An Expert System Integrated with a Bridge Information Management System (BrIMS), Cost Estimating, Deterioration Forecasting, and Linear Scheduling at the Conceptual Design Stage

Abstract

Major bridge stakeholders such as federal and provincial transportation agencies are in dire need for objective knowledge-based systems that assist decision-makers in the selection of bridge type. Besides that, estimating bridge construction costs at the conceptual design stage is an increasing necessity for accurate budgeting and effective allocation of funding. Whilst multiple bridge management systems have already been developed; they still possess major drawbacks pertaining to interoperability and integration with complex time and cost optimization-related problem solving. In another perspective, infrastructure restoration has been backlogged with multifaceted factors that have captured the attention of municipal and federal authorities. Several successful integrations of bridge information management systems (BrIMS) with decision support systems and computer-aided engineering design solutions have significantly leveraged downstream processes of bridge maintenance operations and inspired many researchers. The subjective nature of evaluating bridge conditions and deteriorations is the main factor that influences bridge maintenance, repair, and replacement decisions. In order to overcome this shortcoming, the objectives of this study are intended to demonstrate the viability of integrating a decision support system with a stochastic gamma deterioration model utilizing a probabilistic fuzzy logic strategic approach at the conceptual design stage.

In summary, this study presents a systematic multi-objective knowledge-based approach for selecting bridge type, forecasting elemental deteriorations, linear scheduling, and estimating construction costs at the conceptual design stage. The proposed methodology comprises a framework to deploy a system that automatically generates conceptual cost estimates by integrating objective functions with bridge information modeling (BrIM) through an external data interchange protocol in synchrony with interoperability standards. Deployment of the developed system shall minimize the degree of subjectivity involved while decision makings pertaining to bridge projects and assists designers and cost engineers obtain results in an integrated quantitative, qualitative, and systematic manner. The successful deployment of the expert system signifies a technological achievement of novelty pertaining to the integration of bridge information modeling (BrIM) concept with probabilistic fuzzy logic strategic approaches at the conceptual design stage of bridges.