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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Generalization of NESTLE into a Multi-Energy N-Group Formulation

The NESTLE code is a few-group, diffusion-based core simulation code that employs the Nodal Expansion Method (NEM). NESTLE has the capability to solve both steady-state and transient problems, using either Cartesian or hexagonal geometry, and to apply thermal-hydraulic feedback including single and two-phase flow. A modern version of the NESTLE nodal-diffusion simulator is currently maintained and developed at the University of Tennessee. The original version of the code was limited to only two or four neutron energy groups, therefore, this article describes recent work carried out to expand NESTLE into a general multi-group solver. Generalization of a fixed group finite-difference diffusion theory into arbitrary N groups is a well-known problem [3], however, this paper describes the intricacies associated with the generalization of the Nodal Expansion Method, and the methodical and computational challenges encountered and managed along the way.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Modeling the Molten Salt Reactor Experiment with the RELAP5-3D code

The Molten Salt Reactor Experiment (MSRE) is a liquid-fueled, graphite-moderated, thermal reactor that was operated at Oak Ridge National Laboratory (ORNL) between 1965 and 1969 at a power of ∼8 MWt (thermal). The fuel (as enriched UF{sub 4}) was dissolved in the coolant, a fluoride liquid salt. In the MSRE, the fuel and the coolant were together in the same fluid-the molten salt. The objective of this effort is to modernize and recapture dynamic modeling capability for molten salt reactors. As part of this effort, the MSRE has been modeled with the code RELAP5-3D. This paper presents calculated results and compares them to available data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

SAM Code Development for Transient Safety Analyses of Fluoride-salt-cooled High-temperature Reactors

The System Analysis Module (SAM) is under development at Argonne National Laboratory as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses. It utilizes the object-oriented application framework MOOSE to leverage the modern software environment and advanced numerical methods. The capabilities of SAM are being extended to enable the transient modeling, analysis, and design of various advanced nuclear reactor systems. The molten-salt-cooled pebble-bed reactor, or pebble-bed FHR (PB-FHR) is a promising candidate among advanced nuclear reactor concepts with its improved passive safety characteristics and high thermal efficiency. To support the development and utilization of the SAM code for PB-FHR safety analysis, activities on SAM code enhancements, reference plant model developments, and code validations have been performed in the past a few years to support near-term industry and NRC needs. This report summarizes recent progress under DOE-NE’s Nuclear Energy Advanced Modeling and Simulation program in SAM code development and demonstration for transient safety analysis of Fluoride-salt-cooled High-temperature Reactors. SAM capabilities has been significantly enhanced over the years to add FHR specific modeling features, including salt freezing and thawing, spherical core channel and pebble bed core modeling, solid-fluid thermal radiation, tritium transport and general species transport in fluids and solids, and the general code enhancements on solver schemes of point kinetics module and reactivity feedback models. A reference PB-FHR model is developed, based on publicly available information from Kairos Power’s generic FHR design and the University of California, Berkeley (UCB) Mk1 design. A reference reactor model is foundational to the methodologies employed by NRC to verify the adequacy of computer codes and evaluation models. The reference FHR model was utilized for a number of selected FHR design basis accidents, including station blackout, loss of heat sink, loss of flow, transient overpower, and overcooling events.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

OpenMP in VASP: Threading and SIMD

Abstract The Vienna Ab initio Simulation Package (VASP) is a widely used electronic structure code that originally exploits process‐level parallelism through the Message Passing Interface (MPI) for work distribution within and across nodes. Architectural changes of modern parallel processors urge programmers to address thread‐ and data‐level parallelism as well to benefit most from the available compute resources within a node. We describe for VASP how to approach for an MPI + OpenMP parallelization including data‐level parallelism through OpenMP SIMD constructs together with a generic high‐level vector coding scheme. We can demonstrate an improved scalability of VASP and more than 20% gain over the MPI‐only version as well as a 2× increased performance of collective operations using the multiple‐endpoint MPI feature. The high‐level vector coding scheme applied to VASP's general gradient approximation routine gives up 9× performance gain on AVX512 platforms with the Intel compiler.

