Optimization method and device for foundation pit model data

Abstract

The invention relates to a foundation pit model data optimization method and device, and the method comprises the steps: calculating a standard requirement result and a project amount corresponding to a model data combination of a foundation pit model, and determining a new model data combination through a gradient algorithm under the condition that the standard requirement result and the project amount cannot meet preset requirements, and determining a new standard requirement result and a new project amount, and carrying out iteration until the standard requirement result and the project amount both meet preset requirements or reach preset iteration times, thereby obtaining an optimized model data combination as a foundation for design and arrangement of the foundation pit. Through the scheme of the application, the foundation pit model data can be automatically adjusted and optimized, the efficiency of determining the foundation pit model data is effectively improved, the problem that the data can only be manually modified and repeatedly checked at present is solved, and the building cost is effectively reduced while the preset specification requirements are ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of building software design, and in particular to a method and device for optimizing foundation pit model data. BACKGROUND

[0002] At present, the design and optimization of traditional foundation pits can only be completed by manual work and is highly dependent on the professional experience of engineers. The design and optimization of foundation pits need to be repeatedly manually calculated. In addition, with the development of the real estate market, the development costs such as land price, labor, and building materials are increasing, and how to better save energy and reduce materials has become a focus problem for developers and investors.

[0003] For the design and optimization of foundation pits, the prior art has the following defects:

[0004] 1. The whole process can only be completed by manual work;

[0005] 2. The setting of foundation pit model data is highly dependent on the experience of engineers;

[0006] 3. When the preset specification requirements are not met, the engineers need to repeatedly manually calculate and adjust the foundation pit model data;

[0007] 4. Manual calculation cannot calculate multiple working conditions and multiple drill holes at the same time, and it is also impossible to try all model data combinations, so manual work is difficult to achieve the goal of cost control. SUMMARY

[0008] To solve the problems in the prior art, the present application provides an optimization scheme for foundation pit model data, which can automatically adjust and optimize the foundation pit model data, solve the problem that only manual data modification and repeated calculation are available, and effectively reduce the construction cost while ensuring the preset specification requirements.

[0009] According to a first aspect of the present application, a method for optimizing foundation pit model data is provided, characterized in that it comprises:

[0010] (a) determining the current specification requirement result and the current engineering quantity corresponding to the original foundation pit model according to the original foundation pit model based on the Lizheng deep foundation pit and the Lizheng deep foundation pit software;

[0011] (b) determining the optimization range corresponding to the model data combination of the original foundation pit model;

[0012] (c) determining a gradient algorithm according to the current specification requirement result and the current engineering quantity;

[0013] (d) determining a new model data combination as the current model data combination according to the gradient algorithm and the optimization range;

[0014] (e) calculating, by the Lizheng deep foundation software, a corresponding standard requirement result of the current model data combination as an updated current standard requirement result;

[0015] (f) determining, according to the current model data combination, an engineering quantity corresponding to the foundation pit model as an updated current engineering quantity;

[0016] (g) calculating a cost corresponding to the current engineering quantity; and

[0017] (h) outputting the current model data combination in response to the current standard requirement result satisfying a preset standard requirement and the cost satisfying a preset value range.

[0018] According to a second aspect of the present application, there is provided a device for optimizing foundation pit model data, characterized in that the device comprises:

[0019] a first determining module configured to determine, according to an original foundation pit model based on Lizheng deep foundation and Lizheng deep foundation software, a current standard requirement result and a current engineering quantity corresponding to the original foundation pit model;

[0020] a second determining module configured to determine an optimization range corresponding to a model data combination of the original foundation pit model;

[0021] a third determining module configured to determine, according to the current standard requirement result and the current engineering quantity, a gradient algorithm;

[0022] a fourth determining module configured to determine, according to the gradient algorithm and the optimization range, a new model data combination as a current model data combination;

[0023] a first calculating module configured to calculate, by the Lizheng deep foundation software, a corresponding standard requirement result of the current model data combination as an updated current standard requirement result;

[0024] a fifth determining module configured to determine, according to the current model data combination, an engineering quantity corresponding to the foundation pit model as an updated current engineering quantity;

[0025] a second calculating module configured to calculate a cost corresponding to the current engineering quantity; and

[0026] a first output module configured to output the current model data combination in response to the current standard requirement result satisfying a preset standard requirement and the cost satisfying a preset value range.

