A New Bi-Partite Graph Representation of 3D Solids for Geometric Reasoning and Graph Neural Networks
Explore the source record for details and available documents.
Quadros, William Roshan [Sandia National Laborator↗
SEARCH · Engineering Papers
Results for “network partition”
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.
Electrostatic limits on charge selectivity in ultrahigh charge density polymer membranes
Ion-exchange membranes (IEMs) with ultrahigh charge densities offer the promise of enhanced ion transport for electrochemical technologies, yet the fundamental limits of this membrane design strategy are not yet understood. In this work, we present a systematic study of bis(1-vinyl-3-imidazolium) cross-linked polymer membranes with fixed charge contents ranging from 6 to 9 mol/L[dry polymer], synthesized to isolate the effects of charge density at constant membrane water content. While ionic conductivity increases monotonically with increasing charge density, a sharp decline in charge selectivity is observed for the most densely charged membranes, defying conventional expectations. Structural, thermal, and mechanical analyses reveal a critical onset of network disruption and anomalous ion partitioning behavior in these densely charged membranes. With proper consideration of cross-linker geometry, these results are interpreted using Manning's counter-ion condensation theory, which suggests that closely packed charged cross-linkers amplify inter-chain electrostatic interactions and trigger excess counter-ion condensation. Our findings suggest that, beyond a threshold spacing between fixed charges, increased functionalization may harm rather than help charge selectivity of IEMs.
36 MATERIALS SCIENCE↗
Rectilinear partitioning of irregular data parallel computations
New mapping algorithms for domain oriented data-parallel computations, where the workload is distributed irregularly throughout the domain, but exhibits localized communication patterns are described. Researchers consider the problem of partitioning the domain for parallel processing in such a way that the workload on the most heavily loaded processor is minimized, subject to the constraint that the partition be perfectly rectilinear. Rectilinear partitions are useful on architectures that have a fast local mesh network. Discussed here is an improved algorithm for finding the optimal partitioning in one dimension, new algorithms for partitioning in two dimensions, and optimal partitioning in three dimensions. The application of these algorithms to real problems are discussed.
Nicol, David M.↗
Neural Net-Based Redesign of Transonic Turbines for Improved Unsteady Aerodynamic Performance
A recently developed neural net-based aerodynamic design procedure is used in the redesign of a transonic turbine stage to improve its unsteady aerodynamic performance. The redesign procedure used incorporates the advantages of both traditional response surface methodology (RSM) and neural networks by employing a strategy called parameter-based partitioning of the design space. Starting from the reference design, a sequence of response surfaces based on both neural networks and polynomial fits are constructed to traverse the design space in search of an optimal solution that exhibits improved unsteady performance. The procedure combines the power of neural networks and the economy of low-order polynomials (in terms of number of simulations required and network training requirements). A time-accurate, two-dimensional, Navier-Stokes solver is used to evaluate the various intermediate designs and provide inputs to the optimization procedure. The optimization procedure yields a modified design that improves the aerodynamic performance through small changes to the reference design geometry. The computed results demonstrate the capabilities of the neural net-based design procedure, and also show the tremendous advantages that can be gained by including high-fidelity unsteady simulations that capture the relevant flow physics in the design optimization process.
Madavan, Nateri K.↗
Improving the Unsteady Aerodynamic Performance of Transonic Turbines using Neural Networks
A recently developed neural net-based aerodynamic design procedure is used in the redesign of a transonic turbine stage to improve its unsteady aerodynamic performance. The redesign procedure used incorporates the advantages of both traditional response surface methodology and neural networks by employing a strategy called parameter-based partitioning of the design space. Starting from the reference design, a sequence of response surfaces based on both neural networks and polynomial fits are constructed to traverse the design space in search of an optimal solution that exhibits improved unsteady performance. The procedure combines the power of neural networks and the economy of low-order polynomials (in terms of number of simulations required and network training requirements). A time-accurate, two-dimensional, Navier-Stokes solver is used to evaluate the various intermediate designs and provide inputs to the optimization procedure. The procedure yielded a modified design that improves the aerodynamic performance through small changes to the reference design geometry. These results demonstrate the capabilities of the neural net-based design procedure, and also show the advantages of including high-fidelity unsteady simulations that capture the relevant flow physics in the design optimization process.
