An alternative probabilistic assessment of buildings excited by multi-level seismic loading is presented in this paper. This evaluation is developed for both steel and reinforced concrete buildings using the Performance-Based Seismic Design (PBSD) concept. The methodology implements Probability Density Functions (PDFs) of inter-story drifts to extract structural risk in terms of the reliability index. Ten buildings of steel and reinforced concrete, respectively, are designed considering different locations in Mexico. Then, each structure is excited by ground motions representing different earthquake intensity levels for three performance levels: immediate occupancy, life safety, and collapse prevention. The deterministic seismic response of buildings is extracted using the finite element software OpenSees. Based on the results, it can be stated that the probabilistic assessment technique represents an efficient approach for extracting the seismic risk of structures using PDFs of inter-story drifts. Lastly, it is demonstrated that the evaluation of buildings following PBSD is a step in the right direction, moving from traditional deterministic design concepts to probabilistic philosophies.

In recent years, Interferometric Synthetic Aperture Radar (InSAR) technology has been able to determine the semi-static behavior of bridges. However, most of the research about the use of InSAR in the monitoring of bridges has been applied only in deterministic assessments of their performance. Therefore, in the current manuscript, the Usumacinta Bridge, located in Mexico, was evaluated based on a probabilistic methodology to define structural reliability using images from Sentinel-1. In addition, a controlled experiment was developed using a corner reflector (CR) to evaluate the capabilities of InSAR for determining vertical displacements. In the trial, the CR was designed, oriented, and implemented, finding discrepancies concerning leveling of less than 2 mm. On the other hand, the case of the alternative probabilistic approach integrates the reliability of structures theory and probability density functions (PDFs) of displacements obtained via InSAR technology. In summary, the proposed study focused on the analysis of two years of vertical displacements and monthly velocities; then, implementing the alternative probabilistic approach, the reliability index (β) and probability of risk (P_R) of the bridge were extracted, respectively. Based on the results of the experimental part of the paper, the displacements indicated maximum and minimum values of reliability index of 8.1 and 3.4, respectively. Within this context, the mean and standard deviation obtained were 5.9 and 1.4, respectively. On the other hand, the monthly velocities showed a maximum probability of risk of 2.61%, minimum value of 1.5 × 10⁻⁵%, mean of 0.4%, and standard deviation of 0.8%. Hence, the above-documented results indicate that the Usumacinta Bridge did not suffer any damage during its overloading condition period.

Existing bridges represent a significant challenge for structural engineering due to aging, increased traffic demands, and lack of original design information. This paper presents an investigation of the structural behavior of the Miguel Hidalgo Bridge, located in Culiacán, Sinaloa, México, which has remained in service for over a century. A preliminary visual inspection identified deterioration mechanisms, including cracking, exposed reinforcement, damaged bearings, and localized structural deformations. Given the absence of original design documentation, a structural health monitoring (SHM) strategy was implemented to assess its condition. The SHM methodology integrates field instrumentation using accelerometers for operational modal analysis under ambient vibration and GPS receivers for displacement measurements, complemented by a geometric survey and material characterization through non-destructive techniques. These data were used to develop and calibrate a three-dimensional finite element (FE) model, which was employed to evaluate structural performance under service loads in accordance with AASHTO provisions. Results indicate that the bridge satisfies serviceability criteria; however, certain components exhibit deficiencies in load-carrying capacity. These findings highlight the importance of integrating monitoring data with numerical modeling to support decision-making related to maintenance, rehabilitation, and extension of service life in existing bridge infrastructure.

Seismic excitations induce floor accelerations that can damage non-structural components and, in extreme cases, contribute to global structural failure. Although floor acceleration demands have been widely studied, their integration into probabilistic seismic performance and reliability frameworks remains limited within Performance-Based Seismic Design (PBSD). This study addresses this gap by proposing a reliability-based framework that incorporates the stochastic nature of floor accelerations through their probability density functions. Five-story steel and reinforced concrete (RC) buildings, designed according to Mexican codes, were analyzed using nonlinear dynamic simulations in PERFORM 3D under 33 ground motions corresponding to immediate occupancy (IO), life safety (LS), and collapse prevention (CP) levels. Structural reliability was quantified using the probability of failure ($p_f$) and the reliability index (β). Results show that peak accelerations occur at the roof level, with higher demands in the steel structure. For the IO level, β ranged from approximately 2.29 to values above 4.0 in steel buildings, while RC structures reached up to β ≈ 4.97. At LS and CP levels, RC buildings maintained β values generally above 3.0, whereas steel structures showed values as low as β ≈ 1.32. The Kernel distribution best captured response variability, reflecting high dispersion ($C.V.$ > 30%). The proposed framework enhances PBSD by linking acceleration demands with reliability-based decision-making.

This study assesses ground subsidence and surface angular distortion along the Lerma–Zinacantepec segment of the Mexico-Toluca Intercity Railway. A multitemporal Interferometric Synthetic Aperture Radar (InSAR) framework using the Short Baseline Subset (SBAS) algorithm processed Sentinel-1 imagery (2022–2024), validated against the MXTO Global Navigation Satellite Systems (GNSS) station ($R^2$ of 0.86 and 0.80 for descending and ascending tracks, respectively). Kinematic vector decomposition revealed a mean vertical ground subsidence rate of −2 cm/year. To evaluate geohazard susceptibility, angular distortion was computed from these decomposed vertical displacements using a fixed 160 m spatial baseline. By explicitly integrating intrinsic InSAR measurement uncertainty into the classification, localized steep gradients initially flagged by mathematical models were discarded as statistically negligible artifacts. Consequently, results show widespread ground stability, with the evaluated 16-km segment falling within low-risk thresholds. Corroborating this, in-situ visual inspections revealed no structural damage induced by differential subsidence. Due to Sentinel-1 pixel-mixing limitations, the measured signals represent ground subsidence rather than direct structural deformation. Future monitoring should integrate higher-resolution SAR sensors or localized structural health instrumentation to isolate the behavior of the railway superstructure from regional subsidence.