A 3D printing adaptive bionic spiral anti-collision method and system for a ship lock wall

Abstract

This invention belongs to the field of lock wall protection technology, and discloses a 3D-printed adaptive biomimetic spiral anti-collision method and system for lock walls. The steps of the anti-collision method are as follows: S1, define the manifold space on the lock wall surface; S2, based on the historical ship berthing data of the target lock, construct the impact load probability field on the lock wall surface and calculate the load-driven entropy field; S3, construct 3D printing process constraints to obtain the printing process constraint potential field; S4, fuse the load-driven entropy field and the printing process constraint potential field to form a design driving field; S5, based on the manifold seeding-growth algorithm, using the design driving field as the growth guide field, adaptively generate a non-uniform spiral topology on the lock wall surface; S6, combine the non-uniform spiral topology with the functional partitioning of the lock wall to output the protection unit design model. This invention can generate a non-uniform spiral topology that accurately matches the load and, combined with 3D printing technology, achieve in-situ integrated construction, improving the safety and economy of lock operation.

Description

Technical Field

[0001] This invention belongs to the fields of water conservancy engineering, lock wall protection, and machine learning technology, and in particular relates to a 3D printing adaptive bionic spiral anti-collision method and system for lock walls. Background Technology

[0002] With the modernization of inland waterway transportation infrastructure, the structural safety of locks, as the core of navigation hubs, is subject to increasingly stringent requirements, particularly the ability of lock walls to withstand the impact of low-speed, heavy-load ships. Traditional lock protection mainly relies on steel or rubber fenders, which is essentially a "passive defense" mode that increases cross-sectional stiffness or relies on material compression deformation. This not only results in a bulky structure and low material utilization, but also, when subjected to the impact of ships of tens of thousands of tons, the energy dissipation path is singular and inefficient, making it easy to directly transfer peak loads to the concrete main body of the lock wall, causing structural damage.

[0003] In recent years, drawing inspiration from biomimetic structures in nature, such as the Bouligand spiral configuration, has provided new ideas for developing high-performance collision protection structures due to their efficient energy dissipation characteristics through various mechanisms such as interlayer slip and fiber torsion. However, translating biomimetic principles into large-scale concrete protective structures suitable for ship locks faces three major technical challenges: First, adaptability is difficult: the biological spiral structure is a static and homogeneous evolutionary result, while the energy, angle, and frequency distribution of impacts on different areas of the ship lock wall (such as the gate area, navigation wall, and water level fluctuation zone) are highly non-uniform; a fixed spiral configuration cannot dynamically match this complex and variable real load scenario; Second, design is difficult: currently, there is a lack of intelligent design algorithms that can automatically and quantitatively map macroscopic impact load distribution (data-driven) with microscopic spiral configuration parameters (such as local spiral angle, pitch, density, etc.); the discrete porous structure generated by traditional topology optimization methods has poor compatibility with the biomimetic concept of continuous spirals and 3D printing technology; Third, manufacturing is difficult: even if the theoretically optimal non-uniform spiral topology is obtained, its complex spatial continuous variable cross-section characteristics completely exceed the technological capabilities of traditional template casting or prefabricated component assembly, making it impossible to produce a physical object.

[0004] Currently, research suffers from a disconnect: advanced biomimetic design is detached from practical engineering constraints and construction processes, while concrete 3D printing technology, with its potential for free-form molding, lacks intelligent and precise design methods for lock scenarios. Therefore, developing a comprehensive solution that integrates load analysis, adaptive algorithm design, process constraint fusion, and intelligent construction has become a core technical challenge urgently needing breakthroughs in the field of lock protection. Summary of the Invention

[0005] To address the aforementioned issues, the present invention aims to provide a 3D-printed adaptive biomimetic spiral anti-collision method and system for lock walls. This system can generate a non-uniform spiral topology that precisely matches the load through an algorithm, and combine it with 3D printing technology to achieve in-situ integrated construction.

[0006] To achieve the above-mentioned objectives, the present invention adopts the following technical solution:

[0007] A 3D-printed adaptive biomimetic spiral anti-collision method for lock walls, comprising the following steps:

[0008] S1, Define the manifold space on the gate wall surface;

[0009] S2. Based on the historical ship berthing data of the target lock, construct the impact load probability field of the lock wall surface in step S1, and calculate the load-driven entropy field according to the impact load probability field.

[0010] S3. Construct 3D printing process constraints and obtain the printing process constraint potential field;

[0011] S4. Combine the load-driven entropy field in step S2 with the printing process constraint potential field in step S3 to form the design-driven field.

[0012] S5. Based on the manifold seeding-growth algorithm, the design driving field in step S4 is used as the growth guiding field to simulate the competitive growth and merging process of spiral manifold seeds on the gate wall surface, and adaptively generate non-uniform spiral topology configuration.

[0013] S6. Combine the non-uniform spiral topology generated in step S5 with the gate wall functional zoning to output a zoning and parameterized protection unit design model.

[0014] Further, step S1 above includes: cleaning the surface of the lock wall. Defined as a two-dimensional Riemannian manifold embedded in three-dimensional Euclidean space In the middle; let any point on the manifold The local coordinates are Let the surface be parameterized as 𝑟 The unit normal vector is 𝑛, and the Gaussian curvature at this point is 𝑛. and mean curvature From the first fundamental form coefficients Second fundamental form coefficient Sure:

[0015]

[0016]

[0017] in, , , , , , .

[0018] Further, step S2 above includes:

[0019] Historical AIS data and video surveillance records of the target lock were collected to extract key parameters of typical berthing events, including the total weight of the vessel. Longitudinal speed of the ship approaching the lock wall The angle between the ship's course and the normal direction of the lock wall Coordinates of the position of the ship in contact with the lock wall Aligning AIS timestamps with video frame timestamps and linking ship dynamic data with physical locations in video footage, a historical ship berthing dataset is created. N represents the total number of typical berthing events. A joint probability density function is constructed using kernel density estimation. For the lock wall surface in step S1 any point on the manifold The expected impact kinetic energy it withstands for:

[0020]

[0021] in, Indicates the direction correction factor; This represents the integral summation of the total weight, speed, and included angle of all ships that may collide with the lock wall;

[0022] Based on the definition of Shannon entropy, position The load-driven entropy field at a given location is defined as:

[0023]

[0024]

[0025] in, Indicates impact energy; Indicates impact energy The space of values; Indicates position Impact energy The probability distribution; This means taking the logarithm of the probability density function; This represents the impact energy values ​​for all possible scenarios. Perform integration and summation.

[0026] Further, step S3 above includes: setting the normal vector of the printing nozzle as... The surface of the gate wall is in position The normal vector at is ; Overhang angle ;

[0027] The sag constraint function is expressed as:

[0028]

[0029] in, This represents the suspension sensitivity coefficient; Indicates the maximum theoretical overhang angle; Indicates the critical overhang angle. When the actual overhang angle Exceed When the value is , the constraint is activated, that is ,otherwise Setting it to 1 means there is no penalty;

[0030] Reachability constraints for a printing robotic arm: Jacobian matrix based on the robotic arm condition number The quantization of dexterity, the reachability constraint function is expressed as:

[0031]

[0032] in, Represents the joint angle vector of the robotic arm; Indicates the arrival location Required joint angle; express The maximum value under all possible configurations;

[0033] The constraint potential field of the printing process is represented as:

[0034]

[0035] in, Indicates the overhang weight coefficient; This represents the reachability weight coefficient.

