Journal Articles - Architecture and Construction - 2019

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Browsing Journal Articles - Architecture and Construction - 2019 by Author "Jiri Brozovsky"
  • Publication
    Evaluation of Parameters Affecting the CFST Column Optimization Problem by BMA Method during The Basic Design Phase for Smart Cities in Vietnam
    ( 2019)
    Nguyễn Trần Trung
    ;
    Nguyễn Phú Cường
    ;
    Jiri Brozovsky
    The smart city is the trend of globalisation now. Vietnam is a country that is also aiming at this criterion. There are about ten standards to evaluate as a smart city, including related smart infrastructure and structural design analysis field is also in this criterion. The composite material for the present construction structures is considered suitable for the above problem. The component mentioned in this study is a Concrete-Filled Steel Tube (CFST) Column. It is part of a column system made of composite materials with hollow cross-sections. This column has three typical shapes: i) circular hollow sections with diameters from 20 mm to 1200 mm; ii) square hollow sections with b widths from 40 mm to 400 mm; iii) rectangular hollow sections with h depths from 50 mm to 500 mm, applied in the top-down construction technology. This is the component that receives the full vertical load of the upper structure in the construction process. In particular, when constructing the underground part, this component often occurs buckling due to the rather large column length compared to its cross-section dimension subjected to axial compression load. In designing and analysing advanced structures, the optimal problem has been considered for the above question. The parameters used for the objective functions and the constraint conditions which in they may be: Geometric size of the column, strength of materials and the magnitude of the axial compression load causes column buckling. In this study, the authors will present how to evaluate the correlation of the above parameters, to find out which parameters affect the buckling load by the Bayesian Model Average (BMA) method. This method is being used powerfully in the field of applied statistics and data analysis. The R programming language is employed for this study.