Structural Collapse Visualization Using Blender and BCB

EasyChair Preprint 11308

Abstract

Over the past few years, a range of adverse factors including excess applied structural loads, unequal settlement of the ground beneath foundations, significant deflection, flooding, landslides, material degradation, inadequate maintenance, gaps in the original builder's structural understanding, seismic and earthquake activity, and the force of explosions have all contributed to the failure of buildings and the unfortunate loss of human lives. It has often been reported that these events do not kill people but rather the affected structures do. Hence, the collapse of engineering structures is a contemporary and critical topic all over the world. However, to simulate these phenomena, a great number of input data and failure criteria definitions are required which have an elaborated form owing to the interaction between several elements of engineering structure. Also, the computational cost is relatively high and time-consuming. Hence the justification for an alternative simplified method using Blender software and Bullet Constraints Builder (BCB). Blender software and BCB add-on work in harmony to simulate collapse scenarios. Blender and BCB averaged a multitude of structural attributes using streamlined engineering equations. Consequently, this leads to substantially reduced executable simulation model development time with approximately equal accuracy and debris formation outcomes. The debris formulation of the simplified method could be used to trace victims in the event of a collapse in reality. This study aims to review the alternative simplified method that could be used for visualizing collapse. The review is supported by masonry structure as a case study.

Keyphrases: BCB, Blender, Masonry, RC structure, collapse, visual simulation

@booklet{EasyChair:11308,
  author    = {Ridwan Adebayo Bello and Murat Günaydın and Ahmet Can Altunışık},
  title     = {Structural Collapse Visualization Using Blender and BCB},
  howpublished = {EasyChair Preprint 11308},
  year      = {EasyChair, 2023}}