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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Control Oriented Models for Co-Design: Technical Overview of MT HVDC, MVDC, and Solid State Transformer Building Blocks

The electric power system is shifting toward a power electronics–enabled grid, where converter based “building blocks” (e.g., high voltage direct current (HVDC) links, multi terminal HVDC (MT HVDC) networks, medium voltage DC (MVDC) links, and solid state transformers (SSTs)) provide fast, precise control of power flows, voltage, and frequency. This report develops and applies publicly shareable electromagnetic transient (EMT) and phasor models to examine how such building blocks can be composed and coordinated to support offshore wind integration, inter area transfers, feeder support, and resilience. Section 2 documents a modular multilevel converter (MMC)–based MT HVDC modeling framework and two use cases: a compact WSCC/IEEE 9 bus test system and a 240 bus “mini WECC” case with five offshore wind plants (OWFs). Phasor to EMT transfer, initialization, and sanity checks are summarized, and neutral demonstrations of normal and contingency operation are reported. Section 3 frames the problem of wind plant inertial frequency response (IFR): shaping energy release and recovery to improve nadir while avoiding aerodynamic stall; representative simulations illustrate the issues without disclosing proprietary control. Section 4 develops MVDC concepts through an IEEE 16 bus loop and an Olympic Peninsula case study that compares AC vs. MVDC corridors and shows how feeder headroom can be pooled via DC couplers. Section 5 surveys SST architectures and identifies a gap: scalable, communication free coordination of multiple SSTs for islanded feeder networks. Across the report, novel methods and configurations under separate publication and IP review are not disclosed; only topic oriented, replicable setups and non proprietary results are shown. These models and use cases are intended as foundations for future publications and co design studies on architecture, control, and coordination of PE enabled grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

High flow differential cleaning system

A high flow differential cleaning system uses a source of pressurized compressed dry gas to pressurize a holding tank. A component to be cleaned is securely loaded and oriented against a blast plate designed specifically for the desired pressure, flow, and volume. A fast-actuated valve system opens to direct high volumes of pressurized gas from a holding tank through and around the component(s) held within the cleaning chamber for the removal of remnant powder and foreign particles from interior cavities as well as exterior component surfaces.

Edwards, Kevin Scott↗
DOE OSTI2026

Conditional deep generative models for simultaneous simulation and reconstruction of entire events

We extend the particle-flow neural assisted simulations (arnassus) framework of fast simulation and reconstruction to entire collider events. In particular, we use two generative artificial intelligence tools, continuous normalizing flows and diffusion models, to create a set of reconstructed particle-flow objects conditioned on truth-level particles from CMS Open Simulations. While previous work focused on jets, our updated methods now can accommodate all particle-flow objects in an event along with particle-level attributes like particle type and production vertex coordinates. This approach is fully automated, entirely written in Python, and GPU-compatible. Using a variety of physics processes at the LHC, we show that the extended arnassus is able to generalize beyond the training dataset and outperforms the standard, public tool elphes.

Dreyer, Etienne [Weizmann Institute of Science, Re↗
DOE OSTI2025

Lithium Divertor Targets and Walls for the ASTER Liquid Stellarator Reactor, Distributed Divertor

Stellarators may have advantages for certain liquid metal options as Plasma Facing Components (PFC) for divertor targets and first walls due to the wide range of possible magnetic configurations, which additionally are free of disruptions and fast field variations. In a previous work (V. Queral et al., IEEE Trans. Plasma Sci. 52, 2024), a concept of stellarator reactor (ASTER-CP) based on swirling Li-molten salts and liquid lithium floating on the molten salt as PFC was presented. The divertor matters were not studied then and, thus, they are being studied and experimentally tested now. The ASTER-CP reactor concept, the initial liquid metal experiments and potential concepts for the ASTER-CP divertor and first wall are reported. Concerning the experiments, several small scale experiments of galinstan in a small rotating cylinder under magnetic field have been produced, including one experiment with high viscosity galinstan-mixture for increased thickness of layer. An experiment of floating lithium on the molten salt LiCl-PbCl2 gave fast volatilization/decomposition of the molten salt. Particularly for divertors, the traditional free-flow, Capillary Porous Systems and ‘divertorlets’ have been studied for application to ASTER-CP. Surface waves (hot spots), lack of enough surface fluid turbulence and excessive fluid speed are the main issues found in fast free-flow. The perhaps original concept of Distributed Divertor and Equi-power Surface is tentatively proposed and studied, taking advantage of stellarator fields and low recycling regime.

