CN116029216B - FPSO dynamic pipe cable type intelligent optimization method, system and application - Google Patents
FPSO dynamic pipe cable type intelligent optimization method, system and application Download PDFInfo
- Publication number
- CN116029216B CN116029216B CN202310128121.3A CN202310128121A CN116029216B CN 116029216 B CN116029216 B CN 116029216B CN 202310128121 A CN202310128121 A CN 202310128121A CN 116029216 B CN116029216 B CN 116029216B
- Authority
- CN
- China
- Prior art keywords
- dynamic
- fpso
- cable
- design
- intelligent optimization
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000005457 optimization Methods 0.000 title claims abstract description 75
- 238000000034 method Methods 0.000 title claims abstract description 57
- 238000013461 design Methods 0.000 claims abstract description 91
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 44
- 230000002068 genetic effect Effects 0.000 claims abstract description 40
- 230000000739 chaotic effect Effects 0.000 claims abstract description 39
- 230000003068 static effect Effects 0.000 claims description 22
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 16
- 238000004590 computer program Methods 0.000 claims description 14
- 230000035772 mutation Effects 0.000 claims description 12
- 238000004458 analytical method Methods 0.000 claims description 10
- 238000013507 mapping Methods 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 6
- 230000003044 adaptive effect Effects 0.000 claims description 5
- 238000007667 floating Methods 0.000 claims description 5
- 230000006872 improvement Effects 0.000 claims description 5
- 230000000670 limiting effect Effects 0.000 claims description 4
- 230000009471 action Effects 0.000 claims description 3
- 239000000725 suspension Substances 0.000 claims description 2
- 230000006870 function Effects 0.000 abstract description 8
- 238000012545 processing Methods 0.000 abstract description 8
- 230000007547 defect Effects 0.000 abstract description 5
- 206010063385 Intellectualisation Diseases 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 7
- 238000003860 storage Methods 0.000 description 6
- 239000003921 oil Substances 0.000 description 5
- 238000011161 development Methods 0.000 description 4
- 230000000694 effects Effects 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 238000012423 maintenance Methods 0.000 description 3
- 230000004044 response Effects 0.000 description 3
- 230000001154 acute effect Effects 0.000 description 2
- 238000005452 bending Methods 0.000 description 2
- 238000012938 design process Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 230000003321 amplification Effects 0.000 description 1
- 238000010835 comparative analysis Methods 0.000 description 1
- 239000010779 crude oil Substances 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000013079 data visualisation Methods 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000003199 nucleic acid amplification method Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000008092 positive effect Effects 0.000 description 1
- 230000002829 reductive effect Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012827 research and development Methods 0.000 description 1
- 230000002441 reversible effect Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
Images
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Revetment (AREA)
Abstract
The invention belongs to the technical field of ocean engineering data processing, and discloses an FPSO dynamic pipe-cable type intelligent optimization method, an FPSO dynamic pipe-cable type intelligent optimization system and application. The method comprises the following steps: taking the deepwater dynamic tube cable tether slow wave configuration to be optimized as an object, taking effective tension, curvature, balancing weight and buoyancy block parameters as optimization objective functions, introducing an improved chaotic self-adaptive genetic algorithm, adopting a programming program and nonlinear time domain finite element software program to jointly simulate and control the whole form and local deformation of the tube cable, and carrying out iterative computation to obtain the deepwater dynamic tube cable tether slow wave configuration meeting different sea conditions. The invention can shorten the design period and reduce the design cost while improving the design precision, and realize the intellectualization and high efficiency of the whole design flow. The invention aims to overcome the defects of low efficiency, poor result precision and the like of the existing deepwater dynamic pipe cable optimization design method.
Description
Technical Field
The invention belongs to the technical field of ocean engineering data processing, and particularly relates to an FPSO dynamic pipe-cable type intelligent optimization method, an FPSO dynamic pipe-cable type intelligent optimization system and application.
Background
The deep water FPSO (Floating Production Storage and Offloading, namely a floating production oil storage and discharge device, can be used for carrying out preliminary processing and storage on crude oil, is called as an offshore oil plant) dynamic pipeline type has obvious influence on the dynamic response and service safety of a system, and the linear optimization design method is an important research topic in the field of ocean engineering.
At present, the design method of static design and dynamic check is mainly adopted for the design of the dynamic pipe cable type, firstly, the static result of the pipe cable is analyzed, and then, the dynamic design is equivalent by combining the dynamic amplification coefficient. However, the dynamic tubeand cable design process faces many difficulties such as high degree of nonlinearity and a large number of critical design parameters.
Through the above analysis, the problems and defects existing in the prior art are as follows: the traditional linear design method often needs to carry out a large amount of trial calculation and analysis to meet design criteria and engineering requirements, cannot cope with nonlinear characteristics such as large displacement and large rotation angle of a dynamic pipe cable, is low in efficiency and poor in result precision, and cannot cope with acute operation and maintenance requirements of facilities in emergency working conditions such as natural disasters and engineering accidents in time.
