Full Domain Analysis for Fluid Mechanics

The aim of the project is to apply AI-driven novel optimization algorithms and machine learning methods at different stages of decision-making processes in climate-adaptive urban design to model the late consequences of decisions. The algorithms are used to represent the variety of design and decision options in-silico and by example. Decisions are incorporated into the modeling - thus creating a toolset that accompanies the process. An open, free system is developed for the communication and decision-making processes of sustainable urban development where all stakeholders are involved and understand early in the construction project what impact requirements and constraints have on possible designs and can thus make more informed decisions. The system can be set up and extended with many climate adaptive factors.