A Fast Mathematical Modeling Method for Aerodynamic-Heating Predictions

Author(s):  
C. Luo ◽  
Z. Jiang
2018 ◽  
Vol 38 (10) ◽  
pp. 1022002
Author(s):  
王中昱 Wang Zhongyu ◽  
张连新 Zhang Lianxin ◽  
孙鹏飞 Sun Pengfei ◽  
李建 Li Jian ◽  
尹承真 Yin Chengzhen

2020 ◽  
pp. 1-10
Author(s):  
Dongyang Pan ◽  
Jingrui Liu

Mechanical biology is the study of the influence of the mechanical environment on human health, disease, or injury. To study the mechanism of the organism’s perception and response to mechanical signals can promote the development of biomedical basic and clinical research, and promote human health. The purpose of this paper is to study the mathematical modeling method of the effect of multimodal mechanical signals on cell stretching and compression. This article first established a cell mechanics model based on the generalization of membrane theory, introduced the micro-manipulation techniques used to characterize cell mechanics and the method of cell mechanics loading, and then explained why mathematical modeling was established. Finally, according to the multi-modality During the mechanical preparation process, the effects of multi-modal mechanical signals on the stretching and compression of annulus fibrosus stem cells were studied. The experimental results in this paper show that after planting fibrous stem cells with different elastic modulus, the cell proliferation is obvious after the tensile mechanical stimulation of different conditions, and the different elastic modulus scaffolds are stimulated by the tensile mechanical stimulation of 2% tensile amplitude. The cell morphology is different. The low elastic modulus is round-like, and the high elastic modulus is fusiform-like. After 5% and 12% stretch amplitude, the cells are oriented at different elastic modulus. Arranged, there is no obvious difference in cell morphology.


Author(s):  
Ekaterina Statsenko

Prediction of technological processes in various sectors of the food industry using mathematical modeling is becoming increasingly important. The paper describes the effect of various factors on the grain weight after germination by the method of correlation-regression analysis. Using this modeling method, based on the established relationship, it is possible to predict the weight of the grain after germination in various conditions.


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