Method and device for optimizing buoyant raft impact protection performance under underwater explosion load

Abstract

The invention provides an optimization method and device for buoyant raft impact protection performance under an underwater explosion load, and the method comprises the steps: generating a buoyant raft impact protection system finite element model according to all assemblies in a buoyant raft impact protection system, the material attributes of the assemblies, and the unit type of a geometric model; calculating a buoyant raft impact environment based on an acoustic-solid coupling algorithm; based on an Isight-Abaqus-Python joint simulation algorithm, a buoyant raft impact protection optimization model is built; based on the constructed buoyant raft impact protection optimization model, parameter sensitivity analysis is carried out, influence factors of the buoyant raft on the impact protection performance of the equipment on the buoyant raft under the action of the underwater explosion load are identified, and protection performance optimization parameters of the buoyant raft impact protection system finite element model are obtained; according to protection performance optimization parameters of a finite element model, an optimal solution is iteratively calculated based on an NSGA-II genetic algorithm, and the problems that an underwater explosion test is high in cost and long in period, a buoyant raft impact protection system is complex in structure, and a direct analysis method is difficult to achieve are solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of shock protection for ship equipment, and particularly relates to an optimization method and device for the shock protection performance of a floating raft under underwater explosion loads. Background Art

[0002] With the development of modern weapon technologies, underwater vehicles are facing an increasingly serious threat of underwater explosions. As a common installation carrier for equipment inside underwater vehicles, improving the shock protection performance of the floating raft for the equipment installed on it under underwater explosion loads can effectively enhance the safety of the equipment inside the vehicle. The structure of the floating raft shock protection system is complex, and direct analysis methods are difficult to implement. Underwater explosion tests are costly and time-consuming, which is not conducive to the iterative optimization of the shock protection performance of the floating raft. Therefore, how to provide an optimization method for the shock protection performance of the floating raft under underwater explosion loads has become a technical problem urgently to be solved in this field. Summary of the Invention

[0003] The object of the present invention is to provide an optimization method and device for the shock protection performance of a floating raft under underwater explosion loads.

[0004] According to a first aspect of the present invention, there is provided an optimization method for the shock protection performance of a floating raft under underwater explosion loads, including:

[0005] Generating a finite element model of the floating raft shock protection system according to each component in the floating raft shock protection system, the material properties of the components, and the geometric model element types;

[0006] Presetting an underwater explosion charge load according to the required shock factor, and calculating the floating raft shock environment based on the acoustic-solid coupling algorithm;

[0007] Based on the finite element model of the floating raft shock protection system and the floating raft shock environment, building a floating raft shock protection optimization model based on the Isight-Abaqus-Python joint simulation algorithm;

[0008] Based on the built floating raft shock protection optimization model, performing a parameter sensitivity analysis to identify the influencing factors of the shock protection performance of the floating raft for the equipment on it under underwater explosion loads, and obtaining the protection performance optimization parameters of the finite element model of the floating raft shock protection system;

[0009] Based on the protection performance optimization parameters of the finite element model of the floating raft shock protection system, iteratively calculating the optimal solution based on the NSGA-II genetic algorithm.

[0010] Optionally, the generating a finite element model of the floating raft shock protection system according to each component in the floating raft shock protection system, the material properties of the components, and the geometric model element types includes:

[0011] Establish the geometric model of the raft shock protection system in ANSYS;

[0012] Import the geometric model of the raft shock protection system into Abaqus software and set the material properties of the geometric models of each component;

[0013] Set the element types of the geometric models of each component.

[0014] Perform mesh division;

[0015] Set the bonded boundary condition between the outer surface of the submersible cabin section and the inner surface of the seawater area;

[0016] Set the non-reflecting boundary condition on the outer surface of the seawater area to simulate the infinite sea area.

[0017] Optionally, according to the required shock factor, preset the underwater explosive charge load, and calculate the raft shock environment based on the acoustic-solid coupling algorithm, including:

[0018] Set the underwater explosive charge load;

[0019] Use Abaqus software to perform explicit dynamic analysis and calculate the acceleration response at the equipment installation position;

[0020] Use a Python program to extract the acceleration response time history curve at the equipment installation position from the Abaqus calculation result file;

[0021] Use a Python program to calculate the shock environment spectrum values at the equipment installation position, including spectral displacement, spectral velocity, and spectral acceleration.

[0022] Optionally, according to the finite element model of the raft shock protection system and the raft shock environment, build a raft shock protection optimization model based on the Isight-Abaqus-Python co-simulation algorithm, including:

[0023] Build the Isight-Abaqus-Python co-simulation optimization model;

[0024] Set the functional modules required for co-simulation in the Isight platform, including the Abaqus module, Extract_py module, SRS_Calculate module, Result module, DOE module, and Optimization module.

[0025] Optionally, based on the built raft shock protection optimization model, perform parameter sensitivity analysis to identify the influencing factors of the raft's shock protection performance on the equipment thereon under the action of underwater explosion load, and obtain the optimization parameters of the protection performance of the finite element model of the raft shock protection system, including:

[0026] Determine the parameters to be optimized according to the material properties, structural cross-sectional dimensions, and shock absorber parameters, and use the parameters to be optimized as input factors;

[0027] Select the impact environment spectrum value of the equipment installation position as the output parameter, where the impact environment spectrum value includes spectral displacement, spectral velocity, and spectral acceleration;

[0028] Set the perturbation amount of the input factor;

[0029] Adopt the optimal Latin hypercube design method in the DOE module of Isight to generate the experimental design space;

[0030] Use the Isight-Abaqus-Python joint simulation optimization model to calculate the influence rate of each input factor on the output parameter;

[0031] Sort according to the influence rate of the input factor on the output parameter, and determine the optimization parameters of the floating raft impact protection performance.

