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At least 757 records · Page 42

Synchronization-Based Guaranteed-Performance Formation Design for Swarm Systems

Guaranteed-performance formation control for swarm systems with the second-order dynamics is investigated based on the synchronization control strategy. Firstly, a new formation protocol is presented, where the weights of connected edges are adaptively regulated and the performance constraint is imposed. Then, on the basis of the Riccati inequality, sufficient conditions for synchronization-based guaranteed-performance formation are proposed, and an explicit expression of the guaranteed-performance cost is shown, where it is fully distributed to design gain matrices of the formation protocol in the sense that it is independent of global information of swarm systems. Moreover, the whole motion of a swarm system is determined, which is associated with initial states of all agents and formation control vectors. Finally, two numerical examples are shown to demonstrate theoretical conclusions, where the static whole motion and the dynamic whole motion are considered, respectively.

Dang, Hongtao↗

ARES v1.x - Performance Portable Tool to Simulate Supernovae based on Parthenon Framework

Historically, codes for simulating supernovae (such as Arepo, FLASH or LEAFS) have been at the forefront of scientific high-performance computing to the immense computational resources required for full 3D simulations. However, given the shift towards heterogenous HPC architectures, many current-generation codes are at the risk of losing their competitiveness as they are only designed to run on homogeneous CPU-only systems. There exist several efforts to enable these codes for GPU’s, however, these efforts only consider specific architectures or vendors (e.g., implement only CUDA or HIP), limiting themselves to a small range of exascale computing systems. Frameworks such as Kokkos aim to provide a framework which is agnostic of the targeted architecture, enabling the development of performant and portable code. In the Ares code, we develop a performance portable tool to simulate supernovae based on the Parthenon Framework, which in turn uses Kokkos in the background. Here, the Parthenon Framework provides an interface to the underlying mesh-refinement routines, which form the backbone of our code. In addition, we incorporate the already existing Singularity-EOS toolkit to provide us with various equations of state, primarily the Helmholtz equation of state. We also include the JINA Reaclib as a basis for our nuclear network solver. Finally, we implement a gravity solver to complete the required physics. This setup will provide us with a minimal code base to simulate supernova in a similar style to the tried-and-tested Arepo code, but in a futureproof performance portable framework.

Lim, Hyun↗

Spectral Efficiency and Tandem Performance Calculators [SWR-24-92]

The Spectral Efficiency and Tandem Performance Calculators allow users to test material types for use in tandem photovoltaic devices to better understand if a given material could work well. The Spectral Efficiency (SE) calculator takes a set of current vs voltage (I-V) and quantum efficiency (QE) data along with a spectrum input and plots the spectral efficiency of the cells represented by the datasets for the spectrum provided. The Tandem Performance calculator uses the calculated spectral efficiency of top and bottom cells and the transmission data of the top cell to calculate performance metrics for a tandem device in either a two or four terminal architecture. The SE and Tandem Performance calculators are based on the following publication: Yu, Z., Leilaeioun, M. & Holman, Z. Selecting tandem partners for silicon solar cells. Nat Energy 1, 16137 (2016).

Warren, Emily↗

MUPPET: An automated OpenMP mutation testing framework for performance optimization

MUPPET is a tool for OpenMP programs that identifies program modifications, called mutations, aimed at improving program performance. Existing performance optimization techniques, including profiling-based and auto-tuning techniques, fail to indicate program modifications at the source level thus preventing their portability across compilers. MUPPET aims to help HPC developers reason about performance defects and missed opportunities to improve performance at the source code level.

