A method for predicting human lung damage under shock wave

Abstract

The present invention provides a method for predicting human lung damage under the action of shock waves, and relates to the technical field of data processing. The method includes: constructing an explosion flow field model; constructing an explosion propagation model based on air propagation; simplifying the human chest into a multi-layer composite medium including muscles, chest wall, and lungs in the front-back direction and the left-right direction, equivalent the muscles to spring damping units, equivalent the chest wall to mass units, and equivalent the lungs to spring damping units of viscoelastic porous structures, and constructing a chest wall velocity response dynamics model; determining the shock wave pressure when the explosion is transmitted to the human body; constructing a chest wall velocity response motion equation group according to the chest wall velocity response dynamics model and Newton's second law; substituting the determined shock wave pressure when the explosion is transmitted to the human body into the chest wall velocity response motion equation group, solving the chest wall velocity response motion equation group, and determining the chest wall displacement under the action of the shock wave; and predicting human lung damage according to the chest wall displacement.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method and system for predicting human lung damage under the action of shock waves. Background Art

[0002] In an explosion incident, quickly predicting and assessing the severity of lung damage can help medical staff take effective treatment measures in a timely manner and save lives. Therefore, predicting human lung damage is of great significance.

[0003] Currently, the Lobdell impact trauma model is often used to predict human lung damage under the action of shock waves. Based on the principles of biomechanics and physics, it predicts potential damage by simulating the response of human chest tissue under external forces.

[0004] However, the current Lobdell impact trauma model does not take into account the effect of muscles on shock waves when constructing the model, resulting in low accuracy of the chest wall velocity response determined by the Lobdell impact trauma model, which directly affects the prediction accuracy of human lung damage under the action of shock waves. Summary of the invention

[0005] In order to solve the technical problem that the current Lobdell impact trauma model in the prior art does not take into account the influence of muscles on shock waves when constructing the model, resulting in low accuracy of chest wall velocity response determined according to the Lobdell impact trauma model, which directly affects the prediction accuracy of human lung injury under the action of shock waves, the present invention provides a method and system for predicting human lung injury under the action of shock waves.

[0006] The technical solution provided by the embodiment of the present invention is as follows:

[0007] First aspect

[0008] An embodiment of the present invention provides a method for predicting human lung damage under shock wave action, comprising:

[0009] S1: Construct explosion flow field model;

[0010] S2: Construct explosion propagation model based on airborne transmission;

[0011] S3: The human chest is simplified into a multi-layer composite medium containing muscles, chest wall, and lungs in the front-to-back and left-to-right directions. The muscles are equivalent to spring-damper units, the chest wall is equivalent to mass units, and the lungs are equivalent to spring-damper units with viscoelastic porous structures. The dynamic model of chest wall velocity response is constructed.

[0012] S4: determining the shock wave pressure when the explosion is transmitted to the human body according to the explosion flow field model and the explosion propagation model;

[0013] S5: constructing a chest wall velocity response motion equation group according to the chest wall velocity response dynamics model and Newton's second law;

[0014] S6: Substituting the determined shock wave pressure when the explosion is transmitted to the human body into the chest wall velocity response motion equation group, solving the chest wall velocity response motion equation group, and determining the chest wall displacement under the shock wave;

[0015] S7: Predict human lung injury based on the chest wall displacement.

[0016] Second aspect

[0017] An embodiment of the present invention provides a system for predicting human lung damage under shock wave action, comprising:

[0018] processor;

[0019] A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the method for predicting human lung injury under the action of shock waves as described in the first aspect is implemented.

[0020] The third aspect

[0021] An embodiment of the present invention provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method for predicting human lung damage under the action of shock waves as described in the first aspect is implemented.

[0022] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0023] In the present invention, the human chest is simplified into a multi-layer composite medium including muscles, chest wall, and lungs in the front-to-back and left-to-right directions, the muscles are equivalent to spring damping units, the chest wall is equivalent to mass units, and the lungs are equivalent to spring damping units of viscoelastic porous structures. A chest wall velocity response dynamic model is constructed to improve the accuracy of the chest wall velocity response equation group and the prediction accuracy of human lung damage under the action of shock waves. The human lung damage under the action of shock waves can be predicted quickly and accurately, which can provide a reference for rapid assessment of personnel injuries and treatment and protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 A schematic flow chart of a method for predicting human lung damage under shock wave provided by an embodiment of the present invention;

[0026] Figure 2 A schematic diagram of the structure of a method for predicting human lung damage under shock wave provided by an embodiment of the present invention;

[0027] Figure 3 A schematic diagram of the structure of a system for predicting human lung damage under shock waves provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0028] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0029] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0030] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same. "of", "corresponding, relevant" and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same.

