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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Modelling Nuclear Thermal Propulsion Reactor Startup Transients

The National Aeronautics and Space Administration (NASA) has set the goal of a manned mission to Mars by the year 2030 [1] and charged the national academy of sci- ences "to identify primary technical and programmatic chal- lenges, merits, and risks for maturing space nuclear propulsion technologies of interest to a future human Mars exploration mission" [2]. One relevant technology, nuclear thermal propul- sion (NTP), has notable advantages over traditional chemical rockets; most important among them is the ability to produce larger specific impulse on the order of 900s. The reduction of mission time is crucial for a manned mission to Mars to reduce the risk for the crew. Due to its higher specific impulse, NTP satisfies this need and is pursued as one technology to get humans to Mars [3, 4]. The construction of an NTP sys- tem has to negotiate several challenges laid out in Ref. [2]; one of these challenges is the need to startup the NTP sys- tem from essentially cold conditions to full power within one minute. This paper focuses on studying the neutronics and thermal-hydraulics behavior of a simplified NTP model dur- ing prescribed reactivity insertions and mass flow rate (MFR) ramps. It is the goal of this paper to investigate startup, peak material temperatures, and average specific impulse for a low enriched Uranium (LEU), ceramic and metal material (CER- MET) NTP system when varying reactivity insertion and MFR ramps.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Development of a three-dimensional APOLLO3 neutrons deterministic scheme for the CABRI reactor

CABRI is an experimental reactor to study the fuel behavior during reactivity injection transients. These transients being highly multiphysics, the development of suitable modeling and simulation tools to simulate them is important for the optimization of the tests and the control of the experimental conditions. This paper focuses on the development of an APOLLO3 deterministic core calculation tool dedicated to the CABRI transient analysis. It represents the first stage of the incremental process for the implementation of a multiphysics time-dependent modeling of the CABRI transient. The neutron calculation scheme is based on a classical two-step approach. The first step consists of a 281-energy group calculation flux with the TDT-MOC (Method Of Characteristics) solver for cross-section space and energy (23 groups) collapsing for the CABRI different assembly clusters. The bias on a 2D core neutron calculation due to the self-shielding calculation and collapsing on a restricted pattern are investigated thanks to a comparison with a direct full 2D calculation on a quarter of core. The second step relies on a pin-resolved transport 3D transport core calculation with the SN solver MINARET. A progressive numerical validation process is followed to quantify the calculation biases on reactivity and reaction rates at each step using reference calculations with the stochastic code TRIPOLI4. The next development stage toward a multiphysics scheme will be the implementation of the 3D-kinetics equation resolution and the coupling with a core thermal-hydraulics model. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2014

Pervasive Restart In MOOSE-based Applications

Multiphysics applications are inherently complicated. Solving for multiple, interacting physical phenomena involves the solution of multiple equations, and each equation has its own data dependencies. Feeding the correct data to these equations at exactly the right time requires extensive effort in software design. In an ideal world, multiphysics applications always run to completion and produce correct answers. Unfortunately, in reality, there can be many reasons why a simulation might fail: power outage, system failure, exceeding a runtime allotment on a supercomputer, failure of the solver to converge, etc. A failure after many hours spent computing can be a significant setback for a project. Therefore, the ability to “continue” a solve from the point of failure, rather than starting again from scratch, is an essential component of any high-quality simulation tool. This process of “continuation” is commonly termed “restart” in the computational community. While the concept of restarting an application sounds ideal, the aforementioned complexities and data dependencies present in multiphysics applications make its implementation decidedly non-trivial. A running multiphysics calculation accumulates an enormous amount of “state”: current time, solution history, material properties, status of mechanical contact, etc. This “state” data comes in many different forms, including scalar, tensor, vector, and arbitrary, application-specific data types. To be able to restart an application, you must be able to both store and retrieve this data, effectively recreating the state of the application before the failure. When utilizing the Multiphysics Object Oriented Simulation Environment (MOOSE) framework developed at Idaho National Laboratory, this state data is stored both internally within the framework itself (such as solution vectors and the current time) and within the applications that use the framework. In order to implement restart in MOOSE-based applications, the total state of the system (both within the framework and without) must be stored and retrieved. To this end, the MOOSE team has implemented a “pervasive” restart capability which allows any object within MOOSE (or within a MOOSE-based application) to be declared as “state” data, and handles the storage and retrieval of said data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Electromagnetic Simulations of Newly Designed Semiconductor Bolometers for Submillimeter Observations