[0036] Furthermore, step S4 above includes: driving the entropy field with the load from step S2. With the printing process constraint potential field in step S3 Integration, forming a design-driven field The calculation formula is:

[0037]

[0038] in, This is the penalty coefficient.

[0039] Furthermore, step S5 above includes the following sub-steps:

[0040] S5.1 Initialize the gate wall growth substrate by discretizing the three-dimensional surface of the gate wall into a finite element mesh; at each mesh point Define its state as empty, seed, growing, or entity; in designing the driving field Local maximum location Automatic placement of the initial manifold seed, seed set ;

[0041] Each seed Defined as a quadruple state vector:

[0042] in, Indicates the seed at time The state; Indicates the seed at time Coordinates on the manifold of the gate wall; Indicates the seed at time The growth rate vector; Indicates the seed at time The local helix angle; Indicates the seed at time Material density / growth strength;

[0043] S5.2 Constructing manifold competitive growth, simulating the structure growth process through iterative loops, including:

[0044] (1) Growth direction decision

[0045] The growth of manifolds follows a modified Hamiltonian principle, and its Lagrange... Defined as kinetic energy term With potential energy term Dissipation terms The difference is expressed as:

[0046]

[0047] Among them, the kinetic energy term and Proportional; Potential energy term It is a design-driven field The function; dissipation term Represents the dissipation function;

[0048] The growth trajectory is derived from the Euler-Lagrange equation:

[0049]

[0050] in, Indicates external generalized force. It is a "generalized force" driven by design-driven fields, pointing towards The direction of fastest growth guides the seed to move towards the high-energy-demand region or extend along the potential energy ridge; R is the Rayleigh dissipation function, used to define the dissipation force. Another form, It is the viscous damping coefficient;

[0051] (2) Adaptive adjustment of spiral parameters

[0052] Spiral evolution: helix angle The adaptive change follows a curvature-driven flow, expressed as:

[0053]

[0054] in, Indicates the response intensity coefficient; This represents the gradient of the design field along the tangent of the equipotential surface; This indicates rotational adjustment along the gradient direction; Indicates the smoothing coefficient; Represented as a diffusion smoothing term;

[0055] pitch Physical constraints: pitch With local Gaussian curvature Coupling, position The local pitch at a certain point is expressed as:

[0056]

[0057] in, Indicates the basic pitch; Indicates the curvature coupling coefficient; Indicates the position of the gate wall surface. Gaussian curvature at that point; Represents a sign function, when When, it is 1, when When, it is -1;

[0058] S5.3, Manifold Competition and Fusion Mechanism

[0059] S5.31, Interaction Potential Energy

[0060] When two seeds and Euclidean distance between When, define the interaction potential energy for:

[0061]

[0062] in, This is a preset distance threshold; Indicates the depth of the potential well; Indicates the scale of the effective distance; This represents the helix angle consistency coefficient, whose value is determined by the difference between the two helix angles. The range is (0, 1]; Indicates two seeds and The difference in helix angle, i.e. ; Indicates angular tolerance;

[0063] If the helix angles are consistent, that is As the potential approaches 1, the potential well becomes deeper, at which point fusion occurs.

[0064] If the difference in helix angle is large, that is When the repulsive force approaches 0, competition occurs, and weaker seeds are suppressed.

[0065] S5.32, Topology Merging Criteria

[0066] When merging occurs, the state of the new seed is updated to the weighted average of the two old seeds:

[0067]

[0068] in, This represents the state vector of the new seed generated after fusion; , These represent the growth intensity of the two original seeds;

[0069] S5.4, "Tidal" Sedimentation and Mechanical Equilibrium

[0070] S5.41, Evolution of Volume Fraction

[0071] Define phase field variables , representing a spatial point The material occupancy rate at a given location: 0 = empty, 1 = solid.

[0072] The evolution follows a modified form of the Cahn-Hilliard equation, expressed as:

[0073]

[0074] in, Indicates mobility; chemical potential , representing the thermodynamic driving force that drives material diffusion; Indicates the gradient energy coefficient; It is the print source item;

[0075] S5.42, Structural stability check

[0076] After each layer of deposition is completed, calculate the total potential energy of the system. , is represented as:

[0077]

[0078] Among them, total potential energy Includes strain energy and work done by external forces; Representing strain energy density, through Calculate, where, Represents the strain tensor. Represents the elastic tensor; Represents volume force; Represents the displacement field; 'Indicates surface force;

[0079] According to the principle of minimum potential energy The strain energy density calculated during the growth process Exceeding the material strain energy density threshold At that time, backtrack and adjust the local growth rate vector. Or increase the local material density ;

[0080] S5.5 Define global topology order parameters Based on the Minkowski functional:

[0081]

[0082] in, Indicates at time The volume of the generated structure; Indicates at time Surface area;

[0083] The loop stops when the following condition is met, indicating that the structure has reached the expected topological complexity and growth tends to stagnate; denoted as:

[0084]

[0085] in, Indicates the target topological order parameter; Indicates the topological convergence threshold; This represents the dynamic convergence threshold.

[0086] A 3D-printed adaptive bionic spiral anti-collision system for a lock wall is generated based on the aforementioned 3D-printed adaptive bionic spiral anti-collision method for lock walls. It is formed in one 3D printing process and contains a spatially non-uniform spiral structure. It is combined with the functional zoning of the lock wall for zoning optimization.

[0087] Furthermore, the aforementioned spatial non-uniform spiral structure has a pre-set sensing channel.

[0088] Furthermore, the aforementioned collision avoidance system includes several protective units, namely:

[0089] The heavy-duty energy-absorbing unit is located in the gate region, corresponding to the high impact entropy region, and generates a high-density, small-pitch spiral cluster structure. The internal topology consists of multiple first spiral structures that are closely packed in space.

[0090] Wear-resistant guide units are installed on the navigation wall and applied to the navigation wall area where ships have a high probability of collision. They generate a spiral ribbon structure with a long pitch and a large helix angle. The internal topology is mainly composed of continuous spiral ribbon structures.

[0091] The wet and dry durability unit is located in the water level fluctuation zone and has a pitch that changes continuously from the above-water position to the underwater position; it spans the highest and lowest water level lines, and the internal second spiral structure changes in a gradient along the vertical direction.

[0092] Furthermore, in the aforementioned heavy-duty energy-absorbing unit, the average pitch of the first helical structure... With the outer diameter of the helix The ratio is limited to between 0.5 and 1.5, and the angle between the main axis of each first spiral structure and the normal plane of the gate wall is designed to be less than 30 degrees.

[0093] Furthermore, in the aforementioned wear-resistant guide unit, the average pitch of the spiral ribbon structure... With the outer diameter of the helix The ratio is set between 3.0 and 8.0; the main axis of the spiral ribbon structure is parallel to the center line of the gate, and the spiral angle is designed to be greater than 60 degrees.

