Three-dimensional multifunctional intelligent toughness constraint system for long and large bridge and multi-objective optimization design method of three-dimensional multifunctional intelligent toughness constraint system

Abstract

The invention discloses a long and large bridge three-dimensional multifunctional intelligent toughness constraint system and a multi-objective optimization design method.The constraint system comprises a vertical three-dimensional constraint device, a transverse three-dimensional constraint device and a longitudinal three-dimensional constraint device which are arranged between a main beam and a bridge tower (pier), and the vertical constraint device and the transverse constraint device are both constraint devices with the self-recovery function; the longitudinal restraining device is a static limiting-dynamic damping combined restraining device with a self-recovery function; according to the multi-objective optimization design method, structure additional rigidity, additional damping and additional mass are taken as decision variables, structure toughness, service life and cost are taken as constraint objectives, a genetic algorithm is utilized to carry out multi-objective optimization and solve a Pareto frontier, and a weighted Euclidean distance method is adopted to determine optimal design parameters according to preset toughness, service life and cost weights. The method is suitable for parameter design of the long and large bridge three-dimensional multifunctional intelligent toughness constraint system, and comprehensive optimization of structural toughness, service life and cost is achieved.

Description

Technical Field

[0001] This invention belongs to the field of bridge engineering technology, and in particular relates to a three-dimensional multifunctional intelligent toughness constraint system for long bridges and its multi-objective optimization design method. Background Technology

[0002] Long-span bridges are crucial infrastructure projects for major transportation infrastructure projects such as land-island connectivity and regional intermodal transport, and are widely used in high-speed railways, highways, and urban transportation systems. With the continuous improvement of spanning capacity and functionality, structural systems are becoming more flexible, resulting in reduced overall stiffness, lower damping levels, and significant dynamic coupling effects, making them more sensitive to external loads. Traffic loads, strong wind excitation, and seismic forces can induce significant three-dimensional dynamic responses in key components such as the main girder, main cable, suspenders, towers, and supports. This can easily lead to increased vertical and lateral vibrations of the main girder, excessive vertical displacement, intensified longitudinal impact at the girder ends, and accelerated accumulation of fatigue damage in the suspenders, ultimately affecting the bridge's service safety and durability.

[0003] Existing bridge restraint systems mainly include fixed bearings, elastic restraints, friction energy dissipation devices, viscous dampers, buckling-restrained braces, and central buckles, whose primary function is to restrain or dissipate energy in a single direction. However, these traditional restraint devices generally have the following shortcomings: (1) Single function and lack of synergy. Most constraint devices only provide limiting or energy dissipation in one direction and cannot simultaneously take into account the three-dimensional coupling response of vertical, horizontal and longitudinal directions. (2) Lacking self-recovery capability, it is easy to generate residual deformation. After strong earthquake or extreme load, the traditional device itself and the connected components may undergo irreversible deformation, requiring manual reset or replacement, which is not conducive to the rapid recovery of the bridge's service capability. (3) The damping parameters are not adjustable and it is difficult to adapt to the time-varying characteristics of the load. Wind load, traffic load and seismic action have significant uncertainties and time variability. Traditional damping devices cannot achieve real-time adjustment of damping force. (4) The design requirements of resilience orientation cannot be met. Current designs often focus on strength or displacement control, ignoring the bridge’s ability to maintain function and recover quickly after extreme events, i.e., the structural resilience is insufficient.

[0004] In recent years, technologies such as intelligent dampers, semi-active control devices, and novel self-resetting components have been continuously developed, providing new technical pathways for improving bridge toughness. However, the application of these technologies in long-span bridges is still in the exploratory stage, lacking a systematic control system for the three-dimensional dynamic coupling characteristics. At the same time, intelligent constraint devices have numerous parameters, including stiffness, damping, mass, restoring force, and trigger threshold, and there is a clear multi-objective coupling relationship between them and bridge toughness, fatigue life, and engineering cost. Traditional single-variable or empirical parameter design methods are no longer sufficient to meet engineering requirements. Summary of the Invention

[0005] Purpose of the invention: The purpose of this invention is to provide a three-dimensional multifunctional intelligent toughness constraint system for long bridges, which can improve the dynamic performance of bridges under multiple loads, extend fatigue life, enable rapid post-disaster recovery, and optimize the cost throughout the entire life cycle.

[0006] The second objective of this invention is to provide a multi-objective optimization design method for a three-dimensional multifunctional intelligent toughness constraint system for long bridges.

[0007] Technical Solution: To achieve the above objectives, the three-dimensional multifunctional intelligent toughness constraint system of the present invention includes one or more of the following: a main beam and bridge tower constraint subsystem disposed between the main beam and the bridge tower; a main cable and main beam constraint subsystem disposed between the main cable and the main beam; and a main cable and bridge tower constraint subsystem disposed between the cable saddle structure and the bridge tower. The main beam and bridge tower constraint subsystem is used to regulate the relative movement of the main beam relative to the bridge tower in three dimensions, and includes a vertical constraint device, a lateral constraint device, and a longitudinal constraint device. The main cable and main beam constraint subsystem is used to regulate the relative movement between the main cable and the main beam, and the main cable and bridge tower constraint subsystem is used to regulate the relative movement of the main cable in the tower top region.

[0008] Optionally, the vertical constraint device includes parallel elastic units and damping units, the lateral constraint device includes parallel elastic units and damping units, and the longitudinal constraint device includes parallel elastic units and damping units, as well as a limiting unit connected in series on the branch of the damping unit.

[0009] Optionally, the vertical constraint device may further include parallel inertial units.

[0010] Optionally, the vertical constraint device further includes a limiting unit connected in series on the damping unit branch.

[0011] Optionally, the vertical constraint device may further include parallel limiting units.

[0012] Optionally, the lateral constraint device may further include parallel inertial units.

