CN113761680B - Parameter design method for composite material vertical pipe winding process - Google Patents

Parameter design method for composite material vertical pipe winding process Download PDF

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CN113761680B
CN113761680B CN202111019751.4A CN202111019751A CN113761680B CN 113761680 B CN113761680 B CN 113761680B CN 202111019751 A CN202111019751 A CN 202111019751A CN 113761680 B CN113761680 B CN 113761680B
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composite material
vertical pipe
winding
stress
material vertical
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CN113761680A (en
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康超
叶双
刘赞
周宏根
刘金锋
陈宇
李炳强
谢阳
陈冶
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Jiangsu University of Science and Technology
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Abstract

The application discloses a parameter design method of a composite material vertical pipe winding process, which comprises the following steps: preparing a composite material winding vertical pipe through the set composite material vertical pipe winding process parameters; residual stress detection is carried out on the composite material vertical pipe, and large sample data is constructed by utilizing a virtual sample generation technology; constructing a residual stress model based on the large sample data; constructing a composite material vertical pipe total stress model according to the constructed residual stress model and the composite material vertical pipe stress model based on the laminated plate theory; and obtaining the technological parameters meeting the performance requirements of the composite material in a winding technological parameter domain by utilizing an optimizing algorithm according to the total stress model of the composite material vertical pipe. The application improves the uniformity of structural stress when the composite material vertical pipe is pressed, improves the strength of the first layer of the composite material vertical pipe, solves the problem that the first layer of the composite material vertical pipe is easy to fail at first, improves the quality of the composite material vertical pipe, and ensures the continuous use effect of the composite material vertical pipe.

Description

Parameter design method for composite material vertical pipe winding process
Technical Field
The application belongs to the field of composite material vertical pipe manufacturing, and particularly relates to a parameter design method of a composite material vertical pipe winding process.
Background
The composite material vertical pipe is a key component for ocean oil gas development, and has important significance for realizing ocean national strategic targets in China. With the increase of the sea exploration depth, the requirements on the mechanical properties of the pipe are higher, and how to manufacture products with stronger and more stable properties is a problem to be solved in deep sea exploration. At present, a means for manufacturing a composite material vertical pipe mainly takes a fiber winding forming technology as a main principle, how to manufacture the composite material vertical pipe with better structural performance according to the forming technology still faces a plurality of problems, particularly the composite material vertical pipe still faces the difficulties of early failure and the like under the action of internal pressure of the composite material vertical pipe, and the main reason is that after the traditional composite material vertical pipe is pressed, the traditional technological parameter setting causes that the inner surface stress of the composite material vertical pipe is large, the outer surface stress is small, the stress is in an uneven state, and the stress peak value cannot be effectively reduced, so that a stress larger layer is easy to fail at first.
At present, the existing literature focuses on optimizing winding angles, fiber volume content, layering thickness and the like to design a composite material structure, so that the composite material structure has better performance under the action of external load, such as patents 106126773B, 109543335B and the like; or process design of the process parameters of the winding, such as 111199125A,111931302A, etc. While these patents have designed the winding structure in terms of structural and process parameters, less consideration is given to the influence of residual stress on the structure, less design of the stress of the composite riser under the action of residual stress on the load is more involved, and comprehensive consideration of the working condition and the process of the composite structure is lacking.
Disclosure of Invention
The application aims to: in order to overcome the defects in the prior art, a parameter design method of a composite material vertical pipe winding process is provided, the winding process design method under the influence of the load working condition and the forming residual stress of the composite material vertical pipe is combined, the uniformity of structural stress of the composite material vertical pipe when the composite material vertical pipe is pressed is improved, the stress peak value is reduced, and the strength of a first layer is improved.
