To identify structural damage efficiently and accurately, a hierarchical identification method of structural damage based on structural dynamic characteristics and deep belief network is proposed by combining machine learning with intelligent algorithm, and the damage position and degree are identified in turn. In order to identify the damage location, a 6-element vector is established by using the first three vertical vibration frequencies of the structure and the third modal displacement of a single node, and the damage location is identified by using the 6-element vector as input parameters. To identify the damage degree, the first three natural frequencies and modal displacements of vertical vibration or the 6 nodes modal curvature differences are used as parameters to input the depth confidence network to identify the damage degree. A simple-supported beam is taken as a model to verify it. It is shown that the damage position recognition accuracy can reach 100% even if the noise level reaches 10%. When identifying the damage degree, the deep belief network based on six-node modal curvature difference has strong noise resistance. The maximum relative error of damage degree prediction is less than 5.08% and the mean square error is 0.4878 under the noise of 15%. Compared with BP neural network, the prediction ability of BP neural network is better than that of deep belief network when there is no noise. Under the same noise level, the prediction ability of depth belief network is obviously better than that of BP neural network, which shows that the hierarchical identification method of structural damage based on structural dynamic characteristics and deep belief networks has strong robustness and high accuracy of identification results.

In order to improve the structural damage identification effect based on vibration signal, a structural damage identification method based on the combination of correlation function and convolutional neural network is proposed. Taking a railway steel girder bridge structure as an example, firstly, the signal-to-noise ratio of the vibration signal is improved by performing autocorrelation calculation on the vibration response of the structure, then the autocorrelation sample is used as the input of convolutional neural network, which can significantly improve the recognition accuracy. When the noise level in the vibration signal is higher, the improvement effect of the recognition accuracy of the autocorrelation sample as the convolutional neural network input is more obvious, and the autocorrelation operation has stronger noise immunity than that of the fast Fourier transform. The cross-correlation function is used to fuse the data of the multi-sensors arranged on the structure, then the fused signal is used as the input of the convolutional neural network. Under the premise of effective fusion of the data characteristics of the two sensors, the cross-correlation can double the dimension of the data set and reduce the number of parameters of the network operation, thereby reducing the time and improving the training efficiency, and the cross-correlation sample as the network input also has high recognition accuracy and strong noise immunity.

Due to the problem that the tuned mass damper (TMD) system is easy to be off-tuned when applied to light structures, which leads to the decline of vibration reduction effect, a new shape memory alloy semi-active TMD system is designed in this paper. The system uses steel cables to suspend the mass to bear all its weight. Large shape memory alloy bars with rectangular effective cross sections are used to provide different bending stiffness in the two directions of the TMD system in the horizontal plane. In order to study the semi-active performance of the system, a full-scale shape memory alloy TMD system was subjected to free vibration tests in this paper. By changing the working temperature of the shape memory alloy, the influence of temperature change on the frequency and damping ratio of the TMD system was studied. The test results show that by controlling the working temperature of the shape memory alloy from -40 ℃ to 80 ℃, the frequency of the TMD system shows an increasing trend with temperature increases, while the damping ratio shows a decreasing trend with the temperature increases. The results show that the new shape memory alloy semi-active TMD system is applied to controlled structures, and once the TMD is off-tuned, it can be re-tuned by changing the temperature of the shape memory alloy. Therefore, the new shape memory alloy TMD system designed in this paper has certain engineering application value and prospect for the study of light structure vibration reduction.

