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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 145 records · Page 8

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DOE OSTI2016

Flexible Computer Science Infrastructure (FleCSI)

FleCSI is a compile-time configurable framework designed to support multi-physics application development. As such, FleCSI attempts to provide a very general set of infrastructure design patterns that can be specialized and extended to suit the needs of a broad variety of solver and data requirements. Current support includes multi-dimensional mesh topology, mesh geometry, and mesh adjacency information, n-dimensional hashed-tree data structures, graph partitioning interfaces, and dependency closures. FleCSI also introduces a functional programming model with control, execution, and data abstractions that are consistent with both MPI and state-of-the-art task-based runtimes such as Legion and Charm++. The FleCSI abstraction layer provides the developer with insulation from the underlying runtime, while allowing support for multiple runtime systems, including conventional models like asynchronous MPI. The intent is to give developers a concrete set of user-friendly programming tools that can be used now, while allowing flexibility in choosing runtime implementations and optimizations that can be applied to architectures and runtimes that arise in the future. The control and execution models in FleCSI also provide formal nomenclature for describing poorly understood concepts like kernels and tasks.

Moss, Nicholas↗

DOE OSTI2016

Flexible Computer Science Infrastructure (FleCSI)

Bergen, Ben↗

DOE OSTI2012

Development of an Advanced Performance Assessment Modeling Capability for Geologic Disposal of Nuclear Waste: Methodology and Requirements

This report describes the planning and initial development of an advanced disposal system PA modeling capability to facilitate the science-based evaluation of disposal system performance for a range of fuel cycle alternatives in a variety of geologic media and generic disposal system concepts. The advanced modeling capability will provide a PA model framework that facilitates PA model development, execution, and evaluation within a formal PA methodology. The PA model framework will provide a formalized structure that enables (a) representation and implementation of a range of generic geologic disposal system options, (b) representation of subsystem processes and couplings at varying levels of complexity in an integrated disposal system model, (c) flexible, modular representation of multi-physics processes, including the use of legacy codes, (d) evaluation of system- and subsystem-level performance, (e) uncertainty and sensitivity analyses to isolate key subsystem processes and components, (f) data and configuration management functions, and (g) implementation in HPC environments.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2015

Stand-Alone Dynamic System Simulation of a Fissile Solution System

Dynamic system simulations (DSS) of fissile solution systems (FSS) have been performed at Los Alamos National Laboratory (LANL) for several years. DSS have been designed and executed using the DESIRE (Direct Executing Simulation in Real Time) system, a platform ideal for expert system modelers, as it allows for direct mathematical specification of a model, and facilities for performing experiments and analyses with the model. Models built in DESIRE have been compared to historical data from several historic aqueous homogeneous reactors (AHR) showing close agreement between experimental data and model estimates. Historical systems modeled include: SUPO (Super Power), an AHR that operated at Los Alamos National Laboratory from 1951 to 1974; SILENE, which was operated by CEA at Valduc, France until 2011; KEWB (Kinetics Experiment Water Boiler) A-2 and B-5 cores, operated by North American Atomics during the 1960’s and 1970’s. SUPO is considered a benchmark for steady-state operations, SILENE for pulse, and KEWB as confirmatory for both modes. However, there are some simulation tasks that are not well-suited to DESIRE model implementation. These tasks include engineering design and analysis and providing a hardware simulator backend. It has been determined that executable simulation models would better suit these purposes, hence a process for converting DESIRE simulation models to executable simulation models was designed and implemented, and several models have been converted. DESIRE simulation models are converted to C++ executable models by an automated process. The conversion process is quick, accurate and repeatable, giving confidence that converted models will perform as well as the original DESIRE models. Extensive testing on the SUPO and accelerator driven subcritical system models has shown that the executable models perform almost identically to the DESIRE models. All major trends and events are simulated with excellent agreement and the steady-state results typically agree within a small fraction of a percent (always better than 0.1% and generally better than 0.01% agreement).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

QCOR; A Language Extension Specification for the Heterogeneous Quantum-Classical Model of Computation

