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At least 829 records · Page 46

Toward Multi-scale Modeling and simulation of conduction in heterogeneous materials

This report summarizes a project in which the authors sought to develop and deploy: (i) experimental techniques to elucidate the complex, multiscale nature of thermal transport in particle-based materials; and (ii) modeling approaches to address current challenges in predicting performance variability of materials (e.g., identifying and characterizing physical- chemical processes and their couplings across multiple length and time scales, modeling information transfer between scales, and statically and dynamically resolving material structure and its evolution during manufacturing and device performance). Experimentally, several capabilities were successfully advanced. As discussed in Chapter 2 a flash diffusivity capability for measuring homogeneous thermal conductivity of pyrotechnic powders (and beyond) was advanced; leading to enhanced characterization of pyrotechnic materials and properties impacting component development. Chapter 4 describes success for the first time, although preliminary, in resolving thermal fields at speeds and spatial scales relevant to energetic components. Chapter 7 summarizes the first ever (as far as the authors know) application of TDTR to actual pyrotechnic materials. This is the first attempt to actually characterize these materials at the interfacial scale. On the modeling side, new capabilities in image processing of experimental microstructures and direct numerical simulation on complicated structures were advanced (see Chapters 3 and 5). In addition, modeling work described in Chapter 8 led to improved prediction of interface thermal conductance from first principles calculations. Toward the second point, for a model system of packed particles, significant headway was made in implementing numerical algorithms and collecting data to justify the approach in terms of highlighting the phenomena at play and pointing the way forward in developing and informing the kind of modeling approach originally envisioned (see Chapter 6). In both cases much more remains to be accomplished.

36 MATERIALS SCIENCE↗

RESONANT ABSORPTION OF TRANSVERSE OSCILLATIONS AND ASSOCIATED HEATING IN A SOLAR PROMINENCE. II. NUMERICAL ASPECTS

Transverse magnetohydrodynamic (MHD) waves are ubiquitous in the solar atmosphere and may be responsible for generating the Sun’s million-degree outer atmosphere. However, direct evidence of the dissipation process and heating from these waves remains elusive. Through advanced numerical simulations combined with appropriate forward modeling of a prominence flux tube, we provide the observational signatures of transverse MHD waves in prominence plasmas. We show that these signatures are characterized by a thread-like substructure, strong transverse dynamical coherence, an out-of-phase difference between plane-of-the-sky motions and line-of-sight velocities, and enhanced line broadening and heating around most of the flux tube. A complex combination between resonant absorption and Kelvin–Helmholtz instabilities (KHIs) takes place in which the KHI extracts the energy from the resonant layer and dissipates it through vortices and current sheets, which rapidly degenerate into turbulence. An inward enlargement of the boundary is produced in which the turbulent flows conserve the characteristic dynamics from the resonance, therefore guaranteeing detectability of the resonance imprints. We show that the features described in the accompanying paper through coordinated Hinode and Interface Region Imaging Spectrograph observations match the numerical results well.

79 ASTRONOMY AND ASTROPHYSICS↗

The Quench Protection of Direct Wind Magnets

The direct wind magnets have several unique features. The conductor layout is characterized by thin single conductors wound over long lengths and separated from the other turns with thick layer of insulation. Moreover, there are several layers of winding. The strong non-uniformity in the magnetic field distribution results in different current and thermal margins for quenching in different regions. The quench protection modeling involves multi-physics coupling between electrical, thermal and magnetic transient. The material properties vary over time and location. This coupled with the complexity in the geometry adds to long computation times. The objective of this study is to understand the quench propagation in an EIC high inductance direct wind magnet which enables one to design appropriate quench protection strategies to protect the magnet. An advanced modeling program has been developed to simulate direct wind magnet quench. In conclusion, we validate theoretical simulations with experimental data.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Module-Integrated Power Converters Based on Universal Dock

Solar power installations using alternating current photovoltaic (ACPV) modules have significant cost and performance advantages over systems using conventional solar modules and string inverters. ACPV modules have improved energy harvest due to module-level power point tracking and redundancy. More importantly, ACPV modules are easier and cheaper to install, lowering the total installed cost, indirect costs, and barriers to market entry. Furthermore, ACPV modules have communications and data logging capability, yielding module-level telemetry data that is useful in site diagnostics and other data applications. The products of these efforts were threefold. First, an advanced microinverter power topology was developed, modeled, simulated, and tested. Second, new microinverter enclosure concepts were developed and tested. Third, a new ACPV module prototype was constructed, combining the power topology and the enclosure concepts. SolarBridge filed for patents in each of these areas and is transitioning the project from a concept phase to full development.

