Long-span self-anchored suspension bridges (SAS) with rigid cable towers are intricately designed to satisfy the aesthetic standards of structural design. Unlike the traditional arrangement of bridge towers and main girder, the ellipse-shaped bridge tower runs parallel to the longitudinal girder and exhibits significant variations in stiffness in the longitudinal and transverse directions. There is an internal force redistribution of the girder between the main and side spans during seismic excitations relative to static equilibrium. These unique bridge designs induce striking spatial impacts; earthquakes can potentially result in intricate and unforeseeable reactions within the entire structure. To understand this better, a shaking table test was performed on a 1/50 scale model of a long-span self-anchored suspension bridge with rigid cable towers to analyze its seismic response. The full-bridge model was tested on a dual-shaking-table system to investigate its seismic response under consistent excitation in various input directions. The test results confirmed the accuracy of the test model based on its comparison with a finite element model (FEM). The main tower exhibited the most significant transverse displacement change at the top relative to the base, with the largest strain responses observed near its waist. The vertical acceleration peak of the bridge was substantially greater than that in the horizontal direction owing to the large main span and the involvement of the third mode in the bridge model. Furthermore, the bridge model experienced a higher average variation in the suspender force under longitudinal and vertical excitations than under transverse and vertical excitations. These study findings provide insights into improving the structural designs of modern SAS, thereby ensuring better resistance to earthquake excitations.

During operation, co-linear bridge and tunnel structures are subjected not only to direct actions from various loads but also to vibrational loads transmitted through the surrounding soil from other co-linear structures. Understanding the influence laws of co-linear structures on bridge and tunnel structures and accurately predicting their dynamic and static responses under the combined effects of direct loads and indirect loads from co-linear structures have long been recognized as a challenging problem in structural health monitoring and risk early-warning for urban transportation infrastructure. To address the challenges of excessive complexity in establishing multi-physics coupled models for uncovering underlying laws and predicting structural responses, as well as the limited prediction accuracy of traditional machine learning methods, a prediction method for the response of co-linear bridge and tunnel structures based on the UniST large model was proposed. In this method, multi-source and multi-scale characteristics embedded in timeseries response data were extracted through adaptive segmentation, diverse-frequency sampling, spatiotemporal chunking and encoding, and prompt-based learning. These characteristics were then leveraged by the large model to accurately forecast future structural responses, thereby providing novel insights and methodologies for the proactive identification, early-warning, timely mitigation, and safe operation and maintenance of potential structural risks.

In real-time hybrid testing (RTHT), there is an inevitable time delay in the loading system because of the dynamic characteristics of the loading-specimen system. Time delay can reduce the accuracy or even lead to the instability of the test. Because of the nonlinearity in loading-specimen systems and the uncertainty of the input signals, time delay has significant time-variant characteristics and uncertainty. To guarantee the stability and accuracy of RTHT, a backpropagation neural network time delay compensation method combined with sliding mode (BPNN-SM) is proposed. The BPNN-SM method uses sliding mode as a feedback controller of the loading system to improve robustness and compensate for part of the time delay. BPNN is used as the inverse compensation to compensate for the residual time delay and further improve robustness. The desired command and displacement responses of the experimental substructure are used as the input and output for training the BPNN inverse model of the loading-specimen system with a sliding mode controller. The BPNN has 4 hidden layers and 50 inputs in the input layer, which is expanded by one input data column to get enough data. BPNN can model highly complex nonlinear dynamic characteristics with a fully connected structure and calculate quickly using the error backpropagation mechanism, which makes the compensation more robust. The time delay compensation tests and RTHT of a single-degree-of-freedom (SDOF) structure based on the mast of SEG Plaza were conducted. The test results show that BPNN-SM has an excellent compensation effect.

In real-time hybrid simulation (RTHS), delay compensation is one of the crucial issues that affect the accuracy and reliability of test data. A novel two-stage adaptive delay compensation method is presented in this study to enhance compensation accuracy and robustness. This method employs a Kalman filter-based adaptive nominal model compensation (KF-ANMC) in the first stage to enhance the compensation robustness against system uncertainties. Inverse control compensation serves as the second stage compensation to eliminate the system delay and to improve the accuracy of RTHS. Through computational simulations and real tests of RTHS for high-speed trains, the effectiveness and robustness of the proposed method are validated, and the influence of relevant parameters on its performance is thoroughly analyzed. Results indicate that the proposed method exhibits great robustness against system uncertainties and superior delay compensation performance. Moreover, this study shows that the proposed method is endowed with reduced dependence on the orders of KF-ANMC and nominal system model, and parameter initialization.