[0027] According to a third aspect of the present application, there is provided an electronic device, comprising:

[0028] a processor; and

[0029] a memory storing computer instructions that, when executed by the processor, cause the processor to perform the method of the first aspect.

[0030] According to a fourth aspect of the present application, there is provided a non-transitory computer storage medium storing a computer program that, when executed by a plurality of processors, causes the processors to perform the method of the first aspect.

[0031] According to the method and device for optimizing foundation pit model data provided by the present application, the model data combination of the foundation pit model is calculated to correspond to the specification requirement result and the engineering quantity. In the case that the specification requirement result and the engineering quantity cannot both meet the preset requirements, a new model data combination is determined through a gradient algorithm, and a new specification requirement result and engineering quantity are determined. The iteration is performed until the specification requirement result and the engineering quantity both meet the preset requirements or the preset iteration number is reached, so as to obtain the optimized model data combination as the basis for the design and arrangement of the foundation pit. Through the scheme of the present application, the efficiency of determining the foundation pit model data can be effectively improved, the labor cost is reduced, the building cost is effectively reduced while the preset specification requirements are guaranteed. BRIEF DESCRIPTION OF DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained according to these drawings without exceeding the scope of the present application.

[0033] Figure 1 is a flowchart of the method for optimizing foundation pit model data according to an embodiment of the present application.

[0034] Figure 2 is a flowchart of the method for optimizing foundation pit model data according to another embodiment of the present application.

[0035] Figure 3 is a flowchart of the method for optimizing foundation pit model data according to still another embodiment of the present application.

[0036] Figure 4 is a schematic diagram of the device for optimizing foundation pit model data according to an embodiment of the present application.

[0037] Figure 5 is a schematic diagram of the device for optimizing foundation pit model data according to another embodiment of the present application.

[0038] Figure 6 is a structural diagram of an electronic device provided by the present application. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0040] According to one aspect of the present application, a method for optimizing foundation pit model data is provided. Figure 1 This is a flow chart of a method for optimizing foundation pit model data according to one embodiment of the present application. Figure 1 As shown, the method includes the following steps:

[0041] Step S101 : determining the current specification requirement results and current engineering quantity corresponding to the original foundation pit model based on the Lizheng deep foundation pit and the Lizheng deep foundation pit software.

[0042] In one embodiment, a technician can upload a foundation pit model based on the Lizheng Deep Foundation Pit software to the platform. The data combination in the foundation pit model is the model's own, has not been optimized, and can be called the original foundation pit model. Among them, the data combination of the foundation pit model can include at least one of the embedding depth, pile spacing and pile diameter. The foundation pit model also includes some foundation pit parameters, such as internal force calculation method (such as incremental method), overall stability calculation method (such as Swedish strip method), stability calculation using stress state (such as effective stress method), foundation pit range, depth, slope, etc. Among them, regarding the foundation pit data combination and parameters, reference can be made to the common data and parameters in foundation pit design, and this application does not impose any restrictions on this.

[0043] In one embodiment, the uploaded foundation pit model is read to obtain the model data combination and model parameters of the foundation pit model. The foundation pit model is imported into the Lizheng Deep Foundation Pit software. According to the foundation pit model parameters (for example, determining the internal force calculation method, etc.), the Lizheng Deep Foundation Pit software performs calculations based on the foundation pit model data combination to determine the results required by the specification. In a specific embodiment, the results required by the specification can be output in the form of an RTF (Rich Text Format) file.

[0044] In one embodiment, the current engineering quantity corresponding to the foundation pit model is determined based on the model data combination. In a specific embodiment, the corresponding engineering quantity can be calculated based on the foundation pit model data combination of the embedment depth, pile spacing, and pile diameter. The calculated engineering quantity can be, for example, the weight of concrete and the weight of soil. The engineering quantity can be calculated using any method known in the art, and this application does not impose any limitations thereto.

