Here, in this study, we present a density functional theory (DFT) theory calculation of how co-adsorbed water affects different bond cleavages of acetic acid decomposition on Pt (111). The presence of co-adsorbed water generally enhances O$-$H bond cleavage while inhibiting OC$-$O and OC$-$OH bond cleavage. The influence of co-adsorbed water on C$-$H bond cleavage varies the most and depends on the nature of the transition state and how co-adsorbed water stabilizes the initial and final state. Although these trends are useful as general guidance, they are not sufficient to predict the effect on a complex reaction network such as acetic acid decomposition on Pt (111) which has several parallel reaction paths with similar energies. In the absence of co-adsorbed water, the two lowest energy pathways are decarboxylation (DCX) and decarbonylation (DCN) pathways through a common CH 2 COO intermediate, in which the DCX pathway (C$-$H bond cleavage of CH 2 COO) is more favorable than DCN pathway (OC$-$O bond cleavage of CH 2 COO). In the presence of co-adsorbed water, the energy difference between Csingle bondH bond cleavage and OC$-$O bond cleavage of CH 2 COO increases, suggesting an increase in the favorability of acetic acid decarboxylation (formation of carbon dioxide) over acetic acid decarbonylation (formation of carbon monoxide) on Pt (111).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Pilot microbial electrolysis cell closes the hydrogen loop for hydrothermal wet waste conversion to jet fuel

The global shift toward net-zero emissions necessitates resource recovery from wet waste. In this study, we demonstrate the first feasibility of combining pilot-scale microbial electrolytic cells (MECs) with hydrothermal liquefaction (HTL) for simultaneous post-hydrothermal liquefaction wastewater (PHW) treatment and efficient hydrogen (H₂) production to meet biocrude upgrading requirements. Long-term single reactor operation revealed that fixed anode potential enabled rapid startup, and low catholyte pH and high salinity were effective in suppression of cathodic methanogenesis and acetogenesis – resulting in high current density of 16.6 A m –2 and 9.3 A m –2 when feeding synthetic wastewater and PHW respectively. Additionally, the anode biofilm exhibited spatial variations in response to local environmental conditions. In conclusion, onsite parallel or serial operations of multiple MECs showed good performance using actual PHW with a record-high H 2 production rate of 0.5 L L R day –1 for MEC over 10 liters scale, and the optimal chemical oxygen demand (COD)-to-H 2 yield reached 0.127 kg-H 2 per kg-COD, supporting a self-sufficient, closed-loop upgrade to jet fuel.

08 HYDROGEN↗

DOE OSTI2025

Reconfigurable structural color by reversible switching of colloidal discoid liquid crystal alignment

Combining the effects of alternating-current (AC) electric fields and sedimentation reconfigures colloidal discoids between planar and homeotropic orientational alignments, thereby controlling the material’s structural color. Here, we self-assemble micrometer-size polystyrene discoids in an isopropanol-water mixture. After sedimentation, the discoids adopt a homeotropic alignment, with the minor axis perpendicular to the substrate. Adding an AC electric field (1 kHz) of ≥0.50 V switches the discoids to planar alignment—with the minor axis parallel to the substrate—within ∼100 s. Removing the field switches them back to homeotropic alignment within ∼300 s. Kinetic modeling of the field-induced torques yields good agreement with these measurements. The peak wavelength and intensity of the crystal’s diffraction response shift significantly upon reconfiguration; scattering simulation predicts these shifts. The reconfiguration is maintained for at least 10 cycles. This method is a simple, scalable avenue to reconfigure the optical properties of colloidal crystals produced from simple dielectric spheroids.

colloidal crystals↗

DOE OSTI2024

Plasma potential shaping using end-electrodes in the Large Plasma Device

We perform experiments in the Large Plasma Device at the University of California, Los Angeles, studying how different end-electrode biasing schemes modify the radial potential profile in the machine. We impose biasing profiles of different polarities and gradient signs on a set of five concentric electrodes placed 12 m downstream from the plasma source. We find that imposing concave-down profiles (negative potential radial gradient) on the electrodes creates radial potential profiles halfway up the plasma column that are comparable to those imposed on the electrodes and a few electron temperature in height, regardless of the biasing polarity. On the other hand, imposing concave-up profiles (positive potential radial gradient) leads to non-monotonic radial potential profiles. This observation can be explained by the current drawn through the electrodes and the parallel plasma resistivity, highlighting their important role in controlling the rotation of plasma. Concave-down plasma potential profiles, obtained by drawing electrons on the axis, are predicted to drive azimuthal drift velocities that can approach significant fractions of the ion sound speed in the central region of the plasma column.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Particle-based modelling of axisymmetric tandem mirror devices

In this work, we describe the use of a 1D-2V quasi-neutral hybrid electrostatic PIC with Monte-Carlo Coulomb collisions and non-uniform magnetic field to model the parallel transport and confinement in an axisymmetric tandem mirror device. End-plugs, based on simple-mirrors, are positioned at each end of the device and fueled with neutral beams (25 and 100 keV) to produce a sloshing ion population and increase the density of the end-plugs relative to the central cell. Results show the formation of a potential difference barrier between the central cell and the end-plugs. This potential confines a large fraction of the low energy thermal ions in the central cell which would otherwise be lost in a simple mirror, demonstrating the advantage of the beam-driven tandem mirror configuration relative to simple mirrors. In addition, we explore the effect of end-plug electron temperature on the confinement time of the device and compare it with theoretical estimates. Finally, we discuss the limitations of the code in its present form and describe the next logical steps to improve its predictive capability such as a fully nonlinear Fokker–Planck collision operator, multiply nested flux surface solutions and modeling the exhaust region up to the wall.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