Search NASA⌕ Search

SEARCH · Search NASA

Results for “parallel, scaling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

ParFlow Sand Tank: A tool for groundwater exploration

The ParFlow Sand Tank model is an open source application designed to allow users to interactively simulate and visualize groundwater movement through the subsurface. The app is designed for both research and education; teaching hydrogeology concepts and making it easy explore and run sophisticated groundwater simulations. Our goal is to support increased accessibility and usability of research grade hydrology tools for research and teaching. The Sand Tank application simulates groundwater and surface water fluxes as well as contaminant transport in real time using the integrated physical hydrology model ParFlow (Kollet & Maxwell, 2006; Maxwell & Miller, 2005; Osei-Kuffuor et al., 2014) and the particle tracking code EcoSlim (Maxwell et al., 2019). ParFlow is a numerical hydrology model that simulates spatially distributed groundwater and surface water flow. It is a well established research tool with more than 90 publications documenting its development use to advance our understanding of groundwater dynamics and groundwater surface water interactions from the hillslope to the continental scale e.g. (Condon et al., 2020; Condon & Maxwell, 2019; Maxwell & Condon, 2016). It is designed for efficient parallel computation and has been run on many platforms spanning from laptops to supercomputers. However, one of the challenges of ParFlow is that it requires significant training and hydrologic expertise to develop simulations. The Sand Tank application makes this model accessible to anyone for education and exploration. Our application uses ParFlow for its simulation backend and ParaView for the data loading and processing. The communication infrastructure relies on the ParaViewWeb framework. We use model templates deployed in Docker images to setup the Sand Tank framework. Users can build the application locally or interact with it through our web deployment. When interacting with a template users can interactively change model parameters like subsurface processes or pump/inject water into the subsurface and watch the system respond to their changes in real time as the simulation runs. Additionally, our template setup will allow more advanced users to build custom templates of increasing complexity for both research and educational purposes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Miniaturized Air-to-Refrigerant Heat Exchangers

Air-to-refrigerant Heat eXchangers (HX) are an essential component of Heating, Ventilation, Air-Conditioning, and Refrigeration (HVAC&R) systems, serving as the main heat transfer component. The major limiting factor to HX performance is the large airside thermal resistance. Recent literature aims at improving heat transfer performance by utilizing enhancement methods such as fins and small tube diameters; this has lead to almost exhaustive research on the microchannel HX (MCHX). The objective of this project is to develop a miniaturized air-to-refrigerant HX with at least 20% reduction in volume, material volume, and approach temperature compared to current state-of-the-art multiport flat tube designs and also be capable of production within five years. Moreover, the proposed HX’s are expected to have good water drainage and should succeed in both evaporator and condenser applications. The project leveraged Parallel-Parametrized Computational Fluid Dynamics (PPCFD) and Approximation-Assisted Optimization (AAO) techniques to perform multi-scale analysis and shape optimization with the intent of developing novel HX designs whose thermal-hydraulic performance exceeds that of state-of-the-art MCHX. Nine heat exchanger geometries were initially chosen for detailed analysis, selected from 35+ geometries which were identified in previous work at the University of Maryland, College Park. The newly developed optimization framework was exercised for three design optimization problems: (DP I) 1.0kW radiator, (DP II) 10kW radiator and (DP III) 10kW two-phase HX. DP I consisted of the design and optimization of 1.0kW air-to-water HX’s which exceeded the project requirements of 20% volume/material reduction and 20% better performance. Two prototypes for the 1.0kW HX were prototyped, tested and validated using newly-designed airside and refrigerant side test facilities. DP II, a scaled version DP I for 10kW air-to-water HX applications, also yielded optimized HX designs which met project requirements. Attempts to prototype a 10kW have presented unique manufacturing challenges, especially regarding tube blockages and structural stability. DP III comprised optimizing two-phase HX’s for a 3.0Ton capacity in a heat pump / air-conditioning unit for cooling mode application using R410A as the working fluid. The HX’s theoretically address the project requirements. System-level analysis showed the HX’s achieved up to 15% improvement in COP while also reducing overall unit charge by 30-40%. The project methodology was capable of developing HX’s which can outperform current state-of-the-art MCHX by at least 20% reduction in volume, material volume, and approach temperature. Additionally, the capability for optimization using refrigerant charge as an objective function was developed. The five-year manufacturing feasibility of the proposed HX’s was shown to have a good outlook. Successful prototyping through both conventional manufacturing methods and next generation methods such as additive manufacturing was achieved.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Combining Experiments and Simulations of Extraction Kinetics and Thermodynamics in Advanced Separation Processes for Used Nuclear Fuel