[0045] In an optional embodiment, step S101 can include:

[0046] receiving a model data combination and model parameters of the original foundation pit model;

[0047] calculating a current specification requirement result corresponding to the model data combination according to the model parameters by using the RJ-Tech deep foundation pit software; and

[0048] determining a current engineering quantity corresponding to the foundation pit model according to the model data combination.

[0049] Step S102, determining an optimization range corresponding to the model data combination of the original foundation pit model.

[0050] Determining the optimization range of the data combination can provide a guide for the subsequent optimization process. In a specific embodiment, for the model parameters, there are corresponding model parameter constraints, such as foundation pit depth, soil layer condition, etc. The optimization range corresponding to the model data combination can be determined according to the constraints of the model parameters. For example, the relationship between the foundation pit depth, the soil layer condition and the embedded depth, according to the foundation pit depth and the soil layer condition, the optimization range of the embedded depth is determined.

[0051] In another specific embodiment, if there are no or cannot obtain the constraints of the model parameters, the optimization range corresponding to the model data combination can be determined according to the engineering specification limit.

[0052] In an optional embodiment, step S102 can include:

[0053] determining the optimization range corresponding to the model data combination according to the constraints of the model parameters; and / or

[0054] determining the optimization range corresponding to the model data combination according to the engineering specification limit.

[0055] Step S103, determining a gradient algorithm according to the current specification requirement result and the current engineering quantity;

[0056] Step S104, determining a new model data combination as the current model data combination according to the gradient algorithm and the optimization range.

[0057] In an embodiment, the gradient algorithm can include a gradient minimum value and a change coefficient. In a specific embodiment, the model data combination can include an embedded depth L, a pile spacing S and a pile diameter d, according to the current engineering quantity, the gradient minimum value corresponding to the model data combination respectively can be determined, for example, the gradient minimum value on the embedded depth, the gradient minimum value of the pile spacing and the gradient minimum value of the pile diameter are respectively as follows:

[0058]

[0059] wherein G1 represents the gradient minimum value of the embedment depth, G2 represents the gradient minimum value of the pile spacing and G3 represents the gradient minimum value of the pile diameter, γ0 is the safety factor, K p is the passive earth pressure coefficient, γ is the unit weight of the soil, c is the cohesion, h a is the active earth pressure action height, E a is the active earth pressure, L0 is the total length, k is the single pile comprehensive cost coefficient, f y is the material flexural strength.

[0060] In the process of optimizing the model data combination, the corresponding change coefficient needs to be determined to determine the new model data combination.

[0061] In one embodiment, the change coefficient can be determined according to the current specification requirement result. The specification requirements usually include overturning resistance checking, overall stability checking, displacement specification, etc., and the change coefficient is determined according to the current value closest to the specification value selected according to the specification result. In one specific embodiment, the current specification requirement result is stored in the current specification requirement result (such as an RTF file).

[0062] In one specific embodiment, the change coefficient y can be a multiple of the change required, and the calculation formula for calculating the change coefficient y can be:

[0063] y = - α * (β min - β)

[0064] wherein α represents the proportional coefficient, for example, when the current value of the overturning resistance checking is closest to the specification value, α = β / β min / E, β min represents the overturning resistance specification value, β represents the current value of the overturning resistance in the current specification requirement result, and E represents the absolute value of the difference between the current overturning resistance value and the overturning resistance value under the optimal step number in the iteration process.

[0065] After y is calculated, the embedment depth L', the pile spacing S' and the pile diameter d' are calculated according to y and the gradient minimum value, respectively:

[0066] L' = L - yG1

[0067] S' = S - yG2

[0068] d' = d - yG3

[0069] Wherein, the optimization range of the embedded depth L is between the maximum value Lmax and the minimum value Lmin, the optimization range of the pile spacing S is between the maximum value Smax and the minimum value Smin, and d usually has several fixed values, for example, the value range can be [600, 800, 1000, 1200, 1400]. Under the optimization range of the above model data combination, if L'>Lmax, L' can take Lmax, if L'<Lmin, L' can take Lmin; if S'>Smax, S' can take Smax, if S'<Smin, S' can take Smin; according to the calculated d', the fixed value is taken from the value range composed of several fixed values.

