CN116738537A - Shield hob structure optimization method, system, electronic equipment and storage medium - Google Patents
Shield hob structure optimization method, system, electronic equipment and storage medium Download PDFInfo
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Abstract
The invention discloses a shield hob structure optimization method, a shield hob structure optimization system, electronic equipment and a storage medium, and relates to the field of shield construction. The method comprises the following steps: constructing a rock HJC constitutive model through physical parameters and constitutive parameters of the rock; selecting a sensitive factor of hob structure optimization, and constructing a hob model; performing hob rock breaking numerical simulation based on finite element software LS-DYNA to obtain counter force and crushed rock volume when the hob is cut; constructing a rock breaking specific energy prediction model and a hob abrasion prediction model by adopting an XGBoost algorithm; taking a rock breaking specific energy prediction model and a hob abrasion prediction model as target optimization functions, taking sensitive factors as decision variables, and performing multi-target optimization by using an NSGA II method to obtain an optimal solution; the optimal solution is the optimal hob parameters; and determining an optimal hob structure based on the optimal hob parameters. The method realizes the prediction and multi-objective optimization of the rock breaking efficiency and abrasion of the hob in a low-cost mode, and provides guidance for hob selection and tunneling parameter selection before shield construction.
Description
Technical Field
The invention relates to the technical field of shield construction, in particular to a shield hob structure optimization method, a system, electronic equipment and a storage medium.
Background
The shield method has become a main method for urban tunnel construction due to the advantages of high mechanization degree, high construction efficiency, small environmental disturbance and the like. The disc-type hob is used as a direct rock breaking tool of the shield tunneling machine, and has important influence on the efficiency and safety of shield tunnel construction. The factors such as the cutter width, the penetration, the cutter edge angle and the like of the hob obviously influence the rock breaking efficiency, and simultaneously have great influence on the abrasion of the hob. Most of traditional research methods are based on related preconditions due to the limitation of test amount, and considered factors are limited, so that partial rules are often obtained, and the actual requirements of engineering are difficult to meet. Meanwhile, in the aspect of optimization research, system consideration on hob rock breaking efficiency and hob abrasion is absent. In application, excessive pursuit of rock breaking efficiency may cause the increase of hob abrasion, frequent tool changing adversely affects the construction progress, and the construction cost is increased.
Disclosure of Invention
The invention aims to provide a shield hob structure optimization method, a system, electronic equipment and a storage medium, which are used for solving the problem that the prior art lacks consideration of hob rock breaking efficiency and hob abrasion.
In order to achieve the above object, the present invention provides the following solutions:
a shield hob structure optimization method comprises the following steps:
constructing a rock HJC constitutive model through physical parameters and constitutive parameters of the rock; the physical parameters include: rock density, compressive strength, elastic modulus, poisson's ratio, shear modulus and bulk modulus; the constitutive parameters include: strain rate effect parameters, limit surface parameters, pressure parameters, and damage parameters;
selecting a sensitive factor of hob structure optimization, and constructing a hob model; the sensitive factors comprise a blade fillet, a blade width and a cutter penetration;
importing the hob model and the rock HJC constitutive model into finite element software LS-DYNA, and carrying out hob rock breaking numerical simulation to obtain the counterforce and the crushed rock volume when the hob is cut; the reaction force applied by the hob cutting comprises: rolling force, normal force and lateral force;
based on the sensitive factors, the counterforce applied by the hob during cutting and the crushed rock volume, constructing a rock breaking specific energy prediction model and a hob abrasion prediction model by adopting an XG Boost algorithm;
taking the rock breaking specific energy prediction model and the hob abrasion prediction model as target optimization functions, taking the sensitive factors as decision variables, and performing multi-target optimization by using an NSGA II method to obtain an optimal solution; the optimal solution is an optimal hob parameter;
and determining an optimal hob structure based on the optimal hob parameters.