This 3-year project was a collaboration between University of California Irvine (UC Irvine), Pacific Northwest National Laboratory (PNNL), Idaho National Laboratory (INL), Argonne National Laboratory (ANL) and with an international collaborator at ForschungZentrum Jülich (FZJ). The project was led from UC Irvine under the direction of Profs. Mikael Nilsson and Hung Nguyen. The leads at PNNL, INL, ANL and FZJ were Dr. Liem Dang, Dr. Peter Zalupski, Dr. Nathaniel Hoyt and Dr. Giuseppe Modolo, respectively. Involved in this project at UC Irvine were three full time PhD graduate students, Tro Babikian, Ted Yoo, and Quynh Vo, and one MS student, Alba Font Bosch. The overall objective of this project was to study how the kinetics and thermodynamics of metal ion extraction can be described by molecular dynamic (MD) simulations and how the simulations can be validated by experimental data. Furthermore, the project includes the applied separation by testing the extraction systems in a single stage annular centrifugal contactor and coupling the experimental data with computational fluid dynamic (CFD) simulations. Specific objectives of the proposed research were: Study and establish a rigorous connection between MD simulations based on polarizable force fields and extraction thermodynamic and kinetic data. Compare and validate CFD simulations of extraction processes for An/Ln separation using different sizes (and types) of annular centrifugal contactors. Provide a theoretical/simulation and experimental base for scale-up of batch-wise extraction to continuous contactors. We approached objective 1 and 2 in parallel. For objective 1 we started by studying a well established extraction system with a relatively simple extraction mechanism, namely tributyl phosphate. What we found was that well optimized simulations can inform experiments and new information on TBP behavior was presented in this project, as well be discussed below. The second objective proved a larger challenge and most of the efforts were devoted to experimental studies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Hybrid Encapsulated Ionic Liquids for Post-Combustion Carbon Dioxide (CO 2 ) Capture

It is increasingly clear that carbon dioxide (CO 2 ) capture and sequestration (CCS) must play a critical role in curbing worldwide CO 2 emissions to the atmosphere. Previously, we have developed ionic liquids (ILs) and phase change ionic liquids (PCILs) for post-combustion CO 2 capture. In this project, we synthesized and tested 19 ILs and PCILs and chose one of each for further development. The IL selected for further development was triethyl(octyl)phosphonium 2-cyanopyrrolide ([P 2228 ][2CNPyr]), which has the same anion but a different cation, than used in our previous work. The new cation imparts a lower viscosity than the prior cation. The PCIL selected for further development was tetraethylphosphonium benzimidazolide ([P 2222 ][BnIm]), which was developed in an Advanced Research Projects Agency-Energy (ARPA-E) project. Although we made numerous other candidates, none were better than this original PCIL. Here we showed that the CO 2 absorption by the IL and the PCIL was completely reversible, even when water was present. We determined and quantified the additional chemistry, involving the formation of bicarbonate, when water is present. The IL and PCIL were encapsulated in silicone shells using a microfluidic device. Compatibility between the IL/PCIL and the polymer, viscosity, and surface tension issues, getting sufficiently high IL/PCIL loading and leakage (likely from insufficient cross-linking), were serious challenges. Small quantities (~ 1 g) of microcapsules with good integrity of both the IL and the PCIL were produced. The CO 2 uptake by these capsules was the same as for the free IL and PCIL and the capacity of the capsules decreased only slightly even after five absorption and desorption cycles. As expected, the IL and PCIL (and subsequently the encapsulated IL and PCIL) reacted readily with SO 2 and NO, so, like aqueous amine absorbents, the CO 2 capture unit would have to be located downstream of the flue gas desulfurization and other gas treatment units. Large samples (~70 g and 100 g) of encapsulated PCIL were produced in a parallel microfluidic device and in an in-air device. These capsules were tested in a Laboratory Scale Unit (LSU) to demonstrate uptake capacity in a fluidized bed. We also used the LSU to determine recyclability and mass transfer coefficients. Unfortunately, equivalent experiments with the IL were not possible due to difficulties with producing large samples of the encapsulated IL. This IL encapsulation “scale-up” problem was not solved during the course of this project. Nonetheless, using the PCIL microcapsules we demonstrated that, as expected, the mass transfer is internally controlled. In concert with a new rate-based model of the fluidized bed, we determined that the productivity is increased by a factor of 4.75 in the microcapsule fluidized bed absorber compared to a conventional liquid-gas packed bed absorber. The initial technoeconomic model shows that the capital cost for the microcapsule IL continuous fluidized bed process is similar to that of an aqueous amine process (specifically, the Econamine FG Plus technology). However, the stripping heat requirements are about 35% less for the model IL microcapsule case compared to the monoethanolamine (MEA) case. Thus, encapsulated ILs/PCILs in a continuous fluidized bed absorber for post-combustion CO 2 capture are a significant improvement over the free IL/PCIL case and represent a major reduction in the parasitic energy requirements compared to aqueous amine process.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Hybrid Solar System (Final Scientific/Technical Report)

