• 국제학술발표논문집
• /
• The 3th International Conference on Construction Engineering and Project Management
• /
• pp.700-706
• /
• 2009

Bridges are vital components of any road network which demand crucial and timely decision-making for Maintenance, Repair and Rehabilitation (MR&R) activities. Bridge Management Systems (BMSs) as a decision support system (DSS), have been developed since the early 1990's to assist in the management of a large bridge network. Historical condition ratings obtained from biennial bridge inspections are major resources for predicting future bridge deteriorations via BMSs. Available historical condition ratings in most bridge agencies, however, are very limited, and thus posing a major barrier for obtaining reliable future structural performances. To alleviate this problem, the verified Backward Prediction Model (BPM) technique has been developed to help generate missing historical condition ratings. This is achieved through establishing the correlation between known condition ratings and such non-bridge factors as climate and environmental conditions, traffic volumes and population growth. Such correlations can then be used to obtain the bridge condition ratings of the missing years. With the help of these generated datasets, the currently available bridge deterioration model can be utilized to more reliably forecast future bridge conditions. In this paper, the prediction accuracy based on 4 and 9 BPM-generated historical condition ratings as input data are compared, using deterministic and stochastic bridge deterioration models. The comparison outcomes indicate that the prediction error decreases as more historical condition ratings obtained. This implies that the BPM can be utilised to generate unavailable historical data, which is crucial for bridge deterioration models to achieve more accurate prediction results. Nevertheless, there are considerable limitations in the existing bridge deterioration models. Thus, further research is essential to improve the prediction accuracy of bridge deterioration models.

• Corrosion Science and Technology
• /
• 제3권4호
• /
• pp.166-171
• /
• 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.

• 한국콘크리트학회:학술대회논문집
• /
• 한국콘크리트학회 2000년도 가을 학술발표회 논문집(II)
• /
• pp.1291-1296
• /
• 2000

A basis for the direct use of data from nondestructive evaluation methods in bridge management systems is presented. Bridge management systems use integer-valued condition ratings to recognize conditions of bridge elements, to model progression of deterioration, and to determine repair needs. Data from nondestructive evaluation methods can inform management systems on the extent of damage, on the initiation of deterioration processes, and on the exposure of bridge elements to aggressive agents. In addition, data obtained through nondestructive evaluation methods allow the formation of models of specific deterioration process. The use of these data in bridge management systems requires redefinition of condition ratings together with the creation of procedures for automated interpretation of data. By these action, nondestructive evaluation methods are directly used to assign condition ratings, and condition ratings are made into terse form of NDE data that are compatible with present day bridge management systems. This paper reports work in progress to strategic use of nondestructive evaluation methods in bridge management system.

• 한국철도학회논문집
• /
• 제13권1호
• /
• pp.71-77
• /
• 2010

대부분의 선진국에서 교량의 유지보수 및 보강(Maintenance Repair & Rehabilitation-MR&R)으로 인한 비용은 해마다 증가하고 있다. 전산화된 교량유지관리 및 의사결정시스템(Bridge Management System-BMS)은 가능한 최저의 생애주기비용(Life Cycle Cost - LCC)에 최적의 안정성를 확보하기 위해 개발되었다. 본 논문에서는 제한된 현존하는 교량진단기록을 이용하여 현존하지 않는 과거의 교량상태등급 데이타를 생성하기 위해 Backward Prediction Model(BPM)이라 불리는 인공신경망(Artificial Neural Network-ANN)에 기초한 예측모델을 제시한다. 제안된 BPM은 한정된 교량 정기점검기록으로부터 현존하는 교량진단기록과 연관성을 확립하기 위해 교통량과 인구, 그리고 기후 등과 같은 비구조적 요소를 이용하며, 제한된 교량진단기록과 비구조적 요소 사이에 맺어진 연관성을 통해 현존하지 않는 과거의 교량상태등급 데이타를 생성할 수 있다. BPM의 신뢰도를 측정하기 위하여 Maryland DOT로 부터 얻어진 National Bridge Inventory(NBI)와 BMS 교량진단자료를 이용하였다. 이중 NBI자료를 이용한 Backward comparison 에 있어서 실제 NBI기록과 BPM으로 생성된 교량상태등급과의 차이(상판: 6.68%, 상부구조부: 6.61%, 하부구조부: 7.52%)는 BPM으로 생성된 결과의 높은 신뢰도를 보여준다. 이 연구의 결과는 제한된 정기점검 기록으로 야기되는 BMS의 장기 교량손상 예측에 관련된 사용상의 문제를 최소화하고 전반적인 BMS 결과의 신뢰도를 높이는데 기여 할 수 있다.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2002년도 춘계학술대회논문집
• /
• pp.719-723
• /
• 2002

The purpose of this study is to suggest the correlation of single-number ratings for sound insulation by floor impact. As a assessment method of impact sound insulation. we selected the IIC contour of ISO, A weighted sound level. Inverse A-weighting curve and L-Index of japanese industrial standard. And we estimated the single-number ratings by application the measured data of impact sound level to each method. The results showed that the coefficients of determination between each two single-number ratings were very high (more than 0.9169). And In the condition of same assessment method, the coefficient of determination for light-weight impact sound was higher than that for heavy-weight impact sound.

