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DOE OSTI2024

Exploring the Feasibility of INCONEL® ALLOY 740H® for Power Plant Headers: Integrating Machine Learning with Computational Fluid Dynamics (CFD)

This keynote presentation explores the behavior of headers—essential components of pipeline systems—using ANSYS simulation software and machine learning techniques. The study aims to predict the thermal and mechanical performance of headers under diverse conditions through both steady-state and transient simulations. We investigate critical parameters such as heat transfer coefficient, fluid velocity, and temperature to optimize header design. Conducted as part of a DOE project led by NCAT in collaboration with UNC Charlotte, this research encompasses multiple key topics. The initial section focuses on the behavior of header systems under steady-state conditions using ANSYS simulation. It underscores the importance of headers in industrial infrastructure, especially in the energy sector, and examines the implications of material selection and flow direction on heat transfer dynamics. Methodologically, we employ Computational Fluid Dynamics (CFD) analysis through ANSYS, detailing the development of models, material properties, geometry specifications, boundary conditions, and meshing strategies. Our simulations explore various operational parameters, including temperature and mass flow rates, crucial for predicting heat transfer coefficients and enhancing header design. Results from the study include parametric investigations into mesh sensitivity, viscosity model evaluations, and the effects of heat transfer locations, all validated against theoretical calculations. We conclude with insights on mesh optimization, the suitability of viscosity models, and recommendations for future research aimed at improving header system efficiency and sustainability in industrial applications.

20 FOSSIL-FUELED POWER PLANTS↗

NASA NTRS1980

Effect of grid system on finite element calculation

Detailed parametric studies of the effect of grid system on finite element calculation for potential flows were made. These studies led to the formulation of a design criteria for optimum mesh system and the development of two methods to generate the optimum mesh system. The guidelines for optimum mesh system are: (1) the mesh structure should be regular; (2) the element should be as regular and equilateral as possible; (3) the distribution of size of element should be consistent with that of flow variables to insure maximum uniformity in error distribution; (4) for non-Dirichlet boundary conditions, smaller boundary elements or higher order interpolation functions should be used; and (5) the mesh should accommodate the boundary geometry as accurately as possible. The results of the parametric studies are presented.

Lee, K. D.↗

NASA NTRS1989

Three dimensional discrete particle simulation of an AOTV

A discrete Particle Simulation method, recently formulated by Baganoff, is discussed in the context of its application to the simulation of the flow field about the Aeroassisted Flight Experiment (AFE). As a basis for discussion the current algorithm is first described. Because of the use of a cubic Cartesian mesh, the representation of the geometry is different than that of other particle methods and an algorithm for its generation is discussed. The method is applied to test problems and then to the AFE calculation with the use of 9.52 million particles and 432,000 cells.

Feiereisen, William J.↗

NASA NTRS1992

CFD goes to school

The part that universities should play in the future development of CFD, which must be evaluated in light of CFD's pacing elements and challenges, is discussed. Attention is given to CFD pacing items that must be in place before routine aerodynamic simulation can be performed including grid generation and geometry surface definition, solution adaptive meshing, more efficient time-accurate simulation, modeling of real-gas effects, multiple relative body motion, and prediction of transition and turbulence modeling. As universities have contributed to research in CFD from its inception, this research should continue to enhance and motivate teaching, improve CFD as a discipline, and stimulate faculty and students.

Steger, Joseph L.↗

NASA NTRS1994

An assessment of the adaptive unstructured tetrahedral grid, Euler Flow Solver Code FELISA

A three-dimensional solution-adaptive Euler flow solver for unstructured tetrahedral meshes is assessed, and the accuracy and efficiency of the method for predicting sonic boom pressure signatures about simple generic models are demonstrated. Comparison of computational and wind tunnel data and enhancement of numerical solutions by means of grid adaptivity are discussed. The mesh generation is based on the advancing front technique. The FELISA code consists of two solvers, the Taylor-Galerkin and the Runge-Kutta-Galerkin schemes, both of which are spacially discretized by the usual Galerkin weighted residual finite-element methods but with different explicit time-marching schemes to steady state. The solution-adaptive grid procedure is based on either remeshing or mesh refinement techniques. An alternative geometry adaptive procedure is also incorporated.