In the frame of the SPICA mission, new semiconductor bolometers have been designed for the POL instrument which is directly part of the HERSCHEL/PACS legacy. These detectors are cooled down to 50 mK and are sensitive to polarization for the 100, 200 and 350 μm wavelength bands. In this paper, 3D simulations have been carried out with the COMSOL Multiphysics software to design the two suspended interlaced silicon spirals which support the orthogonal absorbers (sensitive to the two polarizations) of the POL detectors. These simulations allow to optimize the design of the absorbers and to quantify the cross-polarization. In the last part of this paper, we explain how it is possible to reach the 200 and 350 μm bands from the layout of the 100-μm detector.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Measurement and simulation of thermoelectric efficiency for single leg

Thermoelectric efficiency measurements were carried out on n-type bismuth telluride legs with the hot-side temperature at 100 and 150°C. The electric power and heat flow were measured individually. Water coolant was utilized to maintain the cold-side temperature and to measure heat flow out of the cold side. Leg length and vacuum pressure were studied in terms of temperature difference across the leg, open-circuit voltage, internal resistance, and heat flow. Finite-element simulation on thermoelectric generation was performed in COMSOL Multiphysics, by inputting two-side temperatures and thermoelectric material properties. The open-circuit voltage and resistance were in good agreement between the measurement and simulation. Much larger heat flows were found in measurements, since they were comprised of conductive, convective, and radiative contributions. Parasitic heat flow was measured in the absence of bismuth telluride leg, and the conductive heat flow was then available. Finally, the maximum thermoelectric efficiency was derived in accordance with the electric power and the conductive heat flow.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Qualitative Analysis, Structure-Preserving Discretizations and Scalable Solvers for Multiphysics Problems. Final Technical Report

Many problems in physics, engineering, meteorology, computer science, and other fields involve a certain level of coupling between different physical quantities. With the development of advanced computational modeling, simulation, and hardware, simulations for many important multiphysics/multiscale coupling effects are now more tractable. In this project, we have developed robust, efficient, and practical numerical algorithms for such simulation software that are capable of tackling these complex mathematical models in many fundamental ways such as stability, wellposedness, and consistency. We expect that such an integrated theoretical and algorithmic framework will have a substantial impact on numerous multiscale and multiphysics modeling and simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

An open-source hybrid unstructured mesh - CAD fusion multiphysics analysis workflow in SALAMANDER

Plasma facing components in fusion devices will endure extreme neutron and heat fluxes. To facilitate their design using simulation tools, the open-source Fusion Module, Fusion ENergy Integrated multiphys-X (FENIX) framework is being developed to model these components with a high-fidelity multi-physics multi-dimensional approach. It can iteratively resolve couplings between all the physics at play, from neutron radiation, to thermomechanics, to near-wall plasma dynamics. This framework is based on the Multiphysics Object Oriented Simulation Environment (MOOSE), which is developed by a collaboration of US National Laboratories since 2008, for advanced nuclear, geomechanics simulations and other applications. FENIX couples numerous simulation tools, including OpenMC, the Tritium Migration Analysis Program v8, the NekRS CFD software, and most MOOSE modules. For the coupling of radiation transport and other physics, FENIX supports a hybrid workflow between Computer Assisted Design (CAD) and unstructured mesh geometries. The CAD can be generated from skinning the unstructured mesh, to enable a coarse geometry for efficient particle transport, but still resolving the local material compositions and temperature gradients. Neutron transport is performed using DAGMC on the CAD, and Cardinal, integrated in FENIX, maps tallied quantities, such as the heat deposition or the tritium generation rates, from a tally volumetric mesh to the other physics’ unstructured mesh. This coupling was exercised on a simplified tokamak geometry, coupling neutron transport with the heat conduction equation, and on a monoblock divertor problem, coupling additionally with tritium migration. Mesh convergence studies highlight the importance of the mapping conservativeness. Coupling with thermo-mechanics is further enabled by the generalization of the approach to moving meshes. The presentation will include these coupled analysis as well as an update on status of the FENIX framework.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

