Investigating Condensation Risks on Heritage Building Surfaces Using Blinn-Phong BRDF Model and Attribute Information of Point Cloud Data

Abstract

To date, the preservation techniques of heritage buildings in Indonesia are still limited to physical measurement, most of which are based on manual records. Consequently, lack of accuracy, cost and time consumption often lead to misinterpretation of crucial information during the decision-making process. This part includes physical amage (i.e., mold growth, flaking paint, water leaks), caused by condensation due to high relative humidity. Thanks to the development of advanced laser scanning technology, high-precision point cloud datasets can be obtained to conduct surface performance analysis. Furthermore, this study proposes an integrated computational method for detecting condensation risks in heritage buildings by making use of optical and thermal properties calculated from point cloud data. The proposed method specifically employs Blinn-Phong Bidirectional Reflectance Function (BRDF) model to calculate the distributed reflectance in a material based on the angle of incidence and material reflectance. Along with it, the point cloud measurement is also coupled with FLIR One Pro IR camera and HOBO data logger to analyze the thermal performances of the building surface. Ultimately, this study will provide architects with a better understanding regarding potential risks of condensation in the heritage building surface so that they can perform early detection tasks.