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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 OSTI2017

Surrogate Models for TREAT Transient Calculations

The Transient Reactor Test Facility (TREAT) at Idaho National Laboratory (INL) is currently preparing for resumption of operation after more than 20 years in a long-term standby state. In parallel with preparation for operations and a new transient testing program, the DOE-NE Advanced Modeling and Simulation program (NEAMS) has been supporting the development of three-dimensional transient multi-physics modeling capabilities within the reactor physics application MAMMOTH [1]. Recently, the MAMMOTH reactor physics team has begun development of uncertainty and sensitivity analysis for the TREAT core. This research will be used to support the analysis of reactor operation and experiment planning. Traditional approaches, i.e., Monte Carlo simulations, for such tasks require a large number of model evaluations under both steady state and transient conditions. However, exhaustive sets of sampling runs are simply not practical here since evaluations of each model can take a substantial amount of time. A solution to this problem is to build a surrogate model employing a smaller number of model evaluations. The surrogate model is designed to provide an accurate and fast approximation to the detailed TREAT model. In this manner, the surrogate model can be used in place of the TREAT transient model for uncertainty and sensitivity analysis at a fraction of the computational cost. The high dimensional model representation (HDMR) [2] method is employed here for approximating the responses of interest in terms of functions of lower dimensions. This method has been implemented in RAVEN [3] and all TREAT transient calculations are performed using the multiphysics code MAMMOTH. In addition, a code interface has also been developed in order to couple RAVEN with MAMMOTH. The surrogate model is then tested and compared for the MAMMOTH model of the TREAT startup testing program Transient Test #15 core [4], and its accuracy is measured by its ability to estimate the mean, coefficient of variance, skewness, excess kurtosis and probability density function of the outputs of Transient Test #15 model, as well as root mean square error metric.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Integrated Molten Salt Reactor Modeling Capabilities in NEAMS Thermal Hydraulics Tools

The DOE neams program supports a full range of computational thermal fluids analysis capabilities and code developments for a broad range of advanced reactor concepts. The research and development approach under the thermal fluids technical area synergistically combines three length and time scales in a hierarchical multi-scale approach. To enable multi-scale thermal fluids capability using these codes, a key joint effort has been underway to develop an integrated system- and engineering-scale thermal fluids analysis capability, through integration of SAM and Pronghorn codes, both based on the MOOSE framework. This report summarizes recent advances in developing an integrated system- and engineering-scale modeling capability for the msr concept, which has gained significant interest in recent years. A consistent framework was established by coupling Pronghorn and SAM through the Saline interface, with thermophysical properties provided by the Molten Salt Thermal Property Database (MSTDB-TP). Further improvements were made to the coupling schemes and domain-overlapping strategies, enhancing the stability and robustness of multi-code simulations. Verification and validation efforts demonstrate the accuracy of this integration across a range of benchmark problems, including one-dimensional heated pipe flows, three-dimensional natural convection loops with evolving isotopic compositions, and \gls{msre} demonstration cases. Within Pronghorn, new capabilities were introduced to model corrosion and noble-metal plating phenomena, supported by an extended thermal-hydraulics framework and refined turbulence treatments. To capture two-phase flow behavior, a multiphase Euler–Euler model was implemented in Pronghorn, including advanced closure relations, high-resolution advection techniques, and capillary force reconstruction. Preliminary verification cases confirm the fidelity of the approach, while planned validation efforts target canonical multiphase benchmarks and application to msr components such as the msre pump bowl. Finally, updates to SAM’s msr mass transfer modeling were extended to consider noble gas migration into porous structures like graphite. The point kinetics model was updated to include reactivity feedback contributions from any defined species, such as xenon. The gas transport model was expanded for applicability to gas mixtures, bubble efflux phenomena, and species transport between liquid and gas phases. A selection of multi-scale Sherwood number correlations from MOSCATO/NekRS and multi-phase correlations from literature have been added for improved accuracy in calculating mass transfer coefficients. A companion effort on developing system-level redox corrosion has also been incorporated into SAM. Collectively, these enhancements strengthen the predictive capability of SAM and Pronghorn for simulating MSR thermal-hydraulics, corrosion, multiphase behavior, and fission-product transport, providing a more complete toolset for design, safety analysis, and licensing support of next-generation \gls{msr}s.

