Download or read book Deterioration Prediction Models for Condition Assessment of Concrete Bridge Decks Using Machine Learning Techniques written by Nour Hider Almarahlleh and published by . This book was released on 2021 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bridges play a significant role in the U.S. economy. The number of the bridges in the U.S. exceeds six hundred thousand. Almost one third of them are considered structurally deficient and will require more than $164 billion to repair or replace. Identifying the factors that affect the performance of concrete bridge decks during its service life is critical to the development of an accurate condition assessment and deterioration prediction model. Accurate bridge deck deterioration models can provide vital information for predicting short- and long-term behavior of concrete bridge decks and minimizing costly routine inspection and maintenance activities. Therefore, the main goal of this dissertation is to develop a deterioration prediction model for concrete bridge decks that is based on the National Bridge Inventory (NBI) database. To achieve the goal, five deterioration prediction models for concrete bridge decks were developed using Multinomial Logistic Regression, Decision Tree, Artificial Neural Network, k-Nearest Neighbors and Naive Bayesian machine learning techniques. Michigan bridge deck data from NBI between the years 1992 to 2015 were used for training the various prediction models. The results show that the performance of all five developed models were acceptable. However, the artificial neural network achieved the highest accuracy in the validation process. Additionally, bridge decks age, area, average daily traffic, and skew angle are found to be significant factors in the deterioration of concrete bridge decks. Furthermore, it was observed that bridge decks could stay in their condition rating more than the typical 2-year inspection interval, suggesting that inspection schedules could be extended for certain bridges that had slower deterioration rates. The contributions of this work include 1) the development of an optimized deterioration prediction model that can be used in the condition assessment process for concrete bridge decks, 2)the identification of the factors that have the most impact on concrete bridge deck deterioration,and 3) demonstrating that the inspection schedule can be longer than 2 years for bridges that do not deteriorate fast which can lead to cost and time savings. Future work can include the following: (1)developing deterioration prediction models for concrete bridge decks using deep learning techniques; (2) developing deterioration prediction models for other bridge specific elements (i.e., superstructure and substructure) using multivariant analysis; (3) developing deterioration prediction models for other (or all) U.S. states using the framework developed in this research; and (4) investigating the prospect of revising the mandated inspection interval beyond the 2-year period.

Download or read book Deterioration Prediction Modeling for the Condition Assessment of Concrete Bridge Decks written by Aqeed Mohsin Chyad and published by . This book was released on 2018 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bridges are key elements in the US transportation system. There are more than six hundred thousand bridges on the highway system in the United States. Approximately one third of these bridges are in need of maintenance and will cost more than $120 billion to rehabilitate or repair. Several factors affect the performance of bridges over their life spans. Identifying these factors and accurately assessing the condition of bridges are critical in the development of an effective maintenance program. While there are several methods available for condition assessment, selecting the best technique remains a challenge. Therefore, developing an accurate and reliable model for concrete bridge deck deterioration is a key step towards improving the overall bridge condition assessment process. Consequently, the main goal of this dissertation is to develop an improved bridge deck deterioration prediction model that is based on the National Bridge Inventory (NBI) database. To achieve the goal, deterministic and stochastic approaches have been investigated to model the condition of bridge decks. While the literatures have typically proposed the Markov chain method as the best technique for the condition assessment of bridges, this dissertation reveals that some probability distribution functions, such as Lognormal and Weibull, could be better prediction models for concrete bridge decks under certain condition ratings. A new universal framework for optimizing the performance of prediction of concrete bridge deck condition was developed for this study. The framework is based on a nonlinear regression model that combines the Markov chain method with a state-specific probability distribution function. In this dissertation, it was observed that on average, bridge decks could stay much longer in their condition ratings than the typical 2-year inspection interval, suggesting that inspection schedules might be extended beyond 2 years for bridges in certain condition rating ranges. The results also showed that the best statistical model varied from one state to another and there was no universal statistical prediction model that can be developed for all states. The new framework was implemented on Michigan data and demonstrated that the prediction error in the combined model was less than each of the two models (i.e. Markov and Lognormal). The results also showed that average daily traffic, age, deck area, structure type, skew angle, and environmental factors have significant impact on the deterioration of concrete bridge decks. The contributions of the work presented in this dissertation include: 1) the identification of the significant factors that impact concrete bridge deck deterioration; 2) the development of a universal deterioration prediction framework that can be uniquely tailored for each state’s data; and 3) supporting the possibility of extending inspection schedules beyond the typical 2-year cycles. Future work may involve: 1) evaluating each of the factors that impact the deterioration rates in more depth by refining the investigation ranges; 2) investigating the possibility of revising the regular bridge deck inspection intervals beyond the 2-year cycles; and 3) developing deterioration prediction models for other bridge elements (i.e. superstructure and substructure) using the framework developed in this dissertation.