[0031] In the embodiments of the present invention, sometimes a subscript such as W1 may be written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are the same.

[0032] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0033] Reference Manual Attached Figure 1 , showing a flow chart of a method for predicting human lung damage under shock wave provided by an embodiment of the present invention.

[0034] Reference Manual Attached Figure 2 , showing a structural schematic diagram of a method for predicting human lung damage under shock wave provided by an embodiment of the present invention.

[0035] The embodiment of the present invention provides a method for predicting human lung damage under the action of shock waves. The method can be implemented by a device for predicting human lung damage under the action of shock waves. The device for predicting human lung damage under the action of shock waves can be a terminal or a server. The processing flow of the method for predicting human lung damage under the action of shock waves can include the following steps:

[0036] S1: Construct explosion flow field model.

[0037] In a possible implementation, the explosion flow field model is specifically:

[0038]

[0039] Among them, p b represents the pressure generated by the explosion, A1 represents the coefficient of the first exponential term, ω represents the shape parameter of the pressure-volume curve, R1 represents the first exponential factor, V represents the relative volume of the explosive, e represents the natural constant, B1 represents the second exponential term, R2 represents the second exponential factor, E b It represents the initial internal energy per unit volume of explosive.

[0040] In the present invention, the explosion flow field model is constructed to ensure that accurate and reliable pressure distribution data are provided during the simulation of explosion and shock wave propagation, providing a solid foundation for subsequent air transmission, chest wall response and lung injury prediction.

[0041] S2: Construct an explosion propagation model based on airborne transmission.

[0042] In a possible implementation, the explosion propagation model based on air propagation is specifically:

[0043] p air =D0+D1μ+D2μ 2 +D3μ 3 +(D4+D5μ+D6μ 2 )E air

[0044]

[0045] Among them, p air represents air pressure, D0, D1, D2, D3, D4, D5, D6 represent state equation coefficients, E air represents the specific internal energy of air, μ represents the relative density change, ρ represents the air density, and ρ0 represents the air density.

[0046] In the present invention, by using a specific state equation to construct an explosion propagation model based on air propagation, it is possible to ensure that accurate and reliable pressure and density distribution data are provided during the simulation of shock wave propagation, providing a solid foundation for subsequent chest wall response and lung injury prediction.

[0047] S3: The human chest is simplified into a multi-layer composite medium containing muscles, chest wall, and lungs in the front-to-back and left-to-right directions. The muscles are equivalent to spring-damper units, the chest wall is equivalent to mass units, and the lungs are equivalent to spring-damper units with viscoelastic porous structures. A dynamic model of chest wall velocity response is constructed.

[0048] In the present invention, the human chest structure is complex. By simplifying it into a multi-layer composite medium model, the complex biomechanical problem can be converted into a relatively simple mechanical problem. After each part is equivalent to a spring, damping and mass unit, the classical mechanics method can be used to solve it, reducing computing resources and time consumption.

[0049] Furthermore, the muscle was innovatively equivalent to a spring damping unit, which improved the accuracy of the subsequent chest wall velocity response equations and the prediction accuracy of human lung damage under the action of shock waves.

[0050] S4: Determine the shock wave pressure when the explosion is transmitted to the human body based on the explosion flow field model and the explosion propagation model.

[0051] Specifically, based on the explosion flow field model and the explosion propagation model, the shock wave pressure when the explosion is transmitted to the human body can be determined through finite element analysis.

[0052] In the present invention, the characteristics of the explosive and the air propagation characteristics are comprehensively considered to truly reflect the entire process of the shock wave from the explosion point to the human body position, ensure the physical authenticity of the simulation results, and improve the prediction accuracy.

[0053] S5: Based on the chest wall velocity response dynamics model and Newton's second law, a group of chest wall velocity response motion equations is constructed.

[0054] In a possible implementation, the chest wall velocity response motion equation group is specifically:

[0055]

