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Showing 2 results for Building Frame

A. Choubey, M. D. Goel,
Volume 6, Issue 2 (6-2016)
Abstract

The  study  aims  to  investigate  the  progressive  collapse  behaviour  of  RCC  building  under extreme  loading  events  such  as  gas  explosion  in  kitchen,  terroristic  attack,  vehicular collisions  and  accidental  overloads.  The  behavioural  changes  have  been  investigated  and node displacements  are computed when the building is subjected to sudden collapse of the 
load bearing elements.  Herein, a RCC  building  designed based on Indian standard code of practice  is  considered.  The  investigation  is  carried  out  using  commercially  available software. The node displacement values are found under the column removal conditions and collapse  resistance  of  building  frame  is  studied  due  to  increased  loading  for  different 
scenarios.  This  simple analysis  can be used to quickly analyse the  structures  for  different failure conditions and then optimize it for various threat scenarios.


M. Shahrouzi, A. Barzigar, D. Rezazadeh,
Volume 9, Issue 3 (6-2019)
Abstract

Opposition-based learning was first introduced as a solution for machine learning; however, it is being extended to other artificial intelligence and soft computing fields including meta-heuristic optimization. It not only utilizes an estimate of a solution but also enters its counter-part information into the search process. The present work applies such an approach to Colliding Bodies Optimization as a powerful meta-heuristic with several engineering applications. Special combination of static and dynamic opposition-based operators are hybridized with CBO so that its performance is enhanced. The proposed OCBO is validated in a variety of benchmark test functions in addition to structural optimization and optimal clustering. According to the results, the proposed method of opposition-based learning has been quite effective in performance enhancement of parameter-less colliding bodies optimization.

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