Abstract:The advent of parametric design has resulted in a marked increase in the complexity of building. Unfortunately, traditional construction methods make it difficult to meet the needs. Therefore, construction robots have become a pivotal production tool in this context. Since the arm span of a single robot usually does not exceed 3 meters, it is not competent for producing large-scale building components. Accordingly, the extension of the robot,s working range is often achieved by external axes. Nevertheless, the coupling control of external axes and robots and their kinematic solution have become key challenges. The primary technical difficulties include customized construction robots, automatic solutions for external axes, fixed axis joints, and specific motion mode control. This paper proposes solutions to these difficulties, introduces the relevant basic concepts and algorithms in detail, and encapsulates these robotics principles and algorithm processes into the Grasshopper plug-in commonly used by architects to form the FURobot software platform. This platform effectively solves the above problems, lowers the threshold for architects, and improves production efficiency. The effectiveness of the algorithm and software in this paper is verified through simulation experiments.

Abstract:Dimensional quality inspection is a necessary step before delivering finished residences. However, traditional manual inspection methods are time-consuming and labor-intensive. As automated dimensional quality inspection using terrestrial laser scanners receives more attention, automated multi-view point cloud registration of indoor scenes becomes more important. Due to the fact that posting targets indoors is inefficient and a large number of repetitive structures fill the indoor scenes of finished residence, it is not suitable to rely solely on natural geometric primitives or top views for target-less registration. In this paper, a deep learning-based automated multi-view point cloud registration method for indoor scenes is proposed. Firstly, the PointAF neural network is used to semantically segment the scanned point cloud data. Then instance segmentation is performed to obtain point cloud instances with different structures. Next, pairwise registration is performed to compute the transformation parameters using door instances. False matches are then removed using an evaluation function based on overlapping confidence and conflict constraints. Finally, multi-view registration is achieved using a spanning tree based sequential registration method. In the validation and comparison experiments, a total of 21 stations of scanned point cloud data from two sets of finished residences are utilized to demonstrate the effectiveness and accuracy of the proposed method.

Abstract:As a typical labor-intensive sector, the construction industry heavily relies on human workers. However, the current construction industry has to confront challenging issues of labor shortages and safety management. Using construction robots can effectively solve these problems and increase automation in project execution and management. Recent studies have reported that future intelligent construction methods will rely on long-term highly cooperative production models involving human-robot collaboration. This paper systematically reviews the foundational technologies and research frontiers of construction robotics, traces the developmental trajectory of next-generation intelligent construction robots, and identifies four typical human-robot collaboration modes through analysis of construction site characteristics: operator-controlled mode emphasizing human-led real-time interaction, commander-execution mode achieving automated execution of high-risk tasks through remote instructions, collaborative assistant mode combining machine efficiency with human flexibility, and human augmentation mode enhancing worker capabilities through exoskeleton robotics. The study further highlights current technical challenges including insufficient environmental adaptability, communication instability, and cross-platform collaboration difficulties, while suggesting priority research directions for future development in this field.

Abstract:To address the challenge of automated detection of void of the steel-concrete structures interfaces, this paper designs a magnetic wall-climbing robot incorporating image and acoustic feature recognition. First, we introduce the robot’s chassis, magnetic suction device, power system, drive system, and mapping and sound modules. Next, we discuss the robot’s hardware control system and detemine the feasibility of using Neodymium-iron-boron permanent magnet for adsorption force through force analysis and experimental testing. Finally, the composition and functions of the image and acoustic feature recognition software part are detailed. Among them, the image capturing part adopts the image transmission solution based on the Orange Pie platform. The acoustic pattern recognition module consists of front-end, middle-end and back-end architecture: the front-end carries percussion and recording devices for excitation and collection of acoustic patterns; the middle-end of the acoustic pattern recognition WeChat mini program is developed to achieve acoustic pattern noise removal and effective feature extraction; the back-end, through the cooperation of Tencent Cloud and the WeChat mini program, recognizes acoustic pattern data and returns the results to the WeChat mini program. The magnetic wall-climbing robot incorporating image and acoustic feature recognition designed in this paper can achieve the collaborative acquisition and analysis of image and acoustic patterns, providing an effective solution for the automated inspection of steel-concrete and other structural interfaces for debonding.