Aiming at the defects, the invention establishes a static and dynamic optimal design-extreme working condition checking intelligent optimal design scheme of the deepwater dynamic pipe cable based on an improved chaotic self-adaptive genetic algorithm, and obviously shortens the design period, reduces the design cost and realizes the real-time design of the FPSO dynamic pipe cable.
Disclosure of Invention
In order to overcome the problems in the related art, the disclosed embodiments of the present invention provide a method, a system and an application for intelligent optimization of a FPSO dynamic management cable.
The technical scheme is as follows: the FPSO dynamic pipe cable type intelligent optimization method comprises the following steps: taking the deepwater dynamic tube cable tether slow wave configuration to be optimized as an object, taking effective tension, curvature, balancing weight and buoyancy block parameters as optimization objective functions, introducing an improved chaotic self-adaptive genetic algorithm, adopting a programming program and nonlinear time domain finite element software program to jointly simulate and control the whole form and local deformation of the tube cable, and carrying out iterative computation to obtain the deepwater dynamic tube cable tether slow wave configuration meeting different sea conditions.
The improved chaotic self-adaptive genetic algorithm comprises the following steps:
(1) Improving the population initialization mode: the method comprises the steps of establishing a chaotic mapping model, and introducing a sequence of the one-dimensional Logistic chaotic mapping model to generate an initial population, wherein the expression is as follows:
wherein i represents the serial number of individuals in the population, j represents the chaotic variable dimension,
the j-th dimension chaotic variable for the ith population individual,>
is a chaos factor;
(2) Improving crossover and mutation probabilities: introducing an adaptive crossover and mutation operator, selecting crossover and mutation probability according to individual fitness, and crossover probability P c Probability of variation P m The calculation formula is as follows:
wherein:
representing the initial crossover probability, +.>
Represents the probability of variation, k 1 Represents the cross coefficient, k 2 Representing the coefficient of variation->
Representing the fitness of the current generation of individuals, +.>
Representing maximum fitness of individuals in a populationDegree of response, ->
Representing the average value of the fitness of individuals in the population;
(3) Improvement elite strategy: introducing elite strategy into genetic algorithm and improving the genetic algorithm, and replacing N individuals with poor fitness in the external population with N individuals with higher fitness value in the internal population, wherein the expression is:
wherein, pop is the population size.
In one embodiment, an improved chaotic self-adaptive genetic algorithm is introduced, and a programming program and a nonlinear time domain finite element software program are adopted to jointly simulate and control the overall form and the local deformation of the cable, and the iterative calculation is carried out to obtain the deep water dynamic cable tether slow wave configuration meeting different sea conditions, which specifically comprises the following steps:
s1, determining a variable preliminary value range of an FPSO platform and a dynamic pipe cable overall system;
s2, based on an improved chaotic self-adaptive genetic algorithm, combining buoyancy blocks, balancing weights and tether parameters, performing intelligent optimization on the deepwater dynamic pipe cable tether slow wave configuration under a static design working condition;
s3, designing dynamic working conditions, and performing dynamic intelligent optimization design;
and S4, checking the mechanical properties of the deepwater dynamic pipe cable and determining the slow wave configuration of the deepwater dynamic pipe cable tether.
In step S1, the determining of the preliminary variable value range specifically includes:
setting the number, the positions and the arrangement interval variable parameters of the buoyancy blocks and the balancing weights, setting the limiting condition that the floating section of the pipe cable has a certain safety distance from the sea surface, and setting the suspension section distance that the sea bed has a corresponding safety distance; modeling analysis is carried out by utilizing nonlinear time domain finite element software program software, and a design variable preliminary value range required by maintaining the deep water dynamic pipe cable tether slow wave configuration under the still water condition is obtained;
the variable preliminary value range comprises: the initial position of the balancing weight is 0m-300m, the initial position of the buoyancy block is 350m-600m, the number of the balancing weights is 0-20, the number of the buoyancy blocks is 25-45, and the interval of the balancing weights is 2-10m.
In step S3, the performing the dynamic intelligent optimization design specifically includes: combining wave flow combined actions under different working conditions, and dynamically optimizing and designing a deepwater dynamic pipe cable tether slow wave configuration;
the different working conditions are as follows:
working condition 1: an initial position, 0 DEG wave flow; (0 m,0 °);
working condition 2: an initial position, 180 DEG wave flow; (0 m,180 °);
working condition 3: a far offset, 180 wave flow; (-90 m,180 °);
working condition 4: a near offset, 0 wave flow; (90 m,0 °).
