Bionic model of passenger injury with chinese fifth percentile male body sign and construction method and application thereof

Abstract

The application discloses a kind of Chinese fifth percentile old male passenger injury bionical model with sign, also called biomechanical model, is the digital computing tool in the technical field of intelligent high-end detection equipment of automobile safety.This application is based on the fifth percentile male automobile passenger injury bionical model of thurstone, its each part is adjusted with age-related change to represent old male.The injury bionical model provided by the application meets the Chinese fifth percentile old male sign parameter;The model has detailed human anatomy structure characteristics.The Chinese fifth percentile old male passenger injury bionical model developed and constructed in the application not only provides a high-fidelity simulation tool for studying the injury mechanism of Chinese old passengers during the collision process, but also helps to deepen the understanding of the complex relationship between age change, body geometry and tissue mechanical properties and injury risk.

Description

Technical Field

[0001] This invention belongs to the fields of human digital computing model development technology and human injury biomechanics technology, and relates to a biomimetic model of passenger injury with the 50th percentile of elderly male occupants in China, its construction method and application. Background Technology

[0002] Meanwhile, due to the rapid increase in car ownership in my country, it is foreseeable that more and more elderly people will participate in road traffic in the future. However, with the continuous increase in age, changes in the geometry, composition, and materials of various parts of the human body will lead to an increase in the fragility and weakness of the elderly, and their physical functions will gradually decline with age. Once a traffic collision occurs, the elderly population has an extremely high injury and death rate, becoming the primary "vulnerable group" in car accidents, and also one of the key target groups that need to be studied in the field of occupant collision safety research.

[0003] Traditionally, post-mortem human subjects (PMHS) experiments and anthropomorphic test devices (ATDs) have been frequently used to assess human biomechanical response and crash injury tolerance. However, the reproducibility of PMHS experiments in determining occupant kinematic changes and injury conditions is low; ATDs only represent young and healthy drivers and passengers and do not take into account the effects of age. High-fidelity finite element models are an effective tool for studying injury risk in different populations. These finite element models can be used to directly calculate biomechanical indicators of human injury to better understand the impact of age on injury risk, injury type, and injury severity. Furthermore, finite element human models have high repeatability and reproducibility. Currently, mainstream finite element models such as SAFER, THUMS, GHBMC, and VIVA have formed relatively complete simulation systems, but the research subjects are mostly concentrated in the 50th percentile of males and the 5th percentile of females. Even some finite element models for the elderly are developed and designed for European and American physical characteristics.

[0004] Therefore, finite element models of the human body used in automotive passive safety research need to consider not only the physical characteristics of different population groups, but also, in order to accurately assess the relative risk of injury, clearly defined finite element models of young and elderly individuals are required. Constructing elderly models with Chinese physical characteristics is mainly achieved through two technical approaches: one is to adjust relevant parameters and geometrically deform based on a 50th percentile young adult model; the other is to directly reconstruct based on CT image data of the elderly population. Regardless of the method used, the underlying data must clearly reflect the characteristics of the Chinese population. Taking method one as an example, the basic model needs to represent the body size and anatomical structure of Chinese people. However, currently developed elderly models for Chinese people are mostly based on internationally recognized models such as THUMS or GHBMC, which are developed for populations with physical characteristics from Europe and America and are difficult to accurately reflect the physical characteristics of the elderly Chinese population. Similarly, if method two is adopted, the CT image data used must also originate from the elderly Chinese population to ensure the representativeness of the model in terms of anatomical structure and morphology.

[0005] The establishment of the aging model can provide a high-fidelity simulation tool for studying the injury mechanisms of elderly occupants in China during collisions, and at the same time help to deepen the understanding of the complex relationship between age changes, body geometry and tissue mechanical properties and injury risk. Continuous improvement and multi-scenario validation of this model are expected to further enhance the predictive ability of collision injury risk for the elderly in the future, and provide technical support for developing targeted safety protection strategies for elderly occupants. Summary of the Invention

[0006] To address the shortcomings of existing technologies, the purpose of this invention is to provide a biomimetic model of injuries in elderly male passengers with vital signs at the 50th percentile in China, a method for constructing the model, and application scenarios of the biomimetic model of injuries.

[0007] This invention discloses a biomimetic model of occupant injury with the 50th percentile of vital signs in elderly males in China, also known as a biomechanical model. This model serves as a digital computational tool in the field of automotive safety and intelligent high-end testing equipment. The biomimetic model conforms to the latest anthropometric statistics of elderly males in China from the China National Institute of Standardization. The model possesses detailed anatomical structural features; the solid finite element mesh is primarily hexahedral, while the 2D shell elements are primarily quadrilateral. Except for face-to-face contact between adjacent internal organs and muscles, other parts are connected via shared nodes. Different tissue structures are connected through 2D shell elements or solid elements. Based on the different mechanical properties of each tissue, corresponding material properties are assigned to each tissue structure. This invention also discloses the construction method of the aforementioned biomimetic model of occupant injury with the 50th percentile of vital signs in elderly males in China and its application in automotive safety research. This invention not only provides a high-fidelity simulation tool for studying the injury mechanisms of elderly Chinese occupants during collisions, and offers a data foundation and technical support for further improving protective measures for elderly occupants in car crashes, but also helps to deepen our understanding of the complex relationship between age changes, body geometry and tissue mechanical properties, and injury risk. Furthermore, the implementation process has improved the efficiency of parametric human body modeling.

