Title

Dynamic Data Driven Simulation Of Ongoing Construction Processes

Abstract

Most construction operations consist of processes that are repetitive and subject to resource and spatial constraints. In addition to unforeseen site conditions and equipment breakdowns, the evolving nature of a construction project may also introduce uncertainties into an ongoing operation which can result in work interruptions or delays. Discrete Event Simulation (DES) has evolved as a reliable tool during project long-term planning to predict the behavior of resources in different operational scenarios. However, in reality, a construction operation may not follow the strict rules, assumptions, and design parameters of a DES model. Hence, before a DES model can be applied for short-term scheduling and decision making in an ongoing project, additional measures need to be taken in order to continuously update the parameters of the model. This requires the design and implementation of a new layer for real time data acquisition and processing so that the DES model is constantly adapted to the dynamics of a construction system and updated based on the latest collected operational data, and the activities in the immediate future can be appropriately planned and executed. This paper, describes the latest results of an ongoing research in which the paradigm of Dynamic Data-Driven Application System (DDDAS) is used to integrate DES, real time data acquisition, and short-term scheduling in a single decision making framework which will ultimately provide a more efficient and accurate means to predict the behavior of a dynamic construction system based on real time data collected from resources and entities on a jobsite.

Publication Date

12-1-2011

Publication Title

Proceedings, Annual Conference - Canadian Society for Civil Engineering

Volume

4

Number of Pages

2726-2735

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

84855818387 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84855818387

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