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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Neutronics and Thermo-Fluids Simulation of Generic Pebble-Bed Fluoride-Salt-Cooled High-Temperature Reactor

The fluoride-salt-cooled high-temperature reactor (FHR) is one of the advanced reactors that has been attracting considerable interest from both the research community and the nuclear industry. To help facilitate the nuclear community's familiarity with the FHR, Kairos Power has developed a generic FHR (gFHR) benchmark. In the research performed here, this benchmark was used to assess innovative modeling methods that combine stochastic and deterministic computer codes to perform the design and analysis of the gFHR. Further, the Monte Carlo code Serpent 2 was used to generate few-group cross sections that were then used in the neutron diffusion and thermal-fluids code AGREE to perform full-core neutronics and thermal-fluids steady-state and transient core analysis. The Argonne National Laboratory code SAM was then used to model the gFHR system and to simulate the load-follow operation of the gFHR.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

A projection-based analytical Jacobian framework for chemical kinetics applications

A major challenge in simulating complex combustion systems with detailed chemical kinetic models is the cost of integrating the chemical source terms, often done using stiff ODE solvers that require frequent Jacobian evaluations. Using analytically derived Jacobian matrices instead of divided-difference-based numerical Jacobian approximations can significantly reduce the associated computational cost. However, ambiguities arise in the formulation of analytical Jacobians because the chemical state of the system, or state vector, can be expressed in multiple ways, involving variables that are typically not independent from one another. Here, in this work, the consequences of those ambiguities on practical calculations are characterized in detail, and a generalized, projection-based framework is proposed as a mitigation strategy. Performances are assessed in a series of test cases involving a variety of configurations and numerical solution approaches. Results show that with proper treatment, commonly used analytical Jacobian formulations can be considered as equivalent for practical purposes, thereby alleviating concerns that the state vector chosen to express the governing equations and corresponding analytical Jacobian may significantly impact the accuracy of the simulations.

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

Quasi-Lindblad pseudomode theory for open quantum systems

Here, we introduce a new framework to study the dynamics of open quantum systems with linearly coupled Gaussian baths. Our approach replaces the continuous bath with an auxiliary discrete set of pseudomodes with dissipative dynamics, but we further relax the complete positivity requirement in the Lindblad master equation and formulate a quasi-Lindblad pseudomode theory. We show that this quasi-Lindblad pseudomode formulation directly leads to a representation of the bath correlation function in terms of a complex weighted sum of complex exponentials, an expansion that is known to be rapidly convergent in practice and thus leads to a compact set of pseudomodes. The pseudomode representation is not unique and can differ by a gauge choice. When the global dynamics can be simulated exactly, the system dynamics is unique and independent of the specific pseudomode representation. However, the gauge choice may affect the stability of the global dynamics, and we provide an analysis of why and when the global dynamics can retain stability despite losing positivity. We showcase the performance of this formulation across various spectral densities in both bosonic and fermionic problems, finding significant improvements over conventional pseudomode formulations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files

This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification. In this study, a machine-learning-assisted computational framework is presented to identify High-Temperature Reservoir Thermal Energy Storage (HT-RTES) site with optimal performance metrics by combining physics-based simulation with stochastic hydrogeologic formation and thermal energy storage operation parameters, artificial neural network regression of the simulation data, and genetic algorithm-enabled multi-objective optimization. A doublet well configuration with a layered (aquitard-aquifer-aquitard) generic reservoir is simulated for cases of continuous operation and seasonal-cycle operation scenarios. Neural network-based surrogate models are developed for the two scenarios and applied to generate the Pareto fronts of the HT-RTES performance for four potential HT-RTES sites. The developed Pareto optimal solutions indicate the performance of HT-RTES is operation-scenario (i.e., fluid cycle) and reservoir-site dependent, and the performance metrics have competing effects for a given site and a given fluid cycle. The developed neural network models can be applied to identify suitable sites for HT-RTES, and the proposed framework sheds light on the design of resilient HT-RTES systems. All the simulations and the neural network model were done by Idaho National Laboratory. A detailed description of the work was reported in publication linked below.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Pele: An Exascale-Ready Suite of Combustion Codes

