Probabilistic failure assessment method and system for floating objects impacting bridges during flood season

Abstract

The present invention relates to the field of bridge engineering technology, specifically to a probabilistic failure assessment method and system for floating objects hitting bridges during flood season, the method comprising the following steps: collecting floating object data and river hydrological information during flood season and obtaining water flow velocity and floating object movement conditions; establishing a floating object drag force prediction model according to the water flow velocity and floating object movement conditions and analyzing the drag force generated by flood on floating objects based on the model; setting a bridge damage assessment mechanism based on the floating object data during flood season and river hydrological information, and obtaining assessment parameter analysis results based on the assessment mechanism; establishing a probabilistic failure judgment model, combining the drag force, assessment parameter analysis results and the floating object data during flood season and river hydrological information to obtain probabilistic failure assessment results, and realizing risk prediction and assessment of floating objects hitting bridges during flood season. By analyzing the failure mechanism of floating objects hitting bridges, the risk degree of bridge damage under different water flow conditions and floating object characteristics is quantified.

Description

Technical Field

[0001] The present invention relates to the technical field of bridge engineering, and in particular to a probabilistic failure assessment method and system for floating objects impacting bridges during flood season. Background Art

[0002] Bridges are an important part of the modern transportation system. They not only cross natural barriers to connect different places, but also affect the smoothness of economic activities and social interactions. However, the frequent occurrence of extreme climate events has increased the risk of floating objects hitting bridges. The surge in river water levels and the increase in flow speed during the flood season have caused a large number of floating objects such as trees, garbage and out-of-control ships to drift with the current. When these objects hit the bridge, they will release huge kinetic energy, which will pose a serious threat to the bridge structure. In the case of minor damage, it will cause local damage, and in the case of serious damage, it may cause the entire bridge to lose its function.

[0003] Once a bridge fails due to the impact of floating objects, it means traffic interruption and even affects the social and economic order. On the other hand, such events during the flood season may also trigger secondary disasters. For example, the temporary flood barrier formed after the bridge breaks further expands the scope of the disaster, thereby threatening the lives and property safety of residents along the coast. Most of the current failure assessment methods rely on deterministic analysis methods. In the processing process, they fail to fully incorporate factors such as the probabilistic characteristics of floating object distribution, the random changes in river hydrodynamics, and the uncertainty of bridge stress performance, and cannot achieve a comprehensive assessment of probabilistic failures. Therefore, it is necessary to further explore the failure mechanism of floating objects hitting bridges and design a scientific and effective probabilistic assessment system to help ensure the safety of bridge structures and maintain the stability of the transportation network. Summary of the invention

[0004] In view of the defects of existing methods and the shortcomings of practical applications, for extreme events such as floating objects hitting bridges, it is now necessary to combine physical principles, mechanical analysis, and probability statistics to deeply analyze the bridge failure mechanism caused by floating object impact, and quantify the risk of bridge damage under different water flow states and floating object characteristics through mathematical models, so as to more accurately estimate the potential dangers of bridges in flood season, and further provide a scientific basis for the design and subsequent maintenance of bridges. In the first aspect, the present invention provides a probabilistic failure assessment method for floating objects hitting bridges during flood season, the method comprising the following steps: collecting floating object data and river hydrological information during flood season, obtaining water flow velocity and floating object movement status based on the floating object data and river hydrological information during flood season; establishing a floating object drag force prediction model according to the water flow velocity and the floating object movement status, and analyzing the drag force generated by flood on floating objects according to the floating object drag force prediction model; setting a bridge damage assessment mechanism based on the floating object data and river hydrological information during flood season, and obtaining an assessment parameter analysis result according to the bridge damage assessment mechanism; establishing a probabilistic failure judgment model, combining the probabilistic failure judgment model, the drag force, the assessment parameter analysis result and the floating object data and river hydrological information during flood season to obtain a probabilistic failure assessment result, so as to realize the risk prediction and assessment of floating objects hitting bridges during flood season. The present invention collects flood season related information and establishes a mathematical model to assess the risk of floating objects hitting bridges, which can improve the accuracy of risk assessment, realize risk quantitative assessment, enhance the scientific nature of decision-making and promote technological innovation and development.

[0005] Optionally, the obtaining of the water flow velocity and the floating object movement condition based on the flood season floating object data and the river hydrological information includes: establishing a water flow velocity analysis function and a floating object movement analysis equation according to the flood season floating object data and the river hydrological information; obtaining a floating object movement and water flow analysis model by combining the water flow velocity analysis function and the floating object movement analysis equation; obtaining the water flow velocity and the floating object movement condition through the floating object movement and water flow analysis model. The present invention establishes a water flow velocity analysis function and a floating object movement analysis equation, which not only improves the accuracy of the analysis results, but also enhances the prediction ability of the probabilistic failure assessment method.

[0006] Optionally, the water flow velocity analysis function satisfies the following relationship:

[0007]

[0008] in, Indicates the water flow velocity, represents the change of the equation over time, represents the gradient operator, represents the density of water, represents the pressure field, Represents the pressure field The gradient of represents the dynamic viscosity of water, Indicates water flow speed The Laplace operator of The function of the present invention comprehensively considers multiple factors such as the time change rate of water flow velocity, convection effect, pressure gradient force and viscous dissipation, which is conducive to accurately analyzing the dynamic behavior characteristics of water flow velocity.

[0009] Optionally, the floating object motion analysis equation satisfies the following relationship:

[0010]

[0011] in, Indicates the mass of the floating object, represents the speed of the floating object, represents the change of velocity with time, represents the drag force of floating objects, The buoyancy of floating objects, The floating object motion analysis equation of the present invention can more accurately predict the motion trajectory and speed change of the floating object, and provide support for the safety assessment and maintenance of the bridge.

[0012] Optionally, the establishment of a floating object drag force prediction model according to the water flow velocity and the floating object motion condition includes: obtaining the water flow velocity through the water flow velocity analysis function; obtaining the floating object motion condition based on the floating object motion analysis equation; and establishing a floating object drag force prediction model in combination with the water flow velocity and the floating object motion condition. The present invention establishes a floating object drag force prediction model according to the water flow velocity and the floating object motion condition, which helps to improve the prediction accuracy and enhance the model practicality, and helps to accurately analyze the risk of floating objects colliding with bridges.

[0013] Optionally, the floating object drag force prediction model satisfies the following relationship:

[0014]

[0015] in, It represents the drag force of flood on floating objects. represents the density of floating objects, It represents the surface area of ​​the floating object in contact with the water. represents the floating object velocity conversion coefficient, Indicates the water flow velocity, is the Reynolds number, The model of the present invention comprehensively considers multiple factors such as the physical properties of floating objects, water flow velocity, Reynolds number and collision angle, and can more accurately predict the drag force of floating objects in floods.

