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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

3D numerical simulation of the long range propagation of acoustical shock waves through a heterogeneous and moving medium

Many situations involve the propagation of acoustical shock waves through flows. Natural sources such as lightning, volcano explosions, or meteoroid atmospheric entries, emit loud, low frequency, and impulsive sound that is influenced by atmospheric wind and turbulence. The sonic boom produced by a supersonic aircraft and explosion noises are examples of intense anthropogenic sources in the atmosphere. The Buzz-Saw-Noise produced by turbo-engine fan blades rotating at supersonic speed also propagates in a fast flow within the engine nacelle. Simulating these situations is challenging, given the 3D nature of the problem, the long range propagation distances relative to the central wavelength, the strongly nonlinear behavior of shocks associated to a wide-band spectrum, and finally the key role of the flow motion. With this in view, the so-called FLHOWARD (acronym for FLow and Heterogeneous One-Way Approximation for Resolution of Diffraction) method is presented with three-dimensional applications. A scalar nonlinear wave equation is established in the framework of atmospheric applications, assuming weak heterogeneities and a slow wind. It takes into account diffraction, absorption and relaxation properties of the atmosphere, quadratic nonlinearities including weak shock waves, heterogeneities of the medium in sound speed and density, and presence of a flow (assuming a mean stratified wind and 3D turbulent ? flow fluctuations of smaller amplitude). This equation is solved in the framework of the one-way method. A split-step technique allows the splitting of the non-linear wave equation into simpler equations, each corresponding to a physical effect. Each sub-equation is solved using an analytical method if possible, and finite-differences otherwise. Nonlinear effects are solved in the time domain, and others in the frequency domain. Homogeneous diffraction is handled by means of the angular spectrum method. Ground is assumed perfectly flat and rigid. Due to the 3D aspect, the code was massively parallelized using the single program, multiple data paradigm with the Message Passing Interfaces (MPI) for distributed memory architectures. This allows us to handle problems in the order of a thousand billion mesh points in the four dimensions (3 dimensions of space plus time). The validity of the method has been thoroughly evaluated on many cases with known solutions: linear piston, scattering of plane wave by a heterogeneous sphere, propagation in a waveguide with a shear flow, scattering by a finite amplitude vortex and nonlinear propagation in a thermoviscous medium. This validation process allows for a detailed assessment of the advantages and limitations of the method. Finally, applications to atmospheric propagation of shock waves will be presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Assessing Government and Industry Roles to Accelerate Commercialization of Advanced Reactors and Supporting Fuel Cycles

Recent growth in private sector interest and investment in advanced reactor designs signals a new period in the greater than six decade pursuit of commercial nuclear technology. This nuclear entrepreneurship is primarily centered in the North America; meanwhile, national programs in China, France, India, Russia, and South Korea also feature active efforts to design, construct, operate and export advanced reactors .The business case for most private ventures calls for an aggressive commercialization timeline-tied to expectations for returns on investment. Finally, strategic energy portfolio projections and utility resource planning point to the 2030 - 2050 window as the period of greatest need for dispatchable, energy intensive, low-carbon generation options to address retirement of baseload capacity, increased penetration of renewables and economy-scale decarbonization. However, lead times for commercialization range from 30 to 50 years based on more traditional government-centric timelines. Fuel development and fuel cycle infrastructure deployment represent parallel timelines that directly influence the timeline for commercialization of many advanced reactor concepts. While multi-decade development periods appear to be commonplace for new nuclear projects, such timelines were not always the norm-three separate countries set out to develop civilian commercial power from fundamental nuclear principles, in just over a decade, on average. The US led light-water reactor (LWR) development in the 1950's, the UK pioneered a gas-cooled reactor (GCR) concept in the same time period, and Canada forged the path to commercializing the heavy-water reactor (HWR) starting in the mid-1950's and into the mid-1960's. The necessary fuel cycle facilities to support the commercial reactor design also did not appear suddenly, but were a collaborative effort between government and private partners. In this paper, the efforts of these three governments and their private industry partnerships in reactor and fuel cycle development are explored, and a select sample of representative milestones for each is presented, with the roles that each group played. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

