Multi-working-condition adaptive rail transit box type frame structure design method and system

Abstract

The invention belongs to the technical field of rail transit, and particularly discloses a design method and system for a multi-working-condition adaptive rail transit box type frame structure. Comprising the steps of integrating geological and hydrological data, structural parameters and a standard library, generating structured design input, automatically calculating water and soil pressure according to stratum-structure relative positions, generating a load combination matrix, deducing a longitudinal section model in a linkage mode based on cross section parameters and calculation results, bridging a webpage platform and SAP2000 through JSON data, and achieving one-key generation of the model. And multi-objective optimization is carried out on the reinforcement scheme based on an intelligent algorithm, and standard and economical requirements are met. According to the method, data islands in rail transit box type frame structure design are eliminated, automatic parameter circulation and multi-system seamless integration are achieved, cross section and vertical section linkage modeling is achieved, the automation degree of multi-working-condition and multi-section calculation is improved, and manual intervention is reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of rail transit, and more specifically, relates to a design method and system for a box-type frame structure of rail transit with multi-condition adaptability. Background Technique

[0002] The box-type frame structure of rail transit is a structural system widely used in the underground structure of urban rail transit. It is a unidirectional load-bearing structure composed of a middle partition wall or an intermediate longitudinal beam-column system, a middle slab, and a peripheral plate wall. It is widely used in the main body of the station, air ducts, entrance and exit channels, and sections in the open-cut method, with an engineering proportion of more than 80%. Its design and calculation work includes the calculation of the main structure (main beams, columns, slabs, walls) and the calculation of local components (secondary beams at the hole edge, lintels in the wall, driving floor slabs, anti-pulling piles, etc.). Among them, the calculation of the main structure accounts for the main workload, and the overall stress analysis of the structure with specific geometric dimensions at a specific formation depth needs to be carried out. Generally, it is simplified to two-dimensional calculations - cross-section calculations and longitudinal-section (beam-column system) calculations. That is: along the transverse direction, several calculation cross-sections are divided according to different burial depths, structural forms, or structural dimensions respectively, and different beam-column frame systems along the longitudinal direction are used as several calculation longitudinal sections. Through the internal force analysis of multi-condition combinations, the dimensions and reinforcement of each slab, wall, beam, column, and pile component are determined by envelope.

[0003] The traditional cross-section and longitudinal-section calculations of the box-type frame structure of rail transit are a complex and professional process, mainly carried out according to the following steps and methods: (1) Manually query the specifications according to the safety level, seismic grade, civil air defense grade, etc. of the structure to determine the necessary design parameters; (2) Manually preliminarily determine the structural dimensions; (3) Manually calculate various loads acting on the cross-section according to the positional relationship between the structure and the formation, including permanent loads (such as the self-weight of the structure), live loads (such as vehicles, crowd loads), seismic loads, civil air defense loads, etc., and carry out load combinations according to the specifications; (4) Manually establish the mechanical model of the structure and calculate; (5) Manually carry out internal force analysis and the design of the cross-sectional dimensions of the structure; (6) Manually carry out reinforcement calculation, and check the cracks and deformations according to the specifications. (7) Then carry out similar operation calculations for other working conditions of the same cross-section, manually identify the most unfavorable working condition and carry out envelope design for each control position of the cross-section. (8) Then carry out the above operation calculations for other cross-sections and longitudinal sections.

[0004] As can be seen from the above, the cross-section and longitudinal-section calculation process of the box-type frame structure of rail transit is very cumbersome, with a large amount of manual work, and there are the following problems:

[0005] (1) Data silos: 1) The separation of structural parameters, formation information, load calculation, finite element modeling, reinforcement calculation, and specification checking requires manual extraction of information, multiple manual inputs, and data conversion. 2) The cross-section and longitudinal-section calculations are carried out independently, and data linkage cannot be realized, resulting in repeated modeling and calculation.

[0006] (2) Inefficient Process: 1) Key steps such as load calculation, finite element modeling, internal force analysis, and reinforcement design rely on manual operations. The process is cumbersome and difficult to cover all working conditions, accounting for over 60% of the time consumption. 2) Five major working conditions (including different water level combinations) must be calculated one by one: short-term, long-term, accidental, earthquake, and anti-floating. The data volume is huge and omissions are easy to occur, resulting in a rework rate of up to 30%.