The technical scheme is as follows: in order to achieve the above purpose, the application provides a parameter design method of a composite material riser winding process, comprising the following steps:
s1: preparing a composite material winding vertical pipe through preliminarily set composite material vertical pipe winding process parameters;
s2: cutting a composite material vertical pipe, detecting residual stress of the composite material vertical pipe by adopting an experimental method, and constructing large sample data by utilizing a virtual sample generation technology;
s3: constructing a residual stress model based on the large sample data;
s4: constructing a composite material vertical pipe total stress model according to the constructed residual stress model and the composite material vertical pipe stress model based on the laminated plate theory;
s5: and obtaining the technological parameters meeting the performance requirements of the composite material in a winding technological parameter domain by utilizing an optimizing algorithm according to the total stress model of the composite material vertical pipe.
Further, in the step S1, the composite material winding riser includes a metal liner and a composite material winding layer, the metal liner is made of an aluminum alloy material, and the preparation method of the composite material winding riser includes:
a1: firstly, carrying out mechanical processing treatment on a metal lining, carrying out sand blasting treatment on the surface of the metal lining, washing with water to remove impurities, and completely drying; secondly, carrying out secondary acid washing treatment on the surface of the dried metal lining, washing with water and drying; finally, coating a thermosetting binder on the surface of the metal lining;
a2: and (3) using a composite material winding machine, applying winding tension F and winding temperature T to the prefabricated prepreg tows in a winding mode by adopting a dry method/wet method, adopting spiral winding to enable the composite material vertical pipe to have an orthogonal symmetrical structure mode, forming a composite material winding layer after winding is completed, curing the composite material vertical pipe through a curing furnace or an autoclave, and completely curing the composite material vertical pipe for a specific curing time T to obtain the composite material winding vertical pipe.
Further, in the step A2, the composite material winding layer adopts thermosetting epoxy resin, and the fiber is unidirectional carbon fiber.
Further, the method for detecting the residual stress in the step S2 includes:
for the completely solidified composite material vertical pipe, an ultrasonic stress meter is adopted to detect the stress in the composite material winding layer, so as to obtain circumferential stress distribution data points of the composite material, and as the general residual stress of the winding product presents a tension-compression state at two sides of a neutral plane, a distribution curve presents a continuous linear or secondary change form, the following polynomial is adopted to fit the stress distribution:
σ＝a+bx+cx 2 (1)
wherein x is the distance between the corresponding winding layer and the outer surface of the inner liner; a. b and c are coefficients to be determined;
and obtaining undetermined coefficients a, b and c through data fitting, namely determining a hoop stress distribution function under corresponding winding process parameters (F, T and T).
Further, in step S2, in order to reduce the experiment cost, based on the small sample experiment, a virtual sample generation technology is adopted to realize large sample generation, and the specific method is as follows:
b1: taking experimental variables of winding tension F, winding temperature T and curing time T as inputs, and taking undetermined coefficients a, b and c of fitting residual stress as outputs; based on the small samples obtained by the experiment, the sample domain of 6 sets of variables is estimated, and the sample distribution is obtained as MF,
wherein ,
IQR＝Q 3 -Q 1
wherein ,Q3 And Q is equal to 1 For the range of input variables, min and max are minimum and maximum observed values, and Me is a central position;
b2: the trend similarity is calculated by the following method:
selecting two parameters Xp and Xq for calculation, wherein Xp is an input variable, xq is any parameter, and a trend evaluation function g (i) p of an ith observation value between Xp and Xq is:
the similarity between Xp and Xq is calculated as the average of all available observations:
b3: predicting a section to generate a suitable virtual value based on the values g (i) p, q obtained in step B2:
firstly, v is randomly selected xp Then generates v Xq From U (L) Xp ,U Xp ) A temporary value (tv),and calculate MF X p (tv), then a random seed (rs) is selected from U (0, 1) to evaluate whether tv can be kept as the appropriate virtual value v xp The method comprises the steps of carrying out a first treatment on the surface of the Second, the cumulative probability of the cumulative distribution function value F (rs) of rs is calculated, when rs is smaller than MF Xp (tv) tv will be able to remain v Xp Otherwise, tv will be discarded, specifically:
producible prediction intervalThe method comprises the following steps:
wherein the variable is biased to
θ p,q ＝-0.8×|S p,q |+0.9