[0032] Optionally, based on the optimization parameters of the floating raft impact protection performance of the floating raft impact protection system finite element model, iteratively calculate the optimal solution based on the NSGA-II genetic algorithm, including:

[0033] Set the optimization algorithm as the NSGA-II genetic algorithm in the Optimization module of Isight;

[0034] Set the population algebra, iteration times, crossover probability, and mutation probability;

[0035] Set the minimum of the impact environment spectrum value of the equipment installation position as the objective function, and the impact environment spectrum value includes spectral displacement, spectral velocity, and spectral acceleration;

[0036] Set the constraint conditions, and set the constraint conditions according to the optional material properties, structural cross-sectional dimensions, and shock absorber parameter ranges;

[0037] Use the Isight-Abaqus-Python joint simulation optimization model to iteratively optimize and analyze the obtained Pareto solution set.

[0038] According to the second aspect of the present invention, there is provided an optimization device for the floating raft impact protection performance under underwater explosion loads, including:

[0039] A generation module for generating a finite element model of the floating raft impact protection system according to each component in the floating raft impact protection system, the material properties of the components, and the geometric model element types;

[0040] A calculation module for presetting the underwater explosion charge load according to the required impact factors and calculating the floating raft impact environment based on the acoustic-solid coupling algorithm;

[0041] An optimization module, configured to build a floating raft shock protection optimization model based on the floating raft shock protection system finite element model and the floating raft shock environment, by means of the Isight-Abaqus-Python co-simulation algorithm;

[0042] An analysis module, configured to perform parameter sensitivity analysis based on the built floating raft shock protection optimization model, identify the influencing factors of the floating raft's shock protection performance for the equipment thereon under underwater explosion loads, and obtain the protection performance optimization parameters of the floating raft shock protection system finite element model;

[0043] A determination module, configured to iteratively calculate the optimal solution based on the protection performance optimization parameters of the floating raft shock protection system finite element model, by means of the NSGA-II genetic algorithm.

[0044] Optionally, the generation module is configured to:

[0045] Build a geometric model of the floating raft shock protection system in ANSYS;

[0046] Import the geometric model of the floating raft shock protection system into Abaqus software, and set the material properties of the geometric models of each component;

[0047] Set the element types of the geometric models of each component.

[0048] Perform mesh division;

[0049] Set the binding boundary condition between the outer surface of the submersible cabin section and the inner surface of the seawater area;

[0050] Set the non-reflecting boundary condition on the outer surface of the seawater area to simulate an infinite sea area.

[0051] Optionally, the calculation module is configured to:

[0052] Set the underwater explosive charge load;

[0053] Use Abaqus software to perform explicit dynamics analysis and calculate the acceleration response at the equipment installation location;

[0054] Use a Python program to extract the acceleration response time history curve at the equipment installation location from the Abaqus calculation result file;

[0055] Use a Python program to calculate the shock environment spectrum values at the equipment installation location, including spectral displacement, spectral velocity, and spectral acceleration.

[0056] Optionally, the optimization module is configured to:

[0057] Build an Isight-Abaqus-Python co-simulation optimization model;

[0058] Function modules required for co - simulation are set in the Isight platform, including the Abaqus module, the Extract_py module, the SRS_Calculate module, the Result module, the DOE module, and the Optimization module.

[0059] Optionally, the analysis module is used for:

[0060] Determine the parameters to be optimized according to the material properties, the structural cross - section dimensions, and the shock absorber parameters, and use the parameters to be optimized as input factors;

[0061] Select the impact environment spectrum value of the equipment installation location as the output parameter, where the impact environment spectrum value includes spectral displacement, spectral velocity, and spectral acceleration;

[0062] Set the perturbation amount of the input factor;

[0063] Adopt the optimal Latin hypercube design method in the DOE module of Isight to generate the experimental design space;

[0064] Use the Isight - Abaqus - Python co - simulation optimization model to calculate the influence rate of each input factor on the output parameter;

[0065] Sort according to the influence rate of the input factor on the output parameter, and determine the optimization parameters for the floating raft shock protection performance.

[0066] Optionally, the determination module is used for:

[0067] Set the optimization algorithm as the NSGA - II genetic algorithm in the Optimization module of Isight;

[0068] Set the population generation number, the number of iterations, the crossover probability, and the mutation probability;

[0069] Set the minimum of the impact environment spectrum value of the equipment installation location as the objective function, where the impact environment spectrum value includes spectral displacement, spectral velocity, and spectral acceleration;

[0070] Set the constraint conditions, and set the constraint conditions according to the optional material properties, the structural cross - section dimensions, and the shock absorber parameter ranges;

[0071] Use the Isight - Abaqus - Python co - simulation optimization model to iteratively optimize the obtained Pareto solution set.

[0072] In a third aspect, the present application shows an electronic device, which includes: a processor; a memory for storing processor - executable instructions; wherein, the processor is configured to execute the method described in any of the above aspects.

[0073] Fourthly, the present application discloses a non-transitory computer-readable storage medium. When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device can execute the method described in any of the above aspects.

[0074] Fifthly, the present application discloses a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device can execute the method described in any of the above aspects.