14 SOLAR ENERGY↗

Development of Improved Caprock Integrity and Risk Assessment Techniques. Final report for period Oct. 1, 2012 - Sept. 30, 2014

GeoMechanics Technologies has completed a geomechanical caprock integrity analysis and risk assessment study funded through the US Department of Energy. The project included: a detailed review of historical caprock integrity problems experienced in the natural gas storage industry; a theoretical description and documentation of caprock integrity issues; advanced coupled transport flow modelling and geomechanical simulation of three large-scale potential geologic sequestration sites to estimate geomechanical effects from CO₂ injection; development of a quantitative risk and decision analysis tool to assess caprock integrity risks; and, ultimately the development of recommendations and guidelines for caprock characterization and CO₂ injection operating practices. Historical data from gas storage operations and CO₂ sequestration projects suggest that leakage and containment incident risks are on the order of 10 -1 to 10 -2 , which is higher risk than some previous studies have suggested for CO₂. Geomechanical analysis, as described herein, can be applied to quantify risks and to provide operating guidelines to reduce risks. The risk assessment tool developed for this project has been applied to five areas: The Wilmington Graben offshore Southern California, Kevin Dome in Montana, the Louden Field in Illinois, the Sleipner CO₂ sequestration operation in the North Sea, and the In Salah CO₂ sequestration operation in North Africa. Of these five, the Wilmington Graben area represents the highest relative risk while the Kevin Dome area represents the lowest relative risk.

58 GEOSCIENCES↗

ASC FY17 Implementation Plan, Rev. 1

The Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, surety, and reliability of the U.S. nuclear stockpile. The SSP uses nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of experimental facilities and programs, and the computational capabilities to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computational resources that support annual stockpile assessment and certification, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balance of resources, including technical staff, hardware, simulation software, and computer science solutions.

97 MATHEMATICS AND COMPUTING↗

Interactions Between Microturbulence and Magnetohydrodynamic Instabilities in Magnetized Plasmas (Final Technical Report)

The overall goal of this project was to develop a better understanding between small-scale microturbulence and large-scale magnetohydrodynamic (MHD) instabilities, particularly magnetic islands and tearing modes, in fusion relevant magnetically confined plasmas. This project advanced understanding through numerical simulations of different model equations. Questions addressed included how the magnitudes, spatial structures, and scalings of turbulent forcings and drags impact island dynamics, as well as what the "region of influence" of a tearing mode on the turbulence dynamics. A key finding of the project is that the microturbulence (and associated transport) exhibits spatial asymmetries for sufficiently large islands. The results have improved our fundamental understanding of plasma dynamics, motivated new experimental investigations, and will help inform future fusion predictive modeling efforts.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

ASC FY2023 Implementation Plan Revision 0

The DOE National Nuclear Security Administration (NNSA) Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, security, and reliability of the U.S. nuclear stockpile. The SSP incorporates nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. The suite of data analyzed comes from activities including previous nuclear tests, stockpile surveillance, experimental research, and development and engineering programs. This integrated national program requires the continued use of experimental facilities and the computational capabilities to support the SSP missions. These component parts, in addition to an appropriately scaled production capability, enable NNSA to support stockpile requirements. The ultimate goal of the SSP, and thus of the Advanced Simulation and Computing (ASC) Program, is to ensure that the U.S. maintains a safe, secure, and effective strategic deterrent.

