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At least 1,549 records · Page 86

Rendezvous algorithms for large-scale modeling and simulation

Rendezvous algorithms encode a communication pattern that is useful when processors sending data do not know who the receiving processors should be, or vice versa. The idea is to define an intermediate decomposition where datums from different sending processors can ”rendezvous” to perform a computation, in a manner that both the senders and eventual receivers of the results can identify the appropriate rendezvous processor. Though they were originally designed for interpolating between overlaid grids with independent parallel decompositions (Plimpton et al., 2004), we have recently found rendezvous algorithms useful for a variety of operations in particle- or grid-based simulation codes when running large problems on large numbers of processors. In particular, we show they can perform well when a load-balanced intermediate decomposition is randomized and not spatial, requiring all-to-all communication to move data between processors. In this case rendezvous algorithms leverage the large bisection communication bandwidths which parallel machines provide. We describe how rendezvous algorithms work in a scientific computing context and give specific examples for molecular dynamics and Direct Simulation Monte Carlo codes which result in dramatic performance improvements versus simpler algorithms which do not scale as well. We explain how a generic rendezvous algorithm can be implemented, and also point out similarities with the MapReduce paradigm popularized by Google and Hadoop.

97 MATHEMATICS AND COMPUTING↗

Transonic free-flight model testing at large scale

The use of free flight models for transonic testing at high Reynolds numbers is discussed. Several specific examples of experimental investigations are briefly reviewed to illustrate the scope of research that can be conducted by utilizing the advantages of free flight models. These advantages are primarily the lack of interference or constraints imposed by test facilities and model support systems and the dynamic freedom possessed by free flight models. High Reynolds numbers are obtained by using large models flown at relatively low altitudes. It is shown that models 10 meters or more in length will be required for research at Reynolds numbers sufficiently high to provide representative simulation of flow conditions for large modern aircraft. Several methods for launching models of this size are discussed. These methods include free drops from airplanes or balloons and ground launches with the use of internal or external rocket motors. All the launching methods discussed have been successfully demonstrated on flight vehicles of the size and weight required to attain the necessary test conditions.

Gillis, C. L.↗

Progressive Hedging Decomposition for Solutions of Large-Scale Process Family Design Problems

Rapid, wide-scale deployment of green process systems, such as carbon capture or water desalination systems, is essential for combatting climate change. Methods relying on traditional design or modularity fail to capture the benefits of both economies of numbers and economies of scale. We have proposed process family design, which designs a family of processes simultaneously exploiting opportunities for common elements. In previous work, we explored different optimization formulations to solve this problem. In this work, we develop a decomposition approach to tackle larger problems efficiently. We solve a water desalination case study, which is too large to solve within a reasonable timeframe with the discretization formulation. We exploit the block angular structure of the discretization problem to decompose and solve using Progressive Hedging (PH). We use the open-source Python package mpi-sppy to execute PH which allows us to leverage parallelization and a HPC cluster to further improve solution time.

Stinchfield, Georgia↗

Farm-level Interactions Study of a Novel Tri-port Soft-switching Medium-Voltage String Inverter (MVSI) based Large-scale PV-Plus-Storage Farms

A medium-voltage photovoltaic power conversion unit supported by battery based on a novel topology of soft switching solid state transformer is presented in this paper. It can reduce the Levelized Cost of Energy (LCOE) of PVS farm in an extended degree. However, its capability to provide grid-support services, such as frequency response, reactive power support, etc, have not been demonstrated. A series/parallel combination of these modules form a large 20 MVA solar farm. To validate them with reduced computation burden, a small-signal model of MVSI is firstly derived and validated in this paper. The model has been validated to match the full-switch model in both steady-state and dynamic conditions. Next, a farm-level simulation based on the proved small-signal model was implemented to demonstrate grid-support services. Real irradiation date from NREL is used to show the operational capabilities of the system. As a result, the overall farm is simulated based on MATLAB/Simulink domain to check the performance for various cases namely: power transfer from dc-ac side, reactive power support during grid voltage sag and utilization of battery during grid voltage disturbance or partial shading over PV panels.

