Global optimization design method and device of closed-cell aluminum foam impact suppression structure and medium

Abstract

The embodiment of the application discloses a global optimization design method, device and medium for a closed-cell aluminum foam impact suppression structure; the method comprises the following steps: a single-wave model in a plastic shock wave theory is used to describe a dynamic crushing process model of the closed-cell aluminum foam structure under the action of a high-speed impact of a mass block; an evaluation index for evaluating a buffering effect is constructed according to impact parameters in the dynamic crushing process model; a target function is established based on the evaluation index and design parameters of the closed-cell aluminum foam impact suppression structure; a global optimization model of the closed-cell aluminum foam impact suppression structure is constructed according to the target function and constraint conditions of the design parameters; adaptive crossover probability and mutation probability are determined based on evolution generations and fitness values of individuals in a population; the global optimization model is solved by using a genetic algorithm improved by the adaptive crossover probability and the mutation probability, and optimal design parameters of the closed-cell aluminum foam impact suppression structure are obtained.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of material structure design technology, and in particular to a global optimization design method, device and medium for a closed-cell aluminum foam impact suppression structure. Background Technology

[0002] Currently, the methods for describing the macroscopic dynamic crushing process of foam metal structures are mainly divided into two types: the spring-mass model and the plastic shock wave model. Among them, the spring-mass model was developed earlier, but a large number of experiments have shown that the spring-mass model has low accuracy in predicting the dynamic mechanical behavior of foam metals.

[0003] Current design optimization work on impact suppression structures for exploding bolts mainly focuses on optimizing the types of materials used in these structures. Foamed metals, especially foamed aluminum, offer better buffering and energy absorption than other materials, making them more suitable for manufacturing impact suppression structures. However, there is currently no global optimization mathematical model for closed-cell foamed aluminum impact suppression structures that comprehensively considers various optimization objectives, nor is there any research on optimizing foamed metal materials according to the design requirements of impact suppression structures. Summary of the Invention

[0004] In view of this, embodiments of the present invention aim to provide a global optimization design method, apparatus and medium for closed-cell aluminum foam impact suppression structures; capable of global optimization design of closed-cell aluminum foam impact suppression structures to obtain the optimal buffer structure under constraints.

[0005] The technical solution of this invention is implemented as follows:

[0006] In a first aspect, embodiments of the present invention provide a global optimization design method for a closed-cell aluminum foam impact suppression structure, the method comprising:

[0007] A model of the dynamic crushing process of closed-cell foam metal structure under high-speed impact of mass block is described using the single-wave model in plastic shock wave theory.

[0008] Evaluation indicators for assessing buffering effectiveness are constructed based on the impact parameters in the dynamic crushing process model.

[0009] An objective function is established based on the evaluation index and the design parameters of the closed-cell aluminum foam impact suppression structure.

[0010] A global optimization model for the closed-cell aluminum foam impact suppression structure is constructed based on the objective function and the constraints of the design parameters.

[0011] The adaptive crossover probability and mutation probability are determined based on the number of generations and the fitness values ​​of individuals in the population;

[0012] The global optimization model is solved using a genetic algorithm improved by the adaptive crossover probability and mutation probability to obtain the optimal design parameters for the closed-cell aluminum foam impact suppression structure.

[0013] Secondly, embodiments of the present invention provide a global optimization design device for a closed-cell aluminum foam impact suppression structure. The device includes: a model description section, a first construction section, an objective function establishment section, a second construction section, a determination section, and an optimal parameter acquisition section; wherein...

[0014] The model description section is configured to use a single-wave model in plastic shock wave theory to describe the dynamic crushing process of a closed-cell foam metal structure under high-speed impact from a mass block.

[0015] The first construction part is configured to construct evaluation indicators for evaluating the buffering effect based on the impact parameters in the dynamic crushing process model;

[0016] The objective function establishment section is configured to establish an objective function based on the evaluation index and the design parameters of the closed-cell aluminum foam impact suppression structure.

[0017] The second construction part is configured to construct a global optimization model of the closed-cell aluminum foam impact suppression structure based on the objective function and the constraints of the design parameters;

[0018] The determining part is configured to determine the adaptive crossover probability and mutation probability based on the number of generations and the fitness values ​​of individuals in the population;

[0019] The optimal parameter acquisition section is configured to solve the global optimization model using a genetic algorithm improved by the adaptive crossover probability and mutation probability to obtain the optimal design parameters of the closed-cell aluminum foam impact suppression structure.

[0020] Thirdly, embodiments of the present invention provide a computing device, the computing device comprising: a communication interface, a memory, and a processor; the various components are coupled together via a bus system; wherein...

[0021] The communication interface is used for receiving and sending signals during the process of sending and receiving information with other external network elements;

[0022] The memory is used to store computer programs that can run on the processor;

[0023] The processor is configured to, when running the computer program, execute the steps of the global optimization design method for the closed-cell aluminum foam impact suppression structure described in the first aspect.

[0024] Fourthly, embodiments of the present invention provide a computer storage medium storing a global optimization design program for a closed-cell aluminum foam impact suppression structure. When the global optimization design program for the closed-cell aluminum foam impact suppression structure is executed by at least one processor, it implements the steps of the global optimization design method for the closed-cell aluminum foam impact suppression structure described in the first aspect.