Rai, Man Mohan↗
Aerodynamic Design Using Neural Networks
The design of aerodynamic components of aircraft, such as wings or engines, involves a process of obtaining the most optimal component shape that can deliver the desired level of component performance, subject to various constraints, e.g., total weight or cost, that the component must satisfy. Aerodynamic design can thus be formulated as an optimization problem that involves the minimization of an objective function subject to constraints. A new aerodynamic design optimization procedure based on neural networks and response surface methodology (RSM) incorporates the advantages of both traditional RSM and neural networks. The procedure uses a strategy, denoted parameter-based partitioning of the design space, to construct a sequence of response surfaces based on both neural networks and polynomial fits to traverse the design space in search of the optimal solution. Some desirable characteristics of the new design optimization procedure include the ability to handle a variety of design objectives, easily impose constraints, and incorporate design guidelines and rules of thumb. It provides an infrastructure for variable fidelity analysis and reduces the cost of computation by using less-expensive, lower fidelity simulations in the early stages of the design evolution. The initial or starting design can be far from optimal. The procedure is easy and economical to use in large-dimensional design space and can be used to perform design tradeoff studies rapidly. Designs involving multiple disciplines can also be optimized. Some practical applications of the design procedure that have demonstrated some of its capabilities include the inverse design of an optimal turbine airfoil starting from a generic shape and the redesign of transonic turbines to improve their unsteady aerodynamic characteristics.
Rai, Man Mohan↗
A hybrid Penman-Monteith and machine learning model for simulating evapotranspiration and its components
Integrating physical processes with machine learning has advanced evapotranspiration (ET) simulation, yet most hybrid models fail to partition total ET into its components: soil evaporation (E) and vegetation transpiration (T). This study introduces Residual Neural Network–Penman–Monteith (RNN-PM), a novel hybrid dual-source ET model designed to overcome this limitation. The model synergizes the physically-based Penman–Monteith framework with three specialized residual neural networks trained to estimate key conductance parameters (canopy conductance, soil surface conductance, and aerodynamic conductance). Furthermore this explicit parameterization allows for the direct partitioning of total ET. Validation at National Ecological Observatory Network (NEON) flux sites using high-frequency partitioned E and T shows that RNN-PM reliably reproduces ET and the transpiration fraction (T/ET). For ET, the model achieves an average Kling–Gupta efficiency (KGE) of 0.89 and a root-mean-square error (RMSE) of 0.55 mm/day; for T/ET, the KGE is 0.87 with an RMSE of 0.06. Furthermore, RNN-PM demonstrates robust generalization, accurately simulating ET and its components well beyond the initial training dataset, even under extreme climatic conditions. This study extended the analysis by comparing the RNN-PM model with seven established dual-source ET models. The results indicate that RNN-PM outperforms both conventional machine learning models and purely physical process-based models in simulating ET components in most cases. Among the purely physical process-based dual-source models, those based on surface temperature decomposition showed improved performance as the leaf area index (LAI) decreased when evaluated against high-frequency ET component datasets. In contrast, the performance of conductance-based dual-source models declined with decreasing LAI. Although purely machine learning-based models can produce relatively accurate simulations of ET components, they often exhibit limited generalization capability, an issue that the RNN-PM model effectively overcomes. Ultimately, the RNN-PM model represents a significant advance in simulating ET components, offering a novel and scalable approach for improving the representation of land–atmosphere interactions in Earth system models.
