熔丝制造
过程(计算)
传热
材料科学
传热系数
制作
对流换热
热的
长方体
对流
热交换器
维数之咒
机械
机械工程
计算机科学
热力学
3D打印
工程类
复合材料
物理
机器学习
医学
替代医学
病理
操作系统
作者
Kristin M. de Payrebrune,Volker Böß,Kristin M. de Payrebrune
出处
期刊:3D printing and additive manufacturing
[Mary Ann Liebert]
日期:2023-02-20
被引量:1
标识
DOI:10.1089/3dp.2022.0282
摘要
Fused filament fabrication (FFF) is one of the most popular additive manufacturing (AM) processes due to its simplicity and low initial and maintenance costs. However, good printing results such as high dimensionality, avoidance of cooling cracks, and warping are directly related to heat control in the process and require precise settings of printing parameters. Therefore, accurate prediction and understanding of temperature peaks and cooling behavior in a local area and in a larger part are important in FFF, as in other AM processes. To analyze the temperature peaks and cooling behavior, we simulated the heat distribution, including convective heat transfer, in a cuboid sample. The model uses the finite difference method (FDM), which is advantageous for parallel computing on graphics processing units and makes temperature simulations also of larger parts feasible. After the verification process, we validate the simulation with an in situ measurement during FFF printing. We conclude the process simulation with a parameter study in which we vary the function of the heat transfer coefficient and part size. For smaller parts, we found that the print bed temperature is crucial for the temperature gradient. The approximations of the heat transfer process play only a secondary role. For larger components, the opposite effect can be observed. The description of heat transfer plays a decisive role for the heat distribution in the component, whereas the bed temperature determines the temperature distribution only in the immediate vicinity of the bed. The developed FFF process model thus provides a good basis for further investigations and can be easily extended by additional effects or transferred to other AM processes.
科研通智能强力驱动
Strongly Powered by AbleSci AI