[0007] (3) Reliance on experience: Reinforcement design requires manual extraction of multiple working condition calculation results and verification according to specifications, which can easily lead to insufficient or redundant reinforcement due to human negligence. Summary of the Invention

[0008] In response to the above-mentioned defects or improvement needs of the prior art, the present invention provides a multi-condition adaptable rail transit box-type frame structure design method and system, which integrates geological and hydrological data, structural parameters and specification libraries to generate structured design inputs, automatically calculates water and soil pressures based on the relative position of the stratum and structure, generates a load combination matrix, and derives the longitudinal section model based on the cross-sectional parameters and calculation results. The web platform and SAP2000 are connected through JSON data to achieve one-click model generation; the reinforcement scheme is optimized for multiple objectives based on intelligent algorithms to meet regulatory and economic requirements. This method supports batch calculations of multiple working conditions and realizes automated output from data input to calculation books, improving efficiency by 95% and reinforcement economy by 10%-15%. It can be widely used in urban rail transit underground projects.

[0009] To achieve the above objectives, according to one aspect of the present invention, a design method for a multi-operating-condition adaptable rail transit box-type frame structure is proposed, comprising the following steps:

[0010] Step 1: Construct a cross-section calculation project, in which the stratum and water level information, framework information, component information, and load information of the cross section are automatically extracted and analyzed by CAD import or manually input;

[0011] Step 2: Based on the relative relationship between the cross-section stratum, water level and main structure, as well as the load size and partial coefficient, calculate and generate a multi-condition load combination matrix, and save the multi-condition load combination matrix to JSON text;

[0012] Step 3: Use structural analysis software (SAP2000 software) to call the JSON text to automatically generate a cross-sectional model, divide the mesh, and apply boundary conditions. Simultaneously calculate multiple design conditions in parallel and extract the internal force values of each condition to the OUTPUT file.

[0013] Step 4: Based on the cross-sectional parameters and calculation results obtained in step 3, dynamically back-calculate the longitudinal loads and constraints, and establish a continuous longitudinal frame model for finite element calculation;

[0014] Step 5: Based on the cross-sectional model and the longitudinal section frame model, use an intelligent algorithm to perform multi-objective optimization on the reinforcement scheme, generate an optimal reinforcement design scheme, and generate a calculation book.

[0015] As a further optimization, in Step 1, construct a cross-sectional calculation project based on the geotechnical physical and mechanical parameters and design standard information, where

[0016] the geotechnical physical and mechanical parameters include: formation number, geotechnical name, natural unit weight, coefficient of earth pressure at rest, vertical subgrade reaction coefficient, horizontal subgrade reaction coefficient, modulus of deformation, cohesion, and internal friction angle;

[0017] the design standard information includes: safety level, fortification intensity, seismic design category, civil air defense category, crack width, cover thickness, rigid zone, and member force type.

[0018] As a further optimization, in Step 1, the cross-sectional formation and water level information includes the unit weight of the topsoil backfill, formation numbers of each layer, thicknesses of each layer, depth of the anti-floating water level, and depth of the normal water level;

[0019] the frame information includes: number of stories, number of spans, thickness of the overburden soil, height of each story, width of each span, whether there is an external annex, whether the retaining structure is considered, whether a coping beam is set, and whether anti-pull piles are set;

[0020] the member information includes the length of the member cross-section, width of the member cross-section, column spacing, concrete design strength grade, longitudinal reinforcement grade, and grade of the tension bar / stirrup;

[0021] the load information includes at least the main load, accessory load, seismic load, civil air defense load, and other loads;

[0022] the main load includes the water and soil pressure load, equipment load, load of the track roof air duct, ceiling load, pipeline load, decoration load, and construction load, and the other loads include ground surcharge, local surcharge, concentrated force, uniform load, trapezoidal load, and overhanging load.

[0023] As a further optimization, in Step 2, the multi-condition load combination matrix includes:

[0024] short-term design situation, persistent design situation, accidental design situation, and seismic design situation.

[0025] As a further optimization, Step 4 includes the following steps:

[0026] (41) Based on the cross-sectional structure parameters, establish a longitudinal section calculation project. According to the associated cross-section and associated column names, input the applicable axis number, side span position, and elevation difference from the reference plane in the SAP2000 software, and expand it longitudinally into a multi-span continuous frame longitudinal section model;

[0027] (42) Based on the cross-section finite element calculation conditions and results, dynamically back-calculate the longitudinal load and constraints, conduct longitudinal section finite element calculation, and extract the internal force values of each condition to the OUTPUT file.

[0028] As a further optimization, step five includes the following steps:

[0029] (51) According to the OUTPUT file and the reinforcement envelope principle, use an intelligent algorithm to perform multi-objective optimization on the reinforcement scheme, generate the optimal reinforcement design scheme, select the combination with the largest reinforcement among all the optimal reinforcement design scheme combinations as the control condition, and at the same time conduct structural checking according to the specifications to back-calculate the rationality of the reinforcement;

[0030] (52) Compare the calculated reinforcement with the actual input reinforcement value by the user. If the calculated required value < actual input value * 0.85, it meets the design requirements, generate the optimal reinforcement design scheme, and generate a calculation book; otherwise, return to step (51) for recalculation.

