Experimental Estimation of the Elastic Modulus of Concrete Girders from Drive-By Inspections with Force-Balance Accelerometers

Parametric identification of bridges using instrumented vehicles can be challenging, mainly due to the reduced length of the time series associated with the bridge span under test. This research discusses the practicability of a time-domain identification method based on the use of an instrumented vehicle. The highest cross-correlation between the bridge response from an elementary analytical model and the experimental one, acquired by a moving force-balance accelerometer, yields the unknown model parameter. The effect of vehicle-bridge interaction is removed by proper filtering of the signals. Specifically, the authors estimate the elastic moduli of seven prestressed concrete bridges and compare a subset of the results to the outcomes of static load tests carried out on the same bridges. There is a good correlation between the elastic moduli from the instrumented vehicle and those from static load tests: the method grasps the approximate value of the elastic modulus of concrete. Still, the data do not return an excellent match due to the bias in the estimation of the deflection shape—the paper remarks on the issues faced during the experimental tests and proposes possible enhancements of these procedures

The architrave a tasselli

The architrave a tasselli is a peculiar design shape of the traditional stone lintels, which are widespread in Abruzzo, Italy: stone lintels are not usually monolithic elements, being formed by three pieces, the block spanning the opening and the tasselli, two small rectangular pieces. In the current paper, by means of an elementary Wrinkler-type beam model, it has been attempted to capture the behaviour of stone lintels, chasing the mechanical reasons supporting this traditional construction technique. Keywords: Architectural heritage, Theory of elasticity, Masonry building, Traditional constructive technique

Dynamic identification and model updating of an eight-storey CLT building

So far, few in situtests have been carried out to estimate the modal parameters of multi-storey Cross-Laminated-Timber (CLT) buildings: the understanding of their dynamic behaviour under operational conditions is still an open issue. In this paper, the results of the dynamic identification of an eight-storey CLT building are reported and interpreted in the light of a simplified shear-type analytical model. The structural model is calibrated on the experimental modal parameters, which are assessed using the Stochastic Subspace Identification (SSI). The SSI provides mode shapes, natural frequencies and damping factors of the structures in its first linear response range; The minimum of a modal-based objective function gives an estimation of the unknown parameters of the structural model. Given the results of the dynamic identification, the storey-masses are the chosen optimization parameters: the values of the experimental eigenfrequencies likely reveal a continuum-like behaviour of the building without connections. The identified storey masses are indeed realistic and confirm the negligible role of the connections in the low-amplitude dynamic response. The nonlinear effects of connections over the building response to higher displacements are discussed, providing simplified and practice-oriented correlations for the first natural frequency estimation.acceptedVersio

Generative adversarial networks review in earthquake-related engineering fields

Within seismology, geology, civil and structural engineering, deep learning (DL), especially via generative adversarial networks (GANs), represents an innovative, engaging, and advantageous way to generate reliable synthetic data that represent actual samples' characteristics, providing a handy data augmentation tool. Indeed, in many practical applications, obtaining a significant number of high-quality information is demanding. Data augmentation is generally based on artificial intelligence (AI) and machine learning data-driven models. The DL GAN-based data augmentation approach for generating synthetic seismic signals revolutionized the current data augmentation paradigm. This study delivers a critical state-of-art review, explaining recent research into AI-based GAN synthetic generation of ground motion signals or seismic events, and also with a comprehensive insight into seismic-related geophysical studies. This study may be relevant, especially for the earth and planetary science, geology and seismology, oil and gas exploration, and on the other hand for assessing the seismic response of buildings and infrastructures, seismic detection tasks, and general structural and civil engineering applications. Furthermore, highlighting the strengths and limitations of the current studies on adversarial learning applied to seismology may help to guide research efforts in the next future toward the most promising directions

