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Considering the efficiency and environmental issue in balloon inflating and sealing up work,an innovate design scheme cooperated by a variety of transmission structure which is ingenuity and meets the green design concept is put forward. Taking the core component cylindrical cam as an example and the parametric design analysis in its process is expounded and the mechanism is controlled to achieve precise movement by using function expression. On this basis,the optimization design based on the parameter- driven is further studied,by using the genetic algorithm in Matlab optimization toolbox and taking the resistance moment of inverse cam mechanism as objective,the model is modified and the parameter is reset by using the optimization result. The verification is carried out through the functional prototype testing and motion simulation analysis in Recur Dyn solver in UG software,and the optimized design in all the parameter driving is perfected.

A child head-form is usually used to evaluate the head injury criterion (HIC) in the collision between the child pedestrian head and engine hood according to Chinese standard GB/T 24550-2009. However, intracranial response, such as principal strain and shear strain of brain tissues, cannot be evaluated by using head-form because of its poor bio-fidelity without detailed brain tissues. In this paper, a validated 6-year-old child head finite element (FE) model with detailed brain tissues was used to substitute the head-form to impact engine hood in order to investigate the effects of thickness and material properties of engine hood on head responses (HIC value, principal strain and shear strain). The results showed that the thickness of inner panel and outer panel of engine hood significantly influenced the head responses of 6-year-old child, while the effect of material properties of engine hood was not significant. The thinner engine hood could provide better protection for child pedestrian head. [ABSTRACT FROM AUTHOR]

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.

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.

Finite element(FE) model of thorax with high biofidelity is one of the most important methods to investigate thoracic injury mechanism because of the absence of pediatric cadaver experiments. Based on the validated thorax finite element model, the FE models with equivalent muscles and real geometric muscles were developed respectively, and the effect of muscle biofidelity on thoracic injury was analyzed with reconstructing pediatric cadaver thorax impact experiments. The simulation results showed that the thoracic impact force, the maximum displacement and the maximum von-Mises stress of FE models with equivalent muscles were slightly greater than those from FE models with real geometric muscles, and the maximum principal strains of heart and lung were a little lower. And the correlation coefficient between cadaver corridor and FE model with real muscles was also greater than that between cadaver corridor and FE model with equivalent muscles. As a conclusion, the FE models with real geometric muscles can accurately reflect the biomechanical response of thorax during the impact.