Journal of Information Technology in Construction
ITcon Vol. 23, pg. 92-121, http://www.itcon.org/2018/5
Integrating fuzzy-logic decision support with a bridge information management system (BrIMS) at the conceptual stage of bridge design
submitted: | August 2017 | |
revised: | April 2018 | |
published: | May 2018 | |
editor(s): | Turk Ž. | |
authors: | Nizar Markiz, Ph.D. Candidate
Department of Civil Engineering, University of Ottawa Address: 161 Louis Pasteur Pvt., Ottawa, ON, Canada, K1N 6N5 Email:nmark086@uottawa.ca Ahmad Jrade, Associate Professor Department of Civil Engineering, University of Ottawa Address: 161 Louis Pasteur Pvt., Ottawa, ON, Canada, K1N 6N5 Email:ajrade@uottawa.ca | |
summary: | In recent years, infrastructure restoration has been backlogged with complex factors that have captured the attention of municipal and federal authorities in North America and Europe. The subjective nature of evaluating bridge conditions and bridge deterioration is one of the main factors that influences bridge maintenance, repair, and replacement (MR&R) decisions. This study presents a stochastic fuzzy logic decision support integrated with a bridge information management system (BrIMS) to forecast bridge deteriorations and prioritize maintenance, repair, and replacement (MR&R) decisions at the conceptual design stage. The proposed system considers numerous factors that influence the prioritization of bridge MR&R decision making including complex time-dependent gamma shock models. A parametric analysis is conducted in order to quantify the degree of accuracy of the system. Implementation of the system platform demonstrated the viability of integrating BrIMS with fuzzy-logic deterioration forecast techniques at the conceptual stage of bridge design. The proposed system is validated through a case study and found to be in agreement with actual bridge deterioration results with a percentage difference of approximately 10 - 15 %. Besides that, the integrated platform may be utilized as a forecasting tool that is capable of predicting and prioritizing MR&R decisions to components for diverse bridge design alternatives. | |
keywords: | Fuzzy-logic, Decision Support, Deterioration Forecast, Bridge Information Model, Bridge Information Management System | |
full text: | (PDF file, 2.17 MB) | |
citation: | Markiz N, Jrade A (2018). Integrating fuzzy-logic decision support with a bridge information management system (BrIMS) at the conceptual stage of bridge design, ITcon Vol. 23, pg. 92-121, https://www.itcon.org/2018/5 |