[0056] Among them, M f represents the mass of the anterior chest wall, d represents the differential sign, X1 represents the displacement of the anterior chest wall, t represents time, K 12 represents the elastic coefficient of the lung in the anterior-posterior direction, X2 represents the displacement of the posterior chest wall, J 12 A represents the viscosity coefficient of the lung in the front-to-back direction. f represents the cross-sectional area of ​​the anterior chest wall, p 1w represents the forward pressure generated by the compressible gas in the lungs, p 12 represents the pressure in the front and back direction of the lung cavity, K3 represents the elastic coefficient of the anterior chest muscle, X3 represents the displacement of the anterior chest muscle, J3 represents the viscosity coefficient of the anterior chest muscle, and M brepresents the mass of the posterior chest wall, A b represents the cross-sectional area of ​​the posterior chest wall, p 2w represents the backward pressure generated by the compressible gas in the lungs, K4 represents the elastic coefficient of the posterior thoracic muscle, X4 represents the displacement of the posterior thoracic muscle, J4 represents the viscosity coefficient of the posterior thoracic muscle, and p f represents the forward shock wave pressure, p b represents the backward shock wave pressure, M l represents the mass of the left chest wall, X5 represents the displacement of the left chest wall, K 56 represents the elastic coefficient of the lung in the left and right directions, X6 represents the displacement of the right chest wall, J 56 Represents the viscosity coefficient of the lung in the left and right directions, A l represents the cross-sectional area of ​​the left chest wall, p 5w Indicates the leftward pressure generated by the compressible gas in the lungs, p 56 represents the pressure in the left and right directions of the lung cavity, K7 represents the elastic coefficient of the left chest muscle, X7 represents the displacement of the left chest muscle, J7 represents the viscosity coefficient of the left chest muscle, and M r represents the right chest wall mass, A r represents the cross-sectional area of ​​the right chest wall, p 6w represents the rightward pressure generated by the compressible gas in the lungs, K8 represents the elastic coefficient of the right chest muscle, X8 represents the displacement of the right chest muscle, J8 represents the viscosity coefficient of the right chest muscle, and p l represents the leftward shock wave pressure, p r Represents the rightward shock wave pressure.

[0057] In the present invention, by constructing a group of motion equations based on the chest wall velocity response dynamics model and Newton's second law, a systematic mechanical description can be provided, the accuracy and reliability of the model can be improved, complex dynamic behaviors can be captured, numerical solutions and simulations can be facilitated, and multi-directional and multi-level analysis can be supported, providing a basis for personalized protection recommendations and interdisciplinary research. These benefits make this method of great theoretical and practical significance in the prediction of human lung injury under shock waves.

[0058] Optionally, the forward pressure, backward pressure, leftward pressure and rightward pressure generated by the compressible gas in the lungs are specifically:

[0059]

[0060] Among them, p 1w represents the forward pressure generated by the compressible gas in the lungs, p0 represents the pressure of the lung cavity when it is not subjected to shock waves, c0 represents the speed of sound when the lung cavity is not subjected to shock waves, γ represents the gas constant, and p 2w Indicates the backward pressure generated by the compressible gas in the lungs, p 5w Indicates the leftward pressure generated by the compressible gas in the lungs, p 6wIndicates the rightward pressure generated by the compressible gas in the lungs.

[0061] In the present invention, the pressure of the compressible gas in the lungs in all directions is concretized, which can more realistically reflect the stress conditions of the lung tissue under the action of the shock wave and ensure that the model results are closer to reality.

[0062] Optionally, the pressure in the front-to-back direction and the pressure in the left-to-right direction of the lung cavity are specifically:

[0063]

[0064] ΔX 12 =X1-X2

[0065]

[0066] ΔX 56 =X5-X6

[0067] Among them, p 12 represents the pressure in the front and back direction of the lung cavity, p0 represents the pressure in the lung cavity when it is not subjected to shock waves, V represents the volume of the lung cavity, ΔV 12 Indicates the volume change of the lung cavity in the front-to-back direction, D 12 Indicates the distance in the front and back direction of the lung cavity, ΔX 12 Indicates the displacement change of lung cavity in the front and back direction, p 56 Indicates the pressure in the left and right directions of the lung cavity, ΔV 56 Indicates the volume change of the lung cavity in the left and right directions, D 56 Indicates the distance from the lung cavity to the left and right, ΔX 56 Indicates the change in displacement of the lung cavity in the left and right directions.

[0068] In the present invention, the dynamic response of the lung cavity under the action of shock waves can be captured through the embodied pressure calculation, including instantaneous pressure changes and continuous pressure effects, to support dynamic analysis and prediction.

[0069] In a possible implementation, the model parameters in the chest wall velocity response dynamics model are optimized by a harmony search algorithm.

[0070] The model parameters include: lung anterior and posterior viscosity coefficient J 12 , the elastic coefficient of the front chest muscle K3, the viscosity coefficient of the front chest muscle J3, the elastic coefficient of the back chest muscle K4, the viscosity coefficient of the back chest muscle J4, the elastic coefficient of the left and right direction of the lungs K 56 , Viscosity coefficient of lung in left and right direction J 56 , left chest muscle viscosity coefficient J7, right chest muscle elasticity coefficient K8, represents the right chest muscle viscosity coefficient J8.