Delay compensation presents a key component to ensure an accurate and robust real-time hybrid test (RTHT). As RTHT continues to evolve, the scale and degrees of freedom of studied structures increase, requiring greater attention to the responses of higher-order modes. High-frequency components in structural responses at the boundaries of substructures must also be accurately imposed onto the specimen. Robust delay compensation for high-frequency signals loading in RTHT needs to be explored. This paper proposes an adaptive time delay compensation based discrete model strategy combined with sliding mode control method (ADM-SMC). In this method, combining with the robust sliding mode control (SMC), the least squares method is used to update the parameters of the discrete model of the SMC-loading system in real time, which provides a robust compensation method for the wide-band and high-frequency excitation loading. A delay compensation test and a RTHT were conducted to verify the feasibility of this method. The results indicate that the proposed method can compensate varying time delay precisely with robustness for different high-frequency excitation loading.

Hybrid simulation is a powerful and cost-effective technique for structural dynamic tests. However, when the available number of actuators is less than the number of the interface degrees of freedom (DOFs), it is usually difficult to guarantee all the complex boundary conditions on the experimental substructure. To tackle the issue of incomplete boundary conditions, a hybrid simulation method with restoring force correction (HSRFC) was conceived, which is based on the coupling of an auxiliary numerical model, an entire numerical model, and an experimental substructure, such that the numerical model can supplement the responses that cannot be obtained from the experimental substructure. This study focuses on the performance analysis and experimental validation of the HSRFC method. Firstly, the performance of this method was analyzed considering the influence of two major issues, which are the modelling error of the experimental substructure and the coupling degree of the interface DOFs. The effectiveness and feasibility of the HSRFC method were then validated through actual hybrid tests on a precast prestressed efficiently fabricated frame equipped with shear plate dampers (PPEFF-SPD). Results indicated that the negative effect of incomplete boundary conditions was almost eliminated and the accuracy of the hybrid simulation was greatly improved.

This study investigated the dynamic performance of ultra-high performance concrete (UHPC) targets reinforced with honeycomb-steel-tube and polyurea coatings under sequential projectile penetration and blast. Three types of target specimens, including the ordinary target, honeycomb target, and polyurea-reinforced honeycomb targets (PRHTs), were fabricated with UHPC of different compressive strengths. The resistances to both penetration and blast were evaluated through sequential loading tests. Experimental results show that the honeycomb-steeltube effectively constrained lateral damage, which reduced tunnel depth and suppressed crack propagation. Polyurea coatings further enhanced energy absorption and rear surface integrity by delaying crack development and capturing debris. The UHPC with higher strength significantly improved resistances to both penetration and blast loads compared to lower strength UHPC. Under a penetration velocity of 725 m/s, the PRHT exhibited superior damage control, with an intact rear surface and minimized fragmentation. Strain gauge data confirmed substantial energy dissipation by the steel tubes and polyurea, particularly in the high strength UHPC. The PRHTs' structural damage resistance was improved by approximately 30-50 % compared to ordinary target. In addition, numerical simulations of the three target types exhibited strong consistency with the experimental data, further validating the reliability of the findings. These findings offer valuable guidance for the engineering design of UHPC-based composite structures, promoting their effective deployment in protective systems against extreme penetration and blast loads.

Offline iterative control (OIC) is a widely employed technique in shaking table tests for accurately reproducing earthquake waveforms. However, repeated offline iterations can cause cumulative damage to fragile specimens, while the continuously changing dynamic characteristics of nonlinear specimens reduce the control accuracy of OIC. To overcome these limitations, real-time iterative control (RIC) has been introduced and applied to eliminate the need for multiple iterations. To further improve the stability and accuracy of RIC, this study introduced RIC with online system matrix correction (RICSC) method, discussed the control performance of the RICSC method. The RICSC method evaluates the accuracy of the identified system matrix using the following indices: the coherence function (CF) weighted sum, the CF, and the autocorrelation power density spectrum (AS). Based on these evaluations, the system matrix is corrected via frame correction (FC) or frequency point (FP) correction algorithms, thereby enhancing waveform reproduction accuracy and control stability. The performance of the RICSC method was verified via numerical simulations and shaking table tests under 20 test conditions. The results show that the FP correction algorithm (RICSC-FP) achieves the fastest convergence of absolute error, and its reproduction accuracy is higher than those of the traditional RIC and FC (RICSC-FC) algorithms. Both numerical and experimental results demonstrate that the RICSC method provides higher reproduction accuracy than OIC after just one iteration.