Download or read book Development and Validation of Deterioration Models for Concrete Bridge Decks written by Emily K. Winn and published by . This book was released on 2013 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research documents the development and evaluation of artificial neural network (ANN) models to predict the condition ratings of concrete highway bridge decks in Michigan. Historical condition assessments chronicled in the national bridge inventory (NBI) database were used to develop the ANN models. Two types of artificial neural networks, multi-layer perceptrons and ensembles of neural networks (ENNs), were developed and their performance was evaluated by comparing them against recorded field inspections and using statistical methods. The MLP and ENN models had an average predictive capability across all ratings of 83% and 85%,respectively, when allowed a variance equal to bridge inspectors. A method to extract the influence of parameters from the ANN models was implemented and the results are consistent with the expectations from engineering judgment. An approach for generalizing the neural networks for a population of bridges was developed and compared with Markov chain methods. Thus, the developed ANN models allow modeling of bridge deck deterioration at the project (i.e., a specific existing or new bridge) and system/network levels. Further, the generalized ANN degradation curves provided a more detailed degradation profile than what can be generated using Markov models. A bridge management system (BMS) that optimizes the allocation of repair and maintenance funds for a network of bridges is proposed. The BMS uses a genetic algorithm and the trained ENN models to predict bridge deck degradation. Employing the proposed BMS leads to the selection of optimal bridge repair strategies to protect valuable infrastructure assets while satisfying budgetary constraints. A program for deck degradation modeling based on trained ENN models was developed as part of this project.

Download or read book Development of a Condition Assessment Method of Deteriorated Bridge Decks Based on GPR Data and Structural Response written by Dipesh Donda and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bridges are at the heart of transportation systems connecting the roads to and between the mainlands. Thus, bridges are an integral part of the economic growth of any country. They are subjected to dynamic loads of the vehicles and the environmental effects. These loads cause stress and strain cycles causing its deterioration by initiating microcracking. The deterioration is then accelerated due to the chloride attack which causes the corrosion of the steel reinforcement resulting in cracking and delamination of concrete and ultimately leads to failure. It is essential to analyze the bridge with its actual condition which is difficult with a visual inspection. This analysis can help in determining the degree of repairs needed and an approximate idea about its service life. The development of the Non-Destructive Test (NDT) methods helps assess the condition of the bridge without any kind of damage to the original structure. In the past few decades, the Non-Destructive Evaluation (NDE) with the help of Ground Penetration Radar (GPR) has gained popularity due to its ease in the evaluation of the larger areas such as bridge deck and parking lot in a shorter amount of time with sufficient training. The NDE using GPR for Structural Health Monitoring (SHM) has been still evolving with new improvements in its technology as well as the development of new methods for the analysis of its data. A positive step towards detecting the subsurface materials present in the cracks has been undertaken in this study. A methodology to detect the subsurface cracks/gaps in concrete using GPR has been developed here by preparing three concrete samples of dimensions 50 x 25 x 5 cm3, 50 x 25 x 10 cm3, and 50 x 25 x 20 cm3 in the laboratory. The detection of reinforcement of 6 mm, 10 mm, 18 mm, 20 mm diameter, as well as a 21.8 mm Fiber Reinforcement Polymer (FRP) bar, are studied along with the detection of the air gap, water gap, and gap with the salt solutions of thickness 3 mm, 4 mm, 4.8 mm, 5.8 mm and 8.8 mm under the depth of 5 cm, 10 cm, and 15 cm. The amplitude values of these parameters are studied, and a comparison is made to check the ability of GPR to detect this material in cracks and/or delamination with changes in depths. This will be helpful in analyzing the GPR data with more reliability. Along with this, a non-linear finite element model (FEM) of a bridge superstructure using a fiber element is developed. The FE model of the bridge deck is updated and analyzed using a GPR defect map. This procedure of model updating is less tedious than the previous method available in the literature and proves to be time-saving. This model updating procedure will prove to be helpful in estimating the capacity of the bridge and make a prediction for future deterioration with the help of NDE methods (here GPR).