[0071] Among them, the Harmony Search Algorithm (HS) is a meta-heuristic optimization algorithm based on the music improvisation process. It simulates the process of musicians looking for harmonious music combinations when performing, and is used to solve various optimization problems.

[0072] Specifically, the harmony memory is initialized, the harmony memory includes multiple harmonies, the harmony includes multiple components, each harmony represents a feasible model parameter solution, and each component represents a model parameter:

[0073]

[0074] Among them, HM represents the harmony memory, D represents the harmony dimension, and X i represents the i-th harmony, i = 1, 2, ..., HMS, HMS represents the size of the harmony memory bank, x ij represents the jth component in the ith harmony, j = 1, 2, …, D, and D represents the harmony dimension.

[0075] Generate a random number r1 and determine whether the random number r1 is less than the probability of the harmony memory. If so, randomly generate a new harmony through the harmony memory. Otherwise, generate a new harmony through random selection.

[0076] Optionally, randomly generating new harmonies through a harmony memory library is specifically as follows:

[0077] X new =[x new,1 ,x new,2 …,x new,D ]

[0078] x new,j ∈rand[x 1j ,x 2j ,…,x HMS,j ]

[0079] Among them, X new Indicates new harmony, x new,j represents the jth component in the new harmony, j = 1, 2, ..., D, D represents the harmony dimension, rand represents random selection, x ij represents the jth component in the ith harmony, i = 1, 2, ..., HMS, and HMS represents the size of the harmony memory bank.

[0080] In the present invention, the method of randomly generating new harmonies through the harmony memory can maintain the diversity of solutions, enhance the flexibility of search, maintain the effectiveness of the harmony memory, improve the convergence speed, balance exploration and development, and is simple and easy to implement.

[0081] Optionally, generating new harmony by random selection is as follows:

[0082] x new,j = r1[upper j -lower j ]+lower j

[0083] Among them, upper j Represents the upper boundary of the jth component, lower j represents the lower bound of the j-th component.

[0084] In the present invention, by randomly selecting a method for generating new harmonies, the coverage of the search space can be improved, the diversity of solutions can be enhanced, the implementation and calculation can be simplified, the robustness of the algorithm can be enhanced, a balance between exploration and development can be provided, and the search range can be dynamically adjusted.

[0085] Optionally, the upper boundary and the lower boundary are specifically:

[0086]

[0087] in, represents the upper boundary of the jth component at the tth iteration, represents the upper boundary of the jth component at the t-1th iteration, HM(:j) represents the jth component in the harmony memory library, and max[HM(:j)] represents the maximum value of the jth component in the harmony memory library. represents the lower bound of the j-th component at the t-th iteration, represents the lower boundary of the j-th component at the t-1-th iteration, min[HM(:j)] represents the minimum value of the j-th component in the harmony memory library, and T represents the total number of iterations.

[0088] In the present invention, as the number of iterations increases, the upper and lower boundaries gradually shrink, making the search range more and more concentrated, thereby improving the refinement of the optimization process. In the early stages of iteration, the boundaries are wide and the search range is large, which enhances the global search capability and helps explore the entire solution space to avoid falling into a local optimum. In the later stages of iteration, the boundaries shrink and the search range is concentrated, which helps to perform a detailed search in the good areas of the solution space and improves the accuracy of the solution.

[0089] In the case of randomly generating a new harmony through the harmony memory library, a random number r2 is generated, and it is determined whether the random number r2 is less than the pitch fine-tuning probability. If so, a new harmony is generated through pitch fine-tuning. Otherwise, the harmony remains unchanged.

[0090] Optionally, generating a new harmony by fine-tuning the pitch is specifically as follows:

[0091] x' new,j =x new,j+r2BW+r3(x best,j -x worst,j )+x worst,j

[0092] Among them, x' new,j represents the jth component of the harmony after the new harmony is fine-tuned, x new,j Indicates that the jth component in the new harmony is randomly generated through the harmony memory library, BW represents the fine-tuning bandwidth, r3 represents a random number between -1 and 1, and x best,j represents the jth component of the harmony with the highest current fitness value, x worst,j Represents the jth component in the harmony with the lowest current fitness value.

[0093] In the present invention, the method of generating new harmony by fine-tuning the pitch can improve the flexibility and adaptability of the optimization process, enhance the local search capability, increase the convergence speed, balance the global search and the local search, and enhance the diversity of solutions.

[0094] The generated new harmony is compared with the harmony with the lowest fitness value in the harmony memory library to determine whether the fitness value of the new harmony is greater than the fitness value of the harmony with the lowest fitness value in the harmony memory library. If so, the harmony with the lowest fitness value in the harmony memory library is replaced with the new harmony to update the harmony memory library. Otherwise, the harmony memory library remains unchanged.