97 MATHEMATICS AND COMPUTING↗

Differences In High Burnup Fuel Management Strategies to Minimize FFRD and Increase Economic Viability

The nuclear industry is pursuing approval of an increase in the length of the pressurized water reactor (PWR) cycle from 18 months to 24 months to reduce reactor downtime and enhance the economic competitiveness of nuclear energy. Such an increase in reactor cycle length will require that the maximum rod average burnup exceeds the current regulatory limit of 62 GWd/MTU, and it could peak at approximately 75 GWd/MTU, posing potential reactor safety and performance concerns. One such concern is that fuel fragmentation, relocation, and dispersal (FFRD) could occur during a severe loss-of coolant accident (LOCA) in which a fuel rod balloons and bursts, and pulverized fuel fragments are dispersed throughout the reactor’s primary coolant system. Previous analyses have identified which reactor operating conditions leave the core more susceptible to FFRD and have shown that FFRD susceptibility is strongly linked to fuel rod burnup and linear heat rate (LHR) history. The work described in this report uses an optimization strategy known as parallel simulated annealing (PSA) and a coarse mesh Purdue Advanced Reactor Core Simulator (PARCS) reactor physics model to develop two core fuel loading patterns, each with a different optimization objective. One core optimization maximized the core’s cycle length while still respecting regulatory limits on the radial peaking factor and soluble boron concentration with a peak rod average burnup of 75 GWd/MTU. The second optimization was aimed at minimizing FFRD susceptibility while still targeting a 24-month cycle length and respecting regulatory limits. PARCS model predictions were verified using the high-fidelity Virtual Environment for Reactor Applications (VERA). The two core designs were compared to highlight core design strategies to minimize FFRD susceptibility and to maximize economic viability.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A New Modeling Interface for Simulators Implementing the Discrete Event System Specification

The Discrete Event System Specification (DEVS) offers a unique modeling interface that is often perplexing to modelers more familiar with other simulation paradigms. Recent advances in the use of super dense time for discrete event simulation offer an opportunity to recast the traditional interface into a form less confounding for new users. The new interface proposed here allows a natural progression from a message oriented approach to modeling to the familiar DEVS approach. The proposed approach retains the expressive power of the DEVS formalism, and in this sense represents a simple repackaging of the DEVS approach into a more intuitively appealing form.

Nutaro, James J.↗

The International Experimental Thermal-Hydraulic Systems Database TIETHYS: a new NEA Validation Tool

Recent advances in multi-physics modeling and simulation tools and their necessary validation, has reinvigorated interest in fundamental thermal-hydraulics validation data for appropriate test scenarios and associated physical phenomena. The OECD-NEA has a well-established collection of such references known as the CCVM. However common problems encountered with accessibility of this data have prompted work on a new search and access database tool to allow more efficient and comprehensive use of these data. This will complement the existing tools for neutronics validation, as well as other NEA references resources. As well as acting as a means to better access and preserve this valuable information, it also creates an extendable platform for inclusion of new experimental systems, including eventually those for non-water coolants and high fidelity data focused towards novel CFD simulations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Improved computational neutronics methods and validation protocols for the advanced test reactor

The Idaho National Laboratory (INL) is in the process of updating the various reactor physics modeling and simulation tools used to support operation and safety assurance of the Advanced Test Reactor (ATR). Key accomplishments so far have encompassed both computational as well as experimental work. A new suite of stochastic and deterministic transport theory based reactor physics codes and their supporting nuclear data libraries (HELIOS, KENO6/SCALE, NEWT/SCALE, ATTILA, and an extended implementation of MCNP5) has been installed at the INL. Corresponding models of the ATR and ATRC are now operational with all five codes, demonstrating the basic feasibility of the new code packages for their intended purposes. On the experimental side of the project, new hardware was fabricated, measurement protocols were finalized, and the first four of six planned physics code validation experiments based on neutron activation spectrometry have been conducted at the ATRC facility. Data analysis for the first three experiments, focused on characterization of the neutron spectrum in one of the ATR flux traps, has been completed. The six experiments will ultimately form the basis for flexible and repeatable ATR physics code validation protocols that are consistent with applicable national standards. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Development and Validation of a Two-Phase Thermal-Hydraulic CFD Code NEK-2P