Djomehri, M. Jahed↗

NASA NTRS1996

Computational modeling of magnetically actuated propellant orientation

Unlike terrestrial applications where gravity positions liquid at the 'bottom' of the tank, the location of liquid propellant in spacecraft tanks is uncertain unless specific actions are taken or special features are built into the tank. Some mission events require knowledge of liquid position prior to a particular action: liquid must be positioned over the tank outlet prior to starting the main engines and must be moved away from the tank vent before vapor can be released overboard to reduce pressure. It may also be desirable to positively position liquid to improve propulsion system performance: moving liquid away from the tank walls will dramatically decrease the rate of heat transfer to the propellant, suppressing the boil-off rate, thereby reducing overall mission propellant requirements. The process of moving propellant to a desired position is referred to as propellant orientation or reorientation. Several techniques have been developed to positively position propellant in spacecraft tanks and each technique imposes additional requirements on vehicle design. Propulsive reorientation relies on small auxiliary thrusters to accelerate the tank. The inertia of the liquid causes it to collect in the aft-end of the tank if the acceleration is forward. This technique requires that additional thrusters be added to the vehicle, that additional propellant be carried in the vehicle, and that an additional operational maneuver be executed. Another technique uses Liquid Acquisition Devices (LAD's) to positively position propellants. These devices rely on surface tension to hold the liquid within special geometries (i.e. vanes, wire-mesh channels, start-baskets). While avoiding some of the penalties of propulsive orientation, this technique requires the addition of complicated hardware inside the propellant tank and performance for long duration missions is uncertain. The subject of the present research is an alternate technique for positively positioning liquid within spacecraft propellant tanks: magnetic fields.

Hochstein, John I.↗

NASA NTRS1996

Computational Modeling of Magnetically Actuated Propellant Orientation

Unlike terrestrial applications where gravity positions liquid at the "bottom" of the tank, the location of liquid propellant in spacecraft tanks is uncertain unless specific actions are taken or special features are built into the tank. Some mission events require knowledge of liquid position prior to a particular action: liquid must be positioned over the tank outlet prior to starting the main engines and must be moved away from the tank vent before vapor can be released overboard to reduce pressure. It may also be desirable to positively position liquid to improve propulsion system performance: moving liquid away from the tank walls will dramatically decrease the rate of heat transfer to the propellant, suppressing the boil-off rate, thereby reducing overall mission propellant requirements. The process of moving propellant to a desired position is referred to as propellant orientation or reorientation. Propulsive reorientation relies on small auxiliary thrusters to accelerate the tank. The inertia of the liquid causes it to collect in the aft-end of the tank if the acceleration is forward. Liquid Acquisition Devices (LAD's) rely on surface tension to hold the liquid within special geometries, (i.e. vanes, wire-mesh channels, start-baskets), to positively position propellants. Both of these technologies add significant weight and complexity to the spacecraft and can be limiting systems for long duration missions. The subject of the present research is an alternate technique for positively positioning liquid within spacecraft propellant tanks: magnetic fields. LOX is paramagnetic (attracted toward a magnet) and LH2 is diamagnetic (repelled from a magnet). Order-of-magnitude analyses, performed in the 1960's to determine required magnet size, concluded that the magnets would be prohibitively massive and this option has remained dormant during the intervening years. Recent advances in high-temperature superconducting materials hold the promise of electromagnets with sufficient performance to support cryogenic propellant management tasks. In late 1992, NASA MSFC began a new investigation in this technology commencing with the design of the Magnetically-Actuated Propellant Orientation (MAPO) experiment. A mixture of ferrofluid and water is used to simulate the paramagnetic properties of LOX and the experiment is being flown on the KC-135 aircraft to provide a reduced gravity environment. The influence of a 0.4 Tesla ring magnet on flow into and out of a subscale Plexiglas tank is being recorded on video tape. The most efficient approach to evaluating the feasibility of MAPO is to compliment the experimental program with development of a computational tool to model the process of interest. The goal of the present research is to develop such a tool. Once confidence in its fidelity is established by comparison to data from the MAPO experiment, it can be used to assist in the design of future experiments and to study the parameter space of the process. Ultimately, it is hoped that the computational model can serve as a design tool for full-scale spacecraft applications.

