• Corrosion Science and Technology
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• v.3 no.4
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• pp.166-171
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• 2004

Recent developments in Bridge Management Systems (BMS) and in Life-Cycle Cost (LCC) of bridges, have raised the need for evaluation procedure of future condition (Deterioration) of a bridge. Predicting future deterioration is not an easy task due to limited past data to extrapolate from and also due to difficulty in measuring actual deterioration such as section loss of steel on an actual steel bridge. Also, increase in live load and reduction of resistance are random variables, thus a probabilistic approach should be adopted for determining the future deterioration. Due to difficulties in evaluation of future deterioration on steel bridges, accepting uncertainties within a reasonable error, a deterministic procedure using bridge condition rating can be a useful tool for projection of future condition of bridges to identify repair and maintenance needs. The object of this paper is to determine applicability of evaluating deterioration of steel bridge components based on Bridge condition ratings. Bridge condition ratings of bridge components show wide variation for bridges of same age and does not directly correlate well with the age of the bridge and/or deterioration of the bridge. High uncertainty can be reduced by breaking down the rating and by sensitivity analysis. From refined condition rating data, generalized deterioration profile of structures based on age can be derived. Examples are shown for sample bridges in USA. Approximately, 3,000 short to medium span steel bridges were listed in the inventory database. Results show wide variation of rating factors but by subdividing the Bridge condition ratings for various categories general deterioration profiles of steel bridges can be determined.

• 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.

• International Journal of Highway Engineering
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• v.15 no.3
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• pp.37-44
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• 2013

PURPOSES: This study is to develop the deduct value curves for the calculation of pavement condition index of asphalt airfield pavement. METHODS: To develop the deduct value curves of asphalt airfield pavement, panel rating was conducted to decide the pavement condition based on pavement distress type, severity, and density. RESULTS: Results show that standard deviation of deduct values by panel rating is increased at higher severity level and as damage density increases. The deduct value of alligator cracking show the highest. CONCLUSIONS: The deduct value curves based on panel rating could be used without existing problems which were occurred in Shahin's method.

• Journal of the Korea institute for structural maintenance and inspection
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• v.6 no.1
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• pp.111-118
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• 2002

Currently, the inspection of bridges is conduced for the parts or elements of a bridges and the results of inspection are depicted for those local elements. Therefore, the representative rating of a bridge as a whole bridge system is not presented. The purpose of the present study is to purpose a reasonable method which can yield realistic representative rating for an actual bridge. The purpose method consists of two steps, i.e, visual inspection step and safety assessment step. The importance of members is considered by introducing the weighting factors and the number of spans is also considered to obtain the representative rating of a whole bridge system. The purpose method may be efficiently used to calculate the realistic representative rating bridge structures.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.347-354
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• 1999

The credit rating represents an assessment of the relative level of risk associated with the timely payments required by the debt obligation. In this paper, we present a new approach to credit rating of customers based on the rough set theory. The concept of a rough set appeared to be an effective tool for the analysis of customer information systems representing knowledge gained by experience. The customer information system describes a set of customers by a set of multi-valued attributes, called condition attributes. The customers are classified into groups of risk subject to an expert's opinion, called decision attribute. A natural problem of knowledge analysis consists then in discovering relationships, in terms of decision rules, between description of customers by condition attributes and particular decisions. The rough set approach enables one to discover minimal subsets of condition attributes ensuring an acceptable quality of classification of the customers analyzed and to derive decision rules from the customer information system which can be used to support decisions about rating new customers. Using the rough set approach one analyses only facts hidden in data, it does not need any additional information about data and does not correct inconsistencies manifested in data; instead, rules produced are categorized into certain and possible. A real problem of the evaluation of the evaluation of credit rating by a department store is studied using the rough set approach.

• 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.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.396-397
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• 2008

In order to evaluate the nominal rating of breakers in distribution system due to the increased capacity of power transformer from 60 to 100 MVA, the fault currents are calculated in the condition of 3-phase fault and single line-to-ground fault. Consequently, under the condition of the parallel operation of transformers the fault currents were exceed the nominal rating current of breakers in some areas.

• The Korean Nurse
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• v.31 no.5
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• pp.53-64
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• 1992

A nurse is give much weight in the professions of hospital.The effective achievement of a goal of hospital organization needs to get nurses to contribute the structure positively through the rational personnel management of the nurses.The operation of performance rating system is necessary to improve because the nurses hold negative opinions about the resonable management of that system in most Korean hospitals.Therefore, the prupose of this research was to suggest an efficient method to solve the problem in connection with the management of nurses performance rating system.The results of the study are summarized as follows.1. As the performance rating implies the evaluation of employee's functional accomplishment and ability, and essential condition of the job was surveyed according to the job analysis of nursing activities and nurse position.That is to say, Nusrses' performances and capability is estimated in comparision with the condition of the job. 2. It is required adequacy for evaluation factors in performance rating.That is, $\circled1$ as for those who work in psychiatry or newborn baby room they should be appraied in terms of different factors from those applicable to whom work in a general staffs. $\circled2$ Evaluation factors should be concrete so that the quality and quantity of work and the potential ability of them can be correctly appraised. 3. In order to realize the object of perfamance rating system, the training on chief nurses are quite important. Also, careful practices and continuous supplementary training are required before the system is introduced.First of all, the appropriate evaluation can be mad by continuing to record the rating objects every day for the purpose of obtaining the objectivity of rating. 4. In course of transfering of the position and training, the induction of self-rating system and presentation of self-description is required to supplement functionally the performance rating system. 5. For the efficiency of nurses' performance rating system, the results of performance rating system must be reflected in promotion, allocation and training course, which makes the nurses have the motives and the organization accomplish the goal of modern nursing through its activation.

• 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.

• Smart Structures and Systems
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• v.15 no.3
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• pp.751-767
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• 2015

A new procedure is proposed for assessing probabilistic condition of structures considering effect of measured data uncertainty. In this procedure, multiple Finite Element (FE) models are identified by using weighting vectors that represent the uncertainty conditions of measured data. The distribution of structural parameters is analysed using a Principal Component Analysis (PCA) in relation to uncertainty conditions, and the identified models are classified into groups according to their similarity by using a K-means method. The condition of a structure is then assessed probabilistically using FE models in the classified groups, each of which represents specific uncertainty condition of measured data. Yeondae bridge, a steel-box girder expressway bridge in Korea, is used as an illustrative example. Probabilistic condition of the bridge is evaluated by the distribution of load rating factors obtained using multiple FE models. The numerical example shows that the proposed method can quantify uncertainty of measured data and subsequently evaluate efficiently the probabilistic condition of bridges.