Quantum computing (QC) is an emerging computational paradigm that leverages the laws of quantum mechanics to perform elementary logic operations. Existing programming models for QC were designed with fault-tolerant hardware in mind, envisioning stand-alone applications. However, the susceptibility of near-term quantum computers to noise limits their stand-alone utility. To better leverage limited computational strengths of noisy quantum devices, hybrid algorithms have been suggested whereby quantum computers are used in tandem with their classical counterparts in a heterogeneous fashion. This modus operandi calls out for a programming model and a high-level programming language that natively and seamlessly supports heterogeneous quantum-classical hardware architectures in a single-source-code paradigm. Motivated by the lack of such a model, we introduce a language extension specification, called QCOR, which enables single-source quantum-classical programming. Programs written using the QCOR library–based language extensions can be compiled to produce functional hybrid binary executables. After defining QCOR’s programming model, memory model, and execution model, we discuss how QCOR enables variational, iterative, and feed-forward QC. Additionally, QCOR approaches quantum-classical computation in a hardware-agnostic heterogeneous fashion and strives to build on best practices of high-performance computing. The high level of abstraction in the language extension is intended to accelerate the adoption of QC by researchers familiar with classical high-performance computing.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Version of GCAM-USA used for National Climate Assessment 5, Chapter 5: GCAM-USA-v5.3-IM3-NCA5

Overview GCAM-USA-v5.3-IM3-NCA5 is developed using GCAM-USA-v5.3 as its core, with the impact of the thermodynamic global warming scenario "RCP8.5_hotter" on runoff, heating and cooling degree-hours, and agricultural yield and the SSP5 socioeconomic scenario. These scenarios were produced as part of the Integrated Multisector, Multiscale Modeling (IM3) project and used by National Climate Assessment 5. Detailed Information This software package includes the output dataset, which is located in "output/database_rcp85hotter_ssp5". For reproducibility, the model is setup and ready to run for the selected IM3 scenario "rcp85hotter_ssp5". To execute the model, double click "exe/run-gcam.bat".

Climate Change↗

DOE OSTI2020

An Enhanced Vertical Ground Heat Exchanger Model for Whole-Building Energy Simulation

This paper presents an enhanced vertical ground heat exchanger (GHE) model for whole-building energy simulation (WBES). WBES programs generally have computational constraints that affect the development and implementation of component simulation sub-models. WBES programs require models that execute quickly and efficiently due to how the programs are utilized by design engineers. WBES programs also require models to be formulated so their performance can be determined from boundary conditions set by upstream components and environmental conditions. The GHE model developed during this work utilizes an existing response factor model and extends its capabilities to accurately and robustly simulate at timesteps that are shorter than the GHE transit time. This was accomplished by developing a simplified dynamic borehole model and then exercising that model to generate exiting fluid temperature response factors. This approach blends numerical and analytical modeling methods. The existing response factor models are then extended to incorporate the exiting fluid temperature response factor to provide a better estimate of the GHE exiting fluid temperature at short simulation timesteps.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

A cross-platform execution engine for the quantum intermediate representation

Hybrid languages like the quantum intermediate representation (QIR) are essential for programming systems that mix quantum and conventional computing models, while execution of these programs is often deferred to a system-specific implementation. Here, we develop the QIR Execution Engine (QIR-EE) for parsing, interpreting, and executing QIR across multiple hardware platforms. QIR-EE uses LLVM to execute hybrid instructions specifying quantum programs and, by design, presents extension points that support customized runtime and hardware environments. We demonstrate an implementation that uses the XACC quantum hardware-accelerator library to dispatch prototypical quantum programs on different commercial quantum platforms and numerical simulators, and we validate execution of QIR-EE on IonQ, Quantinuum, and IBM hardware. Our results highlight the efficiency of hybrid executable architectures for handling mixed instructions, managing mixed data, and integrating with quantum computing frameworks to realize cross-platform execution.

