Abstract

The fluid flow dynamics on the porous scaffolds and their static responses on the adjacent bone are very crucial parameters for bone adaptation. Researchers are trying to develop different algorithms to design biomimetic porous scaffolds incorporating bone tissue engineering. In this present work, three types of biomimetic heterogeneous porous scaffolds (HPS) were designed with the help of the Voronoi tessellation method and Swarm Intelligence and those were analysed under fluid perfusion as well as under static loading conditions. In computational fluid dynamics (CFD) analysis, the wall shear stress (WSS) and the permeability of the porous scaffolds were compared to the natural trabecular bone to understand their hydrodynamic responses. In static analysis, the von Mises stresses of the Ti₆Al₄V scaffolds were checked to ensure no-yield condition. The strain energy density (SED) distributions were also studied on the neighbouring bone region of the femur greater trochanter to obtain stress shielding (SS) patterns and these findings were then compared with the natural trabecular bone at the same anatomical region. The outcome parameters, viz. the induced WSS, von Mises stress, the permeability, and SS of the scaffold, are found to be independent of the scaffold architecture. The von Mises stress and permeability increased with an increase in porosities, while the induced WSS and SS nature of the scaffolds showed the reverse trend. The results showed that the HPS designed based on the Swarm Intelligence incorporating Physarum Polycephalum algorithm offered the least SS level of 41.096 for 75% porous HPS, which may be considered the most promising result. Considering all the parameters, the novel designed scaffold based on Swarm Intelligence showed the most trabecular bone mimicking nature compared to the other scaffolds.

中文翻译：

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骨组织工程仿生多孔支架设计

摘要

多孔支架上的流体流动动力学及其在相邻骨骼上的静态响应是骨骼适应的非常重要的参数。研究人员正在尝试开发不同的算法来设计结合骨组织工程的仿生多孔支架。在目前的工作中，借助 Voronoi 曲面细分方法和群体智能设计了三种类型的仿生异质多孔支架 (HPS)，并在流体灌注和静态加载条件下进行了分析。在计算流体动力学（CFD）分析中，将多孔支架的壁剪切应力（WSS）和渗透性与天然骨小梁进行比较，以了解它们的流体动力学响应。在静态分析中，检查Ti ₆ Al ₄ V 支架的von Mises 应力以确保不屈服条件。还研究了股骨大转子邻近骨区域的应变能密度 (SED) 分布，以获得应力屏蔽 (SS) 模式，然后将这些结果与同一解剖区域的天然骨小梁进行比较。结果参数，即。发现支架的诱导 WSS、von Mises 应力、渗透性和 SS 与支架结构无关。 von Mises 应力和渗透率随着孔隙率的增加而增加，而支架的诱导 WSS 和 SS 性质则呈现相反的趋势。结果表明，基于群智能并结合多头绒菌算法设计的 HPS 对于 75% 多孔 HPS 提供了 41.096 的最低 SS 水平，这可能被认为是最有希望的结果。考虑到所有参数，与其他支架相比，基于群体智能的新颖设计的支架表现出最模仿骨小梁的性质。