Parasyris, Konstantinos↗

HipBone: A performance-portable graphics processing unit-accelerated C++ version of the NekBone benchmark

We present hipBone, an open-source performance-portable proxy application for the Nek5000 (and NekRS) computational fluid dynamics applications. HipBone is a fully GPU-accelerated C++ implementation of the original NekBone CPU proxy application with several novel algorithmic and implementation improvements which optimize its performance on modern fine-grain parallel GPU accelerators. Our optimizations include a conversion to store the degrees of freedom of the problem in assembled form in order to reduce the amount of data moved during the main iteration and a portable implementation of the main Poisson operator kernel. We demonstrate near-roofline performance of the operator kernel on three different modern GPU accelerators from two different vendors. We present a novel algorithm for splitting the application of the Poisson operator on GPUs which aggressively hides MPI communication required for both halo exchange and assembly. Our implementation of nearest-neighbor MPI communication then leverages several different routing algorithms and GPU-Direct RDMA capabilities, when available, which improves scalability of the benchmark. We demonstrate the performance of hipBone on three different clusters housed at Oak Ridge National Laboratory, namely, the Summit supercomputer and the Frontier early-access clusters, Spock and Crusher. Our tests demonstrate both portability across different clusters and very good scaling efficiency, especially on large problems.

Computer Science↗

Investigation of the effects of passive pre-chamber nozzle pattern and ignition system on engine performance and emissions

The impact of passive pre-chamber (PC) internal volume, nozzle hole pattern (i.e. with and without a central axial nozzle), and PC igniter plug type on performance and emissions was investigated in an optically accessible, single-cylinder, gasoline research engine. The two PC igniter plugs investigated were a conventional inductive coil spark plug and a nanosecond repetitively pulsed (NRP) plasma discharge system previously demonstrated to accelerate early flame propagation. The baseline PC design featured a funnel shaped internal volume with a PC tip that contained six radial nozzles and a larger central axial nozzle. Two additional PC tip geometries were evaluated where either the baseline internal volume was increased or the axial nozzle was removed and the radial nozzle diameters were increased. A sweep of charge equivalence ratios ( ϕ) from nearly stoichiometric to the lean limit was performed for a fixed engine speed (1300 revolutions per minute), and engine load (3.5 bar gross indicated mean effective pressure). Time-resolved PC and main chamber (MC) pressure data as well as MC emissions data were collected to analyze engine performance and emissions characteristics. Combustion in the MC was further investigated using high-speed excited methylidyne radical (CH*) chemiluminescence imaging. Collected results highlighted that while all PC tips and ignition systems exhibited similar performance and emissions down to ϕ = 0.8, relevant differences in thermal efficiency and emissions for leaner charge mixtures were observed, with the results highly dependent on the nozzle pattern and ignition system. Major deviations were correlated to preferential de-pressurization of the PC through the axial nozzle for lean conditions that was not observed for mixture conditions closer to stoichiometric. Results show that a combination of radial and axial nozzle patterns in the PC extended lean-stability limits at the low-load condition evaluated. Further benefits were observed with the use of NRP ignition systems due to faster combustion within the PC volume provided that the volume was sufficiently large.

Di Sabatino, Francesco↗

Regional-scale fault-to-structure earthquake simulations with the EQSIM framework: Workflow maturation and computational performance on GPU-accelerated exascale platforms

Continuous advancements in scientific and engineering understanding of earthquake phenomena, combined with the associated development of representative physics-based models, is providing a foundation for high-performance, fault-to-structure earthquake simulations. However, regional-scale applications of high-performance models have been challenged by the computational requirements at the resolutions required for engineering risk assessments. The EarthQuake SIMulation (EQSIM) framework, a software application development under the US Department of Energy (DOE) Exascale Computing Project, is focused on overcoming the existing computational barriers and enabling routine regional-scale simulations at resolutions relevant to a breadth of engineered systems. This multidisciplinary software development—drawing upon expertise in geophysics, engineering, applied math and computer science—is preparing the advanced computational workflow necessary to fully exploit the DOE’s exaflop computer platforms coming online in the 2023 to 2024 timeframe. Achievement of the computational performance required for high-resolution regional models containing upward of hundreds of billions to trillions of model grid points requires numerical efficiency in every phase of a regional simulation. This includes run time start-up and regional model generation, effective distribution of the computational workload across thousands of computer nodes, efficient coupling of regional geophysics and local engineering models, and application-tailored highly efficient transfer, storage, and interrogation of very large volumes of simulation data. This article summarizes the most recent advancements and refinements incorporated in the workflow design for the EQSIM integrated fault-to-structure framework, which are based on extensive numerical testing across multiple graphics processing unit (GPU)-accelerated platforms, and demonstrates the computational performance achieved on the world’s first exaflop computer platform through representative regional-scale earthquake simulations for the San Francisco Bay Area in California, USA.

