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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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At least 289 records · Page 16

Data-driven prediction of scaling and ignition of inertial confinement fusion experiments

Recent advances in inertial confinement fusion (ICF) at the National Ignition Facility (NIF), including ignition and energy gain, are enabled by a close coupling between experiments and high-fidelity simulations. Neither simulations nor experiments can fully constrain the behavior of ICF implosions on their own, meaning pre- and postshot simulation studies must incorporate experimental data to be reliable. Linking past data with simulations to make predictions for upcoming designs and quantifying the uncertainty in those predictions has been an ongoing challenge in ICF research. We have developed a data-driven approach to prediction and uncertainty quantification that combines large ensembles of simulations with Bayesian inference and deep learning. The approach builds a predictive model for the statistical distribution of key performance parameters, which is jointly informed by past experiments and physics simulations. The prediction distribution captures the impact of experimental uncertainty, expert priors, design changes, and shot-to-shot variations. We have used this new capability to predict a 10× increase in ignition probability between Hybrid-E shots driven with 2.05 MJ compared to 1.9 MJ, and validated our predictions against subsequent experiments. We describe our new Bayesian postshot and prediction capabilities, discuss their application to NIF ignition and validate the results, and finally investigate the impact of data sparsity on our prediction results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Toward Transparent Data Management in Multi-layer Storage Hierarchy for HPC Systems

Upcoming exascale high performance computing (HPC) systems are expected to comprise multi-tier storage hierarchy, and thus will necessitate innovative storage and I/O mechanisms. Traditional disk and block-based interfaces and file systems face severe challenges in utilizing capabilities of storage hierarchies due to the lack of hierarchy support and semantic interfaces. Object-based and semantically-rich data abstractions for scientific data management on large scale systems offer a sustainable solution to these challenges. Such data abstractions can also simplify users involvement in data movement. Here, we take the first steps of realizing such an object abstraction and explore storage mechanisms for these objects to enhance I/O performance, especially for scientific applications. We explore how an object-based interface can facilitate next generation scalable computing systems by presenting the mapping of data I/O from two real world HPC scientific use cases: a plasma physics simulation code (VPIC) and a cosmology simulation code (HACC). Our storage model stores data objects in different physical organizations to support data movement across layers of memory/storage hierarchy. Our implementation sclaes well to 16K parallel processes, and compared to the state of the art, such as MPI-IO and HDF5, our object-based data abstractions and data placement strategy in multi-level storage hierarchy achieves up to 7 X I/O performance improvement for scientific data.

97 MATHEMATICS AND COMPUTING↗

Yield Estimation of the August 2020 Beirut Explosion by Using Physics‐Based Propagation Simulations of Regional Infrasound

Abstract The August 2020 Beirut explosion is the largest single‐fired ammonium nitrate explosion documented in history. The massive explosion excited loud infrasound in the atmosphere, and clear waveforms were recorded by a regional infrasound array at an epicentral distance of 100 km, allowing for accurate measurements of explosion energy. We estimate the explosion size based on the infrasound waveform inversion. Unlike conventional inversions using empirical models, we perform full 3‐D finite‐difference simulations to obtain a physics‐based propagation model for the inversion. Accurate numerical modeling of infrasound is challenging as the propagation is substantially affected by the turbulent atmosphere. Instead of a single deterministic prediction, we provide a range of waveform predictions by running multiple simulations with stochastic weather forecast models, which allows for comprehensive uncertainty analysis of numerical modeling and estimated yields. Finally, we expand the yield estimation technique for seismoacoustic analysis and demonstrate the substantial advantage of the joint approach.

