Operation of environmentally responsive building components requires rapid prediction of the optimal adaptation of geometric shapes and positions, and such responsive configuration needs to be identified during the design process as early as possible. However, building simulation practices to characterize optimized shapes of various geometric design candidates are limited by complex simulation procedures, slow optimization, and lack of site information. This study suggests a practical approach to the design of responsive building façades by integrating on-site sensors, building performance simulation (BPS), machine-learning, and 3D geometry modeling on a unified design interface. To this end, a novel and efficient hybrid optimization algorithm, tabu-based adaptive pattern search simulated annealing (T-APSSA), was developed and integrated with wireless sensor data communication (using nRF24L01 and ESP8266 WiFi modules) on a parametric visual programming language (VPL) interface Rhino Grasshopper (0.9.0076, McNeel, Seattle, USA). The effectiveness of T-APSSA for early-stage BPS and optimal design is compared with other metaheuristic algorithms, and the proposed framework is validated by experimental optimal envelope (window shading) designs for single (daylight) and multiple (daylight and energy) objectives. Test results demonstrate the improved efficiency of T-APSSA in calculations (two to four times faster than other algorithms). This T-APSSA-integrated sensor-enabled design optimization practice supports rapid BPS and digital prototyping of responsive building façade design.

The purpose of this study is to make a complex insulation material with carbonized rice hull and glass wool and to verify the environmental control performance. Full-scale experimental mock-ups were constructed, and the control performance in an indoor environment was compared and verified through monitoring experiments. The complex insulation mock-up showed a relatively high temperature during spring, summer and autumn. The difference in the heat storage capacity of the materials was the cause for this difference. Also, the complex insulation material was proven as more effective at maintaining the stability of the indoor environment and temperature during spring, summer and autumn. In addition, the complex insulation was able to control the indoor humidity at a comfortable level during every season. Our results have therefore verified that the carbonized rice hull was effective at controlling the indoor humidity. When compared with the pure carbonized rice hull insulation, the complex insulation wall was relatively thin; therefore, more net indoor area could be achieved by using the complex insulation material. In addition, if self-produced, the complex insulation could be economically more feasible. Therefore, this complex material was synthetically proven to have merits for insulation of lightweight timber houses for thermal comfort of occupants.

This study investigates the performance of the “green refurbishment” of existing buildings. Two ordinary rooms in an existing building were chosen for examination. Refurbishment measures such as additional insulation, high-performance glazing, and air-tightening were applied to the control room. Temperature and electricity use were monitored to identify heating performance in winter and then compared with a baseline. The results of the field tests showed that green refurbishment significantly improved heating performance. Lowered heating load and electricity use with increased airtightness were also verified through building performance simulations. The empirical investigation suggests a predictive model to obtain indoor minimum temperatures as a function of outdoor temperature swings.