[0095] Determine whether the current number of iterations has reached the maximum number of iterations. If so, output the model parameters with the highest current fitness. Otherwise, return to continue iterating.

[0096] S6: Substitute the determined shock wave pressure when the explosion is transmitted to the human body into the chest wall velocity response motion equation group, solve the chest wall velocity response motion equation group, and determine the chest wall displacement under the shock wave.

[0097] In a possible implementation manner, solving the chest wall velocity response motion equations in S6 is specifically:

[0098] The motion equations of chest wall velocity response were solved using the Newmark-beta algorithm.

[0099] Specifically, the displacement and velocity of the next time step can be predicted based on the displacement, velocity, and acceleration of the current time step:

[0100]

[0101] Among them, X i represents chest wall displacement, i=1,2,5,6, X1 represents the anterior chest wall displacement, X2 represents the posterior chest wall displacement, X5 represents the left chest wall displacement, and X6 represents the right chest wall displacement. represents the predicted value of chest wall displacement at time t+1, represents the chest wall displacement at time t, Δt represents the time step, d represents the differential sign, β represents the displacement iteration parameter, and γ represents the velocity iteration parameter.

[0102] Substitute the predicted displacement and velocity into the system of equations and solve for the acceleration at the next time step.

[0103] According to the acceleration of the next time step, the displacement and velocity of the next time step are corrected:

[0104]

[0105] in, represents the chest wall displacement at time t+1.

[0106] The above iterative process is repeated to determine the chest wall displacement under the action of the shock wave.

[0107] Among them, the Newmark-beta method is an implicit integration method with unconditional stability. It can maintain numerical stability under larger time steps and avoid numerical divergence during the calculation process.

[0108] In the present invention, the chest wall velocity response motion equations are solved by the Newmark-beta algorithm, which can improve numerical stability and accuracy, adapt to nonlinear and complex systems, capture dynamic responses, provide prediction and correction mechanisms, provide complete mechanical response data, facilitate numerical implementation and expansion, and improve the adaptability and versatility of the model.

[0109] S7: Predict human lung injury based on chest wall displacement.

[0110] In a possible implementation, S7 specifically includes sub-steps S701 to S708:

[0111] S701: Calculate the chest wall displacement velocity in each direction based on the chest wall displacement:

[0112] v1=dX1 / dt

[0113] v2=dX2 / dt

[0114] v5=dX5 / dt

[0115] v6=dX6 / dt

[0116] Among them, v1 represents the displacement velocity of the anterior chest wall, d represents the differential sign, t represents time, v2 represents the displacement velocity of the posterior chest wall, v5 represents the displacement velocity of the left chest wall, and v6 represents the displacement velocity of the right chest wall.

[0117] S702: Calculate the work in each direction:

[0118]

[0119] Among them, W1 represents the work performed on the anterior chest wall, p0 represents the pressure in the lung cavity when it is not subjected to shock waves, c0 represents the speed of sound in the lung cavity when it is not subjected to shock waves, γ represents the gas constant, W2 represents the work performed on the posterior chest wall, W5 represents the work performed on the left chest wall, and W6 represents the work performed on the right chest wall.

[0120] S703: Normalize the work in each direction:

[0121]

[0122] Among them, W1 * represents the normalized work on the anterior chest wall, V represents the volume of the lung cavity, and represents the normalized work on the posterior chest wall, represents the normalized work on the left chest wall, represents the normalized work performed on the right chest wall.

[0123] It should be noted that the work is normalized to eliminate the influence of different individuals and environmental conditions and improve the versatility and accuracy of model prediction.

[0124] S704: Calculate the effective work of the shock wave on the lungs:

[0125]

[0126] Among them, W eff represents effective work, β1 represents the effective coefficient of the anterior chest wall work, β2 represents the effective coefficient of the posterior chest wall work, β5 represents the effective coefficient of the left chest wall work, and β6 represents the effective coefficient of the right chest wall work.

[0127] Among them, those skilled in the art can set the sizes of the anterior chest wall effective coefficient β1, the posterior chest wall effective coefficient β2, the left chest wall effective coefficient β5 and the right chest wall effective coefficient β6 according to actual conditions, and the present invention does not limit this.

[0128] It should be noted that by calculating the effective work of the shock wave on the lungs, it is possible to quantify the forces in different directions and locations, providing more detailed damage assessment data.

[0129] S705: Calculate the total work done by the shock wave on the lungs:

[0130] W tot =N α W eff

[0131] Among them, W totrepresents the total work, N represents the number of times the shock wave is impacted, and α represents the repeated impact factor.

