Pushover analysis is a non-linear static method used for the seismic assessment of structures. The simplicity, efficiency in modelling and less computational time make this method popular. Lot of researchers has worked on conventional pushover analysis and after knowing deficiencies of the method have made efforts to improve it. From the literature, it is evident that actual experimental test results carried out so as to verify the analytically obtained pushover results are hardly available. Stress–strain models adopted for modelling of concrete and reinforcement greatly influences both the ultimate load and ultimate displacement for the structure under pushover loads. This paper focuses on assessment of pushover response parameters using response surface methodology (RSM). A three-storied RCC framed structure is tested and the experimental pushover results are available. Uncertain parameters considered include the concrete strength, steel strength, reinforcement cover and hinge location, which are randomly generated by performing stochastic analysis and their effect on responses, which include base shear and displacement is studied. Using Monte Carlo simulation in Sap-2000 design matrix is generated. Modelling and analysis of response parameters are carried out using RSM so as to obtain the characteristics of the pushover curve. The effect of material strength variation, hinge locations and hinge lengths, geometric modelling have been studied, incorporating confined model for concrete. The coefficients and equations that can be used to predict the responses are carried out by performing multiple regression analysis. The validation results demonstrated that the confined model is better than the unconfined.


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    Title :

    Assessment of Pushover Response Parameters Using Response Surface Methodology


    Additional title:

    Lecture Notes in Civil Engineering




    Publication date :

    2020-11-24


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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