157 results about "Structural mechanics" patented technology

The invention provides a construction tunnel surrounding rock stability evaluation method based on digital twinning and a related device. The method comprises the following steps: constructing a tunnel digital twinning model of a tunnel construction section; geological data and real-time progress position data of a target mileage segment in the construction process are obtained; mapping the geological data to a digital twinborn model, and updating soil body unit parameters; according to the real-time progress position data, synchronously updating activation states of a soil body unit and a supporting structure unit in the model by adopting a state change method; and extracting a surrounding rock stability index based on the updated digital twinborn model, evaluating the stability of the current construction tunnel surrounding rock in combination with a safety threshold to obtain a construction tunnel surrounding rock stability evaluation result, and constructing a tunnel construction process dynamic mapping-oriented digital twinborn model by utilizing the description capability of a finite element method on structural mechanical behaviors. Geological conditions and construction progress information which are obtained in real time on site are used as input, and the construction period structure safety risk of the drilling and blasting method tunnel is evaluated and predicted.

The invention discloses a U-shaped aqueduct prestress multi-beam cooperative tensioning control method and system. The method comprises the steps that S1, a quantitative derivation model is constructed, based on an aqueduct structural mechanical equilibrium equation, a prestress coupling effect item is introduced for calculation, a prestress coupling matrix is output, and an initial tensioning sequence is derived; the device is simple in structure, and an initial tensioning sequence is deduced by establishing a mechanical equilibrium equation and introducing a coupling effect item; meanwhile, stress / displacement deviation data collected by a monitoring system in real time are fed back to an edge calculation terminal to calculate a control strategy in real time, adjustment is executed by a tensioning device, and therefore a field data closed-loop optimization mechanism is constructed, the tensioning force and sequence can be dynamically corrected, the limitation of a static model is broken through, and the construction efficiency is improved. And a displacement constraint term is introduced as a punishment or control condition in the optimization process, so that deformation overrun of key parts of the structure is effectively prevented, and the precision, safety and intelligent level of prestress construction are remarkably improved.

The invention relates to the technical field of network public opinion monitoring, and discloses an emotion energy dynamic change-based public opinion inversion recognition method, which comprises the following steps of: constructing a weighted emotion potential energy field, and calculating effective emotion potential energy of nodes; and then calculating semantic field topological stress representing the viewpoint structure tearing degree and emotional potential energy field system entropy representing the energy distribution disorder degree, on this basis, constructing an entropy-stress two-phase state space and a dynamic hysteresis loop model, quantifying the social damping characteristics of the system, monitoring the system state in real time, and determining the state of the system. When the two-phase space yield judgment condition and the damping failure judgment condition are met at the same time, a public opinion inversion early warning signal and a risk probability index are output, the critical characteristics of public opinion system instability can be accurately recognized from the dimensions of structural mechanics and dynamics, and the false alarm rate of inversion early warning is effectively reduced.

The invention relates to the technical field of engineering monitoring, in particular to a bridge structure state monitoring method and system based on digital twinning, and the method comprises the steps: building a multi-source monitoring data matrix based on a data timestamp; establishing a geometric model, a material attribute model and a load model of a bridge structure based on the multi-source monitoring data matrix, and fusing to obtain a bridge digital twin initial model; and carrying out structural mechanical analysis based on the bridge digital twin initial model to obtain stress distribution data of each region of the bridge. Through real-time acquisition and analysis of multi-source monitoring data, the method can dynamically evaluate the structural state of the bridge and timely identify potential safety hazards, so that the safety of the bridge is improved; and through calibration of the initial model, the obtained digital twin precise model reflects the real state of the bridge, and a more accurate data basis is provided for subsequent structural analysis.