14 SOLAR ENERGY↗

A Numerical Comparison of Barrier and Modified Barrier Methods for Large-Scale Bound-Constrained Optimization

When a classical barrier method is applied to the solution of a nonlinear programming problem with inequality constraints, the Hessian matrix of the barrier function becomes increasingly ill-conditioned as the solution is approached. As a result, it may be desirable to consider alternative numerical algorithms. We compare the performance of two methods motivated by barrier functions. The first is a stabilized form of the classical barrier method, where a numerically stable approximation to the Newton direction is used when the barrier parameter is small. The second is a modified barrier method where a barrier function is applied to a shifted form of the problem, and the resulting barrier terms are scaled by estimates of the optimal Lagrange multipliers. The condition number of the Hessian matrix of the resulting modified barrier function remains bounded as the solution to the constrained optimization problem is approached. Both of these techniques can be used in the context of a truncated-Newton method, and hence can be applied to large problems, as well as on parallel computers. In this paper, both techniques are applied to problems with bound constraints and we compare their practical behavior.

Nash, Stephen G.↗

Large-Scale Plasmonic Hybrid Framework with Built-In Nanohole Array as Multifunctional Optical Sensing Platforms

Light coupling with patterned subwavelength hole arrays induces enhanced transmission supported by the strong surface plasmon mode. In this work, a nanostructured plasmonic framework with vertically built-in nanohole arrays at deep-subwavelength scale (6 nm) is demonstrated using a two-step fabrication method. The nanohole arrays are formed first by the growth of a high-quality two-phase (i.e., Au–TiN) vertically aligned nanocomposite template, followed by selective wet-etching of the metal (Au). Such a plasmonic nanohole film owns high epitaxial quality with large surface coverage and the structure can be tailored as either fully etched or half-way etched nanoholes via careful control of the etching process. The chemically inert and plasmonic TiN plays a role in maintaining sharp hole boundary and preventing lattice distortion. Optical properties such as enhanced transmittance and anisotropic dielectric function in the visible regime are demonstrated. Numerical simulation suggests an extended surface plasmon mode and strong field enhancement at the hole edges. Furthermore, two demonstrations, including the enhanced and modulated photoluminescence by surface coupling with 2D perovskite nanoplates and the refractive index sensing by infiltrating immersion liquids, suggest the great potential of such plasmonic nanohole array for reusable surface plasmon-enhanced sensing applications.

42 ENGINEERING↗

Hot-spot mix in large-scale HDC implosions at NIF

Mix of high-Z material from the capsule into the fuel can severely degrade the performance of inertial fusion implosions. On the Hybrid B campaign, testing the largest high-density-carbon capsules yet fielded at the National Ignition Facility, several shots show signatures of high levels of hot-spot mix. We attribute a ~40% yield degradation on these shots to the hot-spot mix, comparable to the level of degradation from large $P_2$ asymmetries observed on some shots. Additionally, a range of instability growth factors and diamond crystallinity were tested and they do not determine the level of mix for these implosions, which is instead set by the capsule quality.

Fusion experiments↗

Large-scale impact and explosion craters - Comparisons of morphological and structural analogs

Crater studies indicate now that there are a broad set of morphological and structural analogs which occur in both impact and explosion craters. A description is presented of impact and explosion analogs for three basic crater types, including bowl-shaped craters, flat-floored craters with central uplift, and flat-floored craters with multirings. A systematic documentation is provided of the more critical morphological and structural analogs common between large natural bowl-shaped impact and explosion craters, between central uplift impact and explosion craters, and between multiring impact and explosion craters. The data presented consist of a set of published and unpublished cratering studies assembled into a single ordered outline with each crater described in the same format and graphic style.

Roddy, D. J.↗

Cosmological density fluctuations and large-scale structure From N-point correlation functions to the probability distribution

Knowledge of N-point correlation functions for all N allows one to invert and obtain the probability distribution of mass fluctuations in a fixed volume. The hierarchical sequence of higher order is applied to correlations with dimensionless amplitudes suggested by the BBGKY equations. The resulting distribution is significantly non-Gaussian, even for quite small mean square fluctuations. The qualitative and to some degree quantitative results are to a large degree independent of the exact sequence of amplitudes. An ensemble of such models compared with N-body simulations fails in detail to account for the low-density frequency distribution.

