Pioneer 7 TDS performance evaluation
Performance evaluation of near-earth and deep space tracking facilities for Pioneer 7 space probe
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Results for “performance evaluation”
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.
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Comparative Performance Evaluation of High-performance Data Transfer Tools
Data transfer in wide-area networks has been long studied in different contexts, from data sharing among data centers to online access to scientific data. Many software tools and platforms have been developed to facilitate easy, reliable, fast, and secure data transfer over wide area networks, such as GridFTP, FDT, bbcp, mdtmFTP, and XDD. However, few studies have shown the full capabilities of existing data transfer tools from the perspective of whether such tools have fully adopted state-of-the-art techniques through meticulous comparative evaluations. In this paper, we evaluate the performance of the four highperformance data transfer tools (GridFTP, FDT, mdtmFTP, and XDD) in various environments. Our evaluation suggests that each tool has strengths and weaknesses. FDT and GridFTP perform consistently in diverse environments. XDD and mdtmFTP show improved performance in limited environments and datasets during our evaluation. Unlike other studies on data transfer tools, we also evaluate the predictability of the tools' performance, an important factor for scheduling different stages of science workflows. Performance predictability also helps in (auto)tuning the configurable parameters of the data transfer tool. We apply statistical learning techniques such as linear/polynomial regression, and k-nearest neighbors (kNN), to assess the performance predictability of each tool using its control parameters. Our results show that we can achieve good prediction performance for GridFTP and mdtmFTP using linear regression and kNN, respectively.
Nadig, Deepak↗
Performance Evaluation of an Advanced Distributed Energy Resource Management Algorithm
This paper presents performance evaluation of a new distributed energy resource management system (DERMS) algorithm via an advanced hardware-in-the-loop (HIL) platform. The HIL platform provides realistic testing in a laboratory environment, including the accurate modeling of sub-transmission and distribution networks, the DERMS software controller, and 84 power hardware solar photovoltaic (PV) inverters, standard communication protocols, and a capacitor bank controller. The DERMS algorithm is also called, Grid-Optimization of Solar (GO-Solar) platform which includes predictive state estimation (PSE) and online multiple objective optimization (OMOO) to dispatch the legacy devices and distributed energy resources (e.g., PV). The voltage regulation performance is evaluated under three scenarios, volt-var smart inverter (baseline), and DERMS control for 100% and 30% of PV. The results show that controlling 30% of PV systems with the GO-Solar platform may provide the best balance of control performance and implementation cost.
distributed energy resource management system (DER↗
NREL Evaluates Performance of Fast-Charge Electric Buses
This real-world performance evaluation is designed to enhance understanding of the overall usage and effectiveness of electric buses in transit operation and to provide unbiased technical information to other agencies interested in adding such vehicles to their fleets. Initial results indicate that the electric buses under study offer significant fuel and emissions savings. The final results will help Foothill Transit optimize the energy-saving potential of its transit fleet. NREL's performance evaluations help vehicle manufacturers fine-tune their designs and help fleet managers select fuel-efficient, low-emission vehicles that meet their bottom line and operational goals. help Foothill Transit optimize the energy-saving potential of its transit fleet. NREL's performance evaluations help vehicle manufacturers fine-tune their designs and help fleet managers select fuel-efficient, low-emission vehicles that meet their bottom line and operational goals.