[0075] The beneficial effects brought by the present invention are as follows:

[0076] As can be seen from the above solutions, the embodiments of the present invention provide an optimization method and device for the shock protection performance of a floating raft under underwater explosion loads, including: generating a finite element model of the floating raft shock protection system according to each component in the floating raft shock protection system, the material properties of the components, and the geometric model unit types; presetting the underwater explosion charge load according to the required shock factor, and calculating the floating raft shock environment based on the acoustic-solid coupling algorithm; building an optimization model for the floating raft shock protection based on the Isight-Abaqus-Python joint simulation algorithm according to the finite element model of the floating raft shock protection system and the floating raft shock environment; performing parameter sensitivity analysis based on the built optimization model for the floating raft shock protection, identifying the influencing factors of the shock protection performance of the floating raft on the equipment thereon under underwater explosion loads, and obtaining the optimization parameters for the shock protection performance of the finite element model of the floating raft shock protection system; and iteratively calculating the optimal solution based on the NSGA-II genetic algorithm according to the optimization parameters for the shock protection performance of the finite element model of the floating raft shock protection system. The embodiments of the present application can effectively improve the shock protection performance of the floating raft on the installed equipment under underwater explosion loads, and solve the problems of high cost and long cycle of underwater explosion tests, complex structure of the floating raft shock protection system, and difficulty in implementing direct analysis methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 is a schematic flow chart of an optimization method for the shock protection performance of a floating raft under underwater explosion loads provided according to an embodiment;

[0078] Figure 2 is a flow chart of optimizing the shock protection performance of a floating raft provided according to an embodiment;

[0079] Figure 3 is a flow chart of establishing a finite element model of a floating raft shock protection system provided according to an embodiment;

[0080] Figure 4 is a finite element model of a floating raft shock protection system provided according to an embodiment;

[0081] Figure 5Schematic diagram of fluid-structure interaction binding boundary conditions and non-reflecting boundary conditions provided according to an embodiment;

[0082] Figure 6 Flow chart of calculating the floating raft shock environment based on the acoustic-structure coupling algorithm provided according to an embodiment;

[0083] Figure 7 Architecture diagram of the Isight-Abaqus-Python co-simulation optimization model provided according to an embodiment;

[0084] Figure 8 Flow chart of parameter sensitivity analysis provided according to an embodiment;

[0085] Figure 9 Flow chart of iteratively calculating the optimal solution based on the NSGA-II genetic algorithm provided according to an embodiment;

[0086] Figure 10 Block diagram of the structure of an optimization device for the floating raft shock protection performance under underwater explosion loads of the present application.

[0087] Figure 11 Block diagram of an electronic device of the present application.

[0088] Figure 12 Block diagram of a computer-readable storage medium of the present application. Detailed implementation manners

[0089] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0090] Refer to Figure 1 , which shows the step flow chart of an optimization method for the floating raft shock protection performance under underwater explosion loads of the present application. This method can be applied to an electronic device. Specifically, the method may include the following steps:

[0091] S101. Generate a finite element model of the floating raft shock protection system according to each component in the floating raft shock protection system, the material properties of the components, and the geometric model element types;

[0092] S102. Preset the underwater explosion charge load according to the required shock factor, and calculate the floating raft shock environment based on the acoustic-structure coupling algorithm;

[0093] S103. Based on the finite element model of the floating raft shock protection system and the floating raft shock environment, an optimization model for the floating raft shock protection is established based on the Isight-Abaqus-Python joint simulation algorithm;

[0094] S104. Based on the established optimization model for the floating raft shock protection, a parameter sensitivity analysis is carried out to identify the influencing factors of the shock protection performance of the floating raft on the equipment thereon under the action of underwater explosion loads, and the optimized parameters for the shock protection performance of the finite element model of the floating raft shock protection system are obtained;

[0095] S105. According to the optimized parameters for the shock protection performance of the finite element model of the floating raft shock protection system, the optimal solution is iteratively calculated based on the NSGA-II genetic algorithm.

[0096] Another embodiment of the present application further supplements and explains the optimization method for the shock protection performance of the floating raft under the underwater explosion load provided in the above embodiment.

[0097] The technical problem solved by the present invention is to identify the main influencing factors and their influencing effects of the shock protection performance of the floating raft on the equipment installed thereon under the action of underwater explosion loads. Improve the shock protection performance of the floating raft on the equipment installed thereon under the action of underwater explosion loads, and solve the problems of high cost and long cycle of underwater explosion tests, complex structure of the floating raft shock protection system, and difficulty in realizing direct analysis methods.

[0098] The solution of the present invention is an optimization method for the shock protection performance of the floating raft under the action of underwater explosion loads based on Isight software, and the main steps include establishing a finite element model of the floating raft shock protection system, calculating the floating raft shock environment based on the acoustic-solid coupling algorithm, building an Isight-Abaqus-Python joint simulation optimization model, parameter sensitivity analysis, and iteratively calculating the optimal solution based on the NSGA-II genetic algorithm.

[0099] Optionally, according to each component in the floating raft shock protection system, the material properties of the components and the geometric model element types, a finite element model of the floating raft shock protection system is generated, including:

[0100] Establish a geometric model of the floating raft shock protection system in ANSYS;

[0101] Import the geometric model of the floating raft shock protection system into Abaqus software and set the material properties of the geometric models of each component;

[0102] Set the geometric model element types of each component.

[0103] Perform mesh division;

[0104] Set the binding boundary condition between the outer surface of the submarine cabin section and the inner surface of the seawater area;

[0105] Set the non-reflecting boundary condition on the outer surface of the seawater domain to simulate an infinite sea area.

[0106] Specifically, (1) Establish a geometric model of the raft shock protection system in ANSYS. The raft shock protection system includes six components: the submersible cabin section, the raft, the raft mounting base, the raft shock absorber, the equipment, and the seawater. The submersible cabin section is composed of a cylindrical shell, ring ribs, bulkheads, and bulkhead stringers. The raft is composed of a platform panel, main beams, main girders, cross beams, inter-platform struts, and side struts.

