Sustainability-Related Parameters and Decision Support Tools for Kinetic Green Façades

Constant challenges, environmental threats, and rapid changes of living conditions on the earth make it necessary to seriously take up the topic of resilience and sustainability. The interdisciplinary and holistic approach is more important than ever before, and engineering science is required to adapt to global conditions. This article presents the results of research aimed at the identification of sustainability-related parameters for kinetic green façades in the preliminary design phase and evaluation of current decision support tools. The authors carried out the comparative analysis of existing decision support methods and tools for sustainable development, used in fields and disciplines such as architectural design, environmental engineering, and structural design. The particular focus of the research was on the preliminary concept design of kinetic green façades. Specific methods such as forecasting and backcasting linked to post-occupancy evaluation tools were also taken into account. Parametric modeling based on optimization algorithms was recognized as the most adequate method. As a result of the conducted research, the steps to be taken at the early design stage for sustainable façade design were identified based on the example of the innovative system of kinetic green façade. The first step is to determine the design criteria of the façade considering the factors related to climate, culture, environment, and special design requirements. In the next step, the design parameters of the façade system are defined depending on the aforementioned criteria. In the third step, system design and modeling are done. Finally, the performance of the façade system is evaluated. If the desired performance is not achieved, the designer returns to the 2nd and 3rd steps. These last three steps of the preliminary design stage of sustainable façade systems are critical since they allow us for the façade design optimization, which in turn has a significant influence on the whole building performance and sustainability parameters.