High fidelity simulations of realistic combustion devices are extremely demanding computationally because of the requirements to capture complex fuel chemical decomposition, its intricate interactions with turbulent, often multiphase, flows, and the wide separation of space and time scales between the thin flame and the device boundaries. Software required to carry out such computations tends to be extremely complex, particularly when designed to exploit hardware accelerators, and can be difficult to port and maintain. We present Pele, a performance portable suite of tools for the simulation of combustion systems, including codes to evolve reactive multiphase configurations in the low Mach number and compressible flow regimes, along with a set of inter-compatible post processing and in situ analysis tools. The Pele suite of tools is built on top of the AMReX framework for block-structured adaptive mesh refinement, which provides efficient data structures and algorithms that enable the development of a wide variety of efficient mesh and particle based PDE integration schemes. A hierarchical MPI+X parallelism scheme supports CPU-only and accelerated architectures, where X can be OpenMP, CUDA, and HIP based approaches for intra-node computational work distribution. The algorithms and data structures underlying the Pele simulation and analysis tools are highly scalable and performant across a wide variety of high-performance computing platforms, including DOEs newest exascale-class machines, Frontier and Aurora. The simulation and analysis tools are fully documented and freely distributed as open source via GitHub. We present key algorithmic and software challenges, solution strategies, performance and resulting set of capabilities.

AMReX↗
DOE OSTI2023

East African Monsoon as a Drawbridge for the Circumnavigation of Madden–Julian Oscillation Events

The seasonality of circumnavigation of Madden-Julian Oscillation (MJO) events is examined using 42 years of observations and global model simulations. MJO events are most likely to propagate across the Atlantic Ocean, Africa and back to equatorial Indian Ocean relatively unweakened during March-April-May and to a lesser extent in October-November-December. These seasons correspond to the "long-rain" and "short-rain" periods of East African monsoon when precipitation over Africa is near the equator and extend farthest east toward Indian Ocean. Moisture budget analysis of a circumnavigating MJO event under real and hypothetical seasonally varying background conditions indicates that the seasonal zonal movement of zonal component of background circulation regulates the moistening of MJO crossing from Eastern Africa to Indian Ocean. Ensembles of Energy Exa-scale Earth System Model (E3SM) simulations of the MJO event under idealized seasonally varying background state confirm the observed drawbridge-like role of East African monsoon in the propagation of MJO.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Fusion Intelligence: A Paradigm for Merging Natural and Artificial Intelligence

Here, this article presents fusion intelligence (FI), a bio-inspired paradigm that synergistically integrates the intrinsic capabilities of intelligent biological organisms with the advanced potential of artificial intelligence (AI)-driven systems. FI harnesses the unique intelligence, sensing, actuation, and mobility attributes of living organisms, such as honeybees, blending these with the sophisticated data-driven problem-solving functionalities of AI. By bridging the gap between natural intelligence (NI) and AI, FI can transform how humans interact with and harness the capabilities of both natural and artificial systems. This article presents the model of FI and its application to solve practical problems, discusses the challenges and future directions of FI research, emphasizing a generalized approach to solve complex problems, where AI can observe/control NI in a closed-loop system. We demonstrate the potential for FI to enhance the performance of an agricultural IoT system via a simulated case study, which achieves 50% improvement in the efficacy of insect pollination (entomophily).

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Grid Spacing Sensitivities of Simulated Mid-Latitude and Tropical Mesoscale Convective Systems in the Convective Gray Zone

The main objective of this study is to observationally constrain processes in tropical and midlatitude mesoscale convective systems (MCSs), and to use these constraints for model evaluation. To accomplish this, we leverage MCS observations collected at the U.S. DOE Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in Oklahoma and ARM's mobile GoAmazon2014/15 site in Manaus, Brazil (MAO). We simulate 13 and 11 of these observed MCSs at the SGP and MAO site, respectively, using the Weather Research and Forecasting model at 12-, 4-, 2-, and 1-km horizontal grid spacing. Observations from radiosondes, surface meteorology, and radar wind profilers are used to characterize MCS properties, such as MCS timing and location, cold pools, and convective drafts, and evaluate these simulations. SGP cases are found in better agreement with observations than MAO cases, and when simulated at 2 km, outperform simulations at 1 km regarding the timing of MCS overpass and the accuracy of surface variable trends. MAO simulations suggest a consistent improvement in model accuracy with increasing model resolution in depicting the downdraft structure, the timing of MCSs, and the surface variables changes, except for the latter two metrics at 2 km. Deficiencies are still evident at km-scales, suggesting the need for higher resolution to simulate tropical MCSs. Overall, location-dependent improvements in MCS representation are obtained with the increasing model resolution, prompting the evaluation of sub-km scale simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Accurate Hellmann–Feynman forces from density functional calculations with augmented Gaussian basis sets

