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Deterioration Prediction Modeling for the Condition Assessment of Concrete Bridge Decks

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Author :
Release : 2018
Genre : Concrete bridges
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Book Synopsis Deterioration Prediction Modeling for the Condition Assessment of Concrete Bridge Decks by : Aqeed Mohsin Chyad

Download or read book Deterioration Prediction Modeling for the Condition Assessment of Concrete Bridge Decks written by Aqeed Mohsin Chyad. This book was released on 2018. 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.

Deterioration Prediction Models for Condition Assessment of Concrete Bridge Decks Using Machine Learning Techniques

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Author :
Release : 2021
Genre : Bridge failures
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Book Synopsis Deterioration Prediction Models for Condition Assessment of Concrete Bridge Decks Using Machine Learning Techniques by : Nour Hider Almarahlleh

Download or read book Deterioration Prediction Models for Condition Assessment of Concrete Bridge Decks Using Machine Learning Techniques written by Nour Hider Almarahlleh. This book was released on 2021. 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.

Nondestructive Testing to Identify Concrete Bridge Deck Deterioration

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Author :
Release : 2013
Genre : Technology & Engineering
Kind : eBook
Book Rating : 338/5 ( reviews)

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Book Synopsis Nondestructive Testing to Identify Concrete Bridge Deck Deterioration by :

Download or read book Nondestructive Testing to Identify Concrete Bridge Deck Deterioration written by . This book was released on 2013. Available in PDF, EPUB and Kindle. Book excerpt: " TRB's second Strategic Highway Research Program (SHRP 2) Report S2-R06A-RR-1: Nondestructive Testing to Identify Concrete Bridge Deck Deterioration identifies nondestructive testing technologies for detecting and characterizing common forms of deterioration in concrete bridge decks.The report also documents the validation of promising technologies, and grades and ranks the technologies based on results of the validations.The main product of this project will be an electronic repository for practitioners, known as the NDToolbox, which will provide information regarding recommended technologies for the detection of a particular deterioration. " -- publisher's description.

Development and Validation of Deterioration Models for Concrete Bridge Decks

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Author :
Release : 2013
Genre : Concrete bridges
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Book Synopsis Development and Validation of Deterioration Models for Concrete Bridge Decks by : Emily K. Winn

Download or read book Development and Validation of Deterioration Models for Concrete Bridge Decks written by Emily K. Winn. This book was released on 2013. 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.

Condition Assessment of Concrete Bridge Decks Using Ground Penetrating Radar

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Author :
Release : 2014
Genre :
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Book Synopsis Condition Assessment of Concrete Bridge Decks Using Ground Penetrating Radar by : Kien Dinh

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

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