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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 919 records · Page 51
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DOE OSTI2025

Q3 Report for FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment

This report describes the work and activities carried out towards the completion of each of the following milestones in FY25 Q3: 1. Demonstrate workflow for generating self-consistent CESOL plasma profiles + first wall and divertor loading prediction and generate the CAT plasma and neutron loading needed for further engineering analysis. • Benchmark between two first wall heat flux mapping methods, identify importance of various heat flux sources and physics impact of using fully coupled CESOL vs post-analysis evaluation. 2. Generate medium fidelity parametrized CAD. • Generate parametrized CAD components for the CAT example case via either user-defined modules called within the geometry generation or by defeatured/parametrized CAD, including DCLL blanket matched to divertor boundary and magnets. Define materials, labels, and boundary conditions for passing the mesh to CFD tools. 3. Demonstrate multiphysics magnet analysis. • Demonstrate magnet analysis workflow called from the FREDA workflow, and 4. Demonstrate nuclear analysis. • Add model to OpenFOAM and/or other codes possibly including Diablo to account for tritium diffusion in solids.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Q2 Report for FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment

This report describes the work and activities carried out towards the completion of each of the following milestones in FY25 Q2: 1. Demonstrate workflow for generating self-consistent CESOL plasma profiles + first wall and divertor loading prediction and generate the CAT plasma and neutron loading needed for further engineering analysis: $\circ$ Run CESOL with BOUT++/Hermes-3 and immersed boundary condition to directly map to wall: • Run BOUT++/Hermes-3 through the IPS workflow to find radial particle and energy diffusivities to match either the Eich or the physics-based scaling of the SOL heat flux width, and • Expand source of first wall heat flux to include charged particles, neutrals, and radiation from the core+edge. 2. Generate medium fidelity parametrized CAD: $\circ$ Develop the TRACER tool to read an existing CAD, regenerate the geometry based on vertex location and connectivity information, define vertex translation and parameters needed for scaling the CAD, and $\circ$ Utilize the FreeGS code to determine CAT PF coil placement, including minimizing the number of coils, coil current, and electromechanical stresses. 3. Utilize plasma loading for engineering analysis: $\circ$ Couple the plasma loading to input for OpenFOAM and demonstrate initial test of thermal analysis of CAT first wall loading with typical DCLL blanket component cooling boundary conditions. 4. Demonstrate nuclear analysis: $\circ$ Apply initial analysis of tritium transport in DCLL blanket by evaluating spatially resolved tritium generation rates, tritium diffusion and convection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Q1 Report for FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment

This report describes the work and activities carried out towards the completion of each of the following milestones in FY25 Q1: 1. Demonstrate workflow for generating self-consistent CESOL plasma profiles + first wall and divertor loading prediction and generate the CAT plasma and neutron loading needed for further engineering analysis: $/circ$ Initially run CESOL with SOLPS and map heat flux using simple HEAT method: ▪ Generate SOLPS grid for CAT reference case, ▪ Implement and apply ‘lower’ fidelity method of using HEAT-like analytic method to map SOLPS heat flux from charged particles to first wall, and ▪ Provide initial heat flux + neutron loading for further engineering analysis. 2. Demonstrate multiphysics magnet analysis: $/circ$ Demonstrate validation of the Elmer workflow by comparing induced stresses due to EM forces generated by TF coils using multiple codes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

A High-Assay Low-Enriched Uranium Fuel Transportation Concept

The uranium 235U enrichment commonly used in fuel production for U.S. light water nuclear reactors typically does not exceed 5 wt%. In contrast, many of the currently investigated advanced reactor concepts demand fuel with higher enrichments. This includes high-assay low-enriched uranium (HALEU), characterized by a 235U enrichment of 5 to 20 wt%. The necessity of HALEU transportation in the fuel production cycle leads to new challenges caused by various technical and regulatory hurdles. Current U.S. Nuclear Regulatory Commission–approved transportation package designs for UF6 with enrichments above 5 wt% provide relatively small payloads [=116 kg (250 lb)]. Furthermore, in accordance with 10 CFR 71.55, package design activities for fissile material enriched above 5 wt% need to consider water infiltration in the containment as part of the criticality safety evaluations. This study presents a transportation package concept for HALEU advanced nuclear reactor fuel with a significantly higher payload of up to 376 kg (830 lb) of fissile material per package and up to 1881 kg (4149 lb) of HALEU per legal weight truck. The anticipated chemical form of the transported material is UO2 downblended from available highly enriched uranium. The concept utilizes a combination of existing transportation packaging, 18 inner canisters, and a novel basket design that includes a borated aluminum flux trap. Criticality and shielding evaluations; fundamental structural, confinement, and thermal assessments; and studies on package operations are presented. The results of this study build significant confidence in the technical feasibility of a high-capacity HALEU transportation package concept while demonstrating the concept’s potential to meet U.S. regulatory requirements.