The Hellmann–Feynman (HF) theorem provides a way to compute forces directly from the electron density, enabling efficient force calculations for large systems through machine learning (ML) models for the electron density. The main issue holding back the general acceptance of the HF approach for atom-centered basis sets is the well-known Pulay force which, if naively discarded, typically constitutes an error upward of 10 eV/Å in forces. In this work, we demonstrate that if a suitably augmented Gaussian basis set is used for density functional calculations, the Pulay force can be suppressed, and HF forces can be computed as accurately as analytical forces with state-of-the-art basis sets, allowing geometry optimization and molecular dynamics to be reliably performed with HF forces. Our results pave a clear path forward for the accurate and efficient simulation of large systems using ML densities and the HF theorem.

Pathak, Shivesh (ORCID:0000000172798195)↗
DOE OSTI2026

Approximation of refrigerant thermophysical properties using neural networks to speed up transient thermofluid simulations

Accurate and efficient evaluations of refrigerant thermophysical properties and their partial derivatives are essential for transient simulations of thermofluid systems, where several computations need to be executed at each integration time step. Since the utilization of an Equation of State for retrieving properties based on a pair of independent inputs typically involves numerical iterations in solution procedures, when the input variables differ from the refrigerant state variables employed in dynamic models, a variety of approaches including lookup table interpolation and curve fitting have been developed to explicitly approximate these properties based on the state variables, and consequently eliminate internal iterations. This paper presents an alternative method that exploits derivative-informed neural networks to model refrigerant properties explicitly from inputs of pressure and enthalpy, while ensuring consistent partial derivatives generated by differentiating the neural networks. Computational speed and accuracy of the proposed approach are demonstrated via transient simulations of a discretized heat exchanger model in Modelica, and comparisons against other property evaluation routines. Simulation results indicate that the proposed approach can realize a significant speedup with negligible discrepancies in predicted transients. The method is implemented in an open-source Modelica library.

Ma, Jiacheng↗
DOE OSTI2024

Conceptual design of a Doppler spectrometer for 102 m/s cross-field flows in tokamak divertors

The cross-field transport in the scrape-off-layers (SOLs) and divertors in tokamaks is of a similar size to the poloidal component of the parallel flow, thereby significantly impacting the plasma transport there. However, its direct observation has been challenging because the drift velocity (102–103 m/s) is significantly below the detection limit of conventional diagnostics. To realize cross-field ion flow measurement, a variety of systematic uncertainties in the system must be narrowed down. Here, we develop a conceptual design of the Doppler spectrometry that enables us to measure the impurity flows with 102-m/s accuracy based on an in situ wavelength-calibration technique developed in the astrophysics field, the iodine-cell method. We discuss its properties and applicability. In particular, the scaling relation between wavelength accuracy and various spectroscopic parameters is newly presented, which suggests the high importance of the wavelength resolution of the system. Based on transport simulations for the JT-60SA divertor, the feasibility of the system is assessed.

Fujii, Keisuke↗
DOE OSTI2025

Spectral Clustering-Based Partitioning of Large-Scale Power Electronics-Based Power Systems for Small-Signal Stability Analysis

The nodal admittance matrix (NAM)-based approach is well-suited for small-signal stability analysis of large-scale power electronics-based power systems (PEPSs), as it preserves the system structure through its admittance matrix. Previous studies have explored partitioning such systems into subareas and interconnections to reduce computational burden; however, they lacked a formal algorithmic procedure for determining feasible partitions. While several grid partitioning methods, such as those based on graph theory or machine learning, exist in the literature, they cannot be directly applied to NAM-based analysis due to differing objectives and constraints. Here, this paper addresses this gap by presenting a systematic, step-by-step procedure for applying a spectral partitioning algorithm that yields a division of the system into subareas suitable for NAM-based analysis. The computational complexity of the proposed method is also derived to demonstrate its efficiency and justify the practicality of the resulting subarea decomposition. The performance of the partitioning method is evaluated by applying the spectral clustering-derived subareas and interconnections to the NAM-based partitioning approach on a 140-bus system. Computational times for the full-system and partitioned NAM analyses are compared using MATLAB. Additionally, PSCAD simulations of the complete system and partitioned subareas are carried out to verify the effectiveness of the proposed method.