distributed divertor↗
DOE OSTI2025

Real-time inference and extrapolation with Time-Conditioned UNet: Applications in hypersonic flows, incompressible flows, and global temperature forecasting

Neural Operators are fast and accurate surrogates for nonlinear mappings between functional spaces within training domains. Extrapolation beyond the training domain remains a grand challenge across all application areas. We present Time-Conditioned UNet (TC-UNet) as an operator learning method to solve time-dependent PDEs continuously in time without any temporal discretization, including in extrapolation scenarios. TC-UNet incorporates the temporal evolution of the PDE into its architecture by combining a parameter conditioning approach with the attention mechanism from the Transformer architecture. After training, TC-UNet makes real-time inferences on an arbitrary temporal grid. We demonstrate its extrapolation capability on a climate problem by estimating the global temperature for several years and also for inviscid hypersonic flow around a double cone. We propose different training strategies involving temporal bundling and sub-sampling. We demonstrate performance improvements for several benchmarks, performing extrapolation for long time intervals and zero-shot super-resolution time.

Deep learning↗
DOE OSTI2021

Propagating neutronic uncertainties for FFTF LOFWOS Test #13

The safety evaluation conducted for licensing a Sodium-cooled Fast Reactor (SFR) may require modeling transients with best-estimate calculation tools that must first be validated against real-world measurements. To provide the community with a valuable benchmarking opportunity for validating SFR analysis tools and methods, the International Atomic Energy Agency (IAEA) initiated a coordinated research project (CRP) in 2018 for the analysis of the Fast Flux Test Facility (FFTF) Loss of Flow Without Scram (LOFWOS) Test #13. The impact of nuclear data uncertainties on neutronics parameters was previously investigated based on the COMMARA-2.0 covariance matrix. Since the transient simulation results are very sensitive to certain reactivity coefficients, it was decided to employ rigorous uncertainty propagation methods to quantify the impact of nuclear data uncertainties on the best-estimate predication of FFTF LOFWOS Test #13. The DAKOTA code is used to propagate neutronic uncertainties through SAS4A/SASSYS-1 transient simulations, while taking into account spatial and reaction-wise correlations within these uncertainties. This study shows that the remaining discrepancies observed between the Argonne National Laboratory (ANL) best-estimate results and the experimental measurements can be partly explained by the uncertainty associated with Gas Expansion Module (GEM) worth, which contributes the majority of the overall nuclear data uncertainty on the output from the FFTF LOFWOS Test #13 transient simulation. This study also confirmed the importance of including spatial and reaction-wise correlations of nuclear data uncertainties on feedback coefficients in the uncertainty propagation to avoid under-estimating their impact during the transient simulations.

42 ENGINEERING↗
DOE OSTI2020

Finite Volume Discretization of the Euler Equations in Pronghorn

Modeling flow and heat transfer in high temperature gas reactors (HTGR) requires the ability to model a wide range of flow speeds from slow (natural convection), to intermediate (forced-flow conditions), to supersonic regimes (depressurization) for a wide range of geometries including the pebble bed, upper and lower plenum, and risers. In previous work, Pronghorn has effectively modeled low-to-medium speed flows in scenarios such as the one described in the two-dimensional PBMR-400 benchmark, using its finite-element-based streamline-upwind Petrov-Galerkin (SUPG) stabilized implementation of the Euler equations. However, limitations of this method become apparent when dealing with more complicated geometries (e.g. imposing slip boundary conditions at nodes belonging to two different boundaries) and when gas speeds are fast enough for shocks and supersonic flow to occur. For these problems, the finite-element-based solver lacks robustness and is plagued by slow iterative convergence or even divergence. In order to address these challenges, the Pronghorn code at INL has been updated with new, modified versions of its original equations. The new Pronghorn models are built on the finite volume method with a Harten-Lax-van Leer-Contact (HLLC) Riemann solver based numerical flux method, which (1) allows imposing slip boundary conditions much more robustly and (2) performs well for a wide range of flow speeds. The finite-volume-based flow solver will form the basis for a robust coarse-mesh thermal-hydraulics capability in Pronghorn.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Experimental measurements of fluid flow in an 84-pin hexagonal rod bundle with spacer grid for a gas-cooled fast modular reactor