[0094] Furthermore, in the aforementioned dry and wet durability unit, in the area above the designed highest water level, the pitch of the second helical structure... Designed as a benchmark In areas below the design minimum water level, the pitch... With water depth Linear increase, satisfying ,in, '' represents the pitch increase factor.

[0095] Furthermore, each of the aforementioned protective units is pre-embedded with fiber optic sensors and conductive concrete sensors.

[0096] Furthermore, the aforementioned collision avoidance system also includes an edge computing server, which is deployed at the lock site to run a lightweight damage diagnosis model, perform real-time analysis of sensor data, and identify abnormal impacts.

[0097] A 3D printing device includes a mobile waterborne operation platform, on which are mounted a 3D scanning module, a multi-axis 3D printing robotic arm, a two-component material extrusion system, and a path planning and quality monitoring system.

[0098] The three-dimensional scanning module is used to reconstruct the surface model of the gate wall and register and calibrate it with the design model;

[0099] The multi-axis 3D printed robotic arm is used to move along a spatially continuous variable parameter path generated by the manifold seeding-growth algorithm;

[0100] The two-component material extrusion system is used to control the extrusion speed, material ratio, and rotation angle of the spiral nozzle to reproduce the designed spiral topology.

[0101] The path planning and quality monitoring system is used to perform the conversion from digital model to physical entity and to ensure the accuracy and quality stability of the printing process, including: generating a multi-dimensional collaborative printing path containing spatial position, nozzle posture and process parameters based on the calibrated gate surface model.

[0102] Furthermore, the aforementioned 3D printing equipment also includes underwater partial cofferdams for underwater partial repair and underwater anti-dispersion concrete printing heads.

[0103] A lock wall protection system is provided, which consists of several anti-collision systems arranged in an array along the lock wall surface. The sensor networks inside each anti-collision system are interconnected and connected to the lock's health monitoring and digital twin platform.

[0104] A lock, wherein the lock wall is equipped with the aforementioned lock wall protection system.

[0105] Due to the adoption of the technical solution described above, the present invention has the following advantages:

[0106] This invention discloses a 3D-printed adaptive biomimetic spiral anti-collision method for lock walls. It generates a non-uniform spiral topology precisely matched to the load using a manifold seeding-growth algorithm, and combines this with 3D printing technology to achieve in-situ integrated construction. The manifold seeding-growth algorithm treats the lock wall surface as a "substrate" for biological growth and the ship impact energy flow as a "growth driving force," generating an optimal topological structure by simulating the natural growth process of biological tissue. The biomimetic spiral structure generated by the manifold seeding-growth algorithm has excellent energy dissipation capabilities. The specific energy absorption efficiency (SEA) of the biomimetic spiral structure is significantly improved compared to traditional rubber fenders, while simultaneously reducing the peak impact force, effectively protecting the main structure of the lock wall and the ship's hull.

[0107] The present invention relates to a 3D-printed adaptive bionic spiral anti-collision system for ship lock walls. Its integrated 3D printing molding can eliminate easily corroded weak links such as bolted connections of traditional fenders. Combined with a gradient material system designed for the water environment, the theoretical service life of the protective structure is greatly increased from the traditional 10 years to more than 50 years.

[0108] The 3D printing equipment of this invention enables rapid and low-interference in-situ construction via a mobile water platform; the printing and installation time of a single standard unit (2m×1m) can be controlled within 8 hours. Compared with the traditional replacement method, the maintenance downtime is reduced by more than 80%, which greatly improves the navigation efficiency of the lock.

[0109] The lock wall protection system of this invention combines an embedded sensor network with a digital twin platform, enabling the protection structure to have intelligent capabilities of "perception-diagnosis-early warning", promoting the transformation of the operation and maintenance mode from passive "post-fault maintenance" to proactive "predictive maintenance", and reducing the total life cycle cost.

[0110] This invention enables a complete technical closed loop for lock protection structures, from data-driven design and intelligent adaptive construction to intelligent operation and maintenance throughout the entire life cycle. It effectively solves the core pain points of traditional fenders, such as low buffer efficiency, poor durability, and serious maintenance impacting navigation, and significantly improves the safety and economy of lock operation. Attached Figure Description

[0111] Figure 1 This is a flowchart of the 3D printing adaptive bionic spiral anti-collision method for the lock wall of the present invention;

[0112] Figure 2 This is a schematic diagram of the structure of the 3D-printed adaptive bionic spiral anti-collision system for the lock wall of the present invention;

[0113] Figure 3 yes Figure 1 A schematic diagram illustrating the principle of the "manifold seeding-growth algorithm" in the anti-collision method being executed on the surface of the gate wall;

[0114] Figure 4 yes Figure 2 The structure of each protective unit of the collision avoidance system and its internal spiral topology diagram, wherein (a) is a heavy-duty energy-absorbing unit, (b) is a wear-resistant guiding unit, and (c) is a dry and wet durability unit;

[0115] In the diagram: 1 – First helical structure; 2 – Helical ribbon structure; 3 – Second helical structure; 4 – Sensing channel. Detailed Implementation

[0116] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can fully understand and implement the present invention.

[0117] like Figure 1 , 3 As shown, a 3D-printed adaptive biomimetic spiral anti-collision method for a ship lock wall includes the following steps:

[0118] S1. Define the manifold space on the surface of the lock wall to accurately describe the generation and growth of protective units on complex curved surfaces, including:

[0119] Includes: the surface of the lock wall Defined as a two-dimensional Riemannian manifold embedded in three-dimensional Euclidean space In the middle; let any point on the manifold The local coordinates are Let the surface be parameterized as 𝑟 The unit normal vector is 𝑛, and the Gaussian curvature at this point is 𝑛. and mean curvature From the first fundamental form coefficients Second fundamental form coefficient Sure:

[0120]

[0121]

[0122] in, , , , , , ;

[0123] These geometric parameters serve as the basis for the "geometric potential" in the subsequent growth process, influencing the tangential growth direction of the manifold;

[0124] S2. Based on the defined manifold space, to ensure the design of the protection unit can accurately respond to the actual load distribution, the impact risk of the lock wall surface is quantified; historical AIS data and video monitoring records of the target lock are collected, and key parameters of typical berthing events are extracted, including the total weight of the vessel. Longitudinal speed of the ship approaching the lock wall The angle between the ship's course and the normal direction of the lock wall Coordinates of the position of the ship in contact with the lock wall (Two-dimensional or three-dimensional coordinates, depending on the model definition) Align AIS timestamps with video frame timestamps, associate ship dynamic data with physical locations in video footage, and form a historical ship berthing dataset. N represents the total number of typical berthing events. A joint probability density function is constructed using kernel density estimation. For the lock wall surface in step S1 any point on the manifold The expected impact kinetic energy it withstands for:

[0125]

[0126] in, Indicates the direction correction factor; This means integrating and summing the total weight, speed, and angle of all possible ships that could collide with the gate wall to obtain a total expected value;

[0127] Based on the definition of Shannon entropy, position The load-driven entropy field at a given location is defined as:

[0128]

[0129]

[0130] in, Indicates impact energy; Indicates impact energy The value space represents the set of all possible impact energy values; Indicates position Impact energy The probability distribution; This means taking the logarithm of the probability density function, with the base as the base. It is usually taken as 2 or a natural constant. ; This represents the impact energy values ​​for all possible scenarios. Perform integration and summation;