Hochstein, John I.↗

NASA NTRS2024

Usage of ChatGPT for Engineering Design and Analysis Tool Development

ChatGPT, a generative AI large language model, has recently captured significant attention in both the computer science community and the broader public domain. It has demonstrated a wide range of capabilities, from answering simple questions to writing fully functional computer code. This study spotlights both the capabilities and limitations of ChatGPT when addressing engineering problems. The model's capacity to generate practical engineering tools is highlighted through an example of a prompt that leads to an interactive plotting tool, enabling the examination of the fluid boundary layer around a fan blade. Subsequently, the paper also uncovers potential pitfalls in ChatGPT’s application, shown through an unsuccessful attempt to use ChatGPT to automate a process in Ansys Workbench through scripting. The research further investigates ChatGPT's proficiency in addressing inquiries and providing explanations about the functionalities of OpenMDAO, an open-source, multidisciplinary design, analysis, and optimization tool developed at NASA Glenn Research Center. Finally, an optimization methodology, developed with ChatGPT’s help, is applied to the structural optimization of a fan blade. The developed optimization method utilizes T-Blade3 for geometry generation, Ansys Mechanical for meshing and finite element analysis, and sci-kit learn’s MLPRegressor method to generate a trained neural network model of the design space. OpenMDAO is then used to find the optimal point within the design space. The outcome is a significant reduction in stress in the optimized model—less than one-fifth of the stress value in the baseline model.

Design↗

NASA NTRSDate not supplied

Usage of ChatGPT for Engineering Design and Analysis Tool Development

Design↗

DOE OSTI2022

Crucible Melter Simulation in Nek5000

Nuclear tank waste at the Hanford site is slated for vitrification in large scale refractory-lined melters to transform it into a stable borosilicate waste form suitable for long-term storage or disposal. Molten glass corrodes the refractory lining over time at a rate correlated to the velocity of molten glass against the refractory-lined wall. To properly design a melter and plan for maintenance, it is necessary to accurately model the glass flow and find the correlation between flow velocity and corrosion rate. This modeling was started in STAR-CCM+ CFD software and is being continued in Nek5000 for its fast-running and quick turnaround code. This poster explains the basic process of reconstructing the geometry, fluid properties, and heating of test melters in Nek5000. The geometry is imported from a mesh file and boundary conditions assigned based on surface IDs. The fluid properties are set in the .par and .usr case files. The heating of the actual crucibles in joule heating with electrodes but simulated in Nek5000 with a volumetric heat source term. This volumetric heat source is fit to the actual heating profile with piecewise polynomials and exponentials. Basic results and verification methods are explained in the poster, as well as further work that must be done to complete modeling.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2013

Reactor physics verification of the MCNP6 unstructured mesh capability

The Monte Carlo software package MCNP6 has the ability to transport particles on unstructured meshes generated from the Computed-Aided Engineering software Abaqus. Verification is performed using benchmarks with features relevant to reactor physics - Big Ten and the C5G7 computational benchmark. Various meshing strategies are tested and results are compared to reference solutions. Computational performance results are also given. The conclusions show MCNP6 is capable of producing accurate calculations for reactor physics geometries and the computational requirements for small lattice benchmarks are reasonable on modern computing platforms. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2018

Tetrahedral-Mesh Simulations of Shock-Turbulence Interaction

Despite decades of development of unstructured mesh methods, direct numerical simulations (DNS) of turbulent flows are still predominantly performed on structured or unstructured hexahedral meshes with high-order finite-difference methods, weighted essentially nonoscillatory (WENO) schemes, or hybrid schemes formed by their combinations. Tetrahedral meshes offer easy mesh generation and adaptation around complex geometries and the potential of an orientation-free grid that would benefit the isotropic nature of small-scale dissipation, as well as the solution accuracy of intermediate scales. To advance the state of the art of unstructured-mesh simulation capabilities for shock/turbulence interaction, DNS using pure tetrahedral meshes are carried out with the space-time conservation element, solution element (CESE) method in this research. By its design, the CESE method is constructed based on a non-dissipative scheme and is a genuinely multidimensional numerical framework that is free from the use of an approximate Riemann-solver. The numerical framework also provides the ability to add numerical dissipation (the nondissipative scheme acts as the reference state like that of the reversible state in thermodynamics) when needed (with justification from mathematics/physics). The above-mentioned features along with the CESE method's consistent shock-capturing approach and strong enforcement of flux conservation in spacetime offers a novel method to accurately simulate turbulent flows and their interaction with shocks using tetrahedral meshes. Two canonical problems, namely, isotropic turbulence interaction with a normal shock and a Mach 2.9 turbulent boundary layer flow over a 24deg compression corner are investigated in this study. Computational results show reasonably good agreement with experimental data and results from structured-mesh, high-order simulations available in the literature. Successful validation of these canonical problems demonstrated here paves the way for future high-fidelity supersonic flow simulations involving complex-geometries.