[0016] Optionally, the bridge damage assessment mechanism is set based on the flood season floating object data and river hydrological information, and the assessment parameter analysis results are obtained according to the bridge damage assessment mechanism, including: setting bridge damage assessment parameters based on the flood season floating object data and river hydrological information, the bridge damage assessment parameters including bridge structure deformation, collision impact force, floating object mass, water flow velocity, bridge stiffness and bearing friction coefficient; setting the bridge damage assessment mechanism in combination with the bridge structure deformation, the collision impact force, the floating object mass, the water flow velocity, the bridge stiffness and the bearing friction coefficient; obtaining the assessment parameter analysis results based on the bridge damage assessment mechanism. The bridge damage assessment mechanism of the present invention integrates the flood season floating object data, river hydrological information and bridge physical characteristics, so that the assessment mechanism can comprehensively consider bridge damage factors, thereby improving the accuracy and feasibility of the assessment results.

[0017] Optionally, the deformation of the bridge structure satisfies the following relationship:

[0018]

[0019] in, represents the deformation of the bridge structure, Indicates the critical value of the deformation of the bridge structure;

[0020] The collision impact force satisfies the following relationship:

[0021]

[0022] in, The impact force of the collision, represents the friction coefficient, Indicates positive pressure;

[0023] The mass of the floating object satisfies the following relationship:

[0024]

[0025] in, Indicates the mass of floating objects, represents the mean of the normal distribution of floating mass, represents the standard deviation of the mass of floating objects;

[0026] The water flow velocity satisfies the following relationship:

[0027]

[0028] in, Indicates the water flow velocity, represents the mean of the normal distribution of water velocity, represents the standard deviation of water velocity;

[0029] The bridge stiffness satisfies the following relationship:

[0030]

[0031] in, represents the stiffness of the bridge structure, represents the mean of the normal distribution of bridge stiffness, represents the standard deviation of bridge stiffness;

[0032] The bearing friction coefficient satisfies the following relationship:

[0033]

[0034] in, is the bearing friction coefficient, represents the mean of the normal distribution of the bearing friction coefficient, Represents the standard deviation of the bearing friction coefficient.

[0035] The present invention sets a clear parameter calculation formula to provide a quantitative standard for bridge damage assessment, making the assessment result more objective and accurate, wherein the randomness and uncertainty of different parameters are fully considered, further improving the robustness and applicability of the probabilistic failure assessment method.

[0036] Optionally, the establishing the probabilistic failure judgment model includes: establishing the probabilistic failure judgment model according to a Monte Carlo simulation framework;

[0037] The probabilistic failure judgment model satisfies the following relationship:

[0038]

[0039] in, represents the failure probability of bridge structure deformation, represents the indicator function, represents the deformation of the bridge structure, represents the critical value of the deformation of the bridge structure, Indicates the number of simulations;

[0040]

[0041] in, represents the sliding failure probability of the bridge structure, represents the indicator function, The impact force of the collision, represents the friction coefficient, Indicates positive pressure, Indicates the number of simulations;

[0042]

[0043] in, represents the probability of failure of the bearing capacity of the bridge structure, represents the failure probability of bridge structure deformation, represents the sliding failure probability of the bridge structure.

[0044] The present invention establishes a probabilistic failure judgment model that can more accurately evaluate the failure risk of bridge structures under specific conditions, helps to more comprehensively consider the impact of various uncertainties and random factors on the bearing capacity of bridge structures, and realizes accurate evaluation of probabilistic failures.

[0045] In the second aspect, the present invention also provides a probabilistic failure assessment system for floating objects hitting bridges during flood season, which can efficiently execute the probabilistic failure assessment method for floating objects hitting bridges during flood season provided by the present invention, and the above system includes an input device, a processor, an output device and a memory, wherein the input device, the processor, the output device and the memory are interconnected, the above memory includes a computer-readable storage medium as described in the first aspect of the present invention, the above memory is used to store a computer program, the above computer program includes program instructions, and the above processor is configured to call program instructions. The probabilistic failure assessment system for floating objects hitting bridges during flood season provided by the present invention has a compact structure, strong applicability, and greatly improves the operating efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a flow chart of the probabilistic failure assessment method of floating objects hitting bridges during flood season of the present invention;

[0047] Figure 2 It is a structural schematic diagram of the probabilistic failure assessment system for floating objects impacting bridges during flood season according to the present invention. DETAILED DESCRIPTION

[0048] The specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described herein are only for illustration and are not intended to limit the present invention. In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present invention. However, it is obvious to those of ordinary skill in the art that these specific details do not need to be adopted to implement the present invention. In other examples, in order to avoid confusing the present invention, known circuits, software or methods are not specifically described.

[0049] Throughout the specification, references to "one embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in conjunction with the embodiment or example is included in at least one embodiment of the present invention. Therefore, the phrases "in one embodiment," "in an embodiment," "an example," or "an example" appearing in various places throughout the specification do not necessarily all refer to the same embodiment or example. In addition, particular features, structures, or characteristics may be combined in one or more embodiments or examples in any suitable combination and / or subcombination. In addition, it should be understood by those of ordinary skill in the art that the figures provided herein are for illustrative purposes and that the figures are not necessarily drawn to scale.

[0050] See also Figure 1 In order to fully understand the failure mechanism caused by floating objects hitting bridges, a comprehensive evaluation and prediction is conducted from multiple dimensions such as physical mechanism, mechanical principle and probability statistics. On this basis, the damage risk that the bridge may suffer under different water flow conditions and floating object characteristics is evaluated, which can more accurately evaluate the safety performance of bridges in various complex environments and provide a more scientific basis for bridge design, maintenance and risk management. The present invention provides a probabilistic failure assessment method for floating objects hitting bridges during flood season, and the above method includes the following steps:

[0051] S1. Collect the floating object data and river hydrological information during the flood season, and obtain the water flow velocity and floating object movement status based on the above floating object data and river hydrological information during the flood season. The implementation steps and specific contents are as follows:

[0052] First, collect floating object data and river hydrological information during the flood season.

[0053] In order to fully understand the dynamic characteristics and hydrological information of floating objects in the river during the flood season, systematic data collection was carried out. The above process covers a wide range of information, including but not limited to the type, quantity, size, density of floating objects, and their distribution and movement patterns in the water flow. At the same time, the river water level, flow rate, flow rate and other possible hydrological phenomena such as eddies and backflows were recorded. The probabilistic failure assessment method combines monitoring technology and data analysis methods to ensure the accuracy and comprehensiveness of the collected data, thereby providing a solid data foundation for subsequent bridge damage assessment and risk management work.

[0054] Then, based on the above-mentioned flood season floating object data and river hydrological information, a water flow velocity analysis function and a floating object motion analysis equation are established; the floating object movement and water flow analysis model can be obtained by combining the water flow velocity analysis function and the floating object motion analysis equation; and the water flow velocity and floating object movement conditions are obtained through the above-mentioned floating object movement and water flow analysis model.