LLVM↗

DOE OSTI2024

pnnl/emp-gnn

Efficient Graph Neural Network for Predicting Molecular Properties software can compare the prediction quality with ab initio DFT results reported by the high-performance state-of-theart NWChem quantum chemistry package [1] through Mean Absolute Error (MAE) obtained by the fitting between DFT and model predictions i.e, MPNN [2]. We also demonstrated the performance benefits by grouping large molecules by atom sizes, and executing GNN models on different types of resources. Since the training times depend on the number of atoms, we demonstrate the impact of distributing the workloads on two GPUs with varying capabilities (e.g., NVIDIA A100 vs. GeForce RTX 2080 Ti) to optimize the efficiency. We are at the precipice of broad adoption of GNNs for molecular property prediction tasks; hence, our work is timely by comparing model prediction against classical approaches with the intent of providing initial screening for specific classes of molecules.

Lee, Hyungro↗

DOE OSTI2016

Study on Modeling of Nuclear Fuel End Drop during a Hypothetical Accident

It is well known that shell elements have been used to model the cladding of single nuclear fuel pins. These have been used, for example, to analyze the response of a fuel assembly by assuming that all fuel pins in a fuel assembly deform in the same pattern. It is increasingly significant to model the entire fuel assembly in order to capture more realistically the behavior of each individual nuclear fuel during a hypothetical accident in a manner that can account for interactions among single pins. However, modeling each individual fuel pin in an entire fuel assembly using shell elements will result in models with large amount of elements and degrees of freedom that take correspondingly larger amount of computational times to execute. Therefore, modeling the nuclear fuel assembly with beam elements may become an option. This paper presents the results of a set of analysis with the LS-DYNA finite element software that investigated the differences and similarities of modeling nuclear fuel assemblies using either shell elements or beam elements. This study provides additional insights on the appropriateness of using beam element models of the fuel pins in the simulation of a hypothetical accident. In this study, two single pin models, a single pin model using shell elements and a single beam model using beam elements, are constructed to analyze end drop scenarios with the LS-DYNA code. Each model is then analyzed for a 19 ft end drop scenario (linear behavior) and 30 ft end drop scenario (non-linear behavior). Comparisons are made between the results obtained with the single pin shell model and with the single pin beam model to study the differences and similarities resulting from the two modeling approaches. In this study, a B and W 15x15 PWR fuel is analyzed for both 30 ft and 19 ft end hypothetical accident drops using both single pin finite element model with shell elements and beam elements for the fuel cladding. It is found that for the 19 ft end drop, the difference in the Max/Min total axial strains is about 12% between the two models. For the 30 ft end drop, the maximum total axial strains calculated with both models is similar, and a difference of about 12% is observed for the minimum total axial strains calculated by the two models. Advantages of the single pin shell model are that it permits consideration of internal pressures and may capture local buckling. Therefore, use of beam elements to model the fuel cladding needs to take into account the possible significance of local buckling and internal pressurization for the problem being analyzed. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Testing, Characterization, and Modeling of the Resonant Plate Test Environment

The resonant plate shock test is a dynamic test of a mid-field pyroshock environment where a projectile is struck against a plate. The structure undergoing the simulated field shock is mounted to the plate. The plate resonates when struck and provides a two sided shock that is representative of the shock observed in the field. This test environment shock simulates a shock in a single coordinate direction for components looking to provide evidence that they will survive a similar or less shock when deployed in their operating environment. However, testing in one axis at a time provides many challenges. The true environment is a multi-axis environment. The test environment exhibits strong off-axis motion when only motion in one axis is desired. Multiple fixtures are needed for a single test series. It would be advantageous if a single test could be developed that tests the multi-axis environment simultaneously. In order to design such a test, a model must be developed and validated. The model can be iterated in design and configuration until the specified multi-axis environment is met. The test can then execute the model driven test design. This report discusses the resonant plate model needed to design future tests and the steps and methods used to obtain the model. This report also details aspects of the resonant plate test discovered during the process of model development that aids in our understanding of the test.