[0070] It can be understood that when yG1, yG2 and yG3 infinitely approach zero or even equal to zero, the absolute value reaches the minimum value, that is, the minimum value in the local sense is obtained; if the gradient yG1 is greater than zero, it means that the embedded depth (yG1) still has the space to be reduced. If the gradient yG1 is less than zero, it means that the embedded depth needs to be increased to minimize its local construction cost; the gradient yG2 and the gradient yG3 are the same.

[0071] In an optional embodiment, step S103 can include:

[0072] determining the gradient minimum value according to the current engineering quantity; and

[0073] determining the change coefficient according to the previous specification requirement result.

[0074] In an optional embodiment, step S104 can include:

[0075] determining a new model data combination as the current model data combination according to the current model data combination and the corresponding gradient minimum value and change coefficient.

[0076] Step S105, calculating the specification requirement result corresponding to the current model data combination by the deep foundation pit software as the updated current specification requirement result;

[0077] Step S106, determining the engineering quantity corresponding to the foundation pit model according to the current model data combination as the updated current engineering quantity;

[0078] Step S107, calculating the construction cost corresponding to the current engineering quantity; and

[0079] Step S108, in response to the current specification requirement result meeting the preset specification requirement and the construction cost meeting the preset value range, outputting the current model data combination.

[0080] After determining the new model data combination, the new model data combination is input into the Lizheng deep foundation pit software to calculate the standard requirement results corresponding to the new model data combination, and to calculate the engineering quantities corresponding to the new model data combination, which can include the concrete body weight and the soil weight. Then, the corresponding cost can be calculated according to the engineering quantities. It can be understood that all suitable ways can be used to calculate the standard requirement results, the engineering quantities and the cost, and the present application does not limit this.

[0081] In one embodiment, after determining the standard requirement results, it can be determined whether the preset standard requirements are met, for example, whether the safety and stability principle is met, in one embodiment, it can be determined by whether the overturning resistance requirement is met (for example, by the overturning resistance specification value). In one embodiment, after determining the cost, it can be compared with the preset value range (for example, the expected cost range) to see whether the preset value range is met.

[0082] If the standard requirement results meet the preset standard requirements and the cost reaches the preset value range, it is considered that the current determined model data combination meets the requirements, and the model data combination can be output, the foundation pit model (containing the current determined model data combination) can be packaged and the generated report can be provided for the technical personnel to download.

[0083] Figure 2 is a flowchart of the optimization method of the foundation pit model data according to another embodiment of the present application. Compared with Figure 1 , Figure 2 steps S201 to S208 of Figure 1 are the same as steps S101 to S108 of Figure 2 , the difference is that

[0084] Step S209, in response to the current standard requirement results not meeting the preset standard requirements and / or the cost not meeting the preset value range, returning to step S203.

[0085] If the standard requirement results do not meet the preset standard requirements and / or the cost does not reach the preset value range (i.e., not all of the standard requirement results and the cost meet the requirements), it is considered that the current determined model data combination does not meet the requirements, and step S203 is returned to determine the gradient algorithm and the new model data combination again, and to continue to determine whether the standard requirement results and the cost corresponding to the new model data combination meet the requirements.

[0086] Figure 3 is a flowchart of the optimization method of the foundation pit model data according to another embodiment of the present application. Compared with Figure 2 , Figure 3 steps S301 to S309 of Figure 2Steps S201 to S209 are the same as those in the method shown in FIG. 2, except that Figure 3 The method shown further comprises:

[0087] Step S310, determining whether a preset stopping iteration condition is reached; and

[0088] Step S311, in the case where the stopping iteration condition is reached, outputting a model data combination corresponding to a time in the preset number of times that meets the preset specification requirement and has the lowest cost.