Abstract:The study aims to address the issues of low efficiency, high cost, and safety hazards associated with manual inspection of building facilities. To address these issues, the study proposes a virtual inspection system based on robotic process automation (RPA) technology. First, a dynamic digital twin building model and an update algorithm are constructed based on BIM data, forming a real-time mapping relationship with the on-site facility operation status. Next, a multi-modal deep learning-based device defect detection network is designed to achieve automatic high-precision defect detection. Finally, the heterogeneous system integration and the application of intelligent scheduling algorithms are realized based on the software robotics technology architecture, and an integrated software robotics inspection system is developed. Preliminary verification was carried out in experimental scenarios. The results show that the virtual inspection robot system based on the software robotics technology architecture has: the facility defect detection accuracy improved to over 97%, surpassing single-modal detection methods; the operation efficiency is increased by an average of more than 62.3% compared to traditional methods; the maintenance manpower demand is reduced to 60%-80%, exemplifying its substantial engineering application value.

Abstract:Laying of secondary cables is an important step in the secondary installation construction process of power transformer projects. Presently, the installation of secondary cables is predominantly executed manually, lacking effective mechanized construction means. Consequently, there are problems such as large workload, complex processes, low efficiency, high labor demand and high cost. Based on the application of cable-pulling robot in the laying of secondary cables, aiming at the localization problem of four-wheel cable-pulling robot during cable laying, this paper proposes a localization scheme of correcting inertial navigation posture by observing an ArUco marker fixed on the wall of the cable trench with a camera. This method solves the problem that localization methods based on vision and laser sensors and GPS-RTK cannot achieve high precision localization of cable-pulling robot in cable trench environment. The method is to identify the ArUco markers pre-arranged on the wall of cable trench during the movement of a four-wheel cable-pulling robot. It will select specific frames based on its pose in the camera plane. The pose information of the inertial navigation is modified by recognizing ArUco markers to realize the pose correction of four-wheel cable-pulling robot. The experimental results show that the method can enable the four-wheel cable-pulling robot to achieve real-time and accurate localization in the cable trenches. This further enhances the intelligence of the secondary cable laying process in power transformer substations, and enhances construction efficiency and quality.

Abstract:With the continuous development of urban rail transit, the demand and quantity of shield tunnel construction are constantly increasing. Backfill grouting behind the shield tunnel lining is a crucial technology for controlling engineering issues such as ground disturbance and segment misalignment, which is vital for ensuring the safety of shield construction and surface buildings. In order to achieve automation and intelligence in backfill grouting detection, and to address the low efficiency of traditional Ground Penetrating Radar (GPR) manual detection, a Loaded-to-Frame (LTF) equipment capable of rapid automated GPR detection of grouting quality is proposed. The hardware composition, operating mode, and main parameters of the LTF equipment are described in detail. A series of model tests conducted under various conditions yielded over 600 000 high-quality labeled A-scan data. Based on both A-scan and B-scan data types and training strategies, intelligent models with excellent performance for backfill grouting thickness recognition are developed. An intelligent detection method for backfill grouting based on a “cloud-edge-end” architecture is proposed, and the GPR-AI Master platform, based on partial “cloud-edge-end” architecture, is developed to achieve cloud deployment and rapid application of the artificial intelligence model. A dynamic feedback mechanism based on the LTF equipment and intelligent analysis results is proposed, realizing comprehensive monitoring throughout the tunnel excavation process. The application is derived from 16 distinct shield tunnel projects domestically and internationally validate the effectiveness of the intelligent detection method, providing valuable references for the secure and intelligent construction of shield tunnels.