[0025] This invention provides a global optimization design method, device, and medium for closed-cell aluminum foam impact suppression structures. Based on plastic shock wave theory, a dynamic crushing theoretical model of closed-cell aluminum foam is established to parameterize the foam, providing the relationship between key impact parameters and the design parameters of the closed-cell aluminum foam itself. This allows for an accurate description of the deformation of the foam metal under high-speed impact loads and the stress-strain state within the structure. Then, based on the number of generations and the fitness values ​​of individuals in the population, adaptive crossover and mutation probabilities are determined to improve the genetic algorithm. The improved genetic algorithm is then used to globally optimize the closed-cell aluminum foam impact suppression structure, obtaining the optimal buffer structure under constraints, thereby accelerating the convergence speed of the genetic algorithm towards the optimal solution. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of a global optimization design method for a closed-cell aluminum foam impact suppression structure provided in an embodiment of the present invention;

[0027] Figure 2 This is a schematic diagram of the dynamic crushing process of the foam metal structure provided in an embodiment of the present invention;

[0028] Figure 3 A schematic diagram showing the changes in total energy absorption, specific energy absorption, stroke efficiency, and peak impact force as a function of the relative density of closed-cell aluminum foam, provided in an embodiment of the present invention.

[0029] Figure 4 This is a schematic diagram of the solution process of the genetic algorithm improved by adaptive crossover probability and mutation probability provided in the embodiments of the present invention;

[0030] Figure 5 A schematic diagram illustrating the results of optimal individual fitness, average population fitness, and number of iteration steps provided in an embodiment of the present invention;

[0031] Figure 6 A schematic diagram of the global optimization design device for the closed-cell aluminum foam impact suppression structure provided in this embodiment of the invention;

[0032] Figure 7 This is a schematic diagram of the hardware structure of a computing device provided in an embodiment of the present invention. Detailed Implementation

[0033] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0034] See Figure 1 This illustrates a global optimization design method for a closed-cell aluminum foam impact suppression structure provided by an embodiment of the present invention. The method may include:

[0035] S101: A model describing the dynamic crushing process of a closed-cell foam metal structure under high-speed impact from a mass block using a single-wave model in plastic shock wave theory.

[0036] S102: Construct evaluation indicators for evaluating buffering effectiveness based on the impact parameters in the dynamic crushing process model;

[0037] S103: Establish an objective function based on the evaluation index and the design parameters of the closed-cell aluminum foam impact suppression structure;

[0038] S104: Construct a global optimization model for the closed-cell aluminum foam impact suppression structure based on the objective function and the constraints of the design parameters;

[0039] S105: Determine the adaptive crossover probability and mutation probability based on the number of generations and the fitness values ​​of individuals in the population;

[0040] S106: Solve the global optimization model using a genetic algorithm improved by the adaptive crossover probability and mutation probability to obtain the optimal design parameters of the closed-cell aluminum foam impact suppression structure.

[0041] pass Figure 1 The technical solution shown establishes a dynamic crushing theoretical model of closed-cell aluminum foam based on the plastic shock wave theory to achieve parameterization of closed-cell aluminum foam. It gives the relationship between the main impact parameters and the design parameters of closed-cell aluminum foam itself, so as to accurately describe the deformation state of the foam metal under high-speed impact load and the stress-strain state inside the structure. Then, based on the evolutionary generation and the fitness value of individuals in the population, the adaptive crossover probability and mutation probability are determined to improve the genetic algorithm. The improved genetic algorithm is then used to perform global optimization design of the impact suppression structure of closed-cell aluminum foam, obtaining the optimal buffer structure under constraints, thereby accelerating the convergence speed of the genetic algorithm to the optimal solution.

[0042] for Figure 1 The technical solution shown, in some possible implementations, includes a model that uses the single-wave model in plastic shock wave theory to describe the dynamic crushing process of a closed-cell foam metal structure under high-speed impact from a mass block, comprising:

[0043] Based on the theory of plastic shock waves, a single-wave model is used to describe the dynamic crushing process of foam metal structures.

[0044] Select at least one impact parameter from the dynamic crushing process model;

[0045] Establish the relationship between each of the impact parameters and impact time.

[0046] In some examples of the above implementation, the impact parameter includes: the waveback stress σ of the waveback portion in the closed-cell foam metal structure. B (t), wave back strain ε B (t), the velocity of the particle after the wave v B (t) and the wavefront position φ(t), where the wavefront particle velocity v B (t) and the velocity v(t) of the mass block; correspondingly, establishing the relationship between each impact parameter and the impact time includes:

[0047] Based on the constitutive equation, the first expression for the waveback stress σ is constructed. B (t)=σ(ε B (t));

[0048] Based on the conservation of mass and momentum across the wavefront, the first expressions for the velocity of the mass block are obtained respectively. And the second expression for post-wave stress

[0049] According to the first expression of the wave-after stress σ B (t)=σ(ε B (t) and the first expression for the velocity of the mass block. And the second expression for post-wave stress The third expression for obtaining the wave back stress Regarding the speed of shock waves The first expression And the second expression for the velocity of the mass block.

[0050] The initial post-wave stress σ0 and initial post-wave strain ε0 are obtained based on the initial impact velocity;

[0051] Based on the initial post-wave stress σ0 and initial post-wave strain ε0, the post-wave strain ε is obtained. B (t), the wave back stress σ B The relationship between the wavefront position φ(t) and the velocity v(t) of the mass block and the impact time t.

[0052] For the above example, preferably, the step of obtaining the wave back strain ε based on the initial wave back stress σ0 and the initial wave back strain ε0 is... B (t), the wave back stress σB The relationships between the wavefront position φ(t) and the mass velocity v(t) as a function of impact time t include:

[0053] The back strain ε is obtained based on the initial back stress σ0 and the initial back strain ε0. B (t) is an implicit expression for the impact time t, expressed by the post-wave strain ε. B (t) Perform a second-order Taylor expansion to obtain the waveback strain ε. B (t) Explicit asymptotic solution with respect to impact time t;

[0054] According to the wave back strain ε B The explicit asymptotic solution of (t) with respect to the impact time t yields the post-wave strain ε. B (t), the wave back stress σ B The relationship between the wavefront position φ(t) and the velocity v(t) of the mass block and the impact time t.