[0089] In one embodiment, in order to control time and computing resources and improve efficiency, one or more stopping iteration conditions are usually preset, including: the current gradient is close to zero; the preset gradient adjustment strategy has been tested one by one; it is impossible to further derive a new gradient direction with optimization significance from the existing data; the preset maximum number of iterations is reached, etc. When these preset stopping iteration conditions are reached, whether the current model data combination meets the specification requirement result and the cost requirement is determined, and the stopping iteration is determined, and the model data combination corresponding to a time in the preset number of times that meets the preset specification requirement and has the lowest cost is outputted.

[0090] According to another aspect of the present application, a pit model data optimization device is provided, Figure 4 FIG. 1 is a schematic diagram of a pit model data optimization device according to an embodiment of the present application. As shown in FIG. 1, the pit model data optimization device comprises a data input unit 101, a data processing unit 102, and a data output unit 103. Figure 4As shown, the apparatus comprises a first determining module 401, a second determining module 402, a third determining module 403, a fourth determining module 404, a first calculating module 405, a fifth determining module 406, a second calculating module 407, and a first output module 408. The first determining module 401 is configured to determine a current specification requirement result and a current quantity of work corresponding to an original foundation pit model according to the original foundation pit model and a Lijian deep foundation pit software. The second determining module 402 is configured to determine an optimization range corresponding to a model data combination of the original foundation pit model. The third determining module 403 is configured to determine a gradient algorithm according to the current specification requirement result and the current quantity of work. The fourth determining module 404 is configured to determine a new model data combination as a current model data combination according to the gradient algorithm and the optimization range. The first calculating module 405 is configured to calculate a specification requirement result corresponding to the current model data combination as an updated current specification requirement result by using the Lijian deep foundation pit software. The fifth determining module 406 is configured to determine a quantity of work corresponding to the foundation pit model according to the current model data combination as an updated current quantity of work. The second calculating module 407 is configured to calculate a cost corresponding to the current quantity of work. The first output module 408 is configured to output the current model data combination in response to that the current specification requirement result meets a preset specification requirement and the cost meets a preset value range.

[0091] In an optional embodiment, the first determining module 401 can be configured to:

[0092] receive a model data combination and a model parameter of the original foundation pit model;

[0093] calculate a current specification requirement result corresponding to the model data combination by using a Lijian deep foundation pit software according to the model parameter; and

[0094] determine a current quantity of work corresponding to the foundation pit model according to the model data combination.

[0095] In an optional embodiment, the second determining module 402 can be configured to:

[0096] determine an optimization range corresponding to the model data combination according to a constraint condition of the model parameter; and / or

[0097] determine an optimization range corresponding to the model data combination according to a specification limit.

[0098] In an optional embodiment, the third determining module 403 can be configured to:

[0099] determine the gradient minimum value according to the current quantity of work; and

[0100] The change coefficient is determined according to the previous specification requirement result.

[0101] In an optional embodiment, the fourth determining module 404 can be configured to:

[0102] According to the current model data combination and the corresponding gradient minimum value and change coefficient, a new model data combination is determined as the current model data combination.

[0103] Figure 5 is a schematic diagram of an optimization device for foundation pit model data according to another embodiment of the present application. Compared with Figure 4 , the step modules 501 to 508 of Figure 5 are the same as the modules 401 to 408 of Figure 4 , except that Figure 5 the device shown further comprises:

[0104] The sixth determining module 509 is configured to determine whether a preset stopping iteration condition is reached; and

[0105] The second output module 510 is configured to output a model data combination corresponding to the preset number of times that meet the preset specification requirements and have the lowest cost, in the case where the stopping iteration condition is reached.

[0106] According to the optimization method and device for foundation pit model data provided in the present application, the model data combination of the foundation pit model is calculated to correspond to specification requirement results and engineering quantities. In the case where the specification requirement results and engineering quantities cannot both meet the preset requirements, a new model data combination is determined through a gradient algorithm, and new specification requirement results and engineering quantities are determined, and the iteration is performed until the specification requirement results and engineering quantities both meet the preset requirements or the preset number of iterations is reached, so as to obtain the optimized model data combination as the basis for the design and arrangement of the foundation pit. Through the scheme of the present application, the efficiency of determining the foundation pit model data can be effectively improved, and the labor cost can be reduced, while the preset specification requirements are guaranteed, and the construction cost is effectively reduced.