GTI Energy (GTI) teamed with the University of California at Merced (UCM) to scaleup the hybrid solar system (HSS) technology for demonstrating its performance at the US Gypsum (USG) plant in Plaster City, California. The technology integrates two-stage concentrating solar collector with matching particle thermal transport and storage (TSS) system to deliver cost-effective, and on-demand distributed high temperature industrial process heat up to 600°C with solar thermal, in this case to a gypsum kettle, to reduce its fuel use and carbon footprint. Current solar technologies, which reach these temperatures, are not distributable (towers) or cost-effective (dish). The research team developed a conceptual system design for host site retrofit, including preliminary heat balance, process flow diagram, particle to process heat exchanger and equipment placements at the site. Subsequently, parallel efforts were carried out at UCM to design, build and test a 12 m long commercial scale prototype concentrating thermal-only collector system and at GTI to design, build and test a matching 650°C capable particle TTS system. The nominal 50 kWth collector consists of a parabolic trough and three 4 m long two-stage receivers in series. Prior to on-sun testing, a 4 m long receiver was fabricated and successfully tested at 650 °C in a laboratory setting for 100 hrs of continuous operation showing less than 15% radiation loss. A 7 m wide x 17 m long parabolic trough was then installed at UCM for on-sun testing of the 12 m long receiver, and concurrently several 4 m long receivers were built. The optics of the parabolic trough were calibrated, and on-sun test were carried out on 12 m long receivers. During tests, the intense solar radiation (53x) caused the absorber tubes in the receivers to bend, reducing the overall optical efficiency. To address the bending issue, a self-consistent algorithm that includes ray tracing, thermal and deformation models was developed to perform thermal stress analysis on absorbers for parabolic solar collectors. Results obtained with this algorithm showed a dramatic rise in deformation as absorber tube length increases. A combined efficiency parameter that includes the occluded area for the mounts was developed to obtain an optimized tube length obtained. Based on the results, a length of 2.7 m for the absorber + 0.2 m for the coupler was chosen to minimize any bending and optimize optical efficiency while maintaining ease of mounting. The associated particle TTS system was designed, built and successfully tested at GTI. It includes storage, receiving and lock hoppers and piping that simulates the transfer of captured solar energy to an actual industrial furnace. Tests over 77 charge-discharge cycles demonstrated <2% particle degradation, with no problematic particle accumulations and no flow interruptions. The piping pressure drop was about 5 psi. The team also worked with Stanley Consultants (Stanley) to prepare conceptual and preliminary engineering packages to facilitate follow-on development and commercialization efforts. These include process and instrumentation diagram’s (P&ID’s), general arrangements, electrical one-line, project definitions document, equipment data sheets, schedule, and construction cost estimate for 2 MWth system. Updated HSS technology commercialization and customer engagement plans and detailed costs and evaluated market trade-offs and manufacturing.

