A ship type comprehensive optimization method

Abstract

This invention relates to the field of ship hull optimization, specifically to a comprehensive ship hull optimization method, comprising: S1, setting constraints; S2, designing deformation control points and their deformation ranges; S3, constructing a genetic algorithm and setting its parameters; S4, calculating the hydrostatic resistance and fitness of individuals; S5, determining whether the maximum number of generations of the genetic algorithm has been reached; S6, selecting and replicating individuals with high fitness; S7, performing crossover and mutation on individuals with high fitness, and returning to S4; S8, terminating the genetic algorithm and outputting at least two hydrostatic resistance optimization schemes; S9, using the slicing method to calculate the wave resistance increase of the hydrostatic resistance optimization schemes; S10, selecting the scheme that best meets the shipowner's needs as the optimal scheme, and calculating the corresponding optimal ship hull hull using the FFD method. This invention achieves a balance between optimizing the speed and seakeeping of ships while reducing computational load.

Description

Technical Field

[0001] This invention relates to the field of ship morphology optimization, and more specifically to a comprehensive ship morphology optimization method. Background Technology

[0002] Today, the research on hull optimization is no longer limited to a single performance characteristic, but rather to the comprehensive optimization of multiple performance characteristics. The resulting optimized hull shapes are more practical, especially in terms of speed and seakeeping. SBD (Simulation Based Design) technology has opened up new possibilities for hull design and configuration innovation, achieving significant drag reduction and energy saving effects. However, this method has two drawbacks: one is that calculating hydrostatic resistance and seakeeping for all generated optimization schemes simultaneously leads to a large computational load; the other is that the generated hull shapes often cannot guarantee simultaneous optimization of hydrostatic resistance and seakeeping.

[0003] Currently, SBD optimization requires simultaneous calculations of resistance and seakeeping for all generated ship type schemes, resulting in excessive computational load. Furthermore, only one of speed and seakeeping performance is often optimized, and the computational workload is large. Summary of the Invention

[0004] To address the problems of excessive computational load in existing technologies and the inability to simultaneously optimize speed and seakeeping performance, this invention proposes a comprehensive ship hull optimization method that achieves a balance between optimizing speed and seakeeping performance while reducing computational load.

[0005] The technical solution of this invention is:

[0006] Step S1: Set constraints, including ship size constraints, design draft and displacement volume constraints, structural draft and displacement volume constraints, and structural draft stability constraints.

[0007] Step S2, design deformation control points and their deformation range: establish a global coordinate system, construct deformation regions at the bow and stern respectively, and set the deformation control points and their deformation range at the bow and stern respectively with X, Y and Z directions as deformation directions.

[0008] The deformation range of the bow control point in the Y direction is negative, that is, the bow width is reduced. According to the prompt of the CASES software, the reduction of the bow width can ensure that the bow waterline area is reduced.

[0009] Step S3: Construct a genetic algorithm. Based on the constraints, global coordinate system, deformation control points and their deformation range set in steps S1-S2, construct an initial population that meets the conditions, and set the genetic algorithm parameters.

[0010] The genetic algorithm parameters include: population size, crossover rate, mutation rate, and maximum number of generations;

[0011] The group consists of individuals of a population size, and each individual is a set of deformation control points and their deformation range.

[0012] Step S4, calculate the hydrostatic resistance of the individual, and calculate the fitness based on the hydrostatic resistance, including:

[0013] Step S401: Calculate the ship type corresponding to the individual using the FFD method;

[0014] Step S402: Calculate the hydrostatic resistance based on the ship type;

[0015] Specifically, the SST kw model is used as the turbulence model when calculating the hydrostatic resistance, and the VOF method is used to solve for the free surface.

[0016] In the VOF method, the discrete method adopts the finite volume method, the time term adopts the implicit Euler scheme, and the convection term adopts the second-order upwind scheme.

[0017] Step S403: Calculate the fitness of an individual based on its hydrostatic resistance, wherein the fitness is negatively correlated with the hydrostatic resistance.

[0018] Step S5: Determine whether the maximum number of generations of the genetic algorithm has been reached. If the maximum number of generations has been reached, proceed to step S8; otherwise, proceed to step S6.

[0019] Step S6: Select and replicate individuals with high fitness.

