논문 상세보기
pp.11-19
PURPOSES : Rut depth of asphalt pavements is a major factor that affects the maintenance of pavements as well as the safety of drivers. The purpose of this study was to analyze the factors influencing rut depth, using data collected periodically on national highways by the pavement management system and, consequently, predict annual rut depth change, to contribute to improved asphalt pavement management.
METHODS : The factors expected to influence rut depth were determined by reviewing relevant literature, and collecting the related data. Further, the correlations between the annual rut depth change and the influencing factors were analyzed. Subsequently, the annual rut depth change model was developed by performing regression analysis using age, present rut depth, and annual average maximum temperature as independent variables.
RESULTS : From the sensitivity analysis of the developed model, it was found that age affected the annual rut depth change the most. Additionally, the relationship between the dependent and independent variables was statistically significant. The model developed in this study could reasonably predict the change in the rut depth of the national highway asphalt pavements. CONCLUSIONS : In summary, it was verified that the model developed in this study could be used to predict the change in the National Highway Pavement Condition Index (NHPCI), which represents comprehensive conditions of national highway pavements. Development of other models that predict changes in surface distress as well as international roughness index is required to predict the change in NHPCI, as they are the independent variables of the NHPCI prediction model.
1. 서론
2. 자료수집 및 분석
2.1. 소성변형 깊이에 영향을 주는 인자 및 PMS를 통한포장상태 예측모형의 한계
2.2. 자료수집 방법
2.3. 대상구간 선정
2.4. 자료수집 결과
3. 연간 소성변형 깊이 변화량 예측모형 개발
3.1. 예측모형 개발 방법
3.2. 독립변수 형태에 따른 정규성 검토 및 정규화
3.3. 연간 소성변형 변화량과 각 인자 간의 상관성 분석
3.4. 그룹화 및 데이터 분할
3.5. 모형 개발 및 검증
3.6. 민감도 분석
4. 결론
REFERENCES