The invention provides a bridge health monitoring missing displacement reconstruction method based on a conditional diffusion model, which comprises the following steps: firstly, constructing a diffusion model taking multi-source physical sensing information as a guide condition, and inputting multi-source heterogeneous sensor information such as strain and acceleration as physical conditions; secondly, a residual module and a time coding mechanism are introduced in the reverse denoising process, and the time sequence feature and deep feature extraction capacity of the model is enhanced; and finally, gradually reconstructing a complete and physically reasonable displacement time history from missing displacement data containing noise by using the model, and realizing reliable reconstruction of bridge structure response. The method aims at stably and efficiently reconstructing a complete displacement time history which is accurate in numerical value and conforms to the structural mechanics principle from incomplete or completely missing displacement data, so that the integrity of SHM data is recovered, and a reliable data basis is provided for subsequent structural safety assessment and damage identification.

The invention discloses a method for setting and controlling a buckle cable adjustment threshold value in large-span arch bridge hoisting construction, which comprises the following steps of: acquiring construction parameters of a current buckle section, and acquiring a corresponding cable adjustment target value; constructing a structural mechanics finite element model of the target buckle cable based on the construction parameters, and introducing a buckle cable multi-harness nonlinear stress mechanism into the model to calculate upper and lower limit thresholds of cable force in the tensioning process; determining an elevation adjustment threshold according to the target axis, the target elevation, the accumulated deviation and the pre-deformation compensation amount in combination with a geometric linear control model; and generating an environmental influence correction coefficient by utilizing construction environmental parameters, and dynamically correcting the cable force and the elevation threshold value to realize real-time updating of the threshold value in the hoisting process. According to the method, the problems of nonlinearity of multiple wire harnesses of the large-span arch bridge buckle cable, high linear sensitivity of the arch rib, remarkable environmental influence and the like are solved, high-precision cooperation of cable force control and linear control is realized, and the safety, controllability and construction efficiency of hoisting construction are improved.

The invention discloses an arch bridge tensioning method and system based on a physical constraint space-time diagram attention network, and the method comprises the steps: constructing a dynamic topological graph of an arch bridge cantilever construction structure, taking a structure initial state parameter, a control force system parameter and a real-time environment parameter as node input features, and taking a structure state response parameter as an output label, generating a training data set based on finite element model simulation; designing a deep learning network model combined with space diagram attention and time sequence causal convolution, and modeling a space-time dependency relationship; defining a mixed loss function of the data fidelity item and the physical residual loss item of the structural mechanical control equation; and training the model through a back propagation algorithm and deploying the model to a field decision control system. According to the method, through graph structure abstraction, spatio-temporal joint modeling and physical constraint embedding, multi-source monitoring data driven structure state online prediction and tension control strategy intelligent optimization are achieved.

The invention relates to the technical field of building safety monitoring, in particular to a building construction safety monitoring system with automatic detection and danger early warning functions. Comprising a multi-dimensional data automatic acquisition unit; a dynamic risk analysis unit; a grading danger early warning unit; and an emergency linkage control unit. According to the invention, through the construction stage identification module, the weight dynamic adjustment module and the risk quantification and feature matching module, the current construction stage is determined based on the excavation depth of the foundation pit, the installation elevation of the steel structural member and the total height of the building; the weight ratio of each physical parameter is dynamically adjusted by combining the basic weight matrix and the mechanical influence factor matrix of the corresponding construction stage, then the comprehensive risk value is calculated through the single-parameter deviation degree and the deviation acceleration, the hidden danger type is matched, and the risk analysis key point can be adjusted according to the structural mechanical characteristics of different construction stages. The problems of lack of dynamic adaptation capability and limited risk assessment precision in the prior art are solved.

The application provides an automatic disk IO method based on structural mechanics CAE simulation software, comprising the following steps: S1, constructing a memory-disk cooperative computing framework, and dynamically monitoring a data access state in a simulation solving process; S2, automatically exchanging non-active core data structures to a high-performance disk according to a data access frequency, a life cycle and a memory pressure; S3, loading back to the memory on demand when subsequent calculation needs to access the data exchanged to the high-performance disk; wherein the core data structures comprise a stiffness matrix, shape function data, an intermediate result vector and derivative physical quantities, and the exchange process is transparent to the solver. According to the application, the exchange process is highly transparent to the core computing logic of the solver, is automatically managed by the system, and does not need user intervention, so that efficient utilization of memory resources and stable operation of super-large-scale model simulation are realized.

