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A Simple Demonstration of Concrete Structural Health Monitoring Framework

  • Sankaran Mahadevan
  • , Vivek Agarwal
  • , Guowei Cai
  • , Paromita Nath
  • , Yanqing Bao
  • , Jose Maria Bru Brea
  • , David Koester
  • , Douglas Adams
  • , David Kosson

Research output: Book/ReportTechnical Report

Abstract

Assessment and management of aging concrete structures in nuclear power plants require a more systematic approach than simple reliance on existing code margins of safety. Structural health monitoring of concrete structures aims to understand the current health condition of a structure based on heterogeneous measurements to produce high confidence actionable information regarding structural integrity that supports operational and maintenance decisions. This ongoing research project is seeking to develop a probabilistic framework for health diagnosis and prognosis of aging concrete structures in a nuclear power plant subjected to physical, chemical, environment, and mechanical degradation. The proposed framework consists of four elements—damage modeling, monitoring, data analytics, and uncertainty quantification. This report describes a proof-of-concept example on a small concrete slab subjected to a freeze-thaw experiment that explores techniques in each of the four elements of the framework and their integration. An experimental set-up at Vanderbilt University’s Laboratory for Systems Integrity and Reliability is used to research effective combination of full-field techniques that include infrared thermography, digital image correlation, and ultrasonic measurement. The measured data are linked to the probabilistic framework: the thermography, digital image correlation data, and ultrasonic measurement data are used for Bayesian calibration of model parameters, for diagnosis of damage, and for prognosis of future damage. The proof-of-concept demonstration presented in this report highlights the significance of each element of the framework and their integration.
Original languageEnglish
Place of PublicationUnited States
DOIs
StatePublished - Mar 2015

Keywords

  • 36 MATERIALS SCIENCE
  • concrete structures
  • damage modeling
  • Data analysis
  • structural health monitoring
  • Uncertainty quantification

INL Publication Number

  • INL/EXT-15-34729

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