B4: bringing the obtained interval critical value into the following formula (8) to obtain v Xp Corresponding virtual sample v Xq ，
Further, the construction method of the residual stress model in the step S3 is as follows: based on the virtual sample and sample data obtained by experiments, constructing a black box model of winding tension F, winding temperature T, curing time T and output variables a, b and c by adopting a deep neural network algorithm; the normalization processing is adopted for the acquired large sample data, so that errors caused by parameter magnitude differences are reduced; then training the sample by adopting a deep neural network algorithm, and obtaining a winding tool after the training is qualifiedThe coefficient between the technological parameter and the residual stress polynomial coefficient is further adopted to obtain a stress distribution function sigma by adopting a hoop stress formula (1) 1 (F,T,t,x)。
Further, in the step S4, the composite material riser stress model based on the laminate theory performs deformation analysis on the composite material riser, and the construction method of the composite material riser stress model is as follows:
firstly, based on the classical laminated plate theory of the composite material, the displacement general solution form of the composite material vertical pipe under an off-axis coordinate system (a cylindrical coordinate system) is obtained,
wherein ,ur For radial displacement, k denotes the number of layers, r denotes the radial position, ε 0 Gamma, a constant corresponding to axial strain 0 Representing torsion per unit length, A (k) And B is connected with (k) Unknown coefficients are to be determined;
secondly, according to the conversion relation between the positive axis and the off-axis of the composite unidirectional material:
wherein ,[Tσ ] (k) And [ T ] ε ] (k) Represents a stiffness conversion matrix, [ C ]] (k) Is the positive axis stiffness;
boundary conditions:
internal and external surface stress conditions:
wherein ,P0 The pressure acting on the inner surface, σ represents the stress, r represents the radial direction, r 0 Represents the inner surface of the first layer, r N Represents the outer surface of the nth layer;
the displacement and stress continuous conditions of each layer in the inner part are as follows:
force and moment balance conditions:
wherein F represents an axial force and M represents a bending moment.
Further, the method for constructing the composite material riser total stress model in the step S4 comprises the following steps:
solving an equation set consisting of all equations in the composite material vertical pipe stress model through numerical calculation software such as Matlab, so as to obtain coefficients A, B and the like of each layer corresponding to a displacement formula, and then obtaining the circumferential stress distribution sigma of each layer of the composite material vertical pipe in the main stress direction according to the displacement stress relation 2 (x)；
The composite riser total stress model is expressed as:
σ＝σ 1 (F,T,t,x)+σ 2 (x) (14)
where σ is the composite riser hoop stress under consideration of the residual stress.
Further, the method for obtaining the technological parameters meeting the performance requirement of the composite material in the step S5 includes:
c1: setting initial values of an optimizing algorithm, wherein the initial values comprise particle swarm evolution times, particle initial updating speed, learning factors and population scale;
c2: the obtained fluctuation value of the circumferential residual stress along the depth direction is taken as a moderate function, and a specific fluctuation value calculation formula is as follows:
and C3: and (3) performing crossing and mutation treatment through an optimizing algorithm, continuously circulating, and finally obtaining winding tension, winding temperature and curing time when the fluctuation value is the minimum value.
The beneficial effects are that: compared with the prior art, the application combines the residual stress with the action load working condition of the composite material vertical pipe, realizes the effective design and optimization of winding process parameters, and has the following advantages:
1. according to the application, the virtual sample generation technology is adopted to realize large sample generation, so that large sample data is provided for the establishment of the residual stress distribution model based on the deep neural network algorithm, and the production cost of experimental modeling is greatly reduced while the model is ensured to be high in precision.
2. By the winding process design, the problem of winding process parameter design under special working conditions is solved, the uniformity of structural stress of the composite material vertical pipe when the composite material vertical pipe is pressed is improved, the hoop stress of the composite material vertical pipe is effectively reduced, the maximum peak value of stress in the thickness direction when the vertical pipe is pressed is effectively reduced, the strength of the first layer of the composite material vertical pipe is improved, the problem that the first layer of the composite material vertical pipe is easy to fail at first is solved, the quality of the composite material vertical pipe is improved, and the continuous use effect of the composite material vertical pipe is ensured.