Fry, J. N.↗

The evolution of large-scale structure in a universe dominated by cold dark matter

The results of numerical simulations of nonlinear gravitational clustering in universes dominated by weakly interacting, 'cold' dark matter are presented. The numerical methods used and the way in which initial conditions were generated are described, and the simulations performed are catalogued. The evolution of the fundamental statistical properties of the models is described and their comparability with observation is discussed. Graphical comparisons of these open models with the observed galaxy distribution in a large redshift survey are made. It is concluded that a model with a cosmological density parameter omega equal to one is quite unacceptable if galaxies trace the mass distribution, and that models with omega of roughly two, while better, still do not provide a fully acceptable match with observation. Finally, a situation in which galaxy formation is suppressed except in sufficiently dense regions is modelled which leads to models which can agree with observation quite well even for omega equal to one.

Davis, M.↗

Infrasonic observations of large-scale HE events

The Los Alamos Infrasound Program has been operating since about mid-1982, making routine measurements of low frequency atmospheric acoustic propagation. Generally, the authors work between 0.1 Hz to 10 Hz; however, much of the work is concerned with the narrower range of 0.5 to 5.0 Hz. Two permanent stations, St. George, UT, and Los Alamos, NM, have been operational since 1983, collecting data 24 hours a day. For the purposes of this discussion, the authors concentrate on their measurements of large, high explosive (HE) events at ranges of 250 km to 5330 km. Because their equipment is well suited for mobile deployments, they can easily establish temporary observing sites for special events. The measurements are from the permanent sites, as well as from various temporary sites. A few observations that are typical of the full data set are given.

Whitaker, Rodney W.↗

Can Large Scale Volcanism Explain the Heat-Death of Venus (and Venus-like worlds?)

One of the fundamental questions about Venus is whether it ever had a habitable period in its distant past. If it did have such a period how did Venus get from a temperate state to its present day hot-house? Recent studies have demonstrated that increasing solar luminosity through time is an unlikely pathway for Venus even if that is one way for Earth to end up in a runaway greenhouse state. Large Igneous Provinces (LIPs; like that of the Siberian Traps) have been responsible for the End Permian mass extinction and other dramatic climate change events throughout Earth’s history. We investigate the hypothesis that overlapping Large Igneous Provinces could have driven Venus from a temperate to a runaway greenhouse state. We look at the LIP record in Earth history and the probability for overlapping LIP events as a proxy.

Venus↗

SolarExPert: Large-Scale OPF, DSSE and HIL

This presentation, part of the ADMS Test Bed Webinar Series, discusses how to accelerate industry adoption of ADMS to improve normal operations with high levels of distributed energy resources (DERs) and improve resilience and reliability.

ADMS↗

Architecture for Web-Based Visualization of Large-Scale Energy Domains: Preprint

With the growing penetration of inverter-based distributed energy resources and increased loads through electrification, power systems analyses are becoming more important and more complex. Moreover, these analyses increasingly involve the combination of interconnected energy domains with data that are spatially and temporally increasing in scale by orders of magnitude, surpassing the capabilities of many existing analysis and decision-support systems. We present the architectural design, development, and application of a high-resolution web-based visualization environment capable of cross-domain analysis of tens of millions of energy assets, focusing on scalability and performance. Our system supports the exploration, navigation, and analysis of large data from diverse domains such as electrical transmission and distribution systems, mobility and electric vehicle charging networks, communications networks, cyber assets, and other supporting infrastructure. We evaluate this system across multiple use cases, describing the capabilities and limitations of a web-based approach for high-resolution energy system visualizations.

grid modernization↗

Predicting Large‐Scale Systematic Missing Pipe Attributes in Water Distribution Networks

Water distribution network (WDN) models are an essential tool used by water utilities for hydraulic analysis. Unfortunately, missing data and insufficient resources often make creating and maintaining these models unfeasible. Existing methods to address missing pipe properties, like sequential imputation for missing values and reconstruction using graph metrics, are designed to accommodate random patterns of missing information and require a significant percentage of the system's attributes to be known. However, these data completeness assumptions do not always align with real‐world scenarios where large sections of the WDN model have missing data. To address this challenge, this study proposes a data‐driven approach for estimating pipe diameter when considering different spatial patterns and degrees of data completeness (i.e., 0%–90%). Using data from 16 WDNs in Kentucky, this study compares the use of machine learning (ML) using topological and geospatial features against an existing deterministic approach. Results demonstrate that WDN models with pipe diameters predicted by the proposed ML method had comparable hydraulic performance to the ground truth models. Moreover, results showed that ML method performance varies between WDNs of differing topological classification. Insights from this study help advance the ability to leverage partial data to create and maintain WDN models amid uncertainty and inadequate resources.