Optionally, the rock HJC constitutive model includes: intensity model, damage evolution equation and state equation;
the expression of the intensity model is as follows:
wherein sigma * To characterize equivalent stress, p * In order to characterize the pressure, the pressure is,to characterize strain rate, A, B, N and S MAX All are limit surface parameters, C is a strain rate effect parameter, and D is a damage parameter;
the expression of the damage evolution equation is as follows:
wherein, delta epsilon p 、Δμ p Calculating an equivalent plastic strain delta and a plastic volume strain delta for the cell within the cycle;for the equivalent plastic strain and equivalent plastic volume strain at the current calculation step, T * Normalized tensile Strength for Material, D 1 、D 2 Is a material damage parameter; EF (electric F) MIN Is the minimum plastic strain at which the material breaks;
the state equation comprises a state equation of an elastic compression stage, a state equation of a compaction deformation stage and a state equation of a deformation stage after compaction;
the expression of the state equation of the compression stage is as follows:
p＝Kμ；-T(1-D)≤p≤p c ；
the expression of the state equation of the compaction deformation stage is as follows:
p＝p 0 -[(1-F)K+FK 1 ](μ 0 -μ))
the expression of the state equation of the deformation stage after compaction is as follows:
wherein p is the water purifying pressure, K is the bulk modulus, mu is the bulk strain, T is the maximum tensile water purifying pressure of the material, and p c For elastic limit water purifying pressure, p 1 To compact the limiting water purification pressure, mu c For volume strain corresponding to elastic limit, mu p To and compact limit water purifying pressure p 1 Corresponding volume strain, p 0 For the corresponding purified water pressure of the volume deformation before unloading, F is an unloading proportionality coefficient,is the corrected volume strain; k (K) 1 、K 2 、K 3 Is a pressure constant.
Optionally, the expression of the specific energy of rock breaking prediction model is as follows:
the expression of the hob abrasion prediction model is as follows:
y 2 ＝Iμ f F y l
wherein y is 1 To break the rock specific energy, y 2 For hob abrasion, F x 、F y Rolling force, normal force, x 3 I and V are respectively the penetration degree, rolling distance and rock breaking volume of the hob, I is the energy abrasion rate and mu f Is the coefficient of friction.
Optionally, before constructing the rock breaking specific energy prediction model and the hob abrasion prediction model by adopting an XG Boost algorithm based on the sensitivity factor, the counterforce applied by the hob cutting and the crushed rock volume, the method further comprises:
and adopting a noise reduction algorithm to reduce the noise of the counter force applied to the hob during cutting.
The invention also provides a shield hob structure optimization system, which comprises:
the rock HJC constitutive model building module is used for building a rock HJC constitutive model through physical parameters and constitutive parameters of the rock; the physical parameters include: rock density, compressive strength, elastic modulus, poisson's ratio, shear modulus and bulk modulus; the constitutive parameters include: strain rate effect parameters, limit surface parameters, pressure parameters, and damage parameters;
the hob model construction module is used for selecting sensitive factors of hob structure optimization and constructing a hob model; the sensitive factors comprise a blade fillet, a blade width and a cutter penetration;
the hob breaking numerical simulation module is used for guiding the hob model and the rock HJC constitutive model into finite element software LS-DYNA, and carrying out hob breaking numerical simulation to obtain counter force and crushed rock volume when the hob is cut; the reaction force applied by the hob cutting comprises: rolling force, normal force and lateral force;
the prediction model construction module is used for constructing a rock breaking specific energy prediction model and a hob abrasion prediction model by adopting an XG Boost algorithm based on the sensitive factors, the counter force applied by the hob during cutting and the crushed rock volume;
the optimizing module is used for carrying out multi-objective optimization by using the rock breaking specific energy prediction model and the hob abrasion prediction model as objective optimizing functions and the sensitive factors as decision variables and using an NSGA II method to obtain an optimal solution; the optimal solution is an optimal hob parameter;
and determining an optimal hob structure based on the optimal hob parameters.
Optionally, the method further comprises:
and the noise reduction module is used for carrying out noise reduction treatment on counter force applied to the hob during cutting by adopting a noise reduction algorithm.
The invention also provides electronic equipment, which comprises a memory and a processor, wherein the memory is used for storing a computer program, and the processor runs the computer program to enable the electronic equipment to execute the shield hob structure optimization method.