[0031] As a further optimization, in the reinforcement scheme, it includes two reinforcement methods: through reinforcement and non-through reinforcement for all slab-wall nodes of the frame structure.

[0032] As a further optimization, the through reinforcement at least includes: the top and bottom longitudinal bars of the slab, the left and right side longitudinal bars of the wall, and the additional bars at the slab-wall nodes. There are 3 types of steel bar input values related to each other and there are constraint conditions. Changing one value will synchronously modify the related positions.

[0033] As a further optimization, the calculation book at least includes: the load calculation process, screenshots of the finite element model and internal force nephograms, the reinforcement detail list and the checking results.

[0034] According to another aspect of the present invention, there is also provided a multi-condition adaptable rail transit box-frame structure design system, including:

[0035] The first main control module is used to construct a cross-section calculation project, and automatically extract and analyze or manually input the stratum and water level information, frame information, component information, and load information of this section through CAD import in the cross-section calculation project;

[0036] The second main control module is used to calculate and generate a multi-condition load combination matrix according to the relative relationship between the stratum, water level and the main structure of the section, as well as the load magnitude and partial factor, and save the multi-condition load combination matrix to a JSON text;

[0037] The third main control module is used to call the JSON text by using SAP2000 software to automatically generate a cross-sectional model, divide the grid and apply boundary conditions, and simultaneously calculate multiple design conditions in parallel, extract the internal force values of each condition to the OUTPUT file;

[0038] The fourth main control module is used to dynamically back-calculate the longitudinal load and constraints based on the cross-sectional parameters and calculation results obtained in step three, and establish a continuous longitudinal section frame model for finite element calculation;

[0039] The fifth main control module is used to perform multi-objective optimization on the reinforcement scheme by using an intelligent algorithm based on the cross-sectional model and the longitudinal section frame model, generate an optimal reinforcement design scheme, and generate a calculation book.

[0040] Generally speaking, compared with the prior art, the above technical solutions conceived by the present invention mainly have the following technical advantages:

[0041] (1) Eliminate data islands in the design of rail transit box frame structures, realize automatic parameter transfer and seamless integration of multiple systems, realize linked modeling of cross-sections and longitudinal sections, and improve design efficiency.

[0042] (2) Improve the automation degree of multi-condition and multi-section calculations and reduce manual intervention.

[0043] (3) Can optimize the reinforcement scheme and checking specifications, avoid human errors, generate a reinforcement optimization scheme, and reduce the amount of redundant steel bars.

[0044] (4) Enhanced adaptability: covering 4 major design conditions and more than 20 load combinations, and supporting parametric modeling of complex cross-sections. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is a schematic structural diagram of a multi-condition adaptable rail transit box frame structure design system according to an embodiment of the present invention;

[0046] Figure 2 is a schematic diagram of the through reinforcement of the cross-section of the rail transit box frame structure. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0047] In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0048] As Figure 1As shown in the figure, a design method for a multi - working - condition adaptable rail transit box - type frame structure based on an intelligent optimization algorithm provided by an embodiment of the present invention includes the following steps:

[0049] S1. Enter basic general information on the web - based platform, and then import or manually enter the geotechnical physical and mechanical parameters and design standard information in the basic general information.

[0050] In a preferred embodiment of the present invention, the geotechnical physical and mechanical parameters are sourced from the "Table of Geotechnical Physical and Mechanical Parameters". Generally, the geotechnical physical and mechanical parameters at least include formation number, geotechnical name, natural unit weight, coefficient of lateral earth pressure at rest, vertical subgrade reaction coefficient, horizontal subgrade reaction coefficient, modulus of deformation, cohesion, and internal friction angle.

[0051] In a preferred embodiment of the present invention, the design standard information at least includes safety level, fortification intensity, seismic grade, civil air defense grade, crack width, cover thickness, rigid zone, and member force type.

[0052] S2. Establish a cross - section calculation project on the web - based platform, and then automatically extract and analyze or manually enter the cross - section formation and water - level information, frame information, component information, and load information in the cross - section calculation project through CAD import.

[0053] In a preferred embodiment of the present invention, in this step, the cross - section formation and water - level information at least includes the unit weight of the top - plate backfill soil, formation numbers of each layer, thicknesses of each layer, depth of the anti - floating water level, and depth of the normal water level.