The iterative hybrid testing (IHT) method, as one novel kinds of real-time hybrid testing (RTHT), provides a new technical support for disclosing the seismic performance of large-scale complex engineering structures. However, the IHT method adopts the methodology of direct whole time-history data exchange between the physical substructure (PS) and the numerical substructure (NS) based on the measured reaction forces of the PS, which results in the problems of slow iteration convergence speed and poor accuracy and stability. For solving these problems, one novel offline iterative hybrid testing method based on model identification and correction (IHT-MIC) is proposed in this paper. In the proposed IHT-MIC, the equivalent Maxwell model is used for precisely modelling the PS by parameter identification, and based on which the reaction force of the PS is corrected to improve the iteration convergence speed, accuracy, and stability. Firstly, the principle of the IHT-MIC is proposed. Furthermore, the numerical simulations and experimental tests are presented for validating the effectiveness and accuracy of the proposed method. It is shown from the numerical and experimental results that the least square method can accurately identify the parameters of Maxwell model, and the Maxwell model can effectively correct the reaction forces of the PS, which indicates that the accuracy of the IHT-MIC is greatly improved. Furthermore, compared with the traditional IHT, the IHT-MIC significantly improves the iteration convergence speed, reduces the oscillation amplitude during the iteration process. The proposed method may have broad application prospects in the fields of engineering structures with velocity-dependent energy dissipators.

One favorable solution to the issue of hunting instability of high-speed trains is to install hunting dampers. However, the nonlinearity of dampers and their interaction with a train present significant challenges in accurately analyzing the dynamic behaviors of both dampers and trains. To address these challenges, we present and investigate a real-time hybrid simulation (RTHS) for hunting dampers of high-speed trains and propose an improved two-stage adaptive time-delay compensation method to resolve its demanding delay issue. This innovative approach combines a numerical train model with a full-scale physical hunting damper, providing a versatile method for simulating and analyzing various dynamic behaviors. The train model incorporates 17 degrees of freedom and accounts for the nonlinear wheel-rail contact relationship to more faithfully represent the dynamic response of the train. A virtual RTHS platform with a loading system model has been developed. Both numerical simulations on this platform and real tests are conducted using the RTHS approach. Results demonstrate that time delays can reduce the hunting stability of a high-speed train, and the improved two-stage adaptive time-delay compensation method outperforms other comparative methods. This research reveals the feasibility and efficacy of the RTHS method for hunting dampers of high-speed trains.

Artificial intelligence technology is receiving more and more attention in structural health monitoring. Fatigue crack detection in steel box girders in long-span bridges is an important and challenging task. This paper presents a semantic segmentation network model for this task based on DeepLabv3+, ResNet50, and active learning. Specifically, the classification network ResNet50 is re-tuned using the crack image dataset. Secondly, with the re-tuned ResNet50 as the backbone network, a crack semantic segmentation network was constructed based on DeepLabv3+, which was trained with the assistance of active learning. Finally, optimization for the probability threshold of the pixel category was performed to improve the pixel-level detection accuracy. Tests show that, compared with the crack detection network based on conventional ResNet50, this model can improve MIoU from 0.6181 to 0.7241.

In order to effectively solve the dynamic delay problem of the servo-hydraulic actuator, simplify the design of the compensator, and improve the robustness of the compensation, an unscented Kalman filter-based two-stage adaptive compensation (UKF-TAC) method is proposed for real-time hybrid simulation (RTHS) in this study. Theoretical analysis and numerical simulations are conducted to verify the performance of the proposed UKF-TAC method. The research results show that the proposed UKF-TAC method can significantly simplify the design of the compensator, effectively improve the compensation accuracy, and has the robustness to adapt to different partitioning cases and resist the interference of uncertain factors.

Serviceability issues associated with structural lateral vibration are observed frequently, where human-structure interaction (HSI) plays a crucial role. Inverted pendulum (IP) models have attracted much attention from researchers due to their ability to naturally present human mechanical behaviors and significant advantages in studying the mechanisms of HSI. This paper investigates the behaviors of a 3D bipedal spring-loaded inverted pendulum (BSLIP) model while walking on laterally vibrating surfaces. First, we adopt feedback control strategies for the 3D BSLIP human walking model to achieve stable walking. Then, we investigate phase drift, phase pulling, and synchronization behaviors of the human body using the 3D BSLIP. The results indicate that the equivalent damping and mass coefficients of the 3D BSLIP basically agree with the available experimental results from the literature. Compared to the 3D IP model with rigid legs, the equivalent coefficients obtained from the 3D BSLIP exhibit similar ranges and trends as the control parameter increases. Furthermore, the 3D BSLIP and 3D IP models successfully replicate phase pulling and synchronization phenomena. The synchronization phase angles fall within the range of 102.9 degrees-228.9 degrees for the 3D IP and 209 degrees-349 degrees for the 3,D BSLIP model, consistent with the experimental results reported in the existing literature.