BeeSwarm: Enabling Parallel Scaling Performance Measurement in Continuous Integration for HPC Applications

Testing is one of the most important steps in software development–it ensures the quality of software. Continuous Integration (CI) is a widely used testing standard that can report software quality to the developer in a timely manner during development progress. Performance, especially scalability, is another key factor for High Performance Computing (HPC) applications. There are many existing profiling and performance tools for HPC applications, but none of these are integrated into CI tools. In this work, we propose BeeSwarm, an HPC container based parallel scaling performance system that can be easily applied to the current CI test environments. BeeSwarm is mainly designed for HPC application developers who need to monitor how their applications can scale on different compute resources. We demonstrate BeeSwarm using a multi-physics HPC application with Travis CI, GitLab CI and GitHub Actions while using ChameleonCloud and Google Compute Engine as the compute backends. Finally, our results show that BeeSwarm can be used for scalability and performance testing of HPC applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Accelerated acquisition of tagged MRI for cardiac motion correction in simultaneous PET-MR: Phantom and patient studies

Purpose: Degradation of image quality caused by cardiac and respiratory motions hampers the diagnostic quality of cardiac PET. It has been shown that improved diagnostic accuracy of myocardial defect can be achieved by tagged MR (tMR) based PET motion correction using simultaneous PET-MR. However, one major hurdle for the adoption of tMR-based PET motion correction in the PET-MR routine is the long acquisition time needed for the collection of fully sampled tMR data. In this work, the authors propose an accelerated tMR acquisition strategy using parallel imaging and/or compressed sensing and assess the impact on the tMR-based motion corrected PET using phantom and patient data. Methods: Fully sampled tMR data were acquired simultaneously with PET list-mode data on two simultaneous PET-MR scanners for a cardiac phantom and a patient. Parallel imaging and compressed sensing were retrospectively performed by GRAPPA and kt-FOCUSS algorithms with various acceleration factors. Motion fields were estimated using nonrigid B-spline image registration from both the accelerated and fully sampled tMR images. The motion fields were incorporated into a motion corrected ordered subset expectation maximization reconstruction algorithm with motion-dependent attenuation correction. Results: Although tMR acceleration introduced image artifacts into the tMR images for both phantom and patient data, motion corrected PET images yielded similar image quality as those obtained using the fully sampled tMR images for low to moderate acceleration factors (<4). Quantitative analysis of myocardial defect contrast over ten independent noise realizations showed similar results. It was further observed that although the image quality of the motion corrected PET images deteriorates for high acceleration factors, the images were still superior to the images reconstructed without motion correction. Conclusions: Accelerated tMR images obtained with more than 4 times acceleration can still provide relatively accurate motion fields and yield tMR-based motion corrected PET images with similar image quality as those reconstructed using fully sampled tMR data. The reduction of tMR acquisition time makes it more compatible with routine clinical cardiac PET-MR studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Detoured flight direction responses along the southwest coast of Lake Erie by night-migrating birds

Abstract Migratory birds encounter the Great Lakes while moving through eastern North America toward breeding grounds to the North, which offers a good opportunity to study variation in migratory behavior as birds face a potentially influencing topographical feature. Using passive infrared technology, we documented the direction of relatively low-flying, nocturnal, mostly passerine migration in spring along the southern coast of Lake Erie’s western basin. We examined the extent to which spring migrants flew across Lake Erie as a continuation of the inland, northeasterly broad front migratory direction, as determined by weather radar and infrared observations, or displayed a tendency to deviate to more closely follow the direction of the coastline. We found that an estimated 62% of all low-flying migrants deviated their flight directions toward the coast of Lake Erie at 2 coastal sites, Cedar Point and Ottawa, which were characterized by northwest–southeast oriented coastlines. Migrants at a third coastal location, Maumee Bay, which has a more east–west oriented coastline, did not display similarly deviated flight directions. We found that even when winds were energetically favorable for a lake crossing, many migrants still routinely displayed deviated flight directions that approached paralleling the coastline. Further, the mean flight direction at one site, Ottawa, shifted more in the direction of the coastline as the night progressed, suggesting that time of night could influence the shift to a more coastal flight direction. The data indicate that the western basin of Lake Erie acts as a salient topographical feature influencing the flight directions of nocturnal migrants. The data further suggest that birds are making active decisions while in flight, based on current environmental and physiological conditions, about whether to continue to cross Lake Erie or take a coastal detour.

