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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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DOE OSTI2024

Extended dynamic mode decomposition for model reduction in fluid dynamics simulations

High computational cost and storage/memory requirements of fluid dynamics simulations constrain their usefulness as a predictive tool. Reduced-order models (ROMs) provide a viable solution to this challenge by extracting the key underlying dynamics of a complex system directly from data. We investigate the efficacy and robustness of an extended dynamic mode decomposition (xDMD) algorithm in constructing ROMs of three-dimensional cardiovascular computations. Focusing on the ROMs' accuracy in representation and interpolation, we relate these metrics to the truncation rank of singular value decomposition, which underpins xDMD and other approaches to ROM construction. Our key innovation is to relate the truncation rank to the singular values of the original flow problem. This result establishes a priori guidelines for the xDMD deployment and its likely success as a means of data compression and reconstruction of the system's dynamics from dominant spatiotemporal structures present in the data.

Mechanics↗
DOE OSTI2022

Prospects of federated machine learning in fluid dynamics

Physics-based models have been mainstream in fluid dynamics for developing predictive models. In recent years, machine learning has offered a renaissance to the fluid community due to the rapid developments in data science, processing units, neural network based technologies, and sensor adaptations. So far in many applications in fluid dynamics, machine learning approaches have been mostly focused on a standard process that requires centralizing the training data on a designated machine or in a data center. In this article, we present a federated machine learning approach that enables localized clients to collaboratively learn an aggregated and shared predictive model while keeping all the training data on each edge device. We demonstrate the feasibility and prospects of such a decentralized learning approach with an effort to forge a deep learning surrogate model for reconstructing spatiotemporal fields. Our results indicate that federated machine learning might be a viable tool for designing highly accurate predictive decentralized digital twins relevant to fluid dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Hydrodynamic flow in small systems or: “How the heck is it possible that a system emitting only a dozen particles can be described by fluid dynamics?”

The "unreasonable effectiveness'' of relativistic fluid dynamics in describing high energy heavy-ion and even proton-proton collisions will be demonstrated and discussed. Several recent ideas of optimizing relativistic fluid dynamics for the specific challenges posed by such collisions will be presented, and some thoughts will be offered why the framework works better than originally expected. I will also address the unresolved question where exactly hydrodynamics breaks down, and why.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Cosmological consequences of first-order general-relativistic viscous fluid dynamics

In this work, we investigate the out-of-equilibrium dynamics of viscous fluids in a spatially flat Friedmann-LemaîtreRobertson-Walker cosmology using the most general causal and stable viscous energy-momentum tensor defined at first order in spacetime derivatives. In this new framework a pressureless viscous fluid having equilibrium energy density ρ can evolve to an asymptotic future solution in which the Hubble parameter approaches a constant while ρ → 0, even in the absence of a cosmological constant (i.e., Λ = 0). Thus, while viscous effects in this model drive an accelerated expansion of the universe, the equilibrium energy density itself vanishes, leaving behind only the acceleration. This behavior emerges as a consequence of causality in first-order theories of relativistic fluid dynamics and it is fully consistent with Einstein’s equations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

An open source fast fluid dynamics model for data center thermal management

Although computational fluid dynamics (CFD) has been widely adopted to improve data center thermal management, the high computational demand limits its applications, such as multivariate optimal design and operation. Fast fluid dynamics (FFD), which has been applied for fast airflow simulation, shows great potential. However, few research applied FFD for optimal design and operation of data center thermal management. This research improves the FFD model for data centers and conducts a comprehensive evaluation and demonstration. First, the FFD model is improved by solving the advection and diffusion equations together using an upwind scheme instead of a semi-Lagrangian advection solver in the conventional FFD model. Second, new features for data centers are added, such as a pressure correction method to simulate plenum airflow and dynamic boundary conditions for IT racks. The new FFD model is first validated with two indoor environment cases and the results show that the new FFD model has slightly better overall prediction accuracy and faster speed compared to the conventional FFD model. It is also observed that both FFD models achieve acceptable accuracy, except for a few localized disparities with experimental data, which might be due to simplified handling of turbulence viscosity near the boundaries. Furthermore, validation with a real data center shows that the FFD model achieves a similar level of accuracy as CFD when compared to the experimental measurements with some level of uncertainties. It is then demonstrated for data center optimal design and operation, which saves 53.4–58.8% of annual energy while still meeting the thermal requirements. In conclusion, with a much faster speed and comparable accuracy compared to CFD, the FFD model parallelized on a graphics processing unit is promising for practical model-based data center early design and operation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Fluid Dynamics Effects on Microstructure Prediction in Single-Laser Tracks for Additive Manufacturing of IN625