42 - ENGINEERING↗
DOE OSTI2025

BISON: A Finite Element-Based Nuclear Fuel Performance Code

BISON is a finite element-based nuclear fuel performance code applicable to a variety of fuel forms including light water reactor fuel rods, TRISO particle fuel, and metallic rod and plate fuel. It is a multiphysics fuel analysis tool that solves fully-coupled thermomechanical problems. BISON is based on MOOSE and can efficiently solve problems using standard workstations or very large high-performance computers in a variety of different dimensions, including full 3D, 2D-RZ axisymmetric, layered axisymmetric 1D, and spherically symmetric 1D systems. It is developed by a team of scientists and engineers at Idaho National Laboratory and by collaborators. The development of BISON is supported by various funding agencies, principally the United States Department of Energy.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Evaluation of accuracy and convergence of numerical coupling approaches for poroelasticity benchmark problems

Accurate modeling of subsurface flow and transport processes is vital as the prevalence of subsurface activities such as carbon sequestration, geothermal recovery, and nuclear waste disposal increases. Computational modeling of these problems leverages poroelasticity theory, which describes coupled fluid flow and mechanical deformation. Although fully coupled monolithic schemes are accurate for coupled problems, they can demand significant computational resources for large problems. In this work, a fixed stress scheme is implemented into the Sandia Sierra Multiphysics toolkit. Two implementation methods, along with the fully coupled method, are verified with one-dimensional (1D) Terzaghi, 2D Mandel, and 3D Cryer sphere benchmark problems. The impact of a range of material parameters and convergence tolerances on numerical accuracy and efficiency was evaluated. Overall the fixed stress schemes achieved acceptable numerical accuracy and efficiency compared to the fully coupled scheme. However, the accuracy of the fixed stress scheme tends to decrease with low permeable cases, requiring the finer tolerance to achieve a desired numerical accuracy. For the fully coupled scheme, high numerical accuracy was observed in most of cases except a low permeability case where an order of magnitude finer tolerance was required for accurate results. Finally, a two-layer Terzaghi problem and an injection–production well system were used to demonstrate the applicability of findings from the benchmark problems for more realistic conditions over a range of permeability. Simulation results suggest that the fixed stress scheme provides accurate solutions for all cases considered with the proper adjustment of the tolerance. Furthermore, this work clearly demonstrates the robustness of the fixed stress scheme for coupled poroelastic problems, while a cautious selection of numerical tolerance may be required under certain conditions with low permeable materials.

58 GEOSCIENCES↗
DOE OSTI2018

Experimental adventures in variable-density mixing

Variable-density mixing occurs in the ocean and atmosphere, inertial confinement fusion capsules, stars, and many industrial processes. Our team studies mixing at the laboratory scale, with the goal of extending our understanding to larger and smaller length scales and into multiphysics regimes that include such physics as chemical and thermonuclear reactions and high energy density plasmas. I will provide examples of studies from Los Alamos in variable-density mixing in multiple regimes, including shock-driven mixing, subsonic mixing, and high energy density (HED) plasma mixing. In all cases, the density differences of the mixing fluids are at least double, making the mixing well outside regimes covered by the Boussinesq approximation. In these flows, we have discovered time-dependent mixing phenomena, asymmetries in mixing and distribution of turbulent kinetic energy, and interscale energy transfer driven by the mean ow that moves energy from small to large scales via eddy stretching. We have improved our physical understanding by implementing diagnostics such as particle image velocimetry and planar laser induced fluorescence in challenging, shock-driven ow regimes. Our experimental studies and physical understanding benefit from collaborations with colleagues studying turbulence modeling and performing validation simulations, and these collaborations push us to further improve our experimental platforms and diagnostics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2017

