초록
본 연구에서는 확률적 LCC 및 확률적 성능평가를 고려한 설계 VA분석 방법을 제안하였으며, 신뢰성 해석의 개념을 도입하여 신뢰도를 확보한 의사결정을 지원하고자 하였다. 상기와 같은 목적과 방법에 따라 진행된 본 연구의 결과를 요약하면 다음과 같다: 1) 기능정의가 완료된 이후 도출된 대안들의 대안평가시 신뢰성 있는 분석을 위하여 개선된 설계VA 절차 와 가치상태함수를 정식화하였으며, 가치평가절차에서의 일관성 및 효율성을 확보하기 위하여 평가지표방안을 제시하였다. 2) 교량의 LCC분석을 위한 DB를 수집 및 분석하였다. 자료의 수집범위는 기존에 수행된 교량의 LCC분석 연구 문헌을 기초로 하여 분석하였으며, 분석결과에 대한 신뢰도 확보 및 수집된 자료의 불확실성 처리를 위해 MCS 기법을 적용하였다. 3) 대안별 성능평가를 위한 가중치 및 평가등급과 LCC 분석을 위한 LCC 분석모델, 분석기간, 할인율, 사용자비용, 안전점검 및 안전진단비용에 대한 조건을 제시하였다. 끝으로, 사례대상인 "OO대교 및 연결도로 건설공사 실시설계" 프로젝트에 대한 VA수행 사례를 중심으로 타당성을 검토하고 결론을 도출하였다.
In this study, a design value analysis technique that considered stochastic LCC and stochastic performance evaluation was proposed, and by introducing the concept of reliability analysis, a decision making that secured reliability was supported. The results of this study, which was carried out according to the above objectives and methods, are summarized as follows: 1) The design value analysis procedures and value state function, improved in order to carry out a reliable analysis when evaluating alternate proposals that were extracted after the function definition was complete, were formalized, and in order to secure consistency and efficiency for value evaluation procedures, an evaluation index scheme was proposed; 2) Database collection and analysis were done for a bridge's LCC analysis. As for the collection scope of data, literature of previous research done on a bridge's LCC analysis was used as the basis for analysis, and for securing reliability regarding analysis results and dealing with uncertainty of collected data, the MCS technique was applied; 3) Weights and evaluation ranks for performance evaluation of each of the alternate proposals, as well as LCC analysis model, analysis period, discount rate, user expense, safety inspection and safety diagnosis expense conditions for LCC analysis were proposed. Lastly, a feasibility study was done and conclusion was made about "OO grand bridge and connecting road construction work execution design" project centered on value analysis execution case.