[0107] (2) Import the geometric model of the raft shock protection system into Abaqus software and set the material properties of each component's geometric model.

[0108] (3) Set the element types of each component's geometric model. The submersible cabin section is a stiffened cylindrical shell structure, and the ring ribs are T-shaped steel. Therefore, the outer shell is simulated using shell elements, and the ring ribs are simulated using beam elements. The raft is a plate-beam and strut structure, the cross and longitudinal beams are T-shaped steel, the inter-platform struts are square steel pipes, and the side struts are I-beams. So, the raft panel is simulated using shell elements, and the stiffeners and struts are simulated using beam elements. The base is a panel and liner structure and is simulated using shell elements. The equipment is established as a solid block with a similar structure and the same mass using solid elements to ensure properties such as the mass and moment of inertia of the equipment. The shock absorber generally includes an elastic energy storage element and a damping energy dissipation element and is simulated using a spring element with three-directional stiffness-damping. The flow field is simulated using acoustic elements.

[0109] (4) Perform mesh division;

[0110] (5) Set the bonded boundary condition between the outer surface of the submersible cabin section and the inner surface of the seawater domain, as Figure 5 shown;

[0111] (6) Set the non-reflecting boundary condition on the outer surface of the seawater domain to simulate an infinite sea area.

[0112] The optimization process of the raft shock protection performance is as Figure 2 shown, the process of establishing the finite element model of the raft shock protection system is as Figure 3 shown, and the finite element model of the raft shock protection system (excluding seawater) is as Figure 4 shown.

[0113] The process of calculating the raft shock environment based on the acoustic-solid coupling algorithm is as Figure 6 shown.

[0114] Optionally, according to the required shock factor, preset the underwater explosive charge load and calculate the raft shock environment based on the acoustic-solid coupling algorithm, including:

[0115] Set the underwater explosive charge load;

[0116] Perform a display dynamics analysis using Abaqus software to calculate the acceleration response at the equipment installation location;

[0117] Use a Python program to extract the acceleration response time history curve at the equipment installation location from the Abaqus calculation result file;

[0118] Use a Python program to calculate the shock environment spectrum values at the equipment installation location, including spectral displacement, spectral velocity, and spectral acceleration.

[0119] Specifically, (1) Set the underwater explosive charge load;

[0120] (2) Perform a display dynamics analysis using Abaqus software to calculate the acceleration response at the equipment installation location;

[0121] (3) Use a Python program to extract the acceleration response time history curve at the equipment installation location from the Abaqus calculation result file;

[0122] (4) Use a Python program to calculate the shock environment spectrum values at the equipment installation location, including spectral displacement, spectral velocity, and spectral acceleration.

[0123] As Figure 7 is the architecture diagram of the Isight - Abaqus - Python co - simulation optimization model. Optionally, based on the finite element model of the floating raft shock protection system and the floating raft shock environment, build a floating raft shock protection optimization model based on the Isight - Abaqus - Python co - simulation algorithm, including:

[0124] Build an Isight - Abaqus - Python co - simulation optimization model;

[0125] Set the functional modules required for co - simulation in the Isight platform, including the Abaqus module, Extract_py module, SRS_Calculate module, Result module, DOE module, and Optimization module.

[0126] Specifically, the building of the Isight - Abaqus - Python co - simulation optimization model lies in setting the functional modules required for co - simulation in the Isight platform, including the Abaqus module, Extract_py module, SRS_Calculate module, Result module, DOE module, and Optimization module. The functions of each module are as follows:

[0127] Abaqus module: Receive the input parameters output from the DOE module or Optimization module, run the ".inp" model file modified in this round, and calculate the impact acceleration response of the installation part of the raft equipment under underwater explosion load by using the explicit dynamic method;

[0128] Extract_py module: The first Simcode module in this process, execute the internal instruction to call the Extract.py program, which is used to extract the impact acceleration time history curve of the installation part of the raft equipment from the ".odb" file of the Abaqus analysis result in this round;

[0129] SRS_Calculate module: The second Simcode module in this process, execute the internal instruction to call the SRS_Calculate.py program, calculate the impact environment spectrum value from the acceleration time history curve extracted by the Extract_py module, and store it in the Result.xlsx table;

[0130] Result module: Used to store the impact environment spectrum value of the installation part of the raft equipment calculated by the SRS_Calculate module in this round, and then transfer it to the DOE module for sensitivity analysis or transfer it to the Optimization module for iterative optimization.

[0131] DOE module: Set the input factors and output parameters, establish the experimental design space, and provide the input parameters for each iteration; Receive the impact environment spectrum value stored in the Result module during each iteration process; Conduct sensitivity analysis and calculate the contribution rate of the input factors to the output parameters;

[0132] Optimization module: Set the optimization algorithm and set the algorithm parameters; Set the objective function; Set the constraint conditions; Optimize the obtained Pareto solution set.

[0133] The parameter sensitivity analysis process is as Figure 8 shown. Optionally, based on the established raft impact protection optimization model, conduct parameter sensitivity analysis,

[0134] Identify the influencing factors of the impact protection performance of the raft on the equipment on it under underwater explosion load, and obtain the optimization parameters of the protection performance of the finite element model of the raft impact protection system, including:

[0135] According to the material properties, structural cross-sectional dimensions and shock absorber parameters, determine the parameters to be optimized, and use the parameters to be optimized as input factors;

[0136] Select the impact environment spectrum value of the equipment installation position as the output parameter, where the impact environment spectrum value includes spectral displacement, spectral velocity, and spectral acceleration;

[0137] Set the input factor perturbation amount;

[0138] In the DOE module of Isight, use the optimal Latin hypercube design method to generate the experimental design space;

[0139] Use the Isight-Abaqus-Python co-simulation optimization model to calculate the influence rate of each input factor on the output parameter;

[0140] Sort according to the influence rate of the input factor on the output parameter, and determine the optimization parameters for the floating raft shock protection performance.