[0132] S706: Calculate the total work done by the shock wave on the lungs:

[0133] W tot =N α W eff

[0134] Among them, W tot represents the total work, N represents the number of times the shock wave is impacted, and α represents the repeated impact factor.

[0135] S707: Calculate the probability of being in each lung injury level:

[0136]

[0137] Among them, P i represents the probability of being in the i-th lung injury level, ln represents the logarithmic function with the natural constant as the base, λ i represents the constant coefficient of the i-th lung injury grade, μ i Represents the logarithmic coefficient of the i-th lung injury grade.

[0138] S708: The lung injury level with the highest probability is taken as the lung injury level caused by this shock wave.

[0139] In the present invention, lung injury prediction using chest wall displacement can provide comprehensive dynamic analysis, improve prediction accuracy, quantify injury assessment, and quickly and accurately predict human lung injury under the action of shock waves, which can provide a reference for rapid assessment of personnel injuries and treatment and protection.

[0140] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0141] In the present invention, the human chest is simplified into a multi-layer composite medium including muscles, chest wall, and lungs in the front-to-back and left-to-right directions, the muscles are equivalent to spring damping units, the chest wall is equivalent to mass units, and the lungs are equivalent to spring damping units of viscoelastic porous structures. A chest wall velocity response dynamic model is constructed to improve the accuracy of the chest wall velocity response equation group and the prediction accuracy of human lung damage under the action of shock waves. The human lung damage under the action of shock waves can be predicted quickly and accurately, which can provide a reference for rapid assessment of personnel injuries and treatment and protection.

[0142] Reference Manual Attached Figure 3 , showing a schematic structural diagram of a system for predicting human lung damage under shock wave provided by the present invention.

[0143] The present invention also provides a system 20 for predicting human lung damage under the action of shock waves, which is applied to the above-mentioned method for predicting human lung damage under the action of shock waves, and comprises:

[0144] Processor 201.

[0145] The memory 202 stores computer-readable instructions. When the computer-readable instructions are executed by the processor 201, the method for predicting human lung damage under the action of shock waves in the method embodiment is implemented.

[0146] The human lung injury prediction system 20 under the action of shock waves provided by the present invention can execute the above-mentioned human lung injury prediction method under the action of shock waves and achieve the same or similar technical effects. To avoid repetition, the present invention will not go into details.

[0147] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0148] In the present invention, the human chest is simplified into a multi-layer composite medium including muscles, chest wall, and lungs in the front-to-back and left-to-right directions, the muscles are equivalent to spring damping units, the chest wall is equivalent to mass units, and the lungs are equivalent to spring damping units of viscoelastic porous structures. A chest wall velocity response dynamic model is constructed to improve the accuracy of the chest wall velocity response equation group and the prediction accuracy of human lung damage under the action of shock waves. The human lung damage under the action of shock waves can be predicted quickly and accurately, which can provide a reference for rapid assessment of personnel injuries and treatment and protection.

[0149] It should be understood that the processor in the embodiment of the present invention may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0150] It should also be understood that the memory in the embodiments of the present invention may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0151] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0152] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0153] In the present invention, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can be represented by: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0154] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0155] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0156] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment, devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0157] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0158] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0159] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0160] If the 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 the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0161] An embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein when the program is executed by a processor, a method for predicting human lung damage under shock waves as described in the method embodiment is implemented.

[0162] A computer-readable storage medium provided by the present invention can implement the steps and effects of the method for predicting human lung damage under the action of shock waves in the above method embodiment. To avoid repetition, the present invention will not go into details.

[0163] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0164] In the present invention, the human chest is simplified into a multi-layer composite medium including muscles, chest wall, and lungs in the front-to-back and left-to-right directions, the muscles are equivalent to spring damping units, the chest wall is equivalent to mass units, and the lungs are equivalent to spring damping units of viscoelastic porous structures. A chest wall velocity response dynamic model is constructed to improve the accuracy of the chest wall velocity response equation group and the prediction accuracy of human lung damage under the action of shock waves. The human lung damage under the action of shock waves can be predicted quickly and accurately, which can provide a reference for rapid assessment of personnel injuries and treatment and protection.

[0165] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

[0166] There are a few points to note:

[0167] (1) The drawings of the embodiments of the present invention only relate to the structures related to the embodiments of the present invention, and other structures may refer to the general design.

[0168] (2) For the sake of clarity, in the drawings used to describe the embodiments of the present invention, the thickness of the layers or regions is exaggerated or reduced, that is, these drawings are not drawn according to the actual scale. It is understood that when an element such as a layer, film, region or substrate is referred to as being "on" or "under" another element, the element may be "directly" "on" or "under" the other element or there may be intermediate elements.