58 GEOSCIENCES↗

Low-abundance populations distinguish microbiome performance in plant cell wall deconstruction

Abstract Background Plant cell walls are interwoven structures recalcitrant to degradation. Native and adapted microbiomes can be particularly effective at plant cell wall deconstruction. Although most understanding of biological cell wall deconstruction has been obtained from isolates, cultivated microbiomes that break down cell walls have emerged as new sources for biotechnologically relevant microbes and enzymes. These microbiomes provide a unique resource to identify key interacting functional microbial groups and to guide the design of specialized synthetic microbial communities. Results To establish a system assessing comparative microbiome performance, parallel microbiomes were cultivated on sorghum ( Sorghum bicolor L. Moench) from compost inocula. Biomass loss and biochemical assays indicated that these microbiomes diverged in their ability to deconstruct biomass. Network reconstructions from gene expression dynamics identified key groups and potential interactions within the adapted sorghum-degrading communities, including Actinotalea , Filomicrobium , and Gemmatimonadetes populations. Functional analysis demonstrated that the microbiomes proceeded through successive stages that are linked to enzymes that deconstruct plant cell wall polymers. The combination of network and functional analysis highlighted the importance of cellulose-degrading Actinobacteria in differentiating the performance of these microbiomes. Conclusions The two-tier cultivation of compost-derived microbiomes on sorghum led to the establishment of microbiomes for which community structure and performance could be assessed. The work reinforces the observation that subtle differences in community composition and the genomic content of strains may lead to significant differences in community performance.

59 BASIC BIOLOGICAL SCIENCES↗

Performing k eff Validation of As-Loaded Criticality Safety Calculations Using UNF-ST&DARDS: Applicable Experiment Selection

The general method for performing validation of as loaded criticality safety calculations using UNF ST&DARDS is presented in a paper by Clarity, which includes a description of the UNF-ST&DARDS system. Proof-of-principle analyses were performed in the summer of 2019 for MPC-32 dual purpose canisters (DPCs) containing pressurized water reactor (PWR) fuel assemblies. Summaries of these results are presented in this and a companion paper for this conference. The current paper describes the TSUNAMI-IP calculations performed to select applicable experiments for validation of 11 MPC-32 DPCs. The companion paper discusses the TSUNAMI-3D calculations used to generate sensitivity data to support the experiment selections discussed here. Experiment selection is based on the sensitivity/uncertainty (S/U) methods used to validate criticality safety calculations of as-loaded DPCs containing pressurized water reactor (PWR) spent nuclear fuel (SNF). This process has been demonstrated and is summarized in this paper. The approach is similar to that used in NUREG/CR-7109, which provides an approach for validation of PWR burnup credit (BUC), including major and minor actinides and major fission products. The premise of S/U-based validation is that applicable experiments—those having a similar bias to a given application system—will have similar sensitivities for each isotope and reaction in the two systems. It is assumed that cross sections with larger uncertainties are more likely to contain data errors which contribute to the bias. The integral index c k thus propagates the system sensitivities with the nuclear covariance data to calculate a correlation coefficient representing the similarity of the two systems. In this work, a c k value of 0.8 or higher is interpreted as identifying an experiment with sufficient similarity for use in validation. This paper presents a brief summary of the characteristics of the 11 MPC-32 DPCs used in the proof of-principle analysis for as-loaded criticality safety calculation validation and an overview of the critical experiment suite with which each of these DPC models was compared. A summary and discussion of c k results is also presented, followed by conclusions and a discussion of future work to be performed for validation of UNF ST&DARDS as-loaded criticality safety calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Performing k eff Validation of As-Loaded Criticality Safety Calculations Using UNF-ST&DARDS: Sensitivity Calculations