[0008] This invention proposes a method for constructing a biomimetic model of injury to elderly male occupants in China at the 50th percentile, using the biomimetic model of injury to elderly male occupants in China at the 50th percentile as a benchmark model for construction.

[0009] Preferably, the TUST IBMs M50-O (50th percentile male car occupant injury biomimetic model) is used as the baseline model.

[0010] The method for constructing the damage bionic model includes the following steps:

[0011] Step A: Deform the baseline rib cavity finite element model in the baseline model to obtain an elderly rib cavity finite element model, including the following sub-steps:

[0012] Step A1: Import the chest CT image data of multiple elderly Chinese males aged 61-70 years who meet the anthropometric characteristics of adult males in GB / T 10000-2023 into the 3D Slicer software, select the rib structure for threshold segmentation, and complete geometric reconstruction and smoothing to obtain the geometric model of the rib cavity of multiple elderly male occupants, and manually select multiple landmark points.

[0013] Preferably, based on the anatomical symmetry of the rib cavity, only the left rib cavity is used to extract and mirror the landmarks, and the number of landmarks on one side is 444.

[0014] Step A2: Extract the rib cavity finite element model from the reference model as the reference rib cavity finite element model. Use the improved ICP non-rigid registration algorithm to deform and match the reference rib cavity finite element model to the corresponding multiple elderly male occupant rib cavity geometric models one by one. Then, based on the marker point sequence information manually extracted from the reference rib cavity finite element model, determine the set of homologous marker points on the deformed multiple elderly male occupant rib cavity geometric models.

[0015] Step A3: Perform Generalized Procrustes Analysis (GPA) on the obtained sets of multiple homologous marker points to eliminate the differences in spatial position and rotation angle between different individuals, and obtain an aligned unified marker point set. Then, calculate the mean of the unified marker point set to finally obtain an average set of rib cavity marker points for elderly male occupants.

[0016] Step A4: Finally, the relevant mesh deformation is performed using the set of marker points on the reference rib cavity finite element model and the set of marker points on the average elderly male occupant's rib cavity to obtain an elderly rib cavity finite element model.

[0017] Step B: By searching relevant literature and obtaining the sagittal angle data of the spine of elderly passengers, each vertebra in the baseline finite element model of the spine is adjusted to the corresponding angle to obtain a finite element model of the spine of an elderly person. This includes the following sub-steps:

[0018] Step B1: By searching publicly available literature on the sagittal parameters of the spine in elderly sitting postures, a set of sagittal angle data of the spine of elderly passengers was obtained.

[0019] Preferably, the range of sagittal angle data of the spine for elderly occupants is as follows: SVA 25.9±26.0mm, TPA 18.1±8.5°, TK 28.5±9.7°, LL 33.8±12.9°, PI 46.2±9.2°, PT 21.1±9.5°, SS 25.1±9.2°, LSA 11.5±7.1°, and L1L5 16.0±13.9°.

[0020] More preferably, the sagittal angle data of the spine of elderly occupants are: SV A The values ​​are 19.9 mm, TPA is 18.2°, TK is 25.1°, LL is 22.8°, PI is 42.6°, PT is 25.2°, SS is 17.4°, LSA is 11.9°, and L1L5 is 11°.

[0021] Step B2: Extract the spinal finite element model from the reference model as the reference spinal finite element model. Referring to the measurement definition of each spinal sagittal parameter in the SRS-Schwab classification standard, and using the sagittal angle data of the elderly passenger's spine as the target value, adjust the spatial position or angle of each corresponding vertebra in the reference spinal finite element model, thereby changing the overall spinal curvature of the reference spinal finite element model so that its sagittal parameters are consistent with the sagittal angle data of the elderly passenger's spine, thus obtaining the elderly spinal finite element model.

[0022] Step C: Adjust the soft tissue areas in the baseline model to accommodate the linkage deformation caused by changes in the skeleton.

[0023] Specifically, the internal organs, muscles, ligaments connecting bones, and tendons connecting muscles and bones within the thoracic cavity are processed. In ANSA software, the thoracic organs are scaled as a whole; if interference with the rib cage still exists, fine-tuning is performed using deformation operations. For muscles, deformation operations are primarily used to adapt the muscles to the deformed rib cage and spine. For ligaments and tendons, the mesh needs to be reconstructed.

[0024] Step D: Check the overall mesh quality of the model, handle interference, and optimize the mesh quality.

[0025] Specifically, the Interior Intersections command is used to check for interference throughout the model, and the Hidden command is used to assess mesh quality. Based on the anatomical structure, the Fix Quality and Grids-Move commands are used for appropriate adjustments.

[0026] Step E: Adjust the material properties of the chest, abdomen, spine, bones, and soft tissues of the obtained model according to age-related changes to represent elderly men, and finally obtain the 50th percentile elderly male occupant injury bionic model in China.