Wende, Florian↗
DOE OSTI2018

Non-convex Multi-species Hopfield Models

In this work we introduce a multi-species generalization of the Hopfield model for associative memory, where neurons are divided into groups and both inter-groups and intra-groups pair-wise interactions are considered, with different intensities. Thus, this system contains two of the main ingredients of modern deep neural-network architectures: Hebbian interactions to store patterns of information and multiple layers coding different levels of correlations. The model is completely solvable in the low-load regime with a suitable generalization of the Hamilton–Jacobi technique, despite the Hamiltonian can be a non-definite quadratic form of the Mattis magnetizations. The family of multi-species Hopfield model includes, as special cases, the 3-layers Restricted Boltzmann Machine with Gaussian hidden layer and the Bidirectional Associative Memory model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

GloVe C++ v. 1.0

This code implements the GloVe algorithm for learning word vectors from a text corpus. It uses a modern C++ approach. This algorithm is described in the open literature in the referenced paper by Pennington, Jeffrey, Richard Socher, and Christopher D. Manning.

Cox, JonathanA.↗
DOE OSTI2021

MFIX-Exa: A path toward exascale CFD-DEM simulations

MFIX-Exa is a computational fluid dynamics–discrete element model (CFD-DEM) code designed to run efficiently on current and next-generation supercomputing architectures. MFIX-Exa combines the CFD-DEM expertise embodied in the MFIX code—which was developed at NETL and is used widely in academia and industry—with the modern software framework, AMReX, developed at LBNL. The fundamental physics models follow those of the original MFIX, but the combination of new algorithmic approaches and a new software infrastructure will enable MFIX-Exa to leverage future exascale machines to optimize the modeling and design of multiphase chemical reactors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Hydrodynamic and Radiographic Toolbox (HART)

With a multi-lab and university team, we propose to develop new methods for a Hydrodynamic and Radiographic Toolbox (HART) that will enable a fuller and more extensive use of experimental radiographic data towards better characterizing and reducing uncertainties in predictive modeling of weapons performance. We will achieve this by leveraging recent developments in areas of computational imaging, statistical and machine learning, and reduced order modeling of hydrodynamics. In terms of software practices, by partnering with XCP (RISTRA Project) we will conform to recent XCP standards that are inline with modern software practices and standards and ensure compatibility and ease of inter-operability with existing codes. Three new activities under this proposal include (a) the development and use of deep learning-based surrogates to accelerate reconstruction and variational inference of density fields from radiographs of hydrotests, (b) a model-data fusion strategy that couples deep learning-based density reconstructions with fast hydrodynamics simulators to better constrain the reconstruction, and (c) a method for treating asymmetries using techniques adopted from limited view tomography. All three new activities will be based on improved treatment of scatter, noise, beam spot movement, detector blur, and flat fielding in the forward model, and a use of sophisticated priors to aid in the re construction. The improvements to the forward model and improved algorithmic design of the reconstruction when complete will be contained in the iterative reconstruction code SHIVA—a code project that we have recently initiated. The many ways in which machine learning can be used in the reconstruction work will be contained in a code HERMES that has been initiated with DTRA support. For example, the significant levels of acceleration that will likely be achieved by the use of machine learning techniques will permit us (and are required) to quantify uncertainties in density retrievals. Next, the two-way coupling between density reconstruction and model-based simulation of the hydrodynamics will be contained in code EREBUS, and will permit a fuller realization of the potential of the data to constrain the hydrodynamic model and better address issues related to asymmetries in the problem. Finally, we anticipate that the better consistency with physics achieved in our reconstructions will allow them to be used by X-Division more so than today.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Investigation of Thermal-Hydraulic Effects of Dry Storage Canister Helium Backfill Loss Using the Horizontal Dry Cask Simulator