Abstract:The structural plane of surrounding rock is one of the key geological factors affecting the efficiency and safety of TBM excavation. Developing a rapid, precise, and adaptable method for identifying the structural plane of surrounding rock in TBM tunnels is of great significance. This article proposes a method for identifying rock structure planes based on multi camera vision and image recognition technology. Specifically, based on the equipment using binocular cameras, color and depth images of large exposed surrounding rocks are captured at fixed positions. The depth images are corrected to overcome image distortion issues based on positional parameters such as the position and shooting angle of the binocular camera. Furthermore, the Fine Boundary Description (CED) method was adopted to achieve precise identification of the structural planes of the surrounding rock. This approach is founded on traditional convolutional neural networks and adds a dual path of forward propagation and backward refinement of image data. In the backward refinement path, it continuously strengthens the capture of local boundaries in the image, captures the differences between structural planes and conventional surrounding rock pixels in the image, and then characterizes the boundaries of surrounding rock structural planes. Based on the TBM construction tunnel of Qingdao Metro Line 6, 427 sets of color and depth images of the surrounding rock were collected on site. By comparing the model recognition with the actual morphology of cracks, this method was further validated.

Abstract:In light of the prevalent diseases of tunnel portals built in the harsh environment of the plateau region and the problems of low efficiency and high risk associated with traditional manual disease detection methods, a novel disease detection method for tunnel portals in the plateau region based on Unmanned Aerial Vehicle (UAV) image and deep learning was proposed. Firstly, an UAV was used to collect the disease images of a tunnel portal in the plateau region of Xinjiang, and a multi-disease semantic segmentation dataset was constructed. Then, based on DeeplabV3+, an improved model TP-DeeplabV3+ was proposed, which used MobileNetV2 as the backbone feature extraction network to reduce model parameters; Used Focal Loss as the loss function to solve the category imbalance problem in disease images; Used the CA attention mechanism to improve the segmentation performance; and proposed the disease quantification method. Experiment results show that TP-DeeplabV3+ attains 88.37% and 94.93% of mIoU and mPA on the test set, respectively. Furthermore, the model volume is reduced by 88.83%. The absolute error of the proposed disease quantification method for disease coverage rate is less than 0.3%, and the relative error is maintained below 7.31%. Compared with the traditional manual method, the proposed method facilitates the intelligent detection of tunnel portal safely and accurately in plateau region.

Abstract:To mitigate the safety hazards posed by the frequent detachment of facade tiles, this study summarized the causes of these defects, identifying hollowing defects as precursors to exterior wall tile detachment. Using an Unmanned Aerial Vehicle (UAV) equipped with infrared thermal imaging camera, the study conducted laboratory tests for hollowing detection. The optimal observation attitude of the UAV was investigated. The impact of defect characteristic parameters on identification accuracy and the effect of UAV rotor operation on the temperature of external walls were evaluated. Additionally, a temperature difference threshold was proposed for the identification of hollowing in exterior wall facade tiles. The study indicated that optimal observation occurs when the UAV is 2 to 3 meters from the external wall, with a vertical angle of -30° to 30° and a horizontal angle of -15° to 15°. The drone rotors increase the cooling rate of external walls by 10%. Recognition improves with hollowing of larger sizes, shallower depths, and greater thicknesses. Hollowing defects in black and red tiles exhibited higher temperatures, while those in yellowish tiles exhibited lower temperatures. Consequently, an outdoor test was conducted to verify the efficacy of the proposed detection method by comparing it with visible light image recognition, which provides a novel threshold for the expeditious identification of hollowing defects in facade tiles.

Abstract:Three-dimensional printed concrete technology has the advantages of flexible, reduced carbon emissions, expedited construction, and the capacity for formless design. However, the interface bonding problem may cause the printing layer to be not tightly bonded, affecting the strength. Overlapping print paths reduce defects and enhance interlayer bonding, increasing compressive strength. For steel fiber reinforced cement-based materials, the distribution direction of steel fiber is easily affected by the printing path, and the research on the compressive strength of 3D-printed steel fiber reinforced cement-based materials under overlapping paths is insufficient. Based on 3D-printed technology, this paper explored the compressive strength by using parallel path and spiral overlapping path printing methods and varying the angle between the load and path direction and the pitch angle to fabricate steel fiber-reinforced cementitious cubic specimens. The following conclusions were drawn: In the X-Y plane, the compressive strength of parallel paths first increased and then decreased with the change in the angle between the load direction and the path direction, but it was less than that of cast-in-place specimens; In the X-Y plane, when the distribution direction of fibers is parallel to the loading direction, the compressive strength in the X direction is the highest (X direction), and when the distribution direction of fibers is perpendicular to the loading direction, the compressive strength is the lowest (Y direction); The compressive strength in the X, Y and Z directions was significantly higher in the 30° and 90° pitch angle paths compared to parallel paths; Compared to parallel structure printing, the bouligand structure reduced mechanical anisotropy. The Bouligand structure printing method has been demonstrated to enhance the compressive strength of components.