The invention also provides a computer readable storage medium which stores a computer program, and the computer program realizes the shield hob structure optimization method when being executed by a processor.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
according to the invention, the constitutive model is built for on-site rock sampling, and the multi-factor hob rock breaking numerical simulation construction sample set is developed, so that the cost consumption is greatly reduced. And (3) establishing a rock breaking specific energy and hob abrasion prediction model to replace a traditional mathematical mapping relation as an objective function of NSGA II through an XG Boost regression algorithm, and obtaining a Pareto optimal solution of the hob through an NSGA II genetic algorithm. The invention fully considers the effects of various sensitive factors, and realizes the prediction of the rock breaking ratio of the hob and the hob abrasion and the hob size optimization based on the two through the established LS-DYNA numerical simulation sample library and the XG Boost-NSGA II prediction-optimization model.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a shield hob structure optimization method provided by the invention;
FIG. 2 is an overall flow chart of the shield hob structure optimization method provided by the invention
FIG. 3 is a schematic diagram of a hob rock breaking size model and sensitive parameters provided by the invention;
fig. 4 is a finite element mesh model diagram divided by HyperMesh software according to the present invention;
fig. 5 is a graph of the results of the numerical simulation of the hob breaking developed by the LS-DYNA software according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide a method, a system, electronic equipment and a storage medium for optimizing a structure of a shield hob, which are used for realizing the prediction and multi-objective optimization of the hob rock breaking efficiency and abrasion in a low-cost mode and can provide guidance for hob type selection and tunneling parameter selection before shield construction.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
Example 1
The embodiment of the invention provides a shield hob structure optimization method. As shown in fig. 1-2, the method comprises the steps of:
s1: constructing a rock HJC constitutive model through physical parameters and constitutive parameters of the rock; the physical parameters include: rock density ρ, compressive strength f c An elastic modulus E, a Poisson ratio v, a shear modulus G and a bulk modulus K; the constitutive parameters include: strain rate effect parameter C, limit surface parameter A, B, N, pressure parameter K 1 、K 2 、K 3 And a damage parameter EF.
And carrying out a related physical and mechanical test on the sampled rock, obtaining physical and mechanical parameters and constitutive parameters of the rock, and constructing a Holmquist-Johnson-Cook (hereinafter, HJC) constitutive model of the rock. If the rock is more common, the HJC constitutive model data can be consulted in the existing test data. The relevant physical and mechanical tests include wax sealing density test, uniaxial compression test, brazilian split test, triaxial compression test and impact test.
Further, the target rock HJC model is built as follows:
HJC the constitutive model comprehensively considers the effects of compression and strain rate effects and the influence of damage on rock and concrete materials. The model comprises an intensity model, a damage evolution equation and a state equation.
(1) Intensity model: HJC Strength model described by characterization of equivalent stress
In sigma * ＝σ/f c To characterize equivalent stress, p * ＝p/f c In order to characterize the pressure, the pressure is, characterizing strain rate; sigma, f c 、/>Respectively the actual equivalent stress, compressive strength and actual strain rate; p, & gt>The unit of purified water pressure and the reference strain rate; A. b, N and S MAX Collectively referred to as limiting surface parameters, C is a strain rate effect parameter and D is a damage parameter. A step of
(2) Injury evolution equation: HJC model considers that plastic damage is accumulated by plastic strain, which includes equivalent plastic strain and equivalent plastic volume strain
Wherein, delta epsilon p 、Δμ p Calculating an equivalent plastic strain delta and a plastic volume strain delta for the cell within the cycle;for the equivalent plastic strain and equivalent plastic volume strain at the current calculation step, T * ＝T/f c Normalizing the tensile strength of the material, wherein T is the maximum tensile water purification pressure of the material; d (D) 1 、D 2 Is a material damage parameter; EF (electric F) MIN Is the minimum plastic strain at which the material breaks.
(3) The equation of state: the method is used for describing the relation between the water purifying pressure and the volume strain and comprises three stages of elastic compression, compaction deformation and deformation after compaction.
