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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

A Fault-Oblivious Extreme-Scale Execution Environment (FOX)

IBM Research’s contribution to the Fault Oblivious Extreme-scale Execution Environment (FOX) revolved around three core research deliverables: • collaboration with Boston University around the Kittyhawk cloud infrastructure which both enabled a development and deployment platform for the project team and provided a fault-injection testbed to evaluate prototypes • operating systems research focused on exploring role-based operating system technologies through collaboration with Sandia National Labs on the NIX research operating system and collaboration with the broader IBM Research community around a hybrid operating system model which became known as FusedOS • IBM Research also participated in an advisory capacity with the Boston University SESA project, the core of which was derived from the K42 operating system research project funded in part by DARPA’s HPCS program. Both of these contributions were built on a foundation of previous operating systems research funding by the Department of Energy’s FastOS Program. Through the course of the X-stack funding we were able to develop prototypes, deploy them on production clusters at scale, and make them available to other researchers. As newer hardware, in the form of BlueGene/Q, came online, we were able to port the prototypes to the new hardware and release the source code for the resulting prototypes as open source to the community. In addition to the open source coded for the Kittyhawk and NIX prototypes, we were able to bring the BlueGene/Q Linux patches up to a more recent kernel and contribute them for inclusion by the broader Linux community. The lasting impact of the IBM Research work on FOX can be seen in its effect on the shift of IBM’s approach to HPC operating systems from Linux and Compute Node Kernels to role-based approaches as prototyped by the NIX and FusedOS work. This impact can be seen beyond IBM in follow-on ideas being incorporated into the proposals for the Exasacale Operating Systems/Runtime program.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

AGR-2 safety test predictions using the PARFUME code

This report documents calculations performed to predict failure probability of TRISO-coated fuel particles and diffusion of fission products through these particles during safety tests following the second irradiation test of the Advanced Gas Reactor program (AGR-2). The calculations include the modeling of the AGR-2 irradiation that occurred from June 2010 to October 2013 in the Advanced Test Reactor (ATR) and the modeling of a safety testing phase to support safety tests planned at Oak Ridge National Laboratory and at Idaho National Laboratory (INL) for a selection of AGR-2 compacts. The heat-up of AGR-2 compacts is a critical component of the AGR-2 fuel performance evaluation, and its objectives are to identify the effect of accident test temperature, burnup, and irradiation temperature on the performance of the fuel at elevated temperature. Safety testing of compacts will be followed by detailed examinations of the fuel particles to further evaluate fission product retention and behavior of the kernel and coatings. The modeling was performed using the particle fuel model computer code PARFUME developed at INL. PARFUME is an advanced gas-cooled reactor fuel performance modeling and analysis code (Miller 2009). It has been developed as an integrated mechanistic code that evaluates the thermal, mechanical, and physico-chemical behavior of fuel particles during irradiation to determine the failure probability of a population of fuel particles given the particle-to-particle statistical variations in physical dimensions and material properties that arise from the fuel fabrication process, accounting for all viable mechanisms that can lead to particle failure. The code also determines the diffusion of fission products from the fuel through the particle coating layers, and through the fuel matrix to the coolant boundary. The subsequent release of fission products is calculated at the compact level (release of fission products from the compact). PARFUME calculates the release fraction as the ratio of the number of atoms released from the compact to the amount produced in the compact fuel kernels and through uranium contamination. These safety test predictions aim at giving guidance for the upcoming safety tests to be conducted at ORNL and INL. The AGR-2 compacts modeled in this study belong to the four U.S. capsules of the AGR-2 irradiation test train. For each capsule, the compacts with the lowest and highest burnups were selected to provide a prediction envelope. The objective of this document is to present results of calculations and analyses made by PARFUME on these selected AGR-2 compacts. These results include: • Fuel failure probability • Palladium penetration • Fractional release of fission products Details associated with completion of these calculations are provided in the remainder of this document: the AGR-2 Safety Testing plan is briefly introduced in Section 2, PARFUME modeling is outlined in Section 3, results are described in Section 4, conclusions are given in Section 5, and references are listed in Section 6.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Scalable and Power Efficient Data Analytics for Hybrid Exascale Systems

