Concrete bridge decks are vital components of bridges that provide the driving surface to bridge users. Partial or complete failure of this component has a significant impact on the overall performance of the bridge and, consequently, on the subsequent highway network(s). In this regard, periodical inspections are typically conducted to ensure the integrity of bridges and to determine the required maintenance, rehabilitation, and replacement work. Nevertheless, current practices in inspection (i.e., visual inspection) are time-consuming and suffer from several limitations, such as subjectivity and uncertainty. In addition, visual inspection provides limited defect-detection capabilities. Therefore, nondestructive technologies (NDTs), such as impact echo, ultrasonic surface wave, half-cell potential, ground-penetrating radar, infrared thermography, and image-based techniques, have been incorporated into inspection processes to tackle such limitations. However, none of these technologies can identify all types of defects, which reveals the critical need for a comprehensive inspection system. Accordingly, several studies have incorporated multitechnology systems in the inspection process to expand defect-detection capabilities and to ensure successful inspection outcomes. Previous studies also investigated the performance criteria of different NDTs, which provide beneficial information for choosing the most effective techniques for inspection purposes. The present research aims at assessing the capabilities of different NDTs, providing an overview of the developed multitechnology systems and reviewing the main criteria to measure the performance of NDTs. The review provides insight into recent developments in the inspection process, which helps in identifying future needs in this field.

Off-site construction (OSC) is an innovative construction method that transfers most of the site-based work to a more controlled environment. Construction waste minimization, speedy schedules, higher sustainability, and better quality are some of the perceived benefits of OSC. Therefore, significant research attention has been given to OSC. However, minimal research attention has been given to procurement management in OSC, which could impact its pace of adoption. Existing studies on the procurement methods of OSC projects have overlooked several criteria related to OSC that impact the selection of the appropriate procurement methods (i.e., design-build, construction management, etc.). In addition, the literature lacks decision-making tools to assist OSC practitioners in selecting the appropriate procurement method. In this regard, this study contributes to the body of knowledge by (1) identifying the criteria that impact the selection of OSC procurement methods; (2) developing a multi-criteria decision-making (MCDM) model to select the appropriate OSC procurement methods. The developed MCDM model uses a hybrid approach of analytic network process (ANP) and evidential reasoning (ER). The ANP, which considers the interdependencies among the collected OSC procurement criteria, is used to calculate the relative importance weights through questionnaire surveys. The ER method evaluates various OSC procurement methods in accordance with the criteria importance weights. The results indicate that project quality, cost control, and funding arrangement are the prominent selection factors. On the other hand, the model reveals that the integrated project delivery (IPD) and construction management (CM) methods have the highest utility scores. The MCDM model has been validated by comparing the results with similar studies. The present study could assist OSC practitioners in selecting the appropriate procurement method for OSC projects.

Non-destructive testing (NDT) methods are typically utilized to thoroughly inspect existing defects in the concrete bridge deck and tackle the limitations of common inspection practices (e.g. visual inspection). Nevertheless, the reliability of inspection outcomes crucially depends on choosing the most appropriate NDT technologies. In this regard, a comprehensive Performance Assessment Model (PAM) was developed. The developed model incorporated 40 parameters to precisely assess the performance of different NDT technologies from diverse perspectives (e.g. defect detection capability, ease of use, speed, and cost). The required data were collected through a survey questionnaire. The model utilized the Analytic Network Process (ANP) technique to calculate the importance weight of each parameter, whereas the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was exploited to compute the performance index (PI) of NDT technologies. The outcomes of this study clearly illustrate the disparity in the performance of different NDT technologies. Furthermore, it was shown that none of these technologies could either exhibit the best performance in all the proposed parameters or efficiently identify all types of defects. Based on the PAM results, a selection model was proposed to assist bridge authorities and consultants in choosing the most efficient NDT technologies for inspection purposes.