Seismic Vulnerability Assessment of RC Buildings via Bayesian Updating: Evidence from the 2017 Puebla Earthquake

OverviewThis dataset contains the high-fidelity structural models, processed seismic records, and statistical frameworks supporting the research article: "Seismic Vulnerability Assessment of RC Buildings via Bayesian Updating: Evidence from the 2017 Puebla Earthquake". The repository enables the full reproduction of a forensic engineering assessment of mid-rise RC buildings with unreinforced masonry (URM) infills, characteristic of Mexico City’s transition zone.Methodology & Refinements (Version 2.0)The research integrates numerical and empirical evidence through a robust Bayesian framework, updated in this version to meet Q1-tier reproducibility standards:Numerical Evidence: Non-linear static (pushover) and stochastic reliability analyses performed in OpenSeesPy. The URM infill behavior is modeled via an equivalent strut approach using the Pinching4 constitutive law, with damage parameters (stiffness/strength degradation) strictly anchored to the mode-II fracture energy ($G_f^{II}$) of Mexican artisanal clay bricks.Stochastic Framework: Epistemic uncertainty in masonry strength ($f'_{me}$) is quantified using a Lognormal probability distribution to ensure physical consistency (positive-definite domain) and eliminate algorithmic bias in the Monte Carlo simulations.Empirical Evidence: Forensic field data from 62 buildings (19 observed collapses) following the 19/09/2017 event.Synthesis: A Beta-Binomial Bayesian Updating framework was implemented to refine the analytical prior collapse probability ($P_f = 46.9\%$) into a posterior estimate ($P_f = 32.9\%$), consistent with observed seismic pathologies.Dataset Structure/scripts: Includes optimized Jupyter Notebooks (.ipynb) for the OpenSeesPy structural engine, Lognormal Monte Carlo sampling, and Bayesian inference algorithms./data: Contains the compressed ground motion suite (Acel_2694_047407.zip) consisting of 73 processed seismic records from the 2017 Puebla Earthquake (PGA max = 1.705 m/s²)./results: Raw data in CSV format, including Pushover capacity curves, fragility function coordinates (Prior vs. Posterior), and high-resolution figures for manuscript validation.Usage NotesThe Python environment requires openseespy, numpy, scipy, matplotlib, and pandas. For reproducibility, the ground motion suite must be unzipped into the working directory. The provided scripts include an autonomous file scanner to process the seismic ensemble.