42 ENGINEERING↗

DOE OSTI2024

ComStock™ 2024 Release 1 [SWR-19-33 and SWR-20-32]

ComStock™ is an NREL model of the U.S. commercial building stock. The model takes some building characteristics from the U.S. Department of Energy's (DOE's) Commercial Prototype Building Models and Commercial Reference Building. However, unlike many other building stock models, ComStock also combines these with a variety of additional public- and private-sector data sets. Collectively, this information provides high-fidelity building stock representation with a realistic diversity of building characteristics. This repository contains the source code used to build and execute ComStock models, including upgrade scenarios. In addition, the sampling of buildings characteristics used for the initial ComStock (V1.0) release is provided. The ComStock model is under active calibration and development, which is publicly visible on this repository. Execution of the ComStock workflow is managed through the buildstockbatch repository, a shared asset of ResStock™ and ComStock™ , specifically developed to scale to execution of tens of millions of simulations through multiple infrastructure providers. The dataset output from the initial ComStock (V1.0) release can be found at the accompanying ComStock data viewer website and additional information about ComStock found on the NREL Buildings Website. For more details about ongoing model development please consult the End Use Load Profiles website. ComStock is a direct result of the NREL residential stock modeling tool ResStock™ (recipient of a R&D100 award) and was inspired by the high-fidelity solar & storage adoption model dGen™. Additionally, this tool would not be possible without the decades of work undertaken by the OpenStudio® and EnergyPlus® visionaries and contributors, significant funding, feedback and support from the Los Angeles Department of Water and Power, and the Department of Energy's Building Technology Office ongoing support of and investment in building energy modeling software. is an analytic methodology for modeling the energy usage of the commercial building stock within the United States of America. The commercial building stock is represented through a sampling of complex probabilistic distributions of various features of interest for modeling energy usage within commercial buildings. Each sample from these distributions is converted into a building energy model based on the features of that specific sample. Each building energy model can be simulated as is, but additional changes can be made to the model through addition of energy conservation measures, component faults, or other desired alterations. The results of the simulations are then processed to provide insights for various stakeholders, including but not limited to policy makers, engineers, and marketers.

Horsey, Henry↗

DOE OSTI2015

Local respiratory motion correction for PET/CT imaging: Application to lung cancer

Purpose: Despite multiple methodologies already proposed to correct respiratory motion in the whole PET imaging field of view (FOV), such approaches have not found wide acceptance in clinical routine. An alternative can be the local respiratory motion correction (LRMC) of data corresponding to a given volume of interest (VOI: organ or tumor). Advantages of LRMC include the use of a simple motion model, faster execution times, and organ specific motion correction. The purpose of this study was to evaluate the performance of LMRC using various motion models for oncology (lung lesion) applications. Methods: Both simulated (NURBS based 4D cardiac-torso phantom) and clinical studies (six patients) were used in the evaluation of the proposed LRMC approach. PET data were acquired in list-mode and synchronized with respiration. The implemented approach consists first in defining a VOI on the reconstructed motion average image. Gated PET images of the VOI are subsequently reconstructed using only lines of response passing through the selected VOI and are used in combination with a center of gravity or an affine/elastic registration algorithm to derive the transformation maps corresponding to the respiration effects. Those are finally integrated in the reconstruction process to produce a motion free image over the lesion regions. Results: Although the center of gravity or affine algorithm achieved similar performance for individual lesion motion correction, the elastic model, applied either locally or to the whole FOV, led to an overall superior performance. The spatial tumor location was altered by 89% and 81% for the elastic model applied locally or to the whole FOV, respectively (compared to 44% and 39% for the center of gravity and affine models, respectively). This resulted in similar associated overall tumor volume changes of 84% and 80%, respectively (compared to 75% and 71% for the center of gravity and affine models, respectively). The application of the nonrigid deformation model in LRMC led to over an order of magnitude gain in computational efficiency of the correction relative to the application of the deformable model to the whole FOV. Conclusions: The results of this study support the use of LMRC as a flexible and efficient correction approach for respiratory motion effects for single lesions in the thoracic area.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Predicting Emission Source Terms in a Reduced-Order Fire Spread Model—Part 1: Particulate Emissions

