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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Numerical Evaluation of Effective Thermal Conductivity of PCM with Metal Foam Incorporating Buoyancy Effects for Thermal Energy Storage

The thermal energy storage (TES) system has the capability to efficiently preserve thermal energy directly derived from the energy source, minimizing any conversion losses. Especially latent heat storage offers distinct advantages, including a substantial increase in energy storage density and minimization of temperature fluctuations within the plants. However, the phase change material (PCM) employed in latent heat storage has low thermal conductivity. Consequently, various studies are being conducted to enhance heat transfer. One approach to enhance heat transfer involves utilizing metal foam to maximize the heat transfer area. However, modeling metal foam with its intricate structure is a challenging task in numerical analysis. For this reason, ongoing research focuses on simplifying the modeling of metal foam. Nevertheless, fully encompassing all the characteristics of actual metal foam proves to be a challenging task for the simplified analytical model. The objective of this paper is to interpret the simple lattice metal foam analysis model from the perspective of behavior induced by buoyancy. When comparing the analysis results of solid PCM and liquid PCM with the same thermal conductivity under changes in porosity and gravity direction, we conducted an analysis to discern the trends in effective thermal conductivity that are overestimated due to convection. In the analysis, a constant heat flux of 10 kW and a constant surface boundary condition of 350 K were applied, and a sensitivity study regarding the mesh was conducted. The results indicate that, from the perspective of gravity in the simple lattice model, the solid analysis yields an effective thermal conductivity 29-47% higher compared to the liquid analysis. Additionally, as porosity increases, there is an observed increase of 24-33% in effective thermal conductivity.

25 ENERGY STORAGE↗
DOE OSTI2024

Computational study on the impact of gasoline-ethanol blending on autoignition and soot/NO x emissions under low-load gasoline compression ignition conditions

Here, in the present work, computational fluid dynamics (CFD) simulations of a single-cylinder gasoline compression ignition (GCI) engine are performed to investigate the impact of gasoline-ethanol blending on autoignition, nitrogen oxide (NO x ), and soot emissions under low-load conditions. In order to represent the test gasoline (RD5-87), a four-component toluene primary reference fuel (TPRF)+ethanol (ETPRF) surrogate (with 10% ethanol by volume; E10) is employed. A three-dimensional (3D) engine CFD model employing finite-rate chemistry with a skeletal kinetic mechanism (including NO x sub-mechanism), adaptive mesh refinement (AMR), and hybrid method of moments (HMOM) is adopted to capture the in-cylinder combustion phenomena and soot/NO x emissions. The engine CFD model is validated against experimental data for three gasoline-ethanol blends: E10, E30 and E100, with varying ethanol content by volume. Model validation is carried out for a broad range of start-of-injection (SOI) timings (−21, −27, −36, and −45 crank angle degrees (°CA) after top-dead-center (aTDC)) with respect to in-cylinder pressure, heat release rate, combustion phasing, NO x and soot emissions. For relatively later injection timings (−21 and −27 °CA aTDC), E30 yields higher amount of soot than E10; while the trend reverses for early injection cases (−36 and −45 °CA aTDC ). On the other hand, E100 yields the lowest amount of soot among all fuels irrespective of SOI timing. Further, E10 shows a non-monotonic trend in soot emissions with SOI timing: SOI-36>SOI-45>SOI-21>SOI-27, while soot emissions from E30 exhibit monotonic decrease with advancing SOI timing. NO x emissions from various fuels follow a trend of E10>E30>E100. On the other hand, NO x emissions increase as SOI timing is advanced for all fuels, with an anomaly for E10 and E100 where NO x decreases when SOI is advanced beyond −36 °CA aTDC. Detailed analysis of the numerical results is performed to investigate the soot/NO x emission trends and elucidate the impact of chemical composition and physical properties on autoignition and emissions characteristics.