[0020] Step S7: Perform crossover and mutation on the individuals with high fitness obtained in step S6, and return to step S4;

[0021] Step S8: End the genetic algorithm and output at least two individuals with the highest fitness and their corresponding hydrostatic resistance. Use the output individuals as the hydrostatic resistance optimization scheme.

[0022] Step S9, using the slicing method to calculate the wave resistance increase of the still water resistance optimization scheme output in step S8, includes:

[0023] Step S901: Based on the ship type, the pitch and heave are calculated using the STF slice method, and based on the pitch and heave, the radiative energy method is used to calculate the increase in ship motion drag.

[0024] Step S902: Based on the ship type, calculate the increased drag due to wave reflection using the total internal reflection approximation formula;

[0025] Step S903: Summing the increased drag from ship motion and the increased drag from wave reflection yields the increased drag from waves.

[0026] Step S10: Based on the static resistance and wave resistance of the optimal static resistance scheme, select the scheme that best meets the shipowner's needs as the best scheme, and calculate the corresponding optimal ship type based on the optimal scheme using the FFD method.

[0027] This invention proposes a comprehensive ship hull optimization method that balances speed and seakeeping performance in ship design while reducing computational load. Specifically, by controlling a set of bow deformation points and their deformation ranges, the waterline area of ​​the bow is reduced to optimize seakeeping performance; a genetic algorithm is used to reduce hydrostatic resistance, thus optimizing speed; and the genetic algorithm selects several schemes with optimal speed performance. Only these schemes need to have their wave resistance increased to reflect seakeeping performance, rather than all schemes, thus reducing computational load. Attached Figure Description

[0028] Figure 1 This is a flowchart of the present invention.

[0029] Figure 2 This is a schematic diagram of the structural deformation region according to an embodiment of the present invention.

[0030] Figure 3 This is a schematic diagram of the X-direction deformation point of the bow in an embodiment of the present invention.

[0031] Figure 4 This is a schematic diagram of the Y-direction deformation point of the bow of a ship according to an embodiment of the present invention.

[0032] Figure 5 This is a schematic diagram of the Z-axis deformation point of the bow in an embodiment of the present invention.

[0033] Figure 6 This is a schematic diagram of the X-direction deformation point at the stern of a ship according to an embodiment of the present invention.

[0034] Figure 7 This is a schematic diagram of the deformation point in the Y direction at the stern of a ship according to an embodiment of the present invention.

[0035] Figure 8 This is a schematic diagram of the Z-axis deformation point at the stern of a ship according to an embodiment of the present invention.

[0036] Figure 9 This is a comparison diagram of the outlines of the optimal ship type and the ship type to be optimized in the embodiments of the present invention. Detailed Implementation

[0037] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0038] This invention proposes a comprehensive hull styling optimization method that combines the FFD geometric reconstruction method and the genetic algorithm, reducing the computational burden of hull styling optimization and simultaneously optimizing both speed and seakeeping performance.

[0039] The flowchart of this invention is as follows Figure 1 As shown, it includes:

[0040] Step S1: Set constraints, including ship size constraints, design draft and displacement volume constraints, structural draft and displacement volume constraints, and structural draft stability constraints.

[0041] In this embodiment, the dimensions of the vessel to be optimized are: length, width, and height of 172.8m, 30.7m, and 21.29m, respectively, with a displacement volume of 29309.7m³ at the design draft and structural draft. 3 38218.37m 3 The structural stability during water flow is 14.39m.

[0042] The constraints that the ship needs to meet during the optimization process are as follows:

[0043] (1) Keep the ship's length, width, and height unchanged;

[0044] (2) When the design draft is 8.5m, the drainage volume shall not be less than 28625.95m3;

[0045] (3) The drainage volume shall not be less than 37545.61 m3 when the structural draft is 10.5 m;

[0046] (4) The structural draft stability is high, not less than 14.30m.

[0047] Step S2: Construct a local coordinate system using the FFD (Free Form Deform) method, construct control points at the bow and stern respectively, and set the control points, deformation direction, and deformation range for the deformation.