[0055] For the above example, preferably, the step of obtaining the wave back strain ε based on the initial wave back stress σ0 and the initial wave back strain ε0 is... B (t), the wave back stress σ B The relationships between the wavefront position φ(t) and the mass velocity v(t) as a function of impact time t include:

[0056] The waveback strain ε is obtained from the DR-PH model through the conservation of mass and momentum across the wavefront. B (t), the wave back stress σ B Implicit solutions for the changes in wavefront position φ(t) and mass velocity v(t) with impact time t;

[0057] Substitute the parameter fitting model of the DR-PH model into the wavelet strain ε in sequence. B (t), the wave back stress σ B The implicit solutions for the changes in wavefront position φ(t) and mass velocity v(t) with impact time t are used to obtain the post-wave strain ε. B (t), the wave back stress σ B The relationship between the wavefront position φ(t) and the velocity v(t) of the mass block and the impact time t.

[0058] For the above implementation methods and examples, in detail, taking closed-cell aluminum foam as an incrementally hardening material as an example, its dynamic crushing model under the high-speed impact of a mass block is as follows: Figure 2 As shown, see Figure 2In the upper figure, a mass block of mass M impacts a foam metal structure fixed at one end with an initial velocity v0. According to the high-speed impact requirement of the Dynamic-Rigid-Plastic Hardening (DR-PH) model, v0 ≥ 50 m / s. The original length of the foam metal structure model is L0, the cross-sectional area is A0, and the density of the foam metal material is ρρ0, where ρ is the relative density of the foam metal, i.e., the ratio of the nominal mass-volume ratio of the material to the density of the matrix material, and ρ0 is the density of the matrix material. Treating the foam metal as a rate-independent rigid-plastic hardening material, its constitutive equation can be expressed as σ = σ(ε), where stress σ and strain ε are positive in the compression direction, the unloading process is assumed to be rigid, and X is the Lagrangian coordinate in the impact direction. Under dynamic impact, the foam metal material will undergo local deformation, and the crushing zone propagates from the impact end to the support end.

[0059] Based on the theory of plastic shock waves, this embodiment of the invention uses a single-wave model to describe the dynamic crushing process of foamed metal structures. (Continue to see...) Figure 2 In the figure below, the model contains a plastic shock wave front propagating from the impact end to the support end, denoted by φ in Lagrange coordinates. Assuming the cross-section of the foam metal structure remains planar throughout deformation and that only uniformly distributed axial stress exists along the cross-section, then the position of the wave front at time t is φ(t), and the shock wave velocity is... See also Figure 2 In the figure below, the wavefront of the shock wave divides the foam metal structure into two parts. The part of the structure in front of the wavefront, which has not yet been crushed and deformed, is defined as the wavefront, and its relevant physical quantities are represented by the subscript A. The part of the structure behind the wavefront has been compacted and is defined as the waveback, and its relevant physical quantities are represented by the subscript B. The mass block M and the waveback part of the foam metal model move towards the support end simultaneously at the same velocity, denoted as v(t). There are stress and strain discontinuities on the shock wave front. The stress, strain, and particle velocity values ​​of the wavefront part at time t are set as follows:

[0060]

[0061] in, This represents the dynamic initial crushing stress of the foam metal in the DR-PH model.

[0062] The stress, strain, and particle velocity values ​​in the waveback region at time t are shown below:

[0063] {σ B (t),ε B (t),v B (t)}={σ B (t),ε B (t),v(t)}

[0064] For the wave-back portion mentioned above, combining the aforementioned constitutive equations, the first expression for the wave-back stress can be obtained as σ. B (t)=σ(ε B (t)).

[0065] According to the mass conservation equation of the transwavefront and the momentum conservation equation of the transwavefront Combining the stress, strain, and particle velocity values ​​of the wavefront and waveback portions, we can obtain the first expression for the mass block's velocity and the second expression for the waveback stress. Combining these results with the expression for waveback stress yields the third expression for waveback stress and the expression for the shock wave velocity. The first expression and the second expression for the velocity of the mass block; substituting the initial impact velocity v0 into the post-wave stress expression yields... This allows us to obtain the initial post-wave strain ε0 and the initial post-wave stress σ0.

[0066] Based on the above, by differentiating the velocity expression with respect to the impact time t, we can obtain... in, according to And about the shock wave velocity The first expression yields the expression for the wavefront position as follows: Integrating both sides of the wavefront position expression with respect to t, we get... The expression for the wavefront position can be derived by integrating both sides of the expression with respect to t. in, It is worth noting that the formula derived above gives the wave back strain ε B (t) is an implicit expression for the impact time t.

[0067] After obtaining the explicit solution to this implicit expression, the third expression for the post-wave stress, the first expression for the shock wave velocity, and the second expression for the mass block's motion velocity can be substituted into the implicit expression to obtain the post-wave strain ε. B (t), the wave back stress σ B The relationship between the wavefront position φ(t) and the velocity v(t) of the mass block and the impact time t.

[0068] Specifically, ε B (t) Perform a second-order Taylor expansion, and define its explicit asymptotic solution form as follows:

[0069] ε B (t)=ε0+ε1τ+ε2τ 2 +…,τ=tT

[0070] From the above explicit asymptotic solution, we can obtain:

[0071]

[0072] According to the DR-PH constitutive equation of foamed metal materials, we can obtain... D represents the dynamic strain hardening parameter (MPa); This represents the dynamic initial crushing stress (MPa).

[0073] By combining the aforementioned initial impact velocity, the initial post-wave stress σ0 can be obtained. And further obtain:

[0074]

[0075]

[0076] Based on the ε0, ε1, and ε2 obtained above, ε can be obtained. B The explicit asymptotic solution of (t) is then obtained, thereby yielding the waveback stress σ. B The relationship between the wavefront position φ(t) and the velocity v(t) of the mass block and the impact time t.