①p＝Kμ；-T(1-D)≤p≤p c
②
p＝p 0 -[(1-F)K+FK 1 ](μ 0 Mu) (unloading)
③
Stage (1) is a linear elastic region, p is the water purification pressure, K is the bulk modulus, μ is the bulk strain, p c For elastic limit water purifying pressure, p l To compact the limiting water purification pressure, p 0 For the corresponding water purification pressure of the volume deformation before unloading, F is the unloading proportionality coefficient, mu c For the volume corresponding to the elastic limitVariable, mu p To and compact limit water purifying pressure p l The corresponding volume strain is used to determine,is the corrected volume strain; k (K) 1 、K 2 、K 3 Is a pressure constant.
The rock HJC model is defined using the key of LS PrePost software MAT JOHNSON HOLMQUIST CONCRETE TITLE. Specifically, RO is density ρ, G is elastic modulus, A, B, N, SFMAX is a limit surface parameter, C is a strain rate effect parameter, FC is uniaxial compressive strength of rock, T is maximum tensile pure water pressure of the material, ESP0 is a reference strain rateEFMIN is the minimum plastic strain EF at material failure MIN PC, UC, PL, UL correspond to p in the state equation c 、p l 、μ c 、μ l 。D 1 、D 2 Is the damage parameter, K of the material 1 、K 2 、K 3 Is a pressure constant.
The rock density is measured by a wax sealing method, the elastic modulus and the uniaxial compressive strength are obtained by a uniaxial compression test, and the maximum tensile pure water pressure is measured by a splitting or tensile test. Carrying out uniaxial compression tests under different strain rates to obtain characteristic equivalent stress (sigma) * ＝σ/f c ) The strain rate hardening index is used to determine the strain rate of the material,developing a triaxial compression test to obtain an M-C intensity envelope according to a molar coulomb criterion>When the damage is not considered, the HJC strength model isLet p=0, < >> And (5) obtaining normalized cohesive strength A by using a simultaneous two-way formula. By-> And obtaining a normalized pressure hardening coefficient B and a strain rate hardening index N. K (K) 1 ，K 2 ，K 3 PC, UC, PL, UL are obtained from the data of the Hugonlot test of Losalamos rock material. And carrying out a cyclic loading test to obtain a sandstone stress-strain relation diagram under cyclic loading, and obtaining damage parameters EFMIN, wherein D1 and D2 can take default values.
S2: selecting a sensitive factor of hob structure optimization, and constructing a hob model; the sensitive factors include blade fillet, blade width and cutter penetration.
Hob optimization sensitive factor x= (x) selected based on hob design concept 1 ,x 2 ,x 3 ) And determining the value range of each sensitive factor according to the feasibility. Wherein x is 1 Is a blade fillet, x 2 Is the width of the blade, x 3 For the tool penetration, parameters with low sensitivity to hob optimization, such as hob radius, remain unchanged.
As shown in FIG. 3, in the embodiment, optimization research is carried out on the CCS disk-shaped hob, the thickness of the hob and the radius of the outer ring of the inner ring are unchanged, and the fillet x of the cutting edge is changed 1 Blade width x 2 Penetration degree x 3 . Specifically, 0.ltoreq.x 1 ≤5；14≤x 2 ≤22；4≤x 3 And is less than or equal to 12. And modeling the hob by using SOLIWORKS, and establishing a total of 25 hob models according to the values of the edge fillets and the edge widths. For penetration, then, it can be directly changed in the k-file of LS-DYNA software.
S3: importing the hob model and the rock HJC constitutive model into finite element software LS-DYNA, and carrying out hob rock breaking numerical simulation to obtain the counterforce and the crushed rock volume when the hob is cut; the reaction force applied by the hob cutting comprises: rolling force, normal force, and lateral force.
And importing the hob and the rock three-dimensional model established by SOLIWORKS into Hypermesh meshing software to carry out meshing. Considering the problems of calculation accuracy and calculation amount, for the mesh local encryption of the contact area of the rock and the hob, the hob is regarded as a rigid body, and the fitting degree of the nodes and the geometric body can be considered without considering the unit quality in mesh division, and the mesh division effect diagram is shown in fig. 4. After grid division, the key words are imported into LS-Prepost software to set other key words, including hob motion control, rock boundary conditions, contact conditions and solving output settings. After finishing the pretreatment work, k files are exported in batches, the penetration degree value is changed, and 125 groups of pretreatment files are obtained. The k file is imported into LS-Run software to perform hob breaking finite element calculation, and the rock breaking condition and equivalent stress after hob cutting are shown in figure 5. Meanwhile, the hob rock breaking force and unit failure data of different models are obtained.