Computational fluid dynamics↗
DOE OSTI2024

Development of Segregated Thermal-Hydraulics Solvers in MOOSE

The simulation of fluid flows is an essential part of the design and analysis of nuclear systems. Algorithms able to simulate flows at different fidelity levels are available in the Multiphysics Object-Oriented Simulation Environment (MOOSE) and MOOSE-based applications such as Pronghorn \cite{novak2018pronghorn}, Pronghorn-Subchannel, RELAP-7, and SAM. Currently, significant effort is being invested in the development of coarse-mesh Computational Fluid Dynamics (CFD) capabilities within MOOSE and Pronghorn for the simulation of Generation IV nuclear reactors. Traditionally, the solution algorithms in MOOSE have relied on Newton or quasi-Newton methods (such as the preconditioned Jacobian-free Newton-Krylov method) where residuals and Jacobians (or approximations thereof) are constructed. Both Newton and quasi-Newton methods require the solution of a linear system at each nonlinear Newton iteration with the Jacobian as the system matrix. The Jacobian contains blocks originating from all variables in the problem (i.e., for thermal-hydraulics at least pressure, velocities, and temperature). Due to the formulation of the problem in a general multiphysics setting on unstructured mesh, creating a good preconditioner for the linear system can be challenging, thus many fluid applications have utilized direct solver-based methods such as LU factorization. However, with increasing system size and complexity in multi-dimensional problems, the direct solution of linear systems becomes computationally expensive both in execution time and and memory. For this reason, recent effort has focused on adapting segregated solution algorithms for CFD problems in MOOSE. These algorithms use fixed-point iteration between segregated systems whose assembly and preconditioning are easier those of the monolithic system. Initial results show that the segregated solution algorithm outperforms the monolithic approach in terms of memory usage and for large 3D problems in terms of CPU time as well.

42 ENGINEERING↗
DOE OSTI2024

Development of Segregated Thermal-Hydraulics Solvers in MOOSE

The simulation of fluid flows is an essential part of the design and analysis of nuclear systems. Algorithms able to simulate flows at different fidelity levels are available in the Multiphysics Object-Oriented Simulation Environment (MOOSE) and MOOSE-based applications such as Pronghorn \cite{novak2018pronghorn}, Pronghorn-Subchannel, RELAP-7, and SAM. Currently, significant effort is being invested in the development of coarse-mesh Computational Fluid Dynamics (CFD) capabilities within MOOSE and Pronghorn for the simulation of Generation IV nuclear reactors. Traditionally, the solution algorithms in MOOSE have relied on Newton or quasi-Newton methods (such as the preconditioned Jacobian-free Newton-Krylov method) where residuals and Jacobians (or approximations thereof) are constructed. Both Newton and quasi-Newton methods require the solution of a linear system at each nonlinear Newton iteration with the Jacobian as the system matrix. The Jacobian contains blocks originating from all variables in the problem (i.e., for thermal-hydraulics at least pressure, velocities, and temperature). Due to the formulation of the problem in a general multiphysics setting on unstructured mesh, creating a good preconditioner for the linear system can be challenging, thus many fluid applications have utilized direct solver-based methods such as LU factorization. However, with increasing system size and complexity in multi-dimensional problems, the direct solution of linear systems becomes computationally expensive both in execution time and and memory. For this reason, recent effort has focused on adapting segregated solution algorithms for CFD problems in MOOSE. These algorithms use fixed-point iteration between segregated systems whose assembly and preconditioning are easier those of the monolithic system. Initial results show that the segregated solution algorithm outperforms the monolithic approach in terms of memory usage and for large 3D problems in terms of CPU time as well.

42 ENGINEERING↗
DOE OSTI2023

Non-Nuclear Test Facility Development to Support Verification and Validation Needs

This study focuses on developing a non-nuclear test facility to help meet the verification and validation (V&V) requirements of a water-cooled small modular reactor (SMR) system. The scaling analysis necessary for reactor system experimentation and assessment model V&V considers various reactor system accident scenarios such as main steam line break (MSLB), steam generator tube rupture (SGTR), and containment condensation and heat transfer. The goal is to identify key physics based phenomena of interest (POI), specific figures of merit (FOMs), and the state of knowledge (SOK) by employing phenomena identification and ranking table (PIRT) studies. Important physics phenomena such as heat transfer, fluid dynamics, structural integrity, and material selection must be addressed when scaling a thermal-hydraulics system. Alongside these considerations, modifications to the facility may be needed to align the scaled system with the available footprint (height and space) of the facility. These modifications may include infrastructure upgrades, changes to the piping layout, implementation of safety measures, and installation of new instrumentation and control systems. The test facility aims to provide a scaled-down version of prototypic facilities for comprehensive V&V activities by overcoming these challenges and making the necessary modifications. This approach minimizes scaling distortion, simulates prototypic plant conditions, and accurately models accident event progressions. Thus, the facility will be capable of adequately modeling a scaled SMR system to support the design, development and licensing needs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Geometry-Driven Detection, Tracking and Visual Analysis of Viscous and Gravitational Fingers