[0013] Optionally, the lateral restraint device further includes a limiting unit connected in series on the damping unit branch.

[0014] Optionally, the lateral restraint device may further include parallel limiting units.

[0015] Optionally, the longitudinal restraint device further includes an inertial unit, which is connected in parallel with the elastic unit, or the inertial unit is connected in series in the branch of the elastic unit, or the inertial unit is connected in series in the combined branch of the damping unit and the elastic unit after they are connected in parallel.

[0016] Optionally, the main cable and main beam restraint subsystem includes multiple sets of symmetrically arranged parallel elastic units and damping units.

[0017] Optionally, the main cable and bridge tower restraint subsystem includes parallel elastic units and damping units, as well as limiting units connected in series on the damping unit branches.

[0018] Optionally, the main cable and tower constraint subsystem may also include an inertial unit.

[0019] Optionally, it also includes a multi-dimensional state sensing unit and a control unit for collecting bridge structure displacement, velocity or acceleration responses. The control unit receives the bridge structure displacement, velocity or acceleration responses collected by the multi-dimensional state sensing unit and adjusts one or more of the main beam and bridge tower constraint subsystem, the main cable and main beam constraint subsystem and the main cable and bridge tower constraint subsystem through a preset control method.

[0020] The multi-objective optimization design method for the three-dimensional multifunctional intelligent toughness constraint system described in this invention includes the following steps: (1) Using additional stiffness, additional damping and additional mass as decision variables, a dynamic model of a long bridge containing a three-dimensional multifunctional intelligent toughness constraint system is established, and the dynamic equation of the bridge structure under external load is obtained. (2) Based on the dynamic equation, solve the displacement, velocity, acceleration and internal force response of the structure under external static and dynamic loads, and construct a toughness index that reflects the structural function retention capability, a life index that reflects the fatigue damage of key components and a cost index that characterizes the engineering cost. (3) Using additional stiffness, additional damping and additional mass as decision variables, and taking the structure’s toughness, life and cost as optimization objectives, a multi-objective optimization model is established; (4) The genetic algorithm is used to solve the multi-objective optimization model to obtain the Pareto optimal solution set for additional stiffness, additional damping and additional mass; (5) Based on the preset toughness, life and cost weights, the Pareto optimal solution set is comprehensively evaluated and sorted using the weighted Euclidean distance method, and the optimal design point is selected; the additional stiffness, additional damping and additional mass parameters corresponding to the optimal design point are used as the optimal design parameters of the three-dimensional multifunctional intelligent toughness constraint system for long bridges.

[0021] Optionally, step (1) specifically includes the following steps: By treating additional stiffness, additional damping, and additional mass as independent design variables, a dynamic model of a long-distance bridge incorporating a three-dimensional multifunctional intelligent toughness constraint system is established. The dynamic equations of the bridge structure under external loads are obtained, expressed as follows: , In the formula, This represents the inherent mass matrix of the bridge structure. This represents the inherent damping matrix of the bridge structure. This represents the inherent stiffness matrix of the bridge structure. This represents the additional mass matrix provided by the three-dimensional multifunctional intelligent toughness constraint system. This represents the additional damping matrix provided by the three-dimensional multifunctional intelligent toughness constraint system. This represents the additional stiffness matrix provided by the three-dimensional multifunctional intelligent toughness constraint system, and , and All are design variables The function; The design variable vector includes the additional stiffness to be optimized. Additional damping and added quality ; For structure in time The displacement vector; For structure in time The velocity vector; For structure in time The acceleration vector; External excitation is the external force related to train load, wind load, or seismic load.

[0022] Optionally, step (2) specifically includes the following steps: Based on the dynamic response of the bridge structure, toughness, lifespan, and cost indicators are obtained. The toughness indicator is expressed as: , In the formula, This is the toughness evaluation function; The structural displacement response includes design variables. For the structural velocity response that includes design variables; Lifespan indicators are expressed as follows: , In the formula, For the stress history of the component, For fatigue life estimation, For life evaluation functions; Cost indicators are expressed as follows: , In the formula, It is a comprehensive life-cycle cost indicator that includes both the bridge structure itself and the three-dimensional multifunctional intelligent toughness constraint system; The construction cost of the long bridge structure itself; To provide the cost function of the device for additional stiffness, To provide a device cost function with additional damping, Cost function for devices that provide additional quality.

[0023] Optionally, step (3) specifically includes the following steps: Construct a multi-objective optimization model for resilience, lifespan, and cost: , And impose design variable range constraints: , In the formula, This represents a multi-objective function vector, which aims to simultaneously maximize the bridge structure's toughness, maximize its lifespan, and minimize its total life-cycle cost. The design space, or feasible domain, is a multi-dimensional space determined by the actual constraints of the engineering project. This represents the lower bound constraint vector for the design variables. This represents the upper limit constraint vector for design variables.

[0024] Optionally, step (4) specifically includes the following steps: The multi-objective optimization model is solved using a genetic algorithm, and its iterative solution process is expressed as follows: First, in the design space Initial population is generated randomly within the population. , Then, through non-dominated sorting and crowding evaluation, and after selection, crossover, and mutation operations, the following results are obtained iteratively: , In the formula, The initial population for the genetic algorithm contains A randomly generated initial design scheme; This indicates the population size, which is the number of design schemes included in each generation of iterative computation; This represents the Pareto optimal solution set obtained after multiple iterations of evolution. Each solution in this optimal solution set represents a non-dominated solution that achieves different balance states between resilience, lifetime, and cost. This represents the total number of nondominated solutions contained in the Pareto optimal solution set.