[0107] In the above embodiments, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0108] It should be noted that, for the foregoing method embodiments, in order to simply describe, they are all described as a series of action combinations, but those skilled in the art should know that the present application is not limited to the order of the actions described, because according to the present application, certain steps can be performed in other order or at the same time. Secondly, those skilled in the art should know that the embodiments described in the specification all belong to optional embodiments, and the actions and modules involved are not necessarily required by the present application.

[0109] In several embodiments provided in the present application, it should be understood that the disclosed apparatus can be implemented in other manners. For example, the division of the apparatus embodiments described above is merely a logical function division, and there can be another division manner in actual implementation. For example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections between different units, or the among different units, can be indirect couplings or communication connections through some interfaces, devices or units, and can be in electrical, mechanical or other forms.

[0110] Referring to Figure 6 , Figure 6 An electronic device is provided, including a processor and a memory. The memory stores computer instructions or one or more programs, when the computer instructions or one or more programs are executed by the processor, the processor executes the computer instructions to implement the method and detailed solutions as shown in Figures 1 to 3 .

[0111] It should be understood that the above-described apparatus embodiments are merely illustrative, and the disclosed apparatus can also be implemented in other manners. For example, the division of the units / modules in the above-described embodiments is merely a logical function division, and there can be another division manner in actual implementation. For example, a plurality of units, modules or components can be combined, or can be integrated into another system, or some features can be ignored or not executed.

[0112] In addition, each functional unit / module in each embodiment of the present application can be integrated into one unit / module, or each unit / module can exist physically, or two or more units / modules can be integrated together. The above-mentioned integrated unit / module can be realized in the form of hardware or in the form of a software program module.

[0113] The integrated units / modules, if implemented in the form of hardware, can be digital circuits, analog circuits, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. Unless otherwise specified, the processor or chip can be any appropriate hardware processor, such as a CPU, a GPU, an FPGA, a DSP, an ASIC, etc. Unless otherwise specified, the on-chip cache, off-chip memory, storage can be any appropriate magnetic storage medium or magneto-optical storage medium, such as resistive random access memory (RRAM), dynamic random access memory (DRAM), static random access memory (SRAM), enhanced dynamic random access memory (EDRAM), high-bandwidth memory (HBM), hybrid memory cube (HMC), etc.

[0114] If the integrated units / modules are implemented in the form of software program modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the present application, essentially or the part that contributes to the prior art, or all or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a number of instructions for making a computer electronic device (which can be a personal computer, a server, or a network electronic device, etc.) execute all or part of the steps of the method described in various embodiments of the present disclosure. The aforementioned storage medium includes: a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and various program code storage media.

[0115] The embodiments of the present application also provide a computer readable storage medium, which stores one or more computer programs, and when the one or more computer programs are executed by a plurality of processors, the processors execute the method and detailed solutions as shown in Figures 1 to 3 .

[0116] The embodiments of the present application also provide a computer program product, which contains a computer program, and when the computer program runs on a computer, the computer executes the method and detailed solutions as shown in Figures 1 to 3 .

[0117] Reference within this specification to features, advantages, or similar language does not imply that all of the features and advantages that can be realized from the present solution should be or are contained in, or must be realized in, any single

[0118] Furthermore, the described features, advantages, and characteristics of the present solution can be combined in any suitable manner in one or more embodiments. One skilled in the relevant art will recognize, in light of the description herein, that the present solution can be practiced without one or more of the specific features or advantages of a particular embodiment. In other instances, additional features and advantages can be recognized in light of the

[0119] The above has been made to the embodiments of the present application in detail, the principle and implementation mode of the present application are described in this paper by applying specific examples, the above embodiment explanation is only for helping to understand the method of the present application and its core idea. At the same time, the person skilled in the art can make changes or deformation according to the idea of the present application, based on the specific implementation mode and application range of the present application, which belongs to the protection scope of the present application. In summary, the content of the specification should not be understood as the limitation of the present application.