Numerical simulation was performed using LS-DYNA finite element software, and the rock size was set to 600X 250X 120mm taking into account the hob radius and the rock breaking process. The hob is regarded as a rigid body, and in the simulation, the rotational freedom around the central axis and the translational freedom in the forward and downward directions are made, and the other 3 directions of freedom are restrained. The rock is defined by a HJC constitutive model, with all degrees of freedom of the rock floor constrained, and four sides set to no reflective boundary conditions to reduce boundary effects. Monitoring the reaction force F= (F) applied during hob cutting x ,F y ,F z ) Wherein F x Is of rolling force, F y Is normal force F z Is a lateral force. The change of the number of rock model units in the cutting process is monitored, and the volume of the failed units is obtained by counting the number of the failed units and the size of the failed units, which is equivalent to the volume V of crushed rock.
S4: based on the sensitive factors, the counterforce applied by the hob during cutting and the crushed rock volume, an XG Boost algorithm is adopted to construct a rock breaking specific energy prediction model and a hob abrasion prediction model.
Obtaining an initial sample sn= [ x, F, V]N is more than or equal to 0 and less than or equal to N, after N is less than or equal to Z,and (3) carrying out noise reduction treatment on F in the sample data by using a noise reduction algorithm, removing noise generated by the rolling of the hob, the continuity of the unit and other factors, acquiring real rock breaking force data, and taking the data of a stationary segment as noise-reduced data. Constructing a target value sequence from the initial sample data, respectively including the rock breaking ratio y 1 Hob abrasion y 2 。
(1) The rock breaking specific energy follows the following mapping relation:
wherein F is x 、F y Respectively representing the rolling force and the normal force of the hob, x 3 L and V are respectively the penetration degree, rolling distance and rock breaking volume of the hob;
(2) Hob wear follows the following mapping:
y 2 ＝Iμ f F y l
wherein I is the energy wear rate, mu f And l is the rolling distance of the hob, and is the friction coefficient.
Obtaining a new training sample set D= { (x) according to the mapping relation 1 ,y 1 ),(x 2 ,y 2 ),…,(x N ,y N ) }. Wherein x is i ＝(x i (1) ,x i (2) ,x i (3) ) T is a feature vector, y i ＝(y i (1) ,y i (2) ) T is the target vector, i=1, 2, …, N is the sample size.
100 sets of samples were taken as training sets and 25 sets of samples were taken as test sets. And calling XGBRegresor in XG Boost to carry out regression prediction, wherein the sub-regression tree model adopts a gbtree model. In order to prevent overfitting and to increase the running speed, the model parameters are optimized. Finally max_depth is set to 20, gamma is set to 0.1, learning_rate is set to 0.2, and the remaining parameter settings remain default.
The final predictor output is expressed as:
where fj represents a regression tree model, J represents the total number of regression tree models, and F is the regression tree space.
For evaluating the reliability of the prediction model, the discrete degree of the prediction value and the true value and the fitting degree R2 are selected for checking the RMSE, and the fitting degree between the prediction value and the true value is measured and is specifically expressed as follows:
wherein n is the number of samples of the training set; y is i ，And respectively representing the sample true values, the sample predicted values and the average value of all the sample true values of the test set.
S5: taking the rock breaking specific energy prediction model and the hob abrasion prediction model as target optimization functions, taking the sensitive factors as decision variables, and performing multi-target optimization by using an NSGA II method to obtain an optimal solution; the optimal solution is an optimal hob parameter.
Adopting NSGA II genetic algorithm to realize multi-objective optimization, the specific implementation steps of the algorithm are as follows:
(1) determining the scale of an initial population, and obtaining a first generation population through selection, crossing and mutation operations;
(2) combining the parent population and the offspring population, and determining individual non-dominant grades by using the rapid non-dominant ordering;
(3) introducing elite strategy, reserving elite individuals, and generating a new offspring population through genetic algorithm;
(4) repeating the steps until the iteration times reach the maximum, and outputting the Pareto optimal solution.