Investigation of Vapor Cooling Enhancements for Applications on Large Cryogenic Systems

The need to demonstrate and evaluate the effectiveness of heat interception methods for use on a relevant cryogenic propulsion stage at a system level has been identified. Evolvable Cryogenics (eCryo) Structural Heat Intercept, Insulation and Vibration Evaluation Rig (SHIIVER) will be designed with vehicle specific geometries (SLS Exploration Upper Stage (EUS) as guidance) and will be subjected to simulated space environments. One method of reducing structure-born heat leak being investigated utilizes vapor-based heat interception. Vapor-based heat interception could potentially reduce heat leak into liquid hydrogen propulsion tanks, increasing potential mission length or payload capability. Due to the high number of unknowns associated with the heat transfer mechanism and integration of vapor-based heat interception on a realistic large-scale skirt design, a sub-scale investigation was developed. The sub-project effort is known as the Small-scale Laboratory Investigation of Cooling Enhancements (SLICE). The SLICE aims to study, design, and test sub-scale multiple attachments and flow configuration concepts for vapor-based heat interception of structural skirts. SLICE will focus on understanding the efficiency of the heat transfer mechanism to the boil-off hydrogen vapor by varying the fluid network designs and configurations. Various analyses were completed in MATLAB, Excel VBA, and COMSOL Multiphysics to understand the optimum flow pattern for heat transfer and fluid dynamics. Results from these analyses were used to design and fabricate test article subsections of a large forward skirt with vapor cooling applied. The SLICE testing is currently being performed to collect thermal mechanical performance data on multiple skirt heat removal designs while varying inlet vapor conditions necessary to intercept a specified amount of heat for a given system. Initial results suggest that applying vapor-cooling provides a 50 heat reduction in conductive heat transmission along the skirt to the tank. The information obtained by SLICE will be used by the SHIIVER engineering team to design and implement vapor-based heat removal technology into the SHIIVER forward skirt hardware design.

small scale testing↗
DOE OSTI2022

Fundamental Investigations into the Properties and Performance of Advanced Materials

Intelligent engineering designs require an accurate understanding of material behavior, since any uncertainties or gaps in knowledge must be counterbalanced with heightened factors of safety, leading to overdesign. Therefore, building better structures and pushing the performance of new components requires an improved understanding of the thermomechanical response of advanced materials under service conditions. This dissertation provides fundamental investigations of several advanced materials: thermoset polymers, a common matrix material for fiber-reinforced composites and nanocomposites; aluminum alloy 7075-T6 (AA7075-T6), a high-performance aerospace material; and ceramic matrix composites (CMCs), an advanced composite for extreme-temperature applications. To understand matrix interactions with various interfaces and nanoinclusions at their fundamental scale, the properties of thermoset polymers are studied at the atomistic scale. An improved proximity-based molecular dynamics (MD) technique for modeling the crosslinking of thermoset polymers is carefully established, enabling realistic curing simulations through its ability to dynamically and probabilistically perform complex topology transformations. The proximity-based MD curing methodology is then used to explore damage initiation and the local anisotropic evolution of mechanical properties in thermoset polymers under uniaxial tension with an emphasis on changes in stiffness through a series of tensile loading, unloading, and reloading experiments. Aluminum alloys in aerospace applications often require a fatigue life of over 109 cycles, which is well over ii the number of cycles that can be practically tested using conventional fatigue testing equipment. In order to study these high-life regimes, a detailed ultrasonic cycle fatigue study is presented for AA7075-T6 under fully reversed tension-compression loading. The geometric sensitivity, frequency effects, size effects, surface roughness effects, and the corresponding failure mechanisms for ultrasonic fatigue across different fatigue regimes are investigated. Finally, because CMCs are utilized in extreme environments, oxidation plays an important role in their degradation. A multiphysics modeling methodology is thus developed to address the complex coupling between oxidation, mechanical stress, and oxygen diffusion in heterogeneous carbon fiber-reinforced CMC microstructures.

