a b s t r a c tUniaxial compression tests are the most common tests for characterizing the strength of concrete-like materials. The dynamic compression strength of concrete-like material is typically obtained by Split Hopkinson Pressure Bar (SHPB) tests. The increase in material strength under dynamic loading is usually attributed to the strain rate effect and modelled with a dynamic increase factor (DIF). However, it was observed by some researchers that the radial inertial confinement caused apparent increase of dynamic strength of concrete-like specimen in SHPB tests. They attributed the material strength increase to this inertial effect, instead of the strain rate effect. In the present study, numerical analyses are performed to investigate the compressive behaviour of concrete-like material at high strain rates. A homogeneous macroscale model and a heterogeneous mesoscale model are developed in the study. In the macroscale model, the material is assumed to be homogeneous and isotropic. In the mesoscale model, the test sample is modelled as a threephase composite consisting of aggregate, mortar matrix and interfacial transaction zone (ITZ) between the aggregate and the mortar matrix. The aggregate is assumed to be circular and the ITZ is modelled as a thin boundary around the aggregate. In the both models, the materials are assumed to be insensitive to the strain rate first. Therefore, the obtained strength enhancement is only due to the inertial confinement. Strain rate sensitive material properties are then used in the two models in the calculations. Numerical simulations of the concrete samples under compression at different strain rates are carried out. The relative contribution of the inertial effect and the strain rate effect on the compressive strength DIF is examined based on the numerical results. The failure process of concrete specimen is also studied.

It is important to take into account the effect of temperature in assessing the structural condition of bridges. However, very few quantitative studies have examined the temperature behavior of large-scale bridges because of their large size and complicated configuration. This paper, for the first time, investigates the temperature distribution and associated responses of a long-span suspension bridge-the 2132-m-long Tsing Ma Bridgethrough a combination of numerical analysis and field monitoring. With appropriate assumptions, fine finite element models of a deck plate, section frame, and bridge tower are constructed to facilitate thermal analysis. With ambient temperature measurements and a solar radiation model, the time-dependent temperature distribution within each of these components is calculated through transient heat transfer analysis. The numerical results are verified by comparing them with field monitoring data on temperature distribution and variation at different times and in different seasons. The temperature data are then input into the structural model of the whole bridge to obtain the displacement and strain responses of various bridge components, with a good level of agreement being achieved between the bridge responses and the monitoring data. This exercise verifies both the accuracy of the analytical method employed and the effectiveness of the monitoring system installed on the bridge. The study shows that integrating numerical analysis with field monitoring data provides for a thorough understanding of the temperature behavior of long-span bridges.

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Summary Conventional vibration‐based damage detection methods employ the Tikhonov regularization in model updating to deal with the problems of underdeterminacy and measurement noise. However, the Tikhonov regularization technique tends to provide over smooth solutions that the identified damage is distributed to many structural elements. This result does not match the sparsity property of the actual damage scenario, in which structural damage typically occurs at a small number of locations only in comparison with the total elements of the entire structure. In this study, an l1 regularization‐based model updating technique is developed by utilizing the sparsity of the structural damage. Both natural frequencies and mode shapes are employed during the model updating. A strategy of selecting the regularization parameter for the l1 regularization problem is also developed. A numerical and an experimental examples are utilized to demonstrate the effectiveness of the proposed damage detection method. The results showed that the proposed l1 regularization‐based method is able to locate and quantify the sparse damage correctly over a large number of elements. The effects of the mode number on the damage detection results are also investigated. The advantage of the present l1 regularization over the traditional l2 regularization method in damage detection is also demonstrated.

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