RADAR: A Framework for Risk Assessment and Degradation Analysis for Cultural Heritage Buildings Through CFD Modeling
Artikel i vetenskaplig tidskrift, 2026

Cultural heritage buildings constitute an irreplaceable record of historical, social, and architectural identity, and their preservation is essential for cultural continuity and sustainable development. However, their conservation is inherently challenging due to material aging, complex construction techniques, limited documentation, and strict intervention constraints that restrict invasive monitoring or retrofitting solutions. Environmental degradation and microclimatic effects further accelerate deterioration, often in ways that are difficult to quantify or predict. This paper presents RADAR, a non-invasive, data-driven framework for assessing environmental and structural risk in cultural heritage buildings. The proposed approach integrates high-resolution geometric acquisition, computational fluid dynamics (CFD) modeling, and environmental monitoring to analyze airflow patterns, temperature distribution, and moisture-related decay mechanisms. By combining measured data with numerical simulations, RADAR enables the identification of high-risk zones and deterioration drivers without altering the building fabric. The framework is demonstrated through a real-world case study, illustrating its applicability as a decision-support tool for preventive conservation and heritage management.

3D visualization

digital twins

computational fluid dynamics (CFD)

environmental degradation

risk assessment

cultural heritage preservation

Författare

Asimina Dimara

Panepistimion Aegaeou

Mariya Pantusheva

Big Data for Smart Society Institute (GATE)

Nikolaos Alexios Stefanis

University of West Attica

Orfeas Eleftheriou

Göteborgs universitet

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Radostin Mitkov

Big Data for Smart Society Institute (GATE)

Vasilis Alexandros Naserentin

Aristotelio Panepistimio Thessalonikis

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Göteborgs universitet

Dessislava Petrova-Antonova

Big Data for Smart Society Institute (GATE)

Anders Logg

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Göteborgs universitet

Christos Nikolaos Anagnostopoulos

Panepistimion Aegaeou

Heritage

25719408 (eISSN)

Vol. 9 3 112

Ämneskategorier (SSIF 2025)

Husbyggnad

DOI

10.3390/heritage9030112

Mer information

Senast uppdaterat

2026-05-18