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Abdelkhalek, S I (2022) Managing the inspection process of concrete bridge decks, Unpublished PhD Thesis, , Hong Kong Polytechnic University.
- Type: Thesis
- Keywords: accuracy; duration; optimization; bridge; traffic; deterioration; estimating; inspection; non-destructive testing; pollution; consultant; simulation
- ISBN/ISSN:
- URL: https://theses.lib.polyu.edu.hk/handle/200/11748
- Abstract:
Bridge deck provides a safe passage that facilitates goods shipping and people transit. This element is exposed to several deterioration sources, such as environmental conditions, pollution, and accidents. Deterioration in bridge deck is the most frequent reason for a bridge being classified as structurally deficient. Accordingly, regular inspections are usually performed to accurately identify the current condition of a bridge deck. Inspection is an essential step to effectively determine the proper interventions, avoid unnecessary or costly maintenance actions, and consequently reduce maintenance cost. In this connection, non-destructive testing (NDT) methods, e.g., impact echo, half-cell potential, and ground penetrating radar, are typically incorporated into the inspection process to eliminate the limitations of the traditional inspection approach (i.e., visual inspection) and to address more accurate assessment for surface and subsurface defects. Nevertheless, NDT techniques possess several challenges related to the selection of the most appropriate NDT approach, the large number of bridges to inspect, and the impact of inspection activities on traffic flow. Therefore, the primary aim of the present study is to optimize the inspection process of a concrete bridge deck considering four objectives: 1) model the duration and cost of the NDT inspection process, 2) assess the performance of NDT technologies from various perspectives, 3) design an optimized multi-technology inspection system, and 4) develop an optimized inspection schedule for a bridge network. Four models were developed to address the research objectives. In the first model (i.e., Bridge Deck Inspection Planning (BDIP) model), agent-based and discrete event simulation approaches were integrated to mimic the sub-processes involved in the inspection using NDT technologies. The BDIP can assist bridge authorities in estimating the inspection duration/cost and in measuring traffic disorder due to inspection activities. As for the second objective, a comprehensive Performance Assessment Model (PAM) was developed to precisely assess the performance of different NDT technologies considering different criteria (e.g., defect detection capability, ease of use, speed, and cost). The required data for this model were collected using a survey questionnaire, whereas the Analytic Network Process (ANP) technique and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) were used to analyze the collected data. The outcomes of the model clearly illustrated the disparity in the performance of different NDT technologies. The findings of PAM and BDIP were integrated to develop a Bridge Inspection System Optimization (BISO) model (third objective). In this model, the simulation-based optimization concept was utilized to optimize the multi-technology inspection systems considering three main criteria: performance of the inspection system, inspection duration, and inspection cost. A discrete event simulation model was built in the optimization algorithm to emulate inspection activities and predict inspection duration and cost. Two optimization techniques were used: genetic algorithm and particle swarm optimization. BISO model aims to optimize the components of the multi-technology inspection systems, inspection team size, and overtime hours. Furthermore, it facilitates the selection of the most appropriate traffic control strategy to reduce traffic delays and bridge user cost. Finally, to consider bridges located in a large geographical area, a Bridge Network Inspection Planning (BNIP) model was developed by integrating discrete event simulation, geospatial information modeling, and genetic algorithm. BNIP aims to optimize the schedule of the inspection activities for a bridge network (i.e., select the best inspection route that connects bridges in the network). The developed models were verified using several techniques, e.g., comparing the findings with the results obtained from previous studies or field tests. In addition, the sensitivity of the developed models to variation in the inspection parameters was tested. The outputs demonstrated the capability of the developed models to optimize the inspection process. The outputs also proved the accuracy and effectiveness of the developed models in measuring inspection process characteristics (e.g., inspection duration and cost). This study made original contributions to the knowledge and practices of bridge deck inspection. In this respect, the main inspection criteria and parameters were identified and mapped. Four original models (i.e., BDIP, PAM, BISO, BNIP) were designed to plan the bridge deck inspection activities. These models provide strong support for bridge authorities, consultants, and contractors in optimizing the inspection process starting from selecting the utilized technologies to implementing the selected inspection technique(s).
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