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Development Of Bridge Deterioration Models For The Alabama Bridge Information Management System
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Book Synopsis Development of Bridge Deterioration Models for the Alabama Bridge Information Management System by : Daniel S. Turner
Download or read book Development of Bridge Deterioration Models for the Alabama Bridge Information Management System written by Daniel S. Turner and published by . This book was released on 1991 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Development of Bridge Deterioration Models for the Alabama Bridge Information Management System for the State of Alabama Highway Department by : Daniel S. Turner
Download or read book Development of Bridge Deterioration Models for the Alabama Bridge Information Management System for the State of Alabama Highway Department written by Daniel S. Turner and published by . This book was released on 1991 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Bridge Deterioration Models to Support Indiana's Bridge Management System by : Milhan Moomen
Download or read book Bridge Deterioration Models to Support Indiana's Bridge Management System written by Milhan Moomen and published by . This book was released on 2016-12-31 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: An effective bridge management system that is equipped with reliable deterioration models enables agency engineers to carry out monitoring and long-term programming of bridge repair actions. At the project level, deterioration models help the agency to track the physical condition of bridge elements and to specify when bridge maintenance, rehabilitation and replacement can be expected. Also, with reliable deterioration models, the agency can customize bridge repair or replacement schedules that incorporate element condition, functional obsolescence, and pre-specified performance thresholds. At the network level, component-specific deterioration models are useful for system-wide needs assessment over a specified future time horizon, and to quantifying the system-wide consequences of funding shortfalls or funding increases in terms of specified performance measures including average values of bridge condition and remaining service life. The bridge deterioration models that are currently in use in the Indiana Bridge Management System were developed over two decades ago. Since then, significant changes have taken place in inspection methods, technologies used, advanced statistical tools for data analysis. Also, because of the lack of reliable data, such items as the truck traffic and climate conditions were not included in past modeling efforts. In recent years, these obstacles have been minimized and therefore, there is an opportunity to update the deterioration models for the various bridge components. In addressing this research need, the present study developed families of curves representing deterioration models for bridge deck, superstructure, and the substructure. The National Bridge Inventory database was used, and the models use the NBI condition ratings as the response variable. The model families were categorized by administrative region, functional class, and superstructure material type. The explanatory variables include traffic volume and truck traffic, design type, and climatic condition, and design features. Deterministic and probabilistic models were developed.
Book Synopsis Development of Deficiency Point Algorithms by : James A. Richardson
Download or read book Development of Deficiency Point Algorithms written by James A. Richardson and published by . This book was released on 1991 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Development of ALBRIDGE by : James L. Keating
Download or read book Development of ALBRIDGE written by James L. Keating and published by . This book was released on 1994 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Development of Deficiency Point Algorithms for the Alabama Bridge Information Management System by : James A. Richardson
Download or read book Development of Deficiency Point Algorithms for the Alabama Bridge Information Management System written by James A. Richardson and published by . This book was released on 1991 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Development of Enhanced Maintenance Procedures and Linkage to the Project Management System for the Alabama Bridge Information Management System by : Daniel S. Turner
Download or read book Development of Enhanced Maintenance Procedures and Linkage to the Project Management System for the Alabama Bridge Information Management System written by Daniel S. Turner and published by . This book was released on 1992 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Development of Performance and Deterioration Curves as a Rational Basis for a Maintenance Management System for Structures by : Kevin K. McGhee
Download or read book Development of Performance and Deterioration Curves as a Rational Basis for a Maintenance Management System for Structures written by Kevin K. McGhee and published by . This book was released on 1993 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Virginia Department of Transportation is deeply committed to the development and implementation of an efficient, cost-effective maintenance management system for its bridges. Much effort is being applied towards the development of a management system that will ensure that appropriate maintenance takes place at the optimum times. Within such systems, the ability to anticipate with reasonable accuracy how rapidly and in what fashion bridges will deteriorate is essential in optimizing expenditures of limited maintenance funds. The research described in this report was undertaken to provide this predictive capability. Specifically, the objective was to use existing bridge inspection data in conjunction with multiple regression analyses to develop models relating the rate of deterioration of structural components with variables such as age, loadings, and environmental factors and to evaluate the relative importance of these variables. In addition, these efforts include a discussion of current bridge management activities and recommendations on needed modifications to the VDOT record-keeping system.