Drawings
FIG. 1 is a flow chart of a composite riser winding process parameter design of the present application;
FIG. 2 is a block diagram of a composite riser of the present application.
Detailed Description
The present application is further illustrated in the accompanying drawings and detailed description which are to be understood as being merely illustrative of the application and not limiting of its scope, and various modifications of the application, which are equivalent to those skilled in the art upon reading the application, will fall within the scope of the application as defined in the appended claims.
As shown in FIG. 1, the application provides a composite material winding vertical pipe, which comprises a metal lining structure and a composite material winding layer, wherein the thickness t1 of the metal lining structure is 1-4mm, the thickness t2 of the winding layer is 2-6mm, the total winding layer number is controlled between 8-30 layers, and the composite material winding vertical pipe can be selected according to requirements.
In the embodiment, a process mode of orthogonal winding is adopted, a composite material winding layer is wound on a metal lining structure, so that a composite material winding vertical pipe is prepared, an aluminum alloy 6061 material is adopted as a metal lining, a thermosetting epoxy resin Y69 is adopted as the composite material winding layer, and unidirectional T700 carbon fibers are adopted as fibers.
Before formally mass producing the composite material winding riser, parameters of the winding process need to be designed, in this embodiment, a method for designing parameters of the winding process of the composite material riser is provided, and referring to fig. 2, the method specifically includes the following steps:
s1: preparing a composite material winding vertical pipe through preliminarily set composite material vertical pipe winding process parameters;
a1: firstly, carrying out mechanical processing treatment on a metal lining cylinder, carrying out sand blasting treatment on the surface of the metal lining, washing with water to remove impurities, and completely drying; secondly, carrying out secondary acid washing treatment on the surface of the dried metal lining, washing with water and drying; finally, coating a thermosetting adhesive AF555 on the surface of the metal lining;
a2: and (3) using a composite material winding machine, applying winding tension F and winding temperature T to the prefabricated prepreg tows in a winding mode by adopting a dry method/wet method, adopting spiral winding to enable the composite material vertical pipe to have an orthogonal symmetrical structure mode, forming a composite material winding layer after winding is completed, curing the composite material vertical pipe through a curing furnace, and enabling the composite material vertical pipe to be completely cured after a specific curing time T at the second step curing temperature of 178 ℃.
S2: cutting a composite material vertical pipe, detecting residual stress of the composite material vertical pipe by adopting an experimental method, and constructing large sample data by utilizing a virtual sample generation technology:
for the completely solidified composite material vertical pipe, an ultrasonic stress meter is adopted to detect the stress in the composite material winding layer, so as to obtain circumferential stress distribution data points of the composite material, and as the general residual stress of the winding product presents a tension-compression state at two sides of a neutral plane, a distribution curve presents a continuous linear or secondary change form, the following polynomial is adopted to fit the stress distribution:
σ＝a+bx+cx 2 (1)
wherein x is the distance between the corresponding winding layer and the outer surface of the inner liner; a. b and c are coefficients to be determined;
the basic data of the experimental sample in the embodiment adopts three-factor three-level orthogonal experiments, nine groups of experiments are adopted, the length of the winding vertical pipe is selected to be 600mm, the outer diameter of the lining is 50mm, the wall thickness is 2mm, and the winding tension is 5N,15N and 25N; winding temperature is 40 ℃,65 ℃ and 90 ℃; the curing time was 1 hour, 1.5 hours, and 2 hours, the winding angle was [.+ -. 15/.+ -. 30/.+ -. 55/.+ -. 30/.+ -. 15].
And obtaining undetermined coefficients a, b and c through data fitting, namely determining a hoop stress distribution function under corresponding winding process parameters (F, T and T).
