Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/83986
Title: Formalization of construction operations simulation framework for modeling large civil engineering projects for decision making purposes
Authors: Lau, Sze Chun
Degree: Ph.D.
Issue Date: 2014
Abstract: Construction simulation provides a virtual platform on computer for design, analysis and experimentation of construction methods in order to offer better understanding and solutions. Despite the fact that computer simulation software has become user friendly to learn and apply and many real-world applications for aiding critical decision making have been demonstrated by simulation researchers, the industry generally has not yet been convinced with the advantages and the cost-effectiveness afforded by simulation. Most of the civil engineering projects are large, featuring extensive site-specific information, numerous practical constraints and convoluted logical sequences. Special-purpose simulation templates with default settings are regarded by the construction managers as being still too general to be directly applied to address their own problems. On the other hand, a general-purpose simulation platform demands the simulation knowledge and application skills of a simulation modeler who is generally trained at PhD level in Construction Engineering and Management. Neither a special-purpose nor a general-purpose simulation approach has yet to be widely implemented in practice. This research formalized the methodologies to approach, structure and represent the reality in construction applications by proposing and implementing 1) a formalized framework for process mapping and simulation modelling and analysis, and 2) a simplified discrete event simulation approach to apply combined modeling for simulating large civil engineering projects, which are predominantly discrete but include some plants or processes that are continuous in nature.
The formalized framework for computer simulation modeling were developed; following the procedures on how to establish a process mapping model bridges the gap between the reality and a simulation model. The detailed procedures were also presented and demonstrated with practical applications. The framework provides hands-on application guidance and reduces many subjective interpretations and assumptions that simulation modelers need to make when building simulation models. The resulting process mapping models can be rapidly converted into simulation models by applying the Simplified Discrete Event Simulation Approach (SDESA). The SDESA models precisely represent extensive construction operations in a straightforward manner and executing SDESA simulations lends effective decision support to construction managers at the construction operations planning stage in terms of use of resources use, cost and time. In addition, special constraints in certain practical problems were identified to demand the use of advanced modeling methods (e.g. discrete-continuous combined modelling). This research has developed an approach for modeling a continuous plant by defining a finite quantity of discrete resource entities to represent a continuous component or process without considerable loss of model accuracy, while retaining the ease of applying discrete simulation modeling. The approach was demonstrated with a concrete pumping case in which a stationary pump system processes truckloads of concrete in continuous flows. A practical application of an iron ore processing plant in a mining site was used to validate the proposed framework and demonstrate its implementation. The formal framework for process mapping and simulation modeling was applied to three large civil engineering projects of 1) an airport demolition project, 2) a microtunneling project, and 3) a mining project. The framework was capable of solving a wide range of construction applications and the resulting process mapping models were converted to simulation models on the SDESA computer platform where the simulation analyses were carried out. The production rate and resource utilization rates derived from simulation indicated a close match between the simulation model and the actual site system in all these case studies. The proposed approach adds to the usefulness and flexibility of a discrete simulation methodology in modeling complicated construction systems.
Subjects: Construction industry -- Management -- Data processing.
Construction industry -- Data processing.
Construction industry -- Decision making.
Hong Kong Polytechnic University -- Dissertations
Pages: xxiii, 278 p. : ill. (some col.) ; 30 cm.
Appears in Collections:Thesis

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