Zoology↗
DOE OSTI2017

Distributed memory parallel Markov random fields using graph partitioning

Markov random fields (MRF) based algorithms have attracted a large amount of interest in image analysis due to their ability to exploit contextual information about data. Image data generated by experimental facilities, though, continues to grow larger and more complex, making it more difficult to analyze in a reasonable amount of time. Applying image processing algorithms to large datasets requires alternative approaches to circumvent performance problems. Aiming to provide scientists with a new tool to recover valuable information from such datasets, we developed a general purpose distributed memory parallel MRF-based image analysis framework (MPI-PMRF). MPI-PMRF overcomes performance and memory limitations by distributing data and computations across processors. The proposed approach was successfully tested with synthetic and experimental datasets. Additionally, the performance of the MPI-PMRF framework is analyzed through a detailed scalability study. We show that a performance increase is obtained while maintaining an accuracy of the segmentation results higher than 98%. The contributions of this paper are: (a) development of a distributed memory MRF framework; (b) measurement of the performance increase of the proposed approach; (c) verification of segmentation accuracy in both synthetic and experimental, real-world datasets

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Sparse Symmetric Format for Tucker Decomposition

Tensor-based methods are receiving renewed attention in recent years due to their prevalence in diverse real-world applications. There is considerable literature on tensor representations and algorithms for tensor decompositions, both for dense and sparse tensors. Many applications in hypergraph analytics, machine learning, psychometry, and signal processing result in tensors that are both sparse and symmetric, making them an important class for further study. Similar to the critical Tensor Times Matrix chain operation (TTM c ) in general sparse tensors, the $\underline{S}$ parse $\underline{S}$ ymmetric $\underline{T}$ ensor $\underline{T}$ imes $\underline{S}$ ame $\underline{M}$ atrix $\underline{c}$ hain (S 3 TTM c ) operation is compute and memory intensive due to high tensor order and the associated factorial explosion in the number of non-zeros. We present the novel Compressed Sparse Symmetric (CSS) format for sparse symmetric tensors, along with an efficient parallel algorithm for the S 3 TTM c operation. We theoretically establish that S 3 TTM c on CSS achieves a better memory versus run-time trade-off compared to state-of-the-art implementations, and visualize the variation of the performance gap over the parameter space. We demonstrate experimental findings that confirm these results and achieve up to 2.72× speedup on synthetic and real datasets. The scaling of the algorithm on different test architectures is also showcased to highlight the effect of machine characteristics on algorithm performance.

42 ENGINEERING↗
DOE OSTI2017

Task-based Parallel Computation of the Density Matrix in Quantum-based Molecular Dynamics using Graph Partitioning

