Development of New Predictive Stability and Performance Metrics for Real-time Hybrid Simulation (NEES-2013-1205)

By Amin Maghareh1, Shirley Dyke1, Fangshu Lin1, Arun Prakash1

1. Purdue University

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Abstract

Title: Development of New Predictive Stability and Performance Metrics for Real-time Hybrid Simulation (NEES-2013-1205)

Year Of Curation: 2014

Description: In this study, new stability and performance indicators, predictive stability indicator (PSI) and predictive performance indicator (PPI), are proposed to predict the stability margin and performance of an RTHS system prior to its implementation. PSI and PPI assess how transfer system dynamics and computational/communication delays, which are the significant sources of systematic experimental error in RTHS, destabilize and distort RTHS responses. Moreover, along with the RTHS stability switch criterion, predictive stability and performance indicators are used to successfully conduct an RTHS experiment.

Award: http://www.nsf.gov/awardsearch/showAward?AWD_ID=1136075

PIs & CoPIs: Amin Maghareh, Shirley Dyke, Fangshu Lin, Arun Prakash

Dates: June 01, 2013 - November 25, 2013

Organizations: Purdue University

Facilities: Purdue University at West Lafayette, IN, United States

Sponsor: NSF - CCF - 1136075

Keywords: --

Publications: Jeffrey Rhoads, "Establishing Predictive Indicators for Stability and Performance of SDOF Real-time Hybrid Simulation" 

Cite this work

Researchers should cite this work as follows:

  • Amin Maghareh; Shirley Dyke; Fangshu Lin; Arun Prakash (2017), "Development of New Predictive Stability and Performance Metrics for Real-time Hybrid Simulation (NEES-2013-1205)," https://datacenterhub.org/resources/14650.

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