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 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.
Book Synopsis Designation of Supplementary Data Items for the Alabama Bridge Information Management System by : Daniel S. Turner
Download or read book Designation of Supplementary Data Items for the Alabama Bridge Information Management System written by Daniel S. Turner and published by . This book was released on 1991 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Background Study and Preliminary Design of the Alabama Bridge Information Management System by : Daniel S. Turner
Download or read book Background Study and Preliminary Design of the Alabama Bridge Information Management System written by Daniel S. Turner and published by . This book was released on 1991 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Investigating and Improving Bridge Management System Methodologies Under Uncertainty by : Minwoo Chang
Download or read book Investigating and Improving Bridge Management System Methodologies Under Uncertainty written by Minwoo Chang and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation presents a novel procedure to select explanatory variables, without the influence of human bias, for deterioration model development using National Bridge Inventory (NBI) data. Using NBI information, including geometric data and climate information, candidate explanatory variables can be converted into normalized numeric values and analyzed prior to the development of deterministic or stochastic deterioration models. The prevailing approach for explanatory variable selection is to use expert opinion solicited from experienced engineers. This may introduce human influenced biases into the deterioration modeling process. A framework using Least Absolute Shrinkage and Selection Operator (LASSO) penalized regression and covariance analysis are combined to compensate for this potential bias. Additionally, the cross validation analysis and solution path is used as a standard for the selection of minimum number of explanatory variables. The proposed method is demonstrated through the creation of deterministic deterioration models for deck, superstructure, and substructure for Wyoming bridges and compared to explanatory variables using the expert selection method. The comparison shows a significant decrease in error using the presented framework based on the L2 relative error norm. The final chapter presents a new method to develop stochastic deterioration models using logistic regression. The relative importance amongst explanatory variables is used to develop a classification tree for Wyoming bridges. The bridges in a subset are commonly associated with several explanatory variables, so that the deterioration models can be more representative and accurate than using a single explanatory variable. The logistic regression is used to introduce the stochastic contribution into the deterioration models. In order to avoid missing data problems, the binary categories condition rating, either remaining the same or decreased, are considered for logistic regression. The probability of changes in bridges0́9 condition rating is obtained and the averages for same condition ratings are used to create transition probability matrix for each age group. The deterioration model based on Markov chain are developed for Wyoming bridges and compared with the previous model based on percentage prediction and optimization approach. The prediction error is analyzed, which demonstrates the considerable performance of the proposed method and is suitable for relatively small data samples.
Book Synopsis Case-based Reasoning for Modeling Bridge Deterioration by :
Download or read book Case-based Reasoning for Modeling Bridge Deterioration written by and published by . This book was released on 2000 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Development of a Markov Model for Bridge Deterioration with Applications to Bridge Management by : Merriann Christine Erkel
Download or read book Development of a Markov Model for Bridge Deterioration with Applications to Bridge Management written by Merriann Christine Erkel and published by . This book was released on 1990 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Adaptive Optimization Methods in System-Level Bridge Management by : Haotian Liu
Download or read book Adaptive Optimization Methods in System-Level Bridge Management written by Haotian Liu and published by . This book was released on 2013 with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt: In 2012, over 25% of the bridges in the United States were rated as structurally deficient or functionally obsolete. Moreover, 35% of bridges are serving beyond their theoretical design lifespan and the number has been projected to increase over the next decade. The imperative needs of improving the overall condition of the bridge system has been impeded by the shortage of funding available for bridge repairs and maintenance. In 2006 the gap between Federal Highway Administration's (FHWA) estimates to eliminate the bridge maintenance backlog and the actual appropriations to bridges for repairs and maintenance from the Highway Bridge Program was $43.4 Billion. In 2009, the gap increased to $65.7 Billion. Such conflict has made effective bridge management