Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “heterogeneous computing”

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 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A characterization of plasma properties of a heterogeneous magnetized low pressure discharge column

An approach is presented for characterizing heterogeneous magnetized plasma discharge tubes through the scattering of electromagnetic plane waves. Here, we formulate the analytical problem of electromagnetic scattering from a gyrotropic plasma column. The scattering accounts for the heterogeneous composition of the cylindrical discharge plasma and facilitates determining its propensity for gyrotropic scattering, particularly when electron collisional damping may be prevalent. The analytical results are validated using computational simulations. Scattered fields from the magnetized plasma are measured experimentally, and, by comparing the analytical and experimental results, the unknown parameters of the discharge, i.e., characteristic plasma and electron collisional damping frequencies, are determined. The technique is relatively straight-forward to use and removes the need for commercial computational electromagnetic simulations when experimental data on scattering characteristics of such cylindrical discharge plasmas are available.

36 MATERIALS SCIENCE↗
DOE OSTI2014

SU-E-T-427: Cell Surviving Fractions Derived From Tumor-Volume Variation During Radiotherapy for Non-Small Cell Lung Cancer: Comparison with Predictive Assays

Purpose: To show that a distribution of cell surviving fractions S{sub 2} in a heterogeneous group of patients can be derived from tumor-volume variation curves during radiotherapy for non-small cell lung cancer. Methods: Our analysis was based on two data sets of tumor-volume variation curves for heterogeneous groups of 17 patients treated for nonsmall cell lung cancer with conventional dose fractionation. The data sets were obtained previously at two independent institutions by using megavoltage (MV) computed tomography (CT). Statistical distributions of cell surviving fractions S{sup 2} and cell clearance half-lives of lethally damaged cells T1/2 have been reconstructed in each patient group by using a version of the two-level cell population tumor response model and a simulated annealing algorithm. The reconstructed statistical distributions of the cell surviving fractions have been compared to the distributions measured using predictive assays in vitro. Results: Non-small cell lung cancer presents certain difficulties for modeling surviving fractions using tumor-volume variation curves because of relatively large fractional hypoxic volume, low gradient of tumor-volume response, and possible uncertainties due to breathing motion. Despite these difficulties, cell surviving fractions S{sub 2} for non-small cell lung cancer derived from tumor-volume variation measured at different institutions have similar probability density functions (PDFs) with mean values of 0.30 and 0.43 and standard deviations of 0.13 and 0.18, respectively. The PDFs for cell surviving fractions S{sup 2} reconstructed from tumor volume variation agree with the PDF measured in vitro. Comparison of the reconstructed cell surviving fractions with patient survival data shows that the patient survival time decreases as the cell surviving fraction increases. Conclusion: The data obtained in this work suggests that the cell surviving fractions S{sub 2} can be reconstructed from the tumor volume variation curves measured during radiotherapy with conventional fractionation. The proposed method can be used for treatment evaluation and adaptation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Atomic-level mechanisms of short-circuit diffusion in materials

This paper reviews the recent progress in understanding the atomic mechanisms of short-circuit diffusion along materials interfaces, such as grain and interphase boundaries, as well as lattice and interfacial dislocations/disconnections. Recent atomistic computer simulations have shown that short-circuit diffusion is dominated by collective atomic rearrangements in the form of strings and rings of mobile atoms. The process is dynamically heterogeneous in space and time and has many features in common with atomic dynamics in supercooled glass-forming liquids. We discuss examples of grain boundary, interphase boundary, and dislocation diffusion in metals and alloys, including the solute effect on the diffusion rates and mechanisms. Interphase boundaries are exemplified by Al–Si interfaces with diverse orientation relationships and atomic structures. The hierarchy of short-circuit diffusion paths in materials is reviewed by comparing the rates of grain boundary, interphase boundary, and dislocation diffusion. Future directions in the field of short-circuit diffusion in defect core regions are discussed.

36 MATERIALS SCIENCE↗
NASA NTRS1988

Programming model for distributed intelligent systems

A programming model and architecture which was developed for the design and implementation of complex, heterogeneous measurement and control systems is described. The Multigraph Architecture integrates artificial intelligence techniques with conventional software technologies, offers a unified framework for distributed and shared memory based parallel computational models and supports multiple programming paradigms. The system can be implemented on different hardware architectures and can be adapted to strongly different applications.