Viscous and gravitational flow instabilities cause a displacement front to break up into finger-like fluids. The detection and evolutionary analysis of these fingering instabilities are critical in multiple scientific disciplines such as fluid mechanics and hydrogeology. However, previous detection methods of the viscous and gravitational fingers are based on density thresholding, which provides limited geometric information of the fingers. The geometric structures of fingers and their evolution are important yet little studied in the literature. In this work, we explore the geometric detection and evolution of the fingers in detail to elucidate the dynamics of the instability. Additionally, we propose a ridge voxel detection method to guide the extraction of finger cores from three-dimensional (3D) scalar fields. After skeletonizing finger cores into skeletons, we design a spanning tree based approach to capture how fingers branch spatially from the finger skeletons. Finally, we devise a novel geometric-glyph augmented tracking graph to study how the fingers and their branches grow, merge, and split over time. Feedback from earth scientists demonstrates the usefulness of our approach to performing spatio-temporal geometric analyses of fingers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Simulation of Premixed and Partially Premixed Jet-in-Crossflow Flames at High Pressure

In this paper, we explore the operational map of a lean axial-staged combustor of premixed and partially premixed reacting jet-in-crossflow flames at high -pressure (5 atm). This study attempts to expand the data to relatively high pressure and could significantly aid scaling to real gas turbine engine conditions at 20–30 atm. High-speed camera, particle image velocimetry (PIV), CH* chemiluminescence, temperature, and pressure measurements were taken and processed to allow accurate reconstruction of six operating points relative to computational fluid dynamics (CFD) simulations under minimal adjustments. Variation of lean main stage (φ = 0.575 and 0.73) and rich jet (φ = 1.1, 4, and 8) equivalence ratio has been investigated for a four mm axial jet. The fully premixed flames were found to be controlled by the crossflow temperature before ignition and the crossflow oxygen content during combustion. Analysis of flame shape and position for the partially premixed operating points describes a lee stabilized as well as a more unsteady windward flame branch. Adjustment of added jet fuel and crossflow temperature along with its corresponding oxygen level is required to attain a compact flame body. Here, the risk of delaying combustion progress is significantly increased at a richer jet φ = 8 and an overshooting, spatially divided flame was attained with a main stage φ = 0.73. Control toward a compact flame body is critical to allow combustion at reasonable reaction rate.

03 NATURAL GAS↗
DOE OSTI2022

Computational study of inertial migration of prolate particles in a straight rectangular channel

Inertial migration of spherical particles has been investigated extensively using experiments, theory, and computational modeling. Yet, a systematic investigation of the effect of particle shape on inertial migration is still lacking. Herein, we numerically mapped the migration dynamics of a prolate particle in a straight rectangular microchannel using smoothed particle hydrodynamics at moderate Reynolds number flows. After validation, we applied our model to 2:1 and 3:1 shape aspect ratio particles at multiple confinement ratios. Their effects on the final focusing position, rotational behavior, and transitional dynamics were studied. In addition to the commonly reported tumbling motion, for the first time, we identified a new logrolling behavior of a prolate ellipsoidal particle in the confined channel. This new behavior occurs when the confinement ratio is above an approximate threshold value of K = 0.72. Our microfluidic experiments using cell aggregates with similar shape aspect ratio and confinement ratio confirmed this new predicted logrolling motion. In this study, we also found that the same particle can undergo different rotational modes, including kayaking behavior, depending on its initial cross-sectional position and orientation. Furthermore, we examined the migration speed, angular velocity, and rotation period as well as their dependence on both particle shape aspect ratio and confinement ratio. Our findings are especially relevant to the applications where particle shape and alignment are used for sorting and analysis, such as the use of barcoded particles for biochemical assays through optical reading, or the shape-based enrichment of microalgae, bacteria, and chromosomes.