Abstract:This paper proposed a processing technology for removing residual inner corners, as well as a highly integrated wood processing device based on the genetic algorithm, solving the problem of residual inner corners in the milling process of mortise-tenon joints. Integrating visual programming technology, standard programs were developed for tool adaptation; existing wood processing techniques were integrated with robotic arm motion systems to create a collaborative wood processing system. An experiment was conducted on the mortise structures within wooden assemblies. Research findings indicate that the genetic algorithm-based technology for removing internal corner residues can effectively eliminate internal corners, thereby resolving the issue of arc residues in milling technology. The proposed collaborative wood processing system, featuring robotic arms, has the capacity to efficiently and precisely complete construction tasks. This system demonstrates the feasibility and applicability of digital construction technology through practical construction experiments.

Abstract:This paper aims to investigate the mesoscopic fracture mechanisms of sandstone under triaxial compression. We conducted triaxial compression tests of sandstone and integrated the Grain-Based Model (GBM) and moment tensor theory to simulate the development characteristics of internal cracks, acoustic emission events, and fracture strength in sandstone. The derivation process of microcracks and the characteristics of acoustic emission response in sandstone are derived, and the spatiotemporal evolution process of cracks and acoustic emission events at the micro scale is comprehensively analyzed. The results indicate that microcracks are randomly distributed in the sandstone sample during the initiation stage of fracture under triaxial compression, and the displacement field shows a horizontally layered distribution. As the loading increases, the number of microcracks increases, penetrates gradually into two macroscopic cracks, and shifts the displacement field to a significant heterogeneity pattern. The cracks in the incubation period show slow development, and cracks grow at extremely high nonlinear rates. The order of crack development follows a sequence of intergranular tensile cracks, intergranular shear cracks, intragranular tensile cracks, and intragranular shear cracks. The simulation analysis revealed that the majority of internal cracks triaxial compression (83.2%) are tensile cracks resulting from tensile failure. The number of acoustic emission events in the samples has a negative exponential correlation with the number of cracks, and a single acoustic emission event generates 75.60% of microcracks. Finally, the analysis of acoustic emission events, the number of microcracks, and the fracture strength indicates that the three factors approximately follow a normal distribution.

Abstract:Defects such as cracks and holes in rocks can easily lead to local damage, which has adverse effects on construction safety and maintenance. The rock mechanics testing system was used to carry out uniaxial compression tests on tuff with double-hole holes of different rock bridge lengths. The acoustic emission （AE）monitoring system was used to monitor the whole process. The AE characteristics of rock deformation and failure process were studied. Based on AE energy, ring count, RA / AF value, b value and other characteristic parameters, the influence of different rock bridge lengths on rock failure was analyzed, and the precursor information of damage evolution characteristics was explored. The results show that the AE parameters change periodically with time, and there are obvious abnormal response characteristics before rock failure. AE energy changes from group earthquake type to solitary earthquake type with the increase of rock bridge length. AE ringing count has experienced quiet period, active period and sudden increase area. AE RA/AF value is sensitive to local small crack propagation. AE b value has experienced rising period, fluctuation period and falling period with time, and the overall trend is decreasing. Each parameter of AE has the precursor of rock failure. The AE cumulative energy, AE cumulative ring count, AE cumulative RA/AF value sudden increase point and the lowest point of AE b value are taken as the “critical failure precursor point” D. The early warning time series follows: AE cumulative RA/AF value > AE cumulative ring count > AE cumulative energy > AE b value.