[0025] Optionally, step (5) specifically includes the following steps: First, the solutions on the Pareto front are normalized. Let the first solution be... The three objective values ​​corresponding to each solution are , In the formula, Indicating the Pareto frontier, the first... The solution is at the th solution. The original values ​​on each target, of which These correspond to toughness, lifespan, and cost, respectively. This represents the objective function value after dimensionless normalization. For the The solution of the first... The target is dimensionlessly normalized. , and They represent the Pareto optimal solutions set, respectively. The maximum and minimum values ​​of the objective function; The vector representing the ideal reference point is composed of the theoretical optimal values ​​of each objective in the normalized space. Establish reference points, , Among them, the goal of "the smaller the better" is acceptable. The goal of "the bigger the better" is acceptable. ; Given the weights of resilience, lifespan, and cost, , Represents the engineering preference weight vector. , , These represent the toughness weight, lifespan weight, and cost weight, respectively, satisfying the following conditions: ; No. The weighted Euclidean distance of each solution relative to the ideal reference point is... , Indicates the first The weighted Euclidean distance of each solution relative to the ideal reference point; Finally, the solution with the smallest distance is selected as the overall optimal design parameter: , This represents the final optimal decision vector. The optimal decision vector Design parameters for a three-dimensional multifunctional intelligent toughness constraint system: , , , Indicates by The optimal physical design parameters obtained from decoding correspond to the optimal stiffness, optimal damping, and optimal inertia / mass parameters of the constraint device, respectively.

[0026] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages: (1) The three-dimensional multifunctional intelligent toughness constraint system proposed in this invention can simultaneously achieve coordinated control of the three-dimensional static and dynamic response of bridges, significantly reduce the three-dimensional response of bridges under static and dynamic effects such as vehicle load, temperature, strong wind and earthquake, and improve the safety and functional recoverability of long bridges under static and dynamic loads. (2) The longitudinal restraint device of the present invention adopts a static limit-dynamic damping combination mode and is equipped with a self-recovery unit. It can automatically reset after extreme events such as earthquakes and strong winds, effectively eliminate residual displacement, reduce post-disaster human intervention, and significantly improve the bridge’s ability to quickly recover its function. (3) The three-dimensional multifunctional toughness constraint device of the present invention integrates intelligent perception, intelligent evaluation and intelligent control unit, which can adjust stiffness, damping or mass parameters in real time according to vehicle load, strong wind and earthquake, effectively overcome the defects of fixed parameters and poor adaptability of traditional devices, and enhance the bridge's adaptive ability to complex time-varying loads. (4) By configuring inertial units, the present invention provides additional energy dissipation, additional damping or equivalent additional stiffness by utilizing inertial effects, effectively improving the vibration response in the low-frequency band of the structure, further enhancing the control performance of the system in the vertical, horizontal or longitudinal directions, and broadening the functional dimensions of the intelligent constraint system. (5) The multi-objective optimization design method of the present invention incorporates additional stiffness, additional damping and additional mass into decision variables, integrates toughness index, life index and cost index to establish a multi-objective optimization model, uses genetic algorithm for efficient solution, and selects the optimal solution based on weighted Euclidean distance to achieve synergistic optimization of structural toughness, life and economic benefits. (6) The constraint system and target optimization design method of the present invention do not depend on a specific bridge type and can be widely applied to improve the toughness and extend the service life of newly built and existing long bridges, and have broad engineering promotion and application value. Attached Figure Description

[0027] Figure 1 This is a diagram of the three-dimensional multifunctional intelligent toughness constraint system architecture in an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of each constraint device in the present invention; Figure 3 This is a schematic diagram of the full-bridge cooperative intelligent control system in this invention; Figure 4 This is a flowchart of the multi-objective optimization design method in this invention; Figure 5 A three-dimensional conceptual diagram illustrating the additional control measures of this invention; Figure 6 This is a schematic diagram of the multi-objective optimization results of the present invention. Detailed Implementation

[0028] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0029] This invention includes a long-span bridge and a three-dimensional multifunctional intelligent toughness constraint system arranged at the connection points of key structural components of the long-span bridge. The long-span bridge includes a bridge tower 2, a main beam 1, a main beam foundation 19, and cable-stayed system components selectively arranged according to the bridge structure. The cable-stayed system components include a main cable 3, a suspender cable 4, a stay cable, or any combination of the above cable-stayed system components, forming a force connection between the main beam 1 and the bridge tower 2 (or the anchorage structure 5).

[0030] The three-dimensional multifunctional intelligent toughness constraint system includes a full-bridge collaborative intelligent control system and one or more of the following: a main girder and bridge tower constraint subsystem 6 located between the main girder and the bridge tower; a main cable and main girder constraint subsystem 7 located between the main cable and the main girder; and a main cable and bridge tower constraint subsystem 8 located between the cable saddle structure 17 and the bridge tower. One or more of these subsystems serve as multifunctional adjustable actuator units. The three-dimensional multifunctional intelligent toughness constraint system is an intelligent control loop capable of adjusting constraint parameters in real time according to the structural response.

[0031] The main girder and tower restraint subsystem 6 is used to regulate the relative movement of the main girder with respect to the tower in three dimensions. This subsystem includes vertical restraint devices, lateral restraint devices, and longitudinal restraint devices. Vertical restraint refers to the direction along gravity, longitudinal restraint refers to the direction along the axis of the main girder, and lateral restraint refers to the direction perpendicular to the axis of the main girder in the horizontal plane. The main cable and main girder restraint subsystem 7 is used to regulate the relative movement between the main cable and the main girder, and the main cable and tower restraint subsystem 8 is used to regulate the relative movement of the main cable in the tower top region. Both the main girder and tower restraint subsystems 6 have self-recovery functions.