[0131] Used to measure location The degree of uncertainty or disorder in the impact energy indicates the location; a higher entropy value signifies a more stable position. The higher the randomness and danger of the load (i.e., the wider the load spectrum, the greater the uncertainty); high entropy points correspond to high-frequency and high-energy impact regions;

[0132] S3. Quantify the physical constraints of the manufacturing process into design constraints to ensure that the complex topologies generated by the algorithm can be printed practically and efficiently; including: assuming the normal vector of the printing nozzle is... The surface of the gate wall is in position The normal vector at is ; Overhang angle This indicates the angle between the printing direction and the normal direction of the gate wall surface. The larger the size, the more difficult it is to print in mid-air;

[0133] The sag constraint function is expressed as:

[0134]

[0135] in, This represents the sag sensitivity coefficient, used for adjustment. Follow The greater the value of the change, the heavier the penalty for the overhang. This represents the maximum theoretical overhang angle, which is a design constant, preferably 45° or 60°, and is the limit angle at which the material can self-support. Indicates the critical overhang angle. When the actual overhang angle Exceed When the value is , the constraint is activated, that is 1, otherwise It is usually set to 1, meaning no penalty;

[0136] As a dimensionless scalar, a larger value indicates a larger position. The higher the difficulty and risk of printing, the more complex and risky the process.

[0137] Reachability constraints for a printing robotic arm: Jacobian matrix based on the robotic arm condition number The quantization of dexterity, the reachability constraint function is expressed as:

[0138]

[0139] in, This represents the joint angle vector of a robotic arm, for example, the joint angle vector of a six-axis robotic arm. ; Indicates the arrival location Required joint angle; express The maximum value under all possible configurations;

[0140] As a dimensionless scalar, a larger value indicates that the robotic arm has reached a certain position. The more awkward the posture, the worse the dexterity;

[0141] The constraint potential field of the printing process is represented as:

[0142]

[0143] in, This represents the overhang weight coefficient, used to adjust the importance of the overhang constraint in the overall constraint. This represents the reachability weighting coefficient, used to adjust the importance of the overhang constraint in the overall constraints;

[0144] The printing process constraint field Used to quantify the position of the gate wall The technological challenges of 3D printing at this location include: assessing whether the end effector of the printing robot can reach the location without interference; assessing the risk of collapse during suspended printing based on the angle between the normal and the direction of gravity at this point (hanging angle); and limiting the minimum size of structural details due to the limitation of the printing nozzle diameter.

[0145] S4. Integrate the load-driven entropy field from step S2 with the printing process constraint potential field from step S3 to define a design driving field as the driving force source for manifold growth, in order to achieve a balance between "optimal performance" and "manufacturing feasibility"; including: integrating the load-driven entropy field from step S2... With the printing process constraint potential field in step S3 Integration, forming a design-driven field The calculation formula is:

[0146]

[0147] in, This is the penalty coefficient;

[0148] This step is used to ensure that the algorithm automatically avoids unprintable geometries while pursuing high-performance structures;

[0149] Manifold seeds will tend to The gradient descent direction (i.e., the low point of potential energy, here referring to the equilibrium point that "requires protection and is easy to print") or tangential growth along the equipotential line, depending on the growth mode.

[0150] S5. Based on the manifold seeding-growth algorithm, the design-driven field in step S4 is used. As a growth guiding field, a competitive growth and merging process simulating a spiral manifold seed is generated on the gate wall surface. This adaptively generates a non-uniform spiral topology configuration precisely matched to different operating conditions, including the heavy-duty zone of the gate, the wear-resistant zone of the navigation wall, and the water level fluctuation zone. The spiral parameters are dynamically and adaptively adjusted during the growth process based on the local entropy field gradient and printing constraints. This includes the following sub-steps:

[0151] S5.1 Initialize the gate wall growth substrate by discretizing the three-dimensional surface of the gate wall into a finite element mesh; at each mesh point Define its state as empty, seed, growing, or entity; in designing the driving field Local maximum location (i.e., the most critical impact protection point) Automatically place the initial manifold seed, seed set. ;

[0152] Each seed Defined as a quadruple state vector:

[0153] in, Indicates the seed at time The state; Indicates the seed at time Coordinates on the manifold of the gate wall; Indicates the seed at time The growth rate vector determines the direction and speed of the seed's movement at the next moment; Indicates the seed at time The local helix angle defines the density of the helical structure formed by the seed growth trajectory; Indicates the seed at time The material density / growth intensity determines the "robustness" of the structure generated by the seed, and is also used for weighting during fusion;

[0154] S5.2 Constructing manifold competitive growth, simulating the structure growth process through iterative loops, including:

[0155] (1) Growth direction decision

[0156] Taking into account both the entropy field gradient and the gate wall boundary normal, the optimal growth vector is determined, and the feasible direction with the smallest angle to the gate wall tangent is selected as the growth path. The growth of the manifold follows the modified Hamiltonian principle, and its Lagrangian... Defined as kinetic energy term With potential energy term Dissipation terms The difference is expressed as:

[0157]

[0158] Among them, the kinetic energy term Usually with Proportional, representing the system's kinetic energy; potential energy term It is a design-driven field The function, the seed tends to move towards the direction of lower potential energy; dissipation term This represents the dissipation function, which is velocity-dependent and simulates energy loss, such as the energy loss caused by viscous damping.

[0159] The growth trajectory is derived from the Euler-Lagrange equation:

[0160]

[0161] in, Indicates external generalized force. It is a "generalized force" driven by design-driven fields, pointing towards The direction of fastest growth guides the seed to move towards the high-energy-demand region or extend along the potential energy ridge; R is the Rayleigh dissipation function, used to define the dissipation force. Another form, It is the viscous damping coefficient;

[0162] (2) Adaptive adjustment of spiral parameters

[0163] To generate efficient biomimetic spiral structures, their geometric parameters need to adapt to local loads and geometric environments;

[0164] Spiral evolution: helix angle The adaptive change follows a curvature-driven flow, expressed as:

[0165]

[0166] in, It represents the response intensity coefficient, which controls how quickly the helix angle responds to the design field gradient; This represents the gradient of the design field along the tangential direction of the equipotential surface, which drives the change of the helix angle to adapt to the load streamline; This indicates rotational adjustment along the gradient direction; It represents the smoothing coefficient, which controls the smoothness of the helix angle variation in space; Represented as a diffusion smoothing term, ensuring the helix angle Continuity of change (Ginzburg-Landau type smoothness);

[0167] pitch Physical constraints: pitch With local Gaussian curvature Coupling is used to prevent self-interference of the helical structure on the curved surface; position The local pitch at a certain point is expressed as:

[0168]

[0169] in, Indicates the basic pitch; This represents the curvature coupling coefficient, used to adjust the intensity of the effect of the gate wall curvature on the pitch; Indicates the position of the gate wall surface. The Gaussian curvature at a given location is used to describe the position. Local bending characteristics; Represents a sign function, when When (convex), the value is 1. When (saddle surface / concave surface), the value is -1;

[0170] In the region of positive curvature (convex surface), the pitch increases, and in the region of negative curvature (concave surface), the pitch decreases.