Abstract:During the service lifetime of gravity dams, seepage flow could adversely affect the dam stability and its stress distribution. In investigating the reliability of gravity dams, it holds paramount importance to account for the seepage effects. In this study, an efficient reliability analysis is conducted to evaluate the stability and stress distribution of gravity dams incorporating the influence of seepage effects. This analysis involves integrating the response surface method and random finite element approach. For a hydropower station project, the key uncertain parameters affecting the stability and stress distribution of gravity dams are identified through a parametric sensitivity analysis. Using the response surface method, the performance function for the anti-sliding stability safety factor of gravity dams under the seepage effects is established, and the failure probability considering multiple failure modes is calculated. Meanwhile, the simulated results are compared with those obtained without considering the seepage effects. The influence of key uncertainty parameters on the failure probability of gravity dam is quantitatively analyzed by the probabilistic failure analysis. These findings show that accounting for seepage effects leads to higher failure probabilities, indicating that neglecting these effects may underestimate the likelihood of dam failure. In comparison with the three failure modes, the heel cracking of the gravity dam and sliding instability along dam-foundation interface are most likely to occur, followed by the dam toe cracking. The results could provide a theoretical foundation and technical guide for evaluating the reliability of practical dam projects.

Abstract:During the shield tunnel construction in composite strata, there are complex interactions between the shield machine and segment due to spatial posture deflection. Causing multidimensional deformation response in various parts of the segment, resulting in extreme floating displacement and segment dislocation. In order to investigate the structural response and derivative mechanisms, this study established a three-dimensional numerical calculation model under multi-source load coupling. Finally, the spatial deformation distribution and evolution characteristics of segments were calculated and analyzed by field 3D LiDAR testing. The results indicate that under the spatial deflection, 64% of the long-axis deformation of the segment occurs before detaching from the shield tail completely, and the long axis deflection is opposite to the circumferential rotation of the shield shell. In addition, 50% of the average increase in longitudinal rotation angle of the segment occurs after the segment detaching from the shield tail completely, while 44% of the increase in circumferential rotation angle occurs during the gradual detachment from the shield tail. During the entire process, the continuous development of circumferential displacement of the segments is mainly caused by the circumferential rotation of the shield shell, and after the segments completely detaching from the shield tail, their radial displacement development and shape changes are mainly affected by their own circumferential displacement changes. The lateral rotation of the shield shell would promote the longitudinal displacement of the segment in the same direction. After detaching from the shield tail, the further development of its longitudinal displacement is mainly affected by the longitudinal deflection. 3D LiDAR point cloud measurement could accurately and quantitatively evaluate the segment deformation.

Abstract:Under the continuous influence of weathering and self-weight, there are a large number of cracks in the wall and roof of Beishan Cave 168 in Dazu Rock Carvings. These cracks lead to the deterioration of the stability of the surrounding rock at the top of the cave and the risk of instability and collapse. In order to effectively reinforce the broken surrounding rock of the roof of the flat-top grotto, this paper adopts a roof reinforcement method of suspended anchor in accordance with the geological conditions of the site. First, the main reasons for the cracking of the grotto roof are analyzed according to the distribution pattern of the roof cracks. Then, the anchorage length of the bolt is calculated by using the new Austrian method considering the most unfavorable surrounding rock stress. Finally, FLAC3D is used to analyze the displacement and stress changes of the grotto roof under rainfall conditions. The results show that the displacement of the roof in all directions is not more than 1 mm under the condition of suspended anchor reinforcement; the stress at the entrance of the grotto and near the inside of the grotto is relatively concentrated; the maximum tensile stress is less than the tensile strength of sandstone, and the roof surrounding rock is in a stable state; the average axial force of the bolt anchorage section is 31 kN. From the field monitoring data, it could be seen that the suspended anchor reinforcement reduces the fluctuation value of cracks. In summary, the grotto remains stable under the condition of suspended anchor reinforcement.

Abstract:The loading condition on the wind turbine during operation is complex. Therefore, based on a wind turbine foundation reinforcement project in Weihai, a systematic monitoring method is proposed to evaluate the performance improvement effect of the reinforced foundation in combination with the field environment. From the construction stage to the operation stage, the tower strain, welding stud strain, and anchor cable axial force of the reinforced foundation are collected to study the stress response of the wind turbine reinforced foundation under different working conditions, conduct correlation analysis, and to explore the performance improvement effect and load transfer mechanism after foundation reinforcement. The results show that the stress response of each component in the reinforcement area has trend similarity and amplitude difference, and the stress improvement effect is obvious with a large safety margin. The reinforcement method changes the stress boundary of the structure by using outsourcing concrete and welding studs, increases the restraint stiffness of the bottom tower, redistributes the upper transferred load, shares the transferred shear force, and ensures the common deformation of the tower and concrete.The systematic monitoring and evaluation method based on this reinforcement scheme can effectively and timely assess the stress state of each component of the reinforcement system and ensure the safety of the subsequent wind turbine operation. The reinforcement scheme improves the stress state of the foundation, rock bolt and flange, and the overall mechanical performance of the foundation is guaranteed.