33 ADVANCED PROPULSION SYSTEMS↗
DRACS thermal performance evaluation for FHR
Direct Reactor Auxiliary Cooling System (DRACS) is a passive decay heat removal system proposed for the Fluoride-salt-cooled High-temperature Reactor (FHR) that combines coated particle fuel and a graphite moderator with a liquid fluoride salt as the coolant. The DRACS features three coupled natural circulation/convection loops, relying completely on buoyancy as the driving force. These loops are coupled through two heat exchangers, namely, the DRACS Heat Exchanger and the Natural Draft Heat Exchanger. In addition, a fluidic diode is employed to minimize the parasitic flow into the DRACS primary loop and correspondingly the heat loss to the DRACS during normal operation of the reactor, and to keep the DRACS ready for activation, if needed, during accidents. To help with the design and thermal performance evaluation of the DRACS, a computer code using MATLAB has been developed. This code is based on a one-dimensional formulation and its principle is to solve the energy balance and integral momentum equations. By discretizing the DRACS system in the axial direction, a bulk mean temperature is assumed for each mesh cell. The temperatures of all the cells, as well as the mass flow rates in the DRACS loops, are predicted by solving the governing equations that are obtained by integrating the energy conservation equation over each cell and integrating the momentum conservation equation over each of the DRACS loops. In addition, an intermediate heat transfer loop equipped with a pump has also been modeled in the code. This enables the study of flow reversal phenomenon in the DRACS primary loop, associated with the pump trip process. Experimental data from a High-Temperature DRACS Test Facility (HTDF) are not available yet to benchmark the code. A preliminary code validation is performed by using natural circulation experimental data available in the literature, which are as closely relevant as possible. The code is subsequently applied to the HTDF that is under construction at the Ohio State University.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Performance Evaluation of Data-Enhanced Hierarchical Control for Grid Operations
This paper presents a hardware-in-the-loop (HIL) simulation to evaluate the performance of voltage regulation of Data-Enhanced Hierarchical Control (DEHC). This DEHC uses an advanced distribution management system (ADMS) for grid operations to control legacy and grid-edge devices and coordinate with distributed energy management systems (DERMS) to manage high penetrations of photovoltaics (PV) on a utility distribution system. The HIL platform provides realistic laboratory testing, including accurate modeling (legacy devices, grid-edge devices, and PV) of the real-world distribution system from a utility partner, a real controller (ADMS), software controller DERMS, hardware grid-edge devices, and standard communications protocols. The test results demonstrate functionalities of the integrated platform and the performance of voltage regulation of the coordinated control systems. Based on laboratory testing, the utility can set up the same grid-automation system to manage DERs, legacy devices, and grid-edge devices to achieve their system-level control and operation objectives (e.g., voltage regulation), thus de-risking potential issues such as instability for field deployment.
41 EE - Solar Energy Technologies Office (EE-4S)↗
Simulation-based Performance Evaluation of Model Predictive Control for Building Energy Systems
The performance of model predictive control (MPC) can be significantly affected by different choices of controller parameters such as the time intervals for model discretization and control sampling. Due to the lack of a systematic understanding on how these parameters affect control performance, they are usually selected arbitrarily in practice.In this paper, the combined impacts of selected time intervals for model discretization and control sampling on the performance of MPC are comprehensively investigated for the first time through detailed simulations. Specifically, a typical MPC strategy is first designed to improve building operations based on a reduced-order model of building dynamics. Then, the performance of the designed MPC is evaluated against different choices of time intervals for model discretization and control sampling on a simulated office building. The detailed simulation results reveal that the time interval for model discretization has a much greater influence on the performance of MPC than the time interval for control sampling. Although the time interval for control sampling usually receives more attentions in practice, it turns out that the time interval for model discretization affects the prediction performance, cost saving, and computation time simultaneously and more significantly. Therefore, the simulation-based performance evaluation presented here sheds light on the impacts of different time intervals and facilitates their selection for practical applications of MPC to building operations
Huang, Sen↗
Performance evaluation system for inertial navigation equipment
Testing system studies inertial characteristics of gyroscopic devices. System consisting of instrument support package, dynamic test table, torque control electronics, and real-time computer evaluates performance of prototype gyroscopic strapdown units in inertial-grade attitude-reference systems. System is applicable to commercial aircraft.
Mc Kern, R. A.↗
Performance evaluation of candidate strapdown and gimballed systems using nominal and abort shuttle trajectories
Space shuttle guidance, evaluating performance of strapdown and gimballed systems by nominal and abort trajectories
Mckern, R. A.↗
Performance evaluation of the three-point angular correlation function
In recent years, we have observed an increase in the diversity of the processors ecosystem. Different designs and architectures are being studied based on their performance and power characteristics. While using benchmarks for this purpose allows for reproducibility and easy understanding of the results, using real scientific applications allows researchers to realize the actual implications of each design on the overall performance of their codes. This paper analyzes the performance of different implementations of a three-point angular correlation function. This function is used in the study of Large-Scale Distribution of galaxies in a variety of computational platforms. The function is based on histogram construction and presents a large computational cost. This cost dramatically increases with the size of the datasets. We have considered two different GPUs, a set of x86 Intel machines (multi- and many-core), ARM chipsets, as well as an FPGA. We first study the best possible implementation for each platform in terms of time to solution. We then compare the power used by those platforms for a predefined number of datasets. Energy is one of the main constraints that computer architects are facing nowadays. The results will be used to evaluate the performance of this function considering those two targets – time and energy – for those platforms and to analyze the suitability of each of those platforms for this specific problem.