The general method for performing validation of as loaded criticality safety calculations using UNF ST&DARDS is presented in a paper by Clarity, which includes a description of the UNF-ST&DARDS system. Proof-of-principle analyses were performed in the summer of 2019 for MPC-32 dual purpose canisters (DPCs) containing pressurized water reactor (PWR) fuel assemblies. Summaries of these results are presented in this and a companion paper for this conference. The current paper describes the TSUNAMI-3D calculations performed to generate sensitivity data, and the companion paper discusses the selection of critical experiments applicable for validation of the 11 MPC-32 DPCs considered. The generation of sensitivity data for as-loaded spent nuclear fuel (SNF) DPCs is a challenge given the detailed model of the fuel compositions generated by UNF ST&DARDS. Each fuel assembly is modeled with its own irradiation history in 18 axial nodes, unless the fuel assembly is damaged and thus considered as fresh by design basis. This results in a set of 576 fuel compositions, each of which must be processed separately in a multigroup (MG) calculation. Therefore, a continuous-energy (CE) TSUNAMI-3D method was chosen to alleviate this challenge. Two CE TSUNAMI-3D methods are available in SCALE 6.2.3: the iterated fission probability (IFP) and contribution-linked eigenvalue sensitivity/uncertainty estimation via track-length importance characterization (CLUTCH). Since the IFP method is not feasible because of memory requirements associated with its implementation in SCALE, the CLUTCH method was selected for these calculations. CLUTCH has been implemented in SCALE in parallel, allowing long calculations to be performed in reasonable timeframes. The two primary user inputs necessary for CLUTCH calculations are the F*(r) mesh and the number of latent generations used in determining the F*(r) function. This F*(r) function is used as the importance function for fission chains originating in a given volume element (voxel), and it is calculated using the IFP method in the skipped generations. A large number of skipped generations is thus required to ensure accurate calculation of this importance function. In these calculations, 500 generations were used to calculate the F*(r) function. For more information regarding the calculation of F*(r), see Jones [4]. The remainder of this paper is focused on the selection of the F*(r) mesh and the number of latent generations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Coupled Thermal-Hydraulic and Fuel Performance Simulations of the TWIST LOCA Commissioning Test Series in TREAT

As the nuclear industry is looking to increase light water reactor (LWR) burnup limits, Idaho National Laboratory has developed an experiment vehicle for the Transient Reactor Test Facility (TREAT) to support high burnup fuel safety testing. One of the main purposes of this vehicle, known as the Transient Water Irradiation System for TREAT (TWIST), is to perform in-pile loss-of-coolant accident (LOCA) experiments on high burnup LWR fuel to investigate phenomena termed fuel fragmentation, relocation, and dispersal (FFRD). Prior to performing experiments on high burnup fuel specimens, a commissioning test series will be performed. The main purpose of the Loss-of-Coolant-Commissioning (LOC-C) test series is to qualify the TWIST device and validate the power coupling between TREAT and the TWIST fuel rod as well as validation of the thermal-hydraulic and fuel performance simulation predictions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Using spatio-temporal graph neural networks to estimate fleet-wide photovoltaic performance degradation patterns

Accurate estimation of photovoltaic (PV) system performance is crucial for determining its feasibility as a power generation technology and financial asset. PV-based energy solutions offer a viable alternative to traditional energy resources due to their superior Levelized Cost of Energy (LCOE). A significant challenge in assessing the LCOE of PV systems lies in understanding the Performance Loss Rate (PLR) for large fleets of PV systems. Estimating the PLR of PV systems becomes increasingly important in the rapidly growing PV industry. Precise PLR estimation benefits PV users by providing real-time monitoring of PV module performance, while explainable PLR estimation assists PV manufacturers in studying and enhancing the performance of their products. However, traditional PLR estimation methods based on statistical models have notable drawbacks. Firstly, they require user knowledge and decision-making. Secondly, they fail to leverage spatial coherence for fleet-level analysis. Additionally, these methods inherently assume the linearity of degradation, which is not representative of real world degradation. To overcome these challenges, we propose a novel graph deep learning-based decomposition method called the Spatio-Temporal Graph Neural Network for fleet-level PLR estimation (PV-stGNN-PLR). PV-stGNN-PLR decomposes the power timeseries data into aging and fluctuation components, utilizing the aging component to estimate PLR. PV-stGNN-PLR exploits spatial and temporal coherence to derive PLR estimation for all systems in a fleet and imposes flatness and smoothness regularization in loss function to ensure the successful disentanglement between aging and fluctuation. We have evaluated PV-stGNN-PLR on three simulated PV datasets consisting of 100 inverters from 5 sites. Experimental results show that PV-stGNN-PLR obtains a reduction of 33.9% and 35.1% on average in Mean Absolute Percent Error (MAPE) and Euclidean Distance (ED) in PLR degradation pattern estimation compared to the state-of-the-art PLR estimation methods.