[0141] Specifically, (1) Initially select the parameters to be optimized as input factors. Mainly select the parameters to be optimized from three aspects: material properties, structural cross-sectional dimensions, and shock absorber parameters.

[0142] (2) Select the shock environment spectrum value of the equipment installation position as the output parameter. The shock environment spectrum value includes spectral displacement, spectral velocity, and spectral acceleration.

[0143] (3) Set the input factor perturbation amount;

[0144] (4) In the DOE module of Isight, use the optimal Latin hypercube design method to generate the experimental design space;

[0145] (5) Use the Isight-Abaqus-Python co-simulation optimization model to calculate the influence rate of each input factor on the output parameter;

[0146] (6) Sort according to the influence rate of the input factor on the output parameter, and determine the optimization parameters for the floating raft shock protection performance.

[0147] The process of iterative calculation of the optimal solution based on the NSGA-II genetic algorithm is as Figure 9 shown. Optionally, according to the optimization parameters of the floating raft shock protection system finite element model, iterative calculation of the optimal solution based on the NSGA-II genetic algorithm includes:

[0148] In the Optimization module of Isight, set the optimization algorithm as the NSGA-II genetic algorithm;

[0149] Set the population algebra, iteration times, crossover probability, and mutation probability;

[0150] Set the minimum shock environment spectrum value of the equipment installation position as the objective function. The shock environment spectrum value includes spectral displacement, spectral velocity, and spectral acceleration;

[0151] Set the constraint conditions, and set the constraint conditions according to the optional material properties, structural cross-sectional dimensions, and shock absorber parameter ranges;

[0152] The Pareto solution set obtained by iterative optimization analysis of the joint simulation of Isight - Abaqus - Python optimization model.

[0153] Specifically, (1) Set the optimization algorithm to the NSGA - II genetic algorithm in the Optimization module of Isight;

[0154] (2) Set the population generation number, iteration times, crossover probability, and mutation probability;

[0155] (3) Set the minimum of the shock environment spectrum value of the equipment installation position as the objective function. The shock environment spectrum value includes spectrum displacement, spectrum velocity, and spectrum acceleration;

[0156] (4) Set the constraint conditions. Set the constraint conditions according to the optional material properties, structural cross - section dimensions, and shock absorber parameter ranges.

[0157] (5) The Pareto solution set obtained by iterative optimization analysis of the joint simulation of Isight - Abaqus - Python optimization model.

[0158] 1. It can identify the main influencing factors and influencing effects of the shock protection performance of the raft on the equipment installed on it under the action of underwater explosion loads;

[0159] 2. It can improve the shock protection performance of the raft on the equipment installed on it under the action of underwater explosion loads, and solve the problems of high cost and long cycle of underwater explosion tests, complex structure of the raft shock protection system, and difficulty in implementing direct analysis methods.

[0160] The embodiment of the present invention provides an optimization method for the shock protection performance of a raft under underwater explosion loads, including: generating a finite - element model of the raft shock protection system according to each component in the raft shock protection system, the material properties of the components, and the geometric model element types; presetting an underwater explosion charge load according to the required shock factor, and calculating the raft shock environment based on the acoustic - solid coupling algorithm; based on the finite - element model of the raft shock protection system and the raft shock environment, building a raft shock protection optimization model based on the Isight - Abaqus - Python joint simulation algorithm; based on the built raft shock protection optimization model, identifying the influencing factors of the shock protection performance of the raft on the equipment on it under the action of underwater explosion loads, and obtaining the protection performance optimization parameters of the finite - element model of the raft shock protection system; based on the protection performance optimization parameters of the finite - element model of the raft shock protection system, iteratively calculating the optimal solution based on the NSGA - II genetic algorithm. The embodiment of the present application can effectively improve the shock protection performance of the raft on the equipment installed on it under the action of underwater explosion loads, and solve the problems of high cost and long cycle of underwater explosion tests, complex structure of the raft shock protection system, and difficulty in implementing direct analysis methods.

[0161] It should be noted that each implementable mode in this embodiment can be implemented independently, or can be implemented in any combination without conflict. This application does not make any limitations.

[0162] Another embodiment of this application provides an optimization device for the shock protection performance of a floating raft under an underwater explosion load, which is used to execute the optimization method for the shock protection performance of a floating raft under an underwater explosion load provided in the above embodiment.

[0163] As Figure 10 shown, it is a schematic structural diagram of the optimization device for the shock protection performance of a floating raft under an underwater explosion load provided in an embodiment of this application. The optimization device for the shock protection performance of a floating raft under an underwater explosion load includes a generation module 1001, a calculation module 1002, an optimization module 1003, an analysis module 1004, and a determination module 1005, where:

[0164] The generation module 1001 is used to generate a finite element model of the floating raft shock protection system according to each component in the floating raft shock protection system, the material properties of the components, and the geometric model unit type.

[0165] The calculation module 1002 is used to preset the underwater explosive charge load according to the required shock factor, and calculate the floating raft shock environment based on the acoustic-solid coupling algorithm.

[0166] The optimization module 1003 is used to build an optimization model for the floating raft shock protection based on the Isight-Abaqus-Python joint simulation algorithm according to the finite element model of the floating raft shock protection system and the floating raft shock environment.