Single-track laser fusion were simulated using a heat-transfer-solidification-only (HTS) model and its extension with fluid dynamics (HTS_FD) model using a parallel open-source code, which included laminar fluid dynamics, flat-free surface of the molten alloy, heat transfer, phase-change, evaporation, and surface tension phenomena. The results illustrate that the fluid dynamics affects the solidification and ensuing microstructure. For the HTS_FD simulations, thermal gradient, G was found to exhibit a maximum at the extremity of the solidified pool ( i.e. , at the free surface), while for HTS simulations, G exhibited a maximum around the entire edge of the solidified pool. HTS_FD simulations predicted a wider range of cooling rates than the HTS simulations, exhibited an increased spread in the solidification speed, V variation within the melt-pool with respect to the HTS model results. Primary dendrite arm spacing (PDAS) were evaluated based on power law correlations and marginal stability theory models using the ( G , V ) from HTS and HTS_FD simulations to quantify the effect of the fluid dynamics on the microstructure. At low-laser powers and low-scan speeds, the PDAS obtained with the fluid dynamics model (HTS_FD) was larger by more than 30 pct with respect to the PDAS calculated with the simple HTS model. A new PDAS correlation, i.e. , \( \lambda_{1} \left[ {\mu {\text{m}}} \right] = 832\;G\left[ {\text{K/m}} \right]^{ - 0.5} V\left[ {\text{m/s}} \right]^{ - 0.25} \) , which uses the ( G , V ) results from the HTS_FD model was developed and validated against experimental results.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A computational fluid dynamics simulation framework for ventricular catheter design optimization

OBJECTIVE Cerebrospinal fluid (CSF) shunts are the primary treatment for patients suffering from hydrocephalus. While proven effective in symptom relief, these shunt systems are plagued by high failure rates and often require repeated revision surgeries to replace malfunctioning components. One of the leading causes of CSF shunt failure is obstruction of the ventricular catheter by aggregations of cells, proteins, blood clots, or fronds of choroid plexus that occlude the catheter’s small inlet holes or even the full internal catheter lumen. Such obstructions can disrupt CSF diversion out of the ventricular system or impede it entirely. Previous studies have suggested that altering the catheter’s fluid dynamics may help to reduce the likelihood of complete ventricular catheter failure caused by obstruction. However, systematic correlation between a ventricular catheter’s design parameters and its performance, specifically its likelihood to become occluded, still remains unknown. Therefore, an automated, open-source computational fluid dynamics (CFD) simulation framework was developed for use in the medical community to determine optimized ventricular catheter designs and to rapidly explore parameter influence for a given flow objective. METHODS The computational framework was developed by coupling a 3D CFD solver and an iterative optimization algorithm and was implemented in a high-performance computing environment. The capabilities of the framework were demonstrated by computing an optimized ventricular catheter design that provides uniform flow rates through the catheter’s inlet holes, a common design objective in the literature. The baseline computational model was validated using 3D nuclear imaging to provide flow velocities at the inlet holes and through the catheter. RESULTS The optimized catheter design achieved through use of the automated simulation framework improved significantly on previous attempts to reach a uniform inlet flow rate distribution using the standard catheter hole configuration as a baseline. While the standard ventricular catheter design featuring uniform inlet hole diameters and hole spacing has a standard deviation of 14.27% for the inlet flow rates, the optimized design has a standard deviation of 0.30%. CONCLUSIONS This customizable framework, paired with high-performance computing, provides a rapid method of design testing to solve complex flow problems. While a relatively simplified ventricular catheter model was used to demonstrate the framework, the computational approach is applicable to any baseline catheter model, and it is easily adapted to optimize catheters for the unique needs of different patients as well as for other fluid-based medical devices.

