Development of statistical design models for concrete sandwich panels with continuous glass-fiber-reinforced polymer shear connectors

Won Hee Kang, Jun Hee Kim

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This article proposes a statistical framework for the development of design models for concrete sandwich panels with glass-fiberreinforced polymer shear grids. The framework is developed by integrating the Bayesian parameter estimation method and the Eurocode-based capacity reduction factor calibration method. In the first part of the framework, probabilistic and deterministic shear flow prediction models are proposed based on 32 experimental data. It is seen that the contribution of glass-fiber-reinforced polymer grids is dominant, although parameters on the geometrical and material properties of insulation and concrete wythes also contribute. Different constant terms for bias correction of the proposed models are proposed according to the insulation type, and the prediction error of the developed model was reduced. In the second part of the framework, the capacity reduction factor for the proposed deterministic formulas is calculated for design purposes. Statistical calibrations for capacity factors are carried out to meet a target reliability level, and the value is estimated to be approximately 0.75 for all proposed models. Further data collection will improve the applicability of the proposed models and clarify quantification of the contribution of parameters.

Original languageEnglish
Pages (from-to)239-254
Number of pages16
JournalAdvances in Structural Engineering
Volume19
Issue number2
DOIs
Publication statusPublished - 2016 Feb

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Glass fibers
Concretes
Polymers
Insulation
Calibration
Shear flow
Parameter estimation
Materials properties
Glass

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Building and Construction

Cite this

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abstract = "This article proposes a statistical framework for the development of design models for concrete sandwich panels with glass-fiberreinforced polymer shear grids. The framework is developed by integrating the Bayesian parameter estimation method and the Eurocode-based capacity reduction factor calibration method. In the first part of the framework, probabilistic and deterministic shear flow prediction models are proposed based on 32 experimental data. It is seen that the contribution of glass-fiber-reinforced polymer grids is dominant, although parameters on the geometrical and material properties of insulation and concrete wythes also contribute. Different constant terms for bias correction of the proposed models are proposed according to the insulation type, and the prediction error of the developed model was reduced. In the second part of the framework, the capacity reduction factor for the proposed deterministic formulas is calculated for design purposes. Statistical calibrations for capacity factors are carried out to meet a target reliability level, and the value is estimated to be approximately 0.75 for all proposed models. Further data collection will improve the applicability of the proposed models and clarify quantification of the contribution of parameters.",
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