[0032] The vertical restraint device includes parallel elastic and damping units. Preferably, the vertical restraint device includes parallel inertial units. Preferably, the vertical restraint device includes limiting units connected in series on the branches of the damping units. Preferably, the vertical restraint device also includes parallel limiting units. The vertical restraint device is a vertical restoring force component with self-restoring capability, which includes adjustable stiffness units or adjustable damping units, capable of automatically restoring to the initial state after vertical deformation, and providing restoring force and energy dissipation functions for the vertical vibration of the main beam.

[0033] The lateral restraint device includes parallel elastic and damping units. Preferably, the lateral restraint device also includes parallel inertial units. Preferably, the lateral restraint device also includes limiting units connected in series on the branches of the damping units. Preferably, the lateral restraint device also includes parallel limiting units. The lateral restraint device is a static restraint-dynamic damping combination device with self-recovery function. Its self-recovery function is provided by shape memory materials, hyperelastic recovery components, or equivalent restoring force mechanisms. It restricts the lateral displacement of the main beam through static restraint units and dissipates lateral vibration energy through dynamic damping units with adjustable damping coefficients.

[0034] The longitudinal restraint device includes parallel elastic and damping units, as well as a limiting unit connected in series on the branch of the damping unit. Preferably, the longitudinal restraint device further includes an inertial unit, which is connected in parallel with the elastic unit, or connected in series on the branch of the elastic unit, or connected in series on the combined branch of the parallel damping and elastic units. The longitudinal restraint device is a static limiting-dynamic damping combination device with self-recovery function. Its self-recovery function is used to actively or passively restore the device to its initial position after the external load dissipates. The static limiting unit provides longitudinal displacement control of the main beam, and the dynamic damping unit reduces the longitudinal dynamic response of the main beam. The vertical, lateral, or longitudinal restraint device may also include an additional inertial unit, which provides additional energy dissipation, additional damping, or additional stiffness through the mass inertia effect to further reduce the vibration response of the main beam in the corresponding direction. The additional inertial unit can be a tuned mass, an additional inertial component, or an equivalent inertial control device, and its specific form does not constitute a limitation of the present invention.

[0035] like Figure 5 As shown, this invention constructs a three-dimensional design space for additional control measures through three directions: additional stiffness, additional damping, and additional mass. The additional stiffness K, additional damping C, and additional mass M correspond to different energy regulation and dynamic control effects, and can be combined and set according to target requirements to form a multi-level and multi-mode collaborative control capability. Figure 5 Abstract representations of the structure's inherent stiffness, damping, and mass in a three-dimensional coordinate system are provided, along with the adjustment relationships of additional control measures in each direction, to aid in understanding the configuration and operational mechanism of the additional control unit in this invention. Vertical, lateral, and longitudinal constraint devices achieve three-dimensional collaborative operation through an intelligent control unit, forming a three-dimensional multifunctional intelligent toughness constraint system that simultaneously provides limiting, energy dissipation, and self-resetting functions. This system is used to improve the overall toughness, service life, and dynamic stability of long bridges under external static and dynamic loads.

[0036] The main cable and main beam restraint subsystem includes multiple sets of symmetrically arranged parallel elastic and damping units.

[0037] The main cable and tower restraint subsystem includes parallel elastic and damping units, as well as limiting units connected in series on the damping unit branches. Preferably, the main cable and tower restraint subsystem also includes inertial units.

[0038] In this invention, the elastic unit provides restoring force or additional stiffness, the damping unit provides energy dissipation, the inertial unit provides additional mass or inertial force, and the limiting unit provides displacement control.

[0039] The elastic unit of the vertical restraint device is an adjustable stiffness unit composed of shape memory alloy SMA cable, hyperelastic recovery component, prestressed restoring rib, or hydraulic stiffness adjuster; the damping unit of the vertical restraint device is an adjustable damping unit composed of one or more combinations of magnetorheological damper, viscous damper, or friction damper; the inertial unit of the vertical restraint device is an adjustable inertial unit composed of tuned mass damper (TMD), flywheel inertial capacity (Inerter), ball screw inertial capacity, or hydraulic inertial capacity component.

[0040] The elastic unit of the lateral restraint device is an adjustable stiffness unit composed of shape memory alloy SMA cables, disc spring groups, hyperelastic recovery components, or prestressed restoring ribs; the damping unit of the lateral restraint device is an adjustable damping unit composed of one or more combinations of magnetorheological dampers, viscous dampers, or friction dampers; the inertial unit of the lateral restraint device is an adjustable inertial unit composed of tuned mass dampers (TMD), flywheel inertial capacitance (Inerter), ball screw inertial capacitance, or hydraulic inertial capacitance components.

[0041] The elastic unit of the longitudinal restraint device is an adjustable stiffness unit composed of shape memory alloy SMA cable, disc spring assembly, hyperelastic recovery component, or prestressed restoring rib; the damping unit of the longitudinal restraint device is an adjustable damping unit composed of one or more combinations of magnetorheological damper, viscous damper, or friction damper; the inertial unit of the longitudinal restraint device is an adjustable inertial unit composed of tuned mass damper (TMD), flywheel inertial capacity (Inerter), ball screw inertial capacity, or hydraulic inertial capacity component; the limiting unit of the longitudinal restraint device is a static limiting unit composed of steel limiting block, buffer limiter, or soft steel limiting device.

[0042] The elastic unit in the main cable and main beam constraint subsystem is an adjustable stiffness unit composed of shape memory alloy SMA cables, hyperelastic recovery components, or prestressed restoring tendons. It can provide adaptive elastic stiffness to limit dynamic displacement and provide elastic restoring force to assist the structure in restoring after external loads. The damping unit is an adjustable damping unit composed of one or more combinations of magnetorheological dampers, viscous dampers, or friction dampers to suppress the coupled vibration of the main cable and main beam.

