2019 CSCE Annual Conference - Laval (Greater Montreal)

2019 CSCE Annual Conference - Laval (Greater Montreal) Conference


Title
RUBBLE-MOUND BREAKWATER CONSTRUCTION SIMULATION


Author(s)
Mr. Alireza Mohammadi, Concordia University (Presenter)
Ms. Kimiya Zakikhani
Dr. Tarek Zayed, The Hong Kong Polytechnic University
Dr. Luis Amador, Concordia university
Abstract

Breakwater is a structure that forms an artificial harbor to protect the shore from severe wave motions. Rubble-mound breakwater is the most typical group of breakwaters with three main sections including core, filter, and armor. Marine structures construction is considered one of the expensive operations compared to other projects, therefore cost efficiency and productivity can play a significant role in breakwaters construction management. The objective of this research is to simulate this type of structure construction process addressing real operation complexity to find the optimum resource quantity and increase production rate and reduce construction costs. In this study, the cyclic construction process of the natural rubble-mound breakwater is studied through MicroCYCLONE and EZstrobe simulation programs. Nineteen similar breakwaters are selected as a case study for which simulation models are developed and validated through available field data. The efficiency of the developed models was verified by 90% and 95% for MicroCYCLONE and EZstrobe respectively. The results of this research indicate that from both cost and production point of views for projects with 10 km hauling distance, using 2 loaders for loading at mine, 12 trucks for hauling materials from mine to site and 3 backhoes for placement would be the best alternative. For projects with 15 km and 30 km hauling distances, the results indicate that it is more efficient to use 14 and 19 trucks respectively. Production rate analysis for different scenarios will provide a means to evaluate the effectiveness of resource allocation and apply necessary changes to obtain the optimum results in terms of production and cost efficiency.