Claims

1. A method for optimizing foundation pit model data, characterized in that: include: (a) determining the current specification requirements and current engineering quantities corresponding to the original foundation pit model based on the Lizheng deep foundation pit and the Lizheng deep foundation pit software; (b) determining an optimization range corresponding to the model data combination of the original foundation pit model; (c) determining a gradient algorithm based on the current specification requirements and the current engineering quantity; (d) determining a new model data combination according to the gradient algorithm and the optimization range as the current model data combination; (e) calculating the specification requirement result corresponding to the current model data combination using the Lizheng deep foundation pit software as the updated current specification requirement result; (f) determining the engineering quantity corresponding to the foundation pit model according to the current model data combination as the updated current engineering quantity; (g) calculating the construction cost corresponding to the current engineering quantity; as well as (h) In response to the current specification requirement result satisfying the preset specification requirement and the construction cost satisfying the preset value range, outputting the current model data combination.

2. The method according to claim 1, wherein Also includes: In response to the current specification requirement result not meeting the preset specification requirement and / or the construction cost not meeting the preset value range, return to step (c).

3. The method according to claim 2, wherein Also includes: Statistically determine the number of times the gradient algorithm is used; as well as When the number of times reaches a preset number of times, the model data combination corresponding to the one of the preset times that meets the preset specification requirements and has the lowest cost is output.

4. The method according to any one of claims 1 to 3, wherein The step (a) comprises: receiving the model data combination and model parameters of the original foundation pit model; According to the model parameters, the current specification requirements corresponding to the model data combination are calculated by using the Lizheng Deep Foundation Pit software; and The current engineering quantity corresponding to the foundation pit model is determined based on the model data combination.

5. The method according to claim 4, wherein The original foundation pit model also includes constraints on the model parameters, and step (b) includes: Determining the optimization range corresponding to the model data combination according to the constraints of the model parameters; and / or The optimization range corresponding to the model data combination is determined according to the engineering specification limit.

6. The method according to any one of claims 1 to 3, wherein: The gradient algorithm includes a gradient minimum and a coefficient of variation, and step (c) includes: Determining the minimum gradient value according to the current engineering quantity; and The coefficient of variation is determined based on the previous specification requirement results.

7. The method according to claim 6, wherein The step (d) comprises: According to the current model data combination and the corresponding minimum gradient value and the variation coefficient, a new model data combination is determined as the current model data combination.

8. The method according to any one of claims 1 to 3, wherein: The model data combination includes at least one of an embedding depth, a pile spacing, and a pile diameter.

9. A device for optimizing foundation pit model data, characterized in that: include: The first determination module is used to determine the current specification requirement results and current engineering quantities corresponding to the original foundation pit model based on the Lizheng deep foundation pit and the Lizheng deep foundation pit software; A second determining module is used to determine the optimization range corresponding to the model data combination of the original foundation pit model; A third determination module is used to determine a gradient algorithm according to the current specification requirement result and the current engineering quantity; a fourth determining module, configured to determine a new model data combination as a current model data combination according to the gradient algorithm and the optimization range; A first calculation module is used to calculate the specification requirement result corresponding to the current model data combination using the Lizheng deep foundation pit software as the updated current specification requirement result; a fifth determining module, configured to determine the engineering quantity corresponding to the foundation pit model according to the current model data combination as the updated current engineering quantity; A second calculation module is used to calculate the construction cost corresponding to the current engineering quantity; as well as The first output module is configured to output the current model data combination in response to the current specification requirement result satisfying the preset specification requirement and the construction cost satisfying the preset value range.

10. An electronic device comprising a memory storing one or more programs and one or more processors, the one or more processors being electrically coupled to the memory and configured to execute the one or more programs to perform the method according to any one of claims 1 to 8. 11 . A non-transitory computer-readable storage medium storing one or more programs configured to, when executed by a processor, cause the method of claim 1 to be performed.

Images