The nonlinear mapping model constructed by the XG Boost algorithm is used as the fitness function of the multi-objective optimization algorithm and expressed as the minf 1 (x)＝min(XGBoost 1 (x))，minf 2 (x)＝min(XGBoost 2 (x) The constraint is that the sensitivity factor x= (x) 1 ,x 2 ,x 3 ) Is a range of values. And performing multi-objective optimization by using an NSGA II genetic algorithm, wherein the number of targets is 2, the population size is 80, the maximum evolution algebra and the stop algebra are set to be 60, the crossover operator is 0.7, the mutation operator is 0.01, and the number of pareto optimal solutions is 10. Due to the rejection between the multiple objective functions, the multiple objective optimization problem does not result in a unique solution, but is represented by an optimal solution set. For both fitness functions of the input, 10 optimal solutions are obtained, representing the remaining 115 decision variables that govern. In engineering, one of the rock breaking specific energy and the rolling to wear performance can be selected according to actual conditions, so that the optimal rock breaking specific energy and rolling to wear performance can be obtained.
S6: and determining an optimal hob structure based on the optimal hob parameters.
The method provided by the invention uses a numerical simulation method to obviously reduce the time and economic cost of the traditional test method, so that the common influence of various sensitive factors can be considered, and a rich and comprehensive sample library based on numerical simulation can be constructed; the data analysis advantages of the machine learning method are fully developed, the XG Boost regression model is introduced to solve the multi-factor complex nonlinear problem, the rock breaking specific energy and hob abrasion prediction model based on the XG Boost regression algorithm is constructed, and effective prediction of the two is achieved; according to the invention, the complex contradiction relation between the rock breaking ratio and hob abrasion is considered, the NSGA II multi-objective optimization algorithm is introduced, the model constructed by the regression algorithm is used for replacing the traditional mathematical function relation, and the model is introduced into the NSGA II model as an objective function, so that errors generated during conversion of the XGBoost model and the NSGA II model are avoided, and the optimization result is more reliable.
Example two
In order to execute the corresponding method of the above embodiment to achieve the corresponding functions and technical effects, a shield hob structure optimization system is provided below.
The system comprises:
the rock HJC constitutive model building module is used for building the rock HJC constitutive model through physical parameters and constitutive parameters of the rock.
The hob model construction module is used for selecting sensitive factors of hob structure optimization and constructing a hob model. The method comprises the steps of carrying out a first treatment on the surface of the
And the hob breaking numerical simulation module is used for guiding the hob model and the rock HJC constitutive model into finite element software LS-DYNA, and carrying out hob breaking numerical simulation to obtain counter force and crushed rock volume when the hob is cut.
And the prediction model construction module is used for constructing a rock breaking specific energy prediction model and a hob abrasion prediction model by adopting an XG Boost algorithm based on the sensitive factors, the counter force applied by the hob during cutting and the crushed rock volume.
The optimizing module is used for carrying out multi-objective optimization by using the rock breaking specific energy prediction model and the hob abrasion prediction model as objective optimizing functions and the sensitive factors as decision variables and using an NSGA II method to obtain an optimal solution; the optimal solution is an optimal hob parameter.
And determining an optimal hob structure based on the optimal hob parameters.
Further comprises:
and the noise reduction module is used for carrying out noise reduction treatment on counter force applied to the hob during cutting by adopting a noise reduction algorithm.
Example III
An electronic device according to a third embodiment of the present invention includes a memory and a processor, where the memory is configured to store a computer program, and the processor is configured to run the computer program to enable the electronic device to execute the shield hob structure optimization method according to the first embodiment.
In practical applications, the electronic device may be a server.
In practical applications, the electronic device includes: at least one processor (processor), memory (memory), bus, and communication interface (communication interface).
Wherein: the processor, communication interface, and memory communicate with each other via a communication bus.
And the communication interface is used for communicating with other devices.
And a processor, configured to execute a program, and specifically may execute the method described in the foregoing embodiment.
In particular, the program may include program code including computer-operating instructions.
The processor may be a central processing unit, CPU, or specific integrated circuit ASIC (ApplicationSpecificIntegratedCircuit), or one or more integrated circuits configured to implement embodiments of the present invention. The one or more processors included in the electronic device may be the same type of processor, such as one or more CPUs; but may also be different types of processors such as one or more CPUs and one or more ASICs.