Another object of the present invention is to provide an FPSO dynamic tube-cable type intelligent optimization system for implementing the FPSO dynamic tube-cable type intelligent optimization method, which includes:
the variable preliminary value range determining module is used for determining the variable preliminary value range of the FPSO platform and the dynamic pipe cable overall system;
the static working condition optimization module is used for intelligently optimizing the deepwater dynamic pipe cable tether slow wave configuration under the static design working condition based on the improved chaotic self-adaptive genetic algorithm and combining buoyancy blocks, balancing weights and tether parameters;
the dynamic working condition optimizing module is used for designing dynamic working conditions and carrying out dynamic intelligent optimizing design;
the tether slow wave configuration determining module is used for checking the mechanical properties of the deepwater dynamic pipe cable under the working condition of typhoons in centuries by combining engineering reality to determine the tether slow wave configuration of the deepwater dynamic pipe cable.
It is another object of the present invention to provide a program storage medium that receives user input, and a stored computer program causes an electronic device to execute the FPSO dynamic tube cable type intelligent optimization method.
It is a further object of the present invention to provide a computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the FPSO dynamic pipelining intelligent optimization method.
Another object of the present invention is to provide a deep water on-board dynamic pipe-and-cable type apparatus that performs the FPSO dynamic pipe-and-cable type intelligent optimization method.
By combining all the technical schemes, the invention has the advantages and positive effects that:
first, aiming at the technical problems existing in the prior art and the difficulty of solving the problems, the technical problems solved by the technical scheme of the invention to be protected, results and data in the research and development process and the like are closely combined, the technical problems solved by the technical scheme of the invention are analyzed in detail and deeply, and some technical effects with creativity brought after the problems are solved are specifically described as follows: the invention provides an intelligent optimization method for a FPSO dynamic pipe cable type, which aims to overcome the defects of low efficiency, poor result precision and the like of the existing optimization design method for the deep water dynamic pipe cable.
Secondly, the technical proposal is regarded as a whole or from the perspective of products, and the technical proposal to be protected has the technical effects and advantages as follows: the invention discloses an intelligent optimization design method for a FPSO dynamic pipe cable, which is characterized in that a chaotic sequence, a self-adaptive genetic operator and elite strategy are introduced to carry out chaotic self-adaptive genetic algorithm improvement, then Matlab (MATRixLABORRY is used for algorithm development, data visualization, data analysis and numerical computation) is adopted for high-level technical computing language and interactive environment.
Thirdly, as the inventive auxiliary evidence of the claims of the present invention, it is also presented in: the FPSO dynamic pipe cable design technology is a bottleneck technology which needs to be broken through urgently in deep sea oil gas development in China, and the current design process has the defects of low efficiency, poor instantaneity and the like. The advanced intelligent optimization algorithm is introduced, and the realization of the intellectualization and the high efficiency of the FPSO dynamic pipe and cable design flow is an important task for accelerating the deep sea oil gas development.
The FPSO dynamic pipe and cable design method adopted in the current engineering needs to carry out reverse check generation and trial calculation, and seriously affects the dynamic pipe and cable design efficiency. The FPSO dynamic pipe cable type intelligent optimization design method based on the improved chaotic self-adaptive genetic algorithm can obviously shorten the design period and reduce the design cost while improving the design precision, realizes the real-time design of the FPSO dynamic pipe cable type, meets the requirements of acute operation and maintenance of facilities in emergency working conditions such as natural disasters, engineering accidents and the like, and provides technical support for the design and operation and maintenance of the FPSO dynamic pipe cable for deep water oil and gas field development in China. Meanwhile, the traditional genetic algorithm is improved, the deepwater FPSO dynamic pipe cable tether slow wave configuration is taken as an optimal design object, effective tension, curvature, balancing weight and buoyancy block parameters are taken as an optimal objective function, and a chaotic sequence, a self-adaptive genetic operator and elite strategy are introduced, so that the problems of insufficient population diversity, easiness in sinking into local optimum and the like of the traditional genetic algorithm are overcome, and the practicability of the design method is further increased.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure;
FIG. 1 is a flow chart of an FPSO dynamic tube cable type intelligent optimization method provided by an embodiment of the invention;
FIG. 2 is a schematic diagram of an FPSO dynamic tube cable type intelligent optimization method provided by an embodiment of the invention;
FIG. 3 is a schematic diagram of static design conditions of a umbilical provided by an embodiment of the present invention;
FIG. 4 is a schematic diagram of a dynamic design condition of a umbilical provided by an embodiment of the present invention;
FIG. 5 is a schematic diagram of an FPSO dynamic tube cable type intelligent optimization system provided by an embodiment of the invention;
FIG. 6 is a schematic view of a slow wave configuration of a FPSO deepwater dynamic tube cable tether provided by an embodiment of the invention;
FIG. 7 is a schematic diagram of an optimal cable configuration extreme condition checking finite element model provided by an embodiment of the invention;
in the figure: 1. the variable preliminary value range determining module; 2. a static working condition optimizing module; 3. a dynamic working condition optimizing module; 4. and the tether slow wave configuration determining module.
Detailed Description
In order that the above objects, features and advantages of the invention will be readily understood, a more particular description of the invention will be rendered by reference to the appended drawings. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. The invention may be embodied in many other forms than described herein and similarly modified by those skilled in the art without departing from the spirit or scope of the invention, which is therefore not limited to the specific embodiments disclosed below.