With the development of wind power resource advantageous areas gradually saturated, the focus of wind power development has shifts to low wind speed areas with relatively poor wind resource conditions. Distributed, high power, high tower and long blades have become the trend in the wind power industry. Based on the above, a new rectangular concrete filled steel tube bundle wind turbine tower is proposed. The tower is made of rectangular concrete filled steel tube bundles, which has the advantages of high strength, rigidity and energy consumption capacity. To study the wind vibration response characteristics of this tower structure, the Kaimal pulsating wind speed power spectrum was chosen and the wind load time curve was simulated using the harmonic synthesis method to carry out the dynamic time analysis. Wind vibration coefficients and equivalent static wind loads were calculated for the tower. The results show that the maximum displacement of the top of this new tower at rated wind speed is 911.84 mm, which corresponds to a horizontal displacement angle of 1/154 and meets the code requirements. The tower components are of good strength and have a large safety margin. The wind vibration coefficient obtained by the displacement-equivalent gust load factor method is lower. Under the equivalent static wind loads calculated by the inertial wind load method, the structural displacements and basal shear forces are basically the same as those obtained from the structural random vibration analysis.

To investigate the vibration comfort level of reinforced truss composite slabs applied in residential building floors, the vibration response of the integral connection reinforced truss composite slabs under human-induced excitation loads was studied through experiments. Three types of loading excitations, including single-person walking, three-person asynchronous walking, and three-person synchronous walking, were designed for experiments. For the single-person walking load experiment, three different walking paths including longitudinal, transverse, and diagonal were designed. The vibration response of the composite slabs under various human-induced excitations and walking paths was investigated. A refined finite element model of the composite slabs was established to analyze the influence of the protective layer thickness at the plate bottom, truss height, density ratio and modulus ratio of concrete to reinforcement on the natural frequency of vibration of the composite slabs. The results show that the peak acceleration under human-induced excitation increases with the layer height. The peak accelerations under different human-induced loading conditions decrease in the following order: three-person synchronous walking, three-person asynchronous walking, and single-person walking, and the peak acceleration under single-person walking condition is independent of the walking path. The natural frequency of the composite slabs decreases with the increase of the thickness of the protective layer at the plate bottom, and reaches the maximum when the truss height is 80 mm. The natural frequency is inversely proportional to the concrete-to-reinforcement density ratio, and is directly proportional to the concrete-to-reinforcement modulus ratio.

Resilience evaluation of infrastructure system provides an essential basis for the resilience enhancement and disaster mitigation of urban communities. This study presents a seismic resilience evaluation model for water supply network that integrates the hydraulic with water quality simulation. The seismic damage scenarios of water supply network are generated according to seismic fragility model of pipelines and the Monte Carlo simulation, and the post-earthquake recovery of pipeline damages is simulated by dynamic importance-based recovery sequence. The negative influence of earthquake hazard on water quality is investigated by the chlorine concentration reduction of water, which depends on the changes in water age and supply path caused by pipeline damages. The water supply of user nodes without quality deterioration after earthquakes is used as the water quality performance index of water supply network. The proposed evaluation model is implemented in two benchmark water supply network with different layouts. Application results show that the water losses of pipeline damages lead to water flow increases and greater chlorine concentration in its upstream pipelines, and lead to prolonged water supply path and smaller chlorine concentration in its downstream pipelines. The water quality resilience of water supply network tends to be lower than that of hydraulic services, and the relative difference between hydraulic and water quality resilience is affected by the layout and operating rules of water supply network. In the application case of water supply network, the relative difference of seismic resilience loss calculated by water quality and hydraulic ranges from 17% to 286%, and there is a large difference between hydraulic and water quality resilience of water supply network whose operating rules are complex and contain regulating tanks.