Sztipanovits, J.↗
NASA NTRS2000

Object-oriented Approach to High-level Network Monitoring and Management

An absolute prerequisite for the management of large investigating methods to build high-level monitoring computer networks is the ability to measure their systems that are built on top of existing monitoring performance. Unless we monitor a system, we cannot tools. Due to the heterogeneous nature of the hope to manage and control its performance. In this underlying systems at NASA Langley Research Center, paper, we describe a network monitoring system that we use an object-oriented approach for the design, we are currently designing and implementing. Keeping, first, we use UML (Unified Modeling Language) to in mind the complexity of the task and the required model users' requirements. Second, we identify the flexibility for future changes, we use an object-oriented existing capabilities of the underlying monitoring design methodology. The system is built using the system. Third, we try to map the former with the latter. APIs offered by the HP OpenView system.

Mukkamala, Ravi↗
DOE OSTI2021

Gouge formation and dilation impacts to flow during fracture shearing

We report flow in fractures is of critical importance to fluid flow in low-permeability shales, particularly when they restrict vertical migration from reservoirs. The Mt. Simon Sandstone is a target for geologic CO 2 sequestration and the overlying Eau Claire Formation is the sealing formation capping this reservoir. The lower Eau Claire, a primary barrier to upward migration of CO 2 from the Mt. Simon, is lithologically heterogenous with a mixture of sandstone and shale. We use a series of flow-through experiments on fractured samples from the Eau Claire to document the morphological changes taking place in the fracture and surrounding rock as it is sheared in a stepwise fashion. The samples were imaged using computed tomography after each shearing episode and flow resistance was calculated based on the pressure differential across each core. We found that gouge accumulations in the fracture plane led to specific instances of self-sealing behavior despite the fact that most samples increased in average fracture aperture and transmissivity. Gouge limited the increase or, in some cases, decreased flow through these samples. Fractures adjacent to shale-rich zones and concordant with bedding were more likely to show evidence of self-sealing, while increased sandstone content and fracture orientation perpendicular to bedding planes was more likely to result in fracture dilation and fracture permeability increases. Reactivation and shearing of vertical fractures in lithologically heterogenous caprocks is more likely to pose risks to long term CO 2 storage scenarios.

58 GEOSCIENCES↗
DOE OSTI2022

Liquid-Phase Effects on Adsorption Processes in Heterogeneous Catalysis

Aqueous solvation free energies of adsorption have recently been measured for phenol adsorption on Pt(111). Endergonic solvent effects of ~1 eV suggest solvents dramatically influence a metal catalyst’s activity with significant implications for the catalyst design. However, measurements are indirect and involve adsorption isotherm models, which potentially reduces the reliability of the extracted energy values. Computational, implicit solvation models predict exergonic solvation effects for phenol adsorption, failing to agree with measurements even qualitatively. In this study, an explicit, hybrid quantum mechanical/molecular mechanical approach for computing solvation free energies of adsorption is developed, solvation free energies of phenol adsorption are computed, and experimental data for solvation free energies of phenol adsorption are reanalyzed using multiple adsorption isotherm models. Explicit solvation calculations predict an endergonic solvation free energy for phenol adsorption that agrees well with measurements to within the experimental and force field uncertainties. Computed adsorption free energies of solvation of carbon monoxide, ethylene glycol, benzene, and phenol over the (111) facet of Pt and Cu suggest that liquid water destabilizes all adsorbed species, with the largest impact on the largest adsorbates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Permeability Prediction Using Vision Transformers

Accurate permeability predictions remain pivotal for understanding fluid flow in porous media, influencing crucial operations across petroleum engineering, hydrogeology, and related fields. Traditional approaches, while robust, often grapple with the inherent heterogeneity of reservoir rocks. With the advent of deep learning, convolutional neural networks (CNNs) have emerged as potent tools in image-based permeability estimation, capitalizing on micro-CT scans and digital rock imagery. This paper introduces a novel paradigm, employing vision transformers (ViTs)—a recent advancement in computer vision—for this crucial task. ViTs, which segment images into fixed-sized patches and process them through transformer architectures, present a promising alternative to CNNs. We present a methodology for implementing ViTs for permeability prediction, its results on diverse rock samples, and a comparison against conventional CNNs. The prediction results suggest that, with adequate training data, ViTs can match or surpass the predictive accuracy of CNNs, especially in rocks exhibiting significant heterogeneity. This study underscores the potential of ViTs as an innovative tool in permeability prediction, paving the way for further research and integration into mainstream reservoir characterization workflows.