1. Explanation of the examples:
the embodiment of the invention provides an FPSO dynamic pipe cable type intelligent optimization method, which comprises the following steps: taking the deepwater dynamic tube cable tether slow wave configuration to be optimized as an object, taking effective tension, curvature, balancing weight and buoyancy block parameters as optimization objective functions, introducing an improved chaotic self-adaptive genetic algorithm, adopting a programming program and nonlinear time domain finite element software program to jointly simulate and control the whole form and local deformation of the tube cable, and carrying out iterative computation to obtain the deepwater dynamic tube cable tether slow wave configuration meeting different sea conditions.
As shown in fig. 1, the FPSO dynamic pipe cable type intelligent optimization method provided by the embodiment of the invention includes the following steps:
s1, determining a variable primary value range of an FPSO platform and a dynamic pipe cable overall system, and ensuring that the system meets basic design requirements of buoyancy and stability in the ocean;
s2, based on an improved chaotic self-adaptive genetic algorithm, combining parameters such as a buoyancy block, a balancing weight, a tether and the like, performing intelligent optimization on a deepwater dynamic pipe cable tether slow wave configuration under a static design working condition;
the method comprises the steps of establishing a chaos self-adaptive genetic algorithm and hydrodynamic analysis integral optimization framework by Matlab software, connecting an optimization algorithm module with a hydrodynamic analysis module, reconstructing a model by mainly using design variables output by the optimization algorithm, dividing grids according to convergence difficulty of the model, and realizing multi-working-condition parallel processing of OrcaFlex by parallel codes.
Based on the integral optimization framework, according to the value range of the preliminary design, the number and position parameters of the buoyancy blocks and the balancing weights are considered, the minimum effective tension and the maximum bending radius are used as optimization targets, and the optimization design is carried out on the deepwater FPSO dynamic pipe cable slow wave configuration under the static design working condition.
S3, then designing a dynamic working condition, and performing dynamic intelligent optimization design;
and S4, finally, combining engineering reality, checking the mechanical properties of the deepwater dynamic pipe cable under the working condition of typhoons in centuries, and finally determining the optimal scheme of the deepwater dynamic pipe cable tether slow wave configuration.
As shown in fig. 2, the FPSO dynamic pipe cable type intelligent optimization method provided by the embodiment of the invention includes the following steps:
step one, determining a variable preliminary value range
And carrying out preliminary design of the dynamic pipe cable type according to the marine pipe cable design specification, thereby meeting the preliminary design requirement of the FPSO deepwater dynamic pipe cable tether slow wave configuration. The design variables are the number, the positions and the arrangement interval parameters of the buoyancy blocks and the balancing weights, and the limiting conditions are that the floating section of the pipe cable has a certain safety distance from the sea surface and the hanging section has a corresponding safety distance from the sea bed. Modeling analysis is carried out by using OrcaFlex software, and a primary value range of a design variable required for maintaining the deep water dynamic pipe cable tether slow wave configuration under the still water condition is provided. The variable preliminary value range comprises: the initial position of the balancing weight is 0m-300m; the initial position of the buoyancy block is 350m-600m; the number of the balancing weights is 0 to 20; the number of the buoyancy blocks is 25-45; the distance between the balancing weights is 2m-10m.
Step two, static optimization
Based on the improved chaotic self-adaptive genetic algorithm, the number and position parameters of buoyancy blocks and balancing weights are considered according to the value range of the primary design, the optimization design is carried out on the deep water dynamic pipe cable tether slow wave configuration, and the mechanical characteristics of the deep water dynamic pipe cable tether slow wave configuration under the static sea condition are analyzed. The optimization objective is to minimize the effective cable tension and maximize the bend radius. The static design conditions are shown in table 1, and the schematic diagram is shown in fig. 3.
TABLE 1 static design Condition of pipe Cable
Step three, dynamic optimization
And (3) dynamically optimizing and designing the tether wave-buffering configuration of the deepwater dynamic pipe cable by considering wave-current combined action under different working conditions based on an improved chaotic self-adaptive genetic algorithm according to an optimal design result obtained by static analysis of the deepwater dynamic pipe cable. In the dynamic optimization design, the deepwater dynamic pipe cable needs to be subjected to time domain dynamic analysis, and the dynamic analysis optimization target is less materials and better performance. The dynamic design conditions are shown in table 2, and the schematic diagram is shown in fig. 4.
TABLE 2 dynamic design conditions of pipe and cable
Step four, checking extreme working conditions
And the engineering practice is combined to design an FPSO mooring mode, the hundred year typhoon working condition is considered, wave flow is in the same direction, waves are Stokes fifth-order waves, and extreme working condition checking is carried out on the tether slow wave configuration obtained through final optimal design, so that the FPSO dynamic pipe and cable system is ensured to actually meet the design requirement under the actual extreme working condition.