Quantum-based molecular dynamics (QMD) is a highly accurate and transferable method for material science simulations. However, the time scales and system sizes accessible to QMD are typically limited to picoseconds and a few hundred atoms. These constraints arise due to expensive self-consistent ground-state electronic structure calculations that can often scale cubically with the number of atoms. Linearly scaling methods depend on computing the density matrix P from the Hamiltonian matrix H by exploiting the sparsity in both matrices. The second-order spectral projection (SP2) algorithm is an O(N) algorithm that computes P with a sequence of 40 - 50 matrix-matrix multiplications. In this paper, we present task-based implementations of a recently developed data-parallel graph-based approach to the SP2 algorithm, G-SP2. We represent the density matrix P as an undirected graph and use graph partitioning techniques to divide the computation into smaller independent tasks. The partitions thus obtained are generally not of equal size and give rise to undesirable load imbalances in standard MPI-based implementations. This load-balancing challenge can be mitigated by dynamically scheduling parallel computations at runtime using task-based programming models. We develop task-based implementations of the data-parallel G-SP2 algorithm using both Intel's Concurrent Collections (CnC) as well as the Charm++ programming model and evaluate these implementations for future use. Scaling and performance results of our implementations are investigated for representative segments of QMD simulations for solvated protein systems containing more than 10,000 atoms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Efficient Parallel Sparse Symmetric Tucker Decomposition for High-Order Tensors

Tensor based methods are receiving renewed attention in recent years due to their prevalence in diverse real-world applications. There is considerable literature on tensor representations and algorithms for tensor decompositions, both for dense and sparse tensors. Many applications in hypergraph analytics, machine learning, psychometry, and signal processing result in tensors that are both sparse and symmetric, making it an important class for further study. Similar to the critical Tensor Times Matrix chain operation (TTMc) in general sparse tensors, the Sparse Symmetric Tensor Times Same Matrix chain (S3TTMc) operation is compute and memory intensive due to high tensor order and the associated factorial explosion in the number of non-zeros. In this work, we present a novel compressed storage format CSS for sparse symmetric tensors, along with an efficient parallel algorithm for the S3TTMc operation. We theoretically establish that S3TTMc on CSS achieves a better memory versus run-time trade-off compared to state-of-the-art implementations. We demonstrate experimental findings that confirm these results and achieve up to 2.9× speedup on synthetic and real datasets.

Shivakumar, Shruti↗
DOE OSTI2019

Highlights from the ATLAS experiment

This report provides an overview of the new results obtained by the ATLAS Collaboration at the LHC, which were presented at the Quark Matter 2018 conference. Furthermore these measurements were covered in 12 parallel talks, one flash talk and 11 posters. In this document, a discussion of results is grouped into four areas: electromagnetic interactions, jet quenching, quarkonia and heavy-flavour production, and collectivity in small and larger systems. Measurements from the xenon-xenon collisions based on a short run collected in October 2017 are reported for the first time.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Role of surface diffusion in formation of unique reactivity for graphite oxidation: Time-resolved measurements in a pulsed diffusion reactor

Quantification of oxidation kinetics is essential to develop graphitic materials for diverse applications: from refractories found in gas-cooled nuclear reactors to catalysts needed for chemical manufacturing. In this work, using well-defined highly oriented pyrolytic graphite, low-pressure isotopic transient experiments combined with controlled annealing periods, we resolve the role of surface diffusion and quantify oxidation kinetics with nanomole-precision. We observe an unexpected increase in reactivity following annealing which is explained by the role of surface diffusion increasing the probability for trapping mobile oxygen at more reactive edge sites. Here, the locus of adsorption and spillover to the basal plane is distinct from the trapping location creating a more active oxygen species. Isotopic products reflect the population dynamics of oxygen added at the edge and surface diffusion that relocates basal plane oxygen to more reactive edge sites. Since this process proceeds in parallel with direct oxidation reactions, it is not likely to be observed using steady-state or conventional ‘bulk’ characterization techniques. Our unique time-resolved non-equilibrium measurement in a well-defined transport regime, enables observation of three distinct behaviors: short-term deactivation due to the balance of rates in oxygen supply/product formation, reactivity increases due to surface diffusion and longer-term reactivity increase with oxygen accumulation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Time-discretization of a plasma-neutral MHD model with a semi-implicit leapfrog algorithm