Download or read book Modeling Deterioration of Concrete Bridge Decks Using Neural Networks written by Ying-Hua Huang and published by . This book was released on 2003 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Bridge Deck Condition Assessment Using Destructive and Nondestructive Methods written by Brandon Tyler Goodwin and published by . This book was released on 2014 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This study investigates two bridge decks in the state of Missouri using both nondestructive and destructive testing methods. The Missouri Department of Transportation (MoDOT) is responsible for the monitoring and maintenance of over 10,000 bridges. Currently monitoring of these bridges includes a comprehensive visual inspection. In this study, ground-coupled ground penetrating radar (GPR) is used to estimate deterioration, along with other traditional methods, including visual inspection, and core evaluation. Extracted core samples were carefully examined, and the volume of permeable pore space was determined for each core. After the initial investigation, the two bridges underwent rehabilitation using hydrodemolition as a method to remove loose or deteriorated concrete. Depths and locations of material removal were determined using light detection and ranging (lidar). Data sets were compared to determine the accuracy of GPR to predict deterioration for condition monitoring and rehabilitation planning of bridge decks. As shown by the lidar survey of the material removed during rehabilitation, the GPR top reinforcement reflection amplitude accurately predicted regions of deterioration within the bridge decks. In general, regions with lower reflection amplitudes, indicating more evidence of deterioration, corresponded to regions with greater depths of material removal during the rehabilitation. Also, the GPR top reinforcement reflection amplitude indicated deterioration in areas where visual deterioration was noticed from the top surface of the deck. The majority of cores with delaminations were extracted from sections where the GPR top reinforcement reflection amplitude indicated greater evidence of deterioration based on lower amplitude values."--Abstract, page iii.

Download or read book Proceedings of the 1st International Congress on Engineering Technologies written by Suhil Kiwan and published by CRC Press. This book was released on 2021-09-30 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: This first volume in the Mosharaka for Research and Studies International Conference Proceedings series (P-MIC) contains peer-reviewed papers presented at the 1st International Congress on Engineering Technologies (EngiTek 2020). This event was held remotely on 16-18 June 2020, and hosted by the Faculty of Engineering, Jordan University of Science & Technology (Irbid, Jordan). The conference represented a major forum for professors, students, and professionals from all over the world to present their latest research results, and to exchange new ideas and practical experiences in the most cutting-edge areas of the field of engineering technologies. Topics covered include electrical engineering, computer science and electronics.

