Earthquake Engineering & Structural Dynamics最新文献

As buildings and structures age, the challenges of reinforcement and retrofitting become more significant, especially as their service life extends and the demand for seismic fortification increases. Integrating buckling-restrained braces (BRBs) is an effective retrofit technique; however, this approach requires multiple iterations of layout adjustments and mechanical performance analysis, which are highly dependent on engineers' design expertise, resulting in low efficiency. To address this, the study proposes a two-stage intelligent retrofit design method that integrates generative Artificial intelligence (AI) techniques with optimization algorithms for reinforced concrete (RC) frame structures using BRBs: (1) a diffusion model-based potential BRB layout generation stage, and (2) an online learning algorithm-based design optimization stage. In Stage 1, a diffusion model was employed to analyze architectural characteristics, identify potential BRB locations, narrow the feasible solution space for the optimization process, and ensure that the design meets empirical constraints. In Stage 2, an optimization algorithm, integrated with mechanical performance evaluation, was employed to determine the optimal locations and sizes of BRBs. Case studies revealed that these two methods enhanced efficiency by approximately 50 times compared to the direct design by engineers while maintaining design rationality and safety. Overall, these results demonstrate the feasibility and generalizability of the method in practical engineering applications, offering a reference for the intelligent design of more complex structural retrofits in the future.

The seismic behaviour of unreinforced masonry (URM) buildings is frequently modelled using macroelements, in the framework of an equivalent-frame schematisation of the walls. Although the advantages of this modelling technique, mainly related to the compromise between computational burden and accuracy of the results, appear to be valid also in the case of reinforced masonry (RM) buildings, few attempts have been made to extend its applicability to RM. This work proposes a mechanics-based macroelement approach to simulate the in-plane nonlinear response of RM piers, starting from a macroelement model widely adopted for URM and implemented in the TREMURI software. The strategy consists of discretising a masonry pier into sub-macroelements, representative of masonry and horizontal reinforcement, with nonlinear beams representing vertical reinforcement. Experimental tests performed on clay blocks RM piers were simulated to test the efficiency of this model in capturing the strength and cyclic behaviour associated with different damage mechanisms. More complex structures were then studied, starting from assemblies of piers, up to entire buildings. Even in these cases, the modelling approach proved to be able to model the nonlinear cyclic behaviour. Finally, the model was used to compare the response of two buildings in their unreinforced and reinforced configurations, through nonlinear static and dynamic analyses.

This paper introduces a novel hierarchical graph-based long short-term memory network designed for predicting the nonlinear seismic responses of building structures. We represent buildings as graphs with nodes and edges and utilize graph neural network (GNN) and long short-term memory (LSTM) technology to predict their responses when subjected to orthogonal horizontal ground motions. The model was trained using the results of nonlinear response-history analyses using 2000 sample 4–7-story steel moment resisting frames and 88 pairs of ground-motion records from earthquakes with a moment magnitude greater than 6.0 and closest site-to-fault distance shorter than 20 km. The results demonstrate the model's great performance in predicting floor acceleration, velocity, and displacement, as well as shear force, bending moment, and plastic hinges in beams and columns. Furthermore, the model has learned to recognize the significance of the first mode period of a building. The model's robust generalizability across diverse building geometry and its comprehensive predictions of floor responses and member forces position it as a potential surrogate model for the response-history analysis of buildings.