54 ENVIRONMENTAL SCIENCES↗
Efficient Use of Distributed Systems for Scientific Applications
Distributed computing has been regarded as the future of high performance computing. Nationwide high speed networks such as vBNS are becoming widely available to interconnect high-speed computers, virtual environments, scientific instruments and large data sets. One of the major issues to be addressed with distributed systems is the development of computational tools that facilitate the efficient execution of parallel applications on such systems. These tools must exploit the heterogeneous resources (networks and compute nodes) in distributed systems. This paper presents a tool, called PART, which addresses this issue for mesh partitioning. PART takes advantage of the following heterogeneous system features: (1) processor speed; (2) number of processors; (3) local network performance; and (4) wide area network performance. Further, different finite element applications under consideration may have different computational complexities, different communication patterns, and different element types, which also must be taken into consideration when partitioning. PART uses parallel simulated annealing to partition the domain, taking into consideration network and processor heterogeneity. The results of using PART for an explicit finite element application executing on two IBM SPs (located at Argonne National Laboratory and the San Diego Supercomputer Center) indicate an increase in efficiency by up to 36% as compared to METIS, a widely used mesh partitioning tool. The input to METIS was modified to take into consideration heterogeneous processor performance; METIS does not take into consideration heterogeneous networks. The execution times for these applications were reduced by up to 30% as compared to METIS. These results are given in Figure 1 for four irregular meshes with number of elements ranging from 30,269 elements for the Barth5 mesh to 11,451 elements for the Barth4 mesh. Future work with PART entails using the tool with an integrated application requiring distributed systems. In particular this application, illustrated in the document entails an integration of finite element and fluid dynamic simulations to address the cooling of turbine blades of a gas turbine engine design. It is not uncommon to encounter high-temperature, film-cooled turbine airfoils with 1,000,000s of degrees of freedom. This results because of the complexity of the various components of the airfoils, requiring fine-grain meshing for accuracy. Additional information is contained in the original.
Taylor, Valerie↗
A Robust Parallel Distributed State Estimation for Large Scale Distribution Systems
The growing need and interest in real-time monitoring of large distribution networks motivated by the rapid population of renewable sources, EVs and etc. demand a computationally efficient state estimation framework. Furthermore, this paper presents an improved computational framework for implementing a robust state estimator using a multi-core processor. The main contribution of the paper is the proposed computational framework along with two partitioning strategies which enable fast and robust state estimation for large scale radial and/or meshed distribution systems. Formulation of the proposed method and its implementation are described in detail. Performance of the estimator is tested by simulations first using a small 84-bus radial distribution system. Then the method’s scalability is demonstrated by simulations on two very large scale distribution networks one configured radially and the other meshed each containing over 12,500 buses.
42 ENGINEERING↗
Multiphase complete exchange: A theoretical analysis
Complete Exchange requires each of N processors to send a unique message to each of the remaining N-1 processors. For a circuit switched hypercube with N = 2(sub d) processors, the Direct and Standard algorithms for Complete Exchange are optimal for very large and very small message sizes, respectively. For intermediate sizes, a hybrid Multiphase algorithm is better. This carries out Direct exchanges on a set of subcubes whose dimensions are a partition of the integer d. The best such algorithm for a given message size m could hitherto only be found by enumerating all partitions of d. The Multiphase algorithm is analyzed assuming a high performance communication network. It is proved that only algorithms corresponding to equipartitions of d (partitions in which the maximum and minimum elements differ by at most 1) can possibly be optimal. The run times of these algorithms plotted against m form a hull of optimality. It is proved that, although there is an exponential number of partitions, (1) the number of faces on this hull is Theta(square root of d), (2) the hull can be found in theta(square root of d) time, and (3) once it has been found, the optimal algorithm for any given m can be found in Theta(log d) time. These results provide a very fast technique for minimizing communication overhead in many important applications, such as matrix transpose, Fast Fourier transform, and ADI.