The present application belongs to the technical field of power transmission line structure health monitoring, and discloses a power transmission line tower group structure mechanics response and multi-source remote sensing parameter fusion analysis method based on graph neural network. The method aims at the problems of existing finite element simulation modeling complexity, incomplete sensor monitoring, lack of physical mapping of multi-source remote sensing data and tower mechanics response, acquires and pre-processes tower structure parameters and multi-source remote sensing data, and constructs a tower group graph data model; taking span as a unit, combining conductor mechanics equation to calculate load and unbalanced tension, building a graph neural network model integrated with tower axial force and bending moment bearing capacity physical regularization constraint; after training by historical working condition data, inputting new remote sensing and meteorological data to reconstruct tower group mechanics response field, generating risk early warning according to safety threshold. The present application realizes deep fusion of mechanics mechanism and remote sensing data, quickly and accurately reconstructs tower group mechanics response field, and outputs the results conforming to the structure mechanics balance law, thereby providing technical support for power transmission line health monitoring.

The scheme belongs to the technical field of structural mechanics, and discloses a metamaterial rod outputting only tensile waves and application thereof.The metamaterial rod comprises an even number of guide rods arranged symmetrically and a plurality of cells linearly arranged on the guide rods, each cell comprising a first connecting plate, a second connecting plate, a first inclined rod, a second inclined rod, a third inclined rod, a fourth inclined rod and a spring, and the stiffness of the first cell is smaller than that of the other cells.By utilizing external friction, the momentum conservation of the system is broken, and through in-depth analysis of the propagation mechanism of elastic waves, the metamaterial rod with uneven distribution is ingeniously designed, and the cells are unevenly arranged, so as to realize the unusual function of outputting only tensile waves.No matter whether an impact, a sudden stretching, a stretching or an alternating repeated load of stretching and compression is applied to one end of the rod, only the tensile signal is output at the other end of the rod, and the transmission of the tensile wave also exhibits the characteristics of a solitary wave, and the original wave shape and amplitude are maintained during the propagation process.

The invention discloses a structural load prediction method, device and equipment and a computer readable storage medium, and relates to the technical field of wind power, and the method comprises the steps: obtaining geometric parameters and material attribute parameters of a to-be-predicted fan structure, and an environment parameter feature range of an environment where the to-be-predicted fan structure is located; constructing a multi-physics field coupling model according to the geometric parameters, the material attribute parameters and the environmental parameter characteristic range; the multi-physics field coupling model comprises a temperature field module, a structural mechanical field module, an airflow field module and a particle impact field module, and the physics field modules perform bidirectional data exchange through coupling interfaces to simulate interaction among the physics fields; acquiring an environmental parameter value of the to-be-predicted fan structure under the target working condition; inputting the environmental parameter values into a multi-physics field coupling model to obtain mechanical response data of the to-be-predicted fan structure under the target working condition; and determining predicted load data of the to-be-predicted fan structure according to the mechanical response data.

This invention belongs to the field of reactor structural mechanics technology, specifically relating to a method for analyzing and evaluating high-temperature bolted connection sealing structures. The invention includes the following steps: selecting the location of the reactor pressure vessel flange and main bolt connection as the object of sealing structure analysis; analyzing and summarizing the influence of gasket data on the deformation and contact surface pressure of various components of the flange bolted connection structure; researching current standards and analyzing their limitations; using the finite element software ANSYS to perform finite element modeling of the reactor pressure vessel flange and main bolt structure; applying loads and constraints to the finite element model of the reactor pressure vessel flange and main bolt structure; calculating the deformation and stress of the structure using different creep and relaxation models; analyzing the relaxation behavior of the high-temperature flange bolted connection structure using experimental methods; and comparing and analyzing the results of the finite element method, the standard method, and the experimental method. This invention enables the analysis and evaluation of the sealing performance of flange bolted connection structures under high-temperature environments.