Numerical modeling represents a pivotal tool in the seismic analysis and design of structural systems, enabling the detailed prediction and examination of structural responses under seismic loading. This research conducts a comparative analysis of two numerical modeling approaches aimed at simulating the seismic response of unbonded fiber-reinforced elastomeric isolators (UFREIs). The research focuses on a finite element (FE) model developed using Abaqus and a developed phenomenological model implemented in OpenSees, outlining the development and calibration processes for each. The FE model is developed based on simple rubber material testing data, while the phenomenological model is calibrated using experimental results from cyclic shear tests conducted on the UFREI device and the FE model. The primary objective of this study is to assess the effectiveness of these modeling approaches in predicting UFREI behavior under seismic conditions. This evaluation entails comparing model predictions with experimental data obtained from unidirectional shake table tests performed on a rigid block isolated by two UFREIs. This paper highlights the distinct advantages and limitations of each model in simulating UFREI dynamic responses during seismic events. Furthermore, it provides insights into the modeling techniques and discusses the computational demands and data requirements of each model, thereby aiding in their application to various aspects of seismic analysis and design.

This paper introduces a stochastic simulator for seismic uncertainty quantification, which is crucial for performance-based earthquake engineering. The proposed simulator extends the recently developed dimensionality reduction-based surrogate modeling method (DR-SM) to address high-dimensional ground motion uncertainties and the high computational demands associated with nonlinear response history analyses. By integrating physics-based dimensionality reduction with multivariate conditional distribution models, the proposed simulator efficiently propagates seismic input into multivariate response quantities of interest. The simulator can incorporate both aleatory and epistemic uncertainties and does not assume distribution models for the seismic responses. The method is demonstrated through three finite element building models subjected to synthetic and recorded ground motions. The proposed method effectively predicts multivariate seismic responses and quantifies uncertainties, including correlations among responses.

The design of a new type of biaxial shaking table is presented. The shaking table is able to apply horizontal and vertical movements to models using two actuators. It is novel in that the two actuators are horizontally aligned, through its use of a scissor mechanism, and because of its compact design which permits simple anchorage to a laboratory strong floor. The scissor mechanism translates the movement of one of the actuators to a purely vertical movement at the table. The other actuator, which moves horizontally the scissor mechanism and its supports, causes the horizontal movement of the table. The horizontal and vertical movements are applied and controlled independently, individually or simultaneously. The capability of the shaking table to control and replicate a variety of uniaxial and biaxial movements is verified by conducting several shaking table experiments. This is done when the table is naked and when it supports a payload having a nonlinear dynamic response. Very good agreements between achieved and desired uniaxial and biaxial movements are attained. Rigidity of the scissor arm mechanism and connections, and preloaded roller bearings and rail blocks, are central to its success. Displacement errors, rolling, pitching and yawing of the table's top plate are negligible. The new table type is slightly more expensive than a uniaxial system, and substantially less expensive than a six degrees-of freedom system, meaning biaxial vertical and horizontal shaking capability can now be achieved in a laboratory at reasonable cost.

Past earthquake reconnaissance reports highlighted extensive seismic damages to suspended ceiling components and connections, including instances of complete ceiling failures. The seismic qualification of these nonstructural elements typically requires comprehensive evaluation through full-scale shake table testing. However, such experimental evaluation is ordinarily not possible for every change made in various components and connections of ceiling systems due to the cost and effort involved. A feasible alternative is to obtain the behavior of components and connections from sub-assemblage testing and incorporate them in appropriate numerical ceiling models to derive mechanical responses for developing alternative or new installation schemes. This paper considers critical connections of three continuous-plasterboard suspended ceiling systems that were evaluated using shake table-generated motions. The connections were classified according to their attachment to typical floors and walls of building structures, and sub-assemblage testing was conducted using both monotonic and cyclic displacement loading. The observed failure modes in each connection were detailed, and appropriate damage states were assigned as the basis for constructing connection fragility curves. The results of the sub-assemblage testing were presented in terms of the hysteresis responses, envelope curves, nonlinear backbone curves, and cumulative energy dissipation curves. Additionally, multilinear models of the connections were derived by approximating nonlinear backbone curves’ initial- and post-yield behaviors. These multilinear models were further idealized to derive three equivalent linearized models for simplified yet reasonably accurate results for linear structural analyses. Finally, fragility curves were derived for all connections, considering their cyclic displacement failure capacities.