Neurosciences & Neurology↗
DOE OSTI2026

Ensemble Kalman filter for data assimilation coupled with low-resolution computations techniques applied in fluid dynamics

This paper presents an innovative Reduced-order model (ROM) for merging experimental and simulation data using data assimilation (DA) to estimate the "True" state of a fluid dynamics system, leading to more accurate predictions. Our methodology introduces a novel approach by implementing the ensemble Kalman filter (EnKF) within a reduced-dimensional framework, grounded in a robust theoretical foundation and applied to fluid dynamics. To address the substantial computational demands of DA, the proposed ROM employs low-resolution (LR) techniques to drastically reduce computational costs. This innovative approach involves downsampling datasets for DA computations, followed by an advanced reconstruction technique based on low-cost singular value decomposition (lcSVD). The lcSVD method, a key innovation in this paper, has never been applied to DA before and offers a highly efficient way to enhance resolution with minimal computational resources. Our results demonstrate significant reductions in both computation time and RAM usage through these LR techniques without compromising the accuracy of the estimations. For instance, in a turbulent test case, for a data compression rate of 15.9, the LR approach can achieve a speed-up of 13.7 and a RAM compression of 90.9% while maintaining a low relative root mean square error (RRMSE) of 2.6%, compared to 0.8% in the high-resolution (HR) reference. Furthermore, we highlight the effectiveness of the EnKF in estimating and predicting the state of fluid flow systems based on limited observations and given low-fidelity numerical data. This paper highlights the potential of the proposed DA method in fluid dynamics applications, particularly for improving computational efficiency in CFD and related fields. Its ability to balance accuracy with low computational and memory costs makes it especially suitable for large-scale and real-time applications, such as environmental monitoring or engineering design. This method will be incorporated into ModelFLOWs-app.

Data Assimilation↗
DOE OSTI2021

Fluid Dynamics in Curvilinear Coordinates without Fictitious Forces

The use of curvilinear coordinates is sometimes indicated by the inherent geometry of a fluid dynamics problem, but this introduces fictitious forces into the momentum equations that spoil the strict conservative form. If one is willing to work in three dimensions, these fictitious forces can be eliminated by solving for rectangular (Cartesian) momentum components on a curvilinear mesh. A thoroughly geometric approach to fluid dynamics on spacetime demonstrates this transparently, while also giving insight into a greater unity of the relativistic and nonrelativistic cases than is usually appreciated.

pseudo-forces↗
DOE OSTI2018

Fluid Dynamics Effects on Microstructure Prediction in Single Laser Tracks for Additive Manufacturing

