A.M. Koniari
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Global urbanisation and climate change mitigation efforts increasingly drive the need for precise urban energy planning and the testing of multiple future scenarios. While Urban Building Energy Modelling (UBEM) and semantic 3D city models, in particular based on the open standard CityGML, provide the foundational framework for these physics-based simulations, they are inherently designed to represent a single, static state of an urban environment. Consequently, existing standards struggle to manage concurrent "what-if" planning scenarios such as building refurbishments or PV device adoption, without duplication of the dataset. Furthermore, they lack the structured data provenance required to explicitly bind simulation results back to the specific input parameters, boundary conditions, and engine configurations that produced them.
This thesis addresses this data management gap by testing and iteratively enhancing the Scenario Application Domain Extension (ADE) for CityGML 2.0. Utilizing a Design Science Research methodology, the schema was refined from an initial Beta 3 to a current functional Beta 6 version. The structural requirements for this enhancement were empirically derived by conducting baseline and exploratory SimStadt energy simulations on case-study neighborhoods in Rotterdam. While urban energy served as the empirical proving ground, the schema was deliberately engineered to remain domain-agnostic. Based on these observations and theoretical research, scenario data was formally decomposed into three storable pillars: Context, Strategy, and Configuration.
To validate the refined schema, foundational operations and four comprehensive test scenarios—Future Climate, Refurbishment, PV Adoption, and Urban Greening—were encoded into both XML instances and a 3DCityDB relational database. The results demonstrate that the Beta 6 Scenario ADE successfully manages concurrent "what if" scenarios in one dataset. Ultimately, this work provides a domain-agnostic data management layer that supports the structured comparison and reproducibility of multi-temporal urban scenarios, demonstrated here within the context of the building energy performance simulations. ...
This thesis addresses this data management gap by testing and iteratively enhancing the Scenario Application Domain Extension (ADE) for CityGML 2.0. Utilizing a Design Science Research methodology, the schema was refined from an initial Beta 3 to a current functional Beta 6 version. The structural requirements for this enhancement were empirically derived by conducting baseline and exploratory SimStadt energy simulations on case-study neighborhoods in Rotterdam. While urban energy served as the empirical proving ground, the schema was deliberately engineered to remain domain-agnostic. Based on these observations and theoretical research, scenario data was formally decomposed into three storable pillars: Context, Strategy, and Configuration.
To validate the refined schema, foundational operations and four comprehensive test scenarios—Future Climate, Refurbishment, PV Adoption, and Urban Greening—were encoded into both XML instances and a 3DCityDB relational database. The results demonstrate that the Beta 6 Scenario ADE successfully manages concurrent "what if" scenarios in one dataset. Ultimately, this work provides a domain-agnostic data management layer that supports the structured comparison and reproducibility of multi-temporal urban scenarios, demonstrated here within the context of the building energy performance simulations. ...
Global urbanisation and climate change mitigation efforts increasingly drive the need for precise urban energy planning and the testing of multiple future scenarios. While Urban Building Energy Modelling (UBEM) and semantic 3D city models, in particular based on the open standard CityGML, provide the foundational framework for these physics-based simulations, they are inherently designed to represent a single, static state of an urban environment. Consequently, existing standards struggle to manage concurrent "what-if" planning scenarios such as building refurbishments or PV device adoption, without duplication of the dataset. Furthermore, they lack the structured data provenance required to explicitly bind simulation results back to the specific input parameters, boundary conditions, and engine configurations that produced them.
This thesis addresses this data management gap by testing and iteratively enhancing the Scenario Application Domain Extension (ADE) for CityGML 2.0. Utilizing a Design Science Research methodology, the schema was refined from an initial Beta 3 to a current functional Beta 6 version. The structural requirements for this enhancement were empirically derived by conducting baseline and exploratory SimStadt energy simulations on case-study neighborhoods in Rotterdam. While urban energy served as the empirical proving ground, the schema was deliberately engineered to remain domain-agnostic. Based on these observations and theoretical research, scenario data was formally decomposed into three storable pillars: Context, Strategy, and Configuration.
To validate the refined schema, foundational operations and four comprehensive test scenarios—Future Climate, Refurbishment, PV Adoption, and Urban Greening—were encoded into both XML instances and a 3DCityDB relational database. The results demonstrate that the Beta 6 Scenario ADE successfully manages concurrent "what if" scenarios in one dataset. Ultimately, this work provides a domain-agnostic data management layer that supports the structured comparison and reproducibility of multi-temporal urban scenarios, demonstrated here within the context of the building energy performance simulations.
This thesis addresses this data management gap by testing and iteratively enhancing the Scenario Application Domain Extension (ADE) for CityGML 2.0. Utilizing a Design Science Research methodology, the schema was refined from an initial Beta 3 to a current functional Beta 6 version. The structural requirements for this enhancement were empirically derived by conducting baseline and exploratory SimStadt energy simulations on case-study neighborhoods in Rotterdam. While urban energy served as the empirical proving ground, the schema was deliberately engineered to remain domain-agnostic. Based on these observations and theoretical research, scenario data was formally decomposed into three storable pillars: Context, Strategy, and Configuration.
To validate the refined schema, foundational operations and four comprehensive test scenarios—Future Climate, Refurbishment, PV Adoption, and Urban Greening—were encoded into both XML instances and a 3DCityDB relational database. The results demonstrate that the Beta 6 Scenario ADE successfully manages concurrent "what if" scenarios in one dataset. Ultimately, this work provides a domain-agnostic data management layer that supports the structured comparison and reproducibility of multi-temporal urban scenarios, demonstrated here within the context of the building energy performance simulations.