Schichtel, Jacob J.↗
DOE OSTI2019

A heuristic model inversion for coupled thermo-hydro-mechanical modelling of triaxial experiments

As multiphysics geomechanical models get developed, their increasing complexity and number of parameters make it particularly difficult to calibrate against experimental data. In this contribution, we present a heuristic workflow to invert for parameters of a coupled Thermo-Hydro-Mechanical (THM) model in a way that helps the theoretical modellers refine their definition of the underlying elasto-visco-plastic model itself. We apply this workflow to the calibration of deviatoric and volumetric data for two sets of triaxial experiments on mudstone and sandstone. Here, we show that beyond the calibration of well-defined parameters of the THM model, one or two scaling factors of the experimentally obtained yield surface and two more factors to capture the confinement and pore pressure dependency of the flow law lead to the satisfactory matching of series of experiments at varying confinements for two different rock types. Using this physical model, we also show that tracking the volumetric component of the mechanical power in the numerical simulations might allow reducing the number of experiments required to calibrate the model.

58 GEOSCIENCES↗
DOE OSTI2023

Corrosion of Al-Fe self-pierce riveting joints with multiphysics-based modeling and experiments

Self-piercing riveting (SPR) is an extensively used joining technique to assemble dissimilar materials. However, this joining of the dissimilar materials can generate galvanic/crevice corrosion, which can drastically impact the mechanical properties and the service life of the joint. In this study, a multiphysics-based hybrid modeling approach is developed for the galvanic corrosion of the Al-Fe SPR joints, which can consider the corrosion initiation and corrosion evaluation jointly. Experimental studies are first performed to extract information regarding the corrosion initiation sites, corrosion evolution and overall corrosion induced material loss in SPR joints. The initiation information is then passed onto the multiphysics FE model thus making it a hybrid model. This model can help understand the influences of metal microstructure on the corrosion propagation while the morphology changes can also be analyzed. Using the developed hybrid modeling approach, thorough parametric studies can be performed to explore the coupled impacts of multiple corrosion factors on the corrosion behavior of the joints. The developed hybrid model is validated on the prediction of galvanic corrosion for the SPR joints by comparing with experimental observations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Differentiable, Learnable, Regionalized Process-Based Models With Multiphysical Outputs can Approach State-Of-The-Art Hydrologic Prediction Accuracy

Predictions of hydrologic variables across the entire water cycle have significant value for water resources management as well as downstream applications such as ecosystem and water quality modeling. Recently, purely data-driven deep learning models like long short-term memory (LSTM) showed seemingly insurmountable performance in modeling rainfall runoff and other geoscientific variables, yet they cannot predict untrained physical variables and remain challenging to interpret. Here, we show that differentiable, learnable, process-based models (called δ models here) can approach the performance level of LSTM for the intensively observed variable (streamflow) with regionalized parameterization. We use a simple hydrologic model HBV as the backbone and use embedded neural networks, which can only be trained in a differentiable programming framework, to parameterize, enhance, or replace the process-based model's modules. Without using an ensemble or post-processor, δ models can obtain a median Nash-Sutcliffe efficiency of 0.732 for 671 basins across the USA for the Daymet forcing data set, compared to 0.748 from a state-of-the-art LSTM model with the same setup. For another forcing data set, the difference is even smaller: 0.715 versus 0.722. Meanwhile, the resulting learnable process-based models can output a full set of untrained variables, for example, soil and groundwater storage, snowpack, evapotranspiration, and baseflow, and can later be constrained by their observations. Both simulated evapotranspiration and fraction of discharge from baseflow agreed decently with alternative estimates. The general framework can work with models with various process complexity and opens up the path for learning physics from big data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Can Polyelectrolyte Mechanical Properties be Directly Modulated by an Electric Field? A Molecular Dynamics Study