Download or read book Statistical Modeling of United States Highway Concrete Bridge Decks written by Omar Ghonima and published by . This book was released on 2017 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the backbone of the US transportation system, bridges are also its most visible part. There are over 600,000 bridges across all US states ensuring network continuity. In order to optimize such activities and use the available monies most effectively, a solid understanding of the parameters that affect the performance of concrete bridge decks is critical. The National Bridge Inventory (NBI), perhaps the single-most comprehensive source of bridge information, gathers data on more than 600,000 bridges in all fifty states, the District of Columbia, and the Commonwealth of Puerto Rico. Recently there has been a growing interest in analyzing the NBI database. The NBI uses visual inspection, a commonly practiced damage detection method, to rate bridge decks. Focusing on concrete highway bridge deck performance, the present study developed a nationwide database based on NBI data and other critical parameters, such as bridge age, deck area, climatic regions, and distance from seawater. Additionally, two new performance parameters were computed from the available concrete bridge deck condition ratings (CR): Time-in-condition rating (TICR) and deterioration rate (DR). Following the aggregation of all these parameters to form a nationwide database, filtering and processing were performed. Approaches to dealing with inconsistencies and missing data are proposed as well. After developing the nationwide database this research presents network-level, one-way statistical relationships to get a better understanding of the parameters. ☐ Next, a data mining technique on the nationwide database was used to analyze the data. Data mining is a discovery procedure to explore and visualize useful but less-than-obvious information or patterns embedded in large collections of data. Given the amount and variety of parameter types in a large data set such as that of the nationwide database, using traditional clustering techniques for discovery is impractical. As a consequence, this research has applied a novel data discovery tool called two-step cluster analysis to visualize associations between concrete bridge deck design parameters and bridge deck condition ratings. Two-step cluster analysis is a powerful knowledge discovery tool that can handle categorical and interval data simultaneously and is capable of reducing dimensions for large data sets. The two-step cluster analysis is a useful tool for bridge owners and agencies to visualize general trends in their concrete bridge deck condition data and support them in their decision-making processes to effectively allocate constrained funds for maintenance, repair, and design of bridge decks. ☐ Understanding the attributes of bridge deck performance is central to asset management. This research attempts to characterize how various environmental and structural parameters affect bridge deck performance by employing a binary logistic regression. The logistic model shows the relationship between a dependent variable (lowest vs. highest bridge deck deterioration) and the relative importance of a number of independent variables selected for this study (predictor variables). Observations of extreme bridge deck deterioration taken from the nationwide database were used in the model. Bridge deck deterioration was computed as the decrease in CR over time. Maintenance responsibility fulfillment, functional classification of inventory route, design and construction type, average daily truck traffic, climatic regions, and distance to seawater, were all used as independent variables. Our application of a binary logistic regression model for bridge deck deterioration provides practical insight regarding how certain parameters influence bridge deck performance. ☐ A leading factor in structural decline of highway bridges is the deterioration of concrete decks. Thus, a method to forecast bridge deck performance is vital for transportation agencies to allocate future repair and rehabilitation funds. The objective of this study was the development of a nationwide CR deterioration model based on the nationwide database through the use of a Bayesian statistical approach that predicts probability of CR decrease. In addition to CR data, the impact of other governing factors on CR decrease are shown in the paper, such as average daily truck traffic (ADTT), maintenance responsibility fulfillment, deck structure type, and regional climate effect. One singular advantage of this method is that it can be continually updated as additional NBI information becomes available. Moreover, the results of this model can be used as prior data in future Bayesian studies. The results presented in this study, by providing a better idea of how US concrete bridge decks are performing based on the NBI data, are intended to furnish a progressive bridge management system. ☐ Results yielded by each of the analysis above will encourage future researchers to add other crucial parameters not contained in the nationwide database such as structural design characteristics (e.g., minimum deck thickness), construction practices (e.g., curing practices), specifications (e.g., water-to-cement ratio), and other notable factors (e.g., application of deicing salts). Furthermore, analyze the nationwide database in various statistical application areas leading to more accurate understating of the factors affecting bridge deck deterioration and enhanced deck deterioration prediction models.

