• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.7
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• pp.36-45
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• 2002

Most of rural bridges have passed 30 years of age since they were built, which have to support unexpected overload caused by changed design load and excessive amount of transportation. For these rural bridges, repairs and replacements are needed. Even though there have been attempt to estimate the safety of existing bridges deteriorated with major defects, those approaches must rely on the observable damage and subsequent decisions are made subjectively. To avoid the high cost of rehabilitation, the bridge rating must correctly represent the present load-carrying capacity. Rating engineers use a methods such as Allowable Stress Design (ASD), Load Factor Design (LFD), and Load Resistance Factor Design (LRFD) to evaluate the bridge load carrying capacity. In this paper, the load rating methods are introduced, and it is illustrated how to use the load test data from literature survey. Load test is conducted to the bridge that was built 30 years ago in rural area. From load test results, new maintenance method is suggested instead of the bridge replacement.

• Journal of the Korea institute for structural maintenance and inspection
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• v.7 no.1
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• pp.239-249
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• 2003

The bridges, which were built between 20 and 30 years ago in rural area, have to support unexpected overload caused by excessive amount of transportation. For these rural bridges, repairs and replacements are needed. To avoid the high cost of rehabilitation, the bridge rating must correctly report the present load-carrying capacity. Rating engineers use Allowable Stress Design (ASD), Load Factor Design (LFD), and Load Resistance Factor Design (LRFD) to evaluate the bridge load carrying capacity. In this paper, the load rating methods are introduced, and it is illustrated how to use the load test data from literature survey. Load test is conducted to the bridge that was built 30 years ago in rural area. From load test results, new maintenance strategy is suggested instead of the bridge replacement.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.11 no.4
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• pp.9-15
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• 1991

This study is directed for the development of rational rating models for realistic safety assessment and the computer rating system for highway bridges. For this purpose, the conventional rating system is considerably improved in appropriate way, and a rational rating system based on the reliabilty method is proposed to estimate safety of deteriorated bridges by using only the visual inspection data or the statistical data available. In addition. the rating system which can assess the realistic allowable passing tonnage of military vehicles in case of the military operations is also presented. From this study, it is known that the presented rating system and the computer program BRS(Bridge Rating System) provide an effective tool which can handle the degree of deterioration and various uncertainities of the bridge systematically. so it can be used widely for assessment of safety and load carrying capacity of existing deteriorated or damaged bridges.

• Journal of the Korean Society for Advanced Composite Structures
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• v.1 no.1
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• pp.34-45
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• 2010

This paper describes the design, manufacturing process, testing, application, and assessment of capacity-ratings of the first all advanced composites bridge on a public highway system. In order to verify the bridge design prior to the field application, a sub-scale bridge superstructure was built and tested in the laboratory. The field load test results were compared with those of the finite element analysis for the verification of validity. To investigate its in-service performance, field load testing and visual inspections were conducted under an actual service environment. The paper includes the presentation and discussion for advanced composites bridge capacity rating based on the stress modification coefficients obtained from the test results. The test result indicates that the advanced composites bridge has no structural problems and is structurally performing well in-service as expected. Since these composite materials are new to bridge applications, reliable data is not available for their in-service performance. The results may provide a baseline data for future field advanced composites bridge capacity rating assessments and also serve as part of a long-term performance of advanced composites bridge.

• Journal of the Korean Society of Safety
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• v.18 no.1
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• pp.108-115
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• 2003

Bridges are rated at two levels by either Load Factor Design (LFD) or Allowable Stress Design (ASD). The lower level rating is called Inventory Rating and the upper level rating is called Operating Rating. To maintain bridges effectively, there is an urgent need to assess actual bridge loading carrying capacity and to predict their remaining life from a system reliability viewpoint. The lifetime functions are introduced and explained to predict the time-dependent failure probability. The bridge studied in this paper was built 30 years ago in rural area. For this bridge, the load test and rehabilitation were conducted. The time-dependent system failure probability is predicted with or without rehabilitation. As a case study, an optional rehabilitation is suggested, and fir this rehabilitation, load rating is computed and the time-dependent system failure probability is predicted. Based on rehabilitation costs and extended service lifes, the optimal rehabilitation is suggested.