Multifunctionality in polymers facilitates their application in emerging technologies. Electrical fields are a preferred stimulus because of the speed and ease of application to bulk polymers. While a wide range of electrically triggered actuators are developed, and electrically controlled adhesion between gels is demonstrated, modification of bulk mechanical properties via electrical stimuli remains elusive. Polymers with covalently incorporated ionic charge (polyelectrolytes) should be well suited to achieving this goal since the mechanical properties depend on electrostatic interactions and these charges are intrinsically susceptible to electric fields. Molecular dynamics simulations are utilized here to investigate whether electric fields can modulate the mechanical properties of polyelectrolytes and to understand the governing mechanisms. Mechanical property modulation by electric field is found to be sensitive to the charge distribution—charges must be tightly attached to the polymer backbone, and responsivity is greater if a single backbone contains both positive and negative charges. The dominant mechanisms are reorientation and stretching of the polymer chains, which also elongate the ionic clusters to maintain strong electrostatic interactions throughout deformation. Furthermore, these insights are critical for future experimental realization of polymers with electric field regulated mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Coupled neutronics and species transport simulation of the Molten Salt Reactor Experiment

This paper presents the development of coupling between the molten salt reactor species transport code Mole and the reactor physics code Griffin. Here, in this study, tracking of delayed neutron precursors was investigated in the Molten-Salt Reactor Experiment (MSRE), accounting for changes in fuel flow velocity as a function of position in the primary loop. The neutron transport calculations in Griffin were performed using 11 energy groups, and the species advection calculations in Mole used 6 delayed neutron precursor groups to predict spatial distribution of the neutron flux and neutron precursors in the MSRE. Mole–Griffin was used to calculate $k$ eff and $β$ eff in the reactor as a function of different volumetric flow rates.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRSDate not supplied

Mixed-Domain Charge Transport in S-Se Alloys as a Li-S Battery Cathode Material

Lithium-sulfur batteries are emerging candidate systems for the next-generation long-range electric aircraft application owing to their potential to deliver high energy density per weight. Their cathodes are to be made primarily with sulfur, but sulfur by itself has much too low electron conductivity to serve as a useful cathode. An idea that has been suggested to overcome this bottleneck is to alloy sulfur with selenium in the hope that electron mobility, which is thought to improve charge transport at some expense of increased weight and reduced energy density. However, understanding of these alloy structures and their transport mechanism is insufficient, and electron mobility at varying degrees of selenium content is not well charted, which are critical for determining the optimum selenium content and testing whether this strategy is generally feasible. The difficulty of computationally characterizing these alloy systems is rooted in the structure. The structures of both sulfur and selenium exhibit eight-atom rings that pack together in various orientations to form their respective crystals. For one, because these crystals (and presumably their alloys as well) feature multiple polymorphs such that their structural coherence is rather unclear. Secondly, these are also relatively large systems (32 atoms per cell) with low-symmetry, which complicate computation both in terms of accuracy and efficiency. Thirdly, such semi-molecular, semi-crystalline structures lead to a combination of band-transport characteristics and hopping-transport characteristics, each of which is a domain with its own physics and set of computational, theoretical challenges. In addition, there is a general dearth of experimental transport data for sulfur-selenium alloys. In this study, we make a comprehensive attempt to tackle this problem using a wide array of first-principles methods. We generate special quasirandom structures to simulate alloy structures, and compute their first-principles Raman spectra for comparison with experimental data to ensure their structural soundness. We then proceed to use recently developed, state-of-the-art tool (AMSET) in order to efficiently compute electronic mobilities under band transport of pure sulfur, pure selenium, as well as their alloys of various compositions at a reasonable accuracy. We then sample numerous dimer configurations of nearest-neighbor eight-atom-ring-pairs and compute electronic hopping rates between them, which yields hopping mobility. A combination of these efforts lead to a general mapping of electron transport behaviors throughout the alloy range. Preliminary results show that introduction of selenium into sulfur initially damages electron mobility due to disorder but eventually improves it beyond that of pure sulfur with additional selenium content, ultimately peaking at the pure-selenium limit. Band transport dominates for holes in sulfur and electrons in selenium, but in all other cases, hopping transport is dominant. Ongoing efforts include determination of charge concentration and conductivity, as well as performing multiphysics modeling to determine the optimum selenium content for best tradeoff between conductivity and energy density for aircraft range.