[0077] In addition, it should be noted that, besides obtaining ε B After obtaining the asymptotic solution of (t), the wave back stress σ is then obtained. B In addition to the relationships between the wavefront position φ(t) and the mass mass velocity v(t) as a function of impact time t, in specific implementations of this invention, the DR-PH model can also be directly substituted into the mass conservation equation across the wavefront. and the momentum conservation equation of the transwavefront In the middle, the wave back stress σ is obtained. B (t), wave back strain ε B The implicit solutions for the changes in wavefront position φ(t) and mass block velocity v(t) with impact time t are obtained. Then, by substituting the parameter fitting model of the DR-PH model, the relationship between the changes in each impact parameter and impact time during the dynamic crushing of the closed-cell aluminum foam structure can be obtained. Specifically, it is as follows:

[0078]

[0079]

[0080]

[0081] During the impact, the mass block M and the wave-rear portion of the foam metal structure move towards the support end with the same velocity v(t). According to Newton's laws of motion, we can obtain... A0 represents the cross-sectional area; this expression provides an implicit solution to the relationship between impact velocity and impact time. When t = 0, v(0) = v0, φ(0) = 0, according to the formula... The initial post-wave strain ε0 and initial post-wave stress σ0 can be obtained. By combining the relationships between the above impact parameters and impact time, and substituting the corresponding initial conditions, the numerical solution of v(t) is obtained using the fourth-order Runge-Kutta method, thus yielding the post-wave stress σ0. B The relationship between the wavefront position φ(t) and the velocity v(t) of the mass block and the impact time t.

[0082] for Figure 1 In some possible implementations of the technical solution shown, the step of constructing evaluation indicators for assessing buffering effectiveness based on the impact parameters in the dynamic crushing process model includes:

[0083] Based on the dynamic crushing process model of the foam metal structure, the total energy absorption, specific energy absorption, stroke efficiency, and peak impact force are selected as the evaluation indicators.

[0084] For the above implementation method, in detail, the total energy absorbed, specific energy absorbed, stroke efficiency, and peak impact force are defined as follows:

[0085] 1) Total energy absorbed is defined as E d =∫F(s)ds;

[0086] Where s represents the deformation of the impact end during the impact process (unit: mm); F(s) represents the impact force borne by the impact end during the impact process (unit: N);

[0087] According to the above definition, the total absorbed energy E d It can be represented as Substituting the aforementioned impact parameters, we have

[0088] According to the principle of energy conservation, the total absorbed energy E can be obtained by calculating the difference in kinetic energy of the entire system before and after the impact process. d The mathematical expression is as follows:

[0089]

[0090] Where, v(t) end ) represents the impact velocity of mass block M at the end of the impact process.

[0091] 2) Specific Energy Absorption (SEA) is used to represent the impact energy absorbed per unit mass of an impact-damping structure during the entire impact process. According to the definition of specific energy absorption, it can be known that...

[0092] 3) Stroke efficiency SE: Based on the one-dimensional shock wave model of the dynamic compression process of foamed metal, the effective compression stroke is the distance traveled by the mass block M when the plastic shock wave propagates to the fixed end in the impact suppression structure. Therefore, the stroke efficiency SE is... The impact velocity v(t) is an implicit function of time, so the numerical solution of the stroke efficiency SE can be obtained by using the fourth-order Runge-Kutta method.

[0093] 4) Peak impact force P max Based on the dynamic crushing model of closed-cell aluminum foam, taking the undeformed region as the research object during the impact process, the force P at the support end can be obtained from Newton's third law as follows: Clearly, during the impact crushing process of the constant-density closed-cell aluminum foam model, the force at the supporting end remains unchanged. Therefore, the mathematical expression for the peak impact force can be obtained as follows:

[0094] for Figure 1 In some possible implementations of the technical solution shown, an objective function is established based on the evaluation index and the design parameters of the closed-cell aluminum foam impact suppression structure.

[0095] Based on the relationship between the evaluation indicators and the design parameters, with the optimization objectives of maximizing total energy absorption, maximizing specific energy absorption, maximizing stroke efficiency, and minimizing peak impact force, corresponding initial objective functions are designed for each evaluation indicator.

[0096] The initial objective function is normalized according to the weights corresponding to each evaluation index to obtain a single objective function.

[0097] In some examples of the above implementation, the step of constructing a global optimization model for the closed-cell aluminum foam impact suppression structure based on the objective function and the constraints of the design parameters includes:

[0098] The global optimization model is constructed based on the design parameters, corresponding constraints, and the single objective function.

[0099] Regarding the above implementation methods and examples, it should be noted that the design parameters can be the relative density ρ, the impact suppression structure length L0, and the cross-sectional radius r0. The relationship between the evaluation indicators and the design parameters can be obtained through simulation using mathematical analysis software. Specifically, the simulation is based on a one-dimensional plastic shock wave theoretical model of the dynamic crushing process of closed-cell aluminum foam structures. The specific design parameters of the closed-cell aluminum foam impact suppression structure are as follows:

[0100] The closed-cell aluminum foam impact suppression structure is assumed to be a cylindrical structure with a length envelope of L0 = 60-75 mm and a cross-sectional radius envelope of r0 = 20-30 mm. For practical processing considerations, the variation step for both length and cross-sectional radius is taken as 0.01 mm. The matrix material of the closed-cell aluminum foam is assumed to be pure aluminum, ignoring additives, with a matrix material density of ρ0 = 2700 kg / m³. The relative density range of the closed-cell aluminum foam is ρ = 0.1-0.4, with a variation step of 0.001. Based on the actual impact velocity and structural mass during the operation of the explosive bolt, the mass of the mass block is assumed to be M = 0.45 kg, the initial impact velocity is v0 = 52 m / s, and the simulation time step for the dynamic crushing process is 0.001 ms. The simulation ends when the plastic shock wave propagation is complete, the wavefront position φ(t) = L0, or the mass block stops moving and v(t) = 0.

