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NASA NTRS2014

Object-Oriented/Data-Oriented Design of a Direct Simulation Monte Carlo Algorithm

Over the past decade, there has been much progress towards improved phenomenological modeling and algorithmic updates for the direct simulation Monte Carlo (DSMC) method, which provides a probabilistic physical simulation of gas Rows. These improvements have largely been based on the work of the originator of the DSMC method, Graeme Bird. Of primary importance are improved chemistry, internal energy, and physics modeling and a reduction in time to solution. These allow for an expanded range of possible solutions In altitude and velocity space. NASA's current production code, the DSMC Analysis Code (DAC), is well-established and based on Bird's 1994 algorithms written in Fortran 77 and has proven difficult to upgrade. A new DSMC code is being developed in the C++ programming language using object-oriented and data-oriented design paradigms to facilitate the inclusion of the recent improvements and future development activities. The development efforts on the new code, the Multiphysics Algorithm with Particles (MAP), are described, and performance comparisons are made with DAC.

Liechty, Derek S.↗

DOE OSTI2018

Multiphysics Simulation of DPC Criticality: Scoping Calculations and Coupling Strategy.

Objectives for Multi-Physics Simulations include: Provide a systematic framework for multi-process modeling — Conduct parallel model development efforts that cover the technical areas needed to support criticality consequence screening in performance assessment (PA) and that will be more closely integrated as development proceeds; Investigate separate effects — Allow partitioning of the overall waste package (WP) internal criticality multi-physics modeling effort during development activities, for study of specific processes that can later be coupled if warranted from interpretation of results; Study scaling and bounding approaches — Where possible, represent criticality consequences in PA using simplification of uncertain criticality event frequency and magnitude, bounding of consequences for screening purposes, and scaling of consequences to multiple WPs; and, Integration among participants — Multiple modeling teams (mainly SNL and ORNL, and their collaborators) will work on different parts of the in-package criticality phenomenology. Insights generated this way will be combined for more realistic coupled modeling, and for validation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2017

Simulating the SuperCDMS Dark Matter Detector Response and Readout

Dark matter is one of the remaining great mysteries of modern physics. Cosmological and astrophysical evidence hints strongly at a new particle, or set of particles, unknown to the Standard Model, comprising some 80% of all of the matter in the universe. SuperCDMS is one of the world-leading direct-detection experiments attempting to directly measure interactions between dark and regular matter. SuperCDMS uses solid state crystalline detectors in a nearly-zero background environment to attempt to measure the particle properties of dark matter. The detectors themselves, however, are quite complex; and a very detailed understanding of the microscopic physics is helpful in analyzing the very rare events that occur within them. Furthermore, better understanding and modeling of the detectors can aid in the design and optimization of future iterations of the experiment. The SuperCDMS detectors are well-understood in ideal cases. However, an accurate understanding of the detector response to outlier events or under non-ideal conditions is important for a low-statistics experiment. This work describes the design and implementation of a low temperature condensed matter physics simulation library built on top of the popular Geant4 particle tracking framework. The library, named \Geant4 Condensed Matter Physics" or G4CMP, introduces several solid state concepts to the Geant4 framework such as crystal lattices, phonon quasiparticles, non-scalar elective masses, and implements several physics processes relevant to cryogenic temperature crystals. In addition to the physics library, which is intended for general use, this work also describes a full Monte Carlo simulation package for the SuperCDMS iZIP detectors which utilizes G4CMP at its core and also fully simulates the detector readout sensors. The document will begin with the canonical motivations for the cold dark matter hypothesis, followed by a description of the SuperCDMS experiment. It will then describe the microscopic physics inside of the SuperCDMS detectors, as well as details on their implementation in G4CMP. The full detector simulation with corresponding sensor readout will follow, along with plans for future work; including both scientific studies and improvements, as well as computational improvements and added efficiencies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2014

Scalable Nonlinear Solvers for Fully Implicit Coupled Nuclear Fuel Modeling. Final Report