58 GEOSCIENCES↗

Hydrocarbon Cold-Flow Simulation of LOX/LH2 Rocket Aerodynamics

In FY19, this project developed a test method which employed heated ethane in the physical simulation of rocket plume aerodynamics. Based on this work, EUS partnered with significant leveraged funding. A portable, self-contained test bed was also fabricated to support validation of the new method. In FY20, this project focused on the formal validation of ethane’s performance as an aerodynamic simulant as well as the development of the analytical and hardware infrastructure required to carry out that task. The test bed was activated, a series of heated-ethane tests on one or more rocket/diffuser configurations were conducted, and characterizations of the performance of the ethane simulation compared to hot-fire were performed. A series of 127 tests were conducted on 13 aerodynamic configurations to evaluate ethane’s performance as a simulant. It was found that the new methodology can reproduce rocket plume flow fields with +/- 0.5% pressure error at ~3% physical scale. The result is a cost-per-test reduction of ~99% compared to the hot-fire subscale testing typically used to obtain equivalent data. Some initial efforts have taken place, and future efforts are being planned with LaRC supersonic retro propulsion and MSFC SLS aerodynamics teams, which are interested in using the ethane system to wind-tunnel test human-rated Mars lander retrorockets and SLS Booster. Details of the prototypical experiments were published as NASA TM 2020-5009122,and have been presented in JANNAF Virtual Conference paper, "New Developments in Retro propulsion Testing for Mars Entry, Descent and Landing".

Daniel Jones↗

Uncertainties propagation in the framework of a Rod Ejection Accident modeling based on a multi-physics approach

The control of uncertainties in the field of reactor physics and their propagation in best-estimate modeling are a major issue in safety analysis. In this framework, the CEA develops a methodology to perform multi-physics simulations including uncertainties analysis. The present paper aims to present and apply this methodology for the analysis of an accidental situation such as REA (Rod Ejection Accident). This accident is characterized by a strong interaction between the different areas of the reactor physics (neutronic, fuel thermal and thermal hydraulic). The modeling is performed with CRONOS2 code. The uncertainties analysis has been conducted with the URANIE platform developed by the CEA: For each identified response from the modeling (output) and considering a set of key parameters with their uncertainties (input), a surrogate model in the form of a neural network has been produced. The set of neural networks is then used to carry out a sensitivity analysis which consists on a global variance analysis with the determination of the Sobol indices for all responses. The sensitivity indices are obtained for the input parameters by an approach based on the use of polynomial chaos. The present exercise helped to develop a methodological flow scheme, to consolidate the use of URANIE tool in the framework of parallel calculations. Finally, the use of polynomial chaos allowed computing high order sensitivity indices and thus highlighting and classifying the influence of identified uncertainties on each response of the analysis (single and interaction effects). (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Performance Assessment of a Generic Nuclear Waste Repository in Shale - 18392

A performance assessment (PA) is an important component of a comprehensive safety analysis for a nuclear waste repository. In a PA, probabilistic simulations of the total repository system are performed, and results are evaluated against performance metrics. Uncertainty and sensitivity analyses help prioritize additional research and model development. The United States Department of Energy (DOE) has been developing a state of the art PA simulation software tool-kit, Geologic Disposal Safety Assessment (GDSA) Framework, that couples increasingly higher fidelity models of subsystem processes into total system PA simulations. Over the past several years, PAs of generic repositories in three geologic media (salt, shale, and crystalline rock) have demonstrated ongoing developments in capability. The current PA of a nuclear waste repository in a generic shale formation showcases GDSA Framework, including capabilities in domain discretization (Cubit), multi-physics simulations (PFLOTRAN), uncertainty and sensitivity analysis (Dakota), and visualization (Paraview). The generic shale reference case considers the disposal of 22,000 metric tons heavy metal of commercial spent nuclear fuel (SNF) in a generic shale formation. PA simulations account for the thermal load and radionuclide inventory of the waste form, components of the engineered barrier system including waste package and buffer, and components of the natural barrier system including the host rock shale and underlying and overlying stratigraphic units. Two repository layouts are considered, one for emplacement of waste packages containing 12 pressurized water reactor (PWR) assemblies, and one for 4-PWR waste package emplacement. Model domains are half-symmetry and contain between 7 and 22 million grid cells. Grid refinement captures the detail of individual waste packages, emplacement drifts, access drifts, and shafts. Simulations are run in a high-performance computing (HPC) environment on 512 or 2048 processes. The governing equations describing coupled heat and fluid flow and reactive transport are solved with PFLOTRAN, an open-source, massively parallel multiphase flow and reactive transport code. Additional simulated processes include waste package degradation; waste form dissolution; radioactive decay and ingrowth in aqueous, solid, and adsorbed phases; and a simple biosphere based on a pumping well. Simulations are run to 106 y; dose and radionuclide concentrations are observed within aquifers at a point approximately 5 km downgradient of the repository. Dakota is used to sample likely ranges of input parameters including waste form and waste package degradation rates and properties of engineered and natural materials to quantify uncertainty in predicted concentrations and sensitivity to input parameters. Given the assumptions of the reference case, results of 12-PWR and 4-PWR simulations are very similar. Dose at the pumping well 5-km downgradient of the repository does not exceed 10-9 Sv/y. I-129 is the largest contributor to dose. The dose due to Cl-36, the next largest contributor, is orders of magnitude smaller. At the pumping well, the concentration of I-129 5-km downgradient does not exceed 10-14 mol/L. Rank correlation coefficients indicate that the maximum concentration of I-129 within the aquifer is sensitive to shale (repository host rock) porosity and aquifer permeability. These results affirm that HPC-capable codes can be used to simulate important multi-physics couplings directly in a total system performance assessment of a geologic repository, and can be used in prioritization of future research and model development. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

