Analysis of physical uncertainties in computer simulations of residential buildings

Abstract The aim of this paper is to analyse physical uncertainties in a computer simulation of a residential building and the implications for its thermal performance. The simulation experiment was performed using the Monte Carlo method, involving the thermal and physical properties of materials. The sensitivity of the variables was also analysed using regression and correlation coefficients. The degree-hours of discomfort criterion for heating and cooling for the climate of Florianópolis-SC were considered, according to adaptive thermal comfort limits. The results showed that uncertainties in degree-hours are high, i.e., 32% for cooling discomfort and 53% for heating discomfort. The uncertainty is largely due to the average monthly temperature of the ground. Other variables, such as the solar absorptance of the roof and the specific heat of the mortar of the walls had a relevant impact on heat discomfort. The density of the mortar and the specific heat of the brickwork walls affected the cooling discomfort. These variables need proper accuracy, either through more reliable databases and/or through field or laboratory measurements.

摘要 本文旨在分析住宅建筑计算机模拟中的物理不确定性及其对建筑热性能的影响。本次模拟实验采用蒙特卡洛（Monte Carlo）方法开展，涉及材料的热物理属性。研究同时通过回归分析与相关系数法，对各变量的敏感性展开了探究。研究结合适应性热舒适限值，采用弗洛里亚诺波利斯-SC（Florianópolis-SC）地区气候下的采暖与制冷不舒适度小时数作为评价标准。结果显示，不舒适度小时数的不确定性较高：制冷不舒适场景的不确定性达32%，采暖不舒适场景则为53%。该不确定性主要源于地面月平均温度。其余变量，如屋顶太阳吸收率与墙体砂浆的比热容，对采暖不舒适度存在显著影响；墙体砂浆密度与砖砌墙体的比热容，则对制冷不舒适度产生相关作用。上述变量需通过更可靠的数据库，或结合实地与实验室测量手段，以保障其精度要求。