Date of Award

9-15-2022

Publication Type

Thesis

Degree Name

M.A.Sc.

Department

Civil and Environmental Engineering

Keywords

Asset Management;Building Information Modelling (BIM);Digital Shadow (DS);Life Cycle Cost;Stormwater Infrastructure Management

Supervisor

Rajeev Ruparathna

Supervisor

Tirupati Bolisetti

Abstract

Recently, there has been an increasing trend in using state-of-the-art technology for infrastructure management solutions. Yet, some civil infrastructure systems, such as stormwater, are currently managed manually. However, this current approach results in data losses and inconsistencies, which subsequently contribute to inaccurate stormwater infrastructure management. Building Information Modeling (BIM) offers a promising platform capable of creating a digital shadow (DS) of infrastructure assets, that can address these complexities in infrastructure management. An extensive literature review has revealed that the infrastructure asset management sector is lacking a DS-based model that facilitates proactive stormwater infrastructure management. The objective of this study is to develop a DS-based proactive stormwater infrastructure management system. This study developed a DS-based methodological framework for proactive maintenance planning of stormwater infrastructure systems. The proposed framework used Markov Chain approach for simulating the stormwater infrastructure condition, and Genetic Algorithm (GA) was used for multi-objective optimization. The optimization was conducted to minimize the lifecycle cost and risk level while maximizing the physical condition. The proposed framework was developed as a tool in the BIM platform and was applied as a case study. Then, the proposed framework was compared to the conventional model of stormwater infrastructure management. The outcome revealed that the Lifecycle Cost (LCC) of the DS-based model is about 63% less than the conventional stormwater infrastructure management approach in long-term planning. The proposed framework enables maintaining an acceptable physical condition while minimizing the risk of failure and LCC. Unlike the conventional approach, the DS-based model can store data for easy reference. This will aid asset managers to eliminate data fragmentation in infrastructure management. Also, it will facilitate collaboration among stakeholders by effectively serving as a data warehouse for the proactive management of stormwater infrastructure systems.

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