[0055] Since the movement of floating objects during the flood season does not exist in isolation, it is affected by the water velocity, flow direction and physical properties of the floating objects, such as mass and shape. In order to more accurately describe the relevant phenomena, the embodiment introduces a velocity field and combines the motion equations of the floating objects to form a comprehensive and dynamic analysis model. The above model not only takes into account the driving effect of the water flow on the floating objects, but also fully considers the movement characteristics and resistance factors of the floating objects themselves, thereby providing a more detailed and accurate floating object motion simulation mechanism and analysis results.

[0056] Based on the water flow velocity field, we can know that the water flow velocity It is determined by hydrodynamic simulation technology. In the embodiment, the fluid motion is described based on the Navier-Stokes equation, and the water flow is modeled and analyzed in two or three dimensions. The established water flow velocity analysis function can capture the complex dynamic behavior in the water flow, including but not limited to turbulence, vortex, etc., so as to accurately describe the water flow velocity field, so that the water flow velocity at any position in the water body at different times can be fully understood, providing a solid data foundation for the subsequent analysis of floating object movement.

[0057] The above water flow velocity analysis function satisfies the following relationship:

[0058]

[0059] in, Indicates the water flow velocity, represents the change of the equation over time, represents the gradient operator, represents the density of water, represents the pressure field, Represents the pressure field The gradient of represents the dynamic viscosity of water, Indicates water flow speed The Laplace operator of Represents the external force term.

[0060] Water flow velocity is a vector that contains the components of the water flow in different directions, x, y, and z, and can describe the speed and direction of flow at any location in the water body.

[0061] The change of the equation over time can also be expressed as time is a key variable in the water flow velocity analysis function, which further reveals the change of fluid dynamics over time.

[0062] The gradient operator can also be called the nabla operator or del operator. It is a vector differential operator that can be used to represent the gradient of the water velocity analysis function in space, that is, the rate and direction of change of the function value with the spatial coordinates. In fluid dynamics, it can be used to calculate the rate of change of physical quantities such as velocity and pressure in space, that is, the gradient, and then reveal that the physical quantity increases or decreases with the change of spatial coordinates.

[0063] The density of water is one of the basic properties of matter. Density determines the mass of matter per unit volume and is one of the key parameters necessary for calculating pressure gradient, momentum change, etc.

[0064] The pressure field is a scalar field that describes the pressure at any position in the water body. The pressure field is one of the important physical quantities in fluid dynamics, which affects the flow direction and speed of the fluid.

[0065] The gradient of the pressure field is a vector that reveals how pressure varies in space and is one of the key factors that produce acceleration or force in the fluid dynamics equations.

[0066] Hydrodynamic viscosity is a measure of the internal friction of a fluid. The above dynamic viscosity determines the smoothness of fluid flow and is crucial for distinguishing between laminar flow and turbulent flow, calculating fluid resistance, etc.

[0067] The Laplace operator of water velocity is the gradient or second-order derivative of the gradient. In fluid dynamics, the Laplace operator can be used to describe the diffusion or dissipation process of fluid velocity and is a key parameter in the water velocity analysis function to describe the fluid viscosity effect.

[0068] The external force term includes all external forces acting on the fluid, such as gravity, buoyancy, wind force, etc. The above external forces are one of the important factors driving the movement of the fluid.

[0069] In summary, the water flow velocity analysis function describes the dynamic behavior of water flow by comprehensively considering multiple aspects such as time changes, spatial gradients, physical properties and external forces. This analysis function has wide application value.

[0070] The movement trajectory of floating objects in water is the manifestation of the interaction between the drag force of the water flow and the inertia force of the floating objects themselves. The drag force shows the direct influence of the water flow on the floating objects, pushing the floating objects to move along the path of the water flow; while the inertia force is the inherent tendency of the floating objects to maintain their original state of motion or move in a straight line at a uniform speed.

[0071] In order to more accurately describe the movement process of floating objects, the embodiment takes into account the shape, size, density of the floating objects and the speed and direction of the water flow, and the influence of the magnitude and direction of the drag force. The above physical quantities are incorporated into the framework of Newton's second law and then the floating object motion analysis equation is established to simulate the actual movement of the floating objects in the water flow.

[0072] The above floating object motion analysis equation satisfies the following relationship:

[0073]

[0074] in, Indicates the mass of the floating object, represents the speed of the floating object, represents the change of velocity with time, represents the drag force of floating objects, The buoyancy of floating objects, Represents the gravity of floating objects.

[0075] The mass of floating objects is one of the basic properties of an object, which is the amount of matter it contains. In the process of analyzing the motion of floating objects, the mass determines the degree of response of the floating objects to external forces, that is, the magnitude of inertia.

[0076] The velocity of a floating object is a vector that describes the displacement of the floating object in a certain direction per unit time. In the floating object motion analysis equation, the velocity changes with time, indicating that the motion state of the floating object is dynamic.

[0077] Time is the independent variable of speed changing with time. In the process of floating object motion analysis, time can describe the change process of floating object motion state with time.

[0078] The drag force of floating objects is the resistance generated by the fluid on the moving object, which can slow down the movement of the object. The magnitude of the above drag force is related to factors such as the speed and density of the fluid, the shape and size of the object, etc. In the analysis process of the movement of floating objects, the drag force is one of the important factors affecting the movement state of floating objects.

[0079] The drag force of the above floating objects satisfies the following relationship:

[0080]

[0081] in, represents the drag force of floating objects, represents the density of floating objects, represents the drag coefficient, It represents the surface area of ​​the floating object in contact with the water. Indicates water flow speed.

[0082] The above drag coefficient is significantly affected by the Reynolds number. In a complex fluid environment such as a flood, the flow state is extremely turbulent, and the velocity and pressure fields fluctuate violently over time and space, which not only generates a large number of eddies, but also leads to significant energy dissipation. When the Reynolds number rises above 4000, the fluid can be regarded as turbulent, and floods, due to their characteristics, are often classified into the category of turbulent models.

[0083] On the other hand, there are significant differences between the drag coefficients of different floating objects. For common floating objects with regular shapes, such as spherical floating objects or logs, their drag coefficients can be estimated with the help of a specific formula, which is derived based on fluid dynamics theory and experimental data, and provides an accurate and practical method for the embodiment to predict the stress conditions of different floating objects in floods.

[0084] The above resistance coefficient satisfies the following relationship:

[0085]

[0086] in, represents the drag coefficient, Reynolds number.

[0087] The Reynolds number is a dimensionless number used to describe the flow characteristics of a fluid. It is mainly defined based on the ratio of the inertial force to the viscous force of the fluid and can be used to distinguish between laminar flow and turbulent flow.

[0088] The buoyancy of a floating object is the upward force exerted by a fluid on an object immersed in it, and its magnitude is equal to the weight of the fluid displaced by the object. In the analysis of the motion of floating objects, buoyancy is the key factor that determines whether a floating object can float on the water surface. When the buoyancy is greater than or equal to the gravity of the floating object, the floating object will remain on the water surface or move near the water surface; when the buoyancy is less than the gravity, the floating object will sink.