Download or read book Condition Assessment of Concrete Bridge Decks Using Ground Penetrating Radar written by Kien Dinh and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Development of Deterioration Models for Bridge Decks Using System Reliability Analysis written by Farzad Ghodoosipoor and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Damage Identification Progression and Condition Rating of Bridge Decks Using Multi modal Non destructive Testing written by Brian M. Pailes and published by . This book was released on 2014 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Bridge Deck Service Life Prediction and Costs written by and published by . This book was released on 2007 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: The service life of Virginia's concrete bridge decks is generally controlled by chloride-induced corrosion of the reinforcing steel as a result of the application of winter maintenance deicing salts. A chloride corrosion model accounting for the variable input parameters using Monte Carlo resampling was developed. The model was validated using condition surveys from 10 Virginia bridge decks built with bare steel. The influence of changes in the construction specifications of w/c = 0.47 and 0.45 and w/cm = 0.45 and a cover depth increase from 2 to 2.75 inches was determined. Decks built under the specification of w/cm = 0.45 (using slag or fly ash) and a 2.75 inch cover depth have a maintenance free service life of greater than 100 years, regardless of the type of reinforcing steel. Galvanized, MMFX-2, and stainless steel, in order of increasing reliability of a service life of greater than 100 years, will provide a redundant corrosion protection system. Life cycle cost analyses were conducted for polymer concrete and portland cement based overlays as maintenance activities. The most economical alternative is dependent on individual structure conditions. The study developed a model and computer software that can be used to determine the time to first repair and rehabilitation of individual bridge decks taking into account the time for corrosion initiation, time from initiation to cracking, and time for corrosion damage to propagate to a state requiring repair.

Download or read book Development and Validation of Deterioration Models for Concrete Bridge Decks written by Nan Hu and published by . This book was released on 2013 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report summarizes a research project aimed at developing degradation models for bridge decks in the state of Michigan based on durability mechanics. A probabilistic framework to implement local-level mechanistic-based models for predicting the chloride-induced corrosion of the RC deck was developed. The methodology is a two-level strategy: a three-phase corrosion process was modeled at a local (unit cell) level to predict the time of surface cracking while a Monte Carlo simulation (MCS) approach was implemented on a representative number of cells to predict global (bridge deck) level degradation by estimating cumulative damage of a complete deck. The predicted damage severity and extent over the deck domain was mapped to the structural condition rating scale prescribed by the National Bridge Inventory (NBI). The influence of multiple effects was investigated by implementing a carbonation induced corrosion deterministic model. By utilizing realistic and site-specific model inputs, the statistics-based framework is capable of estimating the service states of RC decks for comparison with field data at the project level. Predicted results showed that different surface cracking time can be identified by the local deterministic model due to the variation of material and environmental properties based on probability distributions. Bridges from different regions in Michigan were used to validate the prediction model and the results show a good match between observed and predicted bridge condition ratings. A parametric study was carried out to calibrate the influence of key material properties and environmental parameters on service life prediction and facilitate use of the model. A computer program with a user-friendly interface was developed for degradation modeling due to chloride induced corrosion.

Download or read book An Integrated Method for Optimizing Bridge Maintenance Plans written by Eslam Mohammed Abdelkader and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bridges are one of the vital civil infrastructure assets, essential for economic developments and public welfare. Their large numbers, deteriorating condition, public demands for safe and efficient transportation networks and limited maintenance and intervention budgets pose a challenge, particularly when coupled with the need to respect environmental constraints. This state of affairs creates a wide gap between critical needs for intervention actions, and tight maintenance and rehabilitation funds. In an effort to meet this challenge, a newly developed integrated method for optimized maintenance and intervention plans for reinforced concrete bridge decks is introduced. The method encompasses development of five models: surface defects evaluation, corrosion severities evaluation, deterioration modeling, integrated condition assessment, and optimized maintenance plans. These models were automated in a set of standalone computer applications, coded using C#.net in Matlab environment. These computer applications were subsequently combined to form an integrated method for optimized maintenance and intervention plans. Four bridges and a dataset of bridge images were used in testing and validating the developed optimization method and its five models. The developed models have unique features and demonstrated noticeable performance and accuracy over methods used in practice and those reported in the literature. For example, the accuracy of the surface defects detection and evaluation model outperforms those of widely-recognized machine leaning and deep learning models; reducing detection, recognition and evaluation of surface defects error by 56.08%, 20.2% and 64.23%, respectively. The corrosion evaluation model comprises design of a standardized amplitude rating system that circumvents limitations of numerical amplitude-based corrosion maps. In the integrated condition, it was inferred that the developed model accomplished consistent improvement over the visual inspection procedures in-use by the Ministry of Transportation in Quebec. Similarly, the deterioration model displayed average enhancement in the prediction accuracies by 60% when compared against the most commonly-utilized weibull distribution. The performance of the developed multi-objective optimization model yielded 49% and 25% improvement over that of genetic algorithm in a five-year study period and a twenty five-year study period, respectively. At the level of thirty five-year study period, unlike the developed model, classical meta-heuristics failed to find feasible solutions within the assigned constraints. The developed integrated platform is expected to provide an efficient tool that enables decision makers to formulate sustainable maintenance plans that optimize budget allocations and ensure efficient utilization of resources.