14 SOLAR ENERGY↗

Exogenous erythropoietin increases hematological status, fat oxidation, and aerobic performance in males following prolonged strenuous training

Abstract This study investigated the effects of EPO on hemoglobin (Hgb) and hematocrit (Hct), time trial (TT) performance, substrate oxidation, and skeletal muscle phenotype throughout 28 days of strenuous exercise. Eight males completed this longitudinal controlled exercise and feeding study using EPO (50 IU/kg body mass) 3×/week for 28 days. Hgb, Hct, and TT performance were assessed PRE and on Days 7, 14, 21, and 27 of EPO. Rested/fasted muscle obtained PRE and POST EPO were analyzed for gene expression, protein signaling, fiber type, and capillarization. Substrate oxidation and glucose turnover were assessed during 90‐min of treadmill load carriage (LC; 30% body mass; 55 ± 5% V̇O 2 peak) exercise using indirect calorimetry, and 6‐6‐[ 2 H 2 ]‐glucose PRE and POST. Hgb and Hct increased, and TT performance improved on Days 21 and 27 compared to PRE ( p < 0.05). Energy expenditure, fat oxidation, and metabolic clearance rate during LC increased ( p < 0.05) from PRE to POST. Myofiber type, protein markers of mitochondrial biogenesis, and capillarization were unchanged PRE to POST. Transcriptional regulation of mitochondrial activity and fat metabolism increased from PRE to POST ( p < 0.05). These data indicate EPO administration during 28 days of strenuous exercise can enhance aerobic performance through improved oxygen carrying capacity, whole‐body and skeletal muscle fat metabolism.

Drummer, Devin J.↗

Examining the Effects of Oxygen Doping on SRF Cavity Performance

Superconducting radiofrequency (SRF) cavities are resonators with extremely low surface resistance that enable accelerating cavities to have extremely high quality factors (Q₀). High (Q₀) decreases the capital required to keep accelerators cold by reducing power loss. The performance of SRF cavities is largely governed by the surface composition of the first 100 nm of the cavity surface. Impurities such as oxygen and nitrogen have been observed to yield high Q₀, but their precise roles are still being studied. Here, we compare the performance of cavities doped with nitrogen and oxygen in terms of fundamental material properties to understand how these impurities affect performance. This enables us to have further insight into the underlying mechanisms that enable these surface treatments to yield high Q₀ performance.

43 PARTICLE ACCELERATORS↗

SURFACE ROUGHNESS REDUCTION AND PERFORMANCE OF Nb3Sn FILM FOR SRF APPLICATIONS

Nb3Sn offers better RF performance (Q and Eacc) than Nb at any given temperature because of its superior superconducting properties. The potential deployment of Nb3Sn-coated SRF cavities at 4 K, delivering similar performance to that of Nb cavities at 2 K, will be a transformational technology to enable new classes of SRF accelerator applications. A clean and smooth surface can enhance the performance of the Nb3Sn-coated cavity, typically, the attainable acceleration gradient. The reduction of surface roughness is often linked with a correlative reduction in average coating thickness and grain size. A new approach to enhance the nucleation centers using the pre-deposition of Sn on Nb is introduced for surface roughness reduction. Besides Sn supply's careful tuning, the temperature profiles were varied to engineer the coating surface with reduced roughness as low as ~40 nm in 20 µm × 20 µm AFM scans, one-third that of the typical coating. Electropolishing of coated sample shows surface a clear surface smoothening. A few sets of coating parameters were used to coat 1.3 GHz sin-gle-cell cavities to understand the effects of roughness variation on the RF performance. This presentation discusses ways to reduce surface roughness with results from a systematic analysis of the samples and Nb3Sn-coated single-cell cavities.