On Using Linux Kernel Huge Pages with FLASH, an Astrophysical Simulation Code

We present efforts at improving the performance of FLASH, a multi-scale, multi-physics simulation code principally for astrophysical applications, by using huge pages on Ookami, an HPE Apollo 80 A64FX platform. FLASH is written principally in modern Fortran and makes use of the PARAMESH library to manage a block-structured adaptive mesh. We explored options for enabling the use of huge pages with several compilers, but we were only able to successfully use huge pages when compiling with the Fujitsu compiler. As a result, the use of huge pages substantially reduced the number of translation lookaside buffer misses, but overall performance gains were marginal.

79 ASTRONOMY AND ASTROPHYSICS↗

Security Analysis of Smart Grid Cyber Physical Infrastructures Using Modeling and Game Theoretic Simulation

Cyber physical computing infrastructures typically consist of a number of sites are interconnected. Its operation critically depends both on cyber components and physical components. Both types of components are subject to attacks of different kinds and frequencies, which must be accounted for the initial provisioning and subsequent operation of the infrastructure via information security analysis. Information security analysis can be performed using game theory implemented in dynamic Agent Based Game Theoretic (ABGT) simulations. Such simulations can be verified with the results from game theory analysis and further used to explore larger scale, real world scenarios involving multiple attackers, defenders, and information assets. We concentrated our analysis on the electric sector failure scenarios and impact analyses by the NESCOR Working Group Study, From the Section 5 electric sector representative failure scenarios; we extracted the four generic failure scenarios and grouped them into three specific threat categories (confidentiality, integrity, and availability) to the system. These specific failure scenarios serve as a demonstration of our simulation. The analysis using our ABGT simulation demonstrates how to model the electric sector functional domain using a set of rationalized game theoretic rules decomposed from the failure scenarios in terms of how those scenarios might impact the cyber physical infrastructure network with respect to CIA.

Availability↗

Calomplification — the power of generative calorimeter models

Motivated by the high computational costs of classical simulations, machine-learned generative models can be extremely useful in particle physics and elsewhere. They become especially attractive when surrogate models can efficiently learn the underlying distribution, such that a generated sample outperforms a training sample of limited size. This kind of GANplification has been observed for simple Gaussian models. We show the same effect for a physics simulation, specifically photon showers in an electromagnetic calorimeter.