[0043] The elastic unit in the main cable and tower constraint subsystem includes elastic reset elements, shape memory components, or potential energy recovery structures, which can restore the cable saddle structure to its initial equilibrium position after the external load dissipates; the damping unit includes an adjustable damping unit composed of one or more combinations of magnetorheological dampers, viscous dampers, or friction dampers disposed between the cable saddle side and the tower; the limiting unit includes steel limiting blocks, buffer limiting devices, or soft steel limiting devices, which provide rigid or flexible limitation when the relative displacement between the main cable and the tower reaches a preset threshold to prevent excessive slippage of the main cable; the inertial unit includes an adjustable inertial unit composed of tuned mass dampers (TMD), flywheel inertial capacitance, ball screw inertial capacitance, or hydraulic inertial capacitance components.

[0044] like Figure 3 As shown, preferably, it also includes a multi-dimensional state sensing unit and a control unit for collecting bridge structure displacement, velocity, or acceleration responses. The control unit receives the bridge structure displacement, velocity, or acceleration responses collected by the multi-dimensional state sensing unit and adjusts one or more of the main girder and tower constraint subsystems, the main cable and main girder constraint subsystems, and the main cable and tower constraint subsystems through a preset control method, i.e., adjusting the damping force of the damping unit, the stiffness of the elastic unit, or the inertial mass coefficient of the inertial unit. The control method includes at least one selected from PID control, fuzzy control, model predictive control (MPC), and LQG control, all of which are existing algorithms. The control units are connected through an optical fiber network or a wireless communication module to form a full-bridge collaborative intelligent control system. The full-bridge collaborative intelligent control system is configured to coordinate the actuator unit actions of the above subsystems based on the multi-point sensing information of the entire bridge to achieve overall toughness regulation and dynamic optimization of the long-span bridge.

[0045] like Figure 1 and Figure 2 As shown, the three-dimensional multifunctional intelligent toughness constraint system in this embodiment includes a main beam and bridge tower constraint subsystem 6, a main cable and main beam constraint subsystem 7, and a main cable and bridge tower constraint subsystem 8. The main beam and bridge tower constraint subsystem 6 includes a vertical constraint device 9, a first lateral constraint device 10, a second lateral constraint device 11, a first longitudinal constraint device 12, and a second longitudinal constraint device 13. The second lateral constraint device 11 is connected to the bridge tower crossbeam 18.

[0046] The vertical constraint device 9 includes a first elastic unit 901, a first damping unit 902, and a first inertial unit 903 arranged in parallel. The first lateral constraint device 10 includes a second elastic unit 1001 and a second damping unit 1002 arranged in parallel. The second lateral constraint device 11 includes a third elastic unit 1101, a third damping unit 1102, and a second inertial unit 1103 arranged in parallel. The first longitudinal constraint device 12 includes a fourth elastic unit 1201 and a fourth damping unit 1202 arranged in parallel, and a first limiting unit 1203 connected in series on the branch of the fourth damping unit. The second longitudinal constraint device 13 includes a fifth elastic unit 1301, a fifth damping unit 1302, and a third inertial unit 1303 arranged in parallel, and a second limiting unit 1304 connected in series on the branch of the fifth damping unit.

[0047] The main cable and main beam restraint subsystem 7 includes multiple sets of symmetrically arranged first restraint devices 14, each first restraint device 14 including parallel elastic units and damping units.

[0048] The main cable and bridge tower restraint subsystem 8 includes a second restraint device 15 and a third restraint device 16, wherein the second restraint device 15 has the same structural form as the first longitudinal restraint device 12, and the third restraint device 16 is an inertial unit.

[0049] Under external static and dynamic loads, the main girder 2 and the bridge tower 1 will generate coupled responses in the vertical, lateral, and longitudinal directions. The three-dimensional intelligent toughness constraint system proposed in this invention can simultaneously perform multiple functions such as limiting, energy dissipation, inertial adjustment, and self-recovery in three directions, thereby achieving coordinated control of the overall dynamic behavior of the bridge. The static limiting unit in the system first provides a constraint boundary for the displacement of the main girder relative to the tower column, effectively suppressing large displacements caused by temperature effects or vehicle braking forces; the dynamic damping unit continuously dissipates energy during vibration, reducing the vibration amplitude and smoothing the structural response; the additional inertial unit enhances the energy dissipation capacity in the low-to-medium frequency range through the mass inertia effect, improving the system's adaptability to different types of loads; the self-recovery unit ensures that the constraint device automatically returns to its initial position after extreme events or large displacements subside, avoiding the adverse effects of residual deformation on the structural function; at the same time, the intelligent control unit dynamically adjusts stiffness, damping, or mass-related parameters according to the real-time monitored operating status, so that the constraint system continuously maintains the optimal working state. Through the synergistic effect of the aforementioned multifunctional devices, the present invention can significantly reduce the vertical amplitude, lateral sway and longitudinal impact of the main beam, and comprehensively improve the dynamic stability, toughness level and fatigue life of key components of long bridges.

[0050] like Figure 4 As shown, the present invention discloses a multi-objective optimization design method for a three-dimensional multifunctional intelligent toughness constraint system for long bridges, comprising the following steps: (1) Using additional stiffness, additional damping and additional mass as decision variables, a dynamic model of a long bridge containing a three-dimensional multifunctional intelligent toughness constraint system is established, and the dynamic equation of the bridge structure under external load is obtained. Step (1) specifically includes the following steps: By treating additional stiffness, additional damping, and additional mass as independent design variables, a dynamic model of a long-distance bridge incorporating a three-dimensional multifunctional intelligent toughness constraint system is established. The dynamic equations of the bridge structure under external loads are obtained, expressed as follows: , In the formula, This represents the inherent mass matrix of the bridge structure. This represents the inherent damping matrix of the bridge structure. This represents the inherent stiffness matrix of the bridge structure. This represents the additional mass matrix provided by the three-dimensional multifunctional intelligent toughness constraint system. This represents the additional damping matrix provided by the three-dimensional multifunctional intelligent toughness constraint system. This represents the additional stiffness matrix provided by the three-dimensional multifunctional intelligent toughness constraint system, and , and All are design variables The function; The design variable vector includes the additional stiffness to be optimized. Additional damping and added quality ; For structure in time The displacement vector; For structure in time The velocity vector; For structure in time The acceleration vector; External excitation is the external force related to train load, wind load, or seismic load.