42 ENGINEERING↗
DOE OSTI2026

A multiscale packed-bed reactor model for sustainable ethylene production via chemical looping oxidative coupling of methane

The rising global warming concerns and shale gas discovery have prompted research in the direction of greenhouse gas (GHG), such as methane, reduction and conversion. Oxidative coupling of methane (OCM) offers a pathway to low carbon-intense valorization of methane while producing ethylene, a chemical regarded as central to the petrochemical industry. Even after decades of OCM discovery, researchers keep understanding the process and underlying chemical reactions in a pursuit to achieve industrial viability for OCM. Here, in general, OCM suffers from low C 2 selectivity, yield and reactor temperature runaways due to highly exothermic nature of its reactions. Computational Fluid Dynamics (CFD) tools help analyze spatial gradients within the reactor to deeply understand the diffusion of species, mass and heat transfer phenomena. Furthermore, challenges associated with scaling up such as hot spot formation and parametric sensitivity can be addressed without having to expend on costly experiments. The current paper presents a multiscale packed-bed reactor CFD model coupled with a chemical kinetic model for the chemical looping OCM. The CFD model includes two scales i.e., macroscale for catalyst bed and microscale for individual pellets. Moreover, a chemical kinetic model based on 10 gas-phase reactions is integrated with the CFD model. An additional surface reaction for the formation of gas-phase oxygen from catalyst surface is added to account for the absence of feed oxygen. The model is calibrated against experimental results. The calibrated model captures trends in CH 4 conversion, C 2 selectivity and C 2 yield within a ± 4.35 % range across a temperature range of 700-900 °C. Moreover, model fidelity is evaluated by varying key computational parameters such as mesh resolution and time step size. The model is also verified by varying the inlet methane concentration and the gas hourly space velocity (GHSV) and comparing the results with literature. A sensitivity analysis and scale-up of the current model is undergoing.

Chemical looping↗
DOE OSTI2026

Learning turbulent flows with generative models for super resolution and sparse flow reconstruction

Neural operators are promising surrogates for dynamical systems but when trained with standard L 2 losses they tend to oversmooth fine-scale turbulent structures. Here, we show that combining operator learning with generative modeling overcomes this limitation. We consider three practical turbulent-flow challenges where conventional neural operators fail: spatio-temporal super-resolution, forecasting, and sparse flow reconstruction. For Schlieren jet super-resolution, an adversarially trained neural operator (adv-NO) reduces the energy-spectrum error by 15 × while preserving sharp gradients at neural operator-like inference cost. For 3D homogeneous isotropic turbulence, adv-NO trained on only 160 timesteps from a single trajectory forecasts accurately for five eddy-turnover times and offers 114 × wall-clock speed-up at inference than the baseline diffusion-based forecasters, enabling near-real-time rollouts. For reconstructing cylinder wake flows from highly sparse Particle Tracking Velocimetry-like inputs, a conditional generative model infers full 3D velocity and pressure fields with correct phase alignment and statistics. These advances enable accurate reconstruction and forecasting at low compute cost, bringing near-real-time analysis and control within reach in experimental and computational fluid mechanics.

Fluid dynamics↗
DOE OSTI2024

Improvements to the Blade Element Momentum Formulation of OpenFAST for Skewed Inflows

In this work, we modify the blade element momentum algorithm of OpenFAST to improve its predictions under large skewed inflow conditions. We use the well-known Glauert's skew correction and introduce continuous extension of the model for high-thrust conditions. We present the rationale behind Glauert's empirical model and discuss the different conventions possible for the axial induction factor. We verify the model against the higher-fidelity lifting-line vortex method and blade-resolved computational fluid dynamics, and we observe that the new implementation enhances the accuracy and reliability of OpenFAST's aerodynamic modeling capabilities in conditions involving large skew angles. For the parametric studies run using the different codes, we find that the power changes with the skew angle as cos 1.7 (θ skew ) and the thrust as cos 0.65 (θ skew ). An analysis of the azimuthal variation of the induced velocities in the rotor plane reveals that current redistribution models used in blade element momentum codes may need to be refined.