[0167] The analysis module 1004 is used to identify the influencing factors of the shock protection performance of the floating raft on the equipment thereon under the action of the underwater explosion load based on the built optimization model for the floating raft shock protection, and obtain the protection performance optimization parameters of the finite element model of the floating raft shock protection system.

[0168] The determination module 1005 is used to iteratively calculate the optimal solution based on the NSGA-II genetic algorithm according to the protection performance optimization parameters of the finite element model of the floating raft shock protection system.

[0169] Regarding the device in this embodiment, the specific ways for each module to execute operations have been described in detail in the embodiment related to the method, and will not be elaborated here.

[0170] Another embodiment of this application further supplements and explains the optimization device for the shock protection performance of a floating raft under an underwater explosion load provided in the above embodiment.

[0171] Optionally, the generation module is used for:

[0172] Establish the geometric model of the floating raft shock protection system in ANSYS;

[0173] Import the geometric model of the floating raft shock protection system into Abaqus software and set the material properties of each component's geometric model;

[0174] Set the element types of each component's geometric model.

[0175] Perform mesh division;

[0176] Set the bonded boundary condition between the outer surface of the submersible cabin section and the inner surface of the seawater area;

[0177] Set the non-reflective boundary condition on the outer surface of the seawater area to simulate an infinite sea area.

[0178] Optionally, a calculation module for:

[0179] Set the underwater explosive charge load;

[0180] Use Abaqus software for explicit dynamic analysis and calculate the acceleration response at the equipment installation location;

[0181] Use a Python program to extract the acceleration response time history curve at the equipment installation location from the Abaqus calculation result file;

[0182] Use a Python program to calculate the shock environment spectrum values at the equipment installation location, including spectral displacement, spectral velocity, and spectral acceleration.

[0183] Optionally, an optimization module for:

[0184] Build an Isight - Abaqus - Python co - simulation optimization model;

[0185] Set the functional modules required for co - simulation in the Isight platform, including the Abaqus module, Extract_py module, SRS_Calculate module, Result module, DOE module, and Optimization module.

[0186] Optionally, an analysis module for:

[0187] Determine the parameters to be optimized based on the material properties, structural cross - section dimensions, and shock absorber parameters, and use the parameters to be optimized as input factors;

[0188] Select the shock environment spectrum values at the equipment installation location as output parameters, where the shock environment spectrum values include spectral displacement, spectral velocity, and spectral acceleration;

[0189] Set the perturbation amount of the input factors;

[0190] In the DOE module of Isight, the optimal Latin hypercube design method is adopted to generate the experimental design space;

[0191] The Isight-Abaqus-Python co-simulation optimization model is used to calculate the influence rate of each input factor on the output parameter;

[0192] Sort according to the influence rate of the input factor on the output parameter, and determine the optimization parameters for the floating raft shock protection performance.

[0193] Optionally, a determination module is used for:

[0194] In the Optimization module of Isight, set the optimization algorithm to the NSGA-II genetic algorithm;

[0195] Set the population algebra, the number of iterations, the crossover probability, and the mutation probability;

[0196] Set the minimum of the shock environment spectrum value of the equipment installation position as the objective function, and the shock environment spectrum value includes spectrum displacement, spectrum velocity, and spectrum acceleration;

[0197] Set the constraint conditions, and set the constraint conditions according to the optional material properties, the structural cross-sectional dimensions, and the shock absorber parameter ranges;

[0198] Use the Isight-Abaqus-Python co-simulation optimization model to iteratively optimize the obtained Pareto solution set.

[0199] The embodiment of the present invention provides an optimization method and device for the floating raft shock protection performance under underwater explosion loads, including: generating a finite element model of the floating raft shock protection system according to each component in the floating raft shock protection system, the material properties of the components, and the geometric model element types; presetting the underwater explosion charge load according to the required shock factors, and calculating the floating raft shock environment based on the acoustic-solid coupling algorithm; based on the finite element model of the floating raft shock protection system and the floating raft shock environment, building a floating raft shock protection optimization model based on the Isight-Abaqus-Python co-simulation algorithm; identifying the influencing factors of the floating raft's shock protection performance on the equipment thereon under underwater explosion loads based on the built floating raft shock protection optimization model, and obtaining the optimization parameters for the protection performance of the finite element model of the floating raft shock protection system; based on the optimization parameters for the protection performance of the finite element model of the floating raft shock protection system, iteratively calculate the optimal solution based on the NSGA-II genetic algorithm. The embodiments of the present application can effectively improve the shock protection performance of the floating raft on the equipment installed thereon under underwater explosion loads, and solve the problems of high cost and long cycle of underwater explosion tests, the complex structure of the floating raft shock protection system, and the difficulty in implementing direct analysis methods.

[0200] For the apparatus embodiments, since they are basically similar to the method embodiments, they are described relatively simply. For related parts, please refer to the description of the method embodiments.

[0201] Optionally, an embodiment of the present application further provides an electronic device, including: a processor, a memory, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, it implements each process of the above method embodiment and can achieve the same technical effect. To avoid repetition, it will not be elaborated here.

[0202] An embodiment of the present application further provides a computer-readable storage medium. A computer program is stored on the computer-readable storage medium. When the computer program is executed by the processor, it implements each process of the above method embodiment and can achieve the same technical effect. To avoid repetition, it will not be elaborated here. Among them, the computer-readable storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc, etc.