[0048] Freeform deformation (FD) technology overcomes the limitations of traditional methods when performing overall and local shape changes on a target object. The basic principle of this method is as follows: First, a parametric volume is created, and the object to be deformed is embedded into this volume through local coordinate transformation. Second, a control vertex mesh is defined on the parametric volume, transforming it into a Bezier volume. Finally, the deformation of the parametric volume is transferred to the target object by moving the control points on the parametric volume.

[0049] Geometric reconstruction mainly involves the following four steps: constructing a local coordinate system, constructing control points, representing the deformed points, and solving the line equation. Here, we will first complete the first two steps of geometric reconstruction.

[0050] Construct a local coordinate system. The origin of the coordinate system in the deformable region is located at the intersection of the mid-section of the ship, the waterline, and station 0. The positive X-axis points from the stern to the bow, the positive Y-axis points from the mid-section of the ship to the port side, and the positive Z-axis points from the waterline to the deck. The global coordinate system satisfies the right-hand rule.

[0051] This invention selects the semi-parametric modeling method FFD to simultaneously optimize the bow and stern of the ship. When using FFD for parametric deformation, control points are selected to deform a certain area. The more concentrated the control points are, the greater the deformation is applied to the area.

[0052] Establish a deformable frame at both the bow and stern. Based on experience, establish a deformable frame at the bow measuring 88m long, 15.35m wide, and 21.25m high, and at the stern measuring 70m long, 15.35m wide, and 21.25m high. Figure 2 As shown.

[0053] Deformation control points in the X, Y, and Z directions of the bow and stern are selected respectively.

[0054] The bow deformation frame has 4 columns along the length of the ship, 4 columns along the beam, and 6 rows along the height (set up specifically for this ship type). The third row from the bottom is at the design draft of 8.5m. The selection of control points for this bow deformation is mainly based on the following points:

[0055] (1) Because the X-axis control points can affect the slenderness or wideness of the bow geometry, 48 points in the second and third columns along the positive length of the ship are selected for X-axis deformation of the ship, such as... Figure 3 As shown;

[0056] (2) In addition to optimizing the ship's hydrostatic resistance, this invention also needs to optimize its seakeeping performance. Wave resistance is mainly concentrated at the bow, and a smaller waterline area helps reduce wave resistance. According to the CASES software, a narrower bow width ensures a smaller bow waterline area. Therefore, four control points (the third row, at the design draft of 8.5m) are selected for Y-direction deformation, such as... Figure 4 As shown. Considering the practical need to reduce the waterline area, the values ​​of these four control points can only be negative, and they need to have a significant impact on the hull.

[0057] (3) Considering that to obtain the optimal ship shape, the hull needs to be sufficiently deformed, it is still necessary to select control points in the Z-axis to change the positions of each station line. If the points at the bottom of the ship are selected as control points, excessive deformation will occur at the bottom, which will not meet the optimization requirements. Therefore, eight points in the second row are selected for Z-axis deformation, such as... Figure 5 As shown.

[0058] The stern deformation frame has 5 columns along the ship's length, 4 columns along the ship's beam, and 6 rows along the ship's height. The third row from the bottom is at the design draft of 8.5m. Due to the complex stern shape, and because it was found during stern deformation that applying bidirectional deformation at too many control points would lead to excessive changes in the hull shape, especially at the tail fin, resulting in overlapping surfaces and hindering automated calculations, the control points selected at the stern are as follows:

[0059] (1) Select 72 points in the second, third, and fourth columns along the ship's length to deform the stern in the X direction, such as... Figure 6 As shown;

[0060] (2) No excessive deformation is performed in the Y and Z directions. Therefore, four control points are selected for deformation in each direction, such as... Figure 7 , Figure 8 As shown.

[0061] When setting the range of variation for design variables, each design variable must cause significant changes to the hull lines while ensuring that it does not lead to excessive hull deformation. The range of variation for each design variable is shown in Table 1:

[0062] Table 1 Range of Design Variables

[0063]

[0064] Where x, y, and z correspond to the deformation in the X, Y, and Z directions of the bow and stern, respectively.

[0065] Step S3: Construct a genetic algorithm. Based on the constraints, global coordinate system, deformation control points and their deformation range set in steps S1-S2, construct an initial population that meets the conditions, and set the genetic algorithm parameters.