17 WIND ENERGY↗
DOE OSTI2019

Initial Simulations of Empty Room Collapse and Reconsolidation at the Waste Isolation Pilot Plant

The Waste Isolation Pilot Plant (WIPP) is a geologic repository for defense-related nuclear waste. If left undisturbed, the virtually impermeable rock salt surrounding the repository will isolate the nuclear waste from the biosphere. If humans accidentally intrude into the repository in the future, then the likelihood of a radionuclide release to the biosphere will depend significantly on the porosity and permeability of the repository itself. Room ceilings and walls at the WIPP tend to collapse over time, causing rubble piles to form on floors of empty rooms. The surrounding rock formation will gradually compact these rubble piles until they eventually become solid salt, but the length of time for a rubble pile to reach a certain porosity and permeability is unknown. This report details the first efforts to build models to predict the porosity and permeability evolution of an empty room as it closes. Conventional geomechanical numerical methods would struggle to model empty room collapse and rubble pile consolidation, so three different meshless methods, the Immersed Isogeometric Analysis Meshfree, Reproducing Kernel Particle Method (RKPM), and the Conformal Reproducing Kernel method, were assessed. First, the meshless methods and the finite element method each simulated gradual room closure, without ceiling or wall collapse. All three methods produced equivalent room closure predictions with comparable computational speed. Second, the Immersed Isogeometric Analysis Meshfree method and RKPM simulated two-dimensional empty room collapse and rubble pile consolidation. Both methods successfully simulated large viscoplastic deformations, fracture, and rubble pile rearrangement to produce qualitatively realistic results. In addition to geomechanical simulations, the flow channels in damaged salt and crushed salt were measured using micro-computed tomography, and input into a computational fluid dynamics simulation to predict the salt's permeability. Although room for improvement exists, the current simulation approaches appear promising.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Coupled Thermal-Hydraulic Analysis and Species Mass Transport in a Versatile Experimental Salt Irradiation Loop (VESIL) using COBRA-TF

With the resurgence of interest in Molten Salt Reactor (MSR) technology among commercial and governmental agencies, there is a need for new experiments and new modelling capabilities to characterize the unique phenomena present in this fluid fuel system. A Versatile Experimental Salt Irradiation Loop (VESIL) is currently under investigation at Idaho National Laboratory. It is designed to be a dynamic fuel-bearing salt loop placed in the Advanced Test Reactor. One of the key phenomena this proposed experiment plans to elucidate is fission product speciation in the fuel-salt and the subsequent effects this can have on fuel-salt properties, fission product transport and interactions, source term generation, corrosion and redox potential control. Specifically, noble gases (Xe & Kr) will bubble out to a plenum or off-gas system and noble metals (Mo, Tc, Te etc.) will precipitate and deposit in specific zones in the loop. This work extends the mass transfer and species interaction models in the general species transport capability of COBRA-TF (CTF) and applies these models to give a preliminary estimation of fission product behavior in the proposed VESIL design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Perspectives on Microfluidics for the Study of Asphaltenes in Upstream Hydrocarbon Production: A Minireview

The utilization of microfluidics has generated deep insights into asphaltene precipitation mechanisms and oil–water emulsion stabilization. Agglomeration and precipitation of asphaltenes can cause flow assurance problems during the extraction and transportation of crude oil. Change in temperature, pressure, reservoir conditions, and solvents can change the local environment, leading to asphaltene precipitation. Understanding asphaltene properties and precipitation pathways becomes critical in devising mitigation methods, demulsifiers, and suitable conditions during hydrocarbon processing. Microfluidics has helped in high throughput measurement studies, understanding critical processing conditions, fast demulsifier screening, and the effect of solvent concentration on deposition, generating useful information for utilization at the point of resource extraction facilitating improved resource management. It has become possible to capture the porous, complex nature of reservoir formations and the interaction of chemicals during precipitation through integrated analytics and visualization studies available only through microfluidics. The use of droplet microfluidics, with optical microscopy and high-speed imaging to study the oil–water interface, has resulted in greater understanding of the role of asphaltenes in interfacial properties and emulsion stabilization. Here, this minireview highlights the crucial aspects of microfluidics that have been used to understand physicochemical behavior and dynamics of asphaltene deposition. Some of the unique devices have been presented focusing on the key elements of microfluidics design, fabrication, and analysis, as the insight obtained from microfluidics strongly depends on the device design and the controllability of the experimental parameters. Successful implementation of microfluidics for efficient and controlled experiments, short analysis time scales and rapid screening, and generation of high-quality, reliable data that convey asphaltene deposition issues and interface behavior in emulsions shows the importance of microsystems for advancing knowledge in hydrocarbon production and processing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