A project is underway to develop, verify and validate an advanced two-phase flow modeling capability for the highly-scalable, high-performance Computational Fluid Dynamics (CFD) code NEK5000. The goal of this work is to verify and validate the two-phase version of the NEK5000 code, named NEK-2P, to simulate the two-phase flow and heat transfer phenomena that occur in a Boiling Water Reactor (BWR) fuel bundle under various operating conditions. The NEK-2P two-phase flow models follow the approach used for the Extended Boiling Framework (EBF) previously developed at Argonne but include more fundamental physical models of boiling phenomena and advanced numerical algorithms for improved computational accuracy, robustness, and computational speed. The development of the NEK-2P two-phase solver and the implementation of the Extended Boiling Framework two-phase models were initially supported by Argonne National Laboratory (Argonne) through a Laboratory Directed Research and Development (LDRD) project during FY2014-2016. The development and validation of the two-phase models through analyses of selected two-phase boiling flow experiments was supported by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program in FY2017-2020. This report focuses on verification and validation of the water-steam boiling model NEK-2P Two-Phase, CFD code. The NEK-2P was validated with Nuclear Power Engineering Corporation (NUPEC) Pressurized Water Reactor (PWR) Sub-channel and Bundle Test (PSBT) void distribution benchmark. Three different simulations were performed and analyzed for various operating conditions such as wall-heat flux and sub-cooled inlet temperatures. Reasonably good agreement with measured data was obtained in predicting the measured void distributions. Simulations were performed for Virginia Tech. (VT) 3x3 rod bundle geometry with and without spacers. The preliminary results were presented for Simplified Spacer Grid (SSG). In addition, the implementation of interface reconstruction model was tested with one of the Becker benchmark Critical Heat Flux (CHF) experiments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

IMPROVED COMPUTATIONAL NEUTRONICS METHODS AND VALIDATION PROTOCOLS FOR THE ADVANCED TEST REACTOR

The Idaho National Laboratory (INL) is in the process of modernizing the various reactor physics modeling and simulation tools used to support operation and safety assurance of the Advanced Test Reactor (ATR). Key accomplishments so far have encompassed both computational as well as experimental work. A new suite of stochastic and deterministic transport theory based reactor physics codes and their supporting nuclear data libraries (HELIOS, KENO6/SCALE, NEWT/SCALE, ATTILA, and an extended implementation of MCNP5) has been installed at the INL. Corresponding models of the ATR and ATRC are now operational with all five codes, demonstrating the basic feasibility of the new code packages for their intended purpose. Of particular importance, a set of as-run core depletion HELIOS calculations for all ATR cycles since August 2009 was successfully completed during 2011. This demonstration supported a decision late in the year to proceed with the phased incorporation of the HELIOS methodology into the ATR fuel cycle management process beginning in 2012. On the experimental side of the project, new hardware was fabricated, measurement protocols were finalized, and the first four of six planned physics code validation experiments based on neutron activation spectrometry were conducted at the ATRC facility. Data analysis for the first three experiments, focused on characterization of the neutron spectrum in one of the ATR flux traps, has been completed. The six experiments will ultimately form the basis for a flexible, easily-repeatable ATR physics code validation protocol that is consistent with applicable ASTM standards.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

AI Meets Exascale Computing: Advancing Cancer Research With Large-Scale High Performance Computing

The application of data science in cancer research has been boosted by major advances in three primary areas: (1) Data: diversity, amount, and availability of biomedical data; (2) Advances in Artificial Intelligence (AI) and Machine Learning (ML) algorithms that enable learning from complex, large-scale data; and (3) Advances in computer architectures allowing unprecedented acceleration of simulation and machine learning algorithms. These advances help build in silico ML models that can provide transformative insights from data including: molecular dynamics simulations, next-generation sequencing, omics, imaging, and unstructured clinical text documents. Unique challenges persist, however, in building ML models related to cancer, including: (1) access, sharing, labeling, and integration of multimodal and multi-institutional data across different cancer types; (2) developing AI models for cancer research capable of scaling on next generation high performance computers; and (3) assessing robustness and reliability in the AI models. In this paper, we review the National Cancer Institute (NCI) -Department of Energy (DOE) collaboration, Joint Design of Advanced Computing Solutions for Cancer (JDACS4C), a multi-institution collaborative effort focused on advancing computing and data technologies to accelerate cancer research on three levels: molecular, cellular, and population. This collaboration integrates various types of generated data, pre-exascale compute resources, and advances in ML models to increase understanding of basic cancer biology, identify promising new treatment options, predict outcomes, and eventually prescribe specialized treatments for patients with cancer.