[0027] This invention further provides a biomimetic model of injury for elderly male occupants in China at the 50th percentile, constructed based on the aforementioned method. The biomimetic model conforms to the vital signs of elderly male occupants in China at the 50th percentile, specifically including a weight of 63.2 kg, a sitting height of 905 mm, and a total of approximately 1.6 million units and 1.3 million nodes. Each anatomical structure of the model is endowed with realistic biomechanical material properties, effectively representing the deformation behavior and mechanical response of soft tissues during a collision.

[0028] Preferably, the mesh size of the damage biomimetic model is between 0.5 and 10 mm, 90% of the mesh has an aspect ratio of 0 to 6, a warpage of less than 50°, and 98% of the mesh has a Jacobian greater than 0.6.

[0029] The aforementioned biomimetic damage model can assign corresponding material properties to different tissue structures based on their anatomical characteristics and mesh types. This model can be applied to research on the injury mechanisms and safety protection analysis of elderly occupants in automotive collision safety. The model's effectiveness has been verified through experiments on key areas such as the chest, pelvis, knee joint, and head. The establishment of this model fills a gap in the tool range for biomechanical research on injuries to elderly occupants in China. It can accurately simulate the changes in mechanical response characteristics caused by significant differences in bone and muscle development compared to younger individuals during a collision, such as the dynamic response of the chest and abdomen, and the displacement and injury risk of internal organs. This provides crucial data support for the improvement of relevant safety standards and the optimization of protective technologies.

[0030] This invention not only provides a high-fidelity simulation tool for studying the injury mechanisms of elderly Chinese occupants during collisions, but also helps to deepen our understanding of the complex relationship between age changes, body geometry and tissue mechanical properties, and injury risk. In the future, through continuous improvement and multi-scenario validation of this model, it is expected to further enhance the predictive ability for collision injury risks in the elderly and provide technical support for developing targeted safety protection strategies for elderly occupants. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This is a flowchart illustrating the construction method and application of a biomimetic model of injury in elderly male passengers with physical characteristics at the 50th percentile in China, as described in this invention.

[0033] Figure 2 A flowchart of the deformation process of a finite element model of the rib cavity in the elderly.

[0034] Figure 3 This is a schematic diagram of the finite element model of the reference rib cavity.

[0035] Figure 4 This is a schematic diagram of the rib cavity geometry of an elderly male passenger.

[0036] Figure 5 This is a schematic diagram showing the location distribution of the marker point set on the baseline model.

[0037] Figure 6 This provides a framework for the non-rigid registration algorithm of the model.

[0038] Figure 7aA schematic diagram of the baseline model during the visualization process of registering the baseline rib cavity finite element model with the geometric model of the rib cavity of an elderly male passenger.

[0039] Figure 7b A schematic diagram of the target model during the visualization process of registering the baseline rib cavity finite element model with the geometric model of the rib cavity of an elderly male passenger.

[0040] Figure 7c A schematic diagram of rigid registration during the visualization process of registering the baseline rib cavity finite element model with the geometric model of the rib cavity of an elderly male passenger.

[0041] Figure 7d A schematic diagram of non-rigid registration during the visualization process of registering the baseline rib cavity finite element model with the geometric model of the rib cavity of an elderly male passenger.

[0042] Figure 8 This represents the set of left rib cavity landmarks for average elderly male occupants after GPA calibration.

[0043] Figure 9 This is a set of landmark points representing the mean rib cavity value of elderly male passengers.

[0044] Figure 10 This is a schematic diagram comparing the finite element model of the elderly rib cavity after mesh deformation (purple) with the baseline finite element model of the rib cavity (red).

[0045] Figure 11a A schematic diagram of the spinal curvature of a bionic model of an elderly male passenger with physical characteristics at the 50th percentile in China.

[0046] Figure 11b A schematic diagram of the method for measuring the sagittal angle of the spine in a bionic model of an elderly male passenger with physical characteristics at the 50th percentile in China.

[0047] Figure 12 This is a schematic diagram of the injury biomimetic model of an elderly male passenger with the 50th percentile physical characteristics in China, as disclosed in this invention.

[0048] Figure 13a A schematic diagram of a frontal chest impact test on a bionic model of an elderly male passenger with physical characteristics at the 50th percentile in China.

[0049] Figure 13b A schematic diagram of a side impact test on the chest of a bionic model of an elderly male passenger with physical characteristics at the 50th percentile in China.

[0050] Figure 13c A schematic diagram of a seatbelt compression test on the chest of a bionic model of an elderly male passenger with physical characteristics at the 50th percentile in China.

[0051] Figure 13dA schematic diagram of a pelvic side impact test on a bionic model of an elderly male passenger with physical characteristics at the 50th percentile in China.

[0052] Figure 13e This is a schematic diagram of a knee impact test on a bionic model of an elderly male passenger with physical characteristics at the 50th percentile in China.

[0053] Figure 13f A schematic diagram of a rear-collision trolley test using a bionic model of an elderly male occupant with physical characteristics at the 50th percentile in China.

