Buildings and Cities: Difference between revisions

*'''[[Sector-coupled districts and district heating systems]]''': To achieve decarbonization across the heating, electricity, and mobility sectors, they are increasingly coupled within districts in a joint spatial and organizational context. ML can help by providing surrogate models of thermal processes and quantify uncertainties of loads, supply, and mobility behavior.

*'''[[Surrogate modeling]]''': Building energy simulation (BES) programs are software tools that simulate the complex physics of buildings and are key enabling tools for R&D in the building's domain. However, detailed BES models are notoriously difficult to design, tune and typically have high computational demands. ML, in conjunction with physics, can help to build accurate yet computationally efficient surrogate models for faster simulations.

 

=== Urban planning ===