[0089] The gravity of floating objects is the attraction of the earth on objects, which accelerates the objects toward the center of the earth. In the process of analyzing the motion of floating objects, gravity causes floating objects to sink. However, gravity does not necessarily cause floating objects to sink due to the existence of buoyancy; floating objects will only sink when gravity is greater than buoyancy.

[0090] Floating objects tend to reach a nearly steady state in a flood, mainly because the vertical forces they are subjected to reach a dynamic equilibrium state. That is, floating objects will neither continue to rise nor sink in the water, but will maintain a relatively stable height, mainly because a balance is reached between buoyancy, gravity and other possible vertical forces, and the above balance relationship needs to satisfy the following relationship:

[0091]

[0092] in, represents the gravity of the floating object, Indicates the buoyancy of floating objects.

[0093] Further analysis shows that factors such as floating object mass, speed, time and drag force satisfy the following relationship:

[0094]

[0095] in, Indicates the mass of the floating object, represents the speed of the floating object, represents the change of velocity with time, Indicates the drag force of floating objects.

[0096] The floating object motion analysis equation of this embodiment describes the dynamic equilibrium state of the floating object in a water flow or other fluid environment by comprehensively considering the mass, speed, time, drag force, buoyancy and gravity of the floating object. The above equation provides an important mathematical tool for understanding and predicting the motion behavior of the floating object.

[0097] Utilizing the floating object data collected during the flood season and the corresponding river hydrological information, the water velocity analysis function and the floating object motion analysis equation provide an analytical method for in-depth understanding of water flow characteristics and the dynamic behavior of floating objects.

[0098] The water flow velocity analysis function can accurately calculate the water flow velocity distribution based on the river hydrological information; the floating object motion analysis equation combines the physical properties of the floating objects and the various forces exerted on them by the water flow, so as to accurately predict the movement trajectory and speed of the floating objects in the water. The floating object motion and water flow analysis model can simulate the change of water flow velocity and accurately reflect the movement state of the floating objects under specific water flow conditions. It has important utilization value for flood warning, floating object cleaning and river ecological management.

[0099] Furthermore, in the present embodiment, the analysis method of the water flow velocity and the movement status of floating objects is only an optional condition of the present invention. In one or some other embodiments, the analysis method of the water flow velocity and the movement status of floating objects can be adjusted according to the actual situation of the water flow during the flood season and the application requirements of the evaluation method. By adjusting the analysis method, it can better adapt to the water flow characteristics of different rivers and different flood seasons, as well as the accuracy and real-time requirements under different evaluation needs, so that the analysis method of the present invention has a high degree of flexibility and scalability.

[0100] S2. Establish a floating object drag force prediction model based on the water flow velocity and the movement of floating objects, and analyze the drag force generated by floods on floating objects based on the above floating object drag force prediction model. The specific steps and implementation contents are as follows:

[0101] In this embodiment, the water flow velocity is obtained by the water flow velocity analysis function, and the floating object motion condition is obtained based on the floating object motion analysis equation; then, a floating object drag force prediction model is established by combining the water flow velocity and the floating object motion condition.

[0102] In the embodiment, the water velocity analysis function is used to analyze the dynamic change of water velocity. At the same time, the motion trajectory and state of the floating object in the water are described by the floating object motion analysis equation. When the floating object finally interacts with the bridge, it can be reasonably assumed that the drag force exerted by the flood on the floating object is almost equal to the collision force exerted by the floating object on the bridge.

[0103] When the floating object comes into contact with the bridge, the drag force of the flood on the floating object is recorded as , the collision force exerted by floating objects on the bridge is recorded as , and the drag force and collision force satisfy the following relationship:

[0104]

[0105] in, It represents the drag force of flood on floating objects. It represents the drag force of floating objects. Based on this, the relationship between the interaction forces among floods, floating objects and bridges is intuitively revealed, providing an important basis for further analyzing the stress conditions of bridges and evaluating their safety.

[0106] It is further necessary to consider the effect of the collision angle on the drag force of floating objects. At this time, the drag force of the flood on the floating objects needs to satisfy the following relationship:

[0107]

[0108] in, It represents the drag force of flood on floating objects. represents the density of floating objects, It represents the surface area of ​​the floating object in contact with the water. Indicates the water flow velocity, represents the drag coefficient, Indicates the collision angle.

[0109] Based on the proportional relationship between the speed of floating objects and the speed of water flow, the floating object speed conversion coefficient is introduced in the embodiment. Considering the actual situation of the collision between floating objects and bridges, in order to improve the accuracy of calculation, the speed of floating objects used in the embodiment is not simply the speed of water flow. From experimental observation and data analysis, it can be seen that there is a certain proportional relationship between the speed of floating objects and the speed of water flow. The above relationship can be described by relevant mathematical expressions, and the following relationship needs to be satisfied;

[0110]

[0111] in, Indicates the speed of floating objects. represents the floating object velocity conversion coefficient, Indicates water flow speed.

[0112] The speed of floating objects reflects the actual movement speed of floating objects in the water flow.

[0113] The floating object velocity conversion coefficient is a key coefficient that measures the degree to which the floating object velocity is magnified or reduced relative to the water flow velocity.

[0114] Water flow velocity refers to the speed at which flood water flows in a river channel.

[0115] For specific information on the floating object velocity conversion coefficient in this embodiment, please refer to Table 1.

[0116] Table 1 Information table of floating object velocity conversion coefficient

[0117]

[0118] Based on the information in Table 1, it can be seen that for floating objects with lower density, such as foam plastics, their movement state in water is closer to complete floating, so their speed is often very close to the water flow speed. This is because the buoyancy of the water on these floating objects is large, enough to support most or all of their weight, allowing them to move smoothly with the water flow.

[0119] However, when the density of the floating object is so high that part or most of it is submerged in the water, the situation is different. At this time, the floating object will experience greater water resistance, which will cause its speed to be reduced relative to the speed of the water flow, because the part submerged in the water will increase the contact area with the water, thereby increasing friction and resistance, making it difficult for the floating object to maintain the same speed as the water flow.

[0120] To sum up, the speed of floating objects is not only affected by the water flow speed, but also closely related to its own density and floating state in the water. Floating objects with lower density are more likely to move with the water flow, while floating objects with higher density may have their speed reduced due to the increase in water resistance.

[0121] Based on the information in Table 1, the impact force of floating objects on the bridge satisfies the following relationship:

[0122]

[0123] in, It represents the drag force of flood on floating objects. represents the density of floating objects, It represents the surface area of ​​the floating object in contact with the water. Indicates the speed of floating objects. represents the drag coefficient, Indicates the collision angle.

[0124] Based on the above information and analysis function, a floating object drag force prediction model of this embodiment is established, and the following relationship needs to be satisfied:

[0125]

[0126] in, It represents the drag force of flood on floating objects. represents the density of floating objects, It represents the surface area of ​​the floating object in contact with the water. represents the floating object velocity conversion coefficient, Indicates the water flow velocity, is the Reynolds number, Indicates the collision angle.

