ValUr: A High-Fidelity Dataset for Validation of Urban Pollution Dispersion Models – Project Overview and Geometry Preparation
Paper i proceeding, 2025

Computational fluid dynamics (CFD) models, used independently or integrated into city digital twins, can predict air pollution dispersion and support informed decision-making in urban planning. While modelling complexity and capabilities have increased, systematic validation and uncertainty quantification remain crucial, yet are among the least understood and applied aspects of the analysis process. To address this issue, the ValUr project, supported by the ERIES programme, aims to establish a best-practice protocol for urban CFD validation and to generate a high-quality, open-access pollution dispersion dataset. This work introduces the project scope, motivation, and goals, detailing early project activities, including the identification of the study area - part of the city centre of Sofia, Bulgaria, where air quality is a pressing concern, and the creation of a scaled geometry suitable for physical model-making, wind tunnel testing, and CFD simulations. The geometry goes beyond the basic level of detail (LoD) 1, typically used in validation databases and reaches LoD 2.2, capturing the complex building morphologies and realistic urban conditions of the area. By sharing protocols and data openly, ValUr seeks to promote the importance of model reliability and to encourage validation consistency within the computational wind engineering community.

Wind tunnel testing

Urban pollution dispersion modelling

Model validation

Geometry preparation

Författare

Mariya Pantusheva

Sofijski universitet

Radostin Mitkov

Sofijski universitet

Petar O. Hristov

Sofijski universitet

Evgeny Shirinyan

Sofijski universitet

Vasilis Alexandros Naserentin

Göteborgs universitet

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

A. K.R. Jayakumari

Technische Universiteit Eindhoven

Stefanie Gillmeier

Technische Universiteit Eindhoven

Anders Logg

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Göteborgs universitet

Lecture Notes in Civil Engineering

23662557 (ISSN) 23662565 (eISSN)

Vol. 718 LNCE 83-94
9783031988929 (ISBN)

International Workshop in Engineering Research Infrastructures for European Synergies, ERIES-IW 2025
Lisbon, Portugal,

Big data for smart society (GATE)

Europeiska kommissionen (EU) (EC/H2020/857155), 2019-09-01 -- 2026-08-31.

Ämneskategorier (SSIF 2025)

Datavetenskap (datalogi)

DOI

10.1007/978-3-031-98893-6_9

Mer information

Senast uppdaterat

2025-09-03