The semi-implicit leapfrog time-discretization is a workhorse algorithm for initial-value MHD codes to bridge between vastly separated time scales. Inclusion of atomic interactions with neutrals breaks the functional structure of the MHD equations that exploited by the leapfrog. In this work, we address how to best integrate atomic physics into the semi-implicit leapfrog. Following the Crank-Nicolson method, one approach is to time-center the atomic interactions in the linear solver and use a Newton method to include the nonlinear contributions. Alternatively, another family of methods are based on operator-splitting the terms associated with the atomic interactions using a Strang-splitting technique. These methods naturally break equations into constituent ODE and PDE parts and preserve the structure exploited by the semi-implicit leapfrog. We study the accuracy and efficiency of these methods through a battery of 0D and 1D cases and show that a second-order-in-time Douglas-Rachford inspired coupling between the ODE and PDE advances is effective in reducing the time-discretization error to be comparable to that of Crank-Nicolson with Newton iteration of the nonlinear terms. Splitting ODE and PDE parts results in independent matrix solves for each field which reduces the computational cost considerably and provides parallelization over species relative to Crank-Nicolson.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Limited‐memory adaptive snapshot selection for proper orthogonal decomposition

Summary Reduced order models are useful for accelerating simulations in many‐query contexts, such as optimization, uncertainty quantification, and sensitivity analysis. However, offline training of reduced order models (ROMs) can have prohibitively expensive memory and floating‐point operation costs in high‐performance computing applications, where memory per core is limited. To overcome this limitation for proper orthogonal decomposition, we propose a novel adaptive selection method for snapshots in time that limits offline training costs by selecting snapshots according an error control mechanism similar to that found in adaptive time‐stepping ordinary differential equation solvers. The error estimator used in this work is related to theory bounding the approximation error in time of proper orthogonal decomposition‐based ROMs, and memory usage is minimized by computing the singular value decomposition using a single‐pass incremental algorithm. Results for a viscous Burgers' test problem demonstrate convergence in the limit as the algorithm error tolerances go to zero; in this limit, the full‐order model is recovered to within discretization error. A parallel version of the resulting method can be used on supercomputers to generate proper orthogonal decomposition‐based ROMs, or as a subroutine within hyperreduction algorithms that require taking snapshots in time, or within greedy algorithms for sampling parameter space. Copyright © 2016 John Wiley & Sons, Ltd.

Oxberry, Geoffrey M.↗
DOE OSTI2017

Picosecond phase-velocity dispersion of hypersonic phonons imaged with ultrafast electron microscopy

We describe the direct imaging—with four-dimensional ultrafast electron microscopy—of the emergence, evolution, dispersion, and decay of photoexcited, hypersonic coherent acoustic phonons in nanoscale germanium wedges. Coherent strain waves generated via ultrafast in situ photoexcitation were imaged propagating with initial phase velocities of up to 35 km/s across discrete micrometer-scale crystal regions. We then observe that, while each wave front travels at a constant velocity, the entire wave train evolves with a time-varying phase-velocity dispersion, displaying a single-exponential decay to the longitudinal speed of sound (5 km/s) and with a mean lifetime of 280 ps. We also find that the wave trains propagate along a single in-plane direction oriented parallel to striations introduced during specimen preparation, independent of crystallographic direction. Elastic-plate modeling indicates the dynamics arise from excitation of a single, symmetric (dilatational) guided acoustic mode. Further, by precisely determining the experiment time-zero position with a plasma-lensing method, we find that wave-front emergence occurs approximately 100 ps after femtosecond photoexcitation, which matches well with Auger recombination times in germanium. We conclude by discussing the similarities between the imaged hypersonic strain-wave dynamics and electron/hole plasma-wave dynamics in strongly photoexcited semiconductors.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Profiling the BLAST bioinformatics application for load balancing on high-performance computing clusters