The focus of the project is on the development and customization of some highly scalable domain decomposition based preconditioning techniques for the numerical solution of nonlinear, coupled systems of partial differential equations (PDEs) arising from nuclear fuel simulations. These high-order PDEs represent multiple interacting physical fields (for example, heat conduction, oxygen transport, solid deformation), each is modeled by a certain type of Cahn-Hilliard and/or Allen-Cahn equations. Most existing approaches involve a careful splitting of the fields and the use of field-by-field iterations to obtain a solution of the coupled problem. Such approaches have many advantages such as ease of implementation since only single field solvers are needed, but also exhibit disadvantages. For example, certain nonlinear interactions between the fields may not be fully captured, and for unsteady problems, stable time integration schemes are difficult to design. In addition, when implemented on large scale parallel computers, the sequential nature of the field-by-field iterations substantially reduces the parallel efficiency. To overcome the disadvantages, fully coupled approaches have been investigated in order to obtain full physics simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2018

Coupled Calculations of the NuScale FIV Tests – Pre-test Simulations and Sensitivity Analysis

The NEAMS program aims to develop an integrated multi-physics simulation capability “pellet-to-plant” for the design and analysis of future generations of nuclear power plants. In particular, the Reactor Product Line code suite's multi-resolution hierarchy is being designed to ultimately span the full range of length and time scales present in relevant reactor design and safety analyses, as well as scale from desktop to petaflop computing platforms. Flow-induced vibration (FIV) is widespread problem in energy systems because they rely on fluid movement for energy conversion. Vibrating structures may be damaged as fatigue or wear occurs. Given the importance of reliable components in the nuclear industry, flow-induced vibration has long been a major concern in safety and operation of nuclear reactors. In particular, nuclear fuel rods and steam generators have been known to suffer from flow-induced vibration and related failures. Advanced reactors, such as integral Pressurized Water Reactors (PWRs) considered for Small Modular Reactors (SMR), often rely on innovative component designs to meet cost and safety targets. One component that is the subject of advanced designs is the steam generator, some designs of which forego the usual shell-and-tube architecture in order to fit within the primary vessel. A significant amount of data exists on flow-induced vibration in shell-and-tube heat exchangers, and heuristic methods are available to predict FIV based on a set of given assumptions. In contrast, advanced designs have far less data available. Advanced modeling and simulation based on coupled structural and fluid simulations have the potential to predict flow-induced vibration in a variety of designs, reducing the need for expensive experimental programs, especially at the conceptual design stage. Over the past several years, the Reactor Product Line has developed a FIV capability in SHARP. SHARP contains high-fidelity single-physics codes Diablo for structural mechanics and Nek5000 for fluid mechanics calculations. Both codes are state-of-the-art, highly scalable tools that have been extensively validated. In previous reports we have discussed the implementation and validation of an FIV capability for helical steam generators and fuel assemblies. In this report we discuss one-way coupled calculations performed with Nek5000 and Diablo for the NuScale FIV tests. In the turbulent fretting regime one-way coupling is judged to be sufficient because the pressure loads do not cause substantial displacements. It is also the most common source of vibration in helical steam generators per the low flows expected in integral PWRs. The simulations precede the tests, as experimental data was not available at the delivery of this report. Several assumptions had to be made on the support-tube interaction and multiple tests and sensitivity analysis have been performed. Additional work remains to be done and it is discussed in the future work section.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

Impact of detector simulation in particle physics collider experiments

Through the last three decades, precise simulation of the interactions of particles with matter and modeling of detector geometries has proven to be of critical importance to the success of the international high-energy physics experimental programs. For example, the detailed detector modeling and accurate physics of the Geant4-based simulation software of the CMS and ATLAS particle physics experiments at the European Center of Nuclear Research (CERN) Large Hadron Collider (LHC) was a determinant factor for these collaborations to deliver physics results of outstanding quality faster than any hadron collider experiment ever before. This review article highlights the impact of detector simulation on particle physics collider experiments. It presents numerous examples of the use of simulation, from detector design and optimization, through software and computing development and testing, to cases where the use of simulation samples made a difference in the accuracy of the physics results and publication turnaround, from data-taking to submission. It also presents the economic impact and cost of simulation in the CMS experiment. Future experiments will collect orders of magnitude more data, taxing heavily the performance of simulation and reconstruction software for increasingly complex detectors. Consequently, it becomes urgent to find solutions to speed up simulation software in order to cope with the increased demand in a time of flat budgets. The study ends with a short discussion on the potential solutions that are being explored, by leveraging core count growth in multicore machines, using new generation coprocessors, and re-engineering of HEP code for concurrency and parallel computing.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1995

