自然界中用于振动衰减和声音控制的优化结构：综述
Optimized structures for vibration attenuation and sound control in Nature: a review
摘要：
大自然已经设计了复杂的设计，通过数百万年的进化来实现先进的性能和功能。许多生物已经适应了它们的生活环境，产生了非常有效的材料和结构，表现出优化的机械，热，光学特性，目前的技术往往无法复制。这些特性通常是通过使用跨越宏观、介观、微观和纳米尺度的分级结构来实现的，在许多天然材料如木材、骨骼、蜘蛛丝和海绵中广泛观察到。到目前为止，生物启发的方法已经成功地确定优化结构的准静态力学性能，如强度，韧性，粘附力，但相对较少的工作已经做了动态的关注（如振动阻尼，隔音，声音放大等）。特别是，相对有限的知识，目前存在的层次结构如何在自然结构的优化中发挥作用，虽然并发的长度尺度无疑允许解决多个频率范围。在这里，我们回顾了在动态力学性能的结构优化领域中所做的主要工作，突出了不同生物系统中的一些共同特征和策略。我们还讨论了生物启发材料的相关性，特别是在声子晶体和超材料领域，以及利用自然设计技术应用的潜力。
英文摘要：
Nature has engineered complex designs to achieve advanced properties and functionalities through evolution, over millions of years. Many organisms have adapted to their living environment producing extremely efficient materials and structures exhibiting optimized mechanical, thermal, optical properties, which current technology is often unable to reproduce. These properties are often achieved using hierarchical structures spanning macro, meso, micro and nanoscales, widely observed in many natural materials like wood, bone, spider silk and sponges. Thus far, bioinspired approaches have been successful in identifying optimized structures in terms of quasi-static mechanical properties, such as strength, toughness, adhesion, but comparatively little work has been done as far as dynamic ones are concerned (e.g. vibration damping, noise insulation, sound amplification, etc.). In particular, relatively limited knowledge currently exists on how hierarchical structure can play a role in the optimization of natural structures, although concurrent length scales no doubt allow to address multiple frequency ranges. Here, we review the main work that has been done in the field of structural optimization for dynamic mechanical properties, highlighting some common traits and strategies in different biological systems. We also discuss the relevance to bioinspired materials, in particular in the field of phononic crystals and metamaterials, and the potential of exploiting natural designs for technological applications.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