[0054] Figure 14a This diagram illustrates the comparison between the results of a frontal chest impact test on a biomimetic model of an elderly male passenger with physical characteristics at the 50th percentile in China and the results of a cadaver test.

[0055] Figure 14b This is a schematic diagram comparing the results of a side impact test on the chest of a bionic model of an elderly male passenger with physical characteristics at the 50th percentile in China with the results of a cadaver test.

[0056] Figure 14c This diagram illustrates the comparison between the results of a chest seatbelt compression test on a bionic model of an elderly male occupant with physical characteristics at the 50th percentile in China and the results of a cadaver test.

[0057] Figure 14d This is a schematic diagram comparing the results of a pelvic side impact test with the results of a cadaver experiment using a bionic model of an elderly male passenger with physical characteristics at the 50th percentile in China.

[0058] Figure 14e This is a schematic diagram comparing the knee joint impact test results of a bionic model of an elderly male passenger with physical characteristics at the 50th percentile in China with the results of a cadaver experiment.

[0059] Figure 14f This is a schematic diagram comparing the results of a post-collision trolley test with cadaver test results using a bionic model of an elderly male occupant with the 50th percentile physical characteristics in China. Detailed Implementation

[0060] The present invention will be further described in detail below with reference to the specific embodiments and accompanying drawings. Except for the contents specifically mentioned below, the processes, conditions, and experimental methods for implementing the present invention are all common knowledge and general knowledge in the art, and the present invention does not have any particular limitations.

[0061] This invention provides a biomimetic model of injuries in elderly male occupants at the 50th percentile in China, belonging to the field of automotive safety and intelligent high-end testing equipment technology. This model is based on and adjusted from the biomimetic model of injuries in elderly male occupants in China, conforming to the morphological parameters of the physical characteristics of elderly men at the 50th percentile in China, and further refining the human anatomical structure. According to the differences in the mechanical response of various human tissue structures under the physical condition of the elderly, corresponding material properties are assigned to different tissue structures. Simultaneously, to ensure the biomimetic model's realistic biosimulation and to effectively transfer the mechanical properties between tissues, all tissues are connected through common nodes. This invention can provide data support for injury mechanism analysis and safety protection research for the elderly population, a specific group with specific physical characteristics, in areas such as intelligent high-end equipment development, integrated analysis of automotive active and passive safety, and digital vehicle evaluation.

[0062] This invention provides a finite element mesh construction method for a biomimetic model of injury in elderly male occupants at the 50th percentile of the Chinese population, such as... Figure 1 As shown, it includes the following steps:

[0063] Step A: Construction of the finite element model of the rib cavity in the elderly, including the following sub-steps:

[0064] Step A1: Extract the finite element model of the rib cavity from the baseline model as the baseline finite element model of the rib cavity, such as... Figure 3 As shown. Multiple CT scan images of the chest cavity of elderly men without obvious trauma or lesions were selected. The resolution was 512×512 pixels, and the slice spacing was 0.5 mm. These images were imported into 3D Slicer software, where the rib structures were selected for threshold segmentation and 3D reconstruction. The resulting 3D geometric models were then imported into Geomagic Studio software in .obj format for smoothing and filling, ultimately yielding multiple geometric models of the rib cavity in elderly men, as shown. Figure 4 As shown. Based on the anatomical symmetry of the rib cavity, only the markers on the left rib cavity were extracted and mirrored. To ensure that markers were selected at the same locations for the same ribs in different models, the ribs in different regions were divided into equal lengths, meaning that every two adjacent sections had the same length. Four markers were selected on each cross-section of the rib, including the upper, lower, inner, and outer markers. Finally, 444 markers were manually extracted on the left side of the baseline rib cavity finite element model. The specific distribution of the marker locations is as follows. Figure 5 As shown.

[0065] Step A2: Perform non-rigid registration using the improved ICP algorithm to automatically extract marker points. The specific algorithm flow is as follows: Figure 6As shown. The Iterative Closest Point (ICP) algorithm is one of the earliest and most well-known point set registration algorithms. In this algorithm, the nearest point is assumed to be the corresponding point. The transformation matrix is ​​obtained by minimizing the mean square distance. It iteratively solves the transformation from the source point set to the target point set, mapping each point on the reference model to the nearest point on the target model, minimizing the sum of squared distances between them. To address the problem of the ICP algorithm easily getting trapped in local optima, coarse registration can provide a good initial pose for fine registration. This method mainly utilizes this algorithm to register the surfaces of the two models, while performing direction field regularization during the non-rigid deformation of the reference model to the target model. This method is mainly used to extract marker points from the surface of the target geometric model at corresponding positions on the reference model. Based on these marker points, mesh deformation techniques are used to deform the reference finite element model into the target finite element model. Since the reference model and the target model are not necessarily in the same direction or at the same scale in 3D space, several feature points are first manually placed on the surfaces of the two models for initialization. These feature points are used for initial coarse alignment to ensure they are in the same direction. Rigid registration is optimized using an iterative nearest-point algorithm, repositioning the reference model and scaling it to the target model. Finally, non-rigid registration is used to further deform the reference model to adapt to the specific shape of the target geometry. The model deformed using this non-rigid registration method consists of the same number of point clouds as the reference model. The registration method is based on anatomical correspondence features, mapping and fitting the surface of the reference model onto the target model. The anatomical regions on the reference model correspond to the anatomical regions on the target model. That is, if an anatomical feature at a certain location on the surface of the reference model is point 1, then the corresponding anatomical feature at the same location on the deformed model is also point 1.