A previous investigation produced data sets that can be used to benchmark the codes and best practices presently used to determine cladding temperatures and induced cooling air flows in modern horizontal dry storage systems. The horizontal dry cask simulator (HDCS) was designed to generate this benchmark data and add to the existing knowledge base. The objective of the previous HDCS investigation was to capture the dominant physics of a commercial dry storage system in a well-characterized test apparatus for a wide range of operational parameters. The close coupling between the thermal response of the canister system and the resulting induced cooling air flow rate was of particular importance. The previous investigation explored these parameters using helium backfill at 100 kPa and 800 kPa pressure as well as air backfill with a series of simulated decay heats. The helium tests simulated a horizontal dry cask storage system at normal storage conditions with either atmospheric or elevated backfill pressure, while the air tests simulated horizontal storage canisters following a complete loss of helium backfill, in which case the helium would be replaced by air. The present HDCS investigation adds to the previous investigation by exploring steady-state conditions at various stages of the loss of helium backfill from a horizontal dry cask storage system. This is achieved by using helium/air blends as a backfill in the HDCS and running a series of tests using various simulated decay heats to explore the effects of relative helium/air molar concentration on the thermal response of a simulated horizontal dry cask storage system. A total of twenty tests were conducted where the HDCS achieved steady state for various assembly powers, representative of decay heat. The power levels tested were 0.50, 1.00, 2.50, and 5.00 kW. All tests were run at 100 kPa vessel pressure. The backfill gases used in these tests are given in this report as a function of mole fraction of helium (He), balanced by air: 1.0, 0.9, 0.5, 0.1, and 0.0 He. Steady-state conditions (where the steady-state start condition is defined as where the change in temperature with respect to time for the majority of HDCS components is less than or equal to 0.3 K/h) were achieved for all test cases.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

GloVe C++ v. 1.0

This code implements the GloVe algorithm for learning word vectors from a text corpus. It uses a modern C++ approach. This algorithm is described in the open literature in the referenced paper by Pennington, Jeffrey, Richard Socher, and Christopher D. Manning.

Cox, Jonathan A.↗
DOE OSTI2018

Influence of the Asynchronous Multibeam Irradiation of a Spherical Fusion Target by Megajoule Laser Beams on the Efficiency of Thermonuclear Burning

We have studied the dependence of the compression and burning of a spherical direct-drive fusion target on the nonuniformity of its heating caused by the asynchronous arrival of laser beams under conditions of irradiation by a modern laser system with a total energy of 2 MJ intended for the fuel ignition and fusion energy evolution equal to the absorbed laser energy. The investigation is performed by numerical simulation based on 2D hydrodynamic codes. It is established that the limiting permissible spread of the moments of laser pulse action on the target for ignition significantly exceeds the level that can be ensured using modern methods of controlled temporal synchronization of laser beams.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Computing the Properties of Matter with Leadership Computing Resources (Closeout Report for DE-SC0018121)

In order to add more capabilities to Halide, we have designed a new framework called Tiramisu and integrated this framework into Halide. Since Tiramisu enables Halide to target heterogeneous architectures, our development efforts have been refocused on Tiramisu. Most high-performance computer systems today are complex and increasingly heterogeneous; they may have CPUs, GPUs and FPGAs. Achieving best performance requires taking full advantage of all these different architectures. To address this issue, we have designed Tiramisu, an optimization framework that enables Halide (and other DSLs) to target heterogeneous architectures. Tiramisu is an optimization framework that takes as input a high level, architecture-independent representation of code and a set of scheduling and data mapping commands that guide code transformation. The input can either be generated by a domain-specific language (DSL) compiler such as Halide or directly written by a programmer. Tiramisu then applies the user-specified code and data-layout transformations and generates an architecture-specific, low-level intermediate representation (IR) that takes advantage of modern architectural features such as multicore parallelism, non-uniform memory (NUMA) hierarchies, clusters, and accelerators like GPUs and FPGAs. We integrated Tiramisu within Halide and implemented a representative set of benchmarks to evaluate this integration. Tiramisu is now open source and is available for public use (http://tiramisu-compiler.org/). A paper about Tiramisu was published, it shows that Tiramisu extends Halide with many new capabilities and that Tiramisu can generate efficient code for multicores, GPUs, FPGAs and distributed heterogeneous systems. The performance of code generated by the Tiramisu backends matches or exceeds hand optimized reference implementations. For example, the multicore backend matches the highly optimized Intel MKL library on many kernels and shows speedups reaching 4x over the original Halide. In addition to making Tiramisu more robust, we have used Tiramisu to implement a set of representative tensor operation for constructing baryon building blocks required for multi baryon contractions in LQCD. In order to implement this code, we needed to generalize Tiramisu in two ways: first we needed to support indirect array accesses, and second, we needed to add support for complex numbers to Tiramisu. The code generated by Tiramisu is 6x faster than the reference code. Our efforts towards an MPI based multi-node version of tiramisu have matured and the resulting code scales well on multiple nodes (tests up to 512 KNL nodes have been undertaken).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