[0127] In order to evaluate the drag force of flood on floating objects, a floating object drag force prediction model is constructed in the embodiment, and the model comprehensively considers multiple key parameters. First, the drag force is the main force of the flood on the floating objects, which determines the movement state of the floating objects in the water flow. The density of the floating objects is introduced into the prediction model, where density is an important factor affecting the drag force. The greater the density, the stronger the interaction between the floating objects and the water, which may generate a greater drag force.

[0128] In addition, the surface area of ​​the floating object in contact with the water is also an important parameter. The larger the surface area, the greater the impact of the water flow on the floating object, so the drag force will increase accordingly. At the same time, the floating object speed conversion coefficient is taken into account, which reflects the degree of scaling of the floating object speed relative to the water flow speed. The above coefficient is crucial for accurately predicting the drag force and can affect the actual movement speed of the floating object in the water flow.

[0129] At the same time, the Reynolds number is also introduced to describe the state of water flow. The Reynolds number is a dimensionless parameter that reflects the ratio of inertial force to viscous force in water flow. The size of the Reynolds number will affect the flow characteristics of the water flow, thereby affecting the drag force on the floating object. Finally, the collision angle describes the angle between the floating object and the direction of the water flow. Different collision angles will affect the direction and size of the impact force of the water flow on the floating object, thereby affecting the drag force.

[0130] In summary, the floating object drag force prediction model comprehensively considers multiple factors such as the density of the floating objects, the surface area in contact with water, the velocity conversion coefficient, the water flow velocity, the Reynolds number and the collision angle. This model can more accurately predict the drag force generated by floods on floating objects, providing strong support for related engineering design and risk assessment.

[0131] Furthermore, the analysis method of the dragging force of floating objects in the present embodiment is only an optional condition of the present invention. In one or some other embodiments, the analysis method of the dragging force of floating objects can be optimized according to the actual analysis needs of the floating objects and the actual dragging force conditions. As the types of floating objects and water flow conditions continue to change, the present invention can adjust the analysis method at any time to adapt to new situations, so that the probabilistic failure assessment method of floating objects hitting bridges during flood season can be applied to different types of floating objects and water flow environments.

[0132] S3. A bridge damage assessment mechanism is set based on the floating debris data and river hydrological information during the flood season, and the assessment parameter analysis results are obtained according to the above bridge damage assessment mechanism. The specific steps and implementation contents are as follows:

[0133] Based on the above-mentioned flood season floating object data and river hydrological information, bridge damage assessment parameters are set. In the embodiment, the bridge damage assessment parameters mainly include the deformation of the bridge structure, collision impact force, the mass of the floating objects, the water flow velocity, the bridge stiffness and the bearing friction coefficient; and the bridge damage assessment mechanism is set in combination with the deformation of the bridge structure, collision impact force, the mass of the floating objects, the water flow velocity, the bridge stiffness and the bearing friction coefficient; based on the above-mentioned bridge damage assessment mechanism, the assessment parameter analysis results can be obtained.

[0134] Definition and selection of evaluation parameters.

[0135] First, based on the characteristics of floating objects during the flood season, such as size, material, density, etc., and river hydrological information, such as water level changes, flow velocity, flow direction, etc., a series of key evaluation parameters are selected in the embodiment, based on which the damage that floating objects may cause to bridges can be fully reflected. The relevant contents of the above parameters are as follows:

[0136] The deformation of the bridge structure can measure the degree of deformation of the bridge when it is impacted by floating objects and is an important indicator for evaluating the integrity of the bridge structure.

[0137] The collision impact force is the force generated when the floating object collides with the bridge structure, which is directly related to the stress state of the bridge structure.

[0138] The mass of floating objects will affect their kinetic energy, which in turn affects the magnitude of the impact force during a collision.

[0139] The speed of the water flow not only affects the speed and direction of movement of floating objects, but may also intensify or ease the severity of the collision.

[0140] The stiffness of a bridge structure determines its ability to resist deformation and is a key factor in assessing the damage sensitivity of a bridge.

[0141] The bearing friction coefficient, that is, the friction coefficient between the bearing and the pier, affects the overall stability of the bridge and is crucial to assessing the safety of the bridge under extreme conditions.

[0142] Setting up the bridge damage assessment mechanism

[0143] After determining the above-mentioned assessment parameters, a bridge damage assessment mechanism was further established in combination with the flood season floating debris data and river hydrological information. This mechanism comprehensively considers the interaction between various parameters and their contribution to bridge damage. Through mathematical modeling and simulation analysis, a quantitative assessment of the degree of bridge damage can be achieved.

[0144] Data collection and preprocessing: Clean, integrate and standardize flood season floating object data and river hydrological information to ensure data accuracy and consistency.

[0145] Model construction: Based on the principles of physical mechanics, the calculation function and analysis model of the evaluation parameters are constructed to simulate the impact process of floating objects on the bridge under different conditions.

[0146] Parameter input and calculation: By inputting the preprocessed data into the corresponding calculation formula or model, key indicators such as bridge structure deformation and collision impact force can be obtained.

[0147] Damage assessment: Based on parameters such as bridge stiffness and bearing friction coefficient, statistical and machine learning algorithms are used to grade the damage degree of the bridge.

[0148] Result output and interpretation: A detailed assessment report is generated based on the above bridge damage assessment mechanism, including but not limited to the degree of bridge damage, potential risk areas and recommended maintenance measures.

[0149] The specific calculation formulas for different bridge damage assessment parameters in the bridge damage assessment mechanism are as follows:

[0150] The deformation of the bridge structure satisfies the following relationship:

[0151]

[0152] in, represents the deformation of the bridge structure, Indicates the critical value of the deformation of the bridge structure;

[0153] The deformation of a bridge structure refers to the displacement or deformation degree of the bridge structure relative to its original undeformed state under the action of a specific load such as the impact of floating objects. The above deformation can be measured by various means such as displacement sensors, laser rangefinders, etc., which is conducive to real-time monitoring or post-measurement.

[0154] The critical value of the deformation of the bridge structure can also be called the maximum allowable deformation or limit deformation. It can be determined based on factors such as the design specifications of the bridge, material properties, structural type, and expected service life. When the actual deformation of the bridge structure exceeds the above critical value, it means that the structural safety of the bridge is seriously threatened and needs to be inspected, repaired or reinforced in a timely manner.

[0155] In practical applications, monitoring and evaluation of bridge structure deformation is an important part of bridge maintenance and management. Through regular or real-time deformation monitoring, abnormal deformation of bridge structures can be discovered in time, so that corresponding measures can be taken to prevent or reduce potential damage risks. At the same time, for different types of bridges and different use conditions, the critical value of bridge structure deformation will also be different, and it is necessary to set and adjust it scientifically and reasonably according to the specific situation.