SciDAC ISEP: Integrated Simulation of Energetic Particles in Burning Plasmas

The objective of the SciDAC Center for Integrated Simulation of Energetic Particles in Burning Plasmas (ISEP) is to improve physics understanding of energetic particle (EP) confinement and EP interactions with burning thermal plasmas through large-scale simulations. The ISEP center will develop a multiscale and multiphysics ISEP framework for a predictive capability of EP physics and deliver an EP module incorporating both first-principles simulations and high fidelity reduced transport models to the fusion whole device modeling (WDM) project. The ISEP framework will enable us to perform long time, global kinetic simulations of EP physics in burning plasmas, by utilizing the full power of the next generation supercomputers. Our research and development activities will build on fruitful collaborations with computer scientists and applied mathematicians to offer enabling technologies for performance scalability, portability, solvers, coupling for integration with the fusion WDM project, and long-term preservation of data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Stone Content Influence on Land Surface Model Simulation of Soil Moisture and Evapotranspiration at Reynolds Creek Watershed

Considerable advancement in spatiotemporal resolution of remote sensing and ground-based measurements has enabled refinement of parameters used in land surface models for simulating surface water fluxes. However, land surface modeling capabilities are still inadequate for accurate representation of subsurface properties and processes, which continue to limit the accuracy of land surface model simulation. Our objective in this study was to examine the performance of the variously parameterized Noah-Multiphysics (Noah-MP) land surface model and to improve simulations of evapotranspiration (ET) and soil moisture dynamics in stony soils using verification from eddy covariance ET and in-situ soil moisture data. Meteorological and eddy covariance data from the Lower Sheep sub-catchment within the Reynolds Creek Experimental Watershed in Southwestern Idaho were employed to drive Noah-MP and to assess simulation results. We evaluated the performance of Noah-MP considering four different scenarios: (1) A one-layer soil profile with Noah-MP default soil hydraulic parameters, followed by five-layer soil profiles using -(2) Noah-MP default soil hydraulic parameters -(3) soil hydraulic parameters derived from a pedotransfer function using field observations, and -(4) hydraulic parameters from (3) which also accounted for stone content in each layer. Each modeling experiment was forced with the same set of initial conditions, atmospheric input and vegetation parameters. Our results indicated that enhanced representation of soil profile properties and stone content information noticeably improve the Noah-MP land surface model simulation of soil moisture content and evapotranspiration.

Land surface models, Soil hydrology, Noah-MP, Evap↗
DOE OSTI2013

Load Balancing for Multiphysics. In: AIAA 2013-2856,

Coupled Multi-Physics simulations, such as hybrid CFD-MD simulations, represent an increasingly important class of scientific applications. Often the physical problems of interest demand the use of high-end computers, such as TeraGrid resources, which are often accessible only via batch-queues. Batch-queue systems are not developed to natively support the coordinated scheduling of jobs – which in turn is required to support the concurrent execution required by coupled multi-physics simulations. In this paper we develop and demonstrate a novel approach to overcome the lack of native support for coordinated job submission requirement associated with coupled runs. We establish the performance advantages arising from our solution, which is a generalization of the Pilot-Job concept – which in of itself is not new, but is being applied to coupled simulations for the first time. Our solution not only overcomes the initial co-scheduling problem, but also provides a dynamic resource allocation mechanism. Support for such dynamic resources is critical for a load balancing mechanism, which we develop and demonstrate to be effective at reducing the total time-to-solution of the problem. We establish that the performance advantage of using Big Jobs is invariant with the size of the machine as well as the size of the physical model under investigation. The Pilot-Job abstraction is developed using SAGA, which provides an infrastructure agnostic implementation, and which can seamlessly execute and utilize distributed resources.