[0051] (2) Based on the dynamic equation, solve the displacement, velocity, acceleration and internal force response of the structure under external static and dynamic loads, and construct a toughness index that reflects the structural function retention capability, a life index that reflects the fatigue damage of key components and a cost index that characterizes the engineering cost. Step (2) specifically includes the following steps: Based on the dynamic response of the bridge structure, toughness, lifespan, and cost indicators are obtained. The toughness indicator is expressed as: , In the formula, This is a toughness evaluation function that comprehensively considers peak displacement, residual deformation, and functional recovery. The design variable vector includes the additional stiffness to be optimized. Additional damping and added quality ; The structural displacement response includes design variables. For the structural velocity response that includes design variables; Lifespan indicators are expressed as follows: , In the formula, For the stress history of the component, For fatigue life estimation, For life evaluation functions; Cost indicators are expressed as follows: , In the formula, It is a comprehensive life-cycle cost indicator that includes both the bridge structure itself and the three-dimensional multifunctional intelligent toughness constraint system; The construction cost of the long bridge structure itself; , , These are cost functions for providing additional stiffness, additional damping, and additional mass of the constraint devices, respectively.

[0052] (3) Using additional stiffness, additional damping and additional mass as decision variables, and taking the structure’s toughness, life and cost as optimization objectives, a multi-objective optimization model is established; Step (3) specifically includes the following steps: Construct a multi-objective optimization model for resilience, lifespan, and cost: , And impose design variable range constraints: , In the formula, This represents the design variable vector, which contains the key physical parameters of the three-dimensional multifunctional intelligent toughness constraint system, including the additional stiffness to be optimized. Additional damping and added quality parameter; This represents a multi-objective function vector, which aims to simultaneously maximize the bridge structure's toughness, maximize its lifespan, and minimize its total life-cycle cost. The design space, or feasible domain, is a multi-dimensional space determined by the actual constraints of the engineering project. , : These represent the lower and upper constraint vectors of the design variables, respectively, used to limit the physically realizable range of stiffness, damping, and inertia parameters.

[0053] (4) The genetic algorithm is used to solve the multi-objective optimization model to obtain the Pareto optimal solution set for additional stiffness, additional damping and additional mass; Step (4) specifically includes the following steps: The multi-objective optimization model is solved using a genetic algorithm, and its iterative solution process can be expressed as follows: First, in the design space Initial population is generated randomly within the population. , Then, through non-dominated sorting and crowding evaluation, and after operations such as selection, crossover, and mutation, the following results are obtained iteratively: , In the formula, The initial population for the genetic algorithm contains A randomly generated initial design scheme; This indicates the population size, which is the number of design schemes included in each generation of iterative computation; This represents the Pareto optimal solution set or Pareto front obtained after multiple iterations of evolution. Each solution in this set represents a non-dominated solution that achieves different balances between resilience, lifetime, and cost; K represents the total number of non-dominated solutions contained in the Pareto optimal solution set.

[0054] (5) Based on the preset toughness, life and cost weights, the Pareto optimal solution set is comprehensively evaluated and sorted using the weighted Euclidean distance method, and the optimal design point is selected; the additional stiffness, additional damping and additional mass parameters corresponding to the optimal design point are used as the optimal design parameters of the three-dimensional multifunctional intelligent toughness constraint system for long bridges.

[0055] Step (5) specifically includes the following steps: The optimal solution is selected from the Pareto front using the weighted Euclidean distance method. First, the solutions on the Pareto front are normalized. Let the three objective values ​​corresponding to the nth solution be... , In the formula, represents the original value of the i-th solution in the Pareto front for the k-th objective, where k=1,2,3 correspond to toughness, lifespan, and cost, respectively. This represents the objective function value after dimensionless normalization, used to eliminate the differences in dimensions and orders of magnitude between toughness, lifespan, and cost, ensuring fairness in distance calculation; Dimensionless normalization is performed on the nth objective of the nth solution. , , Let represent the maximum and minimum values ​​of the k-th objective function in the Pareto optimal solution set, respectively; The vector representing the ideal reference point is composed of the theoretical optimal values ​​of each objective in the normalized space. Establish reference points, , Among them, the goal of "the smaller the better" is acceptable. The goal of "the bigger the better" is acceptable. Or, a specific value can be set according to the project requirements.

[0056] Given the weights of resilience, lifespan, and cost, , This represents the engineering preference weight vector, reflecting the designer's emphasis on different objectives; , , These represent the toughness weight, lifespan weight, and cost weight, respectively, satisfying the following conditions: Designers can determine the importance level of the bridge based on its grade (e.g., lifeline projects require high priority). ) or budget constraints (such as high costs required for economical projects) Adjustments are made accordingly; The weighted Euclidean distance of the i-th solution relative to the ideal reference point can be written as: , This represents the weighted Euclidean distance of the i-th solution relative to the ideal reference point. The smaller this distance, the closer the design scheme is to the designer's overall expectation. Finally, the solution with the smallest distance is selected as the overall optimal design parameter: , This represents the final optimal decision vector. The optimal decision vector Design parameters for a three-dimensional multifunctional intelligent toughness constraint system: , , , Indicates by The optimal physical design parameters obtained from decoding correspond to the optimal stiffness, optimal damping, and optimal inertia / mass parameters of the constraint device, which are used to guide the manufacturing and parameter tuning of actual products. Based on this, the three-dimensional multifunctional intelligent toughness constraint system for long bridges can be adjusted to achieve the comprehensive optimal design of structural toughness, lifespan, and cost.