[0066] Specifically, the first step of this method is to automatically extract landmark points from the geometric model of the rib cavity of an elderly male. Manually selected landmark points on the baseline rib cavity finite element model are designated as class landmark points. These class landmark points have regular sorting and serial number information. Using the "INFO" function in the GRIDS module of NASTRAN mode in ANSA software (which allows selection of vertices in 3D point cloud data and displays their serial numbers and spatial coordinates), the serial number information of 444 landmark points on the baseline rib cavity finite element model is automatically determined and recorded. The second step is to deform and map the baseline rib cavity finite element model onto the geometric model of the rib cavity of an elderly male. By placing a small number of anatomical feature points on the surfaces of the two models, initial scaling rigid registration is used based on the ICP algorithm, thereby mapping the anatomical feature points onto the geometric model of the rib cavity of an elderly male. Figure 7a The baseline model shown is similar to... Figure 7b The target geometric surfaces are aligned as shown. During rigid registration, only the model's position (translation), orientation (rotation), and scaling are changed, such as... Figure 7c As shown. The third step involves non-rigid registration, changing the shape of the baseline rib cavity finite element model to match the shape of the target surface, as shown... Figure 7dAs shown. During the iterative registration process, both rigid and non-rigid registration require finding the correspondence between points on the surfaces of the two models and updating the correspondence using the weighted k-nearest neighbor method; at the same time, regularization is used to control the smoothness of the surface. Finally, using the serial numbers of the 444 marker points on the reference finite element model that have been recorded above, the new coordinate values ​​of the marker points of the deformed reference rib cavity finite element model are obtained in batches. These new coordinate values ​​are the coordinates of the marker points at the corresponding positions in the geometric model of the rib cavity of elderly men.

[0067] Step A3: Eliminate spatial position and rotation angle differences between individuals. Due to spatial differences between samples, spatial position matching is necessary. GPA analysis matches different target geometries by performing affine transformations such as translation, rotation, and scaling. It calculates the sum of squared distances between each geometry and the average geometry, then uses the least squares method to determine the translation, rotation, and scaling coefficients of the target geometries, finally obtaining an aligned unified set of marker points, such as... Figure 8 As shown; then, the mean of this unified set of landmarks is calculated, and finally an average set of rib cavity landmarks for elderly male occupants is obtained, as shown. Figure 9 As shown.

[0068] Step A4: Finally, mesh deformation is performed using the set of marker points on the baseline model and the set of marker points on the average geometric model of the rib cavity in elderly men to obtain the finite element model of the rib cavity in elderly men, as shown below. Figure 10 As shown.

[0069] Step B: Construction of the finite element model of the spine in the elderly:

[0070] As people age, due to the occurrence and development of degenerative spinal diseases, the sagittal spinal alignment of the elderly differs from that of younger people. Especially in a seated posture, the lumbar lordosis and sacral tilt are greater in the elderly than in younger people, and there are also significant differences in sagittal parameters such as pelvic tilt (PT), thoracic kyphosis (TK), and sagittal vertical axis (SVA). A review of relevant literature yielded the following ranges for sagittal angles of the spine in elderly passengers: SVA 25.9±26.0 mm, TPA 18.1±8.5°, TK 28.5±9.7°, LL 33.8±12.9°, PI 46.2±9.2°, PT 21.1±9.5°, SS 25.1±9.2°, LSA 11.5±7.1°, and L1L5 16.0±13.9°.

[0071] A spinal finite element model is extracted from the baseline model and used as the baseline spinal finite element model, as shown in the example below. Figure 11b The measurement definitions of each sagittal parameter of the spine in the recognized SRS-Schwab classification standard are shown below. Using the sagittal angle data of the elderly passenger's spine as the target value, each vertebra in the reference spinal finite element model is adjusted to the corresponding angle using commands such as rotation and movement in ANSA software. This changes the overall spinal curvature of the reference spinal finite element model, resulting in the elderly spinal finite element model. Figure 11a As shown.

[0072] Step C: Adjust the soft tissue parts in the baseline model to adapt to the linkage deformation caused by the changes in the skeleton. Process the thoracic viscera, muscles, ligaments connecting bones, and tendons connecting muscles and bones: In ANSA software, scale the thoracic viscera as a whole. If there is still interference with the rib cavity, use deformation operations for fine adjustment; for muscles, mainly use deformation operations to adapt the muscles to the deformed rib cavity and spine; for ligaments and tendons, reconstruct the mesh.