Junsoo Park↗
DOE OSTI2025

Characterization of Fuel-to-Coolant Heat Transfer During Reactivity-Initiated Accidents Using Tightly Coupled Thermal Hydraulics and Fuel Thermomechanics

The reactivity-initiated accident (RIA) is a complex scenario with several tightly interacting physical phenomena. Accurately predicting fuel behavior during these transients is difficult due to limitations in the modeling of fuel-to-coolant heat transfer. Common approaches to simulate RIAs involve standalone calculations using either a fuel performance code or a thermal-hydraulic code. The complex interdependencies of thermal-hydraulic and fuel mechanical behavior suggest that a tight coupling between these codes may provide more accurate predictions of fuel-to-coolant heat transfer and cladding mechanical response. Here, RELAP5-3D and BISON are coupled in this paper to simulate RIAs, and a sensitivity analysis is performed to rank key thermal properties and two-phase heat transfer parameters relevant for fuel-to-coolant heat transfer and cladding failure mechanisms in UO 2 –Zircaloy-4 systems. Gas gap conductance, film boiling heat transfer uncertainty, pulse width, fuel-specific heat capacity, and cladding-specific heat capacity were identified as important parameters. Variations in figures of merit resulting from changes to pulse width and the material thermal properties indicate that time-dependent heat transfer rates are significant for safety-relevant mechanical parameters due to the time dependence of cladding ductility and pellet-cladding mechanical interaction loading. The results suggest that the thermal-hydraulic factors have a nonnegligible influence on the thermomechanical solution and vice versa. Tight coupling of both sets of physics is recommended to improve prediction of fuel behavior during RIAs. Highlights include the following: 1. The RELAP5-3D thermal-hydraulic code and the BISON fuel performance code are tightly coupled for simulation of RIA transients with energy depositions at the Zircaloy-4 cladding failure threshold. 2. Departure from nucleate boiling occurred for all simulated cases. Due to the ductility of fresh fuel, substantial ballooning occurred in most cases. 3. Gas gap conductance, fuel-specific heat capacity, cladding-specific heat capacity, transient pulse width, and film boiling heat transfer were the dominant thermal factors impacting the safety figures of merit at energy depositions.

Critical Heat Flux (CHF)↗
DOE OSTI2022

Development of Conceptual Lead Cartridge Design to Perform Irradiation Experiments in VTR

This paper seeks to introduce the latest design of the Extended Length Test Assembly–Cartridge Lead (ELTA-CL) with associated thermal-hydraulic (TH) assessment and related experiment activities to support the critical component development performed by the ELTA-CL team (Los Alamos National Laboratory, Westinghouse Electric Company, and the University of New Mexico). The goal of the ELTA-CL program is to develop and validate an experimental capability to perform irradiation experiments in the Versatile Test Reactor (VTR) addressing Lead Fast Reactor (LFR) technology gaps, in support of the commercial development of advanced lead-cooled fast reactor concepts. Through a design maturation process and parametric study, a conceptual design is proposed to meet the requirements for material and corrosion testing. Thermal-hydraulic characteristics for the conceptual design at desired operating conditions are assessed with systems-level (one-dimensional) and computational fluid dynamics (three-dimensional) simulations. Along with the conceptual design work, experimental activities for the development of critical components such as the pump and flowmeter are undertaken. From both the modeling study and the experimental results, the design requirements of the Phase 1 ELTA-CL (e.g., 500°C and 2 m/s) are achievable with the current conceptual design. Additional design improvements and safety assessments at both steady-state and transient conditions for the final ELTA-CL design will be pursued.