Lohner, Rainald↗
DOE OSTI2025

AdditiveFOAM: A Continuum Multiphysics Code for Additive Manufacturing

AdditiveFOAM is a computational framework that simulates transport phenomena in Additive Manufacturing (AM) processes. It is built on OpenFOAM (Weller et al., 1998), the leading free, open-source software package for computational fluid dynamics (CFD). OpenFOAM offers an extensible platform for solving complex multiphysics problems using state-of-the-art finite volume methods. AdditiveFOAM leverages these capabilities to develop specialized tools aimed at addressing challenges in AM processing. Metal additive manufacturing, also known as metal 3D printing, is an advanced manufacturing technique that creates physical parts from a three-dimensional (3D) digital model by melting metal powder or wire feedstock. A significant area of research in metal AM focuses on process planning to mitigate anomalous features during printing that are deleterious to part performance (e.g., porosity and cracking), as well as controlling localized microstructure and material properties. Given the high costs and substantial time requirements associated with experimental methods for qualifying new materials and processes, there is a compelling incentive for researchers to utilize advanced computational simulations. In this context, AdditiveFOAM offers a simulation framework to better understand undesirable features in printing, thereby enhancing process planning and reducing the reliance on labor-intensive experimental campaigns.

Coleman, John [Oak Ridge National Laboratory (ORNL↗
DOE OSTI2024

Transition in ICF Capsule Implosions

Longstanding design and reproducibility challenges in inertial confinement fusion (ICF) capsule implosion experiments involve recognizing the need for appropriately characterized and modeled three-dimensional initial conditions and high-fidelity simulation capabilities to predict transitional flow approaching turbulence, material mixing characteristics, and late-time quantities of interest—e.g., fusion yield. We build on previous coarse graining simulations of the indirect-drive national ignition facility (NIF) cryogenic capsule N170601 experiment-a precursor of N221205 which resulted in net energy gain. We apply effectively combined initialization aspects and multiphysics coupling in conjunction with newly available hydrodynamics simulation methods, including directional unsplit algorithms and low Mach-number correction-key advances enabling high fidelity coarse grained simulations of radiation-hydrodynamics driven transition. Our presentation includes discussion of the capsule initialization and implosion dynamics, analysis of the vorticity production budget, transition signatures, quantities of interest—late-time ion temperature and fusion-neutron yield, numerical uncertainty quantification, and comparisons with NIF data.

42 ENGINEERING↗
DOE OSTI2023

VERA Integration in the NEAMS Workbench

The Virtual Environment for Reactor Applications (VERA) is a cutting edge simulation code suite used to solve complex multiphysics problems for nuclear reactors. VERA makes use of high performance computing (HPC) systems to solve large problems that were not historically tractable. While extensive work has been put into the usability of VERA, it still takes significant effort to build reactor models, ensure their correctness, properly execute the calculations, and conduct the necessary analysis of the results. This difficulty is common for many complex codes such as VERA. As part of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the NEAMS Workbench has been developed and maintained. The goal of the NEAMS Workbench is to provide a single interface with which to execute a wide variety of physics codes, from building the input models to analyzing the results. This document serves as a manual detailing the current integration of VERA with the NEAMS Workbench and a guide for configuring Workbench to allow remote execution of VERA.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Recent progress on coarse graining simulations

We focus on coarse graining simulations based on the primary conservation equations, effectively codesigned physics and algorithms, and low-Mach-number corrected (LMC) hydrodynamics. Simulation methods involve LANL’s x-Radiation-Adaptive-Grid-Eulerian Large-Eddy Simulation, Besnard-Harlow-Rauenzahn (BHR) Reynolds-Averaged Navier-Stokes (RANS) approach, and Dynamic BHR – a paradigm bridging RANS and LES. A relevant question addressed relates to whether 3D RANS and RANS/LES hybrids – the industry standards for aerospace and automotive research, are presently relevant for practical variable-density applications involving shocked and accelerated interface instabilities. Furthermore, recent simulations of the GaTECH inclined mixing-layer shock-tube and NIF ICF-capsule experiments are used to demonstrate issues, challenges, and potential for 3D coarse grained LMC simulation strategies for robustly simulating complex transitional and coupled hydrodynamics-multiphysics with coarser resolution. Present LES readiness to provide accurate predictions at scale is demonstrated – whereas 3D RANS and RANS/LES bridging do not appear impactful in this context.