Simplified building models are a valuable option for seismic assessment at the regional scale. These models often use calibrated springs to model column behaviour, and recent advances have made them suitable for capturing torsional response in Reinforced-Concrete Moment-Resisting-Frames. Nevertheless, their validation is typically achieved using fixed-base models, which do not include the influence of soil-structure interaction (SSI). This study introduces a novel approach to quantify the accuracy of a recently developed simplified model while accounting for dynamic SSI, using a newly implemented, refined 3D Finite Element non-linear soil model in OpenSees. The accuracy of the simplified structural model is assessed by comparing the results of non-linear dynamic analyses with those of a refined model in terms of (i) a peak structural demand parameter such as the interstorey-drift ratio and (ii) fragility curves computed from cloud analysis and accounting for collapse cases. The study presents details of the proposed refined approach for 3D soil modelling in OpenSees, focusing on implementing free-field boundary conditions and structure-to-soil connections. Results show that the accuracy of the simplified model is maintained, even in the presence of SSI, and it successfully captures the overall structural response measured at peak demand. For the proposed case study, the difference between the simplified and refined models’ fragility curves’ medians is 4% and 2% for fixed and SSI models, respectively. The simplified structural model, combined with the refined soil model for SSI effects, presents an innovative and conservative, yet computationally efficient, alternative for seismic risk analysis, even in the presence of structural irregularity.

To facilitate the logistic processes within a modern warehouse, the contents of steel racking systems are not mechanically connected to the supporting beams, allowing a content-sliding mechanism to develop when static friction is exceeded. Given that the mass of contents is dominant, this is beneficial for limiting the apparent inertia. On the other hand, pallet fall-off may occur during strong seismic excitations, which is a failure mode that is not addressed by current seismic design processes and guidelines for racks. Along these lines, a codifiable methodology is proposed for estimating sliding displacements on steel racking systems, based on the statistical interpretation of a large set of response history analyses, using different rack configurations and ground motions. Firstly, a multi-parametric analysis is conducted using simplified rack models to (i) select the intensity measure and engineering demand parameter that can best describe the problem of pallet sliding and (ii) identify the salient rack characteristics that dominate sliding behavior. Thereafter, a series of multi-stripe analyses are performed using 180 rack realizations with different feature combinations to derive a so-called, Empirical Sliding Prediction Equation (ESPE) by following a three-step procedure: (a) perform regression on maximum sliding, (b) perform regression on the normalized sliding profile, and (c) combine steps a-b to derive the denormalized profile at a given confidence level. The proposed empirical relationships are then validated through a comparison between the observed and fitted sliding displacements in three rack case studies.

The structural response under earthquake excitation can be simulated by shake table tests. However, the performance of the shake table is affected by the Control-Structure Interaction (CSI) effect. In recent years, nonlinear control algorithms were developed to compensate for the CSI effect. In this study, a model reference adaptive control algorithm, named model reference adaptive hierarchical control (MRAHC) framework, is presented. MRAHC consists of a high (adaptive) and low (loop-shaping) level controller. The high-level (adaptive) controller develops the control algorithm on the system level, which directedly considers the inherent nonlinearity of the test specimen and the CSI effect. While the low-level (loop-shaping) controller develops the control algorithm to regulate the hydraulic system and make sure it can follow the reference signal generated by the high-level (adaptive) controller. MRAHC offers many advantages including direct compensation to the structural nonlinearity and the ability to handle the CSI effect. In addition, it allows users to quantify the mass of the test specimens without measurement. To evaluate the performance of the MRAHC method, shake table tests with different upper structure masses were carried out. The performance of the MRAHC was compared with the direct loop-shaping control method (LC) and the Proportional-Integral-Differentiation control method (PID). The results show that the MRAHC can achieve better acceleration tracking compared to the LC and PID control methods. Hence, the MRAHC can be used as an effective nonlinear controller for shake table tests.