[0073] Step D: Check the overall mesh quality of the model, handle interference, and optimize mesh quality: Use the InteriorIntersections command to check for interference in the entire model, identify and locate non-physiological penetration phenomena in the tissue; use the Hidden command to evaluate the mesh quality, focusing on key geometric indicators such as Jacobian and warpage, and eliminate mesh defects that seriously affect computational stability, such as negative volume; based on the anatomical structure, and ensuring that the tissue morphology conforms to the physiological structure, use the Fix Quality command and Grids-Move command to make corresponding adjustments.

[0074] Step E: Adjust material properties according to age. By reviewing relevant literature, the material properties of the baseline model's chest, abdomen, spine, pelvis, and soft tissues of organs were adjusted to reflect age-related changes to represent older men. For the harder skeletal parts, elastoplastic materials were mostly used, while viscoelastic materials were used for most muscles and soft tissues. The main adjustments were made to material parameters such as density, elastic modulus, Poisson's ratio, yield stress, tangent modulus, and failure factor for the chest, abdomen, spine, pelvis, and soft tissues of organs, making the model more representative of the elderly population and achieving higher biofidelity.

[0075] After adjustments, a bionic model of passenger injury with vital signs of elderly males in the 50th percentile of China was obtained, such as... Figure 12 As shown.

[0076] The biomimetic model of an elderly male passenger with physical characteristics at the 50th percentile in China proposed in this invention has a weight of 63.2 kg, a sitting height of 905 mm, 1.6 million elements, and 1.3 million nodes. The model's head, neck, chest, abdomen, upper limbs, and lower limbs possess detailed anatomical structures, and its weight and sitting height meet the requirements of GB / T 10000-2023 for physical characteristics of elderly people at the 50th percentile in China. The model exhibits detailed anatomical features, including tendons, ligaments, muscles, organs, fat, and skin. The body elements are primarily hexahedral meshes with a small portion of pentahedral meshes, while the shell elements are primarily quadrilaterals with a small portion of triangles. All parts of the model are connected by shared nodes, possessing corresponding mechanical properties.

[0077] Example 1

[0078] This embodiment describes the construction of a biomimetic model of occupant injury with the 50th percentile physical characteristics of elderly males in China and its application in automobile collision simulation.

[0079] In this embodiment, the number of chest CT scan images of elderly males aged 61-70 years who meet the body size characteristics of GB / T 10000-2023 and have no obvious trauma or lesions used in step A1 is 20 cases.

[0080] In this embodiment, the sagittal angle data of the elderly passenger's spine used in step B are as follows: SVA is 19.9 mm, TPA is 18.2°, TK is 25.1°, LL is 22.8°, PI is 42.6°, PT is 25.2°, SS is 17.4°, LSA is 11.9°, and L1L5 is 11°.

[0081] In this embodiment, the parameter settings for different materials in step E are shown in Table 1 below, where ρ = density, E = Young's modulus, γ = Poisson's ratio, Bulk = bulk modulus, G0 = short-time shear modulus, GI = long-time shear modulus, σy = yield stress, Etan = tangent modulus, εf = failure coefficient, and beta = attenuation coefficient.