[0101] Based on the above simulation, the effect of relative density ρ on the performance of the impact suppression structure is as follows: When the length L0 and cross-sectional radius r0 of the impact suppression structure are determined, and only the relative density ρ of the closed-cell aluminum foam is changed, the design parameters are set as shown in Table 1 below:

[0102] Table 1

[0103] <![CDATA[Length L0 / mm]]> <![CDATA[Cross-sectional radius r0 / mm]]> Relative density ρ range 70 30 0.1-0.4

[0104] Based on the design parameters shown in Table 1 above, the curves showing the variation of total energy absorption, specific energy absorption, stroke efficiency, and peak impact force with the relative density of closed-cell aluminum foam are as follows: Figure 3 As shown in (a), (b), (c), and (d).

[0105] Similarly, the optimization objective function can be defined based on the relationship between the evaluation index and other design parameters. In this embodiment of the invention, the objective function can be represented by four optimization objectives: maximizing total energy absorption, maximizing specific energy absorption, maximizing stroke efficiency, and minimizing peak impact force. To ensure that the other three optimization objectives are also maximized, the negative of the peak impact force function can be used as the corresponding optimization objective function. Based on this, the four optimization objective functions are defined as follows:

[0106] maxf1(ρ,L0,r0)=maxE d (ρ,L0,r0)

[0107] maxf2(ρ,L0,r0)=maxSEA(ρ,L0,r0),

[0108] maxf3(ρ,L0,r0)=maxSE(ρ,L0,r0),

[0109] maxf4(ρ,L0,r0)=-minP max (ρ,L0,r0).

[0110] For the four objective functions mentioned above, taking the aforementioned optimization objective as an example, and combining the selection of design parameters and their constraints, the corresponding global optimization mathematical model for the closed-cell aluminum foam impact suppression structure is obtained as follows:

[0111]

[0112] It should be noted that, for the four objective functions mentioned above, this embodiment of the invention can transform the multiple objective functions in the above mathematical model into a single objective function for optimization based on the weights of each objective function. Specifically, since the units of each objective function are different, direct conversion is not possible. Therefore, it is necessary to normalize the four evaluation indicators of the impact suppression structure: total energy absorption, specific energy absorption, stroke efficiency, and peak impact force, that is, to unify the dimensions of each objective function. During normalization, the maximum and minimum values ​​of each objective function are first obtained, and then the objective function values ​​from the optimization process are substituted into the following formula:

[0113]

[0114] Among them, f i (x) represents the value of the i-th objective function; minf i (x) represents the minimum value of the i-th objective function; maxf i (x) represents the maximum value of the i-th objective function. The objective functions are then transformed into values ​​between 0 and 1 as described above, as follows:

[0115] 1) Total energy absorbed E d Based on the variation of the total energy absorption of the closed-cell aluminum foam impact suppression structure with the length, cross-sectional radius, and relative density of the closed-cell aluminum foam, and considering the constraints of the three design variables, the total energy absorption function is normalized. The normalized function is:

[0116] 2) Specific Energy Absorption (SEA): Based on the variation of the specific energy absorption of the closed-cell aluminum foam impact suppression structure with the length, cross-sectional radius, and relative density of the closed-cell aluminum foam, and considering the constraints of the three design variables, the SEA function is normalized. The normalized function is:

[0117] 3) Stroke efficiency SE: Based on the variation of stroke efficiency of the closed-cell aluminum foam impact suppression structure with the length, cross-sectional radius, and relative density of the closed-cell aluminum foam, and considering the constraints of the three design variables, the stroke efficiency function is normalized. The normalized function is:

[0118] 4) Peak impact force P maxBased on the variation of the peak impact force of the closed-cell aluminum foam impact suppression structure with the length, cross-sectional radius, and relative density of the closed-cell aluminum foam, and considering the constraints of the three design variables, the mass function is normalized. The normalized function is:

[0119] To optimize the impact suppression structure of closed-cell aluminum foam, four objective functions were considered. The total energy absorption and peak impact force were deemed equally important, and both were slightly more important than specific energy absorption. Specific stroke efficiency was significantly more important, and specific energy absorption was slightly more important than stroke efficiency. Based on this weighting principle, the weights of the objective functions were calculated as follows: the relative weight coefficient for the total energy absorption function was w1 = 0.3908; the relative weight coefficient for the specific energy absorption function was w2 = 0.1509; the relative weight coefficient for the stroke efficiency function was w3 = 0.0675; and the relative weight coefficient for the peak impact force function was w4 = 0.3908.

[0120] After the relative weighting coefficients are calculated, the total energy absorption function, specific energy absorption function, stroke efficiency function, and peak impact force function are transformed into a single objective function for subsequent optimization. The expression for the single objective function is:

[0121] maxf(ρ,L0,r0)=0.3908f1 * +0.1509f2 * +0.0675f3 * +0.3908f4 * .

[0122] for Figure 1 The technical solutions shown, in some possible implementations, determine the adaptive crossover probability and mutation probability based on the number of generations and the fitness values ​​of individuals in the population, including:

[0123] Calculate the first operator p based on the evolutionary algebra according to the following formula. c1 and the second operator p based on the fitness value of individuals in the population c2 ;

[0124]

[0125]

[0126] The adaptive crossover probability is obtained based on the first operator and the second operator, using the following formula:

[0127] p c =p c1 p c2 ;

[0128] Calculate the third operator p based on the evolutionary algebra according to the following formula. m1and the fourth operator p based on the fitness value of individuals in the population m2 ;

[0129]

[0130]

[0131] The adaptive mutation probability is obtained based on the third operator and the fourth operator, using the following formula:

[0132] p m =p m1 p m2 .