This project developed a generic and optimized set of core data analytics functions. These functions organically consolidate a broad constellation of high performance analytical pipelines. As the architectures of emerging HPC systems become inherently heterogeneous, there is a need to design algorithms for data analysis kernels accelerated on hybrid multi-node, multi-core HPC architectures comprised of a mix of CPUs, GPUs, and SSDs. Furthermore, the power-aware trend drives the advances in our performance-energy tradeoff analysis framework which enables our data analysis kernels algorithms and software to be parameterized so that users can choose the right power-performance optimizations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Exploring the Random Phase Approximately for materials chemistry and physics

This proposal focuses on improved accuracy for the delicate energy differences of interest in materials chemistry with the fully nonlocal random phase approximation (RPA) in a density functional context. Could RPA or RPA-like approaches become standard methods of first-principles electronic-structure calculation for atoms, molecules, solids, surfaces, and nano-structures? Direct RPA includes the full exact exchange energy and a nonlocal correlation energy from the occupied and unoccupied Kohn-Sham orbitals and orbital energies, with an approximate but universal description of long-range van der Waals attraction. RPA also improves upon simple pair-wise interaction potentials or vdW density functional theory. This improvement is essential to capture accurate energy differences in metals and different phases of semiconductors. The applications in this proposal are challenges for the simpler approximations of Kohn-Sham density functional theory, which are part of the current “standard model” for quantum chemistry and condensed matter physics. Within this project we already applied RPA on different structural phase transitions on semiconductors, metals and molecules. Although RPA predicts accurate structural parameters, RPA has proven not equally accurate in all kinds of structural phase transitions. Therefore a correction to RPA can be necessary in many cases. We are currently implementing and testing a nonempirical, spatially nonlocal, frequency-dependent model for the exchange-correlation kernel in the adiabatic-connection fluctuation-dissipation context. This kernel predicts a nearly-exact correlation energy for the electron gas of uniform density. If RPA or RPA-like approaches prove to be reliably accurate, then expected increases in computer power may make them standard in the electronic-structure calculations of the future.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2015

AGR-1 Post Irradiation Examination Final Report

The post-irradiation examination (PIE) of the Advanced Gas Reactor (AGR)-1 experiment was a multi-year, collaborative effort between Idaho National Laboratory (INL) and Oak Ridge National Laboratory (ORNL) to study the performance of UCO (uranium carbide, uranium oxide) tristructural isotropic (TRISO) coated particle fuel fabricated in the U.S. and irradiated at the Advanced Test Reactor at INL to a peak burnup of 19.6% fissions per initial metal atom. This work involved a broad array of experiments and analyses to evaluate the level of fission product retention by the fuel particles and compacts (both during irradiation and during post-irradiation heating tests to simulate reactor accident conditions), investigate the kernel and coating layer morphology evolution and the causes of coating failure, and explore the migration of fission products through the coating layers. The results have generally confirmed the excellent performance of the AGR-1 fuel, first indicated during the irradiation by the observation of zero TRISO coated particle failures out of 298,000 particles in the experiment. Overall release of fission products was determined by PIE to have been relatively low during the irradiation. A significant finding was the extremely low levels of cesium released through intact coatings. This was true both during the irradiation and during post-irradiation heating tests to temperatures as high as 1800°C. Post-irradiation safety test fuel performance was generally excellent. Silver release from the particles and compacts during irradiation was often very high. Extensive microanalysis of fuel particles was performed after irradiation and after high-temperature safety testing. The results of particle microanalysis indicate that the UCO fuel is effective at controlling the oxygen partial pressure within the particle and limiting kernel migration. Post-irradiation examination has provided the final body of data that speaks to the quality of the AGR-1 fuel, building on the as-fabricated fuel characterization and irradiation data. In addition to the extensive volume of results generated, the work also resulted in a number of novel analysis techniques and lessons learned that are being applied to the examination of fuel from subsequent TRISO fuel irradiations. This report provides a summary of the results obtained as part of the AGR-1 PIE campaign over its approximately 5-year duration.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Acceptance Test Data for BWXT Coated Particle Batch 93164A Defective IPyC Fraction and Pyrocarbon Anisotropy