Pudasaini, Uttar↗

Leveraging Community and Author Context to Explain the Performance and Bias of Text-Based Deception Detection Models

Deceptive news posts shared in online communities can be detected with NLP models, and much recent research has focused on the development of such models. In this work, we use characteristics of online communities and authors --- the context of how and where content is posted --- to explain the performance of a neural network deception detection model and identify sub-populations who are disproportionately affected by model accuracy or failure. We examine who is posting the content, and where the content is posted to. We find that while author characteristics are better predictors of deceptive content than community characteristics, both characteristics are strongly correlated with model performance. Traditional performance metrics such as F1 score may fail to capture poor model performance on isolated sub-populations such as specific authors, and as such, more nuanced evaluation of deception detection models is critical.

machine learning (ML), machine learning explanatio↗

Performance Understanding and Analysis for Exascale Data Management Workflows (Collaboration)

The general approach of the MONA project is depicted in Figure 1. The figure shows performance monitoring applied to an I/O workflow associated with a scientific simulation, with online measurements captured from this workflow informing methods for workflow reconfiguration and dynamic adjustment. The goal is to maintain suitable levels of Quality of Service for workflow execution, by understanding the underlying causes of workflow performance and behavior. One outcome will be workflow performance models able to characterize realistic workflows. Another outcome will be performance ‘mini-apps’ implementing such workflow behavior. Out of scope for this project are advanced methods for online workflow control.

97 MATHEMATICS AND COMPUTING↗

Filtration Performance Results: Sierra Peaks Material No. 4

Sandia National Laboratories (SNL) assessed the filtration performance of materials from Sierra Peaks to identify alternatives which may perform similarly to materials used in FDA-approved N95 respirators. This work is meant to characterize the aerosol performance of materials to give Sierra Peaks information for them to determine if they elect to submit masks made using these materials for follow-on N95 certification testing at an accredited facility. The R&D testbed used is a large-scale filtration system designed to test commercial filter boxes. System modifications were performed to simulate, where possible, parameters defined by the National Institute for Occupational Safety and Health (NIOSH) for certification of filter materials for N95 respirators (NIOSH 2019). The system is a pull-through design. Air enters through a Laminar Flow Element (LFE) and the volumetric flow is measured based on the pressure drop across the LFE. Pressure is measured via a Pressure Transducer (PT). The air then passes through a High Efficiency Particulate Air (HEPA) filter to purge the air of ambient airborne particulates. Test aerosol is injected into the flow shortly after and mixing is induced via a coarse mesh. The airflow is allowed to fully develop prior to arriving at the test section. The aerosol then passes through the test material mounted in a box in the test section. Pressure drop across the test article is measured and aerosol sampling probes measure the aerosol concentrations upstream and downstream of the sample. The air passes through a second HEPA filter prior to being exhausted to ambient by a blower. A Topas aerosol generator is used to produce the test aerosol from Sodium Chloride (NaC1) dissolved in deionized (DI) water. Generated aerosol passes through a heated mixing chamber and a desiccant dryer to produce nanosized solid-state particulates. A dilution loop allows for the aerosol concentration to be regulated. The aerosol sampling probes upstream and downstream of the test section are aligned with the flow path. These are ducted directly to the aerosol sizing and counting instruments. A Laser Aerosol Spectrometer (LAS) was used for data collection in the original configuration of the system and was also used for initial testing in this project. Because the lower measurement range for the LAS is 90 nanometers (nm), the LAS was switched out for a more complicated Scanning Mobility Particle Sizer (SMPS) spectrometer system. The SMPS is comprised of an Electrostatic Classifier (EC), Differential Mobility Analyzer (DMA), and a Condensation Particle Counter (CPC). This enabled data collection at 75 nm, the particle size called out in the NIOSH guidelines.

36 MATERIALS SCIENCE↗