[0082] Table 1

[0083] Organizational structure Material parameters (aged model) Material parameters (benchmark model) Compact bone of the clavicle <![CDATA[ρ=1.83e-6kg / mm 3 ,E=7.3GPa,γ=0.3,σ y =0.02GPa]]> <![CDATA[ρ=1.83e-6kg / mm 3 ,E=11GPa,γ=0.3]]> Clavicle cancellous bone <![CDATA[ρ=1e-6kg / mm 3 ,E=0.55GPa,γ=0.2,σ y =0.005GPa]]> <![CDATA[ρ=1e-6kg / mm 3 ,E=0.55GPa,γ=0.2]]> Compact bone of the ribs <![CDATA[ρ=2e-6kg / mm 3 ,E=9.5GPa,γ=0.3,σ y =0.077GPa,e f =0.007]]> <![CDATA[ρ=2e-6kg / mm 3 ,E=12GPa,γ=0.3,σ y =0.077GPa,e f =0.02375]]> Cancellous bone of ribs <![CDATA[ρ=1e-6kg / mm 3 ,E=0.04GPa,γ=0.45,σ y =0.002GPa,e f =0.021]]> <![CDATA[ρ=1e-6kg / mm 3 ,E=0.04GPa,γ=0.45,σ y =0.0018GPa]]> Compact bone of the sternum <![CDATA[ρ=2e-6kg / mm 3 ,E=11.5GPa,γ=0.3,σ y =0.088GPa,e f =0.013]]> <![CDATA[ρ=2e-6kg / mm 3 ,E=12GPa,γ=0.3,σ y =0.077GPa,e f =0.02]]> Cancellous bone of the sternum <![CDATA[ρ=1e-6kg / mm 3 ,E=0.038GPa,γ=0.45,σ y =0.0019GPa,e f =0.03]]> <![CDATA[ρ=1e-6kg / mm 3 ,E=0.04GPa,γ=0.45,σ y =0.0018GPa,e f =0.03]]> costal cartilage <![CDATA[ρ=1.1e-6kg / mm 3 ,E=0.05GPa,γ=0.35]]> <![CDATA[ρ=1.6e-6kg / mm 3 ,E=1.2GPa,γ=0.2]]> Compact bone of vertebrae <![CDATA[ρ=1.8e-6kg / mm 3 ,E=9.8GPa,γ=0.3,σ y =0.08GPa,e f =0.0111]]> <![CDATA[ρ=2.5e-6kg / mm 3 ,E=11GPa,γ=0.4]]> Vertebral cancellous bone <![CDATA[ρ=1e-6kg / mm 3 ,E=0.41GPa,γ=0.3,σ y =0.002GPa,e f =0.059]]> <![CDATA[ρ=1e-6kg / mm 3 ,E=1GPa,γ=0.3]]> Fiber ring <![CDATA[ρ=1.1e-6kg / mm 3 ,E=0.0364GPa,γ=0.4]]> <![CDATA[ρ=1.2e-6kg / mm 3 ,E=0.025GPa,γ=0.4]]> muscle <![CDATA[ρ=1.2e-6kg / mm 3 ,Bulk=1.33MPa,G0=0.14MPa,G I =0.04MPa,beta=100]]> <![CDATA[ρ=1.1e-6kg / mm 3 ,Bulk=1.33MPa,G0=0.14MPa,G I =0.04MPa,beta=100]]> ligament <![CDATA[ρ=1.1e-6kg / mm 3 ,E=0.104GPa,γ=0.45]]> <![CDATA[ρ=1e-6kg / mm 3 ,E=0.315GPa,γ=0.45]]> Compact bone of the pelvis <![CDATA[ρ=1.83e-6kg / mm 3 ,E=5.5GPa,γ=0.29,σ y =0.04GPa,e f =0.017]]> <![CDATA[ρ=1.83e-6kg / mm 3 ,E=11GPa,γ=0.3]]> pelvic cancellous bone <![CDATA[ρ=1.6e-6kg / mm 3 ,E=0.07GPa,γ=0.3,σ y =0.01GPa,e f =0.022]]> <![CDATA[ρ=1e-6kg / mm 3 ,E=0.55GPa,γ=0.2]]> heart <![CDATA[ρ=1e-6kg / mm 3 ,Bulk=2.6MPa,G0=0.44MPa,G I =0.15MPa,beta=100]]> <![CDATA[ρ=1e-6kg / mm 3 ,Bulk=2.6MPa,G0=0.44MPa,G I =0.15MPa,beta=0.1]]> lung <![CDATA[ρ=6e-7kg / mm 3 ,Bulk=2.2MPa,G0=0.2MPa,G I =0.075MPa,beta=100]]> <![CDATA[ρ=6e-7kg / mm 3 ,Bulk=2.2MPa,G0=0.2MPa,G I =0.075MPa,beta=0.1]]> Liver / Spleen / Kidney <![CDATA[ρ=1.1e-6kg / mm 3 ,Bulk=2.8MPa,G0=0.23MPa,G I =0.0436MPa,beta=100]]> <![CDATA[ρ=1.1e-6kg / mm 3 ,Bulk=2.8MPa,G0=0.23MPa,G I =0.0436MPa,beta=100]]>

[0084] In this embodiment, the final damaged biomimetic model has a mesh size of 0.5~10mm, 90% of the mesh has an aspect ratio of 0~6, a warpage of less than 50°, and 98% of the mesh has a Jacobian greater than 0.6.

[0085] As shown in Figure 13, impact tests were conducted on different parts of the bionic occupant injury model of Chinese 50th percentile elderly male obtained in this embodiment to study the injury mechanism of the bionic injury model:

[0086] Place the bionic injury model on a horizontal rigid plane, and construct impactors such as a ram impactor and an abdominal seat belt respectively. Impact and compress the model at different speeds, and output the contact force-time curve or contact force-compression curve of each part of the model, as shown in Figure 14. Refer to a biofidelity assessment system (Biofidelity Ranking System, BRS) proposed by NHTSA, and quantitatively calculate the BRS value of the simulation experiment results to evaluate the effectiveness of the model. The BRS value is classified according to biofidelity: Excellent (BRR≤1.0), Good (1.0<R≤2.0), Marginal (2.0<R≤3.0) and Poor (R>3.0). The specific scores and ratings are shown in Table 2. Through data comparison, it is found that although there are deviations between some curves and the results of cadaver experiments, the overall trend is basically the same, and there is a strong correlation with the results of cadaver experiments. This result strongly supports the accuracy and effectiveness of the developed elderly model in vehicle collision simulation and biomechanics research.

[0087] Table 2

[0088]

[0089] Unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by those skilled in the technical field to which this invention belongs. The terms used in the description of this invention are only for the purpose of describing specific embodiments, and are not intended to limit this invention.

[0090] As used in this invention, the term "comprising" is an open expression, that is, it includes the content specified in this invention, but does not exclude other aspects.

[0091] As used in this invention, the term "and / or" includes any one and all combinations of one or more of the related listed items.

[0092] The protection scope of this invention is not limited to the above embodiments. Without departing from the spirit and scope of the inventive concept, changes and advantages that can be想到 by those skilled in the art are included in this invention, and the scope of protection is defined by the appended claims.