Managing Complexity in Multidisciplinary Visualization

As high performance computing technology progresses, computational simulations are becoming more advanced in their capabilities. In the computational aerosciences domain, single discipline steady-state simulations computed on a single grid are far from the state-of-the-art. In their place are complex, time-dependent multidisciplinary simulations that attempt to model a given geometry more realistically. The product of these multidisciplinary simulations is a massive amount of data stored in different formats, grid topologies, units of measure, etc., as a result of the differences in the simulated physical domains. In addition to the challenges posed by setting up and performing the simulation, additional challenges exist in analyzing computational results. Visualization plays an important role in the advancement of multidisciplinary simulations. To date, visualization has been used to aid in the interpretation of large amounts of simulation data. Because the human visual system is effective in digesting a large amount of information presented graphically, visualization has helped simulation scientists to understand complex simulation results. As these simulations become even more complex, integrating several different physical domains, visualization will be critical to digest the massive amount of information. Another important role for visualization is to provide a common communication medium from which the domain scientists can use to develop, debug, and analyze their work. Multidisciplinary analyses are the next step in simulation technology, not only in computational aerosciences, but in many other areas such as global climate modeling. Visualization researchers must understand and work towards the challenges posed by multidisciplinary simulation scenarios. This paper addresses some of these challenges, describing technologies that must be investigated to create a useful visualization analysis tool for domain scientists.

Miceli, Kristina D.↗

DOE OSTI2022

LaSDI: Parametric Latent Space Dynamics Identification

Enabling fast and accurate physical simulations with data has become an important area of computational physics to aid in inverse problems, design-optimization, uncertainty quantification, and other various decision-making applications. This paper presents a data-driven framework for parametric latent space dynamics identification procedure that enables fast and accurate simulations. The parametric model is achieved by building a set of local latent space model and designing an interaction among them. An individual local latent space dynamics model achieves accurate solution in a trust region. By letting the set of trust region to cover the whole parameter space, our model shows an increase in accuracy with an increase in training data. Herein we introduce two different types of interaction mechanisms, i.e., point-wise and region-based approach. Both linear and nonlinear data compression techniques are used. We illustrate the framework of Latent Space Dynamics Identification (LaSDI) enable a fast and accurate solution process on various partial differential equations, i.e., Burgers’ equations, radial advection problem, and nonlinear heat conduction problem, achieving 0 (100)x speed-up and 0 (1)% relative error with respect to the corresponding full order models.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Study of the shape of an optical window in a super-resolution state by electromagnetic-thermal coupled simulation: Effects of melting of an active layer in an optical disc

We performed a multi-physics simulation for the propagation of electromagnetic waves and heat conduction in a super-resolution optical disc that includes an active layer of InSb. Because the change in the optical constant of InSb due to the phase transition is taken into account, the melting of the active layer can be realistically simulated in our calculation. It was found that in the case of an incident light power (P) of 2 mW, a profile of the electric field intensity transmitted through the InSb layer has an asymmetric shape with a narrow peak. This beam-narrowing was suggested to be an essential mechanism of the super-resolution, because a narrower light beam allows the detection of a smaller pit structure than the optical diffraction limit. This beam-narrowing was found to be originating from a small molten region produced in the InSb layer, which works as a mask for light exposure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2018

Coupled Calculations of the Nuscale FIV Tests: Pre-test Simulations and Sensitivity Analysis

42 ENGINEERING↗

DOE OSTI2022

Stochastic simulation of occupant-driven energy use in a bottom-up residential building stock model

The residential buildings sector is one of the largest electricity consumers worldwide and contributes disproportionally to peak electricity demand in many regions. Strongly driven by occupant activities, household energy consumption is stochastic and heterogeneous in nature. However, most residential energy models applied by industry use homogeneous, deterministic activity schedules, which work well for predictions of annual energy consumption, but can result in unrealistic hourly or sub-hourly electric load profiles, with exaggerated or muted peaks. The increasing proportion of variable renewable energy generators means that representing the heterogeneity and stochasticity of occupant behavior is now crucial for reliable planning at both bulk-power and distribution-system scales. This work presents a novel and open-source occupancy simulation approach that can simulate a diverse set of individual occupant and household event schedules for all major electricity, fuel, and hot water end uses. To accomplish this, we evaluated three alternative occupant activity simulation approaches before selecting a hybrid combining time-inhomogeneous Markov chains and probability-sampling of event durations and magnitudes. Further, we integrated the stochastic occupancy simulation with an open-source bottom-up physics-simulation building stock model and published a set of 550,000 diverse household end-use activity schedules representing a national housing stock. The simulator was verified against time-use survey data, and simulation results were validated against measured end-use electricity data for accuracy and reliability. While we use data for the United States, our application demonstrates how similar approaches could be applied using the time-use survey data collected in many countries around the world.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Analysis of superfast encoding performance for electronic structure simulations