Intelligent automatic operational modal analysis

Operational modal analysis methods have been proven especially useful to identify existing structures and infrastructures under serviceability conditions. However, the installation of sensing systems for monitoring continuously an ever larger number of existing constructions has motivated significant efforts towards the automation of the available methods. Within this framework, the present paper introduces a new paradigm for the automatic output-only modal identification of linear structures under ambient vibrations, namely the intelligent automatic operational modal analysis (i-AOMA). It exploits the covariance-based stochastic subspace (SSI-cov) algorithm for the output-only identification of the modal parameters and its workflow consists of two main phases. Initially, quasi-random samples of the control parameters for the SSI-cov algorithm are generated. Once the SSI-cov algorithm is performed for each sample, the corresponding stabilization diagrams are processed in order to prepare a database for training the intelligent core of the i-AOMA method. This is a machine learning technique (namely a random forest algorithm) that predicts which combination of the control parameters for the SSI-cov algorithm is able to provide good modal estimates. Afterward, new quasi-random samples of the control parameters for the SSI-cov algorithm are generated repeatedly until a statistical convergence criterion is achieved. If the generic sample is classified as feasible by the intelligent core of the i-AOMA method, then the SSI-cov algorithm is performed. Finally, stable modal results are distilled from the stabilization diagrams and relevant statistics are computed to evaluate the uncertainty level due to the variability of the control parameters. The proposed i-AOMA method has been applied to identify the modal features of the Al-Hamra Firduos Tower, an iconic 412.6 m tall building located in Kuwait City (Kuwait). The final results well agree with a previous experimental study, and it was also possible to identify two new vibration modes of the structure. The implemented open-source Python code is made freely available

Analysis of the Joint Effects of Thermal Stresses and Corrosion on Integral Abutment Bridges

The corrosion of reinforced concrete structures in coastal areas turns out to be very severe and can extend significantly in windy zones. Additionally, frequent temperature changes and, above all, exposure to extreme temperatures might induce wider cracks and micro‐cracks in concrete structures which, in turn, might accelerate the diffusion of corrosive agents. Motivated by this evidence, the present study aims at verifying the sensitivity of integral abutment bridges to the combined effect of thermal stresses and corrosion. Preliminary results show that a high thermal stress may amplify the negative effects of corrosion but also that the bridge used for the case study is more sensitive to thermal stresses than to corrosion

Buckling capacity model for timber screws loaded in compression: Experimental, analytical and FE investigations

This paper investigates the buckling of screws loaded in compression inserted into timber members. Screws are often used as a reinforcement in timber structures. However, under compression forces, they are prone to axial buckling. The current model for the screw buckling, enclosed in the EC5 proposal, is based on the general framework of EC3 for the instability of compressed steel members. The main shortcomings of the current formulation for the buckling of screws are the following. (1) The analytical expression for calculating the theoretical buckling load does not follow the observed modes. (2) Due to the need for dedicated studies, the value of the imperfection coefficient is arbitrarily chosen. This paper fills the above gaps. Firstly, a simple analytical expression for predicting the buckling of screws is proposed and validated against experimental and finite element (FE) findings. Furthermore, the formulation adopts a more accurate expression for lateral deformation based on experimental observation. Secondly, a FE model calibrated on experimental tests is used to estimate the defect coefficients of the instability curves as a function of the amplitude of the geometric defects of the screw, expressed as a fraction of its length. Finally, a Markov chain Monte Carlo analysis is carried out to simulate the capacity of screws with different sizes, assuming the uncertainty of all input parameters sampled from suitable probability distributions. The results are used to validate the proposed deterministic capacity model and estimate the uncertainty factors of the design equation

Diquark condensation at strong coupling

The possibility of diquark condensation at sufficiently large baryon chemical potential and zero temperature is analyzed in QCD at strong coupling. In agreement with other strong coupling analysis, it is found that a first order phase transition separates a low density phase with chiral symmetry spontaneously broken from a high density phase where chiral symmetry is restored. In none of the phases diquark condensation takes place as an equilibrium state, but, for any value of the chemical potential, there is a metastable state characterized by a non-vanishing diquark condensate. The energy difference between this metastable state and the equilibrium state decreases with the chemical potential and is minimum in the high density phase. The results indicate that there is attraction in the quark-quark sector also at strong coupling, and that the attraction is more effective at high baryon density, but for infinite coupling it is not enough to produce diquark condensation. It is argued that the absence of diquark condensation is not a peculiarity of the strong coupling limit, but persists at sufficiently large finite couplings.Comment: 10 pages, 2 figures. An important discussion concerning the extension of the results to finite couplings adde