Aiming at the problems that the population diversity of the traditional genetic algorithm is insufficient and the traditional genetic algorithm is easy to fall into local optimum and the like, the method improves the traditional genetic algorithm, takes the deepwater dynamic pipe cable tether slow wave configuration as an optimal design object, takes effective tension, curvature, balancing weight and buoyancy block parameters as an optimal objective function, introduces a chaotic sequence, a self-adaptive genetic operator and elite strategy, and adopts the improved chaotic self-adaptive genetic algorithm to optimally design the deepwater dynamic pipe cable tether slow wave configuration. The flow chart of the intelligent optimization method is shown in fig. 2, and the algorithm is specifically improved as follows:
(1) Improving the population initialization mode: the initial population of the traditional genetic algorithm is randomly generated in the primary design variable range, and if the adaptability of certain population is far higher than that of other individuals, the probability of being selected is higher, so that the population is easy to fall into local optimum. The invention establishes a chaotic mapping model, introduces a chaotic sequence to generate an initial population, and enhances the diversity of the population.
(2) Improving crossover and mutation probabilities: the crossover rate and variation probability of the traditional genetic algorithm are fixed values, and are usually selected by depending on a large amount of data and experience, and certain disadvantages exist, so that the quality of the optimal solution is seriously affected. Under the premise of not damaging population diversity, the invention introduces the self-adaptive crossover and mutation operator, selects crossover and mutation probability according to individual fitness, and ensures the algorithm to develop towards global optimum.
(3) Improvement elite strategy: elite strategies are introduced into genetic algorithms and improved, while maintaining excellent individuals while ensuring population diversity.
Illustratively, the improved chaotic adaptive genetic algorithm comprises:
(1) Improving the population initialization mode: the method comprises the steps of establishing a chaotic mapping model, and introducing a sequence of the one-dimensional Logistic chaotic mapping model to generate an initial population, wherein the expression is as follows:
wherein i represents the serial number of individuals in the population, j represents the chaotic variable dimension,
the j-th dimension chaotic variable for the ith population individual,>
is a chaos factor;
(2) Improving crossover and mutation probabilities: introducing an adaptive crossover and mutation operator, selecting crossover and mutation probability according to individual fitness, and crossover probability P c Probability of variation P m The calculation formula is as follows:
wherein:
representing the initial crossover probability, +.>
Represents the probability of variation, k 1 Represents the cross coefficient, k 2 Representing the coefficient of variation->
Representing the fitness of the current generation of individuals, +.>
Represents the maximum fitness of individuals in the population, +.>
Representing the average value of the fitness of individuals in the population;
(3) Improvement elite strategy: elite strategies are introduced into and improved upon genetic algorithms. And replacing N individuals with poor fitness in the external population with N individuals with higher fitness values in the internal population.
Wherein pop is population size.
As shown in fig. 5, the FPSO dynamic pipe-cable type intelligent optimization system provided by the embodiment of the invention includes:
the variable preliminary value range determining module 1 is used for determining the variable preliminary value range of the FPSO platform and the dynamic pipe cable overall system, so that the system is ensured to meet the basic design requirements of buoyancy and stability in the ocean;
the static working condition optimization module 2 is used for intelligently optimizing the deepwater dynamic pipe cable tether slow wave configuration under the static design working condition based on the improved chaotic self-adaptive genetic algorithm and by combining the parameters of the buoyancy block, the balancing weight, the tether and the like;
the dynamic working condition optimizing module 3 is used for designing dynamic working conditions and carrying out dynamic intelligent optimizing design;
and the tether slow wave configuration determining module 4 is used for finally combining engineering reality, checking the mechanical properties of the deepwater dynamic pipe cable under the working condition of typhoon in centuries and finally determining the optimal scheme of the deepwater dynamic pipe cable tether slow wave configuration.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
The content of the information interaction and the execution process between the devices/units and the like is based on the same conception as the method embodiment of the present invention, and specific functions and technical effects brought by the content can be referred to in the method embodiment section, and will not be described herein.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units and modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present invention. For specific working processes of the units and modules in the system, reference may be made to corresponding processes in the foregoing method embodiments.
2. Application examples:
application example 1
The invention can be applied to the intelligent optimization design of the deepwater FPSO dynamic pipe cable, and is specifically as follows:
the first seat of a certain oilfield is a cylindrical FPSO, the pipe cable configuration of the FPSO is in a tether wave-retarding shape, and the platform and the FPSO deepwater dynamic pipe cable system are shown in figure 6. The cylindrical FPSO, dynamic pipe cable, century sea state, buoyancy block and balancing weight related parameters are shown in tables 3, 4, 5, 6 and 7.
TABLE 3 cylindrical FPSO principal parameters
TABLE 4 dynamic Cable section parameters
TABLE 5 dynamic Cable hydrodynamic parameters
TABLE 6 buoyancy block and weight parameters
Table 7 hundred year sea condition parameters
And (3) carrying out optimal design on the dynamic pipe cable configuration under the static working condition based on the initial design range, wherein the efficiency is improved by about 300 percent in one iteration time of about 150 seconds through parallel processing, and the optimization obtains a slow wave configuration meeting the design requirements of tension and curvature, wherein the specific optimization result is shown in a table 8.