In our recent work, we examined various fermion-to-qubit mappings in the context of quantum simulation including the original Bravyi-Kitaev superfast encoding (OSE) as well as a generalized version (GSE). We return to OSE and compare it against the Jordan-Wigner (JW) transform for quantum chemistry considering the number of qubits required, the Pauli weight of terms in the transformed Hamiltonians, and the L 1 norm of the Hamiltonian. We considered a test set of molecular systems known as the Atomization Energy 6 (AE6) as well as hydrogen lattices. Our results showed that the resource efficiency of OSE is strongly affected by the spatial locality of the underlying single-particle basis. We find that OSE is outperformed by JW when the orbitals in the underlying single-particle basis are highly overlapping, which limits its applicability to near-term quantum chemistry simulations utilizing standard basis sets. In contrast, when orbitals are overlapping with only few others, as is the case of hydrogen lattices with very tight orbitals, OSE fares comparatively better. Furthermore, our results illustrate the importance of choosing the right combination of basis sets and fermion-to-qubit mapping to get the most out of a quantum device when simulating physical systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

RIKEN/RBRC Scientific Review Committee Meeting April 5-8, 2016. Proceedings of RIKEN BNL Research Center, Volume 126

Considerable progress in lattice gauge computing has been made by the RBRC Computing Group over the last 5 years. The lattice gauge community has recognized some of this work by awarding two Wilson prizes, in 2012 and in 2015. The Computing Group, in collaboration with RIKEN, BNL and the UKQCD collaboration, has focused on both physics simulations and technical developments, in both software and hardware. The physics output has been primarily in the area of fundamental physical quantities, e.g., in K and B mesons, nucleon form factors, g-2 of the muon, electric dipole moments and physics beyond the Standard Model. The software effort has produced new and/or more efficient algorithms, such as the all-mode averaging (AMA), and ensemble generation techniques. This proceedings records the 14th scientific evaluation of the RIKEN BNL Research Center (RBRC). In order to illustrate the breadth and scope of the RBRC program, each member of the Center made a presentation on his/her research efforts. This encompassed three major areas of investigation: theoretical, experimental and computational physics. In addition, the committee met privately with the fellows and postdocs to ascertain their opinions and concerns. Although the main purpose of this review is a report to RIKEN management on the health, scientific value, management and future prospects of the Center, the RBRC management felt that a compendium of the scientific presentations are of sufficient quality and interest that they warrant a wider distribution. Therefore we have made this compilation and present it to the community for its information and enlightenment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2019

Supporting Simulation Families in Nuclear Reactor Workflows SBIR Phase I. Final Scientific/Technical Report

The US Department of Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) Toolkit has accelerated both the solutions to existing problems and deployment of new designs for current and advanced reactors. Within the toolkit, there exist various families of simulation tools that target specific aspects of a multi-physics simulation for a nuclear reactor. Tools within a specific family vary in both complexity and fidelity as well as the types of resources they require. To complement the NEAMS effort, the Computational Model Builder (CMB) has been designed to provide a graphical user interface to design and execute nuclear reactor workflows. Previously, we had designed a workflow in CMB to design and prepare for execution a neutronics simulation using DIF3D, a diffusion and transport solver developed at Argonne National Laboratory. For this Phase I effort, we extended CMB’s reactor modeling tools to design and execute a workflow using Proteus-SN, a higher-fidelity transport solver developed at Argonne with more preparatory requirements from the workflow. Furthermore, this workflow was designed to maximize the common features of the two workflows, describing the analogous tasks between the workflows as belonging to a “simulation family”. This perspective facilitates the abstraction of the neutronics simulations to a single bifurcated workflow, allowing the engineer to design a reactor and then choose the appropriate simulation according to his or her needs for fidelity and computational cost.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

Refining fast calorimeter simulations with a Schrödinger Bridge

Machine learning-based simulations, especially calorimeter simulations, are promising tools for approximating the precision of classical high energy physics simulations with a fraction of the generation time. Nearly all methods proposed so far learn neural networks that map a random variable with a known probability density, like a Gaussian, to realistic-looking events. In many cases, physics events are not close to Gaussian and so these neural networks have to learn a highly complex function. We study an alternative approach: Schrödinger bridge Quality Improvement via Refinement of Existing Lightweight Simulations (SQuIRELS). SQuIRELS leverages the power of diffusion-based neural networks and Schrödinger bridges to map between samples where the probability density is not known explicitly. We apply SQuIRELS to the task of refining a classical fast simulation to approximate a full classical simulation. On simulated calorimeter events, we find that SQuIRELS is able to reproduce highly non-trivial features of the full simulation with a fraction of the generation time.