[0156] The collision impact force satisfies the following relationship:

[0157]

[0158] in, The impact force of the collision, represents the friction coefficient, Indicates positive pressure;

[0159] The impact force refers to the interaction force generated by the floating object or other impacting object and the bridge structure during the collision process. The impact force is one of the main factors causing damage to the bridge structure. Its magnitude depends on the mass, speed, shape of the floating object and the stiffness and damping characteristics of the bridge structure. In practical applications, the measurement of the impact force can be carried out using sensors or dynamic analysis software for measurement and analysis.

[0160] The friction coefficient represents the ratio between the resistance and the normal pressure generated when two contact surfaces move relative to each other or attempt to move relative to each other. In collision problems, the friction coefficient can be used to describe the friction characteristics between the contact surface of floating objects and bridge structures. The friction coefficient is affected by many factors, such as the material, roughness, humidity, temperature, etc. of the contact surface.

[0161] Normal pressure refers to the force perpendicular to the contact surface generated by the mutual compression of floating objects and bridge structures during the collision process. The magnitude of normal pressure depends on factors such as the mass and speed of the floating objects and the stiffness of the bridge structure. In the collision problem, normal pressure is one of the key factors that determine the magnitude of friction and collision impact force.

[0162] The above relationship describes the dynamic conditions during a collision. When the impact force exceeds the threshold determined by the friction coefficient and the normal pressure, it may cause damage or destruction of the bridge structure.

[0163] The mass of floating objects satisfies the following relationship:

[0164]

[0165] in, Indicates the mass of floating objects, represents the mean of the normal distribution of floating mass, represents the standard deviation of the mass of floating objects;

[0166] The mass of floating objects refers to the amount or weight of the material in the floating objects, and is one of the key factors in the potential impact force of floating objects on bridge structures. The greater the mass of floating objects, the greater the impact force generated when they hit the bridge structure, thus posing a greater threat to the safety of the bridge structure.

[0167] The mean of the normal distribution of floating mass. In statistics, the normal distribution is a continuous probability distribution with a bell-shaped curve shape, and the mean represents the center position or average level of the distribution. In the above expression, It represents the mean or central tendency of all floating material mass data, and thus reflects the typical or expected value of floating material mass.

[0168] The standard deviation of the normal distribution of floating mass. The standard deviation is an important indicator to measure the degree of dispersion of data distribution, which represents the average distance between the data points and the mean. In the above expression It indicates the degree of discreteness or variation of the floating object mass data, and further reflects the difference in the floating object mass between different individuals.

[0169] Based on the above floating object mass analysis function, it can be seen that the mass of floating objects obeys a law: is the mean value, is a normal distribution with a standard deviation, which means that if a floating object is randomly selected, its mass is likely to be close to , and with As the distance increases, the probability of its appearance will gradually decrease, forming a symmetrical bell-shaped distribution, which can predict the impact force of floating objects of different masses on the bridge structure, and thus provide a scientific basis for the maintenance and management of the bridge.

[0170] The water flow velocity satisfies the following relationship:

[0171]

[0172] in, Indicates the water flow velocity, represents the mean of the normal distribution of water velocity, represents the standard deviation of water velocity;

[0173] Water velocity refers to the actual speed of water flow in a river. Water velocity is an important factor affecting the movement, direction and impact force of floating objects on bridge structures. The faster the water velocity, the greater the thrust on floating objects and the greater the kinetic energy when they hit the bridge, causing greater damage to the bridge structure.

[0174] The mean of a normal distribution of water velocity. In this statistical model, the mean represents the central tendency or average level of all observed water velocity data, and thus reflects the typical or expected value of water velocity in a river over a period of time or under specific conditions.

[0175] The standard deviation of the normal distribution of water velocity is an indicator of the degree of dispersion of water velocity data distribution, which represents the average difference between each water velocity observation and the mean. The larger the standard deviation, the higher the degree of variation of water velocity, that is, the greater the difference between water velocity at different times or different locations.

[0176] Based on the water flow velocity analysis function, it can be seen that if a time point or location is randomly selected to measure the water flow velocity, its value is very likely to be close to , and with As the distance increases, the probability of its appearance will gradually decrease.

[0177] Understanding the normal distribution characteristics of water velocity is crucial to assessing the safety of bridge structures during flood seasons. By long-term monitoring and analysis of river water velocity data, we can obtain and The specific value of the floating objects can be used to predict the impact force and impact that floating objects may have on the bridge structure under different water flow speeds, which will help to formulate targeted bridge maintenance strategies and ensure the safe operation of bridges under extreme weather conditions.

[0178] The bridge stiffness satisfies the following relationship:

[0179]

[0180] in, represents the stiffness of the bridge structure, represents the mean of the normal distribution of bridge stiffness, represents the standard deviation of bridge stiffness;

[0181] The stiffness of a bridge structure is an important physical quantity that measures the ability of a bridge structure to resist deformation. It describes the ability of a bridge to maintain its shape and size when subjected to external forces. The greater the stiffness of a bridge, the stronger its ability to resist deformation and the more stable its structure.

[0182] The mean of the normal distribution of bridge stiffness represents the central trend or average level of all observed bridge stiffness data, which reflects the typical or expected value of bridge stiffness under the same conditions. By calculating and analyzing the stiffness data of a large number of bridges, the mean of bridge stiffness can be obtained, thereby understanding the overall performance of the bridge structure.

[0183] The standard deviation of the normal distribution of bridge stiffness is an indicator of the degree of dispersion of the bridge stiffness data distribution, which represents the average difference between the observed values ​​of each bridge stiffness and the mean. The larger the standard deviation, the higher the degree of variation of bridge stiffness, that is, the greater the difference in stiffness between different bridges or the same bridge under different conditions.

[0184] The analytical function of bridge stiffness indicates that the stiffness of the bridge structure obeys a is the mean value, The standard deviation of the normal distribution indicates that if a bridge or a bridge structure condition is randomly selected to measure its stiffness, its value is likely to be close to , and with As the distance increases, the probability of its appearance will gradually decrease.

[0185] Understanding the normal distribution characteristics of bridge stiffness is of great significance for the design, evaluation and maintenance of bridge structures. By collecting and analyzing a large amount of bridge stiffness data, the stability and safety of bridge structures can be evaluated, which helps to formulate targeted bridge maintenance strategies and improve the durability and service life of bridges.

[0186] The friction coefficient of the bearing satisfies the following relationship:

[0187]

[0188] in, is the bearing friction coefficient, represents the mean of the normal distribution of the bearing friction coefficient, Represents the standard deviation of the bearing friction coefficient.

[0189] The mean of the normal distribution of the bearing friction coefficient represents the central tendency or average level of all observed bearing friction coefficient data, which reflects the typical or expected value of the bearing friction coefficient under the same conditions. It is an important indicator for evaluating the overall performance of the bearing friction coefficient, and can further understand the friction characteristics of the bearing under different conditions.