Table 8FPSO deepwater dynamic tube cable tether slow wave configuration static optimization results
Dynamic optimization of design results
And finally obtaining the optimal tether buffer line type through dynamic optimization design scheme, wherein the optimal value of the design variable is shown in table 9. The time of one iteration of the algorithm is 35-80s, and the iteration efficiency is improved by about 400%.
TABLE 9 optimal values of design variables for deep water dynamic pipeline tether and buffer configuration of FPSO
Wherein,,x 1 arranging initial position arc length coordinates for the buoyancy block;x 2 arranging an initial position arc length coordinate for the balancing weight;
1 is the space between buoyancy blocks; />
2 Is the distance between balancing weights;n 1 the number of the buoyancy blocks;n 2 the weight is the number of the balancing weights;x 3 arc length coordinates of the connection part of the tether and the dynamic cable;x 4 the coordinates of the basic position are tethered;U L is the tether length.
And checking the result under extreme working conditions: and (3) establishing a finite element hydrodynamic model (figure 7) of the FPSO deepwater dynamic pipe-cable system in OrcaFlex software by adopting an optimized FPSO optimal tether slow wave type, checking extreme working conditions of the tether slow wave configuration obtained by the final optimal design by considering the working conditions of typhoons in the century and the same wave flow direction, and finally calculating to obtain that the tension and curvature values of the FPSO dynamic pipe-cable system meet the design requirements under the actual extreme working conditions.
Application example 2
The embodiment of the invention provides computer equipment, which comprises: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, which when executed by the processor performs the steps of any of the various method embodiments described above.
Embodiments of the present invention also provide a computer readable storage medium storing a computer program which, when executed by a processor, performs the steps of the respective method embodiments described above.
The embodiment of the invention also provides an information data processing terminal, which is used for providing a user input interface to implement the steps in the method embodiments when being implemented on an electronic device, and the information data processing terminal is not limited to a mobile phone, a computer and a switch.
The embodiment of the invention also provides a server, which is used for realizing the steps in the method embodiments when being executed on the electronic device and providing a user input interface.
Embodiments of the present invention provide a computer program product which, when run on an electronic device, causes the electronic device to perform the steps of the method embodiments described above.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application implements all or part of the flow of the method of the above embodiments, and may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, where the computer program, when executed by a processor, may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to a photographing device/terminal apparatus, recording medium, computer Memory, read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), electrical carrier signals, telecommunications signals, and software distribution media. Such as a U-disk, removable hard disk, magnetic or optical disk, etc.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
3. Evidence of example related effects:
simulation experiments show that: aiming at the problems that the population diversity of the traditional genetic algorithm is insufficient and is easy to fall into local optimum and the like, the method improves the traditional genetic algorithm, takes the tether slow wave configuration of the deep water dynamic pipe cable as an optimal design object, takes effective tension, curvature, balancing weight and buoyancy block parameters as an optimal objective function, introduces a chaotic sequence, a self-adaptive genetic operator and elite strategy, and adopts the improved chaotic self-adaptive genetic algorithm to optimally design the tether slow wave configuration.
The invention finally obtains the optimal tether buffer line type through dynamic optimization design scheme, and the optimal value of the design variable is shown in table 9. The time of one iteration of the algorithm is 35s-80s, and the iteration efficiency is improved by about 400%.
Comparing and analyzing the dynamic tube cable slow wave configuration obtained by the preliminary design with the optimal tether slow wave configuration obtained by the dynamic optimization design, wherein the result is shown in a table 10, and comparing and analyzing shows that the invention obviously reduces the arrangement quantity of the tube cable buoyancy blocks and the balancing weights; in addition, under the hundred year working condition, the maximum tension of the dynamic response of the cable is reduced to 169.3KN from 243.21KN, and the minimum bending radius is increased to 17.8m from 10.63 m; therefore, the FPSO dynamic pipe and cable optimization design method provided by the invention can save the material cost and simultaneously can enable the pipe and cable to have better mechanical properties.
Table 10 results of comparative analysis of the tube and cable configurations before and after optimization
While the invention has been described with respect to what is presently considered to be the most practical and preferred embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, but on the contrary, is intended to cover various modifications, equivalents, and alternatives falling within the spirit and scope of the invention.