Nupur [Univ. of Tennessee, Knoxville, TN (United S↗
DOE OSTI2024

Synergistic Integration of Multiple Wave Energy Converters with Adaptive Resonance and Offshore Floating Wind Turbines through Bayesian Optimization

We developed a synergistic ocean renewable system where an array of Wave Energy Converters (WEC) with adaptive resonance was collocated with a Floating Offshore Wind Turbine (FOWT) such that the WECs, capturing wave energy through the resonance adapting to varying irregular waves, consequently reduced FOWFT loads and turbine motions. Combining Surface-Riding WECs (SR-WEC) individually designed to feasibly relocate their natural frequency at the peak of the wave excitation spectrum for each sea state, and to obtain the highest capture width ratio at one of the frequent sea states for annual average power in a tens of kilowatts scale with a 15 MW FOWT based on a semi-submersible, Bayesian Optimization is implemented to determine the arrangement of WECs that minimize the annual representation of FOWT’s wave excitation spectra. The time-domain simulation of the system in the optimized arrangement is performed, including two sets of interactions: one set is the wind turbine dynamics, mooring lines, and floating body dynamics for FOWT, and the other set is the nonlinear power-take-off dynamics, linear mooring, and individual WECs’ floating body dynamics. Those two sets of interactions are further coupled through the hydrodynamics of diffraction and radiation. For sea states comprising Annual Energy Production, we investigate the capture width ratio of WECs, wave excitation on FOWT, and nacelle acceleration of the turbine compared to their single unit operations. We find that the optimally arranged SR-WECs reduce the wave excitation spectral area of FOWT by up to 60% and lower the turbine’s peak nacelle acceleration by nearly 44% in highly occurring sea states, while multiple WECs often produce more than the single operation, achieving adaptive resonance with a larger wave excitation spectra for those sea states. The synergistic system improves the total Annual Energy Production (AEP) by 1440 MWh, and we address which costs of Levelized Cost Of Energy (LCOE) can be reduced by the collocation.

Engineering↗
DOE OSTI2024

Use of Grid-Forming Medium-Voltage Power Electronics Hub in a Microgrid Setting

This paper presents the application of a new design of a multiport, modular, medium-voltage power electronics hub (M3PE-HUB) in a microgrid setting. The M3PE-HUB system was modeled in a digital real-time simulator (DRTS) and integrated into the Banshee microgrid test system. This paper presents the preliminary DRTS simulation-based results of the M3PE-HUB system connected in a test microgrid system. Verification and validation of the M3PE-HUB architecture and controls in the test microgrid setting are the primary contributions of this work. The results of the operation during the islanding and resynchronization process indicate the feasibility of the proposed architecture in a microgrid setting. This paper also presents results for a system reconfiguration use case where the M3PE-HUB was used to reconfigure the system under a fault condition.

grid forming↗
DOE OSTI2023

Present and Future Changes in Land‐Atmosphere Coupling of Water and Energy Over Extratropical Forest Regions

Abstract Couplings between land and the near surface atmosphere are modulated by interactions between soil conditions, vegetation dynamics, turbulent fluxes, and atmospheric properties. How the land‐atmosphere coupling responds to warming and elevated CO 2 are important for understanding the land surface carbon, energy, and water cycles. In this work, we documented this coupled land‐atmosphere network based on observations and the Energy Exascale Earth System Model (E3SM) simulations over extratropical forest ecosystems. We employed a transfer entropy approach and novel network metrics to reveal patterns and strength of the land‐atmosphere coupling under historical conditions and a future high emission scenario (SSP585). We found that, in observations, the present‐day extratropical forest coupling network has high network connectivity (72%–88% of the targeted processes are coupled). E3SM reasonably captured the extratropical forest coupling network (modeled network connectivity was 81%–96%) and predicted that the coupling strength would significantly increase by 28% (±3%) under warming and elevated CO 2 conditions. Furthermore, E3SM factorial coupled experiments suggested that warming enhanced soil nitrogen mineralization favoring plant nitrogen uptake and vegetation growth were responsible for the strengthening future land‐atmosphere coupling. This work provides new metrics to analyze and document complex couplings for coupled earth system processes and highlights the important roles soil nutrient availability and biogeochemistry have on land‐atmosphere coupling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Increased localization of Majorana modes in antiferromagnetic chains on superconductors