03 NATURAL GAS↗
DOE OSTI2017

Electron–Ion Intensity Dropouts in Gradual Solar Energetic Particle Events during Solar Cycle 23

Since the field-line mixing model of Giacalone et al. suggests that ion dropouts cannot happen in the “gradual” solar energetic particle (SEP) event because of the large size of the particle source region in the event, the observational evidence of ion dropouts in the gradual SEP event should challenge the model. We have searched for the presence of ion dropouts in the gradual SEP event during solar cycle 23. From 10 SEP events the synchronized occurrence of ion and electron dropouts is identified in 12 periods. Our main observational facts, including the mean width of electron–ion dropout periods being consistent with the solar wind correlation scale, during the dropout period the dominance of the slab turbulence component and the enhanced turbulence power parallel to the mean magnetic field, and the ion gyroradius dependence of the edge steepness in dropout periods, are all in support of the solar wind turbulence origin of dropout events. Also, our observation indicates that a wide longitude distribution of SEP events could be due to the increase of slab turbulence fraction with the increased longitude distance from the flare-associated active region.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Energetic particle loss mechanisms in reactor-scale equilibria close to quasisymmetry

Abstract Collisionless physics primarily determines the transport of fusion-born alpha particles in 3D equilibria. Several transport mechanisms have been implicated in stellarator configurations, including stochastic diffusion due to class transitions, ripple trapping, and banana drift-convective orbits. Given the guiding center dynamics in a set of six quasihelical and quasiaxisymmetric equilibria, we perform a classification of trapping states and transport mechanisms. In addition to banana drift convection and ripple transport, we observe substantial non-conservation of the parallel adiabatic invariant which can cause losses through diffusive banana tip motion. Furthermore, many lost trajectories undergo transitions between trapping classes on longer time scales, either with periodic or irregular behavior. We discuss possible optimization strategies for each of the relevant transport mechanisms. We perform a comparison between fast ion losses and metrics for the prevalence of mechanisms such as banana-drift convection (Velasco et al 2021 Nucl. Fusion 61 116059), transitioning orbits, and wide orbit widths. Quasihelical configurations are found to have natural protection against ripple-trapping and diffusive banana tip motion leading to a reduction in prompt losses.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Violation of Field Line Conservation and Associated Spatial Scales in Particle-in-Cell Simulations and MMS Data

For the first time, space flight technology exists to detect, in situ, violation of magnetic field line conservation. The violation of magnetic line conservation on scales smaller than the system size is a necessary and sufficient condition for finite magnetic field reconnection. We demonstrate that violation of line conservation produces a detectable, structured signature both in particle-in-cell simulations of reconnection and in data from the Magnetospheric Multi-Scale mission. In particle-in-cell simulations of asymmetric reconnection, the quantity—which we call M—that identifies this violation achieves significant values in electron skin depth-scale layers that extend away from the separator, with higher values emerging on the low-density, high-magnetic-field side of the current sheet. At the separator, M owes largely to perpendicular gradients in the parallel electric field, while it attains its highest values away from the separator in dispersed, layered structures associated with gradients in the perpendicular nonideal electric field and electron transport. Sub-ion scale bipolar forms of the quantity also appear further from the separator. In two MMS burst data intervals detecting the electron diffusion region, we find that M exceeds measurement uncertainties both at the separator and near the separatrices. One interval has highly sheared reconnecting fields and the other a stronger guide field. For one event, we determine the location and scale of M and the inner electron diffusion region relative to electron outflows and the magnetic separatrices. The measure can therefore serve as a potent diagnostic for magnetic reconnection in space measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Advancing specialized biofoundries via automated adaptive laboratory evolution