Abstract Background The Basic Local Alignment Search Tool (BLAST) is a suite of commonly used algorithms for identifying matches between biological sequences. The user supplies a database file and query file of sequences for BLAST to find identical sequences between the two. The typical millions of database and query sequences make BLAST computationally challenging but also well suited for parallelization on high-performance computing clusters. The efficacy of parallelization depends on the data partitioning, where the optimal data partitioning relies on an accurate performance model. In previous studies, a BLAST job was sped up by 27 times by partitioning the database and query among thousands of processor nodes. However, the optimality of the partitioning method was not studied. Unlike BLAST performance models proposed in the literature that usually have problem size and hardware configuration as the only variables, the execution time of a BLAST job is a function of database size, query size, and hardware capability. In this work, the nucleotide BLAST application BLASTN was profiled using three methods: shell-level profiling with the Unix “time” command, code-level profiling with the built-in “profiler” module, and system-level profiling with the Unix “gprof” program. The runtimes were measured for six node types, using six different database files and 15 query files, on a heterogeneous HPC cluster with 500+ nodes. The empirical measurement data were fitted with quadratic functions to develop performance models that were used to guide the data parallelization for BLASTN jobs. Results Profiling results showed that BLASTN contains more than 34,500 different functions, but a single function, RunMTBySplitDB, takes 99.12% of the total runtime. Among its 53 child functions, five core functions were identified to make up 92.12% of the overall BLASTN runtime. Based on the performance models, static load balancing algorithms can be applied to the BLASTN input data to minimize the runtime of the longest job on an HPC cluster. Four test cases being run on homogeneous and heterogeneous clusters were tested. Experiment results showed that the runtime can be reduced by 81% on a homogeneous cluster and by 20% on a heterogeneous cluster by re-distributing the workload. Discussion Optimal data partitioning can improve BLASTN’s overall runtime 5.4-fold in comparison with dividing the database and query into the same number of fragments. The proposed methodology can be used in the other applications in the BLAST+ suite or any other application as long as source code is available.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Visualizing Hierarchical Performance Profiles of Parallel Codes Using CallFlow

Calling context trees (CCTs) couple performance metrics with call paths, helping understand the execution and performance of parallel programs. To identify performance bottlenecks, programmers and performance analysts visually explore CCTs to form and validate hypotheses regarding degraded performance. However, due to the complexity of parallel programs, existing visual representations do not scale to applications running on a large number of processors. In this work, we present CallFlow, an interactive visual analysis tool that provides a high-level overview of CCTs together with semantic refinement operations to progressively explore CCTs. Using a flow-based metaphor, we visualize a CCT by treating execution time as a resource spent during the call chain, and demonstrate the effectiveness of our design with case studies on large-scale, production simulation codes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Streaming Matching and Edge Cover in Practice

Graph algorithms with polynomial space and time requirements often become infeasible for massive graphs with billions of edges or more. State-of-the-art approaches therefore employ approximate serial, parallel, and distributed algorithms to tackle these challenges. However, such approaches require storing the entire graph in memory and thus need access to costly computing resources such as clusters and supercomputers. In this paper, we present practical streaming approaches for solving massive graph problems using limited memory for two prototypical graph problems: maximum weighted matching and minimum weighted edge cover. For matching, we conduct a thorough computational study on two of the semi-streaming algorithms including a recent breakthrough result that achieves a $1/(2+\varepsilon)$-approximation of the weight while using $O( n \log W /\epsilon)$ memory (here $n$ is the number of vertices and $W$ is the maximum edge weight), designed by Paz and Schwartzman [SODA, 2017]. Empirically, we show that the semi-streaming algorithms produce matchings whose weight is close to the best $1/2$-approximate offline algorithm while requiring less time and an order-of-magnitude less memory. For minimum weighted edge cover, we develop three novel semi-streaming algorithms. Two of these algorithms require a single pass through the input graph, require $O(n \log n)$ memory, and provide a 2-approximation guarantee on the objective. We also leverage a relationship between approximate maximum weighted matching and approximate minimum weighted edge cover to develop a two-pass $3/2+\epsilon$-approximate algorithm with the memory requirement of Paz and Schwartzman's semi-streaming matching algorithm. These streaming approaches are compared against the state-of-the-art 3/2-approximate offline algorithm. The semi-streaming matching and the novel edge cover algorithms proposed in this paper can process graphs with several billions of edges in under 30 minutes using 6 GB of memory, which is at least an order of magnitude improvement from the offline (non-streaming) algorithms. For the largest graph, the best alternative offline parallel approximation algorithm (GPA+ROMA) could not finish in three hours even while employing hundreds of processors and 1 TB of memory. We also demonstrate an application of the semi-streaming algorithm by computing a matching using linearly bounded memory on item intersection graphs derived from three machine learning datasets, whereas the existing offline algorithms could not complete on one of these datasets since their memory requirements exceeded 1TB.

