This study aims to overcome the shortcomings such as low efficiency, high cost and difficult to carry out multi-parameter research, which limited the optimization of infusion bag configuration and manufacture technique by experiment method. We put forward a fluid cavity based finite element method, and it could be used to simulate the stress distribution and deformation process of infusion bag under external load. In this paper, numerical models of infusion bag with different sizes was built, and the fluid-solid coupling deformation process was calculated using the fluid cavity method in software ABAQUS subject to the same boundary conditions with the burst test. The peeling strength which was obtained from the peeling adhesion test was used as failure criterion. The calculated resultant force which makes the computed peeling stress reach the peeling strength was compared with experiment data, and the stress distribution was analyzed compared with the rupture process of burst test. The results showed that considering the errors caused by the difference of weak welding and eccentric load, the flow cavity based finite element method can accurately model the stress distribution and deformation process of infusion bag. It could be useful for the optimization of multi chamber infusion bag configuration and manufacture technique, leading to cost reduction and study efficiency improvement.
Finite Element Analysis ; Software ; Stress, Mechanical

This study explored the variation of bursting force of multi-chamber infusion bag with different geometry size, providing guidance for its optimal design. Models of single-chamber infusion bag with different size were established. The finite element based on fluid cavity method was adopted to calculate the fluid-solid coupling deformation process of infusion bag to obtain corresponding critical bursting force. As a result, we proposed an empirical formula predicting the critical bursting force of one chamber infusion bag with specified geometry size. Besides, a theoretical analysis, which determines the force condition of three chamber infusion bag when falling from high altitude, was conducted. The proportion of force loaded on different chamber was gained. The results indicated that critical bursting force is positively related to the length and width of the chamber, and negatively related to the height of the chamber. While the infusion bag falling, the impact force loaded on each chamber is proportional to the total liquid within it. To raise the critical bursting force of in fusion bag, a greater length and width corresponding to reduced height are recommended considering the volume of liquid needed to be filled in.

Objective To obtain the distribution of stress concentration on the microporous structure of 3D-printed materials through a mapping algorithm with low calculation cost, so as to provide a new method of finite element calculation of 3D-printed materials for the prediction of fatigue life and the optimization of structural design. Methods Node coordinates and stress values within the influential region of the single pore were extracted to calculate the stress concentration coefficients of different nodes. The nearest node to each node on the ideal model was determined by distance, and the corresponding coefficient was multiplied by its stress value. When the nearest nodes of several nodes were the same, the average of these coefficients was assigned. For the pores close to the edge, an edge coefficient must be multiplied to reduce the error. Results An error of less than 8% between the mapping result and the calculation result was achieved for the case in which the pores were not near the edge, but for the case in which the pores were close to each other near the edge, the error was less than 15%. Conclusions The mapping algorithm can effectively characterize the stress concentration of the microporous structure of 3D-printed materials, and determine the stress distribution with low cost. This novel algorithm provides the finite element result for the optimization design and fatigue analysis of implants in clinical applications.

Corona virus disease 2019 (COVID-19) has been the focus of global attention since its outbreak. With the rapid spreading of COVID-19, serious challenges including medical management system, medical resources, emergency response, medical devices and instruments gradually occur, revealing many shortcomings among these aspects. Herein, through the principles, viewpoints and methods of biomechanics, this article recognizes and analyzes the existing problems that are urgently needed to be solved, such as the study of in-vitro viability of the virus, the biomechanics of aerosol, the fluid mechanics in public transportation and places, the relationship between respiratory diseases and cardiovascular diseases, the improvement of medical devices, with an objective of taking advantages of biomechanics in epidemic prevention and control, so as to promote the development of biomechanics.

Abstract OBJECTIVE To develop a vancomycin individualized dosing-assisted decision platform suitable for practical clinical application scenarios and provide individualized dosing recommendations for the rational use of vancomycin. METHODS Based on the vancomycin population pharmacokinetic model that had been constructed and verified to be feasible, the vancomycin individualized assisted decision-making platform was developed by using Idea2019, JDK1.8, ETL and other software tools. The platform development had gone through three main stages, included ①requirement analysis; ②design stage; ③software testing and optimization. RESULTS The vancomycin individualized assisted decision-making platform, which was successfully developed and applied, had the advantages of simple page, perfect function and convenient operation, and was divided into four main modules according to functions, namely retrieval module, information module, concentration prediction module and reporting module. The platform could connect to the hospital intranet platform to automatically obtain patient information, medication information and blood concentration test results, and calculate individual pharmacokinetic parameters for subsequent concentration prediction based on the embedded population pharmacokinetic model, combined with individual parameters. The concentration prediction module incorporated the Bayesian feedback method with patient medication information, drug concentration measurement results and relevant covariate parameter values, took the guideline-recommended trough concentration and AUC range as the target value, calculated the individualized drug administration scheme that met the target concentration range, and set up custom simulation functions considering the actual clinical application scenarios, which was of more popularization and application value. CONCLUSION Based on the vancomycin population pharmacokinetic model that has been successfully constructed in the previous stage, with the assistance of Idea2019, JDK1.8, ETL and other software tools, a vancomycin individualized dosing-assisted decision platform has successfully constructed, which can more efficiently and conveniently assist monitoring pharmacists to provide individualized dosing advice for clinical use of vancomycin.