Adaptive laboratory evolution (ALE) is a powerful strategy for improving microbial phenotypes by harnessing natural selection under defined environmental conditions. Through applying selection regimes, beneficial mutations accumulate, enabling the generation of strains with enhanced properties. However, conventional ALE is labor-intensive and difficult to scale, limiting reproducibility and broader discovery of evolutionary principles. Recent advances in robotics, automation, and computational infrastructure are transforming ALE into a scalable, data-rich experimental paradigm. Automated platforms enable standardized and complex protocols, real-time monitoring, and highly parallel evolution campaigns, improving consistency while generating longitudinal datasets that reveal convergent adaptive mechanisms. Here, we discuss the role of specialized biofoundries in advancing automated ALE and enabling large-scale evolutionary engineering. We review major automated ALE formats and outline key design principles for effective ALE biofoundries, highlighting how automated ALE can support autonomous experimentation and AI-guided strain engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The Astronomy Commons Platform: A Deployable Cloud-based Analysis Platform for Astronomy

Abstract We present a scalable, cloud-based science platform solution designed to enable next-to-the-data analyses of terabyte-scale astronomical tabular data sets. The presented platform is built on Amazon Web Services (over Kubernetes and S3 abstraction layers), utilizes Apache Spark and the Astronomy eXtensions for Spark for parallel data analysis and manipulation, and provides the familiar JupyterHub web-accessible front end for user access. We outline the architecture of the analysis platform, provide implementation details and rationale for (and against) technology choices, verify scalability through strong and weak scaling tests, and demonstrate usability through an example science analysis of data from the Zwicky Transient Facility’s 1Bn+ light-curve catalog. Furthermore, we show how this system enables an end user to iteratively build analyses (in Python) that transparently scale processing with no need for end-user interaction. The system is designed to be deployable by astronomers with moderate cloud engineering knowledge, or (ideally) IT groups. Over the past 3 yr, it has been utilized to build science platforms for the DiRAC Institute, the ZTF partnership, the LSST Solar System Science Collaboration, and the LSST Interdisciplinary Network for Collaboration and Computing, as well as for numerous short-term events (with over 100 simultaneous users). In a live demo instance, the deployment scripts, source code, and cost calculators are accessible. 4 4 http://hub.astronomycommons.org/

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Extreme Scale De Novo Metagenome Assembly

Metagenome assembly is the process of transforming a set of short, overlapping, and potentially erroneous DNA segments from environmental samples into the accurate representation of the underlying microbiomes's genomes. State-of-the-art tools require big shared memory machines and cannot handle contemporary metagenome datasets that exceed Terabytes in size. In this paper, we introduce the MetaHipMer pipeline, a high-quality and high-performance metagenome assembler that employs an iterative de Bruijn graph approach. MetaHipMer leverages a specialized scaffolding algorithm that produces long scaffolds and accommodates the idiosyncrasies of metagenomes. MetaHipMer is end-to-end parallelized using the Unified Parallel C language and therefore can run seamlessly on shared and distributed-memory systems. Experimental results show that MetaHipMer matches or outperforms the state-of-the-art tools in terms of accuracy. Ultimately, MetaHipMer scales efficiently to large concurrencies and is able to assemble previously intractable grand challenge metagenomes. We demonstrate the unprecedented capability of MetaHipMer by computing the first full assembly of the Twitchell Wetlands dataset, consisting of 7.5 billion reads - size 2.6 TBytes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Implementing a neural network interatomic model with performance portability for emerging exascale architectures

The two main thrusts of computational science are increasingly accurate predictions and faster calculations; to this end, the zeitgeist in molecular dynamics (MD) simulations is pursuing machine learned and data driven interatomic models, e.g. neural network potentials, and novel hardware architectures, e.g. GPUs. Current implementations of neural network potentials are orders of magnitude slower than traditional interatomic models and while looming exascale computing offers the ability to run large, accurate simulations with these models, achieving portable performance for MD with new and varied exascale hardware requires rethinking traditional algorithms, using novel data structures, and library solutions. We re-implement a neural network interatomic model in CabanaMD, an MD proxy application, built on libraries developed for performance portability. Our implementation shows significantly improved thread scaling in this complex kernel as compared to a current LAMMPS implementation, across both strong and weak scaling. Our single-source solution enables simulations up to 20 million atoms on a single CPU node and 4 million atoms with improved performance on a single GPU. Furthermore, we also explore parallelism and data layout choices (using flexible data structures called AoSoAs) and their effect on performance, seeing up to ~50% and ~5% improvements in performance on a GPU by choosing the right level of parallelism and data layout respectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Toward Large-Scale Image Segmentation on Summit

