A methodology for a scalable building performance simulation based on modular components

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This thesis presents a methodology incorporating the concept of modularity to realize a scalable building performance simulation. It builds upon the Functional Mock-up Interface for tool-independent co-simulation of Functional Mock-up Units (FMUs). Semantic Web Technologies are deployed to describe FMUs with machine-readable, semantic information. In addition to a generalized description pattern, the association to project-specific data via Building Information Modeling ensures the required context for semantic interpretation of FMUs. The resulting ontology is the basis for a reasoning process aimed at detecting connections between the simulation modules. By combining ontology, per definition a knowledge representation, with queries inferring new triples when executed, the approach is a knowledge-based approach. The methodology allows for automated derivation of a simulation network across several Levels of Detail. As such, a single-zone, a multi-zone and a zonal airflow representation of a building are integrated. With the former models being able to compute performance regarding energy usage, the latter provides a detailed assessment of the resulting indoor climate.