The seismic reliability of water supply networks refers to its capacity to satisfy water demands of customers in the presence of potential seismic events. Currently, the majority of seismic reliability assessments for water supply networks employ Monte Carlo simulations to generate numerous seismic damage samples for evaluation. However, this approach becomes highly demanding in terms of labor and time when assessing extensive and intricate networks. To address these challenges, the equivalent scenario method is proposed as a means to enhance computational efficiency. The proposed method involves the generation of posterior probabilities using seismic damage scenarios. Subsequently, these probabilities are employed to generate equivalent scenarios. Finally, the equivalent scenarios are utilized to determine both the node reliability index and the system reliability index. The simulation results obtained using the proposed algorithm are then compared with those obtained using the traditional Monte Carlo method.The results demonstrate the feasibility of generating equivalent scenarios based on posterior probabilities. Specifically, when evaluating the reliability of 100 equivalent scenarios at a seismic intensity of 8 degrees, a few nodes exhibit evaluation errors exceed 10%, while the evaluation errors for the remaining nodes at lower seismic intensities are below 5%. Additionally, the evaluation errors for small seismic intensities are all below 5%. Moreover, increasing the number of equivalent scenarios from 100 to 250 can further reduce the assessment error to less than 5%. Thus, the algorithm proposed in this paper ensures accurate results while enhancing computational efficiency.

A double shell space damping structure is introduced to reduce the vertical accelerations of the containment in the nuclear power plant. Based on the mechanical characteristics of the structure, a simplified three particle and three degree of freedom dynamic model is established, the structural response transfer functions are further given and the parameter analysis was conducted. The influence rules of the structural mass ratios, damping ratios and frequency ratios on the vertical response of the structure are clarified. The scale shaking table dynamic test of the double shell space damping structure is completed. The test results show that the double shell space damping structure can reduce the vertical accelerations of the inner containment, and the damping ratios are 12.23% ~ 27.84%. The theoretical calculation results are in good agreement with the experimental results. The double shell space damping structure can effectively reduce the vertical acceleration response of the containment in the nuclear power plant.

In this paper, the stilted buildings were taken as the research object, and according to the characteristics of unequal height embedded structure, three types of three-dimensional stilted frame structures were designed: non-isolation, base isolation and the second floor column bottom isolation (interlayer isolation). Then elastic response spectrum analysis and elastic-plastic dynamic time history analysis of analysis models were carried out to investigate the influence of different isolation bearing layout on the dynamic response, failure mode, probability of seismic collapse and other seismic performance of stilted frame structures. The results show that the application of seismic isolation technology to the stilted frame structure on slope can control the dynamic response of the structure and improve the safety margin of the whole structure, which provides a new way to improve its seismic performance. The setting of base isolation can improve the non-uniformity of structural stiffness distribution, reduce the difference of shear distribution between stilted columns and improve the safety reserve of the shortest columns. However, there are differences in the deformation of isolation bearings with different levels. Isolation bearings with different lateral stiffness should be arranged in the base isolation model. Compared with the base isolation, the interlayer isolation has better ability to control the structural damage, the deformation of the upper floor is more uniform, and the probability of seismic collapse is lower. However, in the interlayer isolation design, it should be considered to appropriately reduce the difference of lateral stiffness between stilted columns.

When the lifting platform works at heights in the outside field, river beach and other environments, the dynamic interaction between the soft soil and outriggers of lifting platform will change the dynamic characteristics of the lifting platform system. In this paper, three dynamic models of lifting platform, which are incorporated with three different inerter dynamic vibration absorber (I-DVA) systems defined as SIS, SPIS-1 and SPIS-2, are presented with the consideration of soil-structure interaction. The expression of the amplification factor and the displacement mean square value of the operating platform is derived under harmonic and random force excitation, respectively. The optimal stiffness ratios and damping ratios of the I-DVAs are obtained based on H_∞ and H₂ optimization criteria by genetic algorithm in terms of three different soil foundations. The vibration reduction performance of three I-DVA systems is evaluated under the conditions of their optimal design parameters. The numerical studies show that: SPIS-2 performs the most effective vibration reduction, which not only suppress the resonance amplitude of the lifting platform, but also widen the frequency bandwidth. The soil-structure interaction can reduce the amplification factor under harmonic excitation and the mean square value under random excitation of the operating platform. The soil-structure interaction influences the optimal design parameters of the inerter systems insignificantly under harmonic and random excitation. Therefore, some empirical formulations of the optimal parameters for I-DVAs are fitted in order to provide reference for the vibration reduction design of lifting platform.