The invention discloses a fatigue analysis method and device, electronic equipment and a storage medium, and relates to the technical field of vehicle testing. The fatigue analysis method comprises the following steps: acquiring three-dimensional model data of a mine truck, and constructing a whole vehicle finite element model according to the three-dimensional model data; determining multi-working-condition mechanical response data of the mine truck under a target working condition based on the whole vehicle finite element model, generating a stress analysis result according to the multi-working-condition mechanical response data, and determining a target weak structure of the whole vehicle frame through the stress analysis result; acquiring working condition data of the target weak structure and a preset key part under an actual working condition, and determining a target load spectrum according to the working condition data; and determining structural mechanical response data corresponding to the target load spectrum based on a preset rack control system, and determining the fatigue life of the mine truck according to the structural mechanical response data. According to the embodiment of the invention, the accuracy of determining the fatigue life is improved.

The present application relates to the technical field of structural mechanics analysis, in particular to a spreader saddle stress nephogram generation method and system, comprising the following steps: based on the spreader saddle regional cable segment force measurement and spatial geometric information, constructing the initial stress of the saddle body grid, obtaining the stress concentration rate distribution through homogenization and normalization, extracting the gradient mutation grid to form a sequence of demarcation points, and generating the saddle area nephogram in the HSV space mapping according to the non-uniform color scale. The present application can adaptively identify the area with the most severe stress change by introducing the analysis of stress concentration rate and its spatial gradient, and no longer relies on the fixed color scale division method, but uses the high gradient position as a dynamic anchor point to construct a non-uniform color scale sequence. The processing logic tilts the color scale resolution according to the real stress response of the structure, making the color transition in the stress concentration area more fine, and the stress peak and gradient form are clearly presented. At the same time, a wider color scale interval is used in the stress gentle area for general expression.

The invention discloses a wind power blade subcomponent structure bending torsion loading failure analysis and optimization method, and belongs to the technical field of wind power blade structure mechanical analysis. The analysis method comprises the following steps: establishing a three-dimensional entity finite element model of a wind power blade sub-component, applying pure shimmy, pure torsion and gradient bending-torsion combined load to carry out nonlinear static analysis, extracting critical failure point data, and comparing and analyzing a rear edge buckling waveform, bonding failure migration and contact behavior change, so as to obtain a critical failure point. According to the method, the internal relation of blade rear edge bonding structure failure, buckling waveform and contact behaviors under the bending-torsion coupling working condition is defined, the migration rule of the rear edge failure position along with the torsion angle and the stress distribution difference between the front edge and the rear edge are defined, and the problem that in the prior art, it is difficult to accurately position the blade vulnerable area under bending-torsion coupling is solved; and a mechanical basis is provided for blade structure optimization. The analysis result obtained through the analysis method can be directly used for guiding the anti-bending coupling design of the blade.

The invention belongs to the field of ship strain field inversion, and particularly discloses a ship structure strain field inversion method and system based on a graph neural network, and the method comprises the steps: taking a whole ship structure finite element calculation result as original data, designing a composite objective function through introducing a multi-information attention mechanism based on the graph neural network, and obtaining a ship structure strain field inversion model; guiding the model to learn a strain propagation rule; and iteratively optimizing parameters based on multi-working-condition simulation data, establishing a ship global strain field inversion model, and realizing high-precision reconstruction under sparse observation. According to the method, the relation between the ship local strain points and the strain field is established through an intelligent algorithm, reconstruction of the strain field of the whole ship structure can be inverted through a few strain monitoring points, and then the strain field and stress field states of the ship structure can be analyzed according to structural mechanics knowledge; and a new method is provided for the inversion of the health monitoring strain field of the current ship structure.