Coated particle fuel batch J52O-16-93164 was produced by Babcock and Wilcox Technologies (BWXT) for possible selection as fuel for the Advanced Gas Reactor Fuel Development and Qualification (AGR) Program’s AGR-5/6/7 irradiation test in the Idaho National Laboratory (INL) Advanced Test Reactor (ATR), or may be used as demonstration production-scale coated particle fuel for other experiments. The tristructural-isotropic (TRISO) coatings were deposited in a 150-mm-diameter production-scale fluidizedbed chemical vapor deposition (CVD) furnace onto 425-μm-nominal-diameter spherical kernels from BWXT lot J52L-16-69316. Each kernel contained a mixture of 15.5%-enriched uranium carbide and uranium oxide (UCO) and was coated with four consecutive CVD layers: a ~50% dense carbon buffer layer with 100-μm-nominal thickness, a dense inner pyrolytic carbon (IPyC) layer with 40-μm-nominal thickness, a silicon carbide (SiC) layer with 35-μm-nominal thickness, and a dense outer pyrolytic carbon (OPyC) layer with 40-μm-nominal thickness. The TRISO-coated particle batch was sieved to upgrade the particles by removing over-sized and under-sized material, and the upgraded batch was designated by appending the letter A to the end of the batch number (i.e., 93164A).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Ethanol from Agriculture for Arkansas and America

The purpose of this project was to develop technology that would facilitate production of sugars from agricultural residues to enable biofuels and biobased product manufacturing. Our primary technology is to use genetic engineering to put bacterial and fungal cellulase genes into corn kernels, using the grain as the production system for the enzymes. At the beginning of this DoE funded program, we were producing two cellulases—E1 endocellulase from a bacterium found in a hot spring at Yellowstone National Park, and CBH I exocellulase from a wood rot fungus. Our team developed several new regulatory sequences (promoters) that increased enzyme protein accumulation in two kernel compartments (embryo and endosperm). We were also able to capitalize on the diverse genetics of corn to increase protein accumulation. High oil germplasm in particular was instrumental in this increase. A second task in the program was to produce enzymes and proteins that enhanced the activity of the E1 and CBH I enzymes. Our team produced CBH II, from the same wood rot fungus at a level that enabled highly enhanced deconstruction activity of E1 and CBH I in a synergistic manner. We analyzed an additional protein, expansin from cucumber that was expressed in the maize grain expression system. This protein had been previously shown to enhance cellulase activity (D. Cosgrove, Penn State University), and required a large-scale production platform. Our team showed that the corn production system allows industrial amounts of active expansin to be harvested from the grain. One of the challenges of any new production system is to maximize recovery of active ingredient from the raw materials at a cost compatible with its final use. Our team showed that low pH extraction of grain solubilized the enzymes without contamination of native corn protein and active product could be concentrated through ultrafiltration. The final outcomes of this project were the following: 3 cellulase enzymes and the synergistic protein expansin produced at high levels in corn grain, new promoters and combinations of promoters to enhance protein accumulation in grain, application of unique germplasm pools to enhance protein accumulation, and highly efficient processing enabling cost-effective production of cellulases that are highly active in biomass deconstruction.

09 BIOMASS FUELS↗
DOE OSTI2016

Fission Product Inventory and Burnup Evaluation of the AGR-2 Irradiation by Gamma Spectrometry

Gamma spectrometry has been used to evaluate the burnup and fission product inventory of different components from the US Advanced Gas Reactor Fuel Development and Qualification Program's second TRISO-coated particle fuel irradiation test (AGR-2). TRISO fuel in this irradiation included both uranium carbide / uranium oxide (UCO) kernels and uranium oxide (UO 2 ) kernels. Four of the 6 capsules contained fuel from the US Advanced Gas Reactor program, and only those capsules will be discussed in this work. The inventories of gamma-emitting fission products from the fuel compacts, graphite compact holders, graphite spacers and test capsule shell were evaluated. These data were used to measure the fractional release of fission products such as Cs-137, Cs-134, Eu-154, Ce-144, and Ag-110m from the compacts. The fraction of Ag-110m retained in the compacts ranged from 1.8% to full retention. Additionally, the activities of the radioactive cesium isotopes (Cs-134 and Cs-137) have been used to evaluate the burnup of all US TRISO fuel compacts in the irradiation. The experimental burnup evaluations compare favorably with burnups predicted from physics simulations. Predicted burnups for UCO compacts range from 7.26 to 13.15 % fission per initial metal atom (FIMA) and 9.01 to 10.69 % FIMA for UO 2 compacts. Measured burnup ranged from 7.3 to 13.1 % FIMA for UCO compacts and 8.5 to 10.6 % FIMA for UO 2 compacts. Results from gamma emission computed tomography performed on compacts and graphite holders that reveal the distribution of different fission products in a component will also be discussed. Gamma tomography of graphite holders was also used to locate the position of TRISO fuel particles suspected of having silicon carbide layer failures that lead to in-pile cesium release.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