[0133] Regarding the above implementation, it's important to note that the crossover and mutation steps are crucial for the genetic algorithm to find the global optimum. Crossover is the main step in exploring the unknown space within the constraints of the independent variables, while mutation ensures population diversity and guarantees the genetic algorithm's global search capability. Therefore, the values ​​of crossover and mutation probabilities significantly impact the optimization results. Generally, a higher crossover probability and a lower mutation probability are preferable. However, on the one hand, for individuals with relatively high fitness in the population, crossover and mutation are likely to decrease their fitness; on the other hand, at lower generations, a lower mutation probability is detrimental to maintaining population diversity, while at higher generations, the average fitness of the population is higher, requiring an increased crossover probability to accelerate the convergence speed of the genetic algorithm towards the optimal solution.

[0134] Therefore, in the above implementation, for the crossover probability, the first operator p based on the evolutionary generation... c1 and the second operator p based on the fitness value of individuals in the population c2 The following are examples:

[0135]

[0136]

[0137] Among them, maxp c ,minp c Let represent the maximum and minimum crossover probabilities, respectively; T represents the final generation; T0 represents the initial generation, and T0 = 1; t represents the current generation; k1 and k2 represent operator constants, and k1 ∈ (0, 1], k2 ∈ [1, ∞); fit max This represents the maximum fitness of an individual in the current population; fit min This represents the minimum fitness value of an individual in the current population; fit avg This represents the average fitness of individuals in the current population.

[0138] Considering that T0 is much smaller than T, therefore p c1 It can be simplified to:

[0139] The mutation probability also consists of two parts, based on the third operator p of the evolutionary generations. m1 and the fourth operator p based on the fitness value of individuals in the population m2 They are respectively:

[0140]

[0141]

[0142] Among them, maxp m ,minp m k1 and k2 represent the maximum and minimum mutation probabilities, respectively; k3 and k4 represent the internal constants of the operator, and k3∈(0,1], k4∈[1,∞);

[0143] Considering that T0 is much smaller than T, therefore p m1 It can be simplified to

[0144] Clearly, as the number of generations increases, p c1 continuously increasing, p m1 By continuously decreasing p, the convergence speed towards the optimal solution is accelerated when the population is relatively good in the later stages of the genetic algorithm, while the probability of individual gene mutations leading to poor fitness is reduced. Simultaneously, for individuals with relatively high fitness in the population, p... c2 p m2 The size of the population decreases significantly, which helps to retain the best individuals in the population and speeds up the convergence. However, even the best individuals in the population have a certain probability of crossover and mutation, which helps to maintain the diversity of the population and avoid getting trapped in local optima.

[0145] Based on the aforementioned implementation method, in some examples, the global optimization model is solved using a genetic algorithm improved by the adaptive crossover probability and mutation probability, as detailed below. Figure 4 As shown, in Figure 4 First, a population is established and initialized according to the design parameters. Then, the fitness value of individuals in the population is calculated according to the objective function, and the optimal individual is selected. If the optimal individual meets the termination criterion, it is taken as the optimal solution and determined as the optimal design parameters. If the termination criterion is not met, the individuals in the population are subjected to natural selection, and then crossover and mutation are performed in sequence according to the aforementioned adaptive crossover probability and mutation probability to generate an updated population. The fitness value is then calculated again until the optimal solution is obtained, thus obtaining the optimal design parameters.

[0146] Regarding the aforementioned technical solutions, their implementation methods, and examples, the embodiments of the present invention verify their technical effects through the following simulation experiments, under the following simulation experimental conditions:

[0147] The parameter settings for the improved genetic algorithm are as follows:

[0148] P = 50

[0149] T=300

[0150] max p c =0.9

[0151] min p c =0.5

[0152] max p m =0.08

[0153] min p m =0.04

[0154] k1 = 0.1

[0155] k2 = k4 = 1.1

[0156] k3 = 0.8

[0157] Based on the actual impact velocity and structural mass during the operation of the explosive bolt, assuming the mass of the mass block M = 0.45 kg and the initial impact velocity v0 = 52 m / s, the optimal individual fitness, average population fitness, and number of iterations can be obtained by programming mathematical analysis software, as shown below. Figure 5 (a) and Figure 5 As shown in (b), the calculation process converges.

[0158] Furthermore, the optimal solution combination obtained by implementing the scheme proposed in the embodiments of the present invention is as follows: structural length L0 = 75 mm; cross-sectional radius r0 = 30 mm; relative density of closed-cell aluminum foam ρ = 0.182; optimal individual fitness 0.7705; and average fitness of the population at the end of evolution 0.74. Substituting these values ​​into the dynamic crushing model of closed-cell aluminum foam, the total energy absorbed by the structure is E. d =536.44J, specific energy absorption is SEA=5147.9J / kg, stroke efficiency is SE=0.3114, peak impact force is P max =19.78kN.

[0159] Comparing the above optimization results, it can be seen that when considering the total energy absorption, specific energy absorption, stroke efficiency, and peak impact force function, the improved genetic algorithm improves the total energy absorption performance by 2.67%, decreases the specific energy absorption performance by 1.48%, decreases the stroke efficiency performance by 3.5%, improves the peak impact force performance by 0.8%, and improves the population average performance by 7.9% compared with the classic genetic algorithm.

[0160] Based on the same inventive concept as the aforementioned technical solution, see [link to inventive concept]. Figure 6 This illustration shows a global optimization design device 60 for a closed-cell aluminum foam impact suppression structure provided by an embodiment of the present invention. The device 60 includes: a model description part 601, a first construction part 602, an objective function establishment part 603, a second construction part 604, a determination part 605, and an optimal parameter acquisition part 606; wherein,

[0161] The model description section 601 is configured to use a single-wave model in plastic shock wave theory to describe the dynamic crushing process of a closed-cell foam metal structure under high-speed impact of a mass block.