The invention provides a parallel robot trajectory optimization method and device based on a self-adaptive Bezier curve. The method comprises the steps of data acquisition, attitude analysis, structural mechanics analysis, evaluation index selection and weight formulation. Key posture parameters and stress conditions of the side protection mechanism are obtained by monitoring pressure of a rodless cavity of a side protection jack and displacement of a piston rod, and the side protection state is monitored by selecting six indexes through posture analysis and structural mechanics analysis of the side protection mechanism. In order to solve the problems of small rod diameter, small cylinder diameter and severe working environment of the side protection jack, the built-in wireless pressure and displacement sensor is adopted to obtain displacement and pressure data of a piston rod of the side protection jack, and meanwhile, the posture of the side protection plate is calculated through the obtained data information; recognizing the face protection state according to the key posture parameters of the face protection plate and the supporting force of the face protection plate to guarantee safe and efficient production of the fully mechanized coal mining face.

The invention discloses a BIM-based management and control optimization method for synchronous lifting of electromechanical pipelines along with a steel platform, and relates to the technical field of civil engineering construction. According to the method, through integrated BIM modeling and multi-dimensional verification, space collision between the pipeline and the steel structure is eliminated in advance, a supporting system is precisely designed, stress parameters are calculated, millimeter-level installation precision is achieved, real-time monitoring and improvement of synchronism, pipeline posture and supporting stress and simulation and prediction of finite element structural mechanics are achieved, the distribution reasonability of electromechanical pipelines is improved, and the reliability of the system is improved. The method has the advantages that hierarchical regulation and control can be quickly triggered when abnormal conditions occur, accordingly, high-altitude operation quantities can be greatly reduced, safety risks can be reduced, the construction efficiency can be improved, full-process data can be integrated, BIM models can be associated with one another, traceable operation and maintenance files can be formed, reasonable operation and maintenance spaces can be reserved, data bidirectional query links can be established, and accurate support can be provided for later-stage repair and maintenance; and full-life-cycle synchronous optimization of construction and operation and maintenance is realized.

The invention relates to the technical field of life prediction, in particular to a model for predicting the durability life of a prestressed concrete pipe in a chlorine salt erosion environment. The method comprises the following steps: calibrating material key parameters required by a prediction model through an accelerated corrosion test of a prototype pipe, calculating a time-varying chloride ion diffusion coefficient based on the material key parameters and collected environmental data, solving the time required by diffusion of chloride ions to the surface of a prestressed tendon and reaching a critical concentration through numerical calculation, and taking the time as the corrosion initiation life of the pipeline. And predicting the failure life. According to the method, on the basis of a full-size prototype test, material science, a transmission theory, electrochemistry and structural mechanics are fused, so that the problems of parameter distortion, mechanism simplification, boundary stiffness, lack of engineering representativeness and the like in a traditional life prediction model are solved; and accurate, reliable, explainable and decision-supportable intelligent prediction of the durability of the large water delivery pipeline in a complex service environment is realized.

This invention discloses a method for evaluating the performance impact of porosity in integrated circuit interconnect dielectric materials, comprising the following steps: S1: Testing the porosity, pore size, and pore distribution of the dielectric material in subsequent processes; S2: Establishing a molecular model of the dielectric material at the microscale and calculating the electrical, structural, mechanical, and thermal parameters related to porosity; S3: Performing finite element simulation calculations with coupled electro-thermal-solid multiphysics fields at the macroscale to simulate the electric field, temperature field, stress and deformation field, and the formation and evolution of macroscopic pores during the interconnect process in subsequent processes; S4: Analyzing the impact of porosity on electrical, structural, thermal, and mechanical properties and the manufacturing process based on the multi-scale simulation results. This invention establishes a quantitative relationship between dielectric material, porosity, process, and performance through multi-scale multiphysics field coupled simulation to evaluate the performance impact of porosity in integrated circuit interconnect dielectric materials and guide the design of dielectric materials and structures.

