We are excited to share that the Stand4Heritage team (Workpackage 1 and 4) successfully attended the 9th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS CONGRESS 2024). This event held recently, brought together leading researchers and practitioners to discuss the latest advancements in computational methods.

At this year’s congress, our team presented four conference papers:

Nonparametric Ground Motion Model for Scenario-Based Stochastic Simulation

• Collaborator: Sanaz Rezaeian, USGS (USA)
• Summary: This paper introduced a nonparametric ground motion model for scenario-based stochastic simulation. The model aims to enhance the accuracy and reliability of ground motion predictions, providing valuable insights for earthquake engineering and hazard assessment.

Development of Ground Motion Models for Peak Ground Acceleration (PGA) and Acceleration Spectrum Intensity (ASI) Using CatBoost Algorithm and Covariance Matrix Adaptation Evolution Strategy

• Collaborators: Fahrettin Kuran and Gulum Tanircan from Bogazici University (Turkiye)
• Summary: This research focused on developing advanced ground motion models for predicting Peak Ground Acceleration (PGA) and Acceleration Spectrum Intensity (ASI). By leveraging the CatBoost algorithm and Covariance Matrix Adaptation Evolution Strategy, the study aims to improve the predictive capabilities and robustness of GMMs.

Optimal Composed Intensity Measure for the Seismic Assessment of Masonry Buildings Using Lasso Regression

• Summary: This work derives an optimal composed intensity measure for seismic assessment of masonry buildings using lasso regression. By analyzing 100 earthquake motions and evaluating various intensity measures, the study identifies the most effective ones. The proposed composed intensity measure significantly improves the prediction of maximum roof displacement and provides reliable fragility curves, demonstrating comparable or better performance than individual intensity measures.

On the Optimal Survey of Masonry Texture for the Seismic Assessment of Historic Masonry Structures

• Collaborators: Dr. Marco Francesco Funari from University of Surrey
• Summary: This research investigates the influence of the masonry unit arrangement on the structural behavior of stone masonry structures. A stochastic 2D coursed-rectangular masonry pattern generator is developed to account for uncertainties in the unit dimensions and arrangement quality, followed by structural simulations using a micro limit analysis algorithm.

Stay tuned for more updates and insights from the Stand4Heritage team!