[0162] The first construction part 602 is configured to construct evaluation indicators for evaluating the buffering effect based on the impact parameters in the dynamic crushing process model;

[0163] The objective function establishment part 603 is configured to establish an objective function based on the evaluation index and the design parameters of the closed-cell aluminum foam impact suppression structure.

[0164] The second construction part 604 is configured to construct a global optimization model of the closed-cell aluminum foam impact suppression structure based on the objective function and the constraints of the design parameters;

[0165] The determining part 605 is configured to determine the adaptive crossover probability and mutation probability based on the number of generations and the fitness values ​​of individuals in the population;

[0166] The optimal parameter acquisition section 606 is configured to solve the global optimization model using a genetic algorithm improved by the adaptive crossover probability and mutation probability to obtain the optimal design parameters of the closed-cell aluminum foam impact suppression structure.

[0167] It should be noted that for the specific implementation of the functions configured in each "part" of the above-mentioned device, please refer to the aforementioned... Figure 1 The implementation methods and examples of the corresponding steps in the global optimization design method of the closed-cell aluminum foam impact suppression structure shown are not repeated here.

[0168] Understandably, in this embodiment, "part" can be a part of a circuit, a part of a processor, a part of a program or software, etc., or it can be a unit, a module, or a non-modular one.

[0169] Furthermore, in this embodiment, the components can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional module.

[0170] If the integrated unit is implemented as a software functional module and not sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this embodiment, in essence, or the part that contributes to the prior art, or all or part of the 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 to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the method described in this embodiment. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0171] Therefore, this embodiment provides a computer storage medium storing a global optimization design program for a closed-cell aluminum foam impact suppression structure. When the global optimization design program for the closed-cell aluminum foam impact suppression structure is executed by at least one processor, it implements the steps of the global optimization design method for the closed-cell aluminum foam impact suppression structure described in the above technical solution.

[0172] Based on the globally optimized design device 60 for the aforementioned closed-cell aluminum foam impact suppression structure and the computer storage medium, see [link to relevant documentation]. Figure 7This illustration shows the specific hardware structure of a computing device 70, which is a globally optimized design device 60 capable of implementing the aforementioned closed-cell aluminum foam impact suppression structure, according to an embodiment of the present invention. The computing device 70 can be a wireless device, a mobile or cellular phone (including so-called smartphones), a personal digital assistant (PDA), a video game console (including a video display, a mobile video game device, a mobile video conferencing unit), a laptop computer, a desktop computer, a set-top box, a tablet computing device, an e-book reader, a fixed or mobile media player, etc. The computing device 70 includes: a communication interface 701, a memory 702, and a processor 703; the various components are coupled together through a bus system 704. It is understood that the bus system 704 is used to realize the connection and communication between these components. In addition to a data bus, the bus system 704 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 7 The general designated all buses as Bus System 704. Among them,

[0173] The communication interface 701 is used for receiving and sending signals during the process of sending and receiving information with other external network elements;

[0174] The memory 702 is used to store computer programs that can run on the processor 703;

[0175] The processor 703 is used to execute the steps of the global optimization design method for the closed-cell aluminum foam impact suppression structure described in the above technical solution when running the computer program.

[0176] It is understood that the memory 702 in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memory 702 of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0177] The processor 703 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of the processor 703 or by instructions in software form. The processor 703 can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory 702, and the processor 703 reads the information in memory 702 and, in conjunction with its hardware, completes the steps of the above method.

[0178] It is understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit can be implemented in 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), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described herein, or combinations thereof.

[0179] For software implementation, the techniques described herein can be achieved through modules (e.g., procedures, functions, etc.) that perform the functions described herein. The software code can be stored in memory and executed by a processor. The memory can be implemented within the processor or externally.

[0180] It is understood that the exemplary technical solutions of the global optimization design device 60 and computing device 70 for the aforementioned closed-cell aluminum foam impact suppression structure belong to the same concept as the technical solutions of the aforementioned global optimization design method for the closed-cell aluminum foam impact suppression structure. Therefore, all details not described in detail above regarding the technical solutions of the global optimization design device 60 and computing device 70 for the closed-cell aluminum foam impact suppression structure can be found in the description of the technical solutions of the aforementioned global optimization design method for the closed-cell aluminum foam impact suppression structure. This embodiment of the invention will not elaborate further on these details.

[0181] It should be noted that the technical solutions described in the embodiments of the present invention can be combined arbitrarily without conflict.

[0182] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A global optimization design method for a closed-cell aluminum foam impact suppression structure, characterized in that, The method includes: A model of the dynamic crushing process of closed-cell foam metal structure under high-speed impact of mass block is described using the single-wave model in plastic shock wave theory. Evaluation indicators for assessing buffering effectiveness are constructed based on the impact parameters in the dynamic crushing process model. An objective function is established based on the evaluation index and the design parameters of the closed-cell aluminum foam impact suppression structure. A global optimization model for the closed-cell aluminum foam impact suppression structure is constructed based on the objective function and the constraints of the design parameters. The adaptive crossover probability and mutation probability are determined based on the number of generations and the fitness values ​​of individuals in the population; The global optimization model is solved using a genetic algorithm improved by the adaptive crossover probability and mutation probability to obtain the optimal design parameters of the closed-cell aluminum foam impact suppression structure. The impact parameters include: the waveback stress of the waveback portion in the closed-cell foam metal structure. Post-wave strain Post-wave particle velocity and wavefront position The wave-after particle velocity With the speed of the mass block The same applies; correspondingly, the relationship between each of the impact parameters and impact time includes: The first expression for waveback stress is constructed based on the constitutive relation equation. ; Based on the conservation of mass and momentum across the wavefront, the first expressions for the velocity of the mass block are obtained respectively. And the second expression for post-wave stress ;in, For dynamic-rigid-plastic hardening D R Dynamic initial crush stress of foamed metal in PH model This indicates the density of the foamed metal material. This indicates the relative density of the foamed metal. Indicates the density of the matrix material; According to the first expression of the wave back stress The first expression for the velocity of the mass block. And the second expression for post-wave stress The third expression for the wave back stress is obtained. Regarding the shock wave velocity The first expression And the second expression for the velocity of the mass block. ; Initial post-wave stress obtained based on initial impact velocity and initial wave post-strain ; According to the initial waveback stress Initial wave post-strain The wave back strain was obtained. The wave back stress Wavefront position and the speed of the mass block's movement With impact time The changing relationship.