42 ENGINEERING↗
DOE OSTI2021

SOMAFOAM: An OpenFOAM based solver for continuum simulations of low-temperature plasmas

Here, we report the development of SOMAFOAM, a finite volume framework for performing continuum simulations of low-temperature plasmas. The primary goal of this work is to discuss the features of SOMAFOAM along with representative results provided as examples for a range of operating conditions and geometries. This includes plasma and plasma–dielectric systems operating in direct current, radio frequency, and microwave regimes from pressures as low as 100 mTorr to atmospheric pressure. The code has several useful features including the ability to run massively parallel simulations using arbitrary geometries, structured/unstructured meshes, choice of models such as drift–diffusion/full-momentum at runtime, and species-dependent timesteps to name a few. The verification/validation studies presented include comparison with previously published continuum simulations (low-pressure direct current and radio frequency plasma), with experiments (Gaseous Electronics Conference Reference Cell and microwave microplasma ignited in a split ring resonator), and previously published kinetic simulations (low-pressure radio frequency plasma). Other examples provided include a direct current atmospheric pressure microplasma bounded by dielectric sidewalls and a helium–nitrogen plasma ignited using a needle electrode facing a dielectric. The performance of the code is also discussed with serial and distributed memory parallel runs demonstrated up to 512 cores. The design and implementation of the code in a modular object-oriented framework allows for easy extension and seamless coupling with other codes and can be expected to play an important role in both academia and industry.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Multiscale Modeling of Deformation, Fracture and Failure of Fusion Materials and Structures Final Report

The main objective of the research performed at UCLA under grant number DE-FG02-03ER54708 was to develop a physical understanding of the underlying mechanisms that control high-temperature deformation and fracture of fusion structural materials. The key aspect is the synergistic interaction between thermo-mechanical damage phenomena (e.g. creep, fatigue, and fracture), and irradiation damage phenomena (helium and hydrogen bubbles, and irradiation-induced defects). Another thrust area of the research was on the development of constitutive equations for the mechanical behavior of irradiated structures in fusion components (mainly the First Wall and Plasma-Facing components), and in utilizing them in descriptions in large-scale Finite Element Modeling of fusion structures. A parallel experimental effort on thermo-mechanical and plasma-induced damage is designed to validate and confront the developed theoretical and computational predictions. The models have been experimentally validated through experimental tests in simulated plasma transients on specially-designed W samples. This grant started at UCLA on November 14, 2003 and has had successive continuations till November 14, 2017. Research performed under the grant was to develop a range of hierarchical models for the post-elastic deformation, fracture and failure of fusion structural materials. The developed multiscale modeling approach has been based on rigorous mathematical, physical, and computational methods at the forefront of computational materials science. At the fundamental and smallest length scale (nm-μm), we developed advanced rate theory and Monte Carlo approaches to model microstructure evolution, non-equilibrium phase transformations, and dislocation-defect interactions. Microscopic and mesoscopic models of radiation hardening, ductile-to-brittle-transition, post-elastic deformation, plastic instabilities, and fracture processes are based on Dislocation Dynamics (DD) and Grain Growth Dynamics (GGD). At the continuum level, we focused on modeling fracture and failure mechanisms for Virtual Integrated Testing (VISTA), and for understanding the limits of both materials-by-design versus structural component design through advancing the new approach of multiscale-multiphysics. The overall research has been strongly coupled with the U.S. national experimental program to ascertain and verify the range of investigated phenomena. In the following, we give a summary of research progress supported by this grant since its inception till November 14, 2017. Detailed research results are available in our publications, listed in the publications section of this report.

36 MATERIALS SCIENCE↗
DOE OSTI2025

PCMS: Parallel Coupler For Multimodel Simulations

This paper presents the Parallel Coupler for Multimodel Simulations (PCMS), a new GPU accelerated generalized coupling framework for coupling simulation codes on leadership class supercomputers. PCMS includes distributed control and field mapping methods for up to five dimensions. For field mapping PCMS can utilize discretization and field information to accommodate physics constraints. PCMS is demonstrated with a coupling of the gyrokinetic microturbulence code XGC with a Monte Carlo neutral transport code DEGAS2 and with a 5D distribution function coupling of an energetic particle transport code (GNET) to a gyrokinetic microturbulence code (GTC). Weak scaling is also demonstrated on up to 2,080 GPUs of Frontier with a weak scaling efficiency of 85%.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