Bokhari, Shahid H.↗
Parallel Computation of Unsteady Flows on a Network of Workstations
Parallel computation of unsteady flows requires significant computational resources. The utilization of a network of workstations seems an efficient solution to the problem where large problems can be treated at a reasonable cost. This approach requires the solution of several problems: 1) the partitioning and distribution of the problem over a network of workstation, 2) efficient communication tools, 3) managing the system efficiently for a given problem. Of course, there is the question of the efficiency of any given numerical algorithm to such a computing system. NPARC code was chosen as a sample for the application. For the explicit version of the NPARC code both two- and three-dimensional problems were studied. Again both steady and unsteady problems were investigated. The issues studied as a part of the research program were: 1) how to distribute the data between the workstations, 2) how to compute and how to communicate at each node efficiently, 3) how to balance the load distribution. In the following, a summary of these activities is presented. Details of the work have been presented and published as referenced.
Source record↗
Problem size, parallel architecture and optimal speedup
The communication and synchronization overhead inherent in parallel processing can lead to situations where adding processors to the solution method actually increases execution time. Problem type, problem size, and architecture type all affect the optimal number of processors to employ. The numerical solution of an elliptic partial differential equation is examined in order to study the relationship between problem size and architecture. The equation's domain is discretized into n sup 2 grid points which are divided into partitions and mapped onto the individual processor memories. The relationships between grid size, stencil type, partitioning strategy, processor execution time, and communication network type are analytically quantified. In so doing, the optimal number of processors was determined to assign to the solution, and identified (1) the smallest grid size which fully benefits from using all available processors, (2) the leverage on performance given by increasing processor speed or communication network speed, and (3) the suitability of various architectures for large numerical problems.
Nicol, David M.↗
Problem size, parallel architecture, and optimal speedup
The communication and synchronization overhead inherent in parallel processing can lead to situations where adding processors to the solution method actually increases execution time. Problem type, problem size, and architecture type all affect the optimal number of processors to employ. The numerical solution of an elliptic partial differential equation is examined in order to study the relationship between problem size and architecture. The equation's domain is discretized into n sup 2 grid points which are divided into partitions and mapped onto the individual processor memories. The relationships between grid size, stencil type, partitioning strategy, processor execution time, and communication network type are analytically quantified. In so doing, the optimal number of processors was determined to assign to the solution, and identified (1) the smallest grid size which fully benefits from using all available processors, (2) the leverage on performance given by increasing processor speed or communication network speed, and (3) the suitability of various architectures for large numerical problems.
Nicol, David M.↗
Programming Tools: Status, Evaluation, and Comparison
In this tutorial I will first describe the characteristics of scientific applications and their developers, and describe the computing environment in a typical high-performance computing center. I will define the user requirements for tools that support application portability and present the difficulties to satisfy them. These form the basis of the evaluation and comparison of the tools. I will then describe the tools available in the market and the tools available in the public domain. Specifically, I will describe the tools for converting sequential programs, tools for developing portable new programs, tools for debugging and performance tuning, tools for partitioning and mapping, and tools for managing network of resources. I will introduce the main goals and approaches of the tools, and show main features of a few tools in each category. Meanwhile, I will compare tool usability for real-world application development and compare their different technological approaches. Finally, I will indicate the future directions of the tools in each category.
Cheng, Doreen Y.↗
Graph Partitioning for Parallel Applications in Heterogeneous Grid Environments
The problem of partitioning irregular graphs and meshes for parallel computations on homogeneous systems has been extensively studied. However, these partitioning schemes fail when the target system architecture exhibits heterogeneity in resource characteristics. With the emergence of technologies such as the Grid, it is imperative to study the partitioning problem taking into consideration the differing capabilities of such distributed heterogeneous systems. In our model, the heterogeneous system consists of processors with varying processing power and an underlying non-uniform communication network. We present in this paper a novel multilevel partitioning scheme for irregular graphs and meshes, that takes into account issues pertinent to Grid computing environments. Our partitioning algorithm, called MiniMax, generates and maps partitions onto a heterogeneous system with the objective of minimizing the maximum execution time of the parallel distributed application. For experimental performance study, we have considered both a realistic mesh problem from NASA as well as synthetic workloads. Simulation results demonstrate that MiniMax generates high quality partitions for various classes of applications targeted for parallel execution in a distributed heterogeneous environment.