Eidelpes, Elmar↗
DOE OSTI2024

Compatibility of divertor detachment and ELM suppression in DIII-D high- β p plasmas with ITER-similar shape

Abstract Integration of transient and steady-state divertor heat fluxes control with a high-performance core is necessary for future fusion reactors. In recent DIII-D high- β p experiments, divertor detachment and simultaneous edge localized mode (ELM) suppression are demonstrated while the plasma confinement quality is maintained high in ITER-similar shape. By optimizing the neon injection in high- β p scenario with ITER-similar shape, deep detachment and ELM suppression are achieved with a high-performance core ( β N ∼ 2.8, β p ∼ 2.3) at q 95 ∼ 7.5. Partial divertor detachment and suppression of large ELMs are achieved at q 95 ∼ 6. The stability analyses suggest that with low neon injection, the density pedestal becomes higher and steeper and the T i profile also increases, therefore the increased edge pressure and higher current density destabilize the Peeling-Ballooning mode (PBM), which would lead to a large ELM collapse. With strong neon gas puffing, the significantly reduced pedestal pressure and current density, due to the degraded T e pedestal, lead to the stabilization of PBM and ELMs are suppressed. For both cases, the coupling between the large radius internal transport barrier (ITB) and edge pedestal is the key reason for maintaining high global performance. The formation of large radius ITB compensates for pedestal degradation. Such results could provide an attractive scenario to well control the transient and steady-state heat flux onto the divertor plates while maintaining good plasma performance, which is an important step toward the steady-state operation of future fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Bayesian discovery of optimal reduced order models from mechanistic and experimental data: A case study of Pd penetration in TRISO fuels using BISON

TRistructural ISOtropic (TRISO) particles rely on a silicon carbide (SiC) layer as the primary structural material and barrier to metallic fission products (FPs) release. Accurate prediction of palladium (Pd) transport and penetration is therefore critical for qualifying TRISO fuels for advanced reactors. The empirical correlation for Pd penetration in BISON is derived from historical particle-fuel data, but cannot explain the large scatter in the experimental data that arises from varying experimental conditions. To aid fuel qualification, we previously developed a mechanistic reduced order model (ROM) using BISON that resolves these dependencies. Here, in this work we build on that mechanistic ROM and perform validation and quantify its uncertainty using Bayesian uncertainty quantification (UQ). calibration against a suite of in-pile and out-of-pile experiments spanning particle compositions, geometries, and operating conditions, and we benchmark it against the empirical correlation. Bayesian UQ identifies influential parameters, calibrates them to data, and yields predictive intervals. Results show that while the empirical correlation can be tuned to fit a single experiment type, it transfers poorly; the mechanistic ROM sustains accuracy with credible uncertainty across disparate conditions. This demonstrates a practical path—via Bayesian UQ applied to mechanistic ROMs—to leverage single-effect experiments for inferring in-reactor behavior and supporting TRISO fuel qualification.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

In-situ coating of silicon-rich films on tokamak plasma-facing components with real-time Si material injection