The Laser Powder Bed Fusion Additive Manufacturing (LPBFAM) is one of the most important processes for the production of lightweight, cost-effective, complex, and high-performance enduse parts. At present, the cost and time associated with LPBFAM process development is very high due to a lack of fundamental process understanding. In this project, a multi-physics model was developed on a highly parallel open-source code, Truchas, with the ultimate goal of providing experimentally validated process maps for tailoring microstructure to achieve desired performance for LPBFAM. As a critical step towards fully LPBFAM modeling, modeling of single-track laser fusion (STLF) were conducted. Multi-physics simulations were conducted using Truchas for STLF by considering heat transfer, phase-change, fluid dynamics, surface tension phenomena, and evaporation. In order to assess the effect of the fluid dynamics on the solidification and ensuing microstructure, a heat transfer-and-solidification-only (HTS) model and a fully coupled heat-transfer-solidification and fluid-dynamics (HTS-FD) model were considered. In the HTS_FD model, the fluid flow was considered to be laminar while the molten alloy surface is assumed to be flat and non-deformable. This study is one the first attempt to understand the effect of the fluid flow on microstructure in STLF and LPBFAM. The results show that the fluid flow affects the solidification and ensuing microstructure in STLF. In order to validate Truchas for STLF and LPBFAM modeling, experimental data, which was obtained at GE Global Research (GEGR) for liquid pool shape and microstructure, were compared with those from numerical simulation results. For the keyhole regime case, numerical simulation results indicate that the melt-pool shape was typical to that of the conduction case with very large deviations from the measured melt-pool depths. Two sensitivity studies were conducted by varying the evaporation flux and the surface tension coefficient at fixed laser absorptivities of 0.5 and 0.3, respectively. The minimum value for the overall combined error, between the calculated values with the HTS_FD model and measured values for both the width and height of the melt-pool, was attained for a surface tension coefficient of -0.75e-4 N/m. An analytical solidification model for the columnar-to-equiaxed transition (CET) in rapid solidification was used to assess the microstructure variation within the melt-pool. From numerical simulation results, thermal gradient, G, and solidification velocity, V, were obtained in order to predict the microstructure type (e.g., dendritic, cellular). For the fluid-flow HTS_FD model, G was found to exhibit a maximum at the extremity of the solidified pool (i.e., at the free surface). By contrast, for HTS simulations, G was found to exhibit a maximum around the entire edge of the solidified pool. For the HTS_FD simulations, the minimum values of the cooling rate, GV, were found to be approximately half than their corresponding values for HTS simulations. By contrast with the min GV values, the maximum values for GV were found to occur for the HTS_FD simulations. Thus, HTS_FD simulations were found to exhibit a wider range of cooling rates than the HTS simulations. Concerning the solidification maps, the variation of the solidification velocity, V, as function of the thermal gradient, G, was obtained. It was found that the fluid flow model results (HTS_FD) exhibited an increased spread in the V(G) variation within the melt pool with respect to the HTS model results (without the fluid flow). A preliminary correlation model for the primary dendrite arm spacing (PDAS) based on a power law dependence on thermal gradient and solidification velocity was used to estimate PDAS from HTS and HTS_FD simulations. For low laser powers and low laser speeds, the PDAS obtained 6 with the fluid dynamics model (HTS_FD) was larger by more than 30% with respect to the PDAS calculated with the simple HTS model. In the second part of the project, fifty-seven simulations were conducted in order to obtain data on microstructure variables that can be used for process map development. In order to cover the entire processing space, thirty-three cases were selected STLF process simulations at six power levels and six laser scanning speeds. The 57 STLF process simulations were conducted as follows: 33 simulations with the heat-transfer-only (HTS) model and 24 simulations with the fluid flow model (HTS_FD). The solidification map data shows that for all simulations, a columnar dendritic microstructure would be expected. It was found that the minimum, average, and maximum thermal gradient exhibit exponential variations with respect to a process variable defined as the ratio between the power and square root of scan speed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Verification and Validation of Open-Source Computational Fluid Dynamics Capabilities in MOOSE

The Multiphysics Object Oriented Simulation Environment (MOOSE) advances predictive modeling in nuclear research by simplifying the application design process and making modeling more efficient and accessible to researchers and the broader community. Because of MOOSE’s critical role in the scientific computation field, verification and validation are important to evaluate the reliability and credibility of MOOSE’s code, simulations, and models. To assess MOOSE’s Navier Stokes module and turbulence models, the following verification and validation University of Manchester ERCOFTAC cases were simulated in MOOSE, and the results were compared: Case 032 Turbulent Flow in a 2D Channel Case 079 Natural Convection in an Enclosed Cavity

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2025

Assessing VQLS for Fluid Dynamics on a Hybrid Quantum-HPC Stack

Recent advances in quantum linear solvers offer a promising direction for accelerating extreme scientific computations such as fluid dynamics. However, the deep and complex circuits required by many quantum algorithms limit their practical use on current quantum hardware. The Variational Quantum Linear Solver (VQLS) presents a viable alternative for near-term quantum devices (NISQ), and initial efforts have explored its application to select fluid dynamics problems. In this work, we evaluate the use of VQLS for canonical fluid dynamics problems, aiming to identify pathways for generalizing its implementation across a broader class of systems. We analyze the impact of various circuit ansatz and classical optimizers on solution quality and convergence behavior. Furthermore, we assess the algorithm's feasibility within a hybrid quantum–high-performance computing (HPC) framework by porting it to QFw, a state-of-the-art quantum-HPC software stack. 11This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan. This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the US DOE under Contract No. DE-AC05-00OR22725.