X-ray Analysis of Defects and Anomalies in AGR-5/6/7 TRISO Particles

Coated particle fuel batches J52O-16-93164, 93165, 93166, 93168, 93169, 93170, and 93172 were produced by Babcock and Wilcox Technologies (BWXT) for possible selection as fuel for the Advanced Gas Reactor Fuel Development and Qualification (AGR) Program’s AGR-5/6/7 irradiation test in the Idaho National Laboratory (INL) Advanced Test Reactor (ATR), or may be used for other tests. Each batch was coated in a 150-mm-diameter production-scale fluidized-bed chemical vapor deposition (CVD) furnace. Tristructural isotropic (TRISO) coatings were deposited on 425-μm-nominal-diameter spherical kernels from BWXT lot J52R-16-69317 containing a mixture of 15.4%-enriched uranium carbide and uranium oxide (UCO), with the exception of Batch 93164, which used similar kernels from BWXT lot J52L-16-69316. The TRISO-coatings consisted of a ~50% dense carbon buffer layer with 100-μmnominal thickness, a dense inner pyrolytic carbon (IPyC) layer with 40-μm-nominal thickness, a silicon carbide (SiC) layer with 35-μm-nominal thickness, and a dense outer pyrolytic carbon (OPyC) layer with 40-μm-nominal thickness. Each coated particle batch was sieved to upgrade the particles by removing over-sized and under-sized material, and the upgraded batch was designated by appending the letter A to the end of the batch number (e.g., 93164A). Secondary upgrading by sieving was performed on the upgraded batches to remove specific anomalies identified during analysis for Defective IPyC, and the upgraded batches were designated by appending the letter B to the end of the batch number (e.g., 93165B). Following this secondary upgrading, coated particle composite J52R-16-98005 was produced by BWXT as fuel for the AGR Program’s AGR-5/6/7 irradiation test in the INL ATR. This composite was comprised of coated particle fuel batches J52O-16-93165B, 93168B, 93169B, and 93170B.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Resilient and Robust High Performance Computing Platforms for Scientific Computing Integrity

As technology advances, computer systems are subject to increasingly sophisticated cyber-attacks that compromise both their security and integrity. High performance computing platforms used in commercial and scientific applications involving sensitive, or even classified data, are frequently targeted by powerful adversaries. This situation is made worse by a lack of fundamental security solutions that both perform efficiently and are effective at preventing threats. Current security solutions fail to address the threat landscape and ensure the integrity of sensitive data. As challenges rise, both private and public sectors will require robust technologies to protect its computing infrastructure. The research outcomes from this project try to address all these challenges. For example, we present LAZARUS, a novel technique to harden kernel Address Space Layout Randomization (KASLR) against paging-based side-channel attacks. In particular, our scheme allows for fine-grained protection of the virtual memory mappings that implement the randomization. We demonstrate the effectiveness of our approach by hardening a recent Linux kernel with LAZARUS, mitigating all of the previously presented side-channel attacks on KASLR. Our extensive evaluation shows that LAZARUS incurs only 0.943% overhead for standard benchmarks, and is therefore highly practical. We also introduced HA2lloc, a hardware-assisted allocator that is capable of leveraging an extended memory management unit to detect memory errors in the heap. We also perform testing using HA2lloc in a simulation environment and find that the approach is capable of preventing common memory vulnerabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Design and Thermal Analysis for Irradiation of Pyrolytic Carbon/Silicon Carbide Diffusion Couples in the High Flux Isotope Reactor

