논문 상세보기
pp.25-34
This paper presents a finite-difference method (FDM)-based heat-transfer model for predicting black-ice formation on asphalt pavements and establishes decision criteria using only meteorological data. Black ice is a major cause of winter road accidents and forms under specific surface temperature and moisture conditions; however, its accurate prediction remains challenging owing to dynamic environmental interactions. The FDM incorporates thermodynamic properties, initial pavement-temperature profiles, and surface heat-transfer mechanisms, i.e., radiation, convection, and conduction. Sensitivity analysis shows the necessity of a 28-d stabilization period for reliable winter predictions. Black-ice prediction logic evaluates the surface conditions, relative humidity, wind speed, and latent-heat accumulation to assess phase changes. Field data from Nonsancheon Bridge were used for validation, where a maximum prediction accuracy of 64% is indicated in specific cases despite the overestimation of surface temperatures compared with sensor measurements. These findings highlight the challenges posed by wet surface conditions and prolonged latent-heat retention, which extend the predicted freezing duration. This study provides a theoretically grounded methodology for predicting black ice on various road structures without necessitating additional measurements. Future studies shall focus on enhancing the model by integrating vehicle-induced heat effects, solar radiation, and improved weather-prediction data while comparing the FDM with machine-learning approaches for performance optimization. The results of this study offer a foundation for developing efficient road-safety measures during winter.
1. 서론
2. 온도 예측 및 결빙 예측을 위한 자료 활용
2.1. 현장 계측 자료
2.1. 기상청 계측 자료
3. 포장 온도 및 결빙 예측 모형
3.1. 열전달 FDM 모형 및 강제대류 모형
3.2. 초기 온도 프로파일의 영향 평가
3.3. 재료 열물성의 영향 평가
3.4. 결빙 판단 기준 선정
4. 온도 및 결빙 예측 결과
5. 결론 및 향후 연구 내용
5.1. 요약 및 결론
5.2. 향후 연구 내용
감사의 글
REFERENCES