The journey from forensic to predictive materials science using density functional theory

Approximate methods for electronic structure, implemented in sophisticated computer codes and married to ever-more powerful computing platforms, have become invaluable in chemistry and materials science. The maturing and consolidation of quantum chemistry codes since the 1980s, based upon explicitly correlated electronic wave functions, has made them a staple of modern molecular chemistry. Here, the impact of first principles electronic structure in physics and materials science had lagged owing to the extra formal and computational demands of bulk calculations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

SAM Theory Manual

The System Analysis Module (SAM) is an advanced and modern system analysis tool under development at Argonne National Laboratory for advanced non-LWR reactor safety analysis. It aims to provide fast-running, modest-fidelity, whole-plant transient analyses capabilities, which are essential for fast turnaround design scoping and engineering analyses of advanced reactor concepts. While SAM is being developed as a system-level modeling and simulation tool, advanced modeling techniques being implemented include a reduced-order three-dimensional module, pseudo 3-D conjugate heat transfer modeling in reactor core, flexible and multi-scale modeling of heat transfer between fluid and structures, in addition to the advances in software environments and design, and numerical methods. SAM aims to be a generic system-level safety analysis tool for advanced non-LWRs, including Liquid-Metal-cooled fast Reactors (LMR), Molten Salt Reactors (MSR), Fluoride-salt-cooled High- temperature Reactors (FHR), and High-Temperature Gas-cooled Reactors (HTGR). SAM takes ad- vantage of advances in physical modeling, numerical methods, and software engineering to enhance its user experience and usability. It utilizes an object-oriented computational framework (MOOSE), and its underlying meshing and finite-element library and linear and non-linear solvers, to leverage the modern advanced software environments and numerical methods. This document provides the theoretical and technical basis of the code to help users understand the underlying physical models (such as governing equations, closure models, and component models), system modeling approaches, numerical discretization and solution methods, and the overall capabilities in SAM. As new code capabilities and features are added, the SAM Theory Manual will be updated periodically to keep it consistent with the state of the development.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

SAM Theory Manual

The System Analysis Module (SAM) is an advanced and modern system analysis tool under development at Argonne National Laboratory for advanced non-LWR reactor safety analysis. It aims to provide fast-running, modest-fidelity, whole-plant transient analyses capabilities, which are essential for fast turnaround design scoping and engineering analyses of advanced reactor concepts. While SAM is being developed as a system-level modeling and simulation tool, advanced modeling techniques being implemented include a reduced-order three-dimensional module, pseudo 3-D conjugate heat transfer modeling in reactor core, flexible and multi-scale modeling of heat transfer between fluid and structures, in addition to the advances in software environments and design, and numerical methods. SAM aims to be a generic system-level safety analysis tool for advanced non-LWRs, including Liquid-Metal-cooled fast Reactors (LMR), Molten Salt Reactors (MSR), Fluoride-salt-cooled High-temperature Reactors (FHR), and High-Temperature Gas-cooled Reactors (HTGR). SAM takes advantage of advances in physical modeling, numerical methods, and software engineering to enhance its user experience and usability. It utilizes an object-oriented computational framework (MOOSE), and its underlying meshing and finite-element library and linear and non-linear solvers, to leverage the modern advanced software environments and numerical methods. This document provides the theoretical and technical basis of the code to help users understand the underlying physical models (such as governing equations, closure models, and component models), system modeling approaches, numerical discretization and solution methods, and the overall capabilities in SAM. As new code capabilities and features are added, the SAM Theory Manual will be updated periodically to keep it consistent with the state of the development.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