Magnet-superconductor hybrid (MSH) systems are a key platform for custom-designed topological superconductors. Ideally, the ends of a one-dimensional MSH structure will host Majorana zero-modes (MZMs), the fundamental unit of topological quantum computing. However, some experiments with ferromagnetic (FM) chains show a more complicated picture. Due to tiny gap sizes and hence long coherence lengths, MZMs might hybridize and lose their topological protection. Recent experiments on a niobium surface have shown that both FM and antiferromagnetic (AFM) chains may be engineered, with the magnetic order depending on the crystallographic direction of the chain. While FM chains are well understood, AFM chains are less so. Here, we study two models inspired by the niobium surface: A minimal model to elucidate the general topological properties of AFM chains and an extended model to more closely simulate a real system by mimicking the proximity effect. Here, we find that, in general, for AFM chains, the topological gap is larger than for FM ones, and thus, coherence lengths are shorter for AFM chains, yielding more pronounced localization of MZMs in these chains. While for some parameters AFM chains may be topologically trivial, we find in these cases that adding an adjacent chain can result in a nontrivial system, with a single MZM at each chain end.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Quantum entropy as a harbinger of factorizability

Deeply inelastic scattering (DIS) is a powerful probe for investigating the QCD structure of hadronic matter and testing the standard model (SM). DIS can be described through QCD factorization theorems which separate contributions to the scattering interaction arising from disparate scales — e.g ., with nonperturbative matrix elements associated with long distances and a perturbative hard scattering kernel applying to short-distance parton-level interactions. The fundamental underpinnings of factorization may be recast in the quantum-theoretic terms of entanglement, (de)coherence, and system localization in a fashion which sheds complementary light on the dynamics at work in DIS from QCD bound states. In this Letter, we propose and quantitatively test such a quantum-information theoretic approach for dissecting factorization in DIS and its domain of validity; we employ metrics associated with quantum entanglement such as a differential quantum entropy and associated Kullback-Leibler (KL) divergences in numerical tests. We deploy these methods on an archetypal quark-spectator model of the proton, for which we monitor quantum decoherence in DIS as underlying model parameters are varied. On this basis, we demonstrate quantitatively how factorization-breaking effects may be imprinted on quantum entropies in a kinematic regime where leading-twist factorization increasingly receives large corrections from finite- Q 2 effects; our findings suggest potential applications of quantum simulation to QCD systems and their interactions.

Deep inelastic scattering↗
DOE OSTI2025

Comparing Control Performance Between Simulation and Experiment using the Microreactor Automated Control System Testbed

In the advanced reactor domain, a flexible and scalable software/hardware infrastructure is crucial for integrating and validating various control technologies. This study used the Microreactor Automated Control System (MACS) hardware platform as a testbed. MACS was originally designed to mirror Idaho National Laboratory (INL)'s Microreactor Applications Research Validation and Evaluation (MARVEL), a 85-kW thermal fission microreactor. It features control drums for simulated reactivity control; lights that function as a surrogate reactor core, with the brightness being proportional to the reactor power; and light sensors that emulate neutron detectors. To transform MACS into a physical twin of MARVEL for evaluating control methods, the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) software was employed. This software integrated the hardware with two models of the MARVEL core, based on Reactor Excursion and Leak Analysis Program (RELAP5-3D) and Monte Carlo N-Particle (MCNP) models. The study aimed to demonstrate the gap between control theory and actual practice—a gap that often necessitates empirical adjustments such as control gain retuning, filters, time discretization, and integrator anti-windup measures. Controllers were developed based on increasingly complex simulations without hardware, starting from the base MARVEL model and then introducing actuator saturation constraints and sensor noise. The final control strategy was then tested using MACS, and a comparative performance analysis was conducted.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