42 ENGINEERING↗
DOE OSTI2024

Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks and Operators in Scientific Computing: Fluid and Solid Mechanics

Abstract Advancements in computing power have recently made it possible to utilize machine learning and deep learning to push scientific computing forward in a range of disciplines, such as fluid mechanics, solid mechanics, materials science, etc. The incorporation of neural networks is particularly crucial in this hybridization process. Due to their intrinsic architecture, conventional neural networks cannot be successfully trained and scoped when data are sparse, which is the case in many scientific and engineering domains. Nonetheless, neural networks provide a solid foundation to respect physics-driven or knowledge-based constraints during training. Generally speaking, there are three distinct neural network frameworks to enforce the underlying physics: (i) physics-guided neural networks (PgNNs), (ii) physics-informed neural networks (PiNNs), and (iii) physics-encoded neural networks (PeNNs). These methods provide distinct advantages for accelerating the numerical modeling of complex multiscale multiphysics phenomena. In addition, the recent developments in neural operators (NOs) add another dimension to these new simulation paradigms, especially when the real-time prediction of complex multiphysics systems is required. All these models also come with their own unique drawbacks and limitations that call for further fundamental research. This study aims to present a review of the four neural network frameworks (i.e., PgNNs, PiNNs, PeNNs, and NOs) used in scientific computing research. The state-of-the-art architectures and their applications are reviewed, limitations are discussed, and future research opportunities are presented in terms of improving algorithms, considering causalities, expanding applications, and coupling scientific and deep learning solvers.

Computer Science↗
DOE OSTI2015

Multiphysics Model of Palladium Hydride Isotope Exchange Accounting for Higher Dimensionality

This report summarizes computational model development and simulations results for a series of isotope exchange dynamics experiments including long and thin isothermal beds similar to the Foltz and Melius beds and a larger non-isothermal experiment on the NENG7 test bed. The multiphysics 2D axi-symmetric model simulates the temperature and pressure dependent exchange reaction kinetics, pressure and isotope dependent stoichiometry, heat generation from the reaction, reacting gas flow through porous media, and non-uniformities in the bed permeability. The new model is now able to replicate the curved reaction front and asymmetry of the exit gas mass fractions over time. The improved understanding of the exchange process and its dependence on the non-uniform bed properties and temperatures in these larger systems is critical to the future design of such systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Supplying materials needed for grain growth characterizations of nano-grained UO 2

This activity is supported by the US Nuclear Energy Advanced Modeling and Simulation (NEAMS) Fuels Product Line (FPL) and aims at providing experimental data for the validation of the mesoscale simulation code MARMOT. MARMOT is a mesoscale multiphysics code that predicts the coevolution of microstructure and properties within reactor fuel during its lifetime in the reactor. It is an important component of the Moose-Bison-Marmot (MBM) code suite that has been developed by Idaho National Laboratory (INL) to enable next generation fuel performance modeling capability as part of the NEAMS Program FPL. In order to ensure the accuracy of the microstructure based materials models being developed within the MARMOT code, extensive validation efforts must be carried out. In this report, we summarize our preliminary synchrotron radiation experiments at APS to determine the grain size of nanograin UO 2 . The methodology and experimental setup developed in this experiment can directly apply to the proposed in-situ grain growth measurements. The investigation of the grain growth kinetics was conducted based on isothermal annealing and grain growth characterization as functions of duration and temperature. The kinetic parameters such as activation energy for grain growth for UO 2 with different stoichiometry are obtained and compared with molecular dynamics (MD) simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