• 대한인간공학회지
• /
• 제15권2호
• /
• pp.51-62
• /
• 1996

This research utilized the psychophysical methodology, where secrw drivers are used, to determine the effects of i) the location and orientation of work objects, and ii) wearing gloves, on ratings of perceived exertion at various body parts. The validity of the psychophysical methodology in determining a preferred work pace was also studied. The subjects drove screws with a screw driver into thick wooden sheet at three vertical and three horizontal locations. They drove serews for 3 minutes at each location and assessed the condition using the psychophysical scale. The results showed that only the vertical location was a significant factor in determining the discomfort ratings. Driving screws at elbow height on the vertical surface and with the lower arm close to the body on the horizontal surface were the work locations with the smallest ratings of perceived discomfort. Wearing gloves had significant effects on reducing the pain of the hand. From the experiment in which a comfortable work pace was identified using 20 minute psychophysical adjustment, it was found that the psychophysical method is sensitive to workers perception of the physical stress when the upper limbs are employed. This was confirmend by the high correlation between the psychophysical results and EMG measurement.

• 한국BIM학회 논문집
• /
• 제6권2호
• /
• pp.29-38
• /
• 2016

Road bridges are deteriorating gradually, and it is forecasted that the number of road bridges aging over 30 years will increase by more than 3 times of the current number. To maintain road bridges in a safe condition, current safety conditions of the bridges must be estimated for repair or reinforcement. However, budget and professional manpower required to perform in-depth inspections of road bridges are limited. This study proposes an estimation model for safety rating of road bridges by analyzing the data from Facility Management System (FMS) and Yearbook of Road Bridges and Tunnel. These data include basic specifications, year of completion, traffic, safety rating, and others. The distribution of safety rating was imbalanced, indicating 91% of road bridges have safety ratings of A or B. To improve classification performance, five safety ratings were integrated into two classes of G (good, A and B) and P (poor ratings under C). This rearrangement was set because facilities with ratings under C are required to be repaired or reinforced to recover their original functionality. 70% of the original data were used as training data, while the other 30% were used for validation. Data of class P in the training data were oversampled by 3 times, and Repeated Incremental Pruning to Produce Error Reduction (RIPPER) algorithm was used to develop the estimation model. The results of estimation model showed overall accuracy of 84.8%, true positive rate of 67.3%, and 29 classification rule. Year of completion was identified as the most critical factor on affecting lower safety ratings of bridges.

• 인지과학
• /
• 제20권3호
• /
• pp.335-355
• /
• 2009

위험정보를 확률이나 빈도양식으로 제시하고 질병으로 사망할 확률(기저율)에 대한 위험을 판단하게 하고 양성판정을 받은 사람이 질병에 걸렸을 확률(사후확률)에 대한 위험판단과 추론의 정확성을 비교하였다. 베이스 추론 과제를 사용한 연구 1에서 숫자양식의 효과가 관찰되었다. 참가자들은 위험이 확률보다는 빈도로 제시될 때 더 위험하다고 판단하였고 질병에 걸렸을 확률을 더 정확하게 추론하였다. 빈도의 범위가 좁을 때보다 넓을 때 더 위험하다고 판단하는 효과는 관찰되지 않았다. 분석적 사고체계가 위험판단에 미치는 영향을 검토하려고 사후확률을 계산하는 조건과 계산하지 않는 조건을 비교하였다. 숫자양식의 효과는 여전히 관찰되었다. 연구 2는 기저율과 사후확률의 크기에 따라 숫자양식 효과와 빈도범위 효과가 달라지는지 알아보았다. 숫자양식의 효과는 기저율과 사후확률의 크기에 상관없이 모든 조건에서 관찰되었다. 위험한 사건이 발생할 확률의 높고 낮음에 상관없이 빈도로 제시되었을 때 참가자들이 더 위험하다고 판단하였다. 그러나 빈도범위 효과는 기저율이 낮은 조건에서만 발견되었다. 본 연구의 결과들을 이중처리체계 이론과 관련시켜 논의하였다.

• 터널과지하공간
• /
• 제15권1호
• /
• pp.39-46
• /
• 2005

터널 단층대에서 수평시추로 조사한 막장전방의 암반 상태를 공학적 암반분류법인 RMR값으로 평가하였고 이를 터널 굴착 후 막장을 관찰하여 결정한 RMR값과 비교 분석하였다. 수평시추로 예측한 RMR값은 비교적 정확하여 터널 굴진 후 막장을 관찰하여 구한 RMR값과 큰 차이가 없었다. 그러나 일부 구간에서는 수평시추와 막장관찰로 구한 RMR값의 차이가 약 50까지 발생하였고 이를 RMR 평가항목으로 분석한 결과 불연속면의 상태에 대한 평점에서 24의 차이가 나타났고 암질지수와 단축압축강도 평점에서 각각 15와 13의 차이로 나타났다. 두 방법에서 평가한 RMR값의 차이를 줄이기 위해서는 터널 내 수평시추공의 위치를 터널의 안정성에 가장 큰 영향을 줄 수 있는 곳으로 선정하고 불연속면의 상태에 대한 평가는 불연속면의 연속성, 분리 틈, 풍화도 등 5개의 소항목 각각에 대해 5단계로 구분한 세부평점을 적용하여야 할 것이다.

• Journal of the Korean Data and Information Science Society
• /
• 제18권3호
• /
• pp.659-668
• /
• 2007

Collaborative filtering approach for recommender systems are now widely applied in e-commerce to assist customers to find their needs from many that are frequently available. this approach makes recommendations for users based on the opinions to similar users in the system. But this approach is opened to users who present their preference to items or acquire the preference information form other users, noise in the system makes significant problem for accurate recommendation. In this paper, we analyze the relationship between the standard deviation of preference ratings for each user and the estimated ratings of them. The result shows that the possibility of the pre-filtering condition which detecting the factor of bad effect on the prediction of user's preference. It is expected that using this result will reduce the possibility of bad effect on recommender systems.