60 APPLIED LIFE SCIENCES↗

A fast and accurate modeling approach for water and steam thermodynamics with practical applications in district heating system simulation

In U.S. district heating (DH) systems, steam is the most common heat transport medium. Industry demand for new advanced modeling capabilities of complete steam DH systems is increasing; however, the existing models for water/steam thermodynamics are too slow for large system simulations because of computationally expensive algebraic loops that require the solution to nonlinear systems of equations. For practical applications, this work presents a novel split-medium approach that implements numerically efficient liquid water models alongside various water/steam models, breaking costly algebraic loops by decoupling mass and energy balance equations. New component models for steam DH systems are also presented. We implemented the models in the equation based Modelica language and evaluated accuracy and computing speed across multiple scales: from fundamental thermodynamic properties to complete districts featuring 10 to 200 buildings. Compared to district models with the IF97 water/steam model and equipment models from the Modelica Standard Library, the new implementation improves the scaling rate for large districts from cubic to quadratic with negligible compromise to accuracy. Additionally, for an annual simulation with 180 buildings, this translates to a computing time reduction from 33 to 1-1.5 h. These results are critically important for industry practitioners to simulate steam DH systems at large scales.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

MODULES FOR EXPERIMENTS IN STELLAR ASTROPHYSICS (MESA): BINARIES, PULSATIONS, AND EXPLOSIONS

We substantially update the capabilities of the open-source software instrument Modules for Experiments in Stellar Astrophysics (MESA). MESA can now simultaneously evolve an interacting pair of differentially rotating stars undergoing transfer and loss of mass and angular momentum, greatly enhancing the prior ability to model binary evolution. New MESA capabilities in fully coupled calculation of nuclear networks with hundreds of isotopes now allow MESA to accurately simulate the advanced burning stages needed to construct supernova progenitor models. Implicit hydrodynamics with shocks can now be treated with MESA, enabling modeling of the entire massive star lifecycle, from pre-main-sequence evolution to the onset of core collapse and nucleosynthesis from the resulting explosion. Coupling of the GYRE non-adiabatic pulsation instrument with MESA allows for new explorations of the instability strips for massive stars while also accelerating the astrophysical use of asteroseismology data. We improve the treatment of mass accretion, giving more accurate and robust near-surface profiles. A new MESA capability to calculate weak reaction rates “on-the-fly” from input nuclear data allows better simulation of accretion induced collapse of massive white dwarfs and the fate of some massive stars. We discuss the ongoing challenge of chemical diffusion in the strongly coupled plasma regime, and exhibit improvements in MESA that now allow for the simulation of radiative levitation of heavy elements in hot stars. We close by noting that the MESA software infrastructure provides bit-for-bit consistency for all results across all the supported platforms, a profound enabling capability for accelerating MESA's development.

79 ASTRONOMY AND ASTROPHYSICS↗

Intricate short-range order in GeSn alloys revealed by atomistic simulations with highly accurate and efficient machine-learning potentials

GeSn alloys hold promise for silicon-compatible integrated applications in electronics, photonics, and topological quantum devices. However, understanding their intricate structures using density functional theory (DFT) calculations is hindered by spatiotemporal constraints. To overcome this limitation, we develop highly accurate and efficient machine-learning interatomic potentials based on a neuroevolution potential approach with farthest point sampling on a comprehensive DFT data set. The application of the developed machine-learning potential in large-scale atomistic simulations bridges the spatiotemporal gap between modeling and advanced characterizations, and facilitates the discovery of structural intricacies in GeSn alloys. Through extensive statistical sampling, we identify a type of short-range order (SRO) that is distinguished by both its structural signature and electronic band gap from the SRO structure previously predicted. Modeling based on a large simulation cell reveals the coexistence of nano SRO domains with various degrees of ordering, demonstrating a complex spatial heterogeneity of SRO structure. Finally, our study not only reinforces the significance of fine-level structural information in alloys, but it also constitutes an effective framework for exploring SRO in a broad range of complex alloys based on highly accurate and effective machine-learning potentials.

36 MATERIALS SCIENCE↗