more critical than ever. In bridge management, agencies collect bridge condition data and develop deterioration models that predict the bridges' future conditions and associated costs, based on which maintenance, rehabilitation and reconstruction (MR & R) decisions are made. It is therefore critical to have accurate deterioration models. However, limited availability of data and incomplete understanding of the deterioration process result in inaccurate models, which lead to sub-optimal MR & R decisions and significant cost increases. To address the inaccuracy stemming from limited bridge condition data, researchers have proposed Adaptive Control (AC) methods that update the deterioration models successively as new data become available. The underlying belief is that agencies can obtain more accurate deterioration models through updating and subsequently improve their MR & R decisions and achieve cost savings. State-of-the-art bridge management systems, such as Pontis, use a class of AC procedures known as Certainty Equivalent Control (CEC). The procedure used in Pontis updates the transition probabilities (i.e., the parameters of the component deterioration models) after each condition survey, and uses the updated probabilities in subsequent planning of MR & R decisions. Unfortunately, CEC does not necessarily lead to more accurate models, or guarantee savings in system costs; in other words, updating of the type in Pontis is not necessarily beneficial. In the present dissertation, an AC method, Open-Loop Feedback Control (OLFC), is proposed for system-level bridge management. The performance of OLFC and the Pontis CEC is tested in a numerical study and empirical results show that OLFC has superior performance with respect to two criteria. In terms of improvement in model accuracy, the Pontis CEC yields systematic bias in model parameter estimates and therefore does not improve model accuracy. In all testing scenarios, the resulting deterioration models lead to faster deterioration than the true models. OLFC, on the other hand, results in consistent convergence to the true models in all testing scenarios and improves model accuracy. When evaluated by system costs, the Pontis CEC consistently results in higher system costs than the no-updating scenario. The increases are on the order of $180 Million at the level of the State of California. To the contrary, updating with OLFC consistently achieves system costs savings compared to the no-updating scenario, and results in system costs that do not differ significantly from the system costs when true models are used for MR & R decision-making. In addition, a computationally tractable optimization routine is developed for MR & R decision-making. The routine ensures strict conformity to system budget constraints and achieves satisfactory computational efficiency even given high levels of heterogeneity in bridge systems.
Book Synopsis Development of Deterioration Models for Bridge Decks Using System Reliability Analysis by : Farzad Ghodoosipoor
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:
Book Synopsis Developing Bridge Deterioration Model Using Artificial Neural Network and Markov Chain by : Essam Althaqafi
Download or read book Developing Bridge Deterioration Model Using Artificial Neural Network and Markov Chain written by Essam Althaqafi and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most transportation agencies in the U.S. are facing the challenge of fixing the aging transportation infrastructures with insufficient budget. Pavements and bridges are the two major components of transportation infrastructures. Bridges in very poor condition could become unsafe for the traveling public to drive across. Deteriorating bridge condition coupled with ever increasing costs to maintain, repair, and rehabilitate bridges means difficult budget allocation decisions must be made to keep all bridges in safe operating condition and extending the service life of existing bridges. The existing and projected condition of a bridge is therefore an important input for the decision-making process. Many transportation agencies utilize Bridge Management System (BMS) to help with managing thousands or, sometimes, tens of thousands of bridges. BMS enable agencies to make critical rehabilitation and reconstruction decisions based on systematically collected bridge condition data and projected deterioration trends. This study focuses on developing bridge condition deterioration models to help provide a more accurate prediction of future bridge conditions. Historical bridge condition data for bridges under the jurisdiction of the Ohio Department of Transportation from 1992 to 2019 were obtained from the National Bridge Inventory (NBI) database. These data include ratings for bridge deck, superstructure, and substructure of each bridge, as well as various characteristics of that bridge, such as age of bridge (years in service), bridge materials, structure type, length, width, maintenance done, etc. Two condition prediction models, one based on the Artificial Neural Network (ANN) method, and the other based on the Markov Transitional Probability method, were developed. The results show that the ANN model can produce significantly better results than the Markov model in predicting future bridge condition ratings.