[0190] The standard deviation of the normal distribution of the bearing friction coefficient is an indicator to measure the degree of dispersion of the bearing friction coefficient data distribution. It represents the average difference between the observed values ​​of each bearing friction coefficient and the mean. The larger the value, the higher the variation of the bearing friction coefficient, that is, the greater the difference in friction coefficient between different bearings or the same bearing under different conditions.

[0191] Based on the above bridge damage assessment mechanism, comprehensive and accurate assessment parameter analysis results can be obtained. The analysis results of different assessment parameters not only help to timely discover the potential damage of the bridge, but also provide a scientific basis for subsequent bridge maintenance, reinforcement and renovation.

[0192] Furthermore, the method for constructing the bridge damage assessment mechanism in the present embodiment is only an optional condition of the present invention. In one or some other embodiments, the method for constructing the bridge damage assessment mechanism can be optimized according to the actual analysis needs of probabilistic failures and the actual situation of bridge damage. It can be more flexibly adapted to different types of bridges, different damage conditions and different analysis needs. At the same time, the optimized assessment mechanism can more accurately reflect the actual damage status of the bridge, thereby improving the accuracy of damage assessment, helping to more accurately understand the safety status of the bridge and take corresponding maintenance or repair measures.

[0193] S4. Establish a probabilistic failure judgment model, combine the above probabilistic failure judgment model, drag force, evaluation parameter analysis results and flood season floating object data and river hydrological information to obtain probabilistic failure assessment results, so as to achieve the risk prediction and assessment of floating objects hitting bridges during the flood season. The implementation steps and related contents are as follows:

[0194] In order to evaluate the failure probability of a bridge under the impact of floating objects, an evaluation method based on probability theory and Monte Carlo simulation is proposed in the embodiment. The core of the evaluation method is to construct a probabilistic model that can reflect the impact force of floating objects and its influencing factors, and estimate the probability of failure events through simulation, that is, to establish a probabilistic failure judgment model of the embodiment.

[0195] The calculation of the impact force of floating objects in the probabilistic failure judgment model is a key implementation step. In the embodiment, the above-mentioned floating object drag force prediction model is used to calculate the drag force of flood on floating objects, and the following relationship is satisfied: ,The prediction model takes into account factors such as the mass, speed, shape of floating objects and the structural characteristics of the bridge, and treats the relevant factors as random variables and assigns them corresponding probability distributions, and uses Monte Carlo simulation to generate a large number of impact force samples.

[0196] Based on the calculation result of the impact force of the floating object, i.e., the dragging force in the embodiment, a probabilistic failure judgment model is constructed. The core of the above model is to set a failure threshold. When the impact force of the floating object exceeds this threshold, it can be considered that the bridge will fail. In order to evaluate the failure probability, a large number of impact force samples are generated by Monte Carlo simulation in the embodiment, and the failure indicator variable corresponding to each sample, i.e., whether the impact force exceeds the failure threshold, is calculated. Finally, it is necessary to count the proportion of samples where the failure indicator variable is 1, i.e., the failure occurs. The above proportion result is the failure probability required by the embodiment.

[0197] In the embodiment, a probabilistic failure judgment model is established based on the Monte Carlo simulation framework; the probabilistic failure judgment model satisfies the following relationship:

[0198]

[0199] in, represents the failure probability of bridge structure deformation, represents the indicator function, represents the deformation of the bridge structure, represents the critical value of the deformation of the bridge structure, Indicates the number of simulations;

[0200] The probability of failure due to deformation of a bridge structure refers to the probability that the deformation of a bridge structure exceeds the maximum allowable deformation when it is subjected to external forces such as impact from floating objects. Deformation failure is an important form of failure of bridge structures, which can lead to a decrease in the stability of the bridge structure or loss of its function.

[0201] In the probabilistic failure judgment model, the indicator function can be used to determine whether an event occurs. If the event occurs, such as the deformation of the bridge exceeds the critical value, the indicator function value is 1; if the event does not occur, the indicator function value is 0.

[0202] The deformation of a bridge structure refers to the change in shape of the bridge structure when it is subjected to external forces. The above deformation is one of the important indicators for evaluating the performance of a bridge structure, and its size reflects the structure's ability to resist deformation.

[0203] The critical value of the deformation of the bridge structure refers to the maximum deformation allowed by the bridge structure. If this value is exceeded, it is considered that the structure has deformed and failed. The critical value in the embodiment can be determined and adjusted according to factors such as the design requirements, use conditions and safety of different bridges.

[0204] In Monte Carlo simulation, the number of simulations refers to the number of random sampling and calculations. The more simulations are performed, the closer the results are to the actual situation.

[0205]

[0206] in, represents the sliding failure probability of the bridge structure, represents the indicator function, The impact force of the collision, represents the friction coefficient, Indicates positive pressure, Indicates the number of simulations;

[0207] The probability of bridge structure slip failure refers to the probability of the bridge structure slipping due to insufficient friction when subjected to external force. Slip failure will lead to a decrease in the stability and safety of the bridge structure.

[0208] The impact force of a collision refers to the impact force generated when a floating object collides with a bridge structure. The magnitude of the impact force depends on factors such as the mass, speed, shape of the floating object and the material, shape and stiffness of the bridge structure.

[0209] The friction coefficient refers to the friction coefficient between the bridge structure and the supporting surface, which reflects the ability of the structure to resist slippage when subjected to external forces. The size of the friction coefficient depends on factors such as the material and surface condition of the bridge structure and the properties of the supporting surface.

[0210] Normal pressure refers to the pressure applied to the bridge structure perpendicular to the supporting surface. The magnitude of the normal pressure depends on factors such as the weight of the bridge structure, external loads, and the inclination angle of the supporting surface.

[0211]

[0212] in, represents the failure probability of the bridge structure’s bearing capacity, represents the failure probability of bridge structure deformation, represents the sliding failure probability of the bridge structure.

[0213] The failure probability of the bearing capacity of a bridge structure refers to the probability that the bearing capacity of the bridge structure decreases or is lost due to excessive deformation or slippage when subjected to external forces. The failure probability of the bearing capacity is one of the important indicators for evaluating the safety and reliability of bridge structures.

[0214] On the other hand, in probability theory, the union can be used to represent the probability of at least one of two events occurring. In the probabilistic failure judgment model, if the two failure modes are independent, that is, the occurrence of one failure does not affect the probability of the other failure, the probability addition formula should be used to calculate the total failure probability, that is, On the contrary, if the two failure modes are not completely independent, or there are other complex interactions, a probability model is needed to calculate the total failure probability. Therefore, in practical applications, it is necessary to select and adjust appropriate probability models and methods according to specific circumstances to calculate the failure probability of the bearing capacity of the bridge structure.

[0215] In this embodiment, a probabilistic failure judgment model is established based on probability theory and Monte Carlo simulation. This method can fully consider the uncertainty of the impact force of floating objects and the various possibilities of deformation and sliding failure of the bridge structure, thereby improving the risk assessment accuracy of the probabilistic failure assessment method for floating objects impacting bridges during flood season.