Poff, Jason W. [Oregon State Univ., Corvallis, OR ↗

Buckling Response of a Large-Scale, Seamless, Orthogrid-Stiffened Metallic Cylinder

Results from the buckling test of a compression-loaded 8-ft-diameter seamless (i.e., without manufacturing joints), orthogrid-stiffened metallic cylinder are presented. This test was used to assess the buckling response and imperfection sensitivity characteristics of a seamless cylinder. In addition, the test article and test served as a technology demonstration to show the application of the flow forming manufacturing process to build more efficient buckling-critical structures by eliminating the welded joints that are traditionally used in the manufacturing of large metallic barrels. Pretest predictions of the cylinder buckling response were obtained using a finite-element model that included measured geometric imperfections. The buckling load predicted using this model was 697,000 lb, and the test article buckled at 743,000 lb (6% higher). After the test, the model was revised to account for measured variations in skin and stiffener geometry, nonuniform loading, and material properties. The revised model predicted a buckling load of 754,000 lb, which is within 1.5% of the tested buckling load. In addition, it was determined that the load carrying capability of the seamless cylinder is approximately 28% greater than a corresponding cylinder with welded joints.

Rudd, Michelle Tillotson↗

4D-STEM Coupled with Unsupervised Machine Learning to Reveal at Large-Scale the Microstructural Evolution in Li- and Mn-Rich Cathodes

Li- and Mn-rich (LMR) layered oxides are known to exhibit a thin surface reconstruction layer, which grows during electrochemical cycling in a manner that depends on exposed crystallographic facets, cycling conditions, and electrolyte chemistry. Direct characterization of this layer has traditionally relied on high-resolution electron microscopy, which is inherently limited to small fields of view. Here, we employ four-dimensional scanning transmission electron microscopy (4D-STEM) combined with unsupervised machine-learning clustering to quantitatively map phase distributions over large areas and track their evolution in LMR cathodes during electrochemical aging. Our results show that the surface reconstruction layer consists predominantly of a rocksalt phase, whose thickness varies across different facets following activation cycling and becomes substantially thicker and more uniform during calendar aging. In contrast, a spinel-like phase is observed within the particle bulk. Large-area phase mapping and correlative high-resolution imaging reveal that this spinel-like phase preferentially nucleates at bulk crystallographic defects, including boundaries between 60°-rotated layered domains and associated mixed-phase regions, rather than exclusively at the particle surface. Our findings establish a mechanistic distinction between surface-driven rocksalt formation and bulk-defect-mediated spinel nucleation while demonstrating the unique capability of 4D-STEM to provide statistically robust, mesoscale insight into complex phase-evolution processes in LMR cathodes.

4D-STEM↗

Large-scale cascading of first-order FBG array in a highly multimode coreless fiber using femtosecond laser for distributed thermal sensing

This research focuses on the performance analysis and characterization of a fiber Bragg gratings (FBGs) array, consisting of 10 first-order FBGs inscribed by a femtosecond (FS) laser in a highly multimode coreless fiber. The study evaluates the FBG array's ability to function as a distributed thermal sensing (DTS) platform, with the coreless fiber chosen as the sensing element due to its immunity to dopant migration at high temperatures. The design of a large cascaded first-order FBG array effectively eliminates unwanted harmonic peaks across a wide spectrum range. In contrast, higher-order FBGs introduce limitations due to the overlapping of Bragg peaks with harmonics. The FBG array's performance is evaluated by measuring the reflection spectrum of each grating at different temperatures, showing a high temperature sensitivity of 15.05 pm/°C at a Bragg wavelength of 1606.3 nm, with a linear response in the temperature range of 24 - 1100 °C. The FBG array was designed for a spatial resolution of 5 mm. A mode scrambler in the sensing network is employed, which suppresses multimodal interference, characterizes FBG peak visibility, and stabilizes the interference spectrum. The stability of the FBG array is also assessed over 24 hrs at 1100 °C, and it is observed to be stable during thermal treatment. Heat treatment at 1100°C improves the signal to noise ratio of the FBG array, demonstrating the robustness and suitability of the proposed FBG array on highly multimode coreless fiber as a potential sensing platform for DTS applications in harsh environmental conditions, overcoming the issues of dopant migration presented by dopes silica optical fibers at high temperatures.

47 OTHER INSTRUMENTATION↗