[0054] In a preferred embodiment of the present invention, the frame information at least includes the number of floors, number of spans, thickness of overburden soil, height of each floor, width of each span, whether to connect to an annex (yes, annex form, annex location, number of annex floors, number of annex spans, whether to open holes at the interface), whether to consider the retaining structure (yes, whether to set diaphragm walls, whether to set retaining piles, stiffness reduction coefficient of the retaining structure, embedded depth of the retaining structure), whether to set a coping beam, and whether to set uplift piles (yes, number of uplift piles).

[0055] In a preferred embodiment of the present invention, the component information at least includes the cross - section length and width of components (slab, wall, column, beam), column spacing, concrete design strength grade, longitudinal reinforcement grade, and stirrup / tie bar grade.

[0056] In a preferred embodiment of the present invention, the load information at least includes main loads (soil and water pressure load, equipment load, load of the track - top air duct, ceiling load, pipeline load, decoration load, construction load), annex loads, seismic loads (seismic load calculation methods: response displacement method 1, response displacement method 2), civil air defense loads, and other loads (ground surcharge, local surcharge, concentrated force, uniform load, trapezoidal load, and air - side load).

[0057] S3. On the web - based platform, according to the relative relationships among the formation, water level and the main structure, as well as the load magnitude and partial factors, automatically calculate and generate a load condition combination matrix. Then save all the above - entered information to a JSON text.

[0058] In a preferred embodiment of the present invention, in this step, the load condition combinations at least include the following table:

[0059]

[0060]

[0061]

[0062] S4. Pass parameters to the SAP2000 secondary development plug - in through the JSON file, automatically call the software, automatically generate a cross - section model, divide the mesh and apply boundary conditions. At the same time, calculate 5 types of design conditions in parallel, and extract the internal force values of each condition to the OUTPUT file.

[0063] In this step, the boundary conditions at least include soil spring constraints (including normal springs (horizontal soil springs, vertical springs), tangential springs), structural interface contact springs (hard contact springs between the retaining structure and the main structure, hard contact springs between the coping beam and the main structure), and other special boundaries.

[0064] S5. Based on the cross - section parameters and calculation results, dynamically back - calculate the longitudinal load and constraints, and establish a continuous longitudinal section frame model for finite - element calculation.

[0065] Preferably, this step further includes the following steps:

[0066] S51: Based on the cross - section structure parameters, establish a longitudinal section calculation project, select the associated cross - section and column names, input the applicable axis number, side - span position, and elevation difference from the reference plane, and expand it longitudinally into a multi - span continuous frame longitudinal section model.

[0067] S52: Based on the cross - section finite - element calculation conditions and results, dynamically back - calculate the longitudinal load and constraints, conduct longitudinal section finite - element calculation, and extract the internal force values of each condition to the OUTPUT file.

[0068] S6. Import the above - mentioned OUTPUT file on the web - based platform, conduct reinforcement design based on envelope reinforcement, and finally generate a calculation book. Specifically, in this step:

[0069] S61: Import the aforementioned OUTPUT file on the web platform, where the corresponding loads and internal forces of components under various working conditions can be viewed. Perform calculations for the five major modules of the positive section, inclined section, cracks, deflection, and reinforcement ratio of the slab, wall, beam, and column components of the frame structure. Based on the principle of reinforcement envelope, use intelligent algorithms to perform multi-objective optimization on the reinforcement design plan, generate the optimal reinforcement design plan, select the combination with the largest reinforcement among all combinations as the control working condition, and at the same time perform construction checking according to the specifications to back-calculate the rationality of the reinforcement.

[0070] S62: Compare the calculated reinforcement with the actual reinforcement value input by the user. If the calculated required value > the actual input value, it will be marked in red and does not meet the requirements; if the calculated required value < 0.85 * the actual input value, it will be marked in green, and in other cases it will be black. The construction module determines the actual input value of the user according to the relevant requirements of the specifications for construction. If it does not meet the requirements, it will be marked in red; if it meets the requirements, it will still be black. In this way, the economy of the reinforcement is verified.

[0071] In this step, on the basis of the three objectives of minimizing the reinforcement area, minimizing the material consumption, and maximizing the structural safety, further consider the objectives of maximizing the construction convenience and maximizing the durability, etc., to construct a more comprehensive multi-objective optimization model to comprehensively consider more actual engineering factors and make the optimization results more in line with the actual needs. Specifically, construct a multi-objective optimization model for the optimal reinforcement of "minimizing the reinforcement area, minimizing the material consumption, maximizing the structural safety, maximizing the construction convenience, and maximizing the durability":

[0072]

[0073] In the formula, is the weight coefficient of the reinforcement area. x i is the variable of the reinforcement area. is the weight coefficient of the material consumption. g i is the variable of the material consumption. is the weight coefficient of the structural safety. y i is the variable related to the structural safety (such as crack width, deflection, etc.). is the additional weight coefficient of the material consumption. is the additional variable of the material consumption. c j is the weight coefficient of the connection cost. r j is the connection variable. is the loss function related to the uncertainty. is the uncertainty parameter, I c is the construction convenience index, is the weight coefficient of the construction convenience index.