Claims (9)
1. The FPSO dynamic pipe cable type intelligent optimization method is characterized by comprising the following steps of:
s1, determining a variable preliminary value range of an FPSO platform and a dynamic pipe cable overall system;
s2, based on an improved chaotic self-adaptive genetic algorithm, combining buoyancy blocks, balancing weights and tether parameters, performing intelligent optimization on the deepwater dynamic pipe cable tether slow wave configuration under a static design working condition;
s3, designing dynamic working conditions, and performing dynamic intelligent optimization design;
s4, checking the mechanical properties of the deepwater dynamic pipe cable, and determining the tether slow wave configuration of the deepwater dynamic pipe cable;
in step S2, the improved chaotic adaptive genetic algorithm includes:
(1) Improving the population initialization mode: the method comprises the steps of establishing a chaotic mapping model, and introducing a sequence of the one-dimensional Logistic chaotic mapping model to generate an initial population, wherein the expression is as follows:
L i+1,j ＝μL i,j ×(1-L i,j )
wherein i represents the serial number of individuals in the population, j represents the chaotic variable dimension, L i,j The j-th dimensional chaotic variable of the ith population individual is represented by mu, and mu is a chaotic factor;
(2) Improving crossover and mutation probabilities: introducing an adaptive crossover and mutation operator, selecting crossover and mutation probability according to individual fitness, and crossover probability P c Probability of variation P m The calculation formula is as follows:
wherein:
representing the initial crossover probability, +.>
Represents the probability of variation, k 1 Represents the cross coefficient, k 2 Representing the coefficient of variation, fit (X) representing the fitness of the current generation of individuals, fit max Representing the maximum fitness of individuals in the population, fit avg Representing the average value of the fitness of individuals in the population;
(3) Improvement elite strategy: introducing elite strategy into genetic algorithm and improving the genetic algorithm, and replacing N individuals with poor fitness in the external population with N individuals with higher fitness value in the internal population, wherein the expression is:
N＝10％Popsize
wherein, pop is the population size.
2. The FPSO dynamic tube-cable type intelligent optimization method according to claim 1, wherein in step S1, the preliminary variable value range is determined, specifically comprising:
setting the number, the positions and the arrangement interval variable parameters of the buoyancy blocks and the balancing weights, setting the limiting condition that the floating section of the pipe cable has a certain safety distance from the sea surface, and setting the suspension section distance that the sea bed has a corresponding safety distance; modeling analysis is carried out by using nonlinear time domain finite element software program software, and a design variable preliminary value range required by maintaining the deep water dynamic pipe cable tether slow wave configuration under the still water condition is obtained.
3. The FPSO dynamic tube cable type intelligent optimization method according to claim 2, wherein,
the variable preliminary value range comprises: the initial position of the balancing weight is 0m-300m, the initial position of the buoyancy block is 350m-600m, the number of the balancing weights is 0-20, the number of the buoyancy blocks is 25-45, and the interval of the balancing weights is 2-10m.
4. The FPSO dynamic tube-and-cable type intelligent optimization method according to claim 1, wherein in step S3, the performing dynamic intelligent optimization design specifically includes: and combining wave flow combined actions under different working conditions, and dynamically optimizing and designing the deepwater dynamic tube cable tether slow wave configuration.
5. The FPSO dynamic tube-and-cable type intelligent optimization method according to claim 4, wherein in step S4, the different working conditions are:
working condition 1: an initial position, 0 DEG wave flow;
working condition 2: an initial position, 180 DEG wave flow;
working condition 3: a far offset, 180 wave flow;
working condition 4: near offset, 0 wave flow.
6. An FPSO dynamic tube-cable type intelligent optimization system for implementing the FPSO dynamic tube-cable type intelligent optimization method according to any one of claims 1 to 5, comprising:
the variable preliminary value range determining module (1) is used for determining the variable preliminary value range of the FPSO platform and the dynamic pipe cable overall system;
the static working condition optimization module (2) is used for intelligently optimizing the deepwater dynamic pipe cable tether slow wave configuration under the static design working condition based on the improved chaotic self-adaptive genetic algorithm and combining the buoyancy block, the balancing weight and the tether parameters;
the dynamic working condition optimizing module (3) is used for designing dynamic working conditions and carrying out dynamic intelligent optimization design;
and the tether slow wave configuration determining module (4) is used for checking the mechanical properties of the deepwater dynamic pipe cable under the working condition of typhoon in centuries by combining engineering reality to determine the tether slow wave configuration of the deepwater dynamic pipe cable.
7. A program storage medium for receiving user input, wherein the stored computer program causes an electronic device to perform the FPSO dynamic umbilical-type intelligent optimization method of any one of claims 1-5.
8. A computer device, characterized in that it comprises a memory and a processor, said memory storing a computer program, said computer program, when executed by said processor, causing said processor to perform the FPSO dynamic tube cable intelligent optimization method according to any one of claims 1-5.