Abstract Experiments have been conducted in the DIII-D tokamak to explore the in-situ growth of silicon-rich layers as a potential technique for real-time replenishment of surface coatings on plasma-facing components (PFCs) during steady-state long-pulse reactor operation. Silicon (Si) pellets of 1 mm diameter were injected into low- and high-confinement (L-mode and H-mode) plasma discharges with densities ranging from 3.9– 7.5 × 10 19 m −3 and input powers ranging from 5.5 to 9 MW. The small Si pellets were delivered with the impurity granule injector at frequencies ranging from 4 to 16 Hz corresponding to mass flow rates of 5–19 mg s −1 (1– 4.2 × 10 20 Si s −1 ) at cumulative amounts of up to 34 mg of Si per five-second discharge. Graphite samples were exposed to the scrape-off layer and private flux region plasmas through the divertor material evaluation system to evaluate the Si deposition on the divertor targets. The Si II emission at the sample correlates with silicon injection and suggests net surface Si-deposition in measurable amounts. Post-mortem analysis showed Si-rich coatings containing silicon oxides, of which SiO 2 is the dominant component. No evidence of SiC was found, which is attributed to low divertor surface temperatures. The in-situ and ex-situ analysis found that Si-rich coatings of at least 0.4–1.2 nm thickness have been deposited at 0.4–0.7 nm s −1 . The technique is estimated to coat a surface area of at least 0.94 m 2 on the outer divertor. These results demonstrate the potential of using real-time material injection to form Si-enriched layers on divertor PFCs during reactor operation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Preliminary Reactor Fueling Support Equipment Recommendation

The National Reactor Innovation Center (NRIC) is a national program that was established as part of the Nuclear Energy Innovation Capabilities Act (NEICA). NRIC’s mission is to accelerate the demonstration and deployment of advanced nuclear energy through its mission to inspire stakeholders and the public, empower innovators, and deliver successful outcomes through efficient coordination of partners and resources. NRIC is designed to bridge the gap between research, development, and the marketplace to help convert some of the nation’s most promising advanced nuclear reactors into commercial applications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Center of Excellence Collaboration Projects: Second Wave

The NEAMS program aims to develop an integrated multi-physics simulation capability “pellet-to-plant” for the design and analysis of future generations of nuclear power plants. In particular, the Reactor Product Line code suite's multi-resolution hierarchy is being designed to ultimately span the full range of length and time scales present in relevant reactor design and safety analyses, as well as scale from desktop to petaflop computing platforms. In particular the NEAMS program is supporting the development of novel thermal-hydraulic codes. The Center of Excellence for Thermal Fluids Application in Nuclear Energy, launched in 2018, has as its key goals to serve as a front door to industry. The Center of Excellence for Thermal Fluids Applications in Nuclear Energy has recently launched a program to start collaborative efforts between the laboratories and industry with the objective of stimulating cooperation and increasing adoption of T/H tools developed under NEAMS by the industry-at-large. In particular, two industry partners agreed to participate in a second wave of short-term collaborations aimed at demonstrating the value of NEAMS tools to their designs. These are Framatome and TerraPower who proposed projects related to LWR (Light Water Reactor) and MSFR (Molten Salt Fast Reactor) designs respectively. In this report we present the results of these two collaborations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Homomorphic Encryption for Machine Learning and Artificial Intelligence Applications

Third-party and expert analysis is a cost-effective solution for solving specialized problems or processing large datasets related to reactor structural health monitoring and nondestructive evaluation. However, when handling proprietary information, third-party and expert analysts pose a privacy risk. To address this challenge, Homomorphic Encryption (HE) permits arithmetic operations on encrypted data without exposing the underlying data. Implementations of Machine Learning (ML) and Artificial Intelligence (AI) algorithms using HE greatly enhances the capabilities of third-party analysts while maintaining a low security risk. This paper details current success in applying Principal Component Analysis (PCA) and Fully Connected Neural Networks (NN) using the Microsoft SEAL implementation of the popular CKKS Fully Homomorphic Encryption (FHE) algorithm. The MNIST Handwritten Dataset is analyzed as a proof-of-concept demonstration of the implementations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