A 50 MW e helium-cooled fast modular reactor (FMR) is under development, and as part of the Department of Energy Integrated Research Project (IRP), Texas A&M University is conducting the thermal-hydraulic characterization of its baseline core configuration. Here, we experimentally investigated the axial and cross flow fields characteristics in the hexagonal fuel rod bundle composed of 84 rods, a central rod, and spacer grids at a Reynolds number of 12,000. A fully transparent experimental facility resembling of one unit of the fuel assembly was constructed. Time-resolved particle image velocimetry (TR-PIV) measurements were performed to characterize hydraulic behavior downstream the spacer grid. Velocity measurements were conducted in the axial and radial direction of the rod bundle. From the PIV velocity vector fields, the full-field flow statistics were computed for the mean velocity, vorticity, and Reynolds stresses. An analysis of the energy decay downstream of the spacer grid was conducted with calculations of secondary-flow intensities, turbulent kinetic energy, power spectrum, and spatial-temporal velocity cross correlations. The vorticity field was obtained and pairs of counter-rotating vortexes were identified using a 3D reconstruction of several measurement planes. The data from this experimental campaign will be used to validate numerical models based on Computational Fluid Dynamics and other codes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Measurement of near- and far-field impurity flows during pellet-induced rapid shutdown in DIII-D

Both near-field (<1 m away toroidally from the pellet) and far-field (>1 m away toroidally from the pellet) poloidal and toroidal impurity (carbon ion) flows are measured using visible imaging and fast bolometry during a polypropylene pellet-induced rapid plasma shutdown in the DIII-D tokamak. In the near field, the pellet appears to increase poloidal flow in the ion diamagnetic direction, possibly due to the strong radial temperature gradient caused by the pellet ablation. In the far field, the poloidal impurity flow typically appears slower and in the opposite direction. Toroidal impurity flow appears to be strongly influenced by the plasma initial toroidal rotation, especially in the far field. These results demonstrate that rapid shutdown impurity flows are not necessarily global in structure but can be quite different close to and far from the injected pellet.

Electromagnetic radiation detectors↗
DOE OSTI2023

Flow of the normal component of He-II about bluff objects observed with He$^*_2$ excimers

Flow of the normal fluid component of He II about a cylinder and flat plate in a channel with a square cross-section was observed by tracking clouds of He$^*_2$ excimers. Flow was produced using a lithographically patterned heater. The direction and speed of flow projected onto a plane parallel to the axis of the channel and perpendicular to the heater exhibited significant change with time even after the heater was turned off. Flow was recorded in movies. Excimers moved at least as fast as could be recorded by the camera. Velocity vector field maps of flow suggest formation of structures downstream of the cylinder object that are consistent with parts of eddies. Here, in this paper, we establish a foundation to observe normal component flow of a quantum fluid over centimeters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Joint scheduling of energy, fast and primary frequency response reserves in integrated transmission–distribution networks

Inverter-based distributed energy resources (DERs) connected to distribution networks (DNs) can provide fast frequency support, but their reserve deliverability depends on feeder constraints and differs from synchronous primary frequency response (PFR). Existing transmission–distribution coordination studies usually treat reserve generically or neglect feeder-level feasibility, while frequency-security scheduling studies rarely represent distribution feeders explicitly. This paper develops a bi-level day-ahead scheduling framework for integrated transmission–distribution networks that jointly clears energy, transmission-side PFR, and distribution-side fast frequency response (FFR) under exogenous hourly inertia and largest-loss inputs from an external unit commitment (UC) schedule. The transmission problem is modeled with DC-optimal power flow (OPF) and closed-form second-order cone (SOC) frequency-security constraints, whereas each DN is represented by a reserve-aware branch-flow AC-OPF so that scheduled fast reserves remain deliverable during activation. The bi-level problem is reformulated through Karush–Kuhn–Tucker (KKT) conditions into a mixed-integer SOC program, and a penalty term is used to tighten the distribution-network relaxation. In the reduced test system, lower exogenous inertia increased the required primary response from 179.64 MW to 191.08 MW, distribution-side fast response reduced total frequency-response procurement by up to 4.9%, and neglecting distribution constraints overstated the combined distribution-side energy and reserve award by up to 18%. In the expanded study, the largest case was solved in 2.02 s with a 0.00% optimality gap. Time-domain simulations kept the frequency nadir above 59.0 Hz in all tested hours. These results demonstrate the value of fast-response modeling and distribution-feasible reserve delivery in coordinated market clearing.