In order to reduce the experiment cost, based on a small sample experiment, a virtual sample generation technology is adopted to realize large sample generation, and the specific method is as follows:
b1: taking experimental variables of winding tension F, winding temperature T and curing time T as inputs, and taking undetermined coefficients a, b and c of fitting residual stress as outputs; based on the small samples obtained by the experiment, the sample domain of 6 sets of variables is estimated, and the sample distribution is obtained as MF,
wherein ,
IQR＝Q 3 -Q 1
wherein ,Q3 And Q is equal to 1 For the range of input variables, min and max are minimum and maximum observed values, and Me is a central position;
b2: the trend similarity is calculated by the following method:
selecting two parameters Xp and Xq for calculation, wherein Xp is an input variable, xq is any parameter, and a trend evaluation function g (i) p of an ith observation value between Xp and Xq is:
the similarity between Xp and Xq is calculated as the average of all available observations:
b3: predicting a section to generate a suitable virtual value based on the values g (i) p, q obtained in step B2:
firstly, v is randomly selected xp Then generates v Xq From U (L) Xp ,U Xp ) A temporary value (tv) is randomly selected and an MF is calculated X p (tv), then a random seed (rs) is selected from U (0, 1) to evaluate whether tv can be kept as the appropriate virtual value v xp The method comprises the steps of carrying out a first treatment on the surface of the Second, the cumulative probability of the cumulative distribution function value F (rs) of rs is calculated, when rs is smaller than MF Xp (tv) tv will be able to remain v Xp Otherwise, tv will be discarded, specifically:
producible prediction intervalThe method comprises the following steps:
wherein the variable is biased to
θ p,q ＝-0.8×|S p,q |+0.9
B4: bringing the obtained interval critical value into the following formula (8) to obtain v Xp Corresponding virtual sample v Xq ，
S3: based on the large sample data, constructing a residual stress model:
based on the virtual sample and sample data obtained by experiments, constructing a black box model of winding tension F, winding temperature T, curing time T and output variables a, b and c by adopting a deep neural network algorithm; the normalization processing is adopted for the acquired large sample data, so that errors caused by parameter magnitude differences are reduced; then training the sample by deep neural network algorithm, in this embodiment, connecting implicit layer weight W of input layer 1 Updating matrix for 10 x 3, implicit layer weight matrix W connected to output layer 5 Updating the matrix for 3 x 10 and the intermediate hidden layers total 5-layer form; after the training is qualified, obtaining coefficients between winding process parameters and residual stress polynomial coefficients, and further obtaining a stress distribution function sigma by adopting a hoop stress formula (1) 1 (F,T,t,x)。
S4: constructing a composite material vertical pipe total stress model according to the constructed residual stress model and the composite material vertical pipe stress model based on the laminated plate theory:
firstly, based on the classical laminated plate theory of the composite material, the displacement general solution form of the composite material vertical pipe under an off-axis coordinate system (a cylindrical coordinate system) is obtained,
wherein ,ur For radial displacement, k denotes the number of layers, r denotes the radial position, ε 0 Gamma, a constant corresponding to axial strain 0 Representing torsion per unit length, A (k) And B is connected with (k) Unknown coefficients are to be determined;
secondly, according to the conversion relation between the positive axis and the off-axis of the composite unidirectional material:
wherein ,[Tσ ] (k) And [ T ] ε ] (k) Represents a stiffness conversion matrix, [ C ]] (k) Is the positive axis stiffness;
boundary conditions:
internal and external surface stress conditions:
wherein ,P0 The pressure acting on the inner surface, σ represents the stress, r represents the radial direction, r 0 Represents the inner surface of the first layer, r N Represents the outer surface of the nth layer;
the displacement and stress continuous conditions of each layer in the inner part are as follows:
force and moment balance conditions:
wherein F represents an axial force and M represents a bending moment.
Solving an equation set consisting of all equations in the composite material riser stress model through Matlab and other numerical calculation software to obtain coefficients A, B and the like of each layer corresponding to a displacement formula, and then obtaining the circumferential stress distribution sigma of each layer of the composite material riser in the main stress direction according to the displacement stress relation 2 (x)；
The composite riser total stress model is expressed as:
σ＝σ 1 (F,T,t,x)+σ 2 (x) (14)
where σ is the composite riser hoop stress under consideration of the residual stress.