[0074] In the above solution, the definition of the construction convenience index can be considered from the following aspects:

[0075] Convenience of steel bar connection method: Define the convenience index I of the connection method c，con , and conduct a quantitative score according to the convenience degree of the steel bar connection method (such as welding, mechanical connection, binding, etc.). The value range is [0, 1], where 0 indicates very inconvenient and 1 indicates very convenient.

[0076] Complexity of steel bar arrangement: Define the complexity index I of the arrangement c，con , and measure the construction convenience by analyzing the complexity of the steel bar arrangement pattern. The steel bar arrangement pattern can be divided into three levels: complex, moderately complex, and simple, corresponding to the scores 0.2, 0.5, and 0.8 respectively.

[0077] Construction operation space: Define the construction operation space index I c，spa , and measure whether the operation space for construction workers during steel bar construction is sufficient. The sufficiency of the operation space can be evaluated by comparing the actually measured spatial dimensions of the construction area with the requirements of ergonomics and construction equipment operation. The value range is also [0, 1], where 0 indicates that the operation space is extremely narrow and almost impossible to construct; 1 indicates that the operation space fully meets the construction requirements and construction workers can operate freely.

[0078] Uniformity of steel bar size: Define the size uniformity index I c，uni , and consider the number of steel bar specification types. If the steel bar specification sizes are relatively unified, the material management and construction operations during construction are relatively simple and the convenience is high; on the contrary, if the specifications are complex, the construction process needs to be frequently replaced and adjusted, and the convenience is low.

[0079] Improvement of construction efficiency: Define the construction efficiency improvement index I c，eff , which is measured by the ratio of the actual construction time to the standard construction time. The standard construction time can refer to the industry average level or historical data of similar projects. If the actual construction time is lower than the standard time, it means that the reinforcement scheme helps to improve efficiency in terms of construction convenience. The index value is the reciprocal of the ratio of the actual time to the standard time, and the result is normalized to the [0, 1] interval; if the actual construction time exceeds the standard time, the index value is less than 1.

[0080] Taking the above aspects into comprehensive consideration, a comprehensive construction convenience index I can be constructed c,tot , and the sum is calculated by using the weighted ratio method. The weighted values of each item are determined according to actual engineering experience and importance degree.

[0081] Introduce the economic benefit index E b to measure the economic cost of the reinforcement scheme during the whole life cycle, including material cost, construction cost, maintenance cost, etc. Its calculation formula is:

[0082]

[0083] wherein, c m,i is the unit cost of materials, c l,i is the unit cost of construction labor, c c,ij is the connection construction cost, c mt,t is the maintenance cost coefficient, T is the set of maintenance time points, is the maintenance loss function at time point t.

[0084] Based on the above scheme, it is also necessary to determine the optimization constraints, including the reinforcement area constraint, the material consumption constraint, the structural safety constraint, the construction convenience constraint, and the Wasserstein uncertainty set constraint. According to the above multi-objective constraint function and constraints, process the Wasserstein uncertainty set to construct the worst-case risk:

[0085]

[0086] According to the above worst-case risk, use the particle swarm optimization algorithm to calculate the objective function value, and update the velocity and position of the particles according to the fitness and constraints. Until the maximum number of iterations is reached or the convergence condition is satisfied. Select the reinforcement scheme that satisfies all the constraints and has the optimal objective function value from the optimization results as the candidate scheme.

[0087] In the above scheme, the Wasserstein distance provides an effective tool for measuring the difference between the actual probability distribution and the nominal distribution. In the reinforcement optimization, it can quantify the fluctuation range and influence degree of uncertainty factors such as material properties, loads, and geometric parameters into specific numerical ranges, enabling the optimization model to clearly recognize the risks and challenges that these uncertainty factors may bring. In addition, by constructing the Wasserstein uncertainty set, the uncertainty factors are incorporated into the constraints of the optimization model. This makes the optimization process no longer solely based on deterministic parameter assumptions, but considers the possible fluctuations of the parameters, thereby constructing an optimization model with strong robustness to uncertainty, ensuring that the reinforcement scheme can still meet the design requirements and safety standards when facing uncertainty in actual engineering. Furthermore, based on the Wasserstein uncertainty set, the worst-case risk under the influence of uncertainty factors can be found. Through the analysis and evaluation of the worst case, it can provide a more conservative and safe decision-making basis for the design of the reinforcement scheme, avoiding the situation where the structural performance seriously deteriorates or fails due to uncertainty factors.

