Earthquake Engineering & Structural Dynamics最新文献

Reliability-based design optimization (RBDO) traditionally relies primarily on high-fidelity and computationally expensive simulations to search for and evaluate design solutions. However, significant disparities could emerge for complex nonlinear behavior that are challenging for numerical modeling. In contrast to mitigating the impact of inaccurate numerical modeling through optimization algorithms, laboratory experiments realistically capture the complex nonlinear behavior of structures or their components. Real-time hybrid simulation (RTHS) is widely considered as an efficient and cost-effective technique for integrating numerical modeling with experimental testing for structural response evaluation. This study proposes an innovative framework that utilizes RTHS for the performance assessment of candidate designs to enable RBDO of structures subjected to pulse-like ground motions. RTHS tests are conducted to physically evaluate structural responses through realistically replicating complex nonlinear behavior of experimental substructures. This study introduces a novel penalty function-based efficient global optimization (P-EGO) method to minimize the required number of laboratory tests through surrogating the response quantities of interest derived from RTHS. The proposed framework is experimentally evaluated for design optimization of a two-story four-bay steel moment-resisting frame with self-centering viscous dampers subjected to pulse-like ground motions. The results demonstrate innovative application of RTHS in dynamic optimal design to account for uncertainties. It offers an effective and efficient alternative for traditional RBDO through pure computational simulation, particularly when structural components pose challenges for numerical modeling.

The aim of this study was to examine the seismic performance of reinforced concrete shear walls in in-plane and out-of-plane directions under single main shock and mainshock-aftershock sequences. Two shear wall specimens were designed for low cycle load tests to withstand in-plane, in-plane then out-of-plane (IP-OP), out-plane, and out-of-plane then in-plane (OP-IP) forces, respectively. The seismic performance of shear walls under different forces was assessed by analyzing macroscopic failure phenomena and the novel performance parameters of specimens, following which their damage status was evaluated. The specimens were simulated using finite element software, and two frame shear wall structural systems were designed so that non-linear time history analysis could be performed to assess the deformation and damage to the shear walls in the two directions of the plane under a single main impact and different input directions of mainshock-aftershock sequences. The results revealed that following damage in the in-plane direction of the shear wall, seismic capacity decreased significantly if it was subjected to a force in the out-of-plane direction once again, and the degree of damage under the earthquake action of mainshock-aftershock sequences was significantly higher than that under the single main shock action. Therefore, it is necessary to pay special attention to the seismic performance of the out-of-plane direction of the shear walls and examine the seismic performance of the structural system under different input directions of mainshock-aftershock sequences.

Strong earthquake disasters can cause noticeable damage correlations among regional buildings with similar mechanical properties, termed structure-to-structure seismic damage correlation, which has a pronounced impact on the regional seismic risk assessment and therefore needs to be properly quantified. This study first introduces a time-domain analytical and equivalent frequency-domain analysis based on random vibration theory for calculating structure-to-structure seismic damage correlation coefficients. Subsequently, by employing the spatially consistent white noise excitation and the spatially varying white noise excitation with the Luco–Wong coherence function, the structural filtering effect and the ground motion spatial correlation effect are progressively incorporated, and an analytical interstructural damage correlation model incorporating structural dynamic properties and spatial distance is derived. Comparations with Monte Carlo simulations and existing empirical models demonstrate that the proposed analytical model possesses a clear physical basis and high reliability. Finally, a case study was conducted on a district having 29,461 buildings in Shanghai, China to illustrate the influence of interstructural damage correlation on the regional seismic risk. Results show that disregarding the interstructural seismic damage correlation can lead to underestimation of overall loss uncertainty.

Prediction of the soil seismic response is of primary importance for geotechnical earthquake engineering. Conventional physics-based models such as the finite element method (FEM) often face challenges due to inherent model assumptions and uncertainties of model parameters. Furthermore, these physics-based models require significant computational resources, particularly when simulating seismic responses across numerous soil sites. In this study, a multi- input integrative neural network is developed for predicting soil seismic response based on the recorded data from a large number of downhole array sites. Ground motions, seismic event information, and wave velocity structures of the sites are utilized as input data in the proposed neural network, enabling the model to adapt to various site conditions. Comparative assessments against state-of-the-art FEM models demonstrate that the proposed models exhibit superior prediction performance with increased efficiency. Furthermore, the pre-training technique, a transfer learning method, is employed to predict the seismic response at new stations. By fine-tuning the pre-trained model derived from the extensive dataset with limited recorded data from new stations, high-precision seismic response predictions can be realized, illustrating the adaptability and efficacy of the proposed approach in data-scarce conditions.

The traditional tower-style building (TTSB) is an innovative structural form constructed in modern cities imitating the overall appearance of ancient timber pagodas, and it is an extraordinarily cultured high-rise construction. The limited stipulations for high-rise TTSBs in the seismic design code pose challenges in assessing the reliable performance of the unique structure subjected to severe earthquakes. This paper presents the shaking table test and numerical analyses of a 1/15-scale 13-story TTSB specimen with an integral tower height of 5.36 m, which is a steel frame-braced core-tube structure consisting of seven bright floors (built-out stories evident from the outside, BF) and six dim floors (built-in stories not apparent from the outside, DF), with transition columns and stiffening trusses around the exterior perimeter. The experimental results showed that the tested tower-style building had excellent seismic performance and reliable structural integrity. It only experienced minor damage when subjected to extremely high-intensity motions. The interstory drift, dynamic strain, and floor acceleration response of the core-tube region with eccentric steel braces were more significant under severe excitation than those with cross-centered symmetric steel braces. The vertical reaction increased at the upper floor of the tower under vertical acceleration, and differences in the dynamic response of the middle and upper floors were much more apparent after the test. Moreover, 3D numerical simulation models of the tested tower were established and validated against the test responses. Successively, the validated numerical model was used to investigate the influence of the transition column at different floors on the peak interstory drift response and the relevant strain distribution, and the proposal for a proper position of the transition column was recommended at the end.