The present application relates to the technical field of engine simulation test, in particular to a thrust characteristic coupling model construction and numerical simulation method about attitude-adjusting engine, comprising: ontology model fusion algorithm platform, structural mechanics analysis calculation platform and multi-dimensional physical field coupling calculation platform. The present application extracts and fuses the models in the digital prototype model library and verification environment model library of the attitude-adjusting engine, couples the corresponding models with the conditional load excitation, checks, and realizes the numerical simulation of the thrust characteristic coupling model under the multi-scene algorithm path matching, adjustment and multi-disciplinary policy algorithm module cooperation. Mainly divided into ontology model fusion algorithm platform, structural mechanics analysis calculation platform and multi-dimensional physical field coupling calculation platform.

The invention discloses a method for predicting accumulation of multiple hail impact damages of a composite radome, and belongs to the technical field of composite mechanics and structural mechanics. The method comprises the following steps: firstly, establishing a hail model by adopting a smoothed particle hydrodynamics (SPH) method so as to accurately simulate the impact crushing behavior of the hail model; secondly, performing refined finite element modeling on the composite panel and the honeycomb sandwich structure of the radome, and introducing a progressive damage evolution model based on a Hashin criterion and fracture energy; the core of the method is that a stress field, a damage variable and a deformation field which are obtained by previous impact simulation are used as initial conditions to be imported into subsequent impact analysis, so that accurate transmission of a damage state under multiple impacts and real simulation of an accumulation process are realized. According to the method, the problems that the damage history cannot be reflected by traditional single-time impact analysis, the grid dependence is high and the like are effectively solved, the accuracy and efficiency of multi-time impact damage prediction can be remarkably improved, and a reliable tool is provided for achieving anti-impact design and life evaluation of the radome.

The invention discloses an anti-slide pile cantilever section internal force and displacement calculation method, equipment and a medium, and relates to the technical field of engineering design, and the method comprises the following steps: solving a time-varying support reaction field parameter set and a cantilever section depth computational domain execution structural mechanics equation, and generating a predicted displacement curve and a predicted internal force curve; reconstructing the predicted displacement curve and the predicted internal force curve into a high-order tensor field, extracting local response correlation features through a depth separable convolution kernel, and generating a coupling response feature field; based on the coupling response characteristic field, reverse constraint correction is carried out on the time-varying support reaction field parameter set, combined solving is carried out in combination with a cantilever section depth calculation domain, and a correction displacement curve and a correction internal force curve are generated. According to the method, the space-time Gaussian process prior model is constructed, in computer-aided engineering, the internal force and displacement prediction precision is improved, and the reliability and applicability of cantilever section structure analysis under the complex stratum condition are achieved.

The utility model discloses a concrete-filled steel tube structure mechanical property testing device, which relates to the technical field of concrete-filled steel tube testing and comprises a bottom plate, symmetrical supports fixedly connected to two sides of the bottom plate, a pressing block arranged between the symmetrical supports, a connecting mechanism arranged at the upper end of the pressing block, and an axial testing mechanism arranged on the supports. The axial testing mechanism comprises a sliding groove, a guide groove is formed in the sliding groove and slidably connected with a sliding block, a lifting mechanism is arranged at the lower end of the sliding block, one end, away from the lower pressing block, of the sliding block is fixedly connected with an air cylinder, an output shaft of the air cylinder is fixedly connected with pressing plates, and the lower pressing block is located between the symmetrical pressing plates. The device has the beneficial effects that the sliding block slides in the guide groove, so that the sliding block drives the pressing plate to be coaxial with the concrete-filled steel tube, the air cylinder drives the pressing plate to approach the concrete-filled steel tube for centered limiting, and then the air cylinder drives the pressing plate to extrude the concrete-filled steel tube for axial pressurization, so that a comprehensive performance test is carried out on the concrete-filled steel tube.

The present application belongs to the field of ship strain field inversion, and specifically discloses a ship structure strain field inversion method and system based on a graph neural network, which comprises: taking the full-ship structure finite element calculation results as original data, based on the graph neural network, introducing a multi-information attention mechanism, designing a composite objective function, and guiding the model to learn the strain propagation law; based on the multi-working-condition simulation data, iteratively optimizing the parameters, establishing a ship global strain field inversion model, and realizing high-precision reconstruction under sparse observation. The present application establishes the connection between the ship local strain point and the strain field through an intelligent algorithm, can realize the reconstruction of the entire ship structure strain field from a few strain monitoring points, and can further analyze the ship structure strain field and stress field state according to the knowledge of structural mechanics, thereby providing a new method for the current ship structure health monitoring strain field inversion.

