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Research Article | Open Access

Selecting deconstruction processes using virtual reality comparisons

Yinghui ZhaoaGabriel Earlea( )Yun-Ha JungaCarl HaasaSriram Narasimhanb
Department of Civil and Environmental Engineering, University of Waterloo, Waterloo N2L 3G1, Canada
Department of Civil and Environmental Engineering, University of California Los Angeles, Los Angeles 90095, USA
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Abstract

Grand challenges such as achieving sustainability goals and managing aging infrastructure are creating an unprecedented demand for deconstruction. However, deconstructing aging infrastructure is inherently risky, repetitive, and costly, necessitating effective project planning. Virtual reality (VR) technology offers the potential for planners to improve deconstruction project risk, time, safety, and cost. We propose that planners leverage VR early in the planning phase to compare alternative feasible tools and processes. Planners can create low-fidelity models of various deconstruction process alternatives and collect metrics on their suitability with VR-capable three-dimensional (3D) game engines. We present and formalize a methodology for conducting comparisons of candidate deconstruction processes by modeling candidates in VR, conducting trials, and collecting analytics data from the VR engine. We present a case study that demonstrates our approach to a cutting and waste packing process for nuclear power plant (NPP) decommissioning. As a novel contribution in this paper, we show that VR simulations can efficiently produce detailed insights useful for critically analyzing and comparing deconstruction process alternatives.

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Journal of Intelligent Construction
Article number: 9180022
Cite this article:
Zhao Y, Earle G, Jung Y-H, et al. Selecting deconstruction processes using virtual reality comparisons. Journal of Intelligent Construction, 2024, 2(3): 9180022. https://doi.org/10.26599/JIC.2024.9180022

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Received: 19 October 2023
Revised: 01 February 2024
Accepted: 15 February 2024
Published: 10 July 2024
© The Author(s) 2024. Published by Tsinghua University Press.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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