9. A deep water on-board dynamic tube cable type device, characterized in that it performs the FPSO dynamic tube cable type intelligent optimization method according to any one of claims 1-5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310128121.3A CN116029216B (en) | 2023-02-17 | 2023-02-17 | FPSO dynamic pipe cable type intelligent optimization method, system and application |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310128121.3A CN116029216B (en) | 2023-02-17 | 2023-02-17 | FPSO dynamic pipe cable type intelligent optimization method, system and application |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116029216A CN116029216A (en) | 2023-04-28 |
| CN116029216B true CN116029216B (en) | 2023-06-09 |
Family
ID=86070656
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310128121.3A Active CN116029216B (en) | 2023-02-17 | 2023-02-17 | FPSO dynamic pipe cable type intelligent optimization method, system and application |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116029216B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2016000075A1 (en) * | 2014-07-03 | 2016-01-07 | Dan Grebenisan | System and method for increasing the length of telomeres |
| CN111606471A (en) * | 2020-05-12 | 2020-09-01 | 上海市政工程设计研究总院（集团）有限公司 | Vehicle-mounted device for disinfection and deodorization of sewage inspection well |
| CN114030563A (en) * | 2021-12-13 | 2022-02-11 | 中国海洋石油集团有限公司 | Multi-point mooring system suitable for cylindrical FPSO and design method thereof |
| CN114198569A (en) * | 2021-12-06 | 2022-03-18 | 深圳海油工程水下技术有限公司 | Underwater connection method of dynamic flexible pipe cable and anchoring base |
| CN217110958U (en) * | 2022-02-22 | 2022-08-02 | 深洋海工技术(深圳)有限公司 | Dynamic pipe cable type monitoring system |
-
2023
- 2023-02-17 CN CN202310128121.3A patent/CN116029216B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2016000075A1 (en) * | 2014-07-03 | 2016-01-07 | Dan Grebenisan | System and method for increasing the length of telomeres |
| CN111606471A (en) * | 2020-05-12 | 2020-09-01 | 上海市政工程设计研究总院（集团）有限公司 | Vehicle-mounted device for disinfection and deodorization of sewage inspection well |
| CN114198569A (en) * | 2021-12-06 | 2022-03-18 | 深圳海油工程水下技术有限公司 | Underwater connection method of dynamic flexible pipe cable and anchoring base |
| CN114030563A (en) * | 2021-12-13 | 2022-02-11 | 中国海洋石油集团有限公司 | Multi-point mooring system suitable for cylindrical FPSO and design method thereof |
| CN217110958U (en) * | 2022-02-22 | 2022-08-02 | 深洋海工技术(深圳)有限公司 | Dynamic pipe cable type monitoring system |
Non-Patent Citations (3)
| Title |
|---|
| 南海深水FPSO单点系泊***设计关键技术研究;李达;白雪平;王文祥;易丛;李刚;贾鲁生;李书兆;;中国海上油气(04);全文 * |
| 大型船舶管路优化设计;宋健;;科学技术创新(31);全文 * |
| 转塔式系泊FPSO中的缓波型立管水动力分析;徐显明;朱克强;姬芬芬;刘科伟;白勇;;中国航海(04);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116029216A (en) | 2023-04-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| McCabe et al. | Optimizing the shape of a surge-and-pitch wave energy collector using a genetic algorithm | |
| CN107944545B (en) | Computing method and computing device applied to neural network | |
| CN113268675B (en) | Social media rumor detection method and system based on graph attention network | |
| CN111323228A (en) | Fault diagnosis method based on time series mapping and convolutional neural network | |
| CN112937798B (en) | Efficient damaged ship instability motion assessment method | |
| CN112364942B (en) | Credit data sample equalization method and device, computer equipment and storage medium | |
| Saad et al. | A new kriging–bat algorithm for solving computationally expensive black-box global optimization problems | |
| CN116029216B (en) | FPSO dynamic pipe cable type intelligent optimization method, system and application | |
| CN115438571A (en) | Ground wave radar wave field calculation method and device based on machine learning | |
| CN115759979B (en) | Intelligent process processing method and system based on RPA and process mining | |
| CN116187401A (en) | Compression method and device for neural network, electronic equipment and storage medium | |
| CN110349228B (en) | Triangular mesh compression method for data-driven least square prediction | |
| CN115062769A (en) | Knowledge distillation-based model training method, device, equipment and storage medium | |
| CN112949841A (en) | Attention-based CNN neural network training method | |
| CN113222121A (en) | Data processing method, device and equipment | |
| Tanaka et al. | Template synthesis of cellular neural networks for information coding and decoding | |
| Marco et al. | Parallel genetic algorithms applied to optimum shape design in aeronautics | |
| CN116052096B (en) | Compressed data ship detection method, system and computer storage medium | |
| CN112927136B (en) | Image reduction method and system based on convolutional neural network domain adaptation | |
| CN115170916B (en) | Image reconstruction method and system based on multi-scale feature fusion | |
| CN109242937B (en) | Method and device for converting Mike flow field result file into shape vector file | |
| CN113158679B (en) | Marine industry entity identification method and device based on multi-feature superposition capsule network | |
| Chen et al. | Research on BP Neural Network Image Restoration Algorithm Based on Genetic Algorithm | |
| CN113978663B (en) | Automatic ballast water correction system and method and readable storage medium | |
| CN113345420B (en) | Anti-audio generation method and system based on firefly algorithm and gradient evaluation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |