Accurate structural health monitoring (SHM) is crucial for ensuring safety and preventing catastrophic failures. However, conventional parameter identification methods often assume a fixed-base foundation, neglecting the significant influence of soil-structure interaction (SSI) on the dynamic response, leading to inaccurate damage assessments, especially under seismic loading. Therefore, we introduce a novel approach that explicitly incorporates SSI effects into parameter identification for frame structures, utilizing an optimized variational mode decomposition (VMD) technique. The core innovation is the application of the Subtraction Average-Based Optimizer (SABO) algorithm, coupled with permutation entropy as the fitness function, to optimize the critical VMD parameters. This SABO-VMD method was rigorously validated through a shaking table test on a 12-story frame structure on soft soil. Comparative analysis with EMD and conventional VMD demonstrated that SABO-VMD provides a superior time-frequency representation of the structural response, capturing non-stationary characteristics more effectively. A novel energy entropy index, derived from the SABO-VMD output with SSI, was developed for quantitative damage assessment. It revealed 8.1% lower degree of structural damage compared to the fixed-base assumption. The proposed SABO-VMD-based approach, by explicitly accounting for SSI, offers a substantial advancement in SHM of frame structures, leading to more reliable safety evaluations and improved seismic resilience.

This paper presents a data-driven model updating framework to estimate the operational parameters of a laterally-impacted pile. The goal is to facilitate the estimation of soil-pile interaction parameters such as the mobilized mass and stiffness, as well as geometrical data such as embedded pile length, using output-only information. Accurate knowledge of mass, stiffness, and pile embedded length is essential for understanding foundation behavior when developing digital-twin models of structures for the purpose of damage detection. The method first employs subspace identification to determine modal parameters and quantifies their uncertainties using output-only data. The covariance matrix adaptation evolution strategy (CMA-ES), a stochastic evolutionary algorithm, is subsequently used to update the model. The effectiveness of the approach is demonstrated through its application to numerical models in this paper, to quantify errors, and subsequently to data from a documented full-scale field test of a pile subjected to an impact load. The work underscores the potential of statistical updating in advancing the accuracy and reliability of soil-structure interaction parameter estimation for systems where only output data might exist.

The paper presents a study on the dredging vibrational effects, for nourishment purpose, on the existing structures surrounding the worksite. Nourishment is a common operation when beach (or coasts, or ports) protection is required, allowing to reduce far-field impacts of coastal structures and improve navigability. Nourishment is then performed to reshape underwater land, and it is usually practiced by locating in the zones in which is required, soil coming from nearby areas. This latter is often obtained by a dredging process, in which the phases of excavation, transportation and soil placement are carried out. From the structural point of view, of interest is the excavation phase, which is usually performed in the water environment by a ship equipped with a dredge that mines the seabed, generating a new source of vibrations for the existing structures facing the working area. The aim of this paper is to assess the effects of vibrations induced by dredging operations, by taking as reference the recently performed nourishment in the port of Bari, Southern Italy. To this scope, an existing structure was selected and identified as sentry building, considering its extreme proximity to the worksite. Hence, a structural monitoring was performed, by investigating the behaviour of the structure before, during and after the dredging. Three main controls were carried out within the monitoring campaign: (a) check of the vibration levels and comparison with thresholds provided by the current Italian prescriptions for human comfort and structural damages; (b) operational modal analysis to assess the possible variations of the structural behaviour during dredging; (c) calibration of a numerical model to simulate the structural behaviour of the sentry building and to derive unknown geometrical and mechanical parameters. A full description of the reference building (characterized by a certain irregularity degree) and all the monitoring phases are reported throughout the manuscript. The results show that, over the monitoring period, the dredging vibration levels never exceeded the thresholds provided by code provisions, and subsequently, the sentry building did not report structural damages, as confirmed by the continuous control of dynamic parameters from experimental and numerical models. In addition, the contents of the paper show the paramount importance of the structural health monitoring, and the experience herein reported can inspire the management of buildings under particular actions like the ones herein investigated.

This paper introduces a fully automated modal identification algorithm based on the Multivariate Variational Mode Decomposition (MVMD) of free vibration responses to determine structural modal parameters. Addressing the challenge of setting MVMD parameters, we introduce a fusion parameter combining power spectral cross-entropy with reconstruction error as an adaptive fitness function in the optimization algorithm, enabling optimal parameter selection. Then, modal frequencies, damping ratios, and shapes of structures can be extracted from autonomously decomposed Intrinsic Mode Functions by employing the principle of modal superposition and least squares fitting without manual parameter adjustments. Validated by a four-degree-offreedom numerical model, the method demonstrated accurate, automatic modal parameter identification. The method was further applied to a subway tunnel structure model experiment. Comprehensive modal identification was conducted on tunnel structures under varying degrees of damage. The results validate the proposed method's effectiveness and reveal the damaged segment structure's multimodal parameter variation patterns and surrounding soil.

Since the dawn of civilization, sandstone has been a fantastic building material. Numerous causes have been observed in the past for sandstone damage or deterioration, one of which is sulphur-oxidizing bacteria (SOB) and cyanobacteria. In general, SOB is present in the soil, air, water, humidity, and human activity. The oxidation of sulphur compounds, such as hydrogen sulphide, thiosulphate, or elements of sulphur, provides energy for SOB. These microorganisms contribute to the decay of buildings materials, especially those made of stone, metal, or concrete. The sulphur oxidizing process affects the mechanical properties of sandstone. Mechanical properties are related to strength. Losses of mechanical properties may be the reason for deflection, cracking, collapse, and catastrophic failure of sandstone. Monitoring and evaluation gives an idea about the behavior of structure and the prevention of catastrophic failure. This research paper contains the application of electromechanical impedance with surface bonded Piezoelectric Lead Zirconate Titanate. The sandstone samples and soil samples have been collected from the historical site. Two sets of cylindrical types of sandstone specimens have been used in experimental work. The conductance signature and susceptance signature have been measured every six months. The variation and shifting of the signature curve have been used to identify the structural behavioral change. Statistical methods like the root mean square deviation have been used for the quantification of damage. An equitation has been generated on the basis of the percentage root mean square deviation to quantify the prediction of damages.