Gopalakrishnan Meena, Murali [ORNL] (ORCID:0000000↗
DOE OSTI2024

Evaluating crown scorch predictions from a computational fluid dynamics wildland fire simulator

Abstract Background Crown scorch—the heating of live leaves, needles, and buds in the vegetative canopy to lethal temperatures without widespread combustion—is one of the most common fire effects shaping post-fire canopies. Despite the ability of computational fluid dynamic models to finely resolve fire activity and buoyant plume dynamics including heterogenous 3D distributions of forest canopy heating, these models have had only limited use in simulating fire effects and have not been used to evaluate crown scorch. Here, we demonstrate a method of evaluating crown scorch using a computational fluid dynamics model, FIRETEC, and validate this approach by simulating the experiments that were used to develop Van Wagner’s 1973 crown scorch model. Results The average scorch height prediction from FIRETEC compares well with the empirical model derived by Van Wagner, which is the most widely used empirical model for crown scorch. We further find that the 3D buoyant plume dynamics from a steady and homogeneous idealized heat source on the ground results in a spatially heterogenous crown scorch pattern reflecting complex heating dynamics that are best represented by percent scorch rather than height of scorch. Conclusions The ability of the computational fluid dynamics model to capture variation in crown scorch due to 3D buoyant plume dynamics provides direct links between forest structure, fire behavior, and fire effects that can be used by forest managers and researchers to better understand how fires result in crown damage under various environmental and management scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Minkowski and Galilei/Newton Fluid Dynamics: A Geometric 3 + 1 Spacetime Perspective

A kinetic theory of classical particles serves as a unified basis for developing a geometric 3 + 1 spacetime perspective on fluid dynamics capable of embracing both Minkowski and Galilei/Newton spacetimes. Parallel treatment of these cases on as common a footing as possible reveals that the particle four-momentum is better regarded as comprising momentum and inertia rather than momentum and energy; and, consequently, that the object now known as the stress-energy or energy-momentum tensor is more properly understood as a stress-inertia or inertia-momentum tensor. In dealing with both fiducial and comoving frames as fluid dynamics requires, tensor decompositions in terms of the four-velocities of observers associated with these frames render use of coordinate-free geometric notation not only fully viable, but conceptually simplifying. A particle number four-vector, three-momentum ( 1 , 1 ) tensor, and kinetic energy four-vector characterize a simple fluid and satisfy balance equations involving spacetime divergences on both Minkowski and Galilei/Newton spacetimes. Reduced to a fully 3 + 1 form, these equations yield the familiar conservative formulations of special relativistic and non-relativistic fluid dynamics as partial differential equations in inertial coordinates, and in geometric form will provide a useful conceptual bridge to arbitrary-Lagrange–Euler and general relativistic formulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

A space-time parallel algorithm with adaptive mesh refinement for computational fluid dynamics

This work describes a space-time parallel algorithm with space-time adaptive mesh refinement (AMR). AMR with subcycling is added to multigrid reduction-in-time (MGRIT) in order to provide solution efficient adaptive grids with a reduction in work performed on coarser grids. This algorithm is achieved by integrating two software libraries: XBraid (Parallel time integration with multigrid. https://computation.llnl.gov/projects/parallel-timeintegration-multigrid) and Chombo (Chombo software package for AMR applications—design document, 2014). The former is a parallel time integration library using multigrid and the latter is a massively parallel structured AMR library. Employing this adaptive space-time parallel algorithm is Chord (Comput Fluids 123:202–217, 2015), a computational fluid dynamics (CFD) application code for solving compressible fluid dynamics problems. For the same solution accuracy, speedups are demonstrated from the use of space-time parallelization over the time-sequential integration on Couette flow and Stokes’ second problem. On a transient Couette flow case, at least a 1.5× speedup is achieved, and with a time periodic problem, a speedup of up to 13.7× over the time-sequential case is obtained. In both cases, the speedup is achieved by adding processors and exploring additional parallelization in time. The numerical experiments show the algorithm is promising for CFD applications that can take advantage of the time parallelism. Future work will focus on improving the parallel performance and providing more tests with complex fluid dynamics to demonstrate the full potential of the algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Thermal Analysis of a Solid Particle Light-Trapping Planar Cavity Receiver Using Computational Fluid Dynamics