47 OTHER INSTRUMENTATION↗

Beam Stability Overview [Slides]

Radiographic spot size is affected by many factors, including beam motion due to instabilities. Instabilities and effects that can influence the radiation-source spot size are being evaluated for the Scorpius flash-radiography accelerator. The Scorpius LIA design has a direct influence on beam stability. Many features of the design were specifically incorporated to mitigate instability. The major beam dynamics concerns for high-current LIAs are being evaluated for the long, 102-cell Scorpius design. For these results, all tools available were used including experimental data, analytic theory, and physics simulation codes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Self-consistent Quantum Iteratively Sparsified Hamiltonian Algorithm (SQuISH)

Due to coherence time limitations, reducing the resources required to run quantum algorithms and simulate physical systems on a quantum computer is crucial. With regards to Hamiltonian simulation, a significant effort has focused on building efficient algorithms using various factorizations and truncations, typically derived from the Hamiltonian alone. We introduce a new paradigm for improving Hamiltonian simulation and reducing the cost of ground state problems based on ideas recently developed for classical chemistry simulations. The key idea is that one can find efficient ways to reduce resources needed by quantum algorithms by making use of two key pieces of information: the Hamiltonian operator and an approximate ground state wavefunction. We refer to our algorithm as the self-consistent quantum iteratively sparsified Hamiltonian (SQuISH). By performing our scheme iteratively, one can drive SQuISH to create an accurate wavefunction using a truncated, resource-efficient Hamiltonian. By utilizing this more compact Hamiltonian, our algorithm provides an approach to reduce the gate complexity of ground state calculations on quantum hardware. As proof of principle, we implement SQuISH using configuration interaction for small molecules and coupled cluster for larger systems. Through our combination of approaches, we demonstrate how it performs on a range of systems, the largest of which would require more than 200 qubits to run on quantum hardware.

Diana Chamaki↗

SciDAC - Center for Simulation of Wave Interactions with MHD -- General Atomics Support of ORNL Collaboration

The Center for Simulation of Wave Interactions with Magnetohydrodynamics (SWIM) project is dedicated to conduct research on integrated multi-physics simulations. The Integrated Plasma Simulator (IPS) is a framework that was created by the SWIM team. It provides an integration infrastructure for loosely coupled component-based simulations by facilitating services for code execution coordination, computational resource management, data management, and inter-component communication. The IPS framework features improving resource utilization, implementing application-level fault tolerance, and support of the concurrent multi-tasking execution model. The General Atomics (GA) team worked closely with other team members on this contract, and conducted research in the areas of computational code monitoring, meta-data management, interactive visualization, and user interfaces. The original website to monitor SWIM activity was developed in the beginning of the project. Due to the amended requirements, the software was redesigned and a revision of the website was deployed into production in April of 2010. Throughout the duration of this project, the SWIM Monitoring Portal (http://swim.gat.com:8080/) has been a critical production tool for supporting the project's physics goals.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

CaloScore v2: single-shot calorimeter shower simulation with diffusion models

Diffusion generative models are promising alternatives for fast surrogate models, producing high-fidelity physics simulations. However, the generation time often requires an expensive denoising process with hundreds of function evaluations, restricting the current applicability of these models in a realistic setting. In this work, we report updates on the CaloScorearchitecture, detailing the changes in the diffusion process, which produces higher quality samples, and the use of progressive distillation, resulting in a diffusion model capable of generating new samples with a single function evaluation. Here we demonstrate these improvements using the Calorimeter Simulation Challenge 2022 dataset.

47 OTHER INSTRUMENTATION↗

Developing a Comprehensive Software Suite for Advanced Reactor Performance and Safety Analysis

This paper provides an introduction to the reactor analysis capabilities of the nuclear power reactor simulation tools that are being developed as part of the U.S. Department of Energy s Nuclear Energy Advanced Modeling and Simulation (NEAMS) Toolkit. The NEAMS Toolkit is an integrated suite of multi-physics simulation tools that leverage high-performance computing to reduce uncertainty in the prediction of performance and safety of advanced reactor and fuel designs. The Toolkit effort is comprised of two major components, the Fuels Product Line (FPL), which provides tools for fuel performance analysis, and the Reactor Product Line (RPL), which provides tools for reactor performance and safety analysis. This paper provides an overview of the NEAMS RPL development effort.