[0203] Figure 11 It is a block diagram of an electronic device 800 shown in the present application. For example, the electronic device 800 can be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0204] Referring to Figure 11 , the electronic device 800 may include one or more of the following components: a processing component 802, a memory 804, a power supply component 806, a multimedia component 808, an audio component 810, an input / output (I / O) interface 812, a sensor component 814, and a communication component 816.

[0205] The processing component 802 generally controls the overall operation of the electronic device 800, such as operations associated with display, telephone calls, data communication, camera operations, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the above method. In addition, the processing component 802 may include one or more modules to facilitate the interaction between the processing component 802 and other components. For example, the processing component 802 may include a multimedia module to facilitate the interaction between the multimedia component 808 and the processing component 802.

[0206] The memory 804 is configured to store various types of data to support the operation of the device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phone book data, messages, images, videos, and the like. The memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, a magnetic disk, or an optical disk.

[0207] The power supply component 806 provides power to various components of the electronic device 800. The power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 800.

[0208] The multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen can be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors can not only sense the boundaries of the touch or swipe actions but also detect the duration and pressure associated with the touch or swipe operations. In some embodiments, the multimedia component 808 includes a front camera and / or a rear camera. When the device 800 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera can receive external multimedia data. Each of the front camera and the rear camera can be a fixed optical lens system or have a focal length and optical zoom capabilities.

[0209] The audio component 810 is configured to output and / or input audio signals. For example, the audio component 810 includes a microphone (MIC) that is configured to receive external audio signals when the electronic device 800 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals can be further stored in the memory 804 or transmitted via the communication component 816. In some embodiments, the audio component 810 further includes a speaker for outputting audio signals.

[0210] The I / O interface 812 provides an interface between the processing component 802 and a peripheral interface module, which can be a keyboard, a click wheel, buttons, etc. These buttons can include, but are not limited to: a home button, a volume button, a power-on button, and a lock button.

[0211] The sensor assembly 814 includes one or more sensors for providing a status assessment of various aspects for the electronic device 800. For example, the sensor assembly 814 can detect the on / off state of the device 800, the relative positioning of components, such as the display and keypad of the electronic device 800. The sensor assembly 814 can also detect a change in the position of the electronic device 800 or a component of the electronic device 800, the presence or absence of user contact with the electronic device 800, the orientation or acceleration / deceleration of the electronic device 800, and a change in the temperature of the electronic device 800. The sensor assembly 814 can include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 814 can also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 can also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0212] The communication component 816 is configured to facilitate communication, either wired or wirelessly, between the electronic device 800 and other devices. The electronic device 800 can access a wireless network based on communication standards, such as WiFi, a carrier network (such as 2G, 3G, 4G, or 5G), or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast operation information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 further includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0213] In an exemplary embodiment, the electronic device 800 can be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components for performing the above method.

[0214] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions, such as the memory 804 including instructions, is also provided. The above instructions can be executed by the processor 820 of the electronic device 800 to complete the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0215] Figure 12FIG. 0 is a block diagram of a computer-readable storage medium 1900 shown in the present application. For example, the computer-readable storage medium 1900 may be provided as a server.

[0216] Referring to Figure 12 , the computer-readable storage medium 1900 includes a processing component 1922, which further includes one or more processors, and memory resources represented by a memory 1932 for storing instructions executable by the processing component 1922, such as application programs. The application programs stored in the memory 1932 may include one or more modules each corresponding to a set of instructions. In addition, the processing component 1922 is configured to execute instructions to perform the above-described method.

[0217] The computer-readable storage medium 1900 may further include a power component 1926 configured to perform power management of the computer-readable storage medium 1900, a wired or wireless network interface 1950 configured to connect the computer-readable storage medium 1900 to a network, and an input / output (I / O) interface 1958. The computer-readable storage medium 1900 may operate based on an operating system stored in the memory 1932, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM or the like.

[0218] It should be noted that in this document, the terms "include", "comprise" or any other variation thereof are intended to cover non-exclusive inclusion, such that a process, method, article or apparatus including a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or apparatus. Without further limitation, an element defined by the statement "including a..." does not exclude the presence of additional identical elements in the process, method, article or apparatus including the element.

[0219] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-described example methods can be implemented by means of software plus a necessary general hardware platform, and of course also by hardware, but in many cases the former is a better implementation. Based on such an understanding, the technical solution of the present application, in essence or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions for causing a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present application.

[0220] The embodiments of the present application have been described above in conjunction with the accompanying drawings. However, the present application is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present application, those of ordinary skill in the art can also make many forms without departing from the purpose of the present application and the scope protected by the claims, and all of them fall within the protection scope of the present application.

[0221] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in the embodiments of the present application can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0222] Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0223] In the embodiments provided by the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of the devices or units can be in an electrical, mechanical or other form.

[0224] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0225] In addition, in each embodiment of the present application, the functional units can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.

[0226] When the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art or a part of this technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical discs.

[0227] As described above, the above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should all be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

[0228] The above is the preferred implementation manner of the present invention. It should be noted that for those of ordinary skill in the art in this technical field, without departing from the principle of the present invention, several improvements and refinements can still be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A method for optimizing the impact protection performance of a floating raft under underwater explosion load, characterized in that: include: Generate a finite element model of the floating raft impact protection system according to various components, material properties of the components and geometric model unit types in the floating raft impact protection system; According to the required impact factor, the underwater explosive charge load is pre-set, and the impact environment of the floating raft is calculated based on the acoustic-solid coupling algorithm; According to the finite element model of the raft impact protection system and the raft impact environment, a raft impact protection optimization model is built based on the Isight-Abaqus-Python joint simulation algorithm; Based on the constructed raft impact protection optimization model, parameter sensitivity analysis is carried out to identify the factors affecting the impact protection performance of the equipment on the raft under the action of underwater explosion loads, and the protection performance optimization parameters of the finite element model of the raft impact protection system are obtained; According to the protection performance optimization parameters of the finite element model of the raft impact protection system, the optimal solution is iteratively calculated based on the NSGA-II genetic algorithm.