Noh, Seung-Gil↗
DOE OSTI2024

Pore architecture controls on mineral reactivity

Mineral dissolution rates measured in natural environments are much slower than those measured in laboratory settings. This project tested the hypothesis that the way fluid flows through rocks in natural systems creates areas where mineral dissolution is fast and areas where mineral dissolution is slow. This hypothesis was tested with a combination of laboratory experiments and numerical simulation. We demonstrated a separation of fluid flow pathways and rates of mineral dissolution in laboratory experiments for the first time using an experimental approach where we created synthetic rocks that have different ratios of connected and dead-end pathways for fluid flow. In laboratory experiments with higher proportions of dead-end pathways, the mineral dissolution rates were slower. We found that where fluid flows through connected pathways the continuous refreshing of fluid at the mineral surface creates conditions where dissolution is fast. In contrast, where fluid either flows slowly through poorly connected pathways or is stagnant in dead-end pathways, mineral dissolution is slow. The results from this project suggest that the overall slowing of rates of mineral dissolution is important when the proportion of dead-end pathways is greater than ~40%. This project informs our understanding of the way that fluids react with rocks in carbon dioxide sequestration and enhanced geothermal projects where fluids are purposefully injected into rocks for energy applications.

58 GEOSCIENCES↗
DOE OSTI2021

CsPbI 3 Nanocrystals Go with the Flow: From Formation Mechanism to Continuous Nanomanufacturing

Despite the groundbreaking advancements in the synthesis of inorganic lead halide perovskite (LHP) nanocrystals (NCs), stimulated from their intriguing size-, composition-, and morphology-dependent optical and optoelectronic properties, their formation mechanism through the hot-injection (HI) synthetic route is not well-understood. Here in this work, for the first time, in-flow HI synthesis of cesium lead iodide (CsPbI 3 ) NCs is introduced and a comprehensive understanding of the interdependent competing reaction parameters controlling the NC morphology (nanocube vs nanoplatelet) and properties is provided. Utilizing the developed flow synthesis strategy, a change in the CsPbI 3 NC formation mechanism at temperatures higher than 150 °C, resulting in different CsPbI 3 morphologies is revealed. Through comparison of the flow- versus flask-based synthesis, deficiencies of batch reactors in reproducible and scalable synthesis of CsPbI 3 NCs with fast formation kinetics are demonstrated. The developed modular flow chemistry route provides a new frontier for high-temperature studies of solution-processed LHP NCs and enables their consistent and reliable continuous nanomanufacturing for next-generation energy technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A deep learning-based workflow for fast prediction of 3D state variables in geological carbon storage: A dimension reduction approach

Deep learning (DL) models are extensively used as surrogate models for high-fidelity simulations of multiphase fluid flow in porous media at large scales, enabling fast forecasts of the spatial–temporal evolution of three-dimensional (3D) state variables in geological carbon storage (GCS). However, training these models in high-dimensional space remains computationally demanding and prone to overfitting because of limited training data. This paper presents a novel workflow to address these challenges by integrating dimension reduction (DR) methods. Here, the proposed workflow employed pre-trained DR models to extract the latent variables of geological models and state variables and utilized the multi-layer perceptron (MLP) for constructing mapping functions between the input and output variables in latent spaces. Subsequently, the pre-trained reconstruction models converted the MLP-predicted latent state variables to their original high-dimensional form. Furthermore, we proposed a novel strategy for the DR and reconstruction of 3D saturation fields to account for the unique data characteristics of sparsity, nonuniformity, and discontinuity. The proposed strategy applied PCA and inverse PCA for 2D average saturation fields and developed a DL-based 3D reconstruction model, leveraging three 2D average saturation fields as input to produce a 3D saturation field as output. The pre-training of DR and reconstruction models and training of MLP models were conducted on 84 Gulf of Mexico (GoM) simulations and evaluated on 12 testing simulations. Each simulation contained 720 monthly time steps, with the first 360 months as the injection period and the rest as the post-injection period. The proposed workflow, incorporating DR and DL models, accurately predicts the normalized 3D pressure fields, achieving mean square error (MSE) of 2.92 × 10 -7 compared to the ground truth obtained from a full-physics simulator. Furthermore, the proposed strategy outperformed PCA and convolutional autoencoder (CAE) models on 3D saturation fields, resulting in minor workflow prediction errors with an MSE of 2.93 × 10 -5 . The results suggest the proposed workflow provides sufficient predictive fidelity across temporal and spatial scales, and enables a speedup of 160 times compared to the full-physics simulator, facilitating improved decision-making and risk assessment for large-scale GCS management in real-time scenarios.

