PURPOSES : Previously, airport concrete pavement was designed using only aircraft gear loading without consideration of environmental loading. In this study, a multiple-regression model was developed to predict maximum tensile stress of airport concrete pavement based on finite element analysis using both environmental and B777 aircraft gear loadings. METHODS: A finite element model of airport concrete pavement and B777 aircraft main gears were fabricated to perform finite element analysis. The geometric shape of the pavement, material properties of the layers, and the loading conditions were used as input parameters for the finite element model. The sensitivity of maximum tensile stress of a concrete slab according to the variation in each input parameter was investigated by setting the ranges of the input parameters and performing finite element analysis. Based on the sensitivity analysis results, influential factors affecting the maximum tensile stress were found to be used as independent variables of the multi regression model. The maximum tensile stresses predicted by both the multiple regression model and finite element model were compared to verify the validity of the model developed in this study. RESULTS: As a result of the finite element analysis, it was determined that the maximum tensile stress developed at the bottom of the slab edge where gear loading was applied in the case that environmental loading was small. In contrast, the maximum tensile stress developed at the top of the slab center situated between the main gears in the case that the environmental loading got larger. As a result of the sensitivity analysis and multiple regression analysis, a maximum tensile stress prediction model was developed. The independent variables used included the joint spacing, slab thickness, the equivalent linear temperature difference between the top and bottom of the slab, the maximum take-off weight of a B777 aircraft, and the composite modulus of the subgrade reaction. The model was validated by comparing the predicted maximum tensile stress to the result of the finite element analysis. CONCLUSIONS : The research shown in this paper can be utilized as a precedent study for airport concrete pavement design using environmental and aircraft gear loadings simultaneously.

본 연구는 사과 ‘후지’의 과실 횡경 예측 모델을 개발 하고 검증하고자, 수원지역에서 2000년부터 2014년까지의 연차간 과실 생장과 기상을 포함한 환경요인들을 분석하였다. 2000년부터 2014년까지의 평균 만개일은 4월 28일이었고, 만개 후 수확일까지의 성숙일수는 평균 181 일이었다. 만개 후 약 36일 이후부터의 과실 생장은 단일 S자 곡선이었으며, 과실 횡경에 영향을 미치는 환경 요인들은 BIO2, 9월강수량, 4월 최고·최저·평균기온, 8월 최저기온, 그리고 4월의 생육도일이었다. 그 중에서, 서로 간의 요인이 교차 상관관계를 나태내지 않는 BIO2와 9월 강수량을 각각 다른 요인들과 조합하여 모델을 만들었다. 선발된 모델 중에서 AICc가 92.61이며 보정된 R2 값이 0.53으로 가장 적합도가 높았던 모델을 선택하였으 며 그 최종 모델식은 19.33095+(5.76242×BIO2)-(0.01891×9월강수량)+(2.63046×4월최저온도)이었다. 이 모델을 2000 년부터 2014년까지의 실측치와 비교하였는데, 사과 ‘후지’과실 횡경의 실측치와 예측치의 평균차이는 ±2.9mm, 표준편차는 3.54였다.

Recently, the characteristic of plant production systems in Korea has been changed with the strong trends of integration and large scale, using environmental control techniques. To satisfy this change successfully, first of all, the environmental prediction inside the system must be preceded. While many environmental prediction models for plant production system were developed by many persons, each model cannot be applied to the every situation without the perfect understanding of source codes and the technical modification. The purpose of this study is building the environmental prediction model to predict and evaluate the environment inside the system numerically, and also developing the multipurpose program available for practical design. The model consisted of the basic system model, the cultivation related model and the environmental control related model. The contents of each model are as follows : the basic system model is dealing with thermal and light environments, soil environment and ventilation : the cultivation related model with soil and hydroponic cultures ; and the environmental control related model with thermal curtain and heat exchanging system. The environmental prediction model was developed using a common simulation program, PCSMP, so that it could be easily understood and modified by anyone. Finally, the model was executed and verified through comparison between simulated and measured results for soil culture, and both results showed good agreements.