• Structural Engineering and Mechanics
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• v.47 no.5
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• pp.643-660
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• 2013

In the present work, the capacity ratings of steel truss bridges have been carried out incorporating dynamic effect of moving vehicles and its accumulating effect as fatigue. Further, corrosion in the steel members has been taken into account to examine the rating factor. Dynamic effect has been considered in the rating procedure making use of impact factors obtained from simulation studies as well as from codal guidelines. A steel truss bridge has been considered to illustrate the approach. Two levels of capacity ratings- the upper load level capacity rating (called operating rating) and the lower load level capacity rating (called inventory rating) were found out using Load and Resistance Factor Design (LRFD) method and a proposal has been made which incorporates fatigue in the rating formula. Random nature of corrosion on the steel member has been taken into account in the rating by considering reduced member strength. Partial safety factor for each truss member has been obtained from the fatigue reliability index considering random variables on the fatigue parameters, traffic growth rate and accumulated number of stress cycle using appropriate probability density function. The bridge has been modeled using Finite Element software. Regressions of rating factor versus vehicle gross weight have been obtained. Results show that rating factor decreases when the impact factor other than those in the codal provisions are considered. The consideration of fatigue and member corrosion gives a lower value of rating factor compared to those when both the effects are ignored. In addition to this, the study reveals that rating factor decreases when the vehicle gross weight is increased.

• Smart Structures and Systems
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• v.13 no.6
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• pp.901-925
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• 2014

The reliability of a Bridge management System depends on the quality of visual inspection and the reliable estimation of bridge condition rating. However, the current practices of visual inspection have been identified with several limitations, such as: they are time-consuming, provide incomplete information, and their reliance on inspectors' experience. To overcome such limitations, this paper presents an approach of automating the prediction of condition rating for bridges based on digital image analysis. The proposed methodology encompasses image acquisition, development of 3D visualization model, image processing, and condition rating model. Under this method, scaling defect in concrete bridge components is considered as a candidate defect and the guidelines in the Ontario Structure Inspection Manual (OSIM) have been adopted for developing and testing the proposed method. The automated algorithms for scaling depth prediction and mapping of condition ratings are based on training of back propagation neural networks. The result of developed models showed better prediction capability of condition rating over the existing methods such as, Naïve Bayes Classifiers and Bagged Decision Tree.

• Journal of the Korea institute for structural maintenance and inspection
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• v.5 no.3
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• pp.115-122
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• 2001

Bridge load rating calculations provide a basis for determining the load carrying capacity of bridges. Load rating requires engineering judgement in determining a rating value that is applicable to maintaining the safe use of the bridge and arriving at posting and permit decisions. Load testing is an effective means in calculating the rating value of bridge. In Korea, load carrying capacity of bridge is modified by response modification factor that is determined from comparisons of measured values and analysis results. This paper presents the development of a method for determining the response the modification factor, using traffic loads. The proposed method is based on the results of computer simulations of traffic action effects. The simulation program generates random traffic actions for defined traffic conditions and determines the frequency distribution of maximum traffic action effects. A comparison between the proposed method and the present method shows good agreement in estimating the modified load carrying capacity of bridges.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.533-538
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• 2005

An outline of an Artificial Neural Network (ANN) model for bridge condition rating and the results of a pilot study are presented in this paper. Most BMS implementation systems involve an extensive range of data collection to operate accurately. It takes many years to effectively implement a BMS using existing methodologies. This is due to unmatched data requirements. Such problems can be overcome by adopting the ANN model presented in this paper. The objective of the proposed model is to predict bridge condition ratings using historical bridge inspection data for effective BMS operation.

• Structural Monitoring and Maintenance
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• v.2 no.3
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• pp.199-211
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• 2015

The safety and performance of bridges could be monitored and evaluated by Structural Health Monitoring (SHM) systems. These systems try to identify and locate the damages in a structure and estimate their severities. Current SHM systems are applied to a single bridge, and they have not been used to monitor the structural condition of a network of bridges. This paper propose a new method which will be used in Synthetic Rating Procedures (SRP) developed by the authors of this paper and utilizes SHM systems for monitoring and evaluating the condition of a network of bridges. Synthetic rating procedures are used to assess the condition of a network of bridges and identify their ratings. As an additional part of the SRP, the method proposed in this paper can continuously monitor the behaviour of a network of bridges and therefore it can assist to prevent the sudden collapses of bridges or the disruptions to their serviceability. The method could be an important part of a bridge management system (BMS) for managers and engineers who work on condition assessment of a network of bridges.