Random Generation of Complex Data Structures for the Simulation of Construction Operations

Mubarak Al-Alawi, Ahmed Bouferguene, Yasser Mohamed

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Construction production systems are complex in nature and possess a high level of uniqueness. Modelling and simulation of such systems is challenging due to the randomness, complexity, and interdependency associated with many factors such as the type of product created, the steps of the production process, and the medium or the environment hosting the production process. These factors represent or control the working behaviour of a construction system and need to be realistically represented in a model in order to achieve accurate replication of real system behaviours. However, modeling and simulation of these factors require either a rich real life data set, which is seldom available for construction operations, or random generation of complex data structures with highly correlated attributes. This paper presents an investigation of mathematical techniques that can be used to generate random complex data structures while preserving the correlations between the embedded attributes. Generation of weather and pipelines data sets are selected in this study. We propose a non-parametric approach in the weather generation; its performance is measured against a parametric approach. For the generation of pipeline data sets, we propose a generation methodology based on a Markov chain model for a pipeline structure. It represents part of an ongoing research. A detailed description of the methodology and the progress in this part of the study are discussed.

Original languageEnglish
Title of host publicationConstruction Research Congress 2016
Subtitle of host publicationOld and New Construction Technologies Converge in Historic San Juan - Proceedings of the 2016 Construction Research Congress, CRC 2016
PublisherAmerican Society of Civil Engineers (ASCE)
Pages2510-2521
Number of pages12
ISBN (Electronic)9780784479827
DOIs
Publication statusPublished - 2016
EventConstruction Research Congress 2016: Old and New Construction Technologies Converge in Historic San Juan, CRC 2016 - San Juan, Puerto Rico
Duration: May 31 2016Jun 2 2016

Other

OtherConstruction Research Congress 2016: Old and New Construction Technologies Converge in Historic San Juan, CRC 2016
CountryPuerto Rico
CitySan Juan
Period5/31/166/2/16

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction

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    Al-Alawi, M., Bouferguene, A., & Mohamed, Y. (2016). Random Generation of Complex Data Structures for the Simulation of Construction Operations. In Construction Research Congress 2016: Old and New Construction Technologies Converge in Historic San Juan - Proceedings of the 2016 Construction Research Congress, CRC 2016 (pp. 2510-2521). American Society of Civil Engineers (ASCE). https://doi.org/10.1061/9780784479827.250