[0066] The genetic algorithm parameters include: population size, crossover rate, mutation rate, and maximum number of generations;

[0067] The group consists of individuals of a population size, and each individual is a set of deformation control points and their deformation range.

[0068] The basic parameters of the genetic algorithm are set as shown in Table 2.

[0069] Table 2. Basic parameter settings for the genetic algorithm

[0070] Basic operating parameters Reasonable range The value in this embodiment Population size [20,100] 24 Cross rate [0.4,0.99] 0.9 Variation rate [0.0001,0.1] 0.01 Maximum Algebra Based on the actual situation 10

[0071] Based on the population size and the maximum number of generations, this embodiment will ultimately generate 240 optimized solutions.

[0072] Step S4, calculate the hydrostatic resistance of the individual, and calculate the fitness based on the hydrostatic resistance, including:

[0073] Step S401: Calculate the ship type corresponding to the individual using the FFD method;

[0074] Step S402 calculates the hydrostatic resistance used to indicate the ship's speed. The hydrostatic resistance calculation uses the numerical software starccm+, and the turbulence model used is the SST kw model, a variation of the kw model. This model ensures that it is unaffected by the free surface and maintains high accuracy on the solid wall. The free surface solution uses the VOF (Volume of Fluid) method. The discretization method used in this invention is the finite volume method, the time term uses an implicit Euler scheme, and the convection term uses a second-order upwind scheme, which has higher calculation accuracy than the first-order scheme.

[0075] Step S403: Calculate the fitness of an individual based on its hydrostatic resistance, wherein the fitness is negatively correlated with the hydrostatic resistance.

[0076] Step S5: Determine whether the maximum number of generations of the genetic algorithm has been reached. If the maximum number of generations has been reached, proceed to step S8; otherwise, proceed to step S6.

[0077] Step S6: Select and replicate individuals with high fitness.

[0078] Step S7: Perform crossover and mutation on the individuals with high fitness obtained in step S6, and return to step S4;

[0079] Individuals with high fitness have low hydrostatic resistance, meaning they are fast. By using a genetic algorithm to select, crossover, and mutate individuals with low hydrostatic resistance, the speed of offspring can be guaranteed.

[0080] Step S8: End the genetic algorithm and output at least two individuals with the highest fitness and their corresponding hydrostatic resistance. Use the output individuals as the hydrostatic resistance optimization scheme.

[0081] Step S9 involves calculating the wave drag increase of the still water resistance optimization scheme output in step S8 using the slicing method. This calculation indicates the ship's seakeeping ability and determines the optimal hull form. The wave drag increase consists of ship motion drag and wave reflection drag, and its value can be obtained by calculating and summing these two components. Specifically, this includes:

[0082] Step S901: Based on the ship type, the pitch and heave are calculated using the STF slice method, and based on the pitch and heave, the radiative energy method is used to calculate the increase in ship motion drag.

[0083] Step S902: Based on the ship type, calculate the increased drag due to wave reflection using the total internal reflection approximation formula;

[0084] Step S903: Summing the increased drag from ship motion and the increased drag from wave reflection yields the increased drag from waves.

[0085] Step S10: Based on the static resistance and wave resistance of the optimal static resistance scheme, select the scheme that best meets the shipowner's needs as the best scheme, and calculate the corresponding optimal ship type based on the optimal scheme using the FFD method.

[0086] After processing with a genetic algorithm, an array of still water resistance optimization schemes are obtained. The wave resistance increase of these still water resistance optimization schemes is calculated to obtain the optimal ship type. The design variables are shown in Table 3.

[0087] Table 3 Values ​​corresponding to optimal ship form design variables

[0088] <![CDATA[x1]]> <![CDATA[y1]]> <![CDATA[z1]]> <![CDATA[x2]]> <![CDATA[y2]]> <![CDATA[z2]]> Best ship type -0.699 -0.816 -0.221 0.353 -0.096 0.240

[0089] Comparison of the profiles of the optimal hull form and the hull form to be optimized, for example Figure 9 As shown in the figure, the red line represents the optimal ship type, and the black line represents the ship type to be optimized. The left side is the stern, and the right side is the bow. The curve numbers are the station numbers.

[0090] The calculation results of the static resistance and seakeeping of the optimal hull type and the hull type to be optimized are shown in Table 4 and Table 5, respectively.