[0088] Based on the above scheme, the present invention adopts an improved Particle Swarm Optimization (PSO) algorithm, and utilizes its global search ability and relatively fast convergence speed to find the optimal solution of the multi-objective optimization problem. Initialize the algorithm parameters, determine the particle swarm size N (usually selected according to the complexity of the problem, such as between 30 and 100), and the maximum number of iterations Tmax. Initialize the particle positions and velocities: the particle positions correspond to a set of reinforcement design scheme variables (such as steel bar area, material consumption, etc.), and the velocities represent the change amounts of the variables. Randomly initialize the particle positions and velocities according to the value ranges of the design variables. Randomly generate initial reinforcement schemes, and according to the design specifications and actual engineering situations, randomly generate a certain number (such as the same as the particle swarm size) of initial reinforcement schemes, and each scheme corresponds to a set of design variable values (such as the steel bar areas and material consumptions of different components). Check the constraint conditions, check the constraint conditions for each initial reinforcement scheme, and remove the schemes that do not meet the constraint conditions, such as the reinforcement ratio exceeding the allowable range of the specification, the material consumption exceeding the budget, etc. If the number of schemes that do not meet the constraint conditions is too large, the randomly generated range can be appropriately adjusted or regenerated.

[0089] The specific optimization process is as follows:

[0090] 1. Calculate the objective function values. For each particle (reinforcement scheme), calculate its corresponding objective function values, including the reinforcement area value, material consumption value, structural safety index value, and construction convenience index value, and calculate according to the above objective function formulas.

[0091] 2. Update the individual extreme value and the global extreme value. Compare the current objective function value of each particle with its own historical optimal value (individual extreme value), and if it is better, update the individual extreme value. At the same time, find the optimal value among the individual extreme values of all particles as the global extreme value to guide the population search direction.

[0092] 3. Update the particle velocities and positions. According to the velocity and position update formulas of the particle swarm optimization algorithm, update the velocities and positions of each particle. The velocity update formula is: The position update formula is: Among them, is the velocity of the i-th particle at the t-th moment in the d-th dimension, is the position of the i-th particle at the t-th moment in the d-th dimension, is the individual extreme value position of the i-th particle at the t-th moment in the d-th dimension, is the global extreme value position in the d-th dimension at the t-th moment, ω is the inertia weight, c1 and c2 are learning factors, and r1 and r2 are random numbers.

[0093] 4. Judge the convergence condition. If the maximum number of iterations T maxOr if the change in the objective function value is less than the set convergence accuracy (e.g., the change in the objective function value is less than a certain threshold for several consecutive iterations), stop the iteration and output the reinforcement scheme corresponding to the current global extreme value as the candidate optimal solution; otherwise, return to the step "Calculate the objective function value" and continue the iteration.

[0094] Determine the control working condition and construction check: (1) Select the maximum reinforcement combination. For multiple candidate reinforcement schemes obtained by optimization, calculate the reinforcement area of each component in each scheme, and find the combination with the largest required reinforcement area among all schemes as the control working condition. For example, among multiple schemes, compare the bottom reinforcement area of flexural members, the two-way eccentric compression reinforcement area of middle columns, etc. in each scheme, and take the scheme where the maximum value is located as the control working condition. (2) Construction check. According to national or industry structural design codes, conduct construction checks on the reinforcement scheme under the control working condition. It includes but is not limited to the following contents: Longitudinal reinforcement check: Check whether the diameter, spacing, number of longitudinal stressed reinforcement, etc. meet the construction requirements of the code, such as the minimum diameter shall not be less than 12 mm, and the spacing shall not be greater than 300 mm, etc. Stirrup check: Check whether the number of limbs, diameter, and spacing of stirrups comply with the code regulations, such as the stirrup spacing in the tied skeleton shall not be greater than 15d (d is the minimum diameter of longitudinal compression reinforcement), and shall not be greater than 400 mm. Anchorage length check: Ensure that the anchorage length of the reinforcement is not less than the minimum anchorage length l a , such as the anchorage length l of the tensile reinforcement a ≥α·l a,min (α is the anchorage length correction factor, l a，min is the basic anchorage length). Concrete cover thickness check: Check whether the concrete cover thickness of the reinforcement meets the requirements of durability and fire protection, etc. For example, for structural members in environmental class one, the cover thickness of the slab shall not be less than 15 mm. (3) Back-calculate the rationality of the reinforcement. If problems are found in the construction check (such as not meeting the construction requirements), adjust the reinforcement scheme according to the code requirements, and re-enter it into the multi-objective optimization model for back-calculation until a reinforcement design scheme that not only meets the construction requirements but is also relatively optimal in the sense of multi-objective optimization is found.