[0171] S5.3, Manifold Competition and Fusion Mechanism

[0172] During growth, different seeds interact with each other, forming a complex network structure;

[0173] S5.31, Interaction Potential Energy

[0174] When two seeds and Euclidean distance between When, define the interaction potential energy for:

[0175]

[0176] in, This is a preset distance threshold; This represents the potential well depth and, as an energy constant, determines the strength of the interaction force. This indicates the interaction distance scale, used to determine the effective range of the interaction; This represents the helix angle consistency coefficient, whose value is determined by the difference between the two helix angles. The value range is (0, 1], and the larger the value, the better the compatibility between the two spiral modes; Indicates two seeds and The difference in helix angle, i.e. ; Indicates angular tolerance, control The rate at which the angle difference decreases;

[0177] If the helix angles are consistent, that is As the potential approaches 1, the potential well becomes deeper, at which point fusion occurs.

[0178] If the difference in helix angle is large, that is When the repulsive force approaches zero, competition occurs, and weaker seeds are suppressed. );

[0179] S5.32, Topology Merging Criteria

[0180] When merging occurs, the state of the new seed is updated to the weighted average of the two old seeds:

[0181]

[0182] in, This represents the state vector of the new seed generated after fusion; , These represent the growth strength of the two original seeds, and are used as weights to ensure that the stronger seed dominates the fused state.

[0183] This weighted merging mechanism ensures that the merged structure inherits the superior characteristics of the stronger seed;

[0184] S5.4, "Tidal" Sedimentation and Mechanical Equilibrium

[0185] This step is used to discretize the continuous growth model into a layered deposition process suitable for 3D printing and to check the structural stability in real time; the operation is as follows: simulating the physical process of printing concrete layer by layer, setting virtual layer heights; each growth... The simulation completes one layer of printing. The material's outer contour is calculated based on the current spiral parameters, and self-support and boundary interference checks are performed. Once passed, it is marked as a solid.

[0186] S5.41, Evolution of Volume Fraction

[0187] Define phase field variables , representing a spatial point The material occupancy rate at a given location: 0 = empty, 1 = solid.

[0188] The evolution follows a modified form of the Cahn-Hilliard equations (describing phase separation), serving as a physical model for simulating material deposition and interface evolution, expressed as:

[0189]

[0190] in, Represents mobility, which is a property of... Related functions that control the rate of phase separation; chemical potential , representing the thermodynamic driving force that drives material diffusion, is expressed by the system's free energy functional. Free energy of the body and interface capabilities calculate; It represents the gradient energy coefficient, which is proportional to the interfacial tension and controls the interfacial thickness between different material phases (solid and void); It is the print source term, a non-zero function at the nozzle position that simulates the point-by-point addition of material;

[0191] This equation accurately simulates the physical process of material being extruded from the nozzle and solidifying.

[0192] S5.42 Structural stability check (variational principle)

[0193] After each layer of deposition is completed, calculate the total potential energy of the system. To ensure the stability of the structure under its own weight and impact loads, it is expressed as:

[0194]

[0195] Among them, total potential energy Including strain energy and external force work, it is an indicator for measuring the stability of a structure under the current load; Representing strain energy density, through Calculate, where, The strain tensor is used to describe the degree of deformation of a material. Represents the elastic tensor, used to describe the stiffness properties of a material; Represents volume force; It represents the displacement field and is used to describe the deformation of a structure under load; 'Indicates surface force;

[0196] According to the principle of minimum potential energy The strain energy density calculated during the growth process Exceeding the material strain energy density threshold (The maximum allowable strain energy density of a material, determined through material mechanics experiments (such as uniaxial compression and three-point bending tests), represents the maximum elastic strain energy that the material can store before failure.) When this is discussed, it is necessary to backtrack and adjust the local growth rate vector. Or increase the local material density ;

[0197] S5.5 Termination Criteria

[0198] To determine when the growth process is complete, a global topological order parameter is defined. Used to quantify the complexity and morphology of structures, based on the Minkowski functional:

[0199]

[0200] in, Indicates at time The volume of the generated structure; Indicates at time Surface area;

[0201] The loop stops when the following condition is met, indicating that the structure has reached the expected topological complexity and growth tends to stagnate; denoted as:

[0202]

[0203] in, The target topological order parameter is a preset target value, representing the desired structural complexity. This represents the topological convergence threshold, which is typically a small positive number between 1e-5 and 1e-8, used to determine whether the structural form has reached the target. This represents the kinetic convergence threshold, which is generally a small positive number between 1e-3 and 1e-7, used to determine whether the growth of all seeds has essentially stopped.

[0204] After the partitioning parameter output algorithm terminates, it outputs the complete design parameters for each entity grid point: helix angle. pitch The parameters change continuously in space, naturally forming clusters corresponding to the functional zones of the gate wall, providing direct driving data for subsequent printing.

[0205] S6. Combine the non-uniform spiral topology generated in step S5 with the gate wall functional zones (gate zone, navigation wall, water level fluctuation zone) for zone optimization; based on the load characteristics and functional requirements of different zones, customize the parameters of the spiral structure density, pitch, and spiral angle to finally output a zoned and parameterized protection unit design model that can be directly used for manufacturing.

[0206] like Figure 2 , 4 As shown, a 3D-printed adaptive bionic spiral anti-collision system for a lock wall is generated based on the aforementioned 3D-printed adaptive bionic spiral anti-collision method for lock walls. It is formed in one 3D print and contains a spatially non-uniform spiral structure, which is integrated with the functional zoning of the lock wall for zoning optimization. The anti-collision system includes several protective units, namely:

[0207] A heavy-duty energy-absorbing unit, located in the gate region corresponding to the high impact entropy region, generates a high-density, small-pitch helical cluster structure. Its internal topology consists of multiple spatially tightly packed first helical structures 1; the average pitch of the first helical structures... With the outer diameter of the helix The ratio ( The density is limited to between 0.5 and 1.5 to form high-density energy-dissipating cells. The angle between the main axis of each first helical structure and the normal plane of the gate wall is designed to be less than 30 degrees to ensure that the impact energy is mainly dissipated through the axial compression and radial buckling of the first helical structure; the surface layer uses a high fiber content ( The concrete is reinforced to enhance its impact resistance, with a gradient decrease in stiffness towards the inside to achieve a transition in stiffness; a low-speed printing process is used to ensure uniform extrusion and compaction of high-viscosity, high-fiber-content materials;

[0208] Wear-resistant guide units, installed on the navigation wall, corresponding to the navigation wall area with a high probability of ship collisions, generate a helical ribbon structure with a long pitch and large helix angle. The internal topology is mainly composed of continuous helical ribbon structure 2; the average pitch of the helical ribbon structure With the outer diameter of the helix The ratio ( The angle is set between 3.0 and 8.0 to form an extended guide structure; the main axis of the spiral ribbon structure is parallel to the center line of the gate, and its spiral angle is designed to be greater than 60 degrees to minimize the tangential resistance when ships collide; the surface layer is composite with wear-resistant aggregates such as corundum and polymer fibers to improve wear resistance; multiple nozzles work together, and the wear-resistant material nozzles and the main concrete nozzles are switched as needed;

[0209] The wet and dry durability unit, located in the water level fluctuation zone, has a continuously varying pitch from the above-water position to the underwater position; spanning the highest and lowest water level lines, the internal spiral structure exhibits a gradient change along the vertical direction; in the area above the designed highest water level, the pitch of the second spiral structure 3... Designed as a benchmark In areas below the design minimum water level, the pitch... With water depth Linear increase, satisfying ,in, '' represents the pitch amplification factor; this variable pitch design ensures the support stiffness of the above-water part while optimizing the hydrodynamic characteristics of the underwater part and reducing the force of water flow on the structure; it incorporates hydrophobic agents and anti-freeze-heave additives in a gradient to resist dry-wet cycles and freeze-thaw damage; it connects to real-time water level data and automatically switches material formulations according to elevation.