A Low-Enriched Uranium (LEU) option for the conversion of FRM II

The Forschungs-Neutronenquelle Heinz Maier-Leibnitz (FRM II) is Germany’s most powerful research reactor and uses Highly Enriched Uranium (HEU) fuel enriched at 93 %. The Technical University of Munich (TUM) operates the reactor and has been mandated to convert the FRM II to a lower-enrichment fuel. In preparation for the lower-enrichment fuel downselection, planned for 2023, TUM is evaluating multiple conversion scenarios. In this paper, it is demonstrated that a conversion of FRM II to Low-Enriched Uranium (LEU) is scientifically possible when using the novel monolithic U-10Mo fuel system, which is currently in the qualification process. As a research reactor, safety criteria, neutron flux distribution and cycle length are key metrics. To begin, neutronic and thermal-hydraulic models were created based on current technical drawings and relevant material properties. Specifically tailored computational methods and coupling schemes have also been developed to properly evaluate all relevant characteristics for the conversion of the FRM II reactor. Using these models and methods, a systematic parameter study was performed to explore the defined design space. The results of that study indicate that many LEU designs using monolithic U-10Mo appear to be viable to convert FRM II to LEU. One example of an LEU solution for the FRM II reactor that fulfills the stated safety, compatibility and scientific performance requirements is discussed in more detail.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Development of a calculation framework coupling Monte Carlo neutronics, subchannel thermal-hydraulics and 1.5D fuel thermo-mechanics

A coupled calculation system consisting of the Monte Carlo neutronic solver SERPENT and the fuel behaviour solver TRANSURANUS was extended with the sub-channel thermal-hydraulic solver SUBCHANFLOW to form a coupled calculation framework for multi-physics reactor analyses. The coupling between the 3 solvers was accomplished via a driver program written in Perl that runs the solvers, processes and transfers the output data between the solvers and monitors the convergence. While some features of the coupling are still under development, a steady-state coupled calculation resulting in convergence was performed for a single hexagonal fuel assembly to demonstrate that the base functionalities work as expected. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

High pressure neutron diffraction on WAND 2 with a Paris-Edinburgh press

The Paris-Edinburgh press is a widely available, highly adaptable pressure cell commonly used while collecting neutron scattering data. Here, we detail the use of the VX3 and VX5 Paris-Edinburgh presses on the Wide-Angle Neutron Diffractometer (WAND 2 ) at the High Flux Isotope Reactor at Oak Ridge National Laboratory. We first give a detailed overview of the instrument setup and alignment capabilities used at WAND 2 . We then demonstrate the high pressure capabilities through three examples. In this work, the first example focuses on diffraction data obtained from a lithium-diamond mixture to 10 GPa with the use of single toroidal cubic boron nitride anvils. Other examples include the room temperature compressions of germanium (up to 16 GPa) and the mineral malachite with double toroidal sintered diamond anvils. This work thereby represents the first studies above 10 GPa at the High Flux Isotope Reactor and opens the door for future user experiments at these elevated pressures.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Demonstration of photoreactor platform for on-sun unassisted photoelectrochemical hydrogen generation with tandem III–V photoelectrodes

Photoelectrochemical (PEC) water splitting is a direct solar-driven technology that converts solar energy to storable chemical energy in the form of hydrogen. In addition to semiconductor and catalyst development for improved photoelectrodes, designing reactors for testing and operation of PEC systems under inherently dynamic outdoor solar illumination is necessary to further the commercial viability of PEC technology. Herein, we present a versatile photoreactor system mounted on a solar tracker for outdoor PEC testing and demonstrate unassisted PEC water splitting under real world on-sun conditions. GaInP 2 /GaAs tandem absorber photoelectrodes with a MoS 2 catalyst were fabricated and exhibit >8% solar-to-hydrogen efficiency. On-sun efficiency and stability of the photoelectrodes were characterized on both sunny and partly cloudy days with continuous monitoring of insolation and weather conditions. Furthermore, the versatile photoreactor and outdoor PEC testing capabilities and methods presented here can accelerate the development of other solar fuel generating systems and technologies.

solar fuels↗
DOE OSTI2023

Physics-informed neural network with transfer learning (TL-PINN) based on domain similarity measure for prediction of nuclear reactor transients