A simple, easy-to-evaluate, surrogate model was developed for predicting the particle emission source term in wildfire simulations. In creating this model, we conceptualized wildfire as a series of flamelets, and using this concept of flamelets, we developed a one-dimensional model to represent the structure of these flamelets which then could be used to simulate the evolution of a single flamelet. A previously developed soot model was executed within this flamelet simulation which could produce a particle size distribution. Executing this flamelet simulation 1200 times with varying conditions created a data set of emitted particle size distributions to which simple rational equations could be tuned to predict a particle emission factor, mean particle size, and standard deviation of particle sizes. These surrogate models (the rational equation) were implemented into a reduced-order fire spread model, QUIC-Fire. Using QUIC-Fire, an ensemble of simulations were executed for grassland fires, southeast U.S. conifer forests, and western mountain conifer forests. Resulting emission factors from this ensemble were compared against field data for these fire classes with promising results. Also shown is a predicted averaged resulting particle size distribution with the bulk of particles produced to be on the order of 1 μm in size.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2011

Analytical model for chip formation in case of orthogonal machining process

The present work deals with the presentation of analytical methodology allowing the modelling of chip formation. For that a 'decomposition approach', based on assuming that the material removal is the summation of two contributions: ploughing and pure cut was adopted. Moreover, this analytical model was calibrated by a finite element model and experimental data in terms of temperature and forces evolutions. The global aim is to propose to the industrial community, an efficient rapid-execution analytical model concerning the material removal in the case of an orthogonal cutting process.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Validation for 233U-Fueled Systems in KENO V.a in SCALE 6.2

Validation of the KENO V.a Monte Carlo code has been performed in recent years using benchmark experiments contained in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook. The models used in these recent validation efforts have been drawn from the Verified, Archived Library of Inputs and Data (VALID). Models must be generated and reviewed by qualified individuals to be added to the VALID library, which leads to high confidence in the models and reduces the probability that apparent validation issues are a result of modeling errors. The contents of the VALID library are somewhat limited because of the effort involved in generating and reviewing models, so no 233U-fueled experiments are included in VALID. A large number of models of 233U experiments have been modeled in the past in support of the criticality safety of 233U in storage at Oak Ridge National Laboratory (ORNL). In June 2016, two midshipmen from the United States Naval Academy were assigned to ORNL, and they reviewed and updated these models for execution in SCALE 6.2. The validation of 233U is of interest because some discrepancies in SCALE results were identified by a beta tester at the Nuclear Energy Agency modeling these systems. These discrepancies were related to a data thinning procedure in the continuous-energy nuclear data process, and had been resolved prior to the release of SCALE 6.2

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2016

Validation for {sup 233}U-Fueled Systems in KENO V.a in SCALE 6.2

Validation of the KENO V.a Monte Carlo code has been performed in recent years using benchmark experiments contained in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook. The models used in these recent validation efforts have been drawn from the Verified, Archived Library of Inputs and Data (VALID). Models must be generated and reviewed by qualified individuals to be added to the VALID library, which leads to high confidence in the models and reduces the probability that apparent validation issues are a result of modeling errors. The contents of the VALID library are somewhat limited because of the effort involved in generating and reviewing models, so no {sup 233}U-fueled experiments are included in VALID. A large number of models of {sup 233}U experiments have been modeled in the past in support of the criticality safety of {sup 233}U in storage at Oak Ridge National Laboratory (ORNL). In June, 2016, two midshipmen from the United States Naval Academy were assigned to ORNL, and they reviewed and updated these models for execution in SCALE 6.2. The validation of {sup 233}U is of interest because some discrepancies in SCALE results were identified by a beta tester at the Nuclear Energy Agency modeling these systems. These discrepancies were related to a data thinning procedure in the continuous-energy nuclear data process, and had been resolved prior to the release of SCALE 6.2. (authors)

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2015

Computer-implemented security evaluation methods, security evaluation systems, and articles of manufacture

Computer-implemented security evaluation methods, security evaluation systems, and articles of manufacture are described. According to one aspect, a computer-implemented security evaluation method includes accessing information regarding a physical architecture and a cyber architecture of a facility, building a model of the facility comprising a plurality of physical areas of the physical architecture, a plurality of cyber areas of the cyber architecture, and a plurality of pathways between the physical areas and the cyber areas, identifying a target within the facility, executing the model a plurality of times to simulate a plurality of attacks against the target by an adversary traversing at least one of the areas in the physical domain and at least one of the areas in the cyber domain, and using results of the executing, providing information regarding a security risk of the facility with respect to the target.

97 MATHEMATICS AND COMPUTING↗