Concentrated solar power (CSP) is one of the most effective ways of harnessing solar power to create efficient, durable, and resilient energy systems. This study entails thermal modeling and analysis of a novel central tower receiver configuration. This receiver uses solid particles as the heat transfer fluid (HTF), a promising option for third-generation CSP systems. The configuration considered here is the light-trapping planar cavity receiver (LTPCR) introduced by the National Renewable Energy Laboratory. While heat transfer studies of various LTPCR subsystems have been done, system-level thermal analysis of the LTPCR receiver has not been attempted. This study also presents important sensitivity analyses of the operating parameters of the CSP system, which can help guide the design of future central tower receivers. This study employs Ansys Fluent as a computational fluid dynamics (CFD) tool to model fluid dynamics and heat transfer in the receiver, intending to quantify its thermal performance. The model seamlessly integrates Monte Carlo ray tracing data, which generates absorbed solar flux profiles from the heliostat field design, with the heat transfer characteristics of the fluidized particle bed. This unified model is designed to accurately predict the thermal behavior of the LTPCR. Analysis of preliminary results reveals that the primary loss mechanisms are radiative and natural convective losses, in that order. Based on observations from a baseline case, several strategies are suggested and numerically tested. These solutions include selective cooling of high-temperature regions and manipulation of particle bed parameters. Selective cooling of high-temperature regions reduced the peak temperature by 151 degrees C and decreased thermal losses by 0.9%. Improving the particle-wall heat transfer coefficient (P-W HTC) of the particle bed decreased the thermal losses by 1.7% and decreased the peak temperatures by 57 degrees C. Decreasing the particle inlet temperature (PIT) also reduced thermal losses by 3.5% and decreased peak temperatures by 29 degrees C. Compounding these strategies improved the thermal losses of the receiver from 13.5% in the baseline case to 7.5%. Additionally, the study explores the variation in thermal performance across different locations of the receiver, where a variation of thermal losses from 12.9% to 17.3% is found. This allows a comprehensive evaluation of potential improvements in efficiency and temperature management.

computational fluid dynamics↗
DOE OSTI2022

Numerical fluid dynamics for FRG flow equations: Zero-dimensional QFTs as numerical test cases. I. The O ( N ) model

The functional renormalization group (FRG) approach is a powerful tool for studies of a large variety of systems, ranging from statistical physics over the theory of the strong interaction to gravity. The practical application of this approach relies on the derivation of so-called flow equations, which describe the change of the quantum effective action under the variation of a coarse-graining parameter. In the present work, we discuss in detail a novel approach to solve such flow equations. This approach relies on the fact that RG equations can be rewritten such that they exhibit similarities with the conservation laws of fluid dynamics. This observation can be exploited in different ways. First of all, we show that this allows to employ powerful numerical techniques developed in the context of fluid dynamics to solve RG equations. In particular, it allows us to reliably treat the emergence of nonanalytic behavior in the RG flow of the effective action as it is expected to occur in studies of, e.g., spontaneous symmetry breaking. Second, the analogy between RG equations and fluid dynamics offers the opportunity to gain novel insights into RG flows and their interpretation in general, including the irreversibility of RG flows. Further, we work out this connection in practice by applying it to zero-dimensional quantum-field theoretical models. The generalization to higher-dimensional models is also discussed. Our findings are expected to help improving future FRG studies of quantum field theories in higher dimensions both on a qualitative and quantitative level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

A Scoping Study to Develop a Computational Fluid Dynamics Based Model to Predict Radiological Materials Packaging Temperatures within a Generic Staging Building

The objective of this work is to perform computational fluid dynamics simulations of a ventilated radiological-material-package staging building to determine the effect of including or excluding a variety of physical effects and computational methods on both the predicted package temperatures and required computational resources. The generic building contains 640 drum-packages containing heat-generating, radiological material supported on four racks that are eight levels tall. Additionally, there is a forced ventilation system, lighting, and insulated walls. Computational models were constructed that included or excluded (a) shelving, (b) effects of unsteadiness, and (c) radiation heat transfer. Simulations with each drum modeled separately were compared to simpler simulations with sets of four drums represented by an equivalent box-package. These models employed between 106 to 107 elements. Steady state simulations predicted package temperatures that were within 0.1°C of simulations that included transient effects and required only one-eighth the computational resources. Calculations that excluded shelving predicted temperatures within 0.6°C of simulations that included shelving and required one-fourth the computational resources. Excluding radiation heat transfer systematically increased temperatures by around 1.5°C but reduced computational resources by a factor of four. The box-package model reduced the computational resources by a factor of 3, but systematically predicted higher temperatures by around 1.1°C. These results will be used to develop an efficient computational fluid dynamics model to assess the ability of different staging building designs to prevent the temperature of package components from exceeding specified limits.

42 ENGINEERING↗