CN-121580763-B - Modeling method of multilayer discrete element biological tissue

CN121580763BCN 121580763 BCN121580763 BCN 121580763BCN-121580763-B

Abstract

The application relates to the field of discrete element modeling, and discloses a modeling method of a multilayer discrete element biological tissue, which comprises the following steps of S1, acquiring basic mechanical parameters; S2, constructing a single tissue unit model, S3, calibrating a single tissue bonding parameter, S4, assembling a multi-layer tissue model and defining an interface, S5, calibrating an interlayer bonding parameter, and S6, integrating a complete functional model. According to the application, firstly, through the step 3, the physical damage test and the simulation optimization are combined, the bonding parameters in a single tissue are accurately calibrated, and then, through the step 5, the closed loop process is repeated for a multi-layer structure, so that the interface bonding parameters among different tissues are accurately calibrated. The systematic method for calibrating the model layer by layer from inside to outside ensures that each component part and interaction of each component part of the model are verified through experiments, so that the finally constructed model can highly reproduce complex mechanical response of the multi-layer biological tissue under real load.

Inventors

Zu Hongfei
ZHENG KE
FU HUIQUN
CHEN XUWEN
WANG YANGYANG
ZHOU XUEMEI
MOU YU

Assignees

浙江理工大学
民政部一零一研究所
浙江龙宇智能科技有限公司

Dates

Publication Date: 20260508
Application Date: 20260120

Claims (7)

1. A method of modeling a multi-layered discrete-element biological tissue, comprising the steps of: S1, acquiring basic mechanical parameters, namely carrying out a single biological tissue physical mechanical test to acquire the basic mechanical parameters; S2, constructing a single tissue unit model, namely constructing a single biological tissue discrete element geometric model based on the single biological tissue in the step S1, completing filling of discrete element particles, and constructing a discrete element contact model; s3, calibrating single tissue bonding parameters, namely performing physical damage test on the single biological tissue, constructing a simulation scene matched with the single biological tissue, and screening and optimizing key bonding parameters of a discrete element contact model of the single biological tissue by comparing the physical test and the simulation result to determine the single biological tissue bonding parameters; S4, assembling a multi-layer tissue model and defining an interface, namely acquiring interface contact parameters between single tissues, and constructing a multi-layer biological tissue model based on a single biological tissue discrete element geometric model; S5, calibrating interlayer bonding parameters, namely performing a tissue damage experiment on the multilayer biological tissue, constructing a simulation scene matched with the tissue damage experiment, and screening and optimizing the interlayer bonding parameters of the multilayer biological tissue model by comparing physical experiment and simulation results to determine the multilayer biological tissue bonding parameters; And S6, integrating the complete functional model, namely associating the basic mechanical parameters obtained in the step S1, the single biological tissue bonding parameters optimized in the step 3 and the multi-layer biological tissue interface bonding parameters optimized in the step 5 into discrete element particles of the multi-layer biological tissue model to obtain the multi-layer biological tissue discrete element model.
2. The modeling method of the multilayer discrete element biological tissue according to claim 1 is characterized in that in the step S3, key bonding parameters of a single biological tissue discrete element contact model are screened and optimized, specifically, damage simulation data are collected, a Plackett-Burman test is adopted to screen out key bonding parameters which have obvious influence on a damage result, an optimal steep test is utilized to determine an optimal value area of the key bonding parameters, a response surface model is established in combination with a Box-Behnken test design, multi-objective optimization is carried out on the key bonding parameters, and finally the single biological tissue bonding parameters are determined.
3. The modeling method of the multilayer discrete element biological tissue according to claim 1 is characterized in that in the step S5, interlayer bonding parameters of a multilayer biological tissue model are screened and optimized, specifically, damage simulation data of the multilayer tissue are collected, a Plackett-Burman test is adopted to screen out key parameters which have obvious influence on interlayer bonding force, an optimal steep test is utilized to determine a value range of the key parameters, and the accurate parameter optimization is carried out in combination with a Box-Behnken test to finally determine interlayer bonding parameters of the multilayer biological tissue.
4. The modeling method of a multilayer discrete element biological tissue according to claim 1, wherein in the step S2, the discrete element contact model is a Bond type bonding model, and when the model is constructed, an initial value of a Bond type bonding model parameter is set in a preset parameter interval by combining biological tissue interface microscopic characteristics.
5. The modeling method of the multilayer discrete element biological tissue according to claim 1, wherein in the step S1, the physical and mechanical test comprises a compression test, a sloping plate test and a bouncing test, wherein the elastic modulus and the Poisson ratio of the biological tissue are obtained through the compression test, the static friction coefficient and the rolling friction coefficient among particles are calibrated through the sloping plate test, and the recovery coefficient is calibrated through the bouncing test.
6. The method for modeling a multi-layered discrete biological tissue according to claim 1, wherein in step S4, the interface contact parameters between the individual tissues are obtained, specifically, the coefficient of restitution and the coefficient of friction between the different individual tissues are measured according to the physical mechanical test method in step S1, respectively.
7. The method of modeling a multi-layered discrete meta-biological tissue according to claim 1 wherein the filling parameters of the discrete meta-particles in step S2 are determined based on the measured data obtained in step S1.