[0095] S63: Provide two reinforcement methods, namely through reinforcement and non-through reinforcement, for all slab-wall nodes of the frame structure in the reinforcement interface.

[0096] S64: Finally, you can select to export the cross-section and longitudinal section you want to export, and automatically generate the calculation book with one key.

[0097] In an embodiment of the present invention, the through reinforcement at least includes: the top and bottom continuous bars of the slab, the left and right side continuous bars of the wall, and the additional bars at the slab-wall nodes. There are 3 types of input values related to the reinforcement, and there are constraint conditions. Changing one value will synchronously modify the related positions.

[0098] In an embodiment of the present invention, the calculation book at least includes: the load calculation process (with formulas and parameters), the screenshot of the finite element model and the internal force contour map, the reinforcement details list and the checking calculation results.

[0099] According to another aspect of the present invention, there is also provided a multi-condition adaptable rail transit box frame structure design system based on an intelligent optimization algorithm. This system is used to implement the methods of any of the above embodiments or a combination of multiple embodiments, and includes five major modules: 1. Intelligent data fusion module: integrating geological and hydrological data, structural parameters and the specification library to generate structured design inputs; 2. Multi-condition load engine: automatically calculating the water and soil pressure according to the relative position of the stratum-structure, and generating a load combination matrix. 3. Longitudinal and transverse section linkage modeling tool: based on the cross-section parameters and calculation results, deriving the longitudinal section model in a linkage manner. 4. Finite element calculation automation interface: realizing the one-key generation of the model by bridging the web platform and SAP2000 through JSON data; 5. Reinforcement optimization decision-making system: performing multi-objective optimization on the reinforcement scheme based on the intelligent algorithm to meet the specification and economic requirements. More specifically, in the above modules, the longitudinal and transverse section linkage modeling tool further includes:

[0100] The first main control module is used to construct the cross-section calculation project, and automatically extract and analyze or manually input the stratum and water level information, frame information, component information and load information of this section through CAD import in the cross-section calculation project;

[0101] The second main control module is used to calculate and generate a multi-condition load combination matrix according to the relative relationship between the cross-section stratum, water level and the main structure, as well as the load magnitude and partial factor, and save the multi-condition load combination matrix to a JSON text;

[0102] The third main control module is used to call the JSON text by using SAP2000 software to automatically generate a cross-section model, divide the grid and apply boundary conditions, and simultaneously calculate multiple types of design conditions in parallel, and extract the internal force values of each condition to an OUTPUT file;

[0103] The fourth main control module is used to dynamically back-calculate the longitudinal load and constraints based on the cross-section parameters and calculation results obtained by the third main control module, and establish a continuous longitudinal section frame model for finite element calculation.

[0104] Those skilled in the art can easily understand that the above are only the preferred embodiments of the present invention, and are not used to limit the present invention. Any modifications, equivalent replacements and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A design method for a box-shaped frame structure of rail transit with multi-condition adaptability, characterized in that, It includes the following steps: Step 1: Construct a cross-section calculation project, and automatically extract and analyze or manually enter the stratum and water level information, frame information, component information, and load information of the section in the cross-section calculation project through CAD import; Step 2: Calculate and generate a multi-condition load combination matrix according to the relative relationship between the section stratum, water level and the main structure, as well as the load magnitude and partial factor, and save the multi-condition load combination matrix to a JSON text; Step 3: Use a structural analysis software to call the JSON text to automatically generate a cross-section model, divide the grid and apply boundary conditions, and simultaneously calculate multiple types of design conditions in parallel, and extract the internal force values of each condition to an OUTPUT file; Step 4: Based on the cross-section parameters and calculation results obtained in Step 3, dynamically back-calculate the longitudinal load and constraints, and establish a continuous longitudinal section frame model for finite element calculation; Step 5: Based on the cross-section model and the longitudinal section frame model, use an intelligent algorithm to perform multi-objective optimization on the reinforcement scheme, generate an optimal reinforcement design scheme, and generate a calculation book.

2. A design method for a multi-condition adaptable rail transit box frame structure according to claim 1, characterized in that, In Step 1, a cross-section calculation project is constructed based on geotechnical physical and mechanical parameters and design standard information, where the geotechnical physical and mechanical parameters include: stratum number, geotechnical name, natural unit weight, coefficient of earth pressure at rest, vertical subgrade reaction coefficient, horizontal subgrade reaction coefficient, modulus of deformation, cohesion, and internal friction angle; the design standard information includes: safety level, fortification intensity, seismic grade, civil air defense grade, crack width, cover thickness, rigid zone, and component force type.

