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.

The widespread threat posed by slope structure failures to human lives and property safety is widely acknowledged. Additionally, natural soil often displays spatial variability due to geological deposition and other factors. Therefore, predicting the seismic response of slopes subjected to ground motions and inversely analyzing the spatial distribution of soils remains an unresolved issue. In the present work, a shaking table experimental test is first designed and carried out, in which a soft-soil slope dynamic system is established. To capture the seismic response of the soft-soil slope, specifically the experimental characteristic of acceleration and soil pressure response in both spatial domain and time domain, a series of sensors were pre-embedded in the slope. Subsequently, a model updating approach is proposed for slope seismic analysis that incorporates spatial variability of soil. In addition, to enhance computational efficiency, the dimensionality reduction of Karhunen-Lo & egrave;ve expansion method is introduced to reduce inverse analysis parameters. On the basis of 34 samples collected from experimental data, it is shown that near-fault pulse-like ground motions deliver greater concentrated energy, causing more severe damage to slope structures, especially the topsoil layer. Furthermore, using data obtained from a shaking table test subjected to ground motion Recorded Sequence Number 158H1 from the Pacific Earthquake Engineering Research Center NGA-West2 database as an example, it is also shown that the proposed approach demonstrates high accuracy in predicting the spatial distribution of the maximum shear modulus in soil slope dynamic systems. The present work not only addresses the challenges posed by mainshock-aftershock effects but also highlights the potential of model updating approaches to enhance the understanding of slope behavior under seismic loading conditions. In the present work, a shaking table experimental test is first designed and carried out, in which a soft-soil slope dynamic system is established. Subsequently, a stochastic model updating approach for seismic reliability analysis combing subset simulation with adaptive Bayesian updating with structural algorithm and dimensionality reduction of Karhunen-Lo & egrave;ve expansion is proposed. Combined with shaking table tests, an illustrative example of a slope model is given to demonstrate the feasibility of the proposed approach. image