58 GEOSCIENCES↗
DOE OSTI2023

Assessing pore network heterogeneity across multiple scales to inform CO2 injection models

Geologic heterogeneity is a key feature that must be considered when translations of scaled data are performed. This paper presents the assessment of geologic heterogeneity using a multiscale workflow that includes image analysis-based methods coupled with well log analysis to provide data in which fractals and machine learning methods estimate the carbon dioxide (CO 2 ) storage resource potential of a reservoir. The heterogeneity of rock properties of the complex Bell Creek reservoir in Montana, USA, was explored at the pore scale (~nm to mm), core scale (~mm to m), and well scale (~cm to m). The data used in this study included advanced image analysis of micro-CT (computed tomography) images (pore scale), thin sections (pore scale), plugs and core images (core scale) and well logs (well scale). The micro-CT images were segmented using a U-net segmentation approach into objects of pores and grains. Further, the segmented images were reconstructed into subvolumes of different sizes. Physical properties (porosity and permeability) and fractal dimensions were calculated for the various subvolumes, and Lorenz coefficient (Lc) values, a single parameter to describe the degree of heterogeneity within a pay zone section, were calculated from thin-section images and well logs. Porosity and fractal dimension values were used to estimate the 188-µm threshold of representative elementary volume (REV) in this study. Both the Lc and fractal dimension values were found to be negatively correlated. When these two parameters are combined, it is possible to discern differences in the complex porous networks of the samples analyzed in this study.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Evaluating Portable Parallelization Strategies for Heterogeneous Architectures in High Energy Physics

High-energy physics (HEP) experiments have developed millions of lines of code over decades that are optimized to run on traditional x86 CPU systems. However, we are seeing a rapidly increasing fraction of floating point computing power in leadership-class computing facilities and traditional data centers coming from new accelerator architectures, such as GPUs. HEP experiments are now faced with the untenable prospect of rewriting millions of lines of x86 CPU code, for the increasingly dominant architectures found in these computational accelerators. This task is made more challenging by the architecture-specific languages and APIs promoted by manufacturers such as NVIDIA, Intel and AMD. Producing multiple, architecture-specific implementations is not a viable scenario, given the available person power and code maintenance issues. The Portable Parallelization Strategies team of the HEP Center for Computational Excellence is investigating the use of Kokkos, SYCL, OpenMP, std::execution::parallel and alpaka as potential portability solutions that promise to execute on multiple architectures from the same source code, using representative use cases from major HEP experiments, including the DUNE experiment of the Long Baseline Neutrino Facility, and the ATLAS and CMS experiments of the Large Hadron Collider. This cross-cutting evaluation of portability solutions using real applications will help inform and guide the HEP community when choosing their software and hardware suites for the next generation of experimental frameworks. We present the outcomes of our studies, including performance metrics, porting challenges, API evaluations, and build system integration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Exascale Co-design for Modeling Materials in Extreme Environments

Computational materials science has provided great insight into the response of materials under extreme conditions that are difficult to probe experimentally. For example, shock-induced plasticity and phase transformation processes in single-crystal and nanocrystalline metals have been widely studied via large-scale molecular dynamics simulations, and many of these predictions are beginning to be tested at advanced 4th generation light sources such as the Advanced Photon Source (APS) and Linac Coherent Light Source (LCLS). I will describe our simulation predictions and their recent verification at LCLS, outstanding challenges in modeling the response of materials to extreme mechanical and radiation environments, and our efforts to tackle these as part of the multi-institutional, multi-disciplinary Exascale Co-design Center for Materials in Extreme Environments (ExMatEx). ExMatEx has initiated an early and deep collaboration between domain (computational materials) scientists, applied mathematicians, computer scientists, and hardware architects, in order to establish the relationships between algorithms, software stacks, and architectures needed to enable exascale-ready materials science application codes within the next decade. We anticipate that we will be able to exploit hierarchical, heterogeneous architectures to achieve more realistic large-scale simulations with adaptive physics refinement, and are using tractable application scale-bridging proxy application testbeds to assess new approaches and requirements. Such current scale-bridging strategies accumulate (or recompute) a distributed response database from fine-scale calculations, in a top-down rather than bottom-up multiscale approach.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Noise reduction in X-ray photon correlation spectroscopy with convolutional neural networks encoder–decoder models