S5: according to the total stress model of the composite material vertical pipe, acquiring process parameters meeting the performance requirements of the composite material in a winding process parameter domain by utilizing an optimizing algorithm:
c1: by adopting a particle swarm genetic algorithm, initial values of the algorithm are set, wherein the initial values comprise the particle swarm evolution times maxgen=300, the initial update speed Vmax=1, the Vmin= -1, the learning factor c1=c2=1.6 and the population size sizepop=100
C2: the obtained fluctuation value of the circumferential residual stress along the depth direction is taken as a moderate function, and a specific fluctuation value calculation formula is as follows:
and C3: and (3) performing crossing and mutation treatment through a particle swarm genetic algorithm, and continuously circulating to finally obtain the winding tension, the winding temperature and the curing time when the fluctuation value is the minimum value.
In the embodiment, a particle swarm genetic algorithm main program is written in matlab, and a composite material riser stress fluctuation function is called by a moderate function fitness; meanwhile, respectively calling a stress model established by the laminated plate theory and a residual stress distribution sub-function fitted by a quadratic function in the stress fluctuation function; and calling a black box model established by a deep neural network method by the residual stress distribution function model to obtain residual stress corresponding to the winding process parameters after the main program rand of the particle swarm genetic algorithm. Through continuous circulation and updating iteration of the algorithm, the winding process parameter meeting the minimum moderate function is finally obtained, the winding process parameter specifically designed is winding tension 12N, the winding temperature is 82.5 ℃, and the curing time is 1.5 hours.

Claims (3)

1. The parameter design method of the composite material vertical pipe winding process is characterized by comprising the following steps of:
s1: preparing a composite material winding vertical pipe through preliminarily set composite material vertical pipe winding process parameters;
s2: residual stress detection is carried out on the composite material vertical pipe, and large sample data is constructed by utilizing a virtual sample generation technology;
s3: constructing a residual stress model based on the large sample data;
s4: constructing a composite material vertical pipe total stress model according to the constructed residual stress model and the composite material vertical pipe stress model based on the laminated plate theory;
s5: according to the total stress model of the composite material vertical pipe, acquiring process parameters meeting the performance requirements of the composite material in a winding process parameter domain by utilizing an optimizing algorithm;
the method for detecting the residual stress in the step S2 comprises the following steps:
for the completely solidified composite material vertical pipe, detecting the stress in the composite material winding layer by adopting an ultrasonic stress meter to obtain a circumferential stress distribution data point of the composite material, and fitting the stress distribution by adopting the following polynomials:
σ＝a+bx+cx 2 (1)
wherein x is the distance between the corresponding winding layer and the outer surface of the inner liner; a. b and c are coefficients to be determined;
obtaining undetermined coefficients a, b and c through data fitting, namely determining a circumferential stress distribution function under corresponding winding process parameters (F, T and T);
the construction method of the large sample data in the step S2 comprises the following steps:
b1: taking experimental variables of winding tension F, winding temperature T and curing time T as inputs, and taking undetermined coefficients a, b and c of fitting residual stress as outputs; based on the small samples obtained by the experiment, the sample domain of the variable is estimated, and the sample distribution MF is obtained,
wherein ,
IQR＝Q 3 -Q 1
wherein ,Q3 And Q is equal to 1 For the range of input variables, min and max are minimum and maximum observed values, and Me is a central position;
b2: the trend similarity is calculated by the following method:
selecting two parameters Xp and Xq for calculation, wherein Xp is an input variable, xq is any parameter, and a trend evaluation function g (i) p of an ith observation value between Xp and Xq is:
the similarity between Xp and Xq is calculated as the average of all available observations:
b3: predicting a section to generate a virtual value based on the values g (i) p, q obtained in step B2:
firstly, v is randomly selected xp Then generates v Xq From U (L) Xp ,U Xp ) A temporary value tv is randomly selected and an MF is calculated Xp (tv), then selecting a random seed rs from U (0, 1) to evaluate whether tv can be retained as the virtual value v xp The method comprises the steps of carrying out a first treatment on the surface of the Second, the cumulative probability of the cumulative distribution function value F (rs) of rs is calculated, when rs is smaller than MF Xp (tv) tv will be able to remain v Xp Otherwise, tv will be discarded, specifically:
producible prediction intervalThe method comprises the following steps:
wherein the variable is biased to
θ p,q ＝-0.8×|S p,q |+0.9
B4: bringing the obtained interval critical value into the following formula (8) to obtain v Xp Corresponding virtual sample v Xq ，
The construction method of the residual stress model in the step S3 comprises the following steps: based on the virtual sample and sample data obtained by experiments, constructing a black box model of winding tension F, winding temperature T, curing time T and output variables a, b and c by adopting a deep neural network algorithm; the obtained large sample data is subjected to normalization processing, then a deep neural network algorithm is adopted to train the sample, after the training is qualified, coefficients between winding process parameters and residual stress polynomial coefficients are obtained, and a hoop stress formula (1) is further adopted to obtain a stress distribution function sigma 1 (F,T,t,x)；
The construction method of the composite material vertical pipe stress model based on the laminated plate theory in the step S4 comprises the following steps:
firstly, based on the classical laminated plate theory of the composite material, the displacement general solution form of the composite material vertical pipe under an off-axis coordinate system is obtained,
wherein ,ur For radial displacement, k denotes the number of layers, r denotes the radial position, ε 0 Gamma, a constant corresponding to axial strain 0 Representing torsion per unit length, A (k) And B is connected with (k) Unknown coefficients are to be determined;
secondly, according to the conversion relation between the positive axis and the off-axis of the composite unidirectional material:
wherein ,[Tσ ] (k) And [ T ] ε ] (k) Represents a stiffness conversion matrix, [ C ]] (k) Is the positive axis stiffness;
boundary conditions:
internal and external surface stress conditions:
wherein ,P0 The pressure acting on the inner surface, σ represents the stress, r represents the radial direction, r 0 Represents the inner surface of the first layer, r N Represents the outer surface of the nth layer;
the displacement and stress continuous conditions of each layer in the inner part are as follows:
force and moment balance conditions:
wherein F represents an axial force, and M represents a bending moment;
the construction method of the composite material riser total stress model in the step S4 comprises the following steps:
solving an equation set consisting of all equations in the composite material vertical pipe stress model to obtain coefficients of all layers corresponding to a displacement formula, and then obtaining circumferential stress distribution sigma of all layers of the composite material vertical pipe in the main stress direction according to the displacement stress relation 2 (x)；
The composite riser total stress model is expressed as:
σ＝σ 1 (F,T,t,x)+σ 2 (x) (14)
wherein sigma is the composite riser hoop stress under consideration of residual stress;
the method for acquiring the technological parameters meeting the performance requirements of the composite material in the step S5 comprises the following steps:
c1: setting initial values of an optimizing algorithm, wherein the initial values comprise particle swarm evolution times, particle initial updating speed, learning factors and population scale;
c2: the obtained fluctuation value of the circumferential residual stress along the depth direction is taken as a moderate function, and a specific fluctuation value calculation formula is as follows:
and C3: and (3) performing crossing and mutation treatment through an optimizing algorithm, continuously circulating, and finally obtaining winding tension, winding temperature and curing time when the fluctuation value is the minimum value.
2. The method for designing parameters of a composite riser winding process according to claim 1, wherein the composite riser winding process in step S1 comprises a metal liner and a composite winding layer, and the composite riser winding process comprises the following steps:
a1: firstly, carrying out mechanical processing treatment on a metal lining, carrying out sand blasting treatment on the surface of the metal lining, washing with water to remove impurities, and completely drying; secondly, carrying out secondary acid washing treatment on the surface of the dried metal lining, washing with water and drying; finally, coating a thermosetting binder on the surface of the metal lining;
a2: and (3) using a composite material winding machine, applying winding tension F and winding temperature T to the prefabricated prepreg tows in a winding mode by adopting dry/wet winding, enabling the composite material vertical pipe to have an orthogonal symmetrical structure mode by adopting spiral winding, forming a composite material winding layer after winding, and curing the composite material vertical pipe to obtain the composite material winding vertical pipe.
3. The method for designing parameters of a composite riser winding process according to claim 2, wherein the composite winding layer in the step A2 is made of thermosetting epoxy resin, and the fibers are unidirectional carbon fibers.
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