[0169] (3) In the absence of conflict, the embodiments of the present invention and the features therein may be combined with each other to obtain new embodiments.

[0170] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. The protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for predicting human lung damage under shock wave, characterized in that: include: S1: Construct explosion flow field model; S2: Construct explosion propagation model based on airborne transmission; S3: The human chest is simplified into a multi-layer composite medium containing muscles, chest wall, and lungs in the front-to-back and left-to-right directions. The muscles are equivalent to spring-damper units, the chest wall is equivalent to mass units, and the lungs are equivalent to spring-damper units with viscoelastic porous structures. The dynamic model of chest wall velocity response is constructed. S4: determining the shock wave pressure when the explosion is transmitted to the human body according to the explosion flow field model and the explosion propagation model; S5: constructing a chest wall velocity response motion equation group according to the chest wall velocity response dynamics model and Newton's second law; S6: Substituting the determined shock wave pressure when the explosion is transmitted to the human body into the chest wall velocity response motion equation group, solving the chest wall velocity response motion equation group, and determining the chest wall displacement under the shock wave; S7: Predict human lung injury based on the chest wall displacement.

2. The method for predicting human lung damage under shock wave according to claim 1, characterized in that: The explosion flow field model is specifically: Among them, p b represents the pressure generated by the explosion, A1 represents the coefficient of the first exponential term, ω represents the shape parameter of the pressure-volume curve, R1 represents the first exponential factor, V represents the relative volume of the explosive, e represents the natural constant, B1 represents the second exponential term, R2 represents the second exponential factor, E b It represents the initial internal energy per unit volume of explosive.

3. The method for predicting human lung damage under shock wave according to claim 1, characterized in that: The explosion propagation model based on air propagation is specifically: p air =D0+D1μ+D2μ 2 +D3μ 3 +(D4+D5μ+D6μ 2 )E air Among them, p air represents air pressure, D0, D1, D2, D3, D4, D5, D6 represent state equation coefficients, E air represents the specific internal energy of air, μ represents the relative density change, ρ represents the air density, and ρ0 represents the air density.

4. The method for predicting human lung damage under shock wave according to claim 1, characterized in that: The chest wall velocity response motion equation group is specifically: Among them, M f represents the mass of the anterior chest wall, d represents the differential sign, X1 represents the displacement of the anterior chest wall, t represents time, K 12 represents the elastic coefficient of the lung in the anterior-posterior direction, X2 represents the displacement of the posterior chest wall, J 12 A represents the viscosity coefficient of the lung in the front-to-back direction. f represents the cross-sectional area of ​​the anterior chest wall, p 1w represents the forward pressure generated by the compressible gas in the lungs, p 12 represents the pressure in the front and back direction of the lung cavity, K3 represents the elastic coefficient of the anterior chest muscle, X3 represents the displacement of the anterior chest muscle, J3 represents the viscosity coefficient of the anterior chest muscle, and M b represents the mass of the posterior chest wall, A b represents the cross-sectional area of ​​the posterior chest wall, p 2w represents the backward pressure generated by the compressible gas in the lungs, K4 represents the elastic coefficient of the posterior thoracic muscle, X4 represents the displacement of the posterior thoracic muscle, J4 represents the viscosity coefficient of the posterior thoracic muscle, and p f represents the forward shock wave pressure, p b represents the backward shock wave pressure, M l represents the mass of the left chest wall, X5 represents the displacement of the left chest wall, K 56 represents the elastic coefficient of the lung in the left and right directions, X6 represents the displacement of the right chest wall, J 56 Represents the viscosity coefficient of the lung in the left and right directions, A l represents the cross-sectional area of ​​the left chest wall, p 5w Indicates the leftward pressure generated by the compressible gas in the lungs, p 56 represents the pressure in the left and right directions of the lung cavity, K7 represents the elastic coefficient of the left chest muscle, X7 represents the displacement of the left chest muscle, J7 represents the viscosity coefficient of the left chest muscle, and M r represents the right chest wall mass, A r represents the cross-sectional area of ​​the right chest wall, p 6w represents the rightward pressure generated by the compressible gas in the lungs, K8 represents the elastic coefficient of the right chest muscle, X8 represents the displacement of the right chest muscle, J8 represents the viscosity coefficient of the right chest muscle, and p l represents the leftward shock wave pressure, p r Represents the rightward shock wave pressure.