Claims

1. A method for constructing a biomimetic model of passenger injury with the 50th percentile vital signs of elderly males in China, characterized in that, The specific steps of the construction method are as follows: Step A: Construct a geometric model of the rib cavity of the average elderly male in China. Using the biomimetic model of the injury of the 50th percentile male car occupant in Tust as the benchmark model, the benchmark rib cavity finite element model is adjusted to the elderly rib cavity finite element model through rapid mesh deformation technology. Step B: Adjust the vertebral bodies of the baseline spinal finite element model in the baseline model according to the sagittal angle data of the elderly passenger's spine to obtain the elderly spinal finite element model. Step C: Adjust the material properties of the chest, abdomen, spine, bones, muscles and soft tissues of the baseline model with age-related changes to represent elderly men, thereby obtaining a biomimetic model of occupant injury with the physical characteristics of elderly men in the 50th percentile of China.

2. The construction method as described in claim 1, characterized in that, Step A includes the following sub-steps: Step A1: Reconstruct the rib cavity geometric model from multiple cases of chest CT data of elderly Chinese men through threshold segmentation and smooth the data to obtain multiple cases of rib cavity geometric models of elderly male occupants. Step A2: Extract the rib cavity finite element model of the reference model as the reference rib cavity finite element model. Use a non-rigid registration algorithm to deform and match the reference rib cavity finite element model to the rib cavity geometric model of each elderly male passenger. Then, based on the marker point sequence information manually extracted on the reference rib cavity finite element model, determine the set of homologous marker points on the rib cavity geometric model of each elderly male passenger after deformation mapping. Step A3: Perform GPA analysis on the obtained multiple sets of homologous marker points to eliminate the differences in spatial position and rotation angle between different individuals, and obtain an aligned unified marker point set. Then, calculate the mean of the unified marker point set to finally obtain an average set of rib cavity marker points for elderly male occupants. Step A4: Use the set of marker points on the reference rib cavity finite element model and the set of marker points on the average elderly male occupant rib cavity geometric model to perform mesh deformation, and obtain the elderly rib cavity finite element model.

3. The construction method as described in claim 1, characterized in that, The range of the sagittal angle data of the elderly passenger's spine in step B is as follows: SVA is 25.9±26.0 mm, TPA is 18.1±8.5°, TK is 28.5±9.7°, LL is 33.8±12.9°, PI is 46.2±9.2°, PT is 21.1±9.5°, SS is 25.1±9.2°, LSA is 11.5±7.1°, and L1L5 is 16.0±13.9°.

4. The construction method as described in claim 3, characterized in that, The sagittal angle data of the elderly passenger's spine are: SV A The aperture is 19.9 mm, TPA is 18.2°, TK is 25.1°, LL is 22.8°, PI is 42.6°, PT is 25.2°, SS is 17.4°, LSA is 11.9°, and L1L5 is 11°.

5. The construction method as described in claim 1, characterized in that, In step B, referring to the measurement definitions of each sagittal parameter of the spine in the SRS-Schwab classification standard, the sagittal angle data of the elderly passenger's spine is used as the target value to adjust the spatial position or angle of each corresponding vertebra in the reference spine finite element model, thereby changing the spinal curvature and obtaining the elderly spine finite element model.

6. A biomimetic model of passenger injury with vital signs of an elderly male in China at the 50th percentile, characterized in that, The model is constructed using the method described in any one of claims 1-5; the model conforms to the anatomical structure of an elderly male passenger in the 50th percentile of the Chinese human body, and the biomimetic model structure is constructed by including 2D shell unit mesh, 3D volume mesh, pentahedral mesh and / or hexahedral mesh, and different material properties are used to impart biomechanical characteristics to different parts, which together constitute the biomimetic model.

7. The biomimetic model of passenger injury with vital signs of an elderly male in the 50th percentile of China as described in claim 6, characterized in that, The bionic model has detailed anatomical structures in its head, neck, chest, abdomen, upper limbs, and lower limbs; it weighs 63.2 kg and has a sitting height of 905 mm, which conforms to the anthropometric characteristics of adult males aged 61-70 years in GB / T 10000-2023.

8. The biomimetic model of passenger injury with vital signs of an elderly male in the 50th percentile of China as described in claim 6, characterized in that, The biomimetic damage model contains approximately 1.6 million units and 1.3 million nodes. The model has detailed anatomical features, including tendons, ligaments, bones, muscles, organs, fat, and skin. Except for the surface-to-surface contact between adjacent internal organs and adjacent muscles, all other parts of the model are connected by common nodes and have corresponding mechanical properties.

9. The biomimetic model of passenger injury with vital signs of an elderly male in the 50th percentile of China as described in claim 6, characterized in that, The mesh size of the biomimetic damage model is 0.5~10mm, 90% of the mesh aspect ratio is 0~6, the warpage is less than 50°, and 98% of the mesh Jacobian is greater than 0.

6.

10. The application of a biomimetic model of occupant injury with the 50th percentile vital signs of elderly males in China, as described in any one of claims 6-9, in automobile crash simulation, characterized in that... It can be used for injury mechanism research and safety protection analysis of elderly passengers.

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