Influencing Factors of Renal Blunt Impact Injury: A Finite Element Method Study / 医用生物力学

Objective To study influencing factors of renal blunt impact injury by using finite element (FE) method. Methods Based on CT images of the kidney, the kidney FE models for different age groups were constructed. The renal blunt impact test was reconstructed, and the influence of kidney material constitutive parameters, kidney tissue structure, kidney size, impact position and impact velocity on injury severity were analyzed. Results Under the same impact condition, the stress of renal cortex decreased with the kidney mass increasing, and increased with the impact velocity of the hammer increasing. The renal capsule had a certain energy absorption effect, so as to reduce the kidney stress. When the kidney was impacted, the stress of renal cortex under side impact was significantly higher than that under frontal impact. Conclusions Compared with viscoelastic constitutive model, Mooney Rivlin material constitutive model is more suitable for FE evaluation on renal injury severity. The renal injury decreases with the kidney mass increasing. The increase of impact velocity will intensify the renal injury severity. Renal capsule will reduce renal injury to a certain extent, so the existence of renal capsule structure must be considered in FE modeling of the kidney. Compared with frontal and rear impact, the renal injury severity is greater when the kidney is impacted from the lateral side.

Evaluation of brain injury caused by stick type blunt instruments based on convolutional neural network and finite element method / 生物医学工程学杂志

The finite element method is a new method to study the mechanism of brain injury caused by blunt instruments. But it is not easy to be applied because of its technology barrier of time-consuming and strong professionalism. In this study, a rapid and quantitative evaluation method was investigated to analyze the craniocerebral injury induced by blunt sticks based on convolutional neural network and finite element method. The velocity curve of stick struck and the maximum principal strain of brain tissue (cerebrum, corpus callosum, cerebellum and brainstem) from the finite element simulation were used as the input and output parameters of the convolutional neural network The convolutional neural network was trained and optimized by using the 10-fold cross-validation method. The Mean Absolute Error (MAE), Mean Square Error (MSE), and Goodness of Fit ( R 2) of the finally selected convolutional neural network model for the prediction of the maximum principal strain of the cerebrum were 0.084, 0.014, and 0.92, respectively. The predicted results of the maximum principal strain of the corpus callosum were 0.062, 0.007, 0.90, respectively. The predicted results of the maximum principal strain of the cerebellum and brainstem were 0.075, 0.011, and 0.94, respectively. These results show that the research and development of the deep convolutional neural network can quickly and accurately assess the local brain injury caused by the sticks blow, and have important application value for understanding the quantitative evaluation and the brain injury caused by the sticks struck. At the same time, this technology improves the computational efficiency and can provide a basis reference for transforming the current acceleration-based brain injury research into a focus on local brain injury research.

Effects of Impact Angle on Head Injury in Six-Year-Old Child Pedestrian-Car Collision / 医用生物力学

Objective To explore the influence of child head injury under different impact angles by applying the finite element model of six-year-old child pedestrian as specified in the European New Car Assessment Programme (Euro NCAP). Methods Based on the finite element model of 6-year-old pedestrian with detailed anatomical structure as specified by the Euro NCAP (TB024), four groups of simulation experiments were set up to explore the mechanism of head injury in children under different impact angles. The initial position for head mass center was on the longitudinal center line of the car. The initial speed of the car was 40 km/h. The car contacted with the model from the direction of the right (0°), the front (90°), the left (180°) and the back (270°). The kinematics differences and head impact responses were compared, and injuries of the facial bone and skull were analyzed. Results Through the analysis of head contact force, acceleration of head mass center, resultant velocity of head mass center with the vehicle, head injury criterion (HIC15), facial bone fracture and skull stress distribution, it was found that the risk of head fracture and brain contusion under back impact and front impact was higher than that under side impact. The risk of head fracture and brain contusion was highest under back impact, while the lowest under side impact. Conclusions Child pedestrian head injury was the largest under back impact. The results have important application values for the assessment and development of car-pedestrian collision protection device.

Reverse and Optimization for Constitutive Parameters of Adipose Tissues Based on Feasible Direction Method / 医用生物力学

Objective To study the constitutive model of adipose tissue at medium strain rate and its parameter inversion. Methods Based on experiments of adipose tissue mechanical properties, the compression experiment of adipose tissues was reconstructed by finite element method, and the parameters for characterizing constitutive models of adipose tissues were screened. Combined with the method of feasible direction (MFD) in optimization method, the reverse calculation for parameters of fat tissue constitutive model at medium strain rate was conducted. ResultsCompared with Ogden constitutive model, the viscoelastic constitutive model was more suitable for characterizing the mechanical response at medium strain rate (260 s-1). The parameters of the constitutive model suitable for simulation were obtained using the reverse method. Conclusions The viscoelastic constitutive model was more suitable for characterizing the mechanical response at medium strain rate. The results provide references for studying the influence of human adipose tissues on body injury in finite element simulation of vehicle collisions.

Research on thorax impact injury of children at different ages based on finite element models / 生物医学工程学杂志

The pediatric cadaver impact experiments were reconstructed using the validated finite element(FE) models of the 3-year-old and 6-year-old children. The effect of parameters, such as hammer size, material parameters and thorax anatomical structure characteristics, on the impact mechanical responses of 3-year-old and 6-year-old pediatric thorax was discussed by designing reasonable finite element simulation experiments. The research results showed that the variation of thorax contact peak force for 3-year-old group was far larger than that of 6-year-old group when the child was impacted by hammers with different size, which meant that 3-year-old child was more sensitive to hammer size. The mechanical properties of thoracic organs had little influence on the thorax injury because of the small difference between 3-year-old and 6-year-old child in this research. During the impact, rib deformation led to different impact location and deformation of internal organs because the 3-year-old and 6-year-old children had different geometrical anatomical structures, such as different size of internal organs. Therefore, the injury of internal organs in the two groups was obviously different. It is of great significance to develop children finite element models with high biofidelity according to its real anatomical structures.