A fluid-structure interaction approach is proposed in this paper based on Non-Ordinary State-Based Peridynamics (NOSB-PD) and Updated Lagrangian Particle Hydrodynamics (ULPH) to simulate the fluid-structure interaction problem with large geometric deformation and material failure and solve the fluid-structure interaction problem of Newtonian fluid. In the coupled framework, the NOSB-PD theory describes the deformation and fracture of the solid material structure. ULPH is applied to describe the flow of Newtonian fluids due to its advantages in computational accuracy. The framework utilizes the advantages of NOSB-PD theory for solving discontinuous problems and ULPH theory for solving fluid problems, with good computational stability and robustness. A fluidstructure coupling algorithm using pressure as the transmission medium is established to deal with the fluidstructure interface. The dynamic model of solid structure and the PD-ULPH fluid-structure interaction model involving large deformation are verified by numerical simulations. The results agree with the analytical solution, the available experimental data, and other numerical results. Thus, the accuracy and effectiveness of the proposed method in solving the fluid-structure interaction problem are demonstrated. The fluid-structure interaction model based on ULPH and NOSB-PD established in this paper provides a new idea for the numerical solution of fluidstructure interaction and a promising approach for engineering design and experimental prediction.

Heat conduction is quite common in natural, industrial, and military applications. In this work, the updated Lagrangian particle hydrodynamics (ULPH) theory, is utilized and applied to solve heat conduction problems. Since heat conduction is a second-order problem, the high-order ULPH theory is employed to establish the governing equations of heat conduction in ULPH, which is then validated using various numerical simulations. In this work, numerical simulations have been carried out to solve both static heat conduction problems and dynamic heat convection problems. The results show good accuracy and capability of the ULPH heat conduction model, suggesting promising prospects of the ULPH theory in multiphysics problems. The findings of this paper suggest that ULPH is effective in addressing convective heat transfer problems.

For real-time dynamic substructure testing (RTDST), the influence of the inertia force of fluid specimens on the stability and accuracy of the integration algorithms has never been investigated. Therefore, this study proposes to investigate the stability and accuracy of the central difference method (CDM) for RTDST considering the specimen mass participation coefficient. First, the theory of the CDM for RTDST is presented. Next, the stability and accuracy of the CDM for RTDST considering the specimen mass participation coefficient are investigated. Finally, numerical simulations and experimental tests are conducted for verifying the effectiveness of the method. The study indicates that the stability of the algorithm is affected by the mass participation coefficient of the specimen, and the stability limit first increases and then decreases as the mass participation coefficient increases. In most cases, the mass participation coefficient will increase the stability limit of the algorithm, but in specific circumstances, the algorithm may lose its stability. The stability and accuracy of the CDM considering the mass participation coefficient are verified by numerical simulations and experimental tests on a three-story frame structure with a tuned liquid damper.

Natural convection is a heat transfer mechanism driven by temperature or density differences, leading to fluid motion without external influence. It occurs in various natural and engineering phenomena, influencing heat transfer, climate, and fluid mixing in industrial processes. This work aims to use the Updated Lagrangian Particle Hydrodynamics (ULPH) theory to address natural convection problems. The Navier-Stokes equation is discretized using second-order nonlocal differential operators, allowing a direct solution of the Laplace operator for temperature in the energy equation. Various numerical simulations, including cases such as natural convection in square cavities and two concentric cylinders, were conducted to validate the reliability of the model. The results demonstrate that the proposed model exhibits excellent accuracy and performance, providing a promising and effective numerical approach for natural convection problems.

Real-time hybrid simulation (RTHS) is a widely applied test method in structural engineering, which is developed from pseudo-dynamic test. Much of the past work has been centered on one-dimensional RTHS using a single hydraulic actuator. When the complexity of the problem demands to increase the number of degrees of freedom to be enforced on the boundary conditions, more than one hydraulic actuator must be used. Multiple-actuator or multi-axial RTHS (maRTHS) requires that more than one hydraulic actuator exerts the required motion on experimental substructures demanding the implementation of multiple-input multiple-output (MIMO) control strategies. A new maRTHS benchmark control problem has been developed, focusing on a frame subjected to seismic load at the base, substantially transforming and intensifying the complexity of the problem. The time delay generated by the dynamic characteristics of the loading system and the transmission process as well as the high coupling between the hydraulic actuators and the nonlinear kinematics escalates the complexity of the actuator control tracking. A sliding mode adaptive delay compensation method suitable for maRTHS is proposed, which utilizes a MIMO sliding mode method to reduce the coupling effects of actuators and the adaptive compensation method to compensate the residual delay. The effectiveness of the method is verified by numerical simulating different working conditions in the Benchmark Problem Platform.