[0210] Each of the aforementioned protective units is pre-installed with a sensing channel 4 for embedding fiber optic sensors and conductive concrete sensors. The fiber optic sensors monitor structural strain and temperature distribution in real time, while the conductive concrete sensors monitor the initiation and propagation of microcracks. A sensing channel is also pre-installed within the spatially non-uniform spiral structure.

[0211] Each of the aforementioned protective units also has a reserved maintenance cavity for easy future maintenance.

[0212] The aforementioned collision avoidance system also includes an edge computing server, which is deployed at the lock site to run a lightweight damage diagnosis model, perform real-time analysis of sensor data, and identify abnormal impacts.

[0213] This invention also discloses a 3D printing device, which includes a mobile waterborne operation platform. The mobile waterborne operation platform is equipped with a 3D scanning module, a multi-axis 3D printing robotic arm, a two-component material extrusion system, and a path planning and quality monitoring system.

[0214] The three-dimensional scanning module is used to reconstruct the surface model of the gate wall and register and calibrate it with the design model;

[0215] The multi-axis 3D printed robotic arm is used to move along a spatially continuous variable parameter path generated by the manifold seeding-growth algorithm;

[0216] The two-component (component A: main concrete, component B: functional additives / fibers) material extrusion system is used to control the extrusion speed, material ratio, and rotation angle of the spiral nozzle to reproduce the designed spiral topology.

[0217] The path planning and quality monitoring system is used to perform the conversion from digital model to physical entity and to ensure the accuracy and quality stability of the printing process. Specifically, it includes generating a multi-dimensional collaborative printing path that includes spatial position, nozzle posture and process parameters based on the calibrated gate surface model.

[0218] The aforementioned 3D printing equipment also includes underwater local cofferdams and underwater anti-dispersion concrete printing heads for underwater partial repairs, enabling in-situ operations in non-drainage environments to address repair needs below the waterline.

[0219] The present invention also discloses a lock wall protection system, which consists of several of the above-mentioned anti-collision systems arranged in an array along the lock wall surface. The sensor networks inside each anti-collision system are interconnected and connected to the lock's health monitoring and digital twin platform. The digital twin platform receives on-site data in real time, maps the virtual model status, uses machine learning algorithms to predict the remaining lifespan and performance degradation trend of the structure, and visualizes the health status of the protection system to assist in operation and maintenance decisions.

[0220] The present invention also discloses a lock, wherein a lock wall protection system is installed on the lock wall.

[0221] Example

[0222] Taking the protection project of the left side lock wall of a three-stage inland waterway lock (effective lock chamber dimensions: length 180m × width 23m × water depth 4m) as an example, this paper elaborates on the execution process of the 3D printing adaptive bionic spiral anti-collision method for lock walls, the design of the 3D printing adaptive bionic spiral anti-collision system for lock walls, and the equipment operation.

[0223] Assume the left gate wall is the target, with a total length of 180m, an average height of 8m, and a surface of curved concrete (local Gaussian curvature K∈[-0.02, 0.05] m). -2 Then, AIS data and video monitoring records from the lock over the past 5 years were collected, showing that 70% of collisions occurred in the gate area (within 5m of the gate), 25% of the scraping occurred in the middle of the navigation wall, and 5% of the fatigue impact occurred in the water level fluctuation zone (±1.5m). The design protection requirements are: design life ≥ 50 years, specific energy absorption efficiency (SEA) ≥ 15 kJ / kg, and peak impact force reduction ≥ 40%.

[0224] A 3D-printed adaptive biomimetic spiral anti-collision method for lock walls includes the following specific steps:

[0225] Step 1: Define the manifold space on the gate wall surface

[0226] Point cloud data of the gate wall was acquired using a 3D laser scanner, encapsulated into a NURBS surface using Geomagic software, and embedded into a 3D Euclidean space R³. The gate wall surface was discretized into a finite element mesh (0.1m × 0.1m), and the first and second fundamental form coefficients (E, F, G) and the second fundamental form coefficient (L, M, N) of each mesh point were calculated to obtain the Gaussian curvature K and the average curvature H distribution; for example, K = -0.018 m at the bottom groove of the gate wall. -2 (Saddle surface), K=0.032 m at the top flange -2 (Convex surface);

[0227] Step 2: Construct the probability field and entropy field of the impact load

[0228] Extracting parameters from AIS ( ∈[500, 5000] tons, ∈[0.1, 0.5]m / s, The dataset ∈ [15°, 90°] is aligned with video surveillance (one-to-one correspondence) to generate a historical ship berthing dataset D; the joint probability density function is estimated using kernel density (bandwidth: =500 tons, =0.05m / s, =5°) Calculation Then, the expected impact kinetic energy is calculated by substituting the data. For example, E at the center point u0 of the gate area is calculated. k =2.8×10 4 J, construct the load-driven entropy field. Let b=e, and calculate the entropy value of each zone. For example, calculate the entropy value H of the gate zone. load =4.2 (high uncertainty), navigation wall H load =1.8 (low uncertainty);

[0229] Step 3: Constructing the printing process constraint potential field

[0230] Apply sag constraints and set ϕ crit =45°, ϕ max =60°, λ1=2; for example, at the groove at the top of the gate wall, ϕ=55°, and U is calculated. sag =exp(2(55 / 60-1))=1.15, apply reachability constraints, and calculate the Jacobian condition number k for the six-axis robotic arm. max =15, k(J) in the middle of the gate wall = 8 → U reach =0.53, merging potential field calculation, taking w1=0.7, w2=0.3, the calculated Uprint =0.7×1.15+0.3×0.53=0.97;

[0231] Step 4: Forming a design-driven entropy field

[0232] Let the penalty coefficient η = 1.0, then:

[0233] The center of the gate area has a diameter Φ = 4.2 / (1+0.97) = 2.13 (high drive value), and the navigation wall has a diameter Φ = 1.8 / (1+0.65) = 1.09.

[0234] Step 5: Generating a spiral topology using the manifold seeding-growth algorithm.

[0235] First, seed initialization is performed. Five seeds are placed at local maxima points where Φ>1.5 (three in the gate region and two in the navigation wall). Growth simulation is then conducted. The growth direction is determined by solving the Euler-Lagrange equation, with the seeds extending towards the Φ gradient direction (e.g., converging towards the center in the gate region). The spiral parameters are adjusted, including the spiral pitch in the gate region. =0.85m ( =0.032→ = =0.6×(1+0.5×0.179)=0.85m), Similarly, calculate the navigation wall. =2.5m;

[0236] To engage in competitive fusion, the spacing between the two navigation wall seeds =0.3m < threshold (0.5m), helix angle difference Δθ = 5° → =0.95, merging into a single banded structure; then tidal deposition, using the Cahn-Hilliard equation to simulate a 0.2m thick layer, with strain energy checked for each layer. < =3 MPa ( =3 MPa corresponds to a polypropylene-basalt fiber composite material).