Abstract:The large-diameter pile-enhanced gravity-type anchorage has high anti-sliding capability through lateral load-resistance of the large-diameter piles, and thus has decreased volume and self-weight. As a result, the amount of excavation can be reduced and disturbance to the original ground can be reduced to a minimum. In addition, the piles can help resist the movement of the anchorage under geohazards. However, the combined anti-sliding mechanisms of the rock-socketed piles with the friction between anchorage foundation and ground are unclear, and a practical design method is desired. In this paper, the three-dimensional elasto-plastic finite element method is employed to study the lateral load-carrying capacity of pile-enhanced gravity-type anchorage. To do so, lateral resistance of rock-socketed piles with four different lengths is examined first, and then the coupled anti-sliding capacity of the pile with the foundation friction is investigated for the single-pile-enhanced and the pile-group enhanced anchorage on mediumly weathered sandstone. The cap plasticity model in geomechanics considering volumetric yield of high porosity rocks and the Coulomb contact-friction elements are used in the analysis. The reaction of the rock along the pile depth and the friction between the anchorage and the subsurface are analyzed. The influence of the pile length and layouts on load-carrying capability of the anchorage is examined. It is shown that the piles can take up approximately 70%-80% of the total anti-sliding force, while the actual mobilized friction reaches only 2/3 of the control value. The anti-sliding stability factor of the anchorage is able to meet the requirement of the design code. With well-designed piles, the maximum horizontal displacement of the anchorage can be controlled within 1/10 000 of the main span length. The failure of the pile-enhanced anchorage is caused by the yielding and collapse of the rock around the base-expanded piles on the rear of the anchorage. Compared to the stepped-bottom gravity anchorage, the pile-enhanced gravity anchorage could reduce the self-weight by more than 20%, and is beneficial for green construction of long-span suspension bridges.

Abstract:The method of bearing forced displacement is a control method used in the construction of steel girder bridges, which can largely adjust the position and angle of the bridge closure joint. However, there is currently no detailed theoretical study on the application of this method to the structural system before and after the transformation. In view of this , this paper takes a three-span continuous beam bridge under uniform load as the research object and, based on the Euler-Bernoulli beam bending differential equation, uses the integration method to solve the closed-form solution of the three-span continuous beam bridge under uniform load by using the bearing forced displacement method in two different conditions: the bridge constructed and closed step-by-step and the bridge constructed at one-time. The theoretical calculation results show that the obtained beam deflection functions under the two conditions are completely the same, indicating that under the elastic state, the three-span bridge with the bearing forced displacement method can achieve the ideal effect of one-step construction. Furthermore, this paper combines the practical application of the bearing forced displacement method in the construction of a three-span continuous steel truss bridge with the measured bridge deflection data and finite element calculation results before and after the application of the method, and the two are in good agreement, verifying the practical control effect and engineering application of the proposed method.

Abstract:There is a large amount of low-quality data in the monitoring data of bridge cable dynamic response. The existing data detection research focuses on obviously abnormal data with abnormal time-domain waveforms. However, there is chaotic data in frequency-domain characteristics with normal time-domain waveforms in the monitoring data, which can’t accurately reflect the dynamic characteristics of bridge cables. Aiming at this problem, the existing abnormal data detection is extended to data quality evaluation, and obvious abnormal data and frequency-domain chaotic data are detected at the same time. The data quality evaluation method of bridge cable dynamic response monitoring is established by using a convolutional neural network (CNN) and data frequency-domain features. The implementation process includes: the time-domain data sequence is transformed into a power spectral density function (PSDF) by fast Fourier transform (FFT); the Gramian angular field (GAF) method is used to visualize the PSDF sequence, and a CNN model is built to evaluate the data quality automatically. Taking the cable acceleration monitoring data of a cable-stayed bridge as an example, the proposed method is validated. The results show that compared with the time-domain sequence detection method, the PSDF sequence detection method can better distinguish normal and pseudo-normal data, and has a higher evaluation accuracy; the accuracy of the CNN model, established by using the monitoring data of two sensors, to evaluate the quality of all 26 sensor monitoring data is above 94%. In addition, the evaluation model, established by this method, is applied to the monitoring data quality evaluation of another similar bridge with an accuracy of 95%.