2. The method according to claim 1, characterized in that, The model describing the dynamic crushing process of a closed-cell foam metal structure under high-speed impact from a mass block using the single-wave model in plastic shock wave theory includes: Based on the theory of plastic shock waves, a single-wave model is used to describe the dynamic crushing process of foam metal structures. Select at least one impact parameter from the dynamic crushing process model; Establish the relationship between each of the impact parameters and impact time.

3. The method according to claim 1, characterized in that, The initial wave back stress Initial wave post-strain The wave back strain was obtained. The wave back stress Wavefront position and the speed of the mass block's movement With impact time The relationships of change include: According to the initial waveback stress Initial wave post-strain Obtain the post-wave strain Regarding the impact time The implicit expression, through the wave back strain Perform a second-order Taylor expansion to obtain the wave back strain. Regarding the impact time Explicit asymptotic solution; According to the wave back strain Regarding the impact time The explicit asymptotic solution yields the wave back strain. The wave back stress Wavefront position and the speed of the mass block's movement With impact time The changing relationship.

4. The method according to claim 1, characterized in that, The initial wave back stress Initial wave post-strain The wave back strain was obtained. The wave back stress Wavefront position and the speed of the mass block's movement With impact time The relationships of change include: The waveback strain was obtained using the DR-PH model through the conservation of mass and momentum across the wavefront. The wave back stress Wavefront position and the speed of the mass block's movement With impact time Implicit solutions to variations; Substitute the parameter fitting model of the DR-PH model into the post-wave strain in sequence. The wave back stress Wavefront position and the speed of the mass block's movement With impact time The implicit solution of the variation is used to obtain the wave back strain. The wave back stress Wavefront position and the speed of the mass block's movement With impact time The changing relationship.

5. The method according to claim 1, characterized in that, The step of constructing evaluation indicators for assessing buffering effectiveness based on the impact parameters in the dynamic crushing process model includes: Based on the dynamic crushing process model of the foam metal structure, the total energy absorption, specific energy absorption, stroke efficiency, and peak impact force are selected as the evaluation indicators.

6. The method according to claim 1, characterized in that, The objective function is established based on the evaluation index and the design parameters of the closed-cell aluminum foam impact suppression structure. Based on the relationship between the evaluation indicators and the design parameters, with the optimization objectives of maximizing total energy absorption, maximizing specific energy absorption, maximizing stroke efficiency, and minimizing peak impact force, corresponding initial objective functions are designed for each evaluation indicator. The initial objective function is normalized according to the weights corresponding to each evaluation index to obtain a single objective function.

7. The method according to claim 1, characterized in that, The determination of adaptive crossover probability and mutation probability based on evolutionary generations and the fitness values ​​of individuals in the population includes: Calculate the first operator based on the evolutionary algebra according to the following formula. and the second operator based on the fitness value of individuals in the population ; in, Let represent the maximum and minimum crossover probabilities, respectively. Indicates the termination of the evolutionary generation; Indicates the current generation number; , Let represent the internal constant of the operator, and , ; This represents the maximum fitness of an individual in the current population; This represents the minimum fitness value of an individual in the current population; This represents the average fitness of individuals in the current population. The adaptive crossover probability is obtained based on the first operator and the second operator, using the following formula: ； Calculate the third operator based on the evolutionary algebra according to the following formula. and the fourth operator based on the fitness value of individuals in the population ; in, They represent the maximum and minimum mutation probabilities, respectively. , Let represent the internal constant of the operator, and , ; The adaptive mutation probability is obtained based on the third operator and the fourth operator, using the following formula: 。 8. A globally optimized design device for a closed-cell aluminum foam impact suppression structure, characterized in that, The device implements the steps of the global optimization design method for the closed-cell aluminum foam impact suppression structure according to any one of claims 1 to 7, and the device includes: a model description part, a first construction part, an objective function establishment part, a second construction part, a determination part, and an optimal parameter acquisition part; wherein... The model description section is configured to use a single-wave model in plastic shock wave theory to describe the dynamic crushing process of a closed-cell foam metal structure under high-speed impact from a mass block. The first construction part is configured to construct evaluation indicators for evaluating the buffering effect based on the impact parameters in the dynamic crushing process model; The objective function establishment section is configured to establish an objective function based on the evaluation index and the design parameters of the closed-cell aluminum foam impact suppression structure. The second construction part is configured to construct a global optimization model of the closed-cell aluminum foam impact suppression structure based on the objective function and the constraints of the design parameters; The determining part is configured to determine the adaptive crossover probability and mutation probability based on the number of generations and the fitness values ​​of individuals in the population; The optimal parameter acquisition section is configured to solve the global optimization model using a genetic algorithm improved by the adaptive crossover probability and mutation probability to obtain the optimal design parameters of the closed-cell aluminum foam impact suppression structure.

9. A computer storage medium, characterized in that, The computer storage medium stores a global optimization design program for a closed-cell aluminum foam impact suppression structure. When the global optimization design program for the closed-cell aluminum foam impact suppression structure is executed by at least one processor, it implements the steps of the global optimization design method for the closed-cell aluminum foam impact suppression structure according to any one of claims 1 to 7.

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