Nuclear reactor safety and efficiency can be enhanced through the development of accurate and fast methods for prediction of reactor transient (RT) states. Physics informed neural networks (PINNs) leverage deep learning methods to provide an alternative approach to RT modeling. Applications of PINNs in monitoring of RTs for operator support requires near real-time model performance. However, as with all machine learning models, development of a PINN involves time-consuming model training. Here, we show that a transfer learning (TL-PINN) approach achieves significant performance gain, as measured by reduction of the number of iterations for model training. Using point kinetic equations (PKEs) model with six neutron precursor groups, constructed with experimental parameters of the Purdue University Reactor One (PUR-1) research reactor, we generated different RTs with experimentally relevant range of variables. The RTs were characterized using Hausdorff and Fréchet distance. We have demonstrated that pre-training TL-PINN on one RT results in up to two orders of magnitude acceleration in prediction of a different RT. The mean error for conventional PINN and TL-PINN models prediction of neutron densities is smaller than 1%. We have developed a correlation between TL-PINN performance acceleration and similarity measure of RTs, which can be used as a guide for application of TL-PINNs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

A Regulatory Approach to Accelerated Deployment for New Material or Applications in Advanced Reactors

New advanced reactor developers may embark on deploying materials in novel and unique environments where a material’s long-term performance may be in question or unknown. In many cases, sufficient test data may not exist for the material in the desired application, or that no prescript or applicable regulatory testing requirements are available to demonstrate the safety of the application explicitly. This study endeavors to develop the framework for a regulatory and technical approach for safe and predictable accelerated materials use in advanced reactors guided by 10 CFR Part 50.43(e)(1), Advanced Reactor Design Criteria contained in Regulatory Guide 1.232, and Reliability Integrity Management Program (RIM) principles.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Reactor Performance and Safety Characteristics of Beryllium-Based Composite Moderators as Replacements for Graphite in mHTGRs

Here, this study evaluates beryllium-based two-phase composite moderators as an alternative to graphite in an evaluation of reactor performance and safety characteristics. Historically, modular high-temperature gas-cooled reactors (mHTGRs) use graphite as a moderator because of its high moderating ratio and reasonable thermal properties; however, graphite has unfavorable properties under irradiation, which can require component replacement and a significant radioactive waste burden. In this assessment, we explore advanced moderators comprised of magnesium oxide (MgO) as the host matrix and beryllium metal and/or beryllium oxide (Be and/or BeO) as the entrained moderating phase. For the reactor performance and thermal-hydraulic safety analysis, the core design model of the General Atomics mHTGR-350 was used to demonstrate the feasibility of a “drop-in” replacement of graphite using the beryllium-based moderators. We employed the neutronics code Serpent to analyze the moderating behavior of the composite moderators with comparisons drawn to graphite. We performed a scoping analysis of accidents for mHTGRs using RELAP to show that these moderators do not present impediments to safety and are expected to stay within temperature limits. Measured thermophysical properties of the composite moderators are used in the thermal-hydraulic assessments. Our analysis reveals that the two-phase composite MgO-matrix beryllium-based moderators are a suitable replacement for graphite.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Pressure Drop in Seven-Pin Wire-Wrapped Rod Bundle for the Sodium Cartridge Loop in Versatile Test Reactor

This work studies the hydrodynamics of the seven pin wire-wrapped rod bundle in the sodium cartridge loop for the Versatile Test Reactor (VTR) through scaled water experiments and computational fluid dynamics (CFD) simulations. Here, the scaling analysis is first performed to demonstrate the hydrodynamic similarity between water and sodium flows at the same Reynolds number Re. A separate-effects test facility is designed and constructed based on the scaling analysis. Detailed experimental data on the pressure drop covering a wide range of Re values (1165 to 27 689) are obtained, which are used to evaluate existing correlations for friction factor and to benchmark CFD simulations. The experimentally determined friction factors f Exp agree well with the Upgraded Cheng and Todreas Detailed Correlation and Pacio-Chen-Todreas Detailed Model within ±7% but are significantly underpredicted by Rehme's correlation by 25%. Various CFD near-wall treatment methods are tested using ANSYS Fluent and evaluated by experimental data. It is found that when the recommended wall y + values are met, most of the near-wall treatment methods can give accurate friction factor predictions. The resolved near-wall method (y + ~ 1) with the Shear Stress Transport k - ω turbulence model and the scalable wall functions (y + > 12) with the realizable k - ε turbulence model can predict f Exp within ±5% The standard wall functions (y + > 30) and nonequilibrium wall functions (y + > 30) with the realizable k - ε model can predict f Exp within ±10%.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