Abstract Like other experimental techniques, X-ray photon correlation spectroscopy is subject to various kinds of noise. Random and correlated fluctuations and heterogeneities can be present in a two-time correlation function and obscure the information about the intrinsic dynamics of a sample. Simultaneously addressing the disparate origins of noise in the experimental data is challenging. We propose a computational approach for improving the signal-to-noise ratio in two-time correlation functions that is based on convolutional neural network encoder–decoder (CNN-ED) models. Such models extract features from an image via convolutional layers, project them to a low dimensional space and then reconstruct a clean image from this reduced representation via transposed convolutional layers. Not only are ED models a general tool for random noise removal, but their application to low signal-to-noise data can enhance the data’s quantitative usage since they are able to learn the functional form of the signal. We demonstrate that the CNN-ED models trained on real-world experimental data help to effectively extract equilibrium dynamics’ parameters from two-time correlation functions, containing statistical noise and dynamic heterogeneities. Strategies for optimizing the models’ performance and their applicability limits are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Limiting Surface Density Method Adapted to Large Arrays of Heterogeneous Shipping Packages with Nonlinear Responses

The classic Limiting Surface Density (LSD) method is an empirical calculation technique for analyzing and setting mass limits for fissile items in storage arrays. LSD is a desirable method because it can reduce or eliminate the need for lengthy detailed Monte Carlo models of storage arrays. The original (or classic) method was developed based on idealized arrays of bare spherical metal items in air-spaced cubic units in a water-reflected cubic array. In this case, the geometric and material-based surface densities were acceptably correlated by linear functions. Later updates to the method were made to allow for concrete reflection rather than water, cylindrical masses rather than spheres, different material forms, and noncubic arrays. However, in the intervening four decades since those updates, little work has been done to update the method, especially for use with contemporary highly heterogeneous shipping packages that are noncubic and stored in noncubic arrays. In this work, the LSD method is reevaluated for application to highly heterogeneous shipping packages for fissile material. The package modeled is the 9975 shipping package, currently the primary package used to store fissile material at Savannah River Site’s K-Area Complex. The package is neither cubic nor rectangular but resembles nested cylinders of stainless steel, lead, aluminum, and Celotex. The fissile content is assumed to be a cylinder of plutonium metal. The packages may be arranged in arrays with both an equal number of packages per side (package cubic) and an unequal number of packages per side (noncubic). The cubic arrangements are used to derive the 9975-specific material and geometry constants for the classic linear form LSD method. The linear form of the LSD, with noncubic array adjustment, is applied and evaluated against computational models for these packages to determine the critical unit fissile mass. Sensitivity equations are derived from the classic method, and these are also used to make projections of the critical unit fissile mass. It was discovered that the heterogeneous packages have a nonlinear surface density versus critical mass relationship compared to the acceptably linear response of bare spherical fissile masses. Methodology is developed to address the nonlinear response. In so doing, the solution to the nonlinear LSD method becomes decoupled from the critical mass of a single unit, adding to its flexibility. The ability of the method to predict changes in neutron multiplication due to perturbations in a parameter is examined to provide a basis for analyzing upset conditions. In conclusion, a full rederivation of the classic LSD method from diffusion theory is also included as this was found to be lacking in the available literature.

42 ENGINEERING↗
DOE OSTI2023

Asynchronous Execution of Heterogeneous Tasks in ML-Driven HPC Workflows

Heterogeneous scientific workflows consist of numerous types of tasks that require execution on heterogeneous resources. Asynchronous execution of those tasks is crucial to improve resource utilization, task throughput and reduce workflows' makespan. Therefore, middleware capable of scheduling and executing different task types across heterogeneous resources must enable asynchronous execution of tasks. In this paper, we investigate the requirements and properties of the asynchronous task execution of machine learning (ML)-driven high-performance computing (HPC) workflows. We model the degree of asynchronicity permitted for arbitrary workflows and propose key metrics that can be used to determine qualitative benefits when employing asynchronous execution. Our experiments represent relevant scientific drivers, we perform them at scale on Summit, and we show that the performance enhancements due to asynchronous execution are consistent with our model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Discontinuous Galerkin gradient discretisations for the approximation of second-order differential operators in divergence form

We include in the gradient discretisation method (GDM) framework two numerical schemes based on discontinuous Galerkin approximations: the symmetric interior penalty Galerkin (SIPG) method, and the scheme obtained by averaging the jumps in the SIPG method. We prove that these schemes meet the main mathematical gradient discretisation properties on any kind of polytopal mesh, by adapting discrete functional analysis properties to our precise geometrical hypotheses. Therefore, these schemes inherit the general convergence properties of the GDM, which hold for instance in the cases of the p-Laplace problem and of the anisotropic and heterogeneous diffusion problem. This is illustrated by simple 1D and 2D numerical examples.

97 MATHEMATICS AND COMPUTING↗