And the memory is used for storing programs. The memory may comprise high-speed RAM memory or may further comprise non-volatile memory (non-volatile memory), such as at least one disk memory.
Example IV
Based on the description of the third embodiment, the fourth embodiment of the present invention provides a storage medium having a computer program stored thereon, where the computer program can be executed by a processor to implement the shield hob structure optimization method of the first embodiment.
The shield hob structure optimization system provided by the second embodiment of the invention exists in various forms, including but not limited to:
(1) A mobile communication device: such devices are characterized by mobile communication capabilities and are primarily aimed at providing voice, data communications. Such terminals include: smart phones (e.g., iPhone), multimedia phones, functional phones, and low-end phones, etc.
(2) Ultra mobile personal computer device: such devices are in the category of personal computers, having computing and processing functions, and generally having mobile internet access capabilities. Such terminals include: PDA, MID, and UMPC devices, etc., such as iPad.
(3) Portable entertainment device: such devices may display and play multimedia content. The device comprises: audio, video players (e.g., iPod), palm game consoles, electronic books, and smart toys and portable car navigation devices.
(4) Other electronic devices with data interaction functions.
Thus, particular embodiments of the present subject matter have been described. Other embodiments are within the scope of the following claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may be advantageous.
The system, apparatus, module or unit set forth in the above embodiments may be implemented in particular by a computer chip or entity, or by a product having a certain function. One typical implementation is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being functionally divided into various units, respectively. Of course, the functions of each element may be implemented in the same piece or pieces of software and/or hardware when implementing the present invention. It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, etc., such as Read Only Memory (ROM) or flash memory (flashRAM). Memory is an example of computer-readable media.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by the computing device. Computer readable media, as defined in the present invention, does not include transitory computer readable media (transshipment) such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
The invention may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer.
Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular transactions or implement particular abstract data types. The invention may also be practiced in distributed computing environments where transactions are performed by remote processing devices that are connected through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (8)
1. The shield hob structure optimization method is characterized by comprising the following steps:
constructing a rock HJC constitutive model through physical parameters and constitutive parameters of the rock; the physical parameters include: rock density, compressive strength, elastic modulus, poisson's ratio, shear modulus and bulk modulus; the constitutive parameters include: strain rate effect parameters, limit surface parameters, pressure parameters, and damage parameters;
selecting a sensitive factor of hob structure optimization, and constructing a hob model; the sensitive factors comprise a blade fillet, a blade width and a cutter penetration;
importing the hob model and the rock HJC constitutive model into finite element software LS-DYNA, and carrying out hob rock breaking numerical simulation to obtain the counterforce and the crushed rock volume when the hob is cut; the reaction force applied by the hob cutting comprises: rolling force, normal force and lateral force;
based on the sensitive factors, the counterforce applied by the hob during cutting and the crushed rock volume, constructing a rock breaking specific energy prediction model and a hob abrasion prediction model by adopting an XG Boost algorithm;
taking the rock breaking specific energy prediction model and the hob abrasion prediction model as target optimization functions, taking the sensitive factors as decision variables, and performing multi-target optimization by using an NSGA II method to obtain an optimal solution; the optimal solution is an optimal hob parameter;
and determining an optimal hob structure based on the optimal hob parameters.