SAM Code Validation using the Compact Integral Effects Test (CIET) Experimental Data

The primary objective of this study is to validate the system analysis code, SAM, using experimental data from the Compact Integral Effects Test (CIET) facility. The System Analysis Module (SAM) is an advanced and modern system analysis tool being developed at Argonne National Laboratory under the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. Originally aiming at supporting sodium fast reactor (SFR) design, it is now extended to cover other non-light water reactor (non-LWR) concepts, such as high-temperature gas-cooled reactor (HTGR) designs, molten salt-fueled, and molten salt-cooled reactor designs. To support SAM code development for the wide range of non-LWR applications, it is of paramount importance to validate the code against experiments relevant to these reactor concepts. The Compact Integral Effects Test (CIET) facility, which was designed to reproduce the thermal-hydraulics response of fluoride salt-cooled high-temperature reactors (FHR) under both forced- and natural-circulation conditions, has been identified and selected as one of benchmark test facilities for SAM code validation. Among available CIET experiments, three sets of them with distinctive characteristics were selected for SAM code validation purpose. The three sets experiments are: 1) Power step change transient tests; 2) DHX-DRACS natural circulation tests; and 3) heater frequency response tests. For all tests, steady-state or transient, SAM-predicted results show very good agreement with experimental data. The successful validation of SAM against these selected CIET experiments demonstrates that the computer code is well suited for thermal-hydraulics analysis of FHR designs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

The History of Monte Carlo and MCNP at Los Alamos [Slides]

The Monte Carlo method for radiation particle transport has its origins at LANL dating back to the 1940’s. The creators of these methods were Drs. Stanislaw Ulam, John von Neumann, Robert Richtmyer, and Nicholas Metropolis. Monte Carlo methods for particle transport have been driving computational developments since the beginning of modern computers; this continues today. In the 1950’s and 1960’s, these new methods were organized into a series of special-purpose Monte Carlo codes, including MCS, MCN, MCP, and MCG. These codes were able to transport neutrons and photons for specialized LANL applications. In 1977, these separate codes were combined to create the LANL Monte Carlo N-Particle (MCNP) radiation particle transport code. In 1983, MCNP3 was released for public distribution to the Radiation Safety Information Computational Center (RSICC). MCNP6.3 will be released late in 2021. Each year, LANL has ~100 MCNP new users and RSICC ~1250 new licenses distributed. This talk will review the Los Alamos history of the development of the modern Monte Carlo method and MCNP.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Development for Integrated System-Level Analysis Capabilities in SAM for Molten Salt Reactors

In recent years, there has been renewed interest in Molten Salt Reactors (MSRs) for their potential advantages compared to reactors that rely on solid fuel. In response to such interest, many methods and codes have been developed to capture the unique features of MSRs. Among them, the System Analysis Module (SAM) is a modern system analysis tool that provides fast-running, modest-fidelity, whole-plant transient analysis capabilities, essential for fast-turnaround design scoping and engineering analyses of advanced reactor concepts. For liquid-fuel MSRs, the complex physics and chemistry involved in MSR operation—such as reactor kinetics, fluid flow, heat transfer, and salt composition dynamics—pose significant challenges for system-level modeling. Specific modeling capabilities are needed for system-level transient simulation. This paper presents recent advancements in SAM capability enhancements for system-level modeling of MSRs, focusing on improved simulation fidelity, computational efficiency, and multi-physics integration. Key enhancements include the development of species transport, Delayed Neutron Precursor (DNP) drift, modified Point Kinetics Equations (PKE), decay heat modeling, key fission product behavior, salt corrosion, and thermal-hydraulic coupling, as well as code robustness and performance enhancements for MSR applications. The code enhancement allows for better predictive accuracy in safety analysis, transient behavior, and operational optimization, thus supporting the design and licensing of next-generation MSRs. Results from case studies are presented to demonstrate the benefits of these enhancements in accurately capturing key reactor transient behaviors.

Hu, Rui (ORCID:0000000237712920)↗