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Soil–structure interaction (SSI) leads to a modification in the dynamic properties of structure, but due to the complexity of analysis, it is traditionally assumed in seismic designs that the structure is fixed-supported on the ground, which brings about potential risks to the seismic performances of structure. The study works on the possibility of SSI having detrimental effects by comparing the dynamic responses of the SSI system to a fixed-base structure, and presents charts for an evaluation of the system frequency of SSI for the purpose of engineering practice. In order to reveal the physical nature, the SSI model is reduced to its simplest form, consisting of a SDOF oscillator, a three-dimensional rectangular foundation, and a multi-layered half-space. The energy dissipation in the soil is achieved by foundation impedances and the substructure method. Previously, the foundation impedances are usually acquired by two-dimensional or axisymmetric three-dimensional models in uniform half-space to avoid the high cost of the more realistic, fully 3D models, while a high-precision indirect boundary element method is employed, combined with the non-singular Green's functions of distributed loads to calculate the foundation impedances. Although SSI dampens the peak amplitude of structure response in the frequency domain, case studies on four buildings' responses to 42 earthquakes in the time history show a possibility of 15–20% that SSI amplifies the dynamic responses of structures, such as the maximum and the mean values in the time history, depending on the properties of the structures and the site, as well as the frequency component of incident waves. [ABSTRACT FROM AUTHOR]

Bridges are an important type of transportation infrastructures. Once more than one bridge in a transportation network is extensively or completely damaged in a severe earthquake, the traffic capacity of the network may degrade significantly, resulting in considerable social and economic consequences to the community served. The principles of build back better (BBB) require that the performance level of a critical infrastructure facility should be properly determined in the post-hazard recovery process to reduce the future risk. This paper proposes a continuous-time Markov decision process framework based on life-cycle cost (LCC) for determining the optimum earthquake-resistant levels of the rebuilt bridges. Compared to other optimisation methodologies, the proposed one owns two distinctive features: (1) network-level LCC analyses are performed in the context of BBB principles; (2) optimum decisions are made sequentially at random time points of earthquake occurrence, and the optimum earthquake-resistant level of a rebuilt bridge depends on the performance levels of other bridges in the network. A hypothetical transportation network is investigated to demonstrate the application of the proposed methodology. In particular, the sensitivity of the optimum policy on network topology is studied. [ABSTRACT FROM AUTHOR]

Summary: We propose a computationally efficient stochastic framework and an associated mathematical formulation to assess the improvement in the vibration response of wind turbines with active structural controllers. Uncertainties in the turbulent wind speed as well as in the structural parameters are considered in the formulation for analyzing the 2 important (rated and cut‐out) wind speed conditions. A multimodal wind turbine model based on a NREL 5‐MW wind turbine model is adopted for analysis, and an active tendon controller is used to develop the stochastic framework. Dynamic interaction between the rotor blades and the supporting tower, as well as the coupling induced by the pretwist of the blades, and a collective pitch controller are considered. A time‐evolving phase spectrum method together with a phase delay spectrum model is used to simulate the stochastic wind field, which is computationally less expensive. The probability density contours and the extreme value distributions of the blade tip displacements with and without the active controller are obtained by the wavelet‐based probability density evolution method, followed by the computation of the corresponding failure probabilities. It is observed that the improvement in reliability and performance of the rotor blades with the controller becomes statistically more effective as the wind speed increases (e.g., significant beneficial effects are noticed from the probability distributions in terms of the spread at the cut‐out wind speed). [ABSTRACT FROM AUTHOR]

The probability density evolution method (PDEM) provides a feasible approach for the dynamic response analysis of nonlinear stochastic structures. The key step in this regard is to solve a generalized density evolution equation (GDEE) in order to establish the probability density function (PDF). Previously, a finite difference method (FDM) has often been resorted to solve the GDEE. However, one may encounter the problem of mesh sensitivity in the application of FDM to the PDEM. To this end, a novel difference-wavelet method that can improve the finite difference result by means of a nonlinear wavelet density estimation method is proposed in the present paper. By exploiting the multi-resolution property of wavelet functions and by choosing the optimal scale at each instant, it is expected that the bothering mesh sensitivity issue in finite difference method can be overcome to some extent and a better probability density result can be obtained. In order to verify the proposed method, a single-degree-of-freedom (SDOF) oscillator and an 8-story frame structure are investigated in detail. The results show the notable superiority of the proposed method to finite difference method. [ABSTRACT FROM AUTHOR]