A Workflow for Interactive Visualization of Urban CFD Data in Unreal Engine and via Web Streaming
Paper in proceeding, 2026

To analyze current and predict future conditions, smart-city planning relies on physics-based simulations to support sustainable design, climate adaptation, and citizen engagement. Yet, the analysis results often remain locked inside specialist tools and static plots that are difficult for non-experts to access and interpret. As part of a broader framework developed for scientific results visualization in an urban context, this paper presents a semi-automated workflow for transforming urban Computational Fluid Dynamics (CFD) outputs into interactive 3D visualizations using Unreal Engine and a web-based streaming application. The feasibility of the workflow is demonstrated through a wind-flow case study of an area in central Sofia, Bulgaria. The proposed approach covers the complete process, from problem formulation and data preparation through simulation execution, results processing, and integration into Unreal Engine. The visualization component is implemented through a modular actor-based architecture that supports both point-based and trajectory-based flow representations, which can be flexibly combined and interactively modified within the scene. Additionally, the visualization system is deployed through Pixel Streaming, providing a practical and viable way to transform complex CFD data into exploratory tools that are accessible to a wide range of urban stakeholders.

Interactive Visualization

Urban Digital Twins

Smart Cities

Urban CFD

Unreal Engine

Web Application

Author

Orfeas Eleftheriou

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Vasileios Naserentin

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Aristotle University of Thessaloniki

Mariya Pantusheva

Big Data for Smart Society Institute (GATE)

Dessislava Petrova-Antonova

Big Data for Smart Society Institute (GATE)

Anders Logg

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences

21949042 (ISSN) 21949050 (eISSN)

Vol. 12 4/W2-2026 49-56

10th International Conference on Smart Data and Smart Cities, SDSC 2026
Sofia, Bulgaria,

Subject Categories (SSIF 2025)

Computer Sciences

Architectural Engineering

DOI

10.5194/isprs-annals-XII-4-W2-2026-49-2026

More information

Latest update

10/19/2026