Download or read book Condition Analysis of Concrete Bridge Decks in Utah written by Robert S. Tuttle and published by . This book was released on 2005 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: Several evaluation techniques were employed to assess concrete bridge deck condition, including visual inspection, hammer sounding and chaining, dielectric measurements, ground-penetrating radar imaging, resistivity testing, half-cell potential testing, and chloride concentration testing. The condition assessment testing confirmed that chloride-induced corrosion of reinforcing steel is the primary mechanism of deck deterioration and that inadequate cover over the upper steel mat facilitated accelerated corrosion damage in many instances. The bridge deck condition analyses produced from the results of non-destructive testing were compared to the visual inspection ratings assigned to each deck by UDOT.

Download or read book Updating Bridge Deck Condition Transition Probabilities as New Inspection Data are Collected written by Zequn Li and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Deterioration is among the primary concerns regarding the structural performance and functionality of bridges and their components. In light of annual budget constraints, infrastructure agencies, such as state Departments of Transportation (DOTs) in the US, prioritize their bridge maintenance needs. To make trade-offs across bridges and over time, key inputs to the prioritization and decision making process are bridge condition assessments and predictions. In this study, a Bayesian updating procedure is proposed to estimate a Markov Chain based concrete deck deterioration model in a manner that combines condition data collected over two inspection cycles and the deterioration information available prior to the collection of these condition data. Single period (one year) transition probabilities are estimated using Bayesian updating and maximum likelihood estimation, where in the case of the latter only the collected condition data over two inspection cycles are used.

Download or read book Field Investigation And Statistical Modeling Of In service Performance Of Concrete Bridge Decks In Pennsylvania written by Amir Manafpour and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The condition of the nation's aging infrastructure has been of the highest concern in recent decades. FHWA estimates that $20.5 billion will need to be invested annually in order to eliminate the United States' bridge deficient backlog by 2028. Bridge deck deterioration is one of the primary concerns and cost factors for transportation agencies. Pennsylvania has one of the highest percentages of structurally deficient and functionally obsolete bridges in the USA. This thesis is structured in two papers/studies related to the performance of concrete bridge decks in Pennsylvania.The first paper summarizes the results of expert survey and field investigations of early-age bridge deck cracking in the Commonwealth of Pennsylvania. The goal was to use field data to identify factors that contribute to or reduce early-age cracking in concrete bridge decks and to assess the effect of cracks on long-term durability performance of bridge decks. First, a survey of 71 PennDOT personnel was conducted to collect and document their experience with early-age cracking and its relation to long-term deck performance. Next, inspection data from 203 bridge decks were collected and analyzed to evaluate the effect of concrete mixture proportions and properties, construction methods, and rebar type on the propensity to experience early-age deck cracking. The results suggest that limiting the total cementitious materials content (e.g., to 620 pcy) and the maximum compressive strength (e.g., to 5000 psi at 28 days) is advisable to reduce deck cracking. In addition, epoxy-coated rebar showed good corrosion resistance even in cracked concrete.The second paper focuses on evaluating the deterioration behavior of concrete bridge decks over time. Considering the stochastic nature of infrastructure deterioration, studies have found that time-based probabilistic models are the most accurate for performance prediction. In this paper, a semi-Markov time-based model based on Accelerated Failure Time (AFT) Weibull fitted-parameters is developed. For this purpose, approximately 30 years of in-service performance data for over 22,000 bridges in Pennsylvania were utilized. The proposed approach attempts to relate deck deterioration rates to various explanatory variables such as structural specifications and environmental factors. Furthermore, the effect of remediation on bridge deck deterioration and service life are also evaluated and quantified based on in-service performance data.