A novel, practical, and computationally efficient probabilistic methodology for the stochastic generation of suites of fully non-stationary artificial accelerograms is presented. The proposed methodology ensures that the produced ground motion suites match a given target spectral mean and target variability for the whole period range of interest. This is achieved by first producing an ensemble of random target spectra with the given mean and variability and then using them to generate artificial, target spectrum-compatible, acceleration time-histories with spectral representation techniques. Spectral correlation can also be assumed for the generated ground motion spectra. Based on the same backbone, two different formulations are proposed for generating spectrum-compatible acceleration time-histories of the non-stationary kind. The distinction between these two variants lies in the techniques employed for modeling the temporal and spectral modulation, focusing on the site-compatibility of the produced records. The first approach uses past-recorded seismic accelerograms as seed records, and the second proposes and uses a new, probabilistic time-frequency modulating function. The outcome of the proposed methodology is suites containing site-compatible ground motion time-histories whose spectral mean and variability match those obtained from any of the usually employed target spectra used in the earthquake engineering practice. An online tool implementing the proposed methodology is also freely provided.

This paper presents a comprehensive framework for life-cycle carbon emission assessment of steel frame structures in seismic zones, with a particular focus on emerging self-centering steel structures with reduced residual deformation and enhanced seismic resilience. The proposed framework is illustrated through a life-cycle embodied carbon (EC) emission study on an office building located at Los Angeles, USA. Different structural bracing systems are considered for comparison, namely, conventional concentrically braced frame (CBF), bucking-restrained braced frame (BRBF), and self-centering braced frames (SCBFs). The life cycle assessment (LCA) of EC emissions mainly involves four phases: (1) components manufacturing phase, (2) construction phase, (3) operation and maintenance phase, and (4) EC emissions related to seismic hazard. For the last stage, the engineering demand parameter (EDP) is obtained through incremental dynamic analysis (IDA), and combined with the fragility function and the seismic risk curve to obtain the expected EC emissions related to seismic hazard over the life cycle. Among other findings, the results show that: (1) In the manufacturing process, the EC emissions of the emerging SCBFs are slightly increased (by up to 1.4%) compared with the two other conventional steel frames. (2) During the construction, operation, and maintenance phases, there is no difference in the EC emissions for the different structural systems. (3) The EC emissions related to potential seismic risk are reduced by up to 65.3% when the proposed self-centering structural system (P-SCBF) is used. (4) Compared with the CBF, the total EC emission over a 100-year lifespan can be reduced by up to 14.6% when the P-SCBF is used. Due to the limited deformation capacity of braces, the EC emissions of CBF and BRBF are more sensitive to increases in the intensity measure (IM). Since a building becomes difficult to repair when the maximum residual inter-story drift exceeds 0.5%, BRBF and CBF are more susceptible to demolition due to unacceptable residual deformation, leading to higher EC emissions. The EC reduction efficiency of the emerging steel frames become more remarkable with increasing life span.

To address the issue of costly computational expenditure related to high-fidelity numerical models, surrogate models have been widely used in various engineering tasks, including design optimization. Despite the successful application of the existing surrogate models, physics-based models depend largely on simplifications and assumptions, which render parameter calibration challenging; whereas data-driven models require substantial data to reach their full potential, with their performance often being constrained in tasks when obtaining massive data is difficult. In this study, a hybrid surrogate model is proposed combining physics-based and data-driven models to rapidly estimate building seismic responses. The application of this model is exemplified through effective estimation of inter-story drift ratios (IDRs), being a critical factor in shear-wall structure design. Initially, a data augmentation technique and a parametric modeling procedure are introduced to significantly enhance the dataset diversity. Subsequently, a task decomposition strategy is proposed to effectively integrate a data-driven graph neural network (GNN) and a physics-based flexural-shear model. Additionally, the output layer and the loss function of the GNN are modified to enhance the estimation accuracy by eliminating fundamental errors. Results of numerical experiments indicate that the proposed hybrid model can complete IDR estimations in an average time of 0.56 s, with a mean absolute percentage error of 12.7%. This performance significantly surpasses that of existing purely data-driven and physics-based models. A case study shows that the efficiency of the proposed hybrid model is approximately 100 times greater than that of conventional finite element software. This enables an accurate assessment of the design compliance with code requirements. The results of this study can be applied to the design optimization of seismic-resistant building structures.

This study presents the implementation of an online model updating algorithm within a full-scale hybrid simulation (HS) of a six story, four bay steel moment frame. The experimental substructure consists of a cruciform subassembly generating critical data on the nonlinear behavior of the first story column and two beams with reduced beam sections (RBSs) on each side. The updating algorithm focuses on the modeling parameters of plastic hinge elements representing the RBSs in the numerical model. A smooth plasticity model is utilized for beam plastic hinges with updating parameters identified from on-line experimental data through a modified version of the unscented Kalman filter. The HS shows that the numerical beam hinges based on simple hysteretic model with updated parameters are able to capture the characteristic behavior observed in experiments. Due to fracture of beam flanges is observed in the experiments, a selective updating concept is proposed to allow for updating multiple numerical components accounting for asymmetric behavior and variability in the response. The selective updating method is validated through virtual HSs that are better able to identify and isolate the effects of fracture and other behavioral characteristics. The combination of results from physical and virtual tests highlights the benefits of model updating on the local and overall system-level response.