Tristructural-isotropic (TRISO)–coated particle fuel is a promising advanced fuel concept consisting of a spherical fuel kernel made of uranium oxide and uranium carbide, surrounded by a porous carbonaceous buffer layer and successive layers of dense inner pyrolytic carbon (IPyC), silicon carbide (SiC) deposited by chemical vapor , and dense outer pyrolytic carbon (OPyC). This fuel concept is being considered for advanced reactor applications such as high temperature gas-cooled reactors (HTGRs) and molten salt reactors (MSRs), as well as for accident-tolerant fuel for light water reactors (LWRs). Development and implementation of TRISO fuel for these reactor concepts support the US Department of Energy (DOE) Office of Nuclear Energy mission to promote safe, reliable nuclear energy that is sustainable and environmentally friendly. During operation, the SiC layer serves as the primary barrier to metallic fission products and actinides not retained in the kernel. It has been observed that certain fission products are released from TRISO fuel during operation, notably, Ag, Eu, and Sr [1]. Release of these radioisotopes causes safety and maintenance concerns.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Multi-threaded Sparse Matrix Sparse Matrix Multiplication for Many-Core and GPU Architectures.

Sparse Matrix-Matrix multiplication is a key kernel that has applications in several domains such as scientific computing and graph analysis. Several algorithms have been studied in the past for this foundational kernel. In this paper, we develop parallel algorithms for sparse matrix- matrix multiplication with a focus on performance portability across different high performance computing architectures. The performance of these algorithms depend on the data structures used in them. We compare different types of accumulators in these algorithms and demonstrate the performance difference between these data structures. Furthermore, we develop a meta-algorithm, kkSpGEMM, to choose the right algorithm and data structure based on the characteristics of the problem. We show performance comparisons on three architectures and demonstrate the need for the community to develop two phase sparse matrix-matrix multiplication implementations for efficient reuse of the data structures involved.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Sparse Matrix-Matrix Multiplication on Multilevel Memory Architectures: Algorithms and Experiments

Architectures with multiple classes of memory media are becoming a common part of mainstream supercomputer deployments. So called multi-level memories offer differing characteristics for each memory component including variation in bandwidth, latency and capacity. This paper investigates the performance of sparse matrix multiplication kernels on two leading highperformance computing architectures — Intel's Knights Landing processor and NVIDIA's Pascal GPU. We describe a data placement method and a chunking-based algorithm for our kernels that exploits the existence of the multiple memory spaces in each hardware platform. We evaluate the performance of these methods w.r.t. standard algorithms using the auto-caching mechanisms Our results show that standard algorithms that exploit cache reuse performed as well as multi-memory-aware algorithms for architectures such as Ki\iLs where the memory subsystems have similar latencies. However, for architectures such as GPUS where memory subsystems differ significantly in both bandwidth and latency, multi-memory-aware methods are crucial for good performance. In addition, our new approaches permit the user to run problems that require larger capacities than the fastest memory of each compute node without depending on the software-managed cache mechanisms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

(Active) Learning on Groups of Data with Information-Theoretic Estimators

A wide range of machine learning problems, including astronomical inference about galaxy clusters, scene classification, parametric statistical inference, and predictions of public opinion, can be well-modeled as learning a function on (samples from) distributions. This project explores problems in learning such functions via kernel methods, particularly for large-scale problems. When learning from large numbers of distributions, the computation of typical methods scales between quadratically and cubically, and so they are not amenable to large datasets. We investigate the approach of approximate embeddings into Euclidean spaces such that inner products in the embedding space approximate kernel values between the source distributions. We first improve the understanding of the workhorse methods of random Fourier features: we show that of the two approaches in common usage, one is strictly superior. We then present a new embedding for a class of information-theoretic distribution distances, and evaluate it and existing embeddings on several real-world applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Confirmatory Defect Analyses of AGR-5/6/7 Fuel