2. The shield hob configuration optimization method according to claim 1, characterized in, that the rock HJC constitutive model comprises: intensity model, damage evolution equation and state equation;
the expression of the intensity model is as follows:
wherein sigma * To characterize equivalent stress, p * In order to characterize the pressure, the pressure is,to characterize strain rate, A, B, N and S MAX All are limit surface parameters, C is a strain rate effect parameter, and D is a damage parameter;
the expression of the damage evolution equation is as follows:
wherein, delta epsilon p 、Δμ p Calculating an equivalent plastic strain delta and a plastic volume strain delta for the cell within the cycle;for the equivalent plastic strain and equivalent plastic volume strain at the current calculation step, T * Normalized tensile Strength for Material, D 1 、D 2 Is made of materialA damage parameter; EF (electric F) MIN Is the minimum plastic strain at which the material breaks;
the state equation comprises a state equation of an elastic compression stage, a state equation of a compaction deformation stage and a state equation of a deformation stage after compaction;
the expression of the state equation of the compression stage is as follows:
p＝Kμ；-T(1-D)≤p≤p c ；
the expression of the state equation of the compaction deformation stage is as follows:
p＝p 0 -[(1-F)K+FK 1 ](μ 0 -μ))
the expression of the state equation of the deformation stage after compaction is as follows:
wherein p is the water purifying pressure, K is the bulk modulus, mu is the bulk strain, T is the maximum tensile water purifying pressure of the material, and p c For elastic limit water purifying pressure, p 1 To compact the limiting water purification pressure, mu c For volume strain corresponding to the elastic limit, sigma p To and compact limit water purifying pressure p 1 Corresponding volume strain, p 0 For the corresponding purified water pressure of the volume deformation before unloading, F is an unloading proportionality coefficient,is the corrected volume strain; k (K) 1 、K 2 、K 3 Is a pressure constant.
3. The shield hob structure optimization method according to claim 1, wherein the expression of the rock breaking specific energy prediction model is as follows:
the expression of the hob abrasion prediction model is as follows:
y 2 ＝Iμ f F y l
wherein y is 1 To break the rock specific energy, y 2 For hob abrasion, F x 、F y Rolling force, normal force, x 3 I and V are respectively the penetration degree, rolling distance and rock breaking volume of the hob, I is the energy abrasion rate and mu f Is the coefficient of friction.
4. The shield hob configuration optimization method according to claim 1, characterized in that before constructing a rock breaking specific energy prediction model and a hob abrasion prediction model by using an XG Boost algorithm based on the sensitivity factor, the reaction force applied by the hob during cutting and the crushed rock volume, the method further comprises:
and adopting a noise reduction algorithm to reduce the noise of the counter force applied to the hob during cutting.
5. A shield cutter structure optimization system, comprising:
the rock HJC constitutive model building module is used for building a rock HJC constitutive model through physical parameters and constitutive parameters of the rock; the physical parameters include: rock density, compressive strength, elastic modulus, poisson's ratio, shear modulus and bulk modulus; the constitutive parameters include: strain rate effect parameters, limit surface parameters, pressure parameters, and damage parameters;
the hob model construction module is used for selecting sensitive factors of hob structure optimization and constructing a hob model; the sensitive factors comprise a blade fillet, a blade width and a cutter penetration;
the hob breaking numerical simulation module is used for guiding the hob model and the rock HJC constitutive model into finite element software LS-DYNA, and carrying out hob breaking numerical simulation to obtain counter force and crushed rock volume when the hob is cut; the reaction force applied by the hob cutting comprises: rolling force, normal force and lateral force;
the prediction model construction module is used for constructing a rock breaking specific energy prediction model and a hob abrasion prediction model by adopting an XG Boost algorithm based on the sensitive factors, the counter force applied by the hob during cutting and the crushed rock volume;
the optimizing module is used for carrying out multi-objective optimization by using the rock breaking specific energy prediction model and the hob abrasion prediction model as objective optimizing functions and the sensitive factors as decision variables and using an NSGA II method to obtain an optimal solution; the optimal solution is an optimal hob parameter;
and determining an optimal hob structure based on the optimal hob parameters.
6. The shield tunneling cutter structure optimization system of claim 5, further comprising:
and the noise reduction module is used for carrying out noise reduction treatment on counter force applied to the hob during cutting by adopting a noise reduction algorithm.
7. An electronic device comprising a memory for storing a computer program and a processor that runs the computer program to cause the electronic device to perform the shield hob configuration optimization method according to any one of the claims 1-4.
8. A computer-readable storage medium, characterized in that it stores a computer program which, when executed by a processor, implements the shield hob structure optimization method according to any one of the claims 1-4.
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| CN117852216A (en) * | 2024-03-06 | 2024-04-09 | 山东天工岩土工程设备有限公司 | Method, equipment and medium for configuring shield machine cutter of stratum shield |
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| CN117852216A (en) * | 2024-03-06 | 2024-04-09 | 山东天工岩土工程设备有限公司 | Method, equipment and medium for configuring shield machine cutter of stratum shield |
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