3D reconstruction model↗
DOE OSTI2021

Simulation of the supercritical CO 2 recompression Brayton power cycle with a high-temperature regenerator

The supercritical carbon dioxide (sCO 2 ) recompression Brayton cycle promises higher efficiency and lower capital cost than traditional steam Rankine power cycles. However, achieving high efficiency requires large, highly effective recuperators. Regenerators may be a low-cost alternative to printed circuit and micro-tube heat exchangers for recuperation in sCO 2 power cycles. Regenerators are a periodic heat exchanger in which thermal energy is extracted from the hot stream, stored in solid media, and then released to the cold stream at a later time. Fixed bed regenerators with valves to direct fluid are the preferred method for implementing regenerators in power cycles, but the inherently transient nature of these systems has not been characterized for this application. This study presents the simulation of a high-temperature regenerator within a 10 MWe sCO 2 recompression Brayton cycle. A transient, one-dimensional regenerator model presented in a previous study is used to simulate the regenerator. Dynamic heat exchanger models are also developed for the precooler, low-temperature recuperator, and primary heat exchanger, and the compressors and the turbine are modeled with off-design performance maps. We assess two regenerator-valve design options; one for fast switching, and one for reduced flow rate fluctuations. System simulation finds that both designs see significant fluctuations in turbomachinery flow rate, turbomachinery and system power, and regenerator discharge process outlet temperature. While designing the regenerator-valve subsystem for lower fluctuations is possible, the regenerator cold discharge temperature and net power still fluctuate by ±77.6°C and 6%, respectively. Increasing buffer volume is not effective at sufficiently reducing these fluctuations, but adding a packed bed in between the regenerator and the primary heat exchanger can reduce regenerator discharge process outlet temperature fluctuations to 6.4°C. Further reductions could be possible by increasing the size of this packed bed.

42 ENGINEERING↗
DOE OSTI2023

Advanced two-phase subchannel method via non-linear iteration

A fast-running, robust two-phase flow, sub-channel model is presented based on non-linear solution of the steady-state subchannel fluid flow equations. The drift-flux model solves for conservation of liquid and vapor mass, mixture energy, and axial and transverse mixture momentum as part of an efficient planar marching scheme and nonlinear, nested outer and inner iteration. Here, models based on mechanistic subcooled boiling, two-phase turbulent void mixing, and drift are included. Solution verification and mesh convergence studies were performed for modern GE 10 × 10 fuel geometry and are shown to have excellent convergence behavior. Run time performance for a 50 axial mesh model showed 2.2 seconds on a single CPU core to tightly converge all 3D distributions (flow, void, pressure) for the GE 10 × 10 fuel geometry, supporting its efficient use within the Virtual Environment for Reactor Applications boiling water reactor framework.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Xcompact3D: An open-source framework for solving turbulence problems on a Cartesian mesh

Xcompact3D is a Fortran 90–95 open-source framework designed for fast and accurate simulations of turbulent flows, targeting CPU-based supercomputers. It is an evolution of the flow solver Incompact3D which was initially designed in France in the mid-90’s for serial processors to solve the incompressible Navier–Stokes equations. Incompact3D was then ported to parallel High Performance Computing (HPC) systems in the early 2010’s. Very recently the capabilities of Incompact3D have been extended so that it can now tackle more flow regimes (from incompressible flows to compressible flows at low Mach numbers), resulting in the design of a new user-friendly framework called Xcompact3D. The present manuscript presents an overview of Xcompact3D with a particular focus on its functionalities, its ready-to-run simulations and a few case studies to demonstrate its impact.

17 WIND ENERGY↗