Multi-physics↗

Understanding Differences in California Climate Projections Produced by Dynamical and Statistical Downscaling

Abstract We compare historical and end‐of‐century temperature and precipitation patterns over California from one dynamically downscaled simulation using the Weather Research and Forecast (WRF) model and two simulations statistically downscaled using Localized Constructed Analogs (LOCA). We uniquely separate causes of differences between dynamically and statistically based future climate projections into differences in historical climate (gridded observations versus regional climate model output) and differences in how these downscaling techniques explicitly handle future climate changes (numerical modeling versus analogs). In these methods, solutions between different downscaling techniques differ more in the future compared to the historical period. Changes projected by LOCA are insensitive to the choice of driving data. Only through dynamical downscaling can we simulate physically consistent regional springtime warming patterns across the Sierra Nevada, while the statistical simulations inherit an unphysical signal from their parent Global Climate Model (GCM) or gridded data. The results of our study clarify why these different techniques produce different outcomes and may also provide guidance on which downscaled products to use for certain impact analyses in California and perhaps other Mediterranean regimes.

54 ENVIRONMENTAL SCIENCES↗

Towards Multifluid Multiphysics Continuum Plasma Simulation for Modeling Magnetically-driven Experiments on Z

Magnetically driven experiments supporting pulsed-power utilize a wide range of configurations, including wire-arrays, gas-puffs, flyer plates, and cylindrical liners. This experimental flexibility is critical to supporting radiation effects, dynamic materials, magneto-inertial-fusion (MIF), and basic high energy density laboratory physics (HEDP) efforts. Ultimately, the rate at which these efforts progress is limited by our understanding of the complex plasma physics of these systems. Our effort has been to begin to develop an advanced algorithmic structure and a R&D code implementation for a plasma physics simulation capability based on the five-moment multi-fluid / full-Maxwell plasma model. This model can be used for inclusion of multiple fluid species (e.g., electrons, multiple charge state ions, and neutrals) and allows for generalized collisional interactions between species, models for ionization/recombination, magnetized Braginskii collisional transport, dissipative effects, and can be readily extended to incorporate radiation transport physics. In the context of pulsed-power simulations this advanced model will help to allow SNL to computationally simulate the dense continuum regions of the physical load (e.g. liner implosions, flyer plates) as well as partial power-flow losses in the final gap region of the inner MITL. In this report we briefly summarize results of applying a preliminary version of this model in the context of verification type problems, and some initial magnetic implosion relevant prototype problems. The MIF relevant prototype problems include results from fully-implicit / implicit-explicit (IMEX) resistive MHD as well as full multifluid EM plasma formulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

COSMIC DAWN: Distributed Analysis of Wireless at Nextscale

Distributed Analysis of Wireless at Nextscale (DAWN) is a novel simulation framework for large-scale design-space exploration (DSE) of unmodified software-defined radio (SDR) applications interacting in a scalable, high-fidelity, virtual physics environment. The software-defined nature of the coupled software-physics simulation leverages hardware emulation to permit in-depth examination and modification of not only the electromagnetic environment, including each signal in flight, but also the precise state of system software and components. DAWN supports modular, customizable physics environments allowing realistic propagation effects so that computationally efficient empirical models, reduced order/surrogate models, or large-scale, high-fidelity, site-specific simulations can be used as a propagation medium based on scenario requirements. This paper introduces DAWN’s design and initial implementation, detailing key architectural components, including the Physics Realization Engine (PhyRE), Runtime Infrastructure for Simulation Environments (RISE), and the design space exploration (DSE) suite. It concludes with demonstrations using unmodified 4G/LTE software available from srsRAN on computing resources ranging from a small cluster to ORNL’s Frontier Exascale system.

Wise, Mike [ORNL] (ORCID:0000000266120641)↗