Optimal Seismic Design of RC Shear Wall-Frame Structures

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Details

In this study, optimal seismic design of RC shear wall-frame building structures is done by proposing a new method of structural optimization. The main purpose of this research is to propose an automated-structural optimization method for RC shear wall structures to minimize the total cost of the structure whereas satisfying related design code criteria. Databases are generated for section sizes based on automated structural optimization method utilizing Active-Set Algorithm in MATLAB platform. The validity of proposed method is examined through numerical example of 15 storied 3D RC shear wall frame-structure based on equivalent linear static analysis. In addition, with modification of mathematical formulations, the result is compared with optimal solutions of size constraints and without size constraints to obtain the most practical section sizes. The most suitable combination of section sizes are selected as for the final design application conforming to ACI 318-14 to minimize the total cost of the structure. An analytical procedure is followed to validate the accuracy of proposed method by comparing stresses on structural members through output files of MATLAB and ETABS.

Autorentext

Hamid Nikzad did his Master's course of Science and Engineering at Ritsumeikan University in Japan in September 2018, and his Bachelor in civil engineering at Kabul Polytechnic University in Afghanistan in September 2012 . He has been working as design engineer with Kabul Municipality of Afghanistan since 2012.

Weitere Informationen

  • Allgemeine Informationen
    • Autor Hamid Nikzad , Shinta Yoshitomi
    • Titel Optimal Seismic Design of RC Shear Wall-Frame Structures
    • Veröffentlichung 26.03.2019
    • ISBN 6139464528
    • Format Kartonierter Einband
    • EAN 9786139464524
    • Jahr 2019
    • Größe H220mm x B150mm x T6mm
    • Untertitel Structural Optimization Method for 3D Reinforced Concrete Building Structure with Shear Wall
    • Gewicht 149g
    • Genre Kunst
    • Anzahl Seiten 88
    • Herausgeber LAP LAMBERT Academic Publishing
    • GTIN 09786139464524

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