[0237] Using the termination condition as the criterion, after 500 iterations, =0.32 close to the target =0.3, and <10 -4 ;

[0238] Step 6: Output the partitioned protection unit model

[0239] Heavy-duty energy absorption unit (gate area): =0.8 / 1.2=0.67, helix angle θ=25°. This parameter range is much smaller than the equivalent parameter of traditional protective structures, aiming to achieve higher local energy density through a tighter helical arrangement.

[0240] Wear-resistant guide unit (navigation wall): = 4.5 / 1.0 = 4.5, helix angle 65°;

[0241] Dry and wet durability unit (water level fluctuation zone): =0.6m+0.1×h (h is the water depth in meters);

[0242] The output is a STEP format file, which includes a pre-embedded sensing channel (fiber optic hole with a diameter of 5mm).

[0243] A 3D printing device operates as follows:

[0244] Position the robot to the gate wall coordinates (x=90m, y=0m), calibrate the model deviation to <2mm using the 3D scanning module, move the robot arm along the spiral trajectory generated by the algorithm, control the overhang angle to ϕ<40°, set the extrusion speed of the two-component nozzle to 10 kg / h, and match the spiral nozzle rotation speed to the pitch (e.g., 30 rpm in the gate area).

[0245] Deployment of the protection system: 90 standard units (2m×1m) are arranged along the gate wall array, and the sensor network is connected to the edge server via LoRaWAN; the digital twin platform displays the unit strain data in real time, and triggers an early warning when the peak strain > 0.2%.

[0246] Effect prediction

[0247] Impact tests of the prototype showed that the SEA was ≤18kJ / kg, and the peak force was reduced by 45%. It also greatly improved construction efficiency, with unit printing and installation taking no more than 6 hours, saving 75% of downtime compared to traditional fender replacement.

[0248] The 3D printing adaptive bionic spiral anti-collision method and anti-collision system for lock walls of this invention can realize a complete technical closed loop from data-driven design and intelligent adaptive construction to intelligent operation and maintenance throughout the entire life cycle of lock protection structures.

[0249] The scope of protection of this invention is not limited to the specific embodiments described above. Any changes made based on the core principles of this invention, including but not limited to equivalent substitutions of technical solutions and structural improvements, should be considered to fall within the scope of protection of the claims of this invention. Various modifications and adjustments made to the implementation schemes by those skilled in the art without departing from the design concept of this invention also fall within the scope of protection of this invention.

Claims

1. A 3D-printed adaptive biomimetic spiral anti-collision method for lock walls, characterized by: It includes the following steps: S1, Define the manifold space on the gate wall surface; S2. Based on the historical ship berthing data of the target lock, construct the impact load probability field of the lock wall surface in step S1, and calculate the load-driven entropy field according to the impact load probability field. S3. Construct 3D printing process constraints and obtain the printing process constraint potential field; S4. Combine the load-driven entropy field in step S2 with the printing process constraint potential field in step S3 to form the design-driven field. S5. Based on the manifold seeding-growth algorithm, the design driving field in step S4 is used as the growth guiding field to simulate the competitive growth and merging process of spiral manifold seeds on the gate wall surface, and adaptively generate non-uniform spiral topology configuration. S6. Combine the non-uniform spiral topology generated in step S5 with the gate wall functional zoning to output a zoning and parameterized protection unit design model.

2. The 3D-printed adaptive bionic spiral anti-collision method for lock walls according to claim 1, characterized in that: Step S1 includes: cleaning the surface of the lock wall. Defined as a two-dimensional Riemannian manifold embedded in three-dimensional Euclidean space In the middle; let any point on the manifold The local coordinates are Let the surface be parameterized as 𝑟 The unit normal vector is 𝑛, and the Gaussian curvature at this point is 𝑛. and mean curvature From the first fundamental form coefficients Second fundamental form coefficient Sure: in, , , , , , .

3. The 3D-printed adaptive bionic spiral anti-collision method for lock walls according to claim 2, characterized in that: Step S2 includes: Historical AIS data and video surveillance records of the target lock were collected to extract key parameters of typical berthing events, including the total weight of the vessel. Longitudinal speed of the ship approaching the lock wall The angle between the ship's course and the normal direction of the lock wall Coordinates of the position of the ship in contact with the lock wall Aligning AIS timestamps with video frame timestamps and linking ship dynamic data with physical locations in video footage, a historical ship berthing dataset is created. N represents the total number of typical berthing events. A joint probability density function is constructed using kernel density estimation. For the lock wall surface in step S1 any point on the manifold The expected impact kinetic energy it withstands for: in, Indicates the direction correction factor; This represents the integral summation of the total weight, speed, and included angle of all ships that may collide with the lock wall; Based on the definition of Shannon entropy, position The load-driven entropy field at a given location is defined as: in, Indicates impact energy; Indicates impact energy The space of values; Indicates position Impact energy The probability distribution; This means taking the logarithm of the probability density function; This represents the impact energy values ​​for all possible scenarios. Perform integration and summation; Step S3 includes: setting the normal vector of the printing nozzle as... The surface of the gate wall is in position The normal vector at is ; Overhang angle ; The sag constraint function is expressed as: in, This represents the suspension sensitivity coefficient; Indicates the maximum theoretical overhang angle; Indicates the critical overhang angle. When the actual overhang angle Exceed When the value is , the constraint is activated, that is ,otherwise Setting it to 1 means there is no penalty; Reachability constraints for a printing robotic arm: Jacobian matrix based on the robotic arm condition number The quantization of dexterity, the reachability constraint function is expressed as: in, Represents the joint angle vector of the robotic arm; Indicates the arrival location Required joint angle; express The maximum value under all possible configurations; The constraint potential field of the printing process is represented as: in, Indicates the overhang weight coefficient; This represents the reachability weight coefficient.

4. The 3D-printed adaptive bionic spiral anti-collision method for lock walls according to claim 3, characterized in that: Step S4 includes: driving the entropy field with the load from step S2. With the printing process constraint potential field in step S3 Integration, forming a design-driven field The calculation formula is: in, This is the penalty coefficient.

