About City Digital Twin Project
City Digital Twin Pilot Project aims to implement the digital twin as a technical solution that scales to real-world problems, including design, exploration and experimentation of urban environment and processes.
City Digital Twin Pilot Project aims to implement the digital twin as a technical solution that scales to real-world problems, including design, exploration and experimentation of urban environment and processes.
The 3D city model of District Lozenets and its visualisation are the first steps towards implementation of City Digital Twin pilot project of GATE Institute. It covers the Buildings and Relief thematic modules of CityGML 2.0. The 3D model of the buildings is hosted on the Cesium ion platform and visualized using CesiumJS.
The parametric urban planning naturally follows the basic idea of the digital twin – "design, test and build first digitally". A tool that provides data-driven decision support on urban planning is developed based on preliminary defined neighbourhood indicators related to population density, access to social infrastructure, transport connectivity, etc.
Computational Fluid Dynamics (CFD) simulations are now being widely used for the prediction and assessment of high-rise building aerodynamics and pedestrian wind comfort. Results from CFD wind simulation are reliable sources of quantitative and qualitative data useful to make important design decisions.
Indoor air quality and thermal comfort are two factors that affect occupant’s health, performance, and overall well-being. They are modelled, analyzed and predicted by applying CFD, so that suitable control measures can be taken in due time. The overall building design, ventilation and heating effectiveness is assessed and optimized through different what-if scenarios.
An automated approach for assessment of social facility coverage is developed. It solves a supply and demand problem based on a graph network, where kindergartens and nurseries are considered as supply nodes, and residential buildings as demand nodes. Supply and demand are balanced based on a 15-min walking distance and the capacity of social facilities.
The aim is to provide a way of combining data from different sensor stations and to develop a platform for the real-time prediction of air quality throughout Sofia city. To achieve this, methods from the field of uncertainty quantification and statistical learning are used, which enable the analysis of existing sensor data in a probabilistic way.
Walking is the most accessible form of mobility, delivering benefits to both cities and their residents. To increase walkability, the pedestrian network, integrating all transportation modes, should be optimized. The pedestrian accessibility to public transport stops and parks in Sofia is evaluated by applying network and spatial analysis based on a 10-min walking distance.
The study aims to numerically estimate the impact of UHI in Sofia and its surroundings on the air temperature using the state-of-the-art Weather Research and Forecasting (WRF) with very high resolution. The study also estimates the impact of building and transport separately..
The 3D city model of District Lozenets and its visualisation are the first steps towards implementation of City Digital Twin pilot project of GATE Institute. It covers the Buildings and Relief thematic modules of CityGML 2.0. The 3D model of the buildings is hosted on the Cesium ion platform and visualized using CesiumJS
The parametric urban planning naturally follows the basic idea of the digital twin – "design, test and build first digitally". A tool that provides data-driven decision support on urban planning is developed based on preliminary defined neighbourhood indicators related to population density, access to social infrastructure, transport connectivity, etc.
An automated approach for assessment of social facility coverage is developed. It solves a supply and demand problem based on a graph network, where kindergartens and nurseries are considered as supply nodes, and residential buildings as demand nodes. Supply and demand are balanced based on a 15-min walking distance and the capacity of social facilities.
Computational Fluid Dynamics (CFD) simulations are now being widely used for the prediction and assessment of high-rise building aerodynamics and pedestrian wind comfort. Results from CFD wind simulation are reliable sources of quantitative and qualitative data useful to make important design decisions.
The aim is to provide a way of combining data from different sensor stations and to develop a platform for the real-time prediction of air quality throughout Sofia city. To achieve this, methods from the field of uncertainty quantification and statistical learning are used, which enable the analysis of existing sensor data in a probabilistic way.
Indoor air quality and thermal comfort are two factors that affect occupant’s health, performance, and overall well-being. They are modelled, analyzed and predicted by applying CFD, so that suitable control measures can be taken in due time. The overall building design, ventilation and heating effectiveness is assessed and optimized through different what-if scenarios.
The study aims to numerically estimate the impact of UHI in Sofia and its surroundings on the air temperature using the state-of-the-art Weather Research and Forecasting (WRF) with very high resolution. The study also estimates the impact of building and transport separately..
Walking is the most accessible form of mobility, delivering benefits to both cities and their residents. To increase walkability, the pedestrian network, integrating all transportation modes, should be optimized. The pedestrian accessibility to public transport stops and parks in Sofia is evaluated by applying network and spatial analysis based on a 10-min walking distance.
Integratation of big geospatial data, spatial analysis, and AI methods to understand natural and social phenomena in urban environment.
Applying Computational Fluid Dynamics in indoor and outdoor simulation of air pollution, wind flow and noise simulation.
Visualisation of 3D city models and viasual representation of analytical and CFD results.
Integration of data from a variety of sources, feature extraction and semanticaly enrichment.
Sofia, Bulgaria
5 James Bourchier Blvd., Sofia 1164, Bulgaria
dessislava.petrova@gate-ai.eu