Abstract:Using the FE-SEA mixed method, this study establishes a coupled model of the track-cover-upper covered building to analyze the impact of subway car depot operation on vibration and indoor secondary structure noise in an upper covered building. The vibration and noise of the roof building and indoor secondary structure in different frequency domains are analyzed under subway vibrations. The mechanism underlying the generation of vibrations in overlying buildings is revealed, while also delving into the propagation patterns governing vibration and noise in such structures. Results show that the FE-SEA mixed method accurately predicts roof-building vibrations and indoor structural noise. Each floor,s vibration is affected by its natural frequency, with main-frequency vibrations located in the low-frequency band between 31.5 and 50 Hz. Vehicle-induced roof-building Z-vibration levels attenuate to their lowest point on the ninth floor before magnifying as floors increase; typical room secondary structure noise pressure mainly concentrates within the 20~80 Hz range, with A-levels decreasing then increasing as floors rise; application of a vibration isolation support effectively reduces natural frequencies while reducing higher-frequency responses from roof structures above this range. These findings provide a useful reference for predicting, reducing, or isolating subway-depot-related vibrations.

Abstract:Based on a triple-tower suspension bridge, the finite element model was established. Using nonlinear time-history analysis, the seismic responses of the suspension bridge under different stiffnesses of elastic cables between the tower and deck were calculated, and the influence of elastic cable on the seismic response of the suspension bridge was studied. The seismic response of the suspension bridge with the flexible central buckle was analyzed, and the result was compared with that without a central buckle. According to the seismic response characteristics, the elastic-plastic seismic mitigation device was taken as the central buckle. To investigate the influence of the elastic-plastic central buckle on the bridge,s seismic response, the seismic responses of the suspension bridge with different elastic-plastic central buckles were calculated. The seismic mitigation effectiveness of the long-span triple-tower bridge with different seismic mitigation systems was discussed. The results show that the elastic cables between the tower and deck are unfavorable to the seismic forces of the middle tower, the flexible central buckle is vulnerable to the suspension bridge under earthquake. The elastic-plastic device can be used as the suspension bridge central buckle. By installing the elastic-plastic central buckle, the longitudinal seismic displacement of the deck can be effectively controlled and the seismic forces of the tower can be improved. When the combination of elastic cables and the elastic-plastic central buckle was installed, the displacement of the suspension bridge is reduced more obviously, the adverse effect of the elastic cable on the middle tower can be mitigated. The seismic performance of the triple-tower suspension bridge can be effectively improved by the application of the elastic-plastic central buckle.

Abstract:Traditional bridges with isolation bearings have the problem of residual displacement of the isolator and the response of internal pier force during the impact of an strong earthquake or near-fault earthquake. This research suggests a variable-stiffness friction pendulum bearing based on a gravity-well surface, gaining inspiration from the facility for gravity-well surfaces in the science museum. Its surface is comprised of a gravity-well surface outside and a sphere inside. First, the theoretical derivation-based restoring force model in the horizontal shear direction is revealed. Second, a footprint variable stiffness friction pendulum bearing specimen is designed, constructed, and put through a cyclic shear test to further examine its mechanical and hysteresis characteristics. The friction material is a modified ultra-high molecular weight polyethylene with better compression resistance. In the end, numerical simulations are used to compare the dynamic properties of the gravity well friction pendulum bearing with the spherical bearing. The sliding surface of the variable stiffness double friction pendulum bearing is asymmetrical. The high local stress on the friction pad can be accommodated by the modified ultra-high molecular weight polyethylene (UHMWPE) friction material. The gravity-well friction pendulum bearing can also significantly reduce the internal force demand under the action of ground motion when compared to the conventional spherical double friction pendulum bearing, and it has the same superior self-reset performance as the small-radius spherical friction pendulum bearing.