3. A design method for a multi-condition adaptable rail transit box frame structure according to claim 1, characterized in that, In Step 1, the section stratum and water level information includes the unit weight of the topsoil backfill, the number of each layer of stratum, the thickness of each layer, the depth of the anti-floating water level, and the depth of the normal water level; the frame information includes: number of floors, number of spans, thickness of overburden soil, height of each floor, width of each span, whether it is externally connected to an annex, whether the retaining structure is considered, whether a coping beam is set, and whether anti-pulling piles are set; the component information includes the length of the component cross-section, the width of the component cross-section, column spacing, concrete design strength grade, longitudinal bar grade, and stirrup grade; the load information includes at least the main load, annex load, seismic load, civil air defense load, and other loads; the main load includes the water and soil pressure load, equipment load, load of the track top air duct, ceiling load, pipeline load, decoration load, and construction load, and the other loads include ground overload, local overload, concentrated force, uniform load, trapezoidal load, and overhanging load.

4. A design method for a multi-condition adaptable rail transit box frame structure according to claim 1, characterized in that, In Step 2, the multi-condition load combination matrix includes: short-term design condition, persistent design condition, accidental design condition, and seismic design condition.

5. A design method for a multi-condition adaptable rail transit box frame structure according to claim 1, characterized in that, Step 4 includes the following steps: (41) Based on the cross-section structure parameters, establish a longitudinal section calculation project, and input the applicable axis number, side span position, and height difference from the reference plane in the web platform according to the associated cross-section and associated column name, and expand it longitudinally into a multi-span continuous frame longitudinal section model; (42) Based on the cross-section finite element calculation conditions and results, dynamically back-calculate the longitudinal load and constraints, perform longitudinal section finite element calculation, and extract the internal force values of each condition to an OUTPUT file.

6. A design method for a multi-condition adaptable rail transit box frame structure according to claim 1, characterized in that, Step 5 includes the following steps: (51) According to the OUTPUT file and the principle of reinforcement envelope, a multi-objective optimization of the reinforcement scheme is carried out by using an intelligent algorithm to generate an optimal reinforcement design scheme. Select the combination with the largest reinforcement among all the combinations of the optimal reinforcement design schemes as the control condition. At the same time, conduct a structural check according to the specifications and back-calculate the rationality of the reinforcement. (52) Compare the calculated reinforcement with the actual reinforcement value input by the user. If the calculated required value < actual input value * 0.85, the design requirements are met, generate the optimal reinforcement design scheme and generate a calculation book. Otherwise, return to step (51) for recalculation.

7. A design method for a multi-condition adaptable rail transit box frame structure according to claim 6, characterized in that, In the reinforcement scheme, it includes two reinforcement methods: through reinforcement and non-through reinforcement for all slab-wall nodes in the frame structure.

8. A design method for a multi-condition adaptable rail transit box frame structure according to claim 6, characterized in that The through reinforcement at least includes: the top and bottom longitudinal bars of the slab, the left and right longitudinal bars of the wall, and the additional bars at the slab-wall nodes. There are 3 types of input values of the bars related to each other and there are constraint conditions. Changing one value will synchronously modify the related positions.

9. A design method for a multi-condition adaptable rail transit box frame structure according to claim 1, characterized in that, The calculation book at least includes: the load calculation process, screenshots of the finite element model and the internal force contour map, the reinforcement detail list and the check results.

10. A design system for a box-shaped frame structure of rail transit with multi-condition adaptability, characterized in that, It includes: The first main control module is used to construct a cross-section calculation project, and automatically extract and analyze or manually input the formation and water level information, frame information, component information and load information of this section through CAD import in the cross-section calculation project. The second main control module is used to calculate and generate a multi-condition load combination matrix according to the relative relationship between the cross-section formation, water level and the main structure, as well as the load magnitude and partial coefficient, and save the multi-condition load combination matrix to a JSON text. The third main control module is used to call the JSON text by using a structural analysis software to automatically generate a cross-section model, divide the grid and apply boundary conditions, and at the same time calculate multiple types of design conditions in parallel, and extract the internal force values of each condition to the OUTPUT file. The fourth main control module is used to dynamically back-calculate the longitudinal load and constraints based on the cross-section parameters and calculation results obtained in step three, and establish a continuous longitudinal section frame model for finite element calculation. The fifth main control module is used to carry out multi-objective optimization of the reinforcement scheme by using an intelligent algorithm based on the cross-section model and the longitudinal section frame model, generate an optimal reinforcement design scheme, and generate a calculation book.

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