Ferdous, S M.↗
DOE OSTI2020

Sodium Exposure Tests of A709 Steel (FY2020 Progress Report)

Sodium exposure tests were conducted on the first commercial heat, H58776 of A709 steel. Six different processing and heat treatment conditions were investigated, including three processing conditions, namely, Argon-Oxygen-Decarburization (AOD), Electro-slag Remelting (ESR), and Electro-slag Remelting with subsequent homogenization (HOMO), and two heat treatment conditions, i.e. solution annealing at 1100°C (SA1100°C) or 1150°C (SA1150°C). Specimens of AOD-SA1100°C, AOD-SA1150°C, ESR-SA1100°C, ESR-SA1150°C, HOMO-SA1100°C, and HOMO-SA1150°C were tested in sodium at 650°C and for times up to 10,152 h. Specimens in the AOD-SA1100°C and AOD-SA1150°C conditions were also tested in sodium at 550 and 600°C. Parallel thermal aging experiments were carried out for comparison with sodium exposure tests to separate the thermal and sodium effects. It was found that A709 H58776 generally showed a weight loss after sodium exposures at 650°C except a few data points of the ESR-SA1100°C specimens. The corrosion rate showed large variations in the initial stage and decreased with increasing exposure time. Long-term exposure tests are needed to determine its steady-state corrosion rate. The AOD-SA1100°C and HOMO-SA1100°C specimens showed similar tensile responses after thermal or sodium exposures at 650°C. The yield stress increased, the ultimate tensile strength decreased, and the uniform and total elongations were reduced after thermal or sodium exposures. A longer exposure time had a minimal effect on the tensile strength but further reduced the tensile ductility. The sodium-exposed specimens had higher tensile strength than the thermally-aged specimens. In contrast, the ESR-SA1100°C specimens showed an increase in the yield stress and the ultimate tensile strength after thermal or sodium exposures at 650°C and ~10,000 h. The AOD-SA1150°C and ESR-SA1150°C specimens showed similar tensile behavior after thermal or sodium exposures at 650°C.Thermal or sodium exposures at 650°C increased the yield stress, decreased the ultimate tensile strength, and reduced uniform and total elongations. There were minimal differences in tensile properties between the sodium-exposed and thermally-aged specimens after an ~3000 h exposure. After an exposure for ~10,000 h the sodium-exposed specimens showed higher yield stress and ultimate tensile strength and lower uniform and total elongations than the thermally-aged specimens. For the HOMO-SA1150°C specimens, thermal or sodium exposures at 650°C significantly increased the yield stress but had a minimal effect on the ultimate tensile strength. Both uniform and total elongations were significantly reduced at an exposure time of ~3,000 h, and they were further reduced after an exposure of ~10,000 h. The sodium-exposed specimens had lower tensile ductility than the thermally-aged specimens. Before exposure, the stress-strain curves of the specimens in all six processing-heat treatment conditions showed serrations indicating the dynamic aging effect at 650°C. Thermal aging or sodium exposures at 650°C after ~10,000 h completely removed the serrations of the flow curves in A709 H58776, indicating strong precipitation during thermal or sodium exposures. Longer-term sodium exposure tests are needed to determine the steady-state corrosion rates in sodium for A709 H58776 and fully understand the influence of sodium exposures on its mechanical performance.

36 MATERIALS SCIENCE↗