Title: Damage detectability and effects of environmental and operational variability in structural health monitoring. 

Organisers: Dr. David Garcia Cava (University of Edinburgh), Dr. Luis David Avendano Valencia (University of Southern Denmark)

The effect of Environmental and Operational Variability (EOV) in structural dynamics comprises one of the main hurdles in the realization of practical Structural Health Monitoring (SHM) strategies. Consequently, in recent years there has been a growing interest on the SHM towards this issue. Despite the apparent maturity of this field, the matter of damage diagnosis under the influence of EOV remains considerably underexplored. Here, the application of machine learning and other data-driven techniques, integrating with the physical knowledge of the effects of EOV in the dynamic characteristics of a structure are essential. Should your research encompass methodologies pertinent to the mitigation of EOV and/or enhancement of damage detectability, we cordially invite your contributions to enrich this discourse. We extend an invitation for scholarly submissions, particularly those pertaining to machine learning techniques designed for the mitigation of EOV effects, methodologies for feature normalization, hybrid approaches amalgamating explicit and implicit compensation techniques, physics-informed models facilitating the interpretability of long-term performance, as well as investigations addressing the intricacies of damage detectability and comprehensive long-term performance assessment. Your valuable insights would be highly appreciated and would serve to further advance this ongoing dialogue.