2. The method for optimizing the impact protection performance of a floating raft under underwater explosion load according to claim 1, characterized in that: The method of generating a finite element model of the floating raft impact protection system according to each component in the floating raft impact protection system, the material properties of the components and the type of geometric model unit comprises: Establish the geometric model of the raft impact protection system in ANSYS; Import the geometric model of the raft impact protection system into the Abaqus software and set the material properties of the geometric model of each component; Set the geometric model unit type for each component. Perform mesh division; Set the binding boundary conditions between the outer surface of the submersible compartment and the inner surface of the sea water area; A non-reflecting boundary condition is set on the outer surface of the sea water area to simulate an infinite sea area.

3. The method for optimizing the impact protection performance of a floating raft under underwater explosion load according to claim 1, characterized in that: The method of presetting the underwater explosive charge load according to the required impact factor and calculating the impact environment of the floating raft based on the acoustic-solid coupling algorithm includes: Setting underwater explosive charge load; Use Abaqus software to perform display dynamics analysis and calculate the acceleration response of the equipment installation location; Use Python program to extract the acceleration response time history curve of the equipment installation position from the Abaqus calculation result file; The Python program is used to calculate the shock environment spectrum values ​​of the equipment installation location, including spectrum displacement, spectrum velocity and spectrum acceleration.

4. The method for optimizing the impact protection performance of a floating raft under underwater explosion load according to claim 1, characterized in that: According to the finite element model of the floating raft impact protection system and the floating raft impact environment, based on the Isight-Abaqus-Python joint simulation algorithm, a floating raft impact protection optimization model is built, including: Build the Isight-Abaqus-Python joint simulation optimization model; The functional modules required for joint simulation are set in the Isight platform, including Abaqus module, Extract_py module, SRS_Calculate module, Result module, DOE module and Optimization module.

5. The method for optimizing the impact protection performance of a floating raft under underwater explosion load according to claim 1, characterized in that: Based on the constructed floating raft impact protection optimization model, parameter sensitivity analysis is performed to identify the factors affecting the impact protection performance of the floating raft on the equipment on it under the action of underwater explosion load, and the protection performance optimization parameters of the finite element model of the floating raft impact protection system are obtained, including: Determine the parameters to be optimized according to the material properties, the structural cross-section dimensions and the shock absorber parameters, and use the parameters to be optimized as input factors; Selecting the shock environment spectrum value of the equipment installation position as the output parameter, wherein the shock environment spectrum value includes spectrum displacement, spectrum velocity, and spectrum acceleration; Set the input factor disturbance amount; The optimal Latin hypercube design method is used in the DOE module of Isight to generate the experimental design space; The Isight-Abaqus-Python joint simulation optimization model is used to calculate the influence rate of each input factor on the output parameters; The impact rate of input factors on output parameters is ranked to determine the optimization parameters of the raft impact protection performance.

6. The method for optimizing the impact protection performance of a floating raft under underwater explosion load according to claim 1, characterized in that: The method of iteratively calculating the optimal solution based on the NSGA-II genetic algorithm according to the protection performance optimization parameters of the finite element model of the floating raft impact protection system includes: In the Optimization module of Isight, set the optimization algorithm to NSGA-II genetic algorithm; Set population generations, number of iterations, crossover probability, and mutation probability; Set the minimum value of the shock environment spectrum at the equipment installation location as the objective function. The shock environment spectrum value includes spectrum displacement, spectrum velocity, and spectrum acceleration. Set constraints based on optional material properties, structural section dimensions, and damper parameter ranges; The Pareto solution set obtained from iterative optimization analysis using the Isight-Abaqus-Python joint simulation optimization model.

7. A device for optimizing the impact protection performance of a floating raft under underwater explosion load, characterized in that: include: A generation module, used for generating a finite element model of the floating raft impact protection system according to various components, material properties of the components and geometric model unit types in the floating raft impact protection system; A calculation module is used to pre-set the underwater explosive charge load according to the required impact factor and calculate the impact environment of the floating raft based on the acoustic-solid coupling algorithm; An optimization module, used for building a raft impact protection optimization model based on the Isight-Abaqus-Python joint simulation algorithm according to the finite element model of the raft impact protection system and the raft impact environment; The analysis module is used to perform parameter sensitivity analysis based on the constructed raft impact protection optimization model, identify the factors affecting the impact protection performance of the equipment on the raft under the action of underwater explosion load, and obtain the protection performance optimization parameters of the finite element model of the raft impact protection system; The determination module is used to iteratively calculate the optimal solution based on the NSGA-II genetic algorithm according to the protection performance optimization parameters of the finite element model of the raft impact protection system.

8. The device for optimizing the impact protection performance of a floating raft under underwater explosion load according to claim 1, characterized in that: The generating module is used for: Establish the geometric model of the raft impact protection system in ANSYS; Import the geometric model of the raft impact protection system into the Abaqus software and set the material properties of the geometric model of each component; Set the geometric model unit type for each component. Perform mesh division; Set the binding boundary conditions between the outer surface of the submersible compartment and the inner surface of the sea water area; A non-reflecting boundary condition is set on the outer surface of the sea water area to simulate an infinite sea area.

9. An electronic device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program implements the method according to any one of claims 1 to 6 when executed by the processor.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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