Description

Modeling method of multilayer discrete element biological tissue Technical Field The invention relates to the technical field of discrete element modeling, in particular to a modeling method of a multilayer discrete element biological tissue. Background The discrete element simulation technology is a numerical simulation method based on particle discrete characteristics, and can accurately restore macroscopic and microscopic behaviors of a particle system in the processes of movement, collision, extrusion and the like by establishing a mechanical model of particle-particle interaction, thereby providing reliable simulation data support for research and development of related equipment and process optimization. The technology is widely applied to multiple fields, can be used for simulating the flow rule of grains in the grain harvesting and conveying processes and optimizing the structure of agricultural equipment in the agricultural field, can simulate the ore crushing and sorting processes in the ore field and guide the design and production of mining machinery, and plays an important role in the fields of building material preparation, chemical grain reaction, food processing and the like, and can assist various industries in improving the production efficiency and the product quality. However, in the technical field of biomass innocent treatment, a discrete element simulation technology is not introduced at present, and in the field of discrete element modeling research, a technical scheme capable of constructing a multi-layer biological tissue structure does not appear. This makes discrete element techniques neither able to serve process simulation of the target biological object in this particular scenario nor able to support construction of a multi-layered biomechanical model. Therefore, the exploration of a modeling method of multilayer discrete element biological tissues is a key for breaking through the limitation of the prior art and constructing a core biomechanical model required by the field. Disclosure of Invention Aiming at the defects of the prior art, the invention provides a modeling method of a multilayer discrete element biological tissue, which aims to solve the problems in the background art. In order to achieve the purpose, the invention is realized by the following technical scheme that the modeling method of the multilayer discrete biological tissue based on the discrete element method comprises the following steps: And step 1, developing a single biological tissue compression test, a sloping plate test and a bouncing test to obtain basic mechanical parameters, wherein the compression test is used for measuring the elastic modulus and the poisson ratio, the sloping plate test is used for calibrating the inter-particle friction coefficient, and the bouncing test is used for assisting in calibrating the recovery coefficient so as to ensure that the parameters are matched with the actual mechanical characteristics of the tissue. And 2, constructing a single biological tissue discrete element geometric model, completing filling of discrete element particles, and finally constructing and endowing a bond type bonding model aiming at a discrete element particle system corresponding to the tissue. Parameters (such as elastic modulus, poisson ratio and friction coefficient) for representing the mechanical properties of the discrete element filling particles are determined based on the measured data obtained in the first step, and initial values of the parameters of a bond bonding model are defined in a scientific and reasonable parameter interval by combining biological tissue interface microscopic properties in order to ensure the reliability and accuracy of simulation results of the follow-up model. And 3, performing a tissue destruction experiment on the single biological tissue sample, setting a simulation scene matched with the single biological tissue sample, running single biological tissue model simulation, simulating a destruction mode of the actual test, and collecting destruction simulation data. And screening key bonding parameters through PB and an optimal steep slope test, and optimizing by combining with BB test to finally determine the bonding parameters of the single biological tissue. And 4, obtaining discrete element parameters of single tissues such as pork, pig bones and the like, and performing test measurement on the coefficient of restitution and the coefficient of friction between the single tissues according to the method of the step 1. Based on the basic splicing, constructing multi-layer biological tissue models of pig trotters, pig with skin and five flowers and the like, combining the single tissue models according to an anatomical structure, setting binding models on different tissue interfaces, and preliminarily defining the value range of Bonding parameters of each interface. And 5, performing a tissue destruction experiment on the multi-layer biological tiss