[0091] Table 4 Comparison of changes in hydrostatic resistance

[0092] Calculation result / N change% Ship type to be optimized 60.14 － Best ship type 58.66 -2.46％

[0093] Table 5. Calculation results of wave resistance

[0094]

[0095] Thus, this invention simultaneously ensures both the speed and seakeeping of the vessel. Furthermore, compared to existing technologies that calculate the speed and seakeeping of all possible solutions, this invention only calculates the seakeeping performance of a few solutions with good speed, reducing the computational load required for the optimization process.

[0096] It should be noted that the specific embodiments described above enable those skilled in the art to more fully understand the present invention, but do not limit the present invention in any way. Therefore, although the present invention has been described in detail with reference to the accompanying drawings and embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the present invention. In short, all technical solutions and improvements that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the present invention patent.

Claims

1. A method for comprehensive optimization of ship hull design, characterized in that, include: Step S1: Set constraints, including ship size constraints, design draft and displacement volume constraints, structural draft and displacement volume constraints, and structural draft stability constraints. Step S2, design deformation control points and their deformation range: establish a global coordinate system, construct deformation regions at the bow and stern respectively, and set the deformation control points and their deformation range at the bow and stern respectively with X, Y and Z directions as deformation directions. The deformation range of the bow control point in the Y direction is negative, that is, the bow width is reduced. According to the prompt of the CASES software, the reduction of the bow width can ensure that the bow waterline area is reduced. Step S3: Construct a genetic algorithm. Based on the constraints, global coordinate system, deformation control points and their deformation range set in steps S1-S2, construct an initial population that meets the conditions, and set the genetic algorithm parameters. The genetic algorithm parameters include: population size, crossover rate, mutation rate, and maximum number of generations; The group consists of individuals of a population size, and each individual is a set of deformation control points and their deformation range. Step S4: Calculate the hydrostatic resistance of an individual, and calculate the fitness based on the hydrostatic resistance. The fitness is negatively correlated with the hydrostatic resistance. Step S5: Determine whether the maximum number of generations of the genetic algorithm has been reached. If the maximum number of generations has been reached, proceed to step S8; otherwise, proceed to step S6. Step S6: Select and replicate individuals with high fitness. Step S7: Perform crossover and mutation on the individuals with high fitness obtained in step S6, and return to step S4; Step S8: End the genetic algorithm and output at least two individuals with the highest fitness and their corresponding hydrostatic resistance. Use the output individuals as the hydrostatic resistance optimization scheme. Step S9: Calculate the wave resistance enhancement of the still water resistance optimization scheme output in step S8 using the slicing method. Step S10: Based on the static resistance and wave resistance of the optimal static resistance scheme, select the scheme that best meets the shipowner's needs as the best scheme, and calculate the corresponding optimal ship type based on the optimal scheme using the FFD method.

2. The ship morphology comprehensive optimization method according to claim 1, characterized in that, In step S4, the method for calculating the fitness is as follows: Step S401: Calculate the ship type corresponding to the individual using the FFD method; Step S402: Calculate the hydrostatic resistance based on the ship type; Step S403: Calculate the fitness of an individual based on its hydrostatic resistance, wherein the fitness is negatively correlated with the hydrostatic resistance.

3. The ship morphology comprehensive optimization method according to claim 2, characterized in that, The calculation of hydrostatic resistance uses the SST kw model as the turbulence model and the VOF method to solve for the free surface.

4. The ship morphology comprehensive optimization method according to claim 3, characterized in that, In the VOF method, the discrete method adopts the finite volume method, the time term adopts the implicit Euler scheme, and the convection term adopts the second-order upwind scheme.

5. The ship morphology comprehensive optimization method according to claim 1, characterized in that, In step S9, the method for calculating the wave resistance enhancement includes: Step S901: Based on the ship type, the pitch and heave are calculated using the STF slice method, and based on the pitch and heave, the radiative energy method is used to calculate the increase in ship motion drag. Step S902: Based on the ship type, calculate the increased drag due to wave reflection using the total internal reflection approximation formula; Step S903: Summing the increased drag from ship motion and the increased drag from wave reflection yields the increased drag from waves.

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