[0057] like Figure 6 As shown, by using a genetic algorithm to perform multi-objective optimization on three decision variables—added stiffness, added damping, and added mass—a Pareto optimal solution set can be obtained, balancing toughness, lifespan, and cost. The surface in the figure represents the distribution characteristics of the optimized solutions; the black scatter points represent the optimization results of different parameter combinations, and the color intensity indicates the trade-offs between performance objectives. This schematic diagram demonstrates that the multi-objective optimization design method proposed in this invention can effectively obtain compromise solutions for structural performance, providing a scientific basis for the final parameter selection.

[0058] This invention constructs a three-dimensional multifunctional intelligent toughness constraint system capable of simultaneously achieving vertical, lateral, and longitudinal control functions. It also establishes a quantifiable, solvable, and engineering-compatible multi-objective optimization method based on intelligent optimization theory to achieve parameter collaborative design of the constraint system. By using additional stiffness, additional damping, and additional mass as decision variables, and comprehensively considering objectives such as improving structural toughness, extending the lifespan of key components, and controlling engineering costs, advanced optimization techniques such as genetic algorithms are employed to solve for Pareto optimal solutions. Furthermore, intelligent criteria are used to select the optimal configuration, providing reliable technical support for the toughness design of long-span bridges.

Claims

1. A three-dimensional multifunctional intelligent toughness constraint system for long-length bridges, characterized in that, The system includes one or more of the following: a main beam and bridge tower restraint subsystem located between the main beam and the bridge tower; a main cable and main beam restraint subsystem located between the main cable and the main beam; and a main cable and bridge tower restraint subsystem located between the cable saddle structure and the bridge tower. The main beam and bridge tower restraint subsystem is used to regulate the relative movement of the main beam relative to the bridge tower in three dimensions, and includes a vertical restraint device, a lateral restraint device, and a longitudinal restraint device. The main cable and main beam restraint subsystem is used to regulate the relative movement between the main cable and the main beam, and the main cable and bridge tower restraint subsystem is used to regulate the relative movement of the main cable in the tower top region.

2. The three-dimensional multifunctional intelligent toughness constraint system for long-length bridges according to claim 1, characterized in that: The vertical constraint device includes parallel elastic units and damping units, the lateral constraint device includes parallel elastic units and damping units, and the longitudinal constraint device includes parallel elastic units and damping units, as well as limiting units connected in series on the branches of the damping units.

3. The three-dimensional multifunctional intelligent toughness constraint system for long-length bridges according to claim 2, characterized in that: The vertical constraint device also includes parallel inertial units.

4. The three-dimensional multifunctional intelligent toughness constraint system for long-length bridges according to claim 2 or 3, characterized in that: The vertical constraint device also includes a limiting unit connected in series on the damping unit branch.

5. The three-dimensional multifunctional intelligent toughness constraint system for long-length bridges according to claim 2 or 3, characterized in that: The vertical constraint device also includes parallel limiting units.

6. The three-dimensional multifunctional intelligent toughness constraint system for long-length bridges according to claim 2, characterized in that: The lateral restraint device also includes parallel inertial units.

7. The three-dimensional multifunctional intelligent toughness constraint system for long-length bridges according to claim 2 or 3, characterized in that: The lateral restraint device also includes a limiting unit connected in series on the damping unit branch.

8. The three-dimensional multifunctional intelligent toughness constraint system for long-length bridges according to claim 2 or 3, characterized in that: The lateral restraint device also includes parallel limiting units.

9. The three-dimensional multifunctional intelligent toughness constraint system for long-length bridges according to claim 2, characterized in that: The longitudinal restraint device also includes an inertial unit, which is connected in parallel with the elastic unit, or the inertial unit is connected in series in the branch of the elastic unit, or the inertial unit is connected in series in the combined branch of the damping unit and the elastic unit after they are connected in parallel.

10. The three-dimensional multifunctional intelligent toughness constraint system for long-length bridges according to claim 1, characterized in that: The main cable and main beam restraint subsystem includes multiple sets of symmetrically arranged parallel elastic units and damping units.

11. The three-dimensional multifunctional intelligent toughness constraint system for long-length bridges according to claim 1, characterized in that: The main cable and tower restraint subsystem includes parallel elastic units and damping units, as well as limiting units connected in series on the branches of the damping units.

12. The three-dimensional multifunctional intelligent toughness constraint system for long-length bridges according to claim 11, characterized in that: The main cable and tower constraint subsystem also includes an inertial unit.

13. The three-dimensional multifunctional intelligent toughness constraint system for long-length bridges according to claim 1, characterized in that: It also includes a multi-dimensional state sensing unit and a control unit for collecting bridge structure displacement, velocity or acceleration responses. The control unit receives the bridge structure displacement, velocity or acceleration responses collected by the multi-dimensional state sensing unit and adjusts one or more of the main beam and bridge tower constraint subsystem, the main cable and main beam constraint subsystem and the main cable and bridge tower constraint subsystem through a preset control method.

14. A multi-objective optimization design method for a three-dimensional multifunctional intelligent toughness constraint system for long bridges according to claims 1 to 13, characterized in that, Includes the following steps: (1) Using additional stiffness, additional damping and additional mass as decision variables, a dynamic model of a long bridge containing a three-dimensional multifunctional intelligent toughness constraint system is established, and the dynamic equation of the bridge structure under external load is obtained. (2) Solve the displacement, velocity, acceleration and internal force response of the structure under external static and dynamic loads based on the dynamic equation, and construct a toughness index that reflects the structural function retention capability, a life index that reflects the service life of key components and a cost index that characterizes the engineering cost. (3) Using additional stiffness, additional damping and additional mass as decision variables, and taking the structure’s toughness, life and cost as optimization objectives, a multi-objective optimization model is established; (4) The genetic algorithm is used to solve the multi-objective optimization model to obtain the Pareto optimal solution set for additional stiffness, additional damping and additional mass; (5) Based on the preset toughness, life and cost weights, the Pareto optimal solution set is comprehensively evaluated and sorted using the weighted Euclidean distance method, and the optimal design point is selected; the additional stiffness, additional damping and additional mass parameters corresponding to the optimal design point are used as the optimal design parameters of the three-dimensional multifunctional intelligent toughness constraint system for long bridges.

