Building structures are considered as major contributors to global energy consumption (30-40%) and they are responsible for the 40-50% of greenhouse gas emissions.Due to huge energy consumption and material use, tall buildings have drawn particular attention with reference to their environmental impact. The influence of structural systems on the environmental performance of tall buildings is studied in this work, calculating the embodied energy and CO2 emissions of construction materials. In this direction, characteristic structural systems of tall buildings are considered in order to compare their environmental behavior and to account for their differences on the amount of construction materials used for their formation. In order to achieve this comparison, the structural systems are material-cost optimized using the optimization computing platform (OCP), developed by the authors for solving real-world structural design optimization problems. The results of this research provide valuable findings for the significant role of structural optimization in sustainable design of tall buildings as well as in limiting the production of construction materials.
Despite the promising benefits of data-driven applications to improve building performance, they are still developed on an ad-hoc basis, mainly due to the burden of discovering and reusing building data across deployment sites. Recent efforts in semantic data modelling aim to overcome these barriers, though application development remains building-specific, leading to bespoke configurations that cannot scale. This research seeks to establish a new regime of data-driven applications that are developed once and run across multiple buildings -similarly to the applications we download and use in our mobile phones. This research contributes to realising this vision in two ways: introducing (a) a method for automatic building metadata model generation through the lifecycle, and (b) a portable application development paradigm that offsets the burden of configuration in the authoring process. An overview of this vision and contributions are illustrated in Figure 1. These advancements are expected to overcome expertise barriers, reduce time for applications' configuration and deployment, and thus, accelerate their adoption at scale.
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