5. The 3D-printed adaptive bionic spiral anti-collision method for lock walls according to claim 1 or 4, characterized in that: Step S5 includes the following sub-steps: S5.1 Initialize the gate wall growth substrate by discretizing the three-dimensional surface of the gate wall into a finite element mesh; at each mesh point Define its state as empty, seed, growing, or entity; in designing the driving field Local maximum location Automatic placement of the initial manifold seed, seed set ; Each seed Defined as a quadruple state vector: in, Indicates the seed at time The state; Indicates the seed at time Coordinates on the manifold of the gate wall; Indicates the seed at time The growth rate vector; Indicates the seed at time The local helix angle; Indicates the seed at time Material density / growth strength; S5.2 Constructing manifold competitive growth, simulating the structure growth process through iterative loops, including: (1) Growth direction decision The growth of manifolds follows a modified Hamiltonian principle, and its Lagrange... Defined as kinetic energy term With potential energy term Dissipation terms The difference is expressed as: Among them, the kinetic energy term and Proportional; Potential energy term It is a design-driven field The function; dissipation term Represents the dissipation function; The growth trajectory is derived from the Euler-Lagrange equation: in, Indicates external generalized force. It is a "generalized force" driven by design-driven fields, pointing towards The direction of fastest growth guides the seed to move towards the high-energy-demand region or extend along the potential energy ridge; R is the Rayleigh dissipation function, used to define the dissipation force. Another form, It is the viscous damping coefficient; (2) Adaptive adjustment of spiral parameters Spiral evolution: helix angle The adaptive change follows a curvature-driven flow, expressed as: in, Indicates the response intensity coefficient; This represents the gradient of the design field along the tangent of the equipotential surface; This indicates rotational adjustment along the gradient direction; Indicates the smoothing coefficient; Represented as a diffusion smoothing term; pitch Physical constraints: pitch With local Gaussian curvature Coupling, position The local pitch at a certain point is expressed as: in, Indicates the basic pitch; Indicates the curvature coupling coefficient; Indicates the position of the gate wall surface. Gaussian curvature at that point; Represents a sign function, when When, it is 1, when When, it is -1; S5.3 Manifold Competition and Fusion Mechanism S5.31, Interaction Potential Energy When two seeds and Euclidean distance between When, define the interaction potential energy for: in, This is a preset distance threshold; Indicates the depth of the potential well; Indicates the scale of the effective distance; This represents the helix angle consistency coefficient, whose value is determined by the difference between the two helix angles. The range is (0, 1]; Indicates two seeds and The difference in helix angle, i.e. ; Indicates angular tolerance; If the helix angles are consistent, that is As the potential approaches 1, the potential well becomes deeper, at which point fusion occurs. If the difference in helix angle is large, that is When the repulsive force approaches 0, competition occurs, and weaker seeds are suppressed. S5.32, Topology Merging Criteria When merging occurs, the state of the new seed is updated to the weighted average of the two old seeds: in, This represents the state vector of the new seed generated after fusion; , These represent the growth intensity of the two original seeds respectively; S5.4, "Tidal" Sedimentation and Mechanical Equilibrium S5.41, Evolution of Volume Fraction Define phase field variables , representing a spatial point The material occupancy rate at a given location: 0 = empty, 1 = solid. The evolution follows a modified form of the Cahn-Hilliard equation, expressed as: in, Indicates mobility; chemical potential , representing the thermodynamic driving force that drives material diffusion; Indicates the gradient energy coefficient; It is the print source item; S5.42 Structural stability check After each layer of deposition is completed, calculate the total potential energy of the system. , is represented as: Among them, total potential energy Includes strain energy and work done by external forces; Representing strain energy density, through Calculate, where, Represents the strain tensor. Represents the elastic tensor; Represents volume force; Represents the displacement field; 'Indicates surface force; According to the principle of minimum potential energy The strain energy density calculated during the growth process Exceeding the material strain energy density threshold At that time, backtrack and adjust the local growth rate vector. Or increase the local material density ; S5.5 Define global topology order parameters Based on the Minkowski functional: in, Indicates at time The volume of the generated structure; Indicates at time Surface area; The loop stops when the following condition is met, indicating that the structure has reached the expected topological complexity and growth tends to stagnate; denoted as: in, Indicates the target topological order parameter; Indicates the topological convergence threshold; This represents the dynamic convergence threshold.

6. A 3D-printed adaptive biomimetic spiral anti-collision system for a lock wall, generated based on the 3D-printed adaptive biomimetic spiral anti-collision method for lock walls as described in any one of claims 1 to 5, characterized in that: It is 3D printed in one piece, and contains a non-uniform spiral structure inside, which is integrated with the functional zoning of the lock wall for zoning optimization; it includes several protective units, namely: The heavy-duty energy-absorbing unit is located in the gate region, corresponding to the high impact entropy region, and generates a high-density, small-pitch spiral cluster structure. The internal topology consists of multiple first spiral structures that are closely packed in space. Wear-resistant guide units are installed on the navigation wall and applied to the navigation wall area where ships have a high probability of collision. They generate a spiral ribbon structure with a long pitch and a large helix angle. The internal topology is mainly composed of continuous spiral ribbon structures. The wet and dry durability unit is located in the water level fluctuation zone and has a pitch that changes continuously from the above-water position to the underwater position; it spans the highest and lowest water level lines, and the internal second spiral structure changes in a gradient along the vertical direction.

7. The 3D-printed adaptive bionic spiral anti-collision system for lock walls according to claim 6, characterized in that: It also includes one or more of the following features: (1) In the heavy-duty energy-absorbing unit, the average pitch of the first helical structure With the outer diameter of the helix The ratio is limited to between 0.5 and 1.5, and the angle between the main axis of each first spiral structure and the normal plane of the gate wall is designed to be less than 30 degrees. (2) In the wear-resistant guide unit, the average pitch of the spiral ribbon structure With the outer diameter of the helix The ratio is set between 3.0 and 8.0; the main axis of the spiral ribbon structure is parallel to the center line of the gate, and the spiral angle is designed to be greater than 60 degrees; (3) In the dry and wet durability unit, in the area above the designed highest water level, the pitch of the second spiral structure Designed as a benchmark In areas below the design minimum water level, the pitch... With water depth Linear increase, satisfying ,in, '' represents the pitch amplification factor; (4) Each of the protection units is pre-embedded with fiber optic sensors and conductive concrete sensors. (5) It also includes an edge computing server, which is deployed at the lock site to run a lightweight damage diagnosis model, perform real-time analysis of sensor data, and identify abnormal impacts.

8. A 3D printing device, used for printing a 3D-printed adaptive bionic spiral anti-collision system for a lock wall as described in claim 6 or 7, characterized in that: It includes a mobile waterborne operation platform, which is equipped with a 3D scanning module, a multi-axis 3D printing robotic arm, a two-component material extrusion system, and a path planning and quality monitoring system. The three-dimensional scanning module is used to reconstruct the surface model of the gate wall and register and calibrate it with the design model; The multi-axis 3D printed robotic arm is used to move along a spatially continuous variable parameter path generated by the manifold seeding-growth algorithm; The two-component material extrusion system is used to control the extrusion speed, material ratio, and rotation angle of the spiral nozzle to reproduce the designed spiral topology. The path planning and quality monitoring system is used to perform the conversion from digital model to physical entity and to ensure the accuracy and quality stability of the printing process, including: generating a multi-dimensional collaborative printing path containing spatial position, nozzle posture and process parameters based on the calibrated gate surface model.

9. A lock wall protection system, comprising the 3D-printed adaptive bionic spiral anti-collision system of the lock wall as described in claim 6 or 7, characterized in that: It consists of several anti-collision systems arranged in an array along the gate wall. The sensor networks inside each anti-collision system are interconnected and connected to the lock's health monitoring and digital twin platform.

10. A lock, wherein the lock wall is equipped with the lock wall protection system of claim 9.

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