CFD modeling of non-catalytic, partial-oxidation engine reformer for flare mitigation

Flaring associated natural gas is commonly employed in the oil and gas industry to reduce methane (CH 4 ) emissions but generates carbon dioxide (CO 2 ) and harmful pollutants, significantly contributing to air pollution and posing risks to public health. To mitigate this impact, M2X Energy Inc. has developed a small-scale, modular gas-to-methanol system. This system features an engine reformer that performs fuel-rich partial oxidation of wellhead gas to produce syngas—a mixture of carbon monoxide (CO) and hydrogen (H 2 )—followed by a downstream reactor for methanol synthesis. This study focused on computational fluid dynamics (CFD) modeling of the engine reformer to simulate partial oxidation chemistry, predict the rich-burn operating limit, and assess syngas quality, ultimately aiding in design and operational optimization. The CFD model, developed within a Reynolds-Averaged Navier-Stokes (RANS) turbulence framework, incorporated sub-models for turbulent combustion, a chemical mechanism with polycyclic aromatic hydrocarbon (PAH) pathways, and soot emissions to accurately capture the fuel-rich, turbulent jet ignition and combustion processes. Model validation against experimental data showed good agreement across pre- and main-chamber pressures, apparent heat release rates, and exhaust gas concentrations of key species (H 2 , CO, CO 2 , CH 4 ) for varying intake equivalence ratios. Here, the model identified a rich-burn operating limit near a fuel-air equivalence ratio of 2.35, consistent with experimental observations. Furthermore, syngas quality analysis revealed that extending the rich-burn limit through engine reformer optimization could enhance syngas production, contributing to higher methanol synthesis efficiency.

Computational Fluid Dynamics↗
DOE OSTI2021

High-speed impact of micron-sized diesel drop trains—Splashing dynamics, secondary droplet formation, and effects of pre-existing film thickness

This work investigates surface impingement of monodispersed diesel drop trains using computational simulations. The three-dimensional simulations include high-speed impact of micrometer-sized fuel drops onto initially dry and wetted stainless steel substrates. The drop size and impact velocity are representative of fuel injection conditions in internal combustion engines (ICEs). The drop trains serve as a simplified representation of fuel spray. To accurately capture the film that naturally develops on initially dry substrates, a dynamic diesel-stainless steel contact angle model was developed using experiments of single drop impact under ICE representative temperature. Simulations are presented for a highly splashing case and the effects of a pre-existing film on splashing dynamics were investigated, including the temporal evolution of splashed mass and film thickness. It was concluded that for thin films, the effect of pre-existing film thickness is less significant than in single drop impingement. Secondary droplet characterization was performed on simulation results, leading to instantaneous and time-averaged distributions of secondary droplet size, velocity magnitude, and trajectory angle. It was found that for each drop impingement, approximately 58% of the splashed mass is from the impinging drop itself, while the remainder of the splashed mass is composed of film liquid. From a high resolution case, details of secondary droplet formation are observed and three distinct phases of secondary droplet formation are identified. The detailed analysis of drop train impingement under engine-relevant conditions serves as a first step toward a robust understanding of fuel impingement and the development of cleaner and more efficient ICEs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

High fidelity multiphysics tightly coupled model for a lead cooled fast reactor concept and application to statistical calculation of hot channel factors

A tightly coupled multiphysics code system is established using the MOOSE framework for hot channel factor (HCF) evaluation on a Lead Fast Reactor (LFR) concept. The coupled system is driven by the Griffin multiphysics coupling capability under which the MOOSE Heat Transfer module and NekRS computational fluid dynamics solver are coupled for conjugate heat transfer using the Cardinal application. The coupled capability is demonstrated on an LFR assembly model based on materials and geometry of a prototypical lead-cooled fast reactor design by Westinghouse Electric Company, LLC. Moreover, the work integrates the Multiphysics Object Oriented Simulation Environment (MOOSE) Stochastic Tools Module (STM) to perform calculations for statistical analysis of HCF. Furthermore, the coupling strategy and workflow demonstrated in this paper is not only useful for predicting accurate hot channel factors for different kinds of advanced reactors but also for other engineering applications such as control rod worth assessment, generation of high-fidelity database for Artificial intelligence (AI)/machine learning (ML) training, design optimization and multi-resolution modeling.

Cardinal↗