[0216] The probabilistic failure assessment method for floating objects impacting bridges during flood season can flexibly adjust the failure threshold and assessment parameters according to the design requirements, use conditions and safety factors of different bridges, and is thus applicable to various types of bridges and floating object impact scenarios. Compared with the traditional deterministic assessment method, the probabilistic failure judgment model can more accurately estimate the failure probability by simulating a large number of samples, thereby avoiding unnecessary conservative design and waste of resources, and improving the cost-effectiveness of the probabilistic failure assessment method.

[0217] The probabilistic failure assessment method for floating objects hitting bridges during flood season can provide early warning for bridge management departments, help formulate effective response measures and emergency plans before the flood season arrives, and ensure the safe operation of bridges. At the same time, it further promotes technological innovation and development in the field of bridge risk assessment, provides new ideas and methods for related research and applications, helps improve the safety and reliability of bridges, and contributes to the sustainable development of transportation infrastructure.

[0218] See also Figure 2 In an optional embodiment, the present invention further provides a probabilistic failure assessment system for floating objects hitting bridges during flood season, the system comprising a processor, an input device, an output device and a memory, the processor, the input device, the output device and the memory being interconnected, wherein the memory is used to store a computer program, the computer program comprising program instructions, the processor being configured to call the program instructions, and executing the probabilistic failure assessment method for floating objects hitting bridges during flood season and the specific steps of the related embodiments provided by the present invention. The probabilistic failure assessment system for floating objects hitting bridges during flood season of the present invention has a complete structure and is objective and stable.

[0219] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A probabilistic failure assessment method for floating objects impacting bridges during flood season, characterized in that: The steps include: Collecting data on floating objects during the flood season and river hydrological information, and obtaining water flow velocity and movement status of floating objects based on the data on floating objects during the flood season and river hydrological information; Establishing a floating object drag force prediction model according to the water flow velocity and the movement status of the floating object, and analyzing the drag force generated by the flood on the floating object according to the floating object drag force prediction model; A bridge damage assessment mechanism is set based on the flood season floating object data and river hydrological information, and an assessment parameter analysis result is obtained according to the bridge damage assessment mechanism; Establishing a probabilistic failure judgment model, combining the probabilistic failure judgment model, the drag force, the evaluation parameter analysis results, the flood season floating object data and the river hydrological information to obtain a probabilistic failure assessment result, so as to achieve risk prediction and assessment of floating objects hitting bridges during the flood season; The water flow velocity and floating object movement conditions obtained based on the flood season floating object data and river hydrological information include: Establishing a water flow velocity analysis function and a floating object motion analysis equation based on the flood season floating object data and river hydrological information; Combining the water flow velocity analysis function with the floating object motion analysis equation to obtain a floating object motion and water flow analysis model; The water flow velocity and the movement status of the floating objects are obtained by the floating object movement and water flow analysis model; The water flow velocity analysis function satisfies the following relationship: in, Indicates the water flow velocity, represents the change of the equation over time, represents the gradient operator, represents the density of water, represents the pressure field, Represents the pressure field The gradient of represents the dynamic viscosity of water, Indicates water flow speed The Laplace operator of represents the external force term; The floating object motion analysis equation satisfies the following relationship: in, Indicates the mass of the floating object, represents the speed of the floating object, represents the change of velocity with time, represents the drag force of floating objects, The buoyancy of floating objects, Indicates the weight of floating objects; The establishment of a floating object drag force prediction model according to the water flow velocity and the floating object movement condition comprises: Obtaining the water flow velocity through the water flow velocity analysis function; Obtaining the movement status of the floating object based on the floating object movement analysis equation; Establishing a floating object drag force prediction model based on the water flow velocity and the movement status of the floating object; The floating object drag force prediction model satisfies the following relationship: in, It represents the drag force of flood on floating objects. represents the density of floating objects, It represents the surface area of ​​the floating object in contact with the water. represents the floating object velocity conversion coefficient, Indicates the water flow velocity, is the Reynolds number, Indicates the collision angle.

2. The probabilistic failure assessment method for floating objects impacting bridges during flood season according to claim 1 is characterized in that: The bridge damage assessment mechanism is set based on the flood season floating object data and river hydrological information, and the assessment parameter analysis results are obtained according to the bridge damage assessment mechanism, including: Setting bridge damage assessment parameters based on the flood season floating object data and river hydrological information, the bridge damage assessment parameters including bridge structure deformation, collision impact force, floating object mass, water flow velocity, bridge stiffness and bearing friction coefficient; A bridge damage assessment mechanism is set in combination with the deformation of the bridge structure, the collision impact force, the mass of the floating object, the water flow velocity, the bridge stiffness and the bearing friction coefficient; Based on the bridge damage assessment mechanism, an assessment parameter analysis result is obtained.

3. The probabilistic failure assessment method for floating objects impacting bridges during flood season according to claim 2 is characterized in that: The deformation of the bridge structure satisfies the following relationship: in, represents the deformation of the bridge structure, Indicates the critical value of the deformation of the bridge structure; The collision impact force satisfies the following relationship: in, The impact force of the collision, represents the friction coefficient, Indicates positive pressure; The mass of the floating object satisfies the following relationship: in, Indicates the mass of floating objects, represents the mean of the normal distribution of floating mass, represents the standard deviation of the mass of floating objects; The water flow velocity satisfies the following relationship: in, Indicates the water flow velocity, represents the mean of the normal distribution of water velocity, represents the standard deviation of water velocity; The bridge stiffness satisfies the following relationship: in, represents the stiffness of the bridge structure, represents the mean of the normal distribution of bridge stiffness, represents the standard deviation of bridge stiffness; The bearing friction coefficient satisfies the following relationship: in, is the bearing friction coefficient, represents the mean of the normal distribution of the bearing friction coefficient, Represents the standard deviation of the bearing friction coefficient.

4. The probabilistic failure assessment method for floating objects impacting bridges during flood season according to claim 1 is characterized in that: The establishment of a probabilistic failure judgment model comprises: Establish a probabilistic failure judgment model based on the Monte Carlo simulation framework; The probabilistic failure judgment model satisfies the following relationship: in, represents the failure probability of bridge structure deformation, represents the indicator function, represents the deformation of the bridge structure, represents the critical value of the deformation of the bridge structure, Indicates the number of simulations; in, represents the sliding failure probability of the bridge structure, represents the indicator function, The impact force of the collision, represents the friction coefficient, Indicates positive pressure, Indicates the number of simulations; in, represents the probability of failure of the bearing capacity of the bridge structure, represents the failure probability of bridge structure deformation, represents the sliding failure probability of the bridge structure.

5. A probabilistic failure assessment system for floating objects hitting bridges during flood season, characterized by: The system includes a processor, an input device, an output device and a memory, wherein the processor, the input device, the output device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the probabilistic failure assessment method for floating objects impacting a bridge during flood season as described in any one of claims 1 to 4.

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