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A finite element model for 3D printed recycled parts from end-of-life wind turbine blades

机译:从报废的风力涡轮机叶片中 3D 打印回收部件的有限元模型

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摘要

Wind turbines are important for clean electric energy, but the increasing number of end-of-life wind turbine blades has become a hazardous waste problem worldwide. A novel recycling approach based on mechanical grinding and combined with 3D printing techniques is a promising solution that will reduce waste at a low cost while retaining the excellent mechanical properties of recycled fabricated samples. Considering the material structure complexity of 3D printed samples, the Representative Volume Element (RVE) is a promising simulation model. This paper proposes a Modified Random Sequential Adsorption (MRSA) algorithm for the efficient generation of RVEs with hybrid and arbitrary-geometry reinforcements. Compared with the classical RSA algorithm, MRSA is advantageous in fiber intersection computational cost. The error between FEA and experiments is lower than results obtained from Mori-Tanaka and Halpin-Tsai. The effects of fiber content, fiber aspect ratio, fiber orientation and local fiber density are discussed. The model will be helpful for accurately predicting properties of 3D printing materials that use recycled wind turbine waste.
机译:风力涡轮机对于清洁电能非常重要,但报废的风力涡轮机叶片数量不断增加已成为全球的危险废物问题。一种基于机械研磨并结合 3D 打印技术的新型回收方法是一种很有前途的解决方案,它将以低成本减少浪费,同时保留回收制造样品的优异机械性能。考虑到3D打印样品的材料结构复杂性,代表性体积元(RVE)是一种很有前途的模拟模型。该文提出一种改进的随机顺序吸附(MRSA)算法,用于高效生成具有混合和任意几何增强的RVE。与经典的RSA算法相比,MRSA在光纤交集计算成本方面具有优势。有限元分析与实验之间的误差低于Mori-Tanaka和Halpin-Tsai的结果。讨论了纤维含量、纤维长径比、纤维取向和局部纤维密度的影响。该模型将有助于准确预测使用回收风力涡轮机废料的3D打印材料的特性。

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