Semantic segmentation of images is an important computer vision task that emerges in a variety of application domains such as medical imaging, robotic vision and autonomous vehicles to name a few. While these domain-specific image analysis tasks involve relatively small image sizes (~ 10 2 × 10 2 ), there are many applications that need to train machine learning models on image data with extents that are orders of magnitude larger (~10 4 × 10 4 ). Training deep neural network (DNN) models on large extent images is extremely memory-intensive and often exceeds the memory limitations of a single graphical processing unit, a hardware accelerator of choice for computer vision workloads. Here, an efficient, sample parallel approach to train U-Net models on large extent image data sets is presented. Its advantages and limitations are analyzed and near-linear strong-scaling speedup demonstrated on 256 nodes (1536 GPUs) of the Summit supercomputer. Using a single node of the Summit supercomputer, an early evaluation of a recently released model parallel framework called GPipe is demonstrated to deliver ~ 2X speedup in executing a U-Net model with an order of magnitude larger number of trainable parameters than reported before. Performance bottlenecks for pipelined training of U-Net models are identified and mitigation strategies to improve the speedups are discussed. Together, these results open up the possibility of combining both approaches into a unified scalable pipelined and data parallel algorithm to efficiently train U-Net models with very large receptive fields on data sets of ultra-large extent images.

Seal, Sudip↗
DOE OSTI2021

Proactive Operations and Investment Planning via Stochastic Optimization to Enhance Power Systems’ Extreme Weather Resilience

We present scalable stochastic optimization approaches for improving power systems’ resilience to extreme weather events. We consider both proactive redispatch and transmission line hardening as alternatives for mitigating expected load shed due to extreme weather, resulting in large-scale stochastic linear programs (LPs) and mixed-integer linear programs (MILPs). We solve these stochastic optimization problems with progressive hedging (PH), a parallel, scenario-based decomposition algorithm. Our computational experiments indicate that our proposed method for enhancing power system resilience can provide high-quality solutions efficiently. With up to 128 scenarios on a 2,000-bus network, the operations (redispatch) and investment (hardening) resilience problems can be solved in approximately 6 min and 2 h of wall-clock time, respectively. Additionally, we solve the investment problems with up to 512 scenarios, demonstrating that the approach scales very well with the number of scenarios. Moreover, the method produces high quality solutions that result in statistically significant reductions in expected load shed. Our proposed approach can be augmented to incorporate a variety of other operational and investment resilience strategies, or a combination of such strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

XScan: An Integrated Tool for Understanding Open Source Community-Based Scientific Code

Many scientific communities have adopted community-based models that integrate multiple components to simulate whole system dynamics. The community software projects’ complexity, stems from the integration of multiple individual software components that were developed under different application requirements and various machine architectures, has become a challenge for effective software system understanding and continuous software development. The paper presents an integrated software toolkit called X-ray Software Scanner (in abbreviation, XScan) for a better understanding of large-scale community-based scientific codes. Our software tool provides support to quickly summarize the overall information of scientific codes, including the number of lines of code, programming languages, external library dependencies, as well as architecture-dependent parallel software features. The XScan toolkit also realizes a static software analysis component to collect detailed structural information and provides an interactive visualization and analysis of the functions. We use a large-scale community-based Earth System Model to demonstrate the workflow, functions and visualization of the toolkit. We also discuss the application of advanced graph analytics techniques to assist software modular design and component refactoring.