The invention provides an insulating gas operation and injection integrated device based on finite element analysis and a control method, and the method comprises the steps: building a finite element model, and generating multiple groups of working condition combinations to form a structured data set; and constructing a neural network to predict structural mechanical response data of the device. The method comprises the following steps: establishing a mapping relation between a device structure and load response by constructing a mechanical database covering all working conditions; based on the accurate data, a deep neural network is trained, and high-delay mechanical simulation data is converted into device mechanical behavior prediction, so that whether the stainless steel heater is used for hoisting a gas cylinder or not, the maximum deformation area is located in the midspan of a heating area and the edge of a mechanical arm abutment, and the stainless steel heater is not used for hoisting the gas cylinder or not; the maximum MISES stress position is located at the joint of the mechanical arm pier and the heating area; in the hoisting process, the maximum MISES stress position is located at the fixed end joint of the mechanical arm and the abutment, and therefore the running state of the device is predicted, regulated and controlled.

This application relates to the field of culvert design technology, specifically to a culvert design method based on a refined BIM model. The method includes: establishing a culvert BIM model; converting the model into a culvert finite element model; meshing the model to obtain all mesh elements for each component in the culvert finite element model; calculating the first evaluation value, local curvature, second evaluation value, and evaluation coefficient for each mesh element; filtering all mesh elements to obtain the mesh to be refined; refining the mesh; optimizing the culvert BIM model through seismic simulation analysis of the refined culvert finite element model; and generating culvert design drawings using the optimized culvert BIM model. This application avoids unnecessary global refinement, reduces computational resource consumption, and simultaneously achieves refined analysis to improve the accuracy of culvert structural mechanical performance evaluation, ensuring the safety and reliability of culvert design.

The application discloses a kind of large-span space curved surface special-shaped structure intelligent form finding design method, and the method comprises the following steps: constructing the initial three-dimensional parameterized model of curved surface special-shaped structure;Establish a hybrid loss function with structural mechanics performance index as the core;Intelligent form finding model is constructed based on conditional generative adversarial network, wherein the generator is responsible for the intelligent adjustment and variation of the initial model in curved surface form, and the discriminator synchronously judges the mechanical rationality, geometric feasibility and architectural expressiveness of the generated structure based on the hybrid loss function;Through the adversarial iterative training of generator and discriminator, the structure form is driven to be optimized based on mechanical properties, architectural form and other targets, and finally the ideal structure form is output.The application deeply integrates intelligent adversarial generation and reinforcement learning in structure form finding, and realizes the automatic, efficient and intelligent generation and performance-driven self-evolution of structure form under complex architectural constraints.

This invention discloses a stability analysis method for the bearing arch of a large-span tunnel based on compressive and tensile safety factors, belonging to the field of tunnel and underground engineering construction data analysis technology. The method includes the following steps: obtaining the tunnel geometry, surrounding rock mechanical strength, ground stress, and support parameters; simplifying the bearing arch formed by anchor spraying reinforcement into an arched beam elastically fixed to the sidewalls at both ends; determining the plastic loosening zone of the roof slab through numerical simulation, and using its self-weight as the main vertical load; calculating the internal forces and edge normal stresses of key sections of the bearing arch using structural mechanics, and classifying them into compressive and tensile stresses accordingly; calculating the compressive and tensile safety factors of each section based on the natural strength parameters of the surrounding rock, and using the minimum value as a quantitative index for evaluating the overall stability of the bearing arch. This invention establishes a quantitative mechanical model of the bearing arch, realizing accurate and convenient assessment of the safety of the anchor spraying support structure of the roof slab of ultra-large span tunnels.