The Advanced Gas Reactor (AGR) Fuel Development and Qualification Program has executed a series of experiments to test and qualify tristructural isotropic (TRISO) particle fuels for use in high-temperature gas-cooled reactors. The most recent irradiation experiments, AGR-5/6/7, are testing fuel that was fabricated in near production-scale equipment. There are three important defect fractions that must be characterized, using a deconsolidation-leach-burn-leach (DLBL) method, to better predict and understand fuel performance during irradiation. These are the dispersed uranium fraction (DUF), exposed kernel fraction (EKF), and silicon carbide defect fraction (SDF). The DLBL characterization data from analyses of the four compact batches, fabricated and characterized by the BWX Technologies Nuclear Operations Group (BWXT-NOG), showed unexpectedly higher values for all three defect fractions relative to the parent TRISO particle defect fractions. The DUF and SDF should not have changed significantly during compact fabrication and the apparent increase in the EKF, a metric for particle damage, was higher than anticipated for the compacts with 40% volumetric packing fraction (PF). Analytical results showed no net increase in the EKF for the 25% PF compacts. Compacts from one compact batch of each packing fraction were sent to Oak Ridge National Laboratory (ORNL), along with uncompacted tristructural isotropic (TRISO) particles, overcoated to a thickness targeting a 40% PF, for confirmatory analyses of the defect fractions and determination of the source(s) of damage. The ORNL results did not confirm the BWXT-NOG results for either the DUF or the SDF; the ORNL results showed no significant change in these defect fractions relative to the parent TRISO particle lot. The ORNL results did, however, confirm that a large increase in the exposed kernel fraction was found in the 40% PF compacts and that the 25% PF compacts sustained little if any damage. Data suggest that a large majority of the mechanical damage to the TRISO particles occurred in the overcoater when targeting the 40% PF. The analytical laboratories at both BWXT-NOG and ORNL had inconsistent outcomes on analyses of individual batches. Although the ORNL data is more consistent with the parent TRISO lot and expectations, the data set is too limited in size to justifiably reject suspect data from either laboratory at this time. It is recommended that an additional analysis be done to provide sufficient data for estimating the true defect fractions for interpreting the radionuclide release data during the AGR-5/6/7 irradiation experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

DARMA-Kokkos Data and Execution Interoperability WBS 2.3.1.04 Milestone 16 (ECP Milestone Report)

DARMA (Distributed Asynchronous Resilient Models for Applications) is a runtime library supporting the Sandia ATDM (Advanced Technology Development and Mitigation) program. The main application drivers fall within the ECP milestone 2.2.5.03 ADNN03-ASC ATDM SNL Application, which includes applications that require load balancing and asynchronous communication for high performance. The DARMA runtime infrastructure has been modified to be compatible with Kokkos/OpenMP parallelization within tasks, which is a critical requirement for high performance for the Sandia ATDM apps. DARMA development has occurred in parallel with a verification milestone for ATDM in FY18. For FY19, DARMA should impact ATDM by enabling dynamic load balancing and communication through only incremental changes to the existing verified MPI codes. DARMA can now support the intra-kernel thread parallelization in the parent MPI apps, allowing DARMA to be easily added without rewriting individual math kernels. The results presented here demonstrate the DARMA results for an MPI mini-app.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

ECP Milestone Deliverable Memo 2.3.1.04.15

The DARMA many-task framework provides asynchronous communication and load balancing functionality. This functionality is embedded in standard , modern C++ through the use of the template wrapper classes similar to futures. DARMA codes previously could not interoperate with MPI. A new C++ interface and extended semantics now allow quiescence of DARMA kernels and transfer of data ownership back into MPI, allowing 1) isolated DARMA kernels to be inserted in a larger MPI code or 2) reuse of MPI libraries like solvers within a DARMA application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Coupled Bison/Thermochimica Simulation of Hydride Formation in Zircalloy Cladding

The report describes implementation of the thermodynamics models for simulation of zirconium hydride formation in LWR fuel cladding. The current models for ZrH x formation are based on empirical rate models that must calibrated to materials and regimes of interest. The thermodynamic approach enables hydride formation calculations based on fundamental thermodynamics principles and material composition. Thermodynamic formulations and models were implemented in the Idaho National Laboratory fuel performance code Bison using Material, Kernel and AuxKernel methods. The results for the Material and Kernel implementation are shown in this report. The Material method implementation naturally fits the concept of modeling evolution of material state in the material models. Given the relatively high cost of thermodynamic computation, the advantage of the AuxKernel compared to Material implementation is the ability to control the execution and computational cost. The implemented formulations are illustrated on example problems which fit the experimental data and satisfy the computational requirements of conservation equations.

36 MATERIALS SCIENCE↗