Venkatachari, Balaji Shankar↗

DOE OSTI2015

Preliminary Analysis of the Transient Reactor Test Facility (TREAT) with PROTEUS

The neutron transport code PROTEUS has been used to perform preliminary simulations of the Transient Reactor Test Facility (TREAT). TREAT is an experimental reactor designed for the testing of nuclear fuels and other materials under transient conditions. It operated from 1959 to 1994, when it was placed on non-operational standby. The restart of TREAT to support the U.S. Department of Energy’s resumption of transient testing is currently underway. Both single assembly and assembly-homogenized full core models have been evaluated. Simulations were performed using a historic set of WIMS-ANL-generated cross-sections as well as a new set of Serpent-generated cross-sections. To support this work, further analyses were also performed using additional codes in order to investigate particular aspects of TREAT modeling. DIF3D and the Monte-Carlo codes MCNP and Serpent were utilized in these studies. MCNP and Serpent were used to evaluate the effect of geometry homogenization on the simulation results and to support code-to-code comparisons. New meshes for the PROTEUS simulations were created using the CUBIT toolkit, with additional meshes generated via conversion of selected DIF3D models to support code-to-code verifications. All current analyses have focused on code-to-code verifications, with additional verification and validation studies planned. The analysis of TREAT with PROTEUS-SN is an ongoing project. This report documents the studies that have been performed thus far, and highlights key challenges to address in future work.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2016

Charged particle tracking through electrostatic wire meshes using the finite element method

Wire meshes are used across many disciplines to accelerate and focus charged particles, however, analytical solutions are non-exact and few codes exist which simulate the exact fields around a mesh with physical sizes. A tracking code based in Matlab-Simulink using field maps generated using finite element software has been developed which tracks electrons or ions through electrostatic wire meshes. The fields around such a geometry are presented as an analytical expression using several basic assumptions, however, it is apparent that computational calculations are required to obtain realistic values of electric potential and fields, particularly when multiple wire meshes are deployed. The tracking code is flexible in that any quantitatively describable particle distribution can be used for both electrons and ions as well as other benefits such as ease of export to other programs for analysis. The code is made freely available and physical examples are highlighted where this code could be beneficial for different applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

toughio v1.2.2

TOUGH is a widely used general purpose numerical simulator designed for fluid and heat flows of multiphase, multicomponent fluid mixtures in porous and fractured media, which has been applied to many real-world problems such as underground geological storage, geothermal reservoir engineering or nuclear waste disposal, to name a few. `toughio` is a lightweight, object-oriented and vectorized Python library that aims to provide user-friendly routines to facilitate pre- and post-processing of a TOUGH simulation. Although its primary target is the latest version TOUGH3, `toughio` can also be used to read/write TOUGH2 input/output files. Currently, to the best of our knowledge, only PyTOUGH offers an exhaustive number of features to carry out a complete TOUGH simulation using a scripting language. `toughio` and PyTOUGH share the same objectives, yet with different approaches and philosophies. On the one hand, a PyTOUGH mesh is represented as a MULGRAPH geometry where elements can be unstructured horizontally but only layered vertically. It also checks that the model parameters are valid to ensure that a TOUGH simulation runs smoothly. On the other hand, although it provides basic meshing features, `toughio` mostly relies on common third-party softwares (e.g. Abaqus, FLAC3D, Gmsh, LaGriT) to generate the mesh by importing and converting it to a TOUGH mesh, which also conveniently facilitates the coupling of TOUGH with any other simulator that also supports the same mesh formats. Besides, `toughio` is designed to be just a TOUGH input and output file reader/writer. It assumes that the user knows what he is doing and does not verify the validity of the model parameters (`toughio` does verify the functional arguments).