Bisws, Rupak↗
GPS Monitoring of Surface Change During and Following the Fortuitous Occurrence of the M(sub w) = 7.3 Landers Earthquake in our Network
Accomplishments: (1) Continues GPS monitoring of surface change during and following the fortuitous occurrence of the M(sub w) = 7.3 Landers earthquake in our network, in order to characterize earthquake dynamics and accelerated activity of related faults as far as 100's of kilometers along strike. (2) Integrates the geodetic constraints into consistent kinematic descriptions of the deformation field that can in turn be used to characterize the processes that drive geodynamics, including seismic cycle dynamics. In 1991, we installed and occupied a high precision GPS geodetic network to measure transform-related deformation that is partitioned from the Pacific - North America plate boundary northeastward through the Mojave Desert, via the Eastern California shear zone to the Walker Lane. The onset of the M(sub w) = 7.3 June 28, 1992, Landers, California, earthquake sequence within this network poses unique opportunities for continued monitoring of regional surface deformation related to the culmination of a major seismic cycle, characterization of the dynamic behavior of continental lithosphere during the seismic sequence, and post-seismic transient deformation. During the last year, we have reprocessed all three previous epochs for which JPL fiducial free point positioning products available and are queued for the remaining needed products, completed two field campaigns monitoring approx. 20 sites (October 1995 and September 1996), begun modeling by development of a finite element mesh based on network station locations, and developed manuscripts dealing with both the Landers-related transient deformation at the latitude of Lone Pine and the velocity field of the whole experiment. We are currently deploying a 1997 observation campaign (June 1997). We use GPS geodetic studies to characterize deformation in the Mojave Desert region and related structural domains to the north, and geophysical modeling of lithospheric behavior. The modeling is constrained by our existing and continued GPS measurements, which will provide much needed data on far-field strain accumulation across the region and on the deformational response of continental lithosphere during and following a large earthquake, forming the basis for kinematic and dynamic modeling of secular and seismic-cycle deformation. GPS geodesy affords both regional coverage and high precision that uniquely bear on these problems.
Miller, M. Meghan↗
Shifts in Evapotranspiration Components During Heatwaves Alter Surface Cooling
Heatwave events significantly alter ecosystem water and energy balance and are often accompanied by extreme surface temperatures. Understanding how surface temperatures during such events are regulated by soil evaporation (E) and vegetation transpiration (T) remains limited due to challenges in partitioning total evapotranspiration (ET). Here, high-frequency turbulence methods are used to partition observed ET at 32 National Ecological Observatory Network sites across the contiguous United States. Heatwaves were defined as at least three consecutive days with daily maximum air temperature exceeding the site-specific 90th percentile of the 2019–2021 record. Across 268 identified events, the T/ET ratio decreased by 32% ± 16% relative to the non-heatwave baseline of 0.65, with greater reductions at lower biomass sites. The T/ET ratio was typically suppressed below non-heatwave conditions during the early and middle stages of the heatwave (first two-thirds of event duration), but was on average higher than non-heatwave baseline levels during late stages (final third) due to extremely low soil evaporation. Of the studied heatwaves, 71% of these had surface temperatures above 38°C in their late stage; however, heatwaves sustaining higher evaporation fluxes (upper tertile of observed fluxes) during the late stage were associated with relative surface temperature anomalies that were on average 45% lower than those of heatwaves with lower evaporation fluxes (lower tertile). The commensurate surface cooling induced by higher transpiration was only 2% during heatwaves, suggesting that transpiration has a limited ability to mitigate extreme surface temperatures. This study allows for improved prediction of ecosystem feedbacks under extreme thermal stress.
54 ENVIRONMENTAL SCIENCES↗
Maintenance and operations cost model for DSN subsystems
A procedure is described which partitions the recurring costs of the Deep Space Network (DSN) over the individual DSN subsystems. The procedure results in a table showing the maintenance, operations, sustaining engineering and supportive costs for each subsystems.
Burt, R. W.↗