5. The method for predicting human lung damage under shock wave according to claim 4, characterized in that: Optimizing the model parameters in the chest wall velocity response dynamics model by using a harmony search algorithm; The model parameters include: lung front-to-back viscosity coefficient J 12 , the elastic coefficient of the front chest muscle K3, the viscosity coefficient of the front chest muscle J3, the elastic coefficient of the back chest muscle K4, the viscosity coefficient of the back chest muscle J4, the elastic coefficient of the left and right direction of the lungs K 56 , Viscosity coefficient of lung in left and right direction J 56 , left chest muscle viscosity coefficient J7, right chest muscle elasticity coefficient K8, represents the right chest muscle viscosity coefficient J8.

6. The method for predicting human lung damage under shock wave according to claim 4, characterized in that: The forward pressure, backward pressure, left pressure and right pressure generated by the compressible gas in the lungs are as follows: Among them, p 1w represents the forward pressure generated by the compressible gas in the lungs, p0 represents the pressure in the lung cavity when it is not subjected to shock waves, c0 represents the speed of sound in the lung cavity when it is not subjected to shock waves, γ represents the gas constant, and p 2w Indicates the backward pressure generated by the compressible gas in the lungs, p 5w Indicates the leftward pressure generated by the compressible gas in the lungs, p 6w Indicates the rightward pressure generated by the compressible gas in the lungs.

7. The method for predicting human lung damage under shock wave according to claim 4, characterized in that: The pressure in the front-to-back direction and the left-to-right direction of the lung cavity are as follows: ΔX 12 =X1-X2 ΔX 56 =X5-X6 Among them, p 12 represents the pressure in the front and back direction of the lung cavity, p0 represents the pressure in the lung cavity when it is not subjected to shock waves, V represents the volume of the lung cavity, ΔV 12 Indicates the volume change of the lung cavity in the front-to-back direction, D 12 Indicates the distance in the front and back direction of the lung cavity, ΔX 12 Indicates the displacement change of lung cavity in the front and back direction, p 56 Indicates the pressure in the left and right directions of the lung cavity, ΔV 56 Indicates the volume change of the lung cavity in the left and right directions, D 56 Indicates the distance from the lung cavity to the left and right, ΔX 56 Indicates the change in displacement of the lung cavity in the left and right directions.

8. The method for predicting human lung damage under shock wave according to claim 5, characterized in that: The step S6 of solving the chest wall velocity response motion equations is specifically: The chest wall velocity response motion equations are solved by the Newmark-beta algorithm.

9. The method for predicting human lung damage under shock wave according to claim 8, characterized in that: The S7 specifically includes: S701: Calculate the chest wall displacement speed in each direction according to the chest wall displacement: v1=dX1 / dt v2=dX2 / dt v5=dX5 / dt v6=dX6 / dt Among them, v1 represents the displacement velocity of the anterior chest wall, d represents the differential sign, t represents time, v2 represents the displacement velocity of the posterior chest wall, v5 represents the displacement velocity of the left chest wall, and v6 represents the displacement velocity of the right chest wall; S702: Calculate the work in each direction: Wherein, W1 represents the work done on the anterior chest wall, p0 represents the pressure of the lung cavity when it is not subjected to the shock wave, c0 represents the speed of sound when the lung cavity is not subjected to the shock wave, γ represents the gas constant, W2 represents the work done on the posterior chest wall, W5 represents the work done on the left chest wall, and W6 represents the work done on the right chest wall; S703: Normalize the work in each direction: Among them, W1 * represents the normalized work on the anterior chest wall, V represents the volume of the lung cavity, and represents the normalized work on the posterior chest wall, represents the normalized work on the left chest wall, represents the normalized work performed on the right chest wall; S704: Calculate the effective work of the shock wave on the lungs: Among them, W eff represents effective work, β1 represents the effective coefficient of the work received by the anterior chest wall, β2 represents the effective coefficient of the work received by the posterior chest wall, β5 represents the effective coefficient of the work received by the left chest wall, and β6 represents the effective coefficient of the work received by the right chest wall; S705: Calculate the total work done by the shock wave on the lungs: W tot =N α W eff Among them, W tot represents the total work, N represents the number of times the shock wave is impacted, and α represents the repeated impact factor; S706: Calculate the total work done by the shock wave on the lungs: W tot =N α W eff Among them, W tot represents the total work, N represents the number of times the shock wave is impacted, and α represents the repeated impact factor; S707: Calculate the probability of being in each lung injury level: Among them, P i represents the probability of being in the i-th lung injury level, ln represents the logarithmic function with the natural constant as the base, λ i represents the constant coefficient of the i-th lung injury grade, μ i represents the logarithmic coefficient of the ith lung injury grade; S708: The lung injury level with the highest probability is taken as the lung injury level caused by this shock wave.

Images