Computer Science↗
Capturing provenance as a diagnostic tool for workflow performance evaluation and optimization
In extreme-scale computing environments such as the DOE Leadership Computing Facilities scientific workflows are routinely used to coordinate software processes for the execution of complex, computational applications that perform in-silico experiments. Monitoring the performance of workflows without also simultaneously tracking provenance is not sufficient to understand variations between runs, configurations, versions of a code, and between changes in an implemented stack, and systems, i.e. the variability of performance metrics data in their historical context. We take a provenance-based approach and demonstrate that provenance is useful as a tool for evaluating and optimizing workflow performance in extreme-scale HPC environments. We present Chimbuko, a framework for the analysis and visualization of the provenance of performance. Chimbuko implements a method for the evaluation of workflow performance from multiple components that enables the exploration of performance metrics data at scale.
97 MATHEMATICS AND COMPUTING↗
Performance Evaluation of Distributed Energy Resource Management via Advanced Hardware-in-the-Loop Simulation
This poster provides an overview of the performance evaluation of distributed energy resource management via advanced hardware-in-the-loop simulation.
DER↗
Aftertreatment protocols for catalyst characterization and performance evaluation: low-temperature oxidation, storage, three-way, and NH3-SCR catalyst test protocols
A set of standardized and realistic aftertreatment catalyst test protocols have been developed by the Advanced Combustion and Emission Control Technical Team in support of the U.S.DRIVE Partnership. The protocols are intended to accelerate the pace of aftertreatment catalyst innovation by enabling the accurate evaluation and comparison of aftertreatment catalyst performance data from various testing and research facilities to maximize the impact of discovery-phase research occurring across the nation. The protocols address a need identified by the Partnership’s industry partners for consistent and accurate metrics for aftertreatment catalyst evaluation and comparison. The protocols consist of a set of standardized requirements and test procedures that sufficiently capture the performance capability of a catalyst technology in a manner that is adaptable in various laboratories. The protocols provide a detailed description of the necessary reactor system, the steps for achieving a desired aged state of the catalyst, all necessary sample pretreatment to be performed prior to testing, and realistic test conditions for evaluating performance. This article details four low-temperature catalyst test protocols applicable to (1) oxidation catalysts, (2) passive storage (and release) catalysts, (3) three-way catalysts, and (4) NH3-SCR catalysts. The catalyst test protocol descriptions are presented in five (5) sections: protocol general guidelines and the four individual catalyst test protocol descriptions. The general guidelines plus the individual protocol description forms the complete low-temperature catalyst test protocol for the application.
Emission control, Three-way catalyst, oxidation, S↗
Performance Evaluation of a Two-Dimensional Flood Model on Heterogeneous High-Performance Computing Architectures
This paper describes the implementation of a two-dimensional hydrodynamic flood model with two different numerical schemes on heterogeneous high-performance computing architectures. Both schemes were able to solve the nonlinear hyperbolic shallow water equations using an explicit upwind first-order approach on finite differences and finite volumes, respectively, and were conducted using MPI and CUDA. Four different test cases were simulated on the Summit supercomputer at Oak Ridge National Laboratory. Both numerical schemes scaled up to 128 nodes (768 GPUs) with a maximum 98.2x speedup of over 1 GPU. The lowest run time for the 10 day Hurricane Harvey event simulation at 5 meter resolution (272 million grid cells) was 50 minutes. GPUDirect communication proved to be more convenient than the standard communication strategy. Both strong and weak scaling are shown.
Sharif, Md Bulbul↗
Performance Evaluation of Vertical Federated Machine Learning Against Adversarial Threats on Wide-Area Control System: Preprint
Federated machine learning (FL) is gaining significant popularity to develop cybersecurity solutions in power grids because of its advanced capability to support decentralized data handing at local devices, its privacy preservation, and its low-bandwidth requirement. However, the evolving adversarial machine learning (AML) threats raise significant concerns for the cybersecurity of FL architectures. The FL-based split neural network (SplitNN) achieves high performance through the decentralized training of local neural network models while preserving data privacy across multiple entities. In this paper, we propose a methodology for evaluating the performance of a vertical FLbased anomaly detector against different types of AML attacks, including denial-of-service attacks, adversarial data injection attacks, and replay attacks on the trained local models deployed in the grid network. For a case study, we consider the modified IEEE 13-bus system, and we develop SplitNN-based binary and multiclass classification models to detect, locate, and identify different types of data integrity attacks on the volt-watt control with two pooling layers: maximum pooling and AvgPool. Our experimental results, computed through performance metrics, reveal that the severity of these AML attacks varies with the integrated pooling mechanism, the type of classification model, and the nature of the cyberattack. Further, the AML attacks negatively impacted the prediction time per sample for the pretrained SplitNN during the online testing.
adversarial threats↗
Design and performance evaluation of a 1000-year evapotranspiration-capillary surface barrier
Not Available
Zhang, Zhuanfang Fred↗