15. The multi-objective optimization design method for a three-dimensional multifunctional intelligent toughness constraint system for long-length bridges according to claim 14, characterized in that, Step (1) specifically includes the following steps: By treating additional stiffness, additional damping, and additional mass as independent design variables, a dynamic model of a long-distance bridge incorporating a three-dimensional multifunctional intelligent toughness constraint system is established. The dynamic equations of the bridge structure under external loads are obtained, expressed as follows: ， In the formula, This represents the inherent mass matrix of the bridge structure. This represents the inherent damping matrix of the bridge structure. This represents the inherent stiffness matrix of the bridge structure. This represents the additional mass matrix provided by the three-dimensional multifunctional intelligent toughness constraint system. This represents the additional damping matrix provided by the three-dimensional multifunctional intelligent toughness constraint system. This represents the additional stiffness matrix provided by the three-dimensional multifunctional intelligent toughness constraint system, and , and All are design variables The function; The design variable vector includes the additional stiffness to be optimized. Additional damping and added quality ; For structure in time The displacement vector; For structure in time The velocity vector; For structure in time The acceleration vector; External excitation is the external force related to train load, wind load, or seismic load.

16. The multi-objective optimization design method for a three-dimensional multifunctional intelligent toughness constraint system for long bridges according to claim 15, characterized in that, Step (2) specifically includes the following steps: Based on the dynamic response of the bridge structure, toughness, lifespan, and cost indicators are obtained. The toughness indicator is expressed as: ， In the formula, This is a toughness evaluation function; The structural displacement response includes design variables. For the structural velocity response that includes design variables; Lifespan indicators are expressed as follows: ， In the formula, For the stress history of the component, For fatigue life estimation, For life evaluation functions; Cost indicators are expressed as follows: ， In the formula, It is a comprehensive life-cycle cost indicator that includes both the bridge structure itself and the three-dimensional multifunctional intelligent toughness constraint system; The construction cost of the long bridge structure itself; To provide the cost function of the device for additional stiffness, To provide a device cost function with additional damping, Cost function for devices that provide additional quality.

17. The multi-objective optimization design method for a three-dimensional multifunctional intelligent toughness constraint system for long bridges according to claim 16, characterized in that, Step (3) specifically includes the following steps: Construct a multi-objective optimization model for resilience, lifespan, and cost: ， And impose design variable range constraints: ， In the formula, This represents a multi-objective function vector, which aims to simultaneously maximize the bridge structure's toughness, maximize its lifespan, and minimize its total life-cycle cost. The design space, or feasible domain, is a multi-dimensional space determined by the actual constraints of the engineering project. This represents the lower bound constraint vector for the design variables. This represents the upper limit constraint vector for design variables.

18. The multi-objective optimization design method for a three-dimensional multifunctional intelligent toughness constraint system for long-length bridges according to claim 17, characterized in that, Step (4) specifically includes the following steps: The multi-objective optimization model is solved using a genetic algorithm, and its iterative solution process is expressed as follows: First, in the design space Initial population is generated randomly within the population. ， Then, through non-dominated sorting and crowding evaluation, and after selection, crossover, and mutation operations, the following results are obtained iteratively: ， In the formula, This represents the initial population for the genetic algorithm, containing... A randomly generated initial design scheme; This indicates the population size, which is the number of design schemes included in each generation of iterative computation; This represents the Pareto optimal solution set obtained after multiple iterations of evolution. Each solution in this optimal solution set represents a non-dominated solution that achieves different balance states between resilience, lifetime, and cost. This represents the total number of nondominated solutions contained in the Pareto optimal solution set.

19. The multi-objective optimization design method for a three-dimensional multifunctional intelligent toughness constraint system for long bridges according to claim 18, characterized in that, Step (5) specifically includes the following steps: First, the solutions on the Pareto front are normalized. Let the first solution be... The three objective values ​​corresponding to each solution are ， In the formula, Indicating the Pareto frontier, the first... The solution is at the th solution. The original values ​​on each target, of which These correspond to toughness, lifespan, and cost, respectively. This represents the objective function value after dimensionless normalization. For the The solution of the first... Dimensionless normalization is performed on each target. ， and They represent the Pareto optimal solutions set, respectively. The maximum and minimum values ​​of the objective function; The vector representing the ideal reference point is composed of the theoretical optimal values ​​of each objective in the normalized space. Establish reference points, ， Among them, the goal of "the smaller the better" is acceptable. The goal of "the bigger the better" is acceptable. ; Given the weights of resilience, lifespan, and cost, ， Represents the engineering preference weight vector. , , These represent the toughness weight, lifespan weight, and cost weight, respectively, satisfying the following conditions: ; No. The weighted Euclidean distance of each solution relative to the ideal reference point is... ， Indicates the first The weighted Euclidean distance of each solution relative to the ideal reference point; Finally, the solution with the smallest distance is selected as the overall optimal design parameter: ， This represents the final optimal decision vector. The optimal decision vector Design parameters for a three-dimensional multifunctional intelligent toughness constraint system: ， , , Indicates by The optimal physical design parameters obtained from decoding correspond to the optimal stiffness, optimal damping, and optimal inertia / mass parameters of the constraint device, respectively.

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