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

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.

Authors

Publication Details

Journal
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
Published
2026-09-28
DOI
https://doi.org/10.5194/isprs-annals-xii-4-w2-2026-49-2026
Primary Topic
Wind and Air Flow Studies
Type
article
Field-Weighted Citation Impact
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article

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

Dessislava Petrova‐Antonova, Anders Logg, Mariya Pantusheva, Orfeas Eleftheriou et al.
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
Wind and Air Flow Studies
article

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

Dessislava Petrova‐Antonova, Anders Logg, Mariya Pantusheva, Orfeas Eleftheriou, Vasilis Naserentin
article en

Abstract

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.

ISPRS annals of the photogrammetry, remote sensing and spatial information sciencesVol. XII-4/W2-2026(0)
Climate action
Openalex Percentile: Top 19%
Wind and Air Flow Studies
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A Workflow for Interactive Visualization of Urban CFD Data in Unreal Engine and via Web Streaming — Dessislava Petrova‐Antonova, Anders Logg, et al. · ISPRS annals of the photogrammetry, remote sensing and spatial information sciences (2026) | TGRS Research Map | TGRS