Zheng, Weijian↗
DOE OSTI2017

Shock-driven transition to turbulence: Emergence of power-law scaling

Here, we consider two cases of interaction between a planar shock and a cylindrical density interface. In the first case (planar normal shock), the axis of the gas cylinder is parallel to the shock front and baroclinic vorticity deposited by the shock is predominantly two dimensional (directed along the axis of the cylinder). In the second case, the cylinder is tilted, resulting in an oblique shock interaction and a fully-three-dimensional shock-induced vorticity field. Furthermore, the statistical properties of the flow for both cases are analyzed based on images from two orthogonal visualization planes, using structure functions of the intensity maps of fluorescent tracer premixed with heavy gas. And at later times, these structure functions exhibit power-law-like behavior over a considerable range of scales. Manifestation of this behavior is remarkably consistent in terms of dimensionless time τ defined based on Richtmyer's linear theory within the range of Mach numbers from 1.1 to 2.0 and the range of gas cylinder tilt angles with respect to the plane of the shock front (0–30°).

42 ENGINEERING↗
DOE OSTI2021

MemXCT: Design, Optimization, Scaling, and Reproducibility of X-Ray Tomography Imaging

Here, this work extends our previous research entitled "MemXCT: Memory-centric X-ray CT Reconstruction with Massive Parallelization" that was originally published at SC19 conference (Hidayetoglu et al., 2019) with reproducibility of the computational imaging performance. X-ray computed tomography (XCT) is regularly used at synchrotron light sources to study the internal morphology of materials at high resolution. However, experimental constraints, such as radiation sensitivity, can result in noisy or undersampled measurements. Further, depending on the resolution, sample size and data acquisition rates, the resulting noisy dataset can be in the order of terabytes. Advanced iterative reconstruction techniques can produce high-quality images from noisy measurements, but their computational requirements have made their use an exception rather than the rule. We propose a novel memory-centric approach that avoids redundant computations at the expense of additional memory complexity. We develop a memory-centric iterative reconstruction system, MemXCT, that uses an optimized SpMV implementation with two-level pseudo-Hilbert ordering and multi-stage input buffering. We evaluate MemXCT on various supercomputer architectures involving KNL and GPU. MemXCT can reconstruct a large (11Kx11K) mouse brain tomogram in 10 seconds using 4096 KNL nodes (256K cores). The results presented in our original article at the SC19 were based on large-scale supercomputing resources. The MemXCT application was selected for the Student Cluster Competition (SCC) Reproducibility Challenge and evaluated on a variety of cloud computing resources by universities around the world in the SC20 conference. We summarize the results of the top-ranked SCC Reproducibility Challenge teams and identify the most pertinent measures for ensuring the reproducibility of our experiments in this article.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Dependence of Solar Wind Proton Temperature on the Polarization Properties of Alfvénic Fluctuations at Ion-kinetic Scales

In this work, we use fluctuating magnetic helicity to investigate the polarization properties of Alfvénic fluctuations at ion-kinetic scales in the solar wind as a function of β p , the ratio of proton thermal pressure to magnetic pressure, and θ vB , the angle between the proton flow and local mean magnetic field, B 0 . Using almost 15 yr of Wind observations, we separate the contributions to helicity from fluctuations with wavevectors, k, quasi-parallel and oblique to B 0 , finding that the helicity of Alfvénic fluctuations is consistent with predictions from linear Vlasov theory. This result suggests that the nonlinear turbulent fluctuations at these scales share at least some polarization properties with Alfvén waves. Furthermore, we also investigate the dependence of proton temperature in the β p –θ vB plane to probe for possible signatures of turbulent dissipation, finding that it correlates with θ vB . The proton temperature parallel to B 0 is higher in the parameter space where we measure the helicity of right-handed Alfvénic fluctuations, and the temperature perpendicular to B 0 is higher where we measure left-handed fluctuations. This finding is inconsistent with the general assumption that by sampling different θ vB in the solar wind we can analyze the dependence of the turbulence distribution on θ kB , the angle between k and B 0 . After ruling out both instrumental and expansion effects, we conclude that our results provide new evidence for the importance of local kinetic processes that depend on θ vB in determining proton temperature in the solar wind.

79 ASTRONOMY AND ASTROPHYSICS↗