Calorimeter methods↗

DOE OSTI2012

Adding a MOAB Geometry Interface to SHARP Structural Mechanics

The authors briefly summarize the development of, and test experience with, an initial data interface between the structural mechanics code Diablo and the SHARP reactor simulation system data hub MOAB. That interface has been exercised both to write MOAB databases from Diablo, and then also to use such a database to read in part of a simulation definition for a subsequent Diablo execution. All enhancements are integrated into the central Diablo source repository. The SHARP software system for advanced simulation of nuclear reactors and power plant systems is sponsored by DOE's Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. SHARP has been architected as a federation of single-physics simulation tools to permit flexibility in programming languages and leveraging of past and on-going investments. Solution of multi-physics problems will be coordinated by, and data passed through, a central 'hub'. SHARP's hub implementation is utilizing MOAB: a Mesh-Oriented datABase. This same data hub approach is also intended to enable multi-resolution simulations, e.g, lower-dimension plant-scale simulations can be informed by high-fidelity 3D models of particular critical components.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2026

The high explosives & affected targets (HEAT) dataset

Artificial Intelligence (AI) surrogate models offer a computationally efficient alternative to full-physics simulations, yet no existing datasets are publicly available for training, testing, and validation of machine learning models of the dynamics of high-explosive driven shocks through multiple materials. Shock propagation through materials is a computationally challenging problem because simulations must include material-specific equations of state (EOS) along with descriptions of other physical processes such as plastic deformation, phase change, damage processes, fluid instabilities, and multi-material interactions. Shocks are typically initiated by high-velocity impacts or explosive loading. The latter case necessitates the addition of models of reactive materials to represent high-explosive (HE) detonation. Here, to address the lack of an expansive dataset for multi-material shock propagation in the AI/ML community, we present the High-Explosives and Affected Targets (HEAT) Dataset. HEAT is a physics-rich collection of two-dimensional, cylindrically symmetric, simulations generated using an Eulerian, multi-material, shock-propagation code developed at Los Alamos National Laboratory. The dataset includes two partitions: (1) the expanding shock-cylinder (CYL) simulations, Figs. 1, and (2) the Perturbed Layered Interface (PLI) simulations, Fig. 2. Entries in both partitions consist of time series of arrays of thermodynamic fields (pressure, density, and temperature), kinematic fields (position and velocity), and additional fields that depend on thermodynamic and/or kinematic fields (e.g., material stress). Materials in the CYL partition include solids (aluminium, copper, depleted uranium, stainless steel, tantalum, and a generic polymer), a liquid (water), gases (air, nitrogen), and a generic detonating material (high explosive, HE). The PLI partition spans a highly varying geometry but consists of fixed materials across entries: Copper, aluminium, stainless steel, generic polymer, and generic HE. HEAT captures critical phenomena such as momentum transfer, shock propagation, plastic deformation, and thermal effects, making HEAT a valuable benchmark for development of AI/ML emulation of multi-material shock propagation.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Multi-physics Object Oriented Simulation Environment (MOOSE)

This two-day workshop is a hands-on introduction to the Multi-Physics Object Oriented Simulation Environment (MOOSE). MOOSE is a simulation framework built from PETSc that enables efficient simulation of complex physical systems with minimal programming background. Attendees are encouraged to visit the MOOSE website at www.mooseframework.org and walk through the step by step process of installing the framework on their computer. Support through this process is provided through the MOOSE Google Group message board. The workshop itself will consist of interactive modules where instructors from the MOOSE development team will work with attendees to build a simple plasma model. Each module will build on previous modules to introduce fundamental MOOSE features that will combine to demonstrate simulation capabilities for low temperature plasma modeling. The intention is not to provide an exhaustive overview of simulation capabilities but to instead provide attendees with the necessary tools to build unique simulation capabilities for their specific research challenges. Users should attend the workshop with laptop computers with MOOSE installed to allow for interactive instruction. At the completion of the workshop attendees will be able to install and run MOOSE and associated applications as well as carry out plasma simulations studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