Luu, Keurfon↗

DOE OSTI2023

Coupled Target-Beam-Moderator Optimization for the Second Target Station

This report describes the results for a coupled target-beam-moderator optimization analysis for the Second Target Station (STS) at ORNL's Spallation Neutron Source. This study is a continuation of the optimization analysis for the moderators in the preliminary design of STS performed in 2022. In the 2022 analysis the dimensions of the moderators are parameterized, while the target and the proton beam profile are kept constant. In this analysis the target height and the proton beam profile are added as parameters. This allows to study the coupled effects of changing target, moderator and beam dimensions. Similar to the 2022 analysis, this work is performed with an automated optimization workflow that uses the optimization toolbox DAKOTA, parameterized geometries in CREO and SpaceClaim, the unstructured mesh generation in Attila4MC, and the particle transport code MCNP6.2©. This workflow enables an efficient optimization using high-fidelity geometries. The main conclusions of this analysis are the following: • Coupled beam-target-moderator optimization provides a few additional percent performance gain over stand-alone moderator optimization. • The moderator performance is not very sensitive to the target height (between ≈60 and ≈80 mm) as long as the beam profile is chosen adequately. • The moderator performance is sensitive to the choice of beam spatial standard deviations, even when the footprint is kept constant. • The optimal moderator radius is the same for a beam footprint of 30 cm 2 , 62.5 cm 2 , and 90 cm 2 . Also the slope of the super-gaussian beam profile does not significantly impact the optimal moderator radius. • The optimal parameters and sensitivities are very similar to the 2022 optimization analysis. These results only indicate a a difference in the optimal radius of the cylindrical moderator, however, this has been corrected in the final design moderator optimization. The main purpose of this report is to document the simulations, results and lessons learned. The most impactful results are summarized in. We also note that the target geometry used in this work is not the final design.

43 PARTICLE ACCELERATORS↗

DOE OSTI2014

Surface Remeshing with Robust High-Order Reconstruction

Remeshing is an important problem in variety of applications, such as finite element methods and geometry processing. Surface remeshing poses some unique challenges, as it must deliver not only good mesh quality but also good geometric accuracy. For applications such as finite elements with high-order elements (quadratic or cubic elements), the geometry must be preserved to high-order (third-order or higher) accuracy, since low-order accuracy may undermine the convergence of numerical computations. The problem is particularly challenging if the CAD model is not available for the underlying geometry, and is even more so if the surface meshes contain some inverted elements. We describe remeshing strategies that can simultaneously produce high-quality triangular meshes, untangling mildly folded triangles and preserve the geometry to high-order of accuracy. Our approach extends our earlier works on high-order surface reconstruction and mesh optimization by enhancing its robustness with a geometric limiter for under-resolved geometries. We also integrate high-order surface reconstruction with surface mesh adaptation techniques, which alter the number of triangles and nodes. We demonstrate the utilization of our method to meshes for high-order finite elements, biomedical image-based surface meshes, and complex interface meshes in fluid simulations.

Ray, Navamita↗

DOE OSTI2014

Rigorous Two-Step Activation for Fusion Systems with PyNE - Paper 127

In fusion systems, high energy neutrons activate system components. After shutdown, the biological dose rate from photons emitted from these components must be estimated as a function of position and time for maintenance planning. High resolution results can be obtained using the mesh-based Rigorous Two-Step (R2S) method. A neutron transport simulation provides mesh-based neutron fluxes. Using these fluxes and an appropriate irradiation scenario, a nuclear inventory analysis code is used to determine the photon source density within each mesh volume element at any decay time after shutdown. The photon source density mesh is used as a source for photon transport. Photon fluxes are tallied at positions of interest and flux-to-dose rate conversion factors are used to estimate the biological dose rate. Previous work by the authors involved the creation of R2S-ACT, an open source R2S workflow, using the Direct Accelerated Geometry Monte Carlo (DAGMC) version of MCNP5 (DAG-MCNP5) for both transport steps and the ALARA nuclear inventory analysis code. Various use cases may require different combinations of transport and activation codes, and nearly all of the capabilities of R2S-ACT have broader utility. For these reasons, the individual components of R2S-ACT were reimplemented within PyNE. PyNE is a collaborative, trans-institutional, open source project consisting of Python, Cython, and C++ code pertinent to nuclear simulations and analysis. This work involved additions to the PyNE mcnp, mesh, material, alara, dagmc, and sampling modules. A lightweight r2s module was then added to connect the code from these modules. The r2s and sampling modules, together with DAG-MCNP5 and ALARA form a complete R2S workflow for obtaining shutdown dose rate results. Mesh operations, geometry discretization, physics code input/output parsing, and mesh-based source sampling capabilities have been added to PyNE generically, eliminating the need to duplicate this effort across multiple applications. The PyNE r2s module uses these capabilities to couple MCNP and ALARA to form an R2S workflow, which has been validated with the FNG shutdown dose rate benchmark. Future work will involve benchmarking the workflow using tetrahedral mesh and also non-analog sampling options. added so that they can be used interchangeably. This will allow for comparisons between results obtained by different physics codes with minimal human effort. Work will also be done to create and implement an importance sampling method for biasing neutron transport towards regions of phase space of high importance to photon dose rate tallies. This will improve the efficiency of obtaining shutdown dose rate results in large, highly-attenuating geometries. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