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用于悬停的生物启发式火星飞行器的数据驱动计算流体动力学缩放

Data-driven CFD Scaling of Bioinspired Mars Flight Vehicles for Hover.

作者信息

Pohly Jeremy A, Kang Chang-Kwon, Landrum D Brian, Bluman James E, Aono Hikaru

机构信息

University of Alabama in Huntsville, Huntsville, AL 35899.

United States Military Academy, West Point, NY 10996.

出版信息

Acta Astronaut. 2021 Mar;180:545-559. doi: 10.1016/j.actaastro.2020.12.037. Epub 2021 Jan 3.

Abstract

One way to improve our model of Mars is through aerial sampling and surveillance, which could provide information to augment the observations made by ground-based exploration and satellite imagery. Flight in the challenging ultra-low-density Martian environment can be achieved with properly scaled bioinspired flapping wing vehicle configurations that utilize the same high lift producing mechanisms that are employed by insects on Earth. Through dynamic scaling of wings and kinematics, we investigate the ability to generate solutions for a broad range of flapping wing flight vehicles masses ranging from insects (10) kg to the Mars helicopter (10) kg. A scaling method based on a neural-network trained on 3D Navier-Stokes solutions is proposed to determine approximate wing size and kinematic values that generate bioinspired hover solutions. We demonstrate that a family of solutions exists for designs that range from 1 to 1000 grams, which are verified and examined using a 3D Navier-Stokes solver. Our results reveal that unsteady lift enhancement mechanisms, such as delayed stall and rotational lift, are present in the bioinspired solutions for the scaled vehicles hovering in Martian conditions. These hovering vehicles exhibit payloads of up to 1 kg and flight times on the order of 100 minutes when considering the respective limiting cases of the vehicle mass being comprised entirely of payload or entirely of a battery and neglecting any transmission inefficiencies. This method can help to develop a range of Martian flying vehicle designs with mission viable payloads, range, and endurance.

摘要

改进我们火星模型的一种方法是通过空中采样和监测,这可以提供信息以增强地面探索和卫星图像所做的观测。在具有挑战性的超低密度火星环境中飞行,可以通过适当缩放的仿生扑翼飞行器配置来实现,这些配置利用了与地球上昆虫相同的高效产生升力的机制。通过对翅膀和运动学进行动态缩放,我们研究了为从昆虫(10毫克)到火星直升机(10千克)的广泛扑翼飞行器质量范围生成解决方案的能力。提出了一种基于在三维纳维-斯托克斯解上训练的神经网络的缩放方法,以确定产生仿生悬停解决方案的近似翅膀尺寸和运动学值。我们证明,对于质量从1克到1000克的设计存在一系列解决方案,这些解决方案使用三维纳维-斯托克斯求解器进行了验证和检验。我们的结果表明,在火星条件下悬停的缩放飞行器的仿生解决方案中存在不稳定升力增强机制,如延迟失速和旋转升力。当考虑飞行器质量完全由有效载荷或完全由电池组成的各自极限情况并忽略任何传动效率低下时,这些悬停飞行器的有效载荷可达1千克,飞行时间约为100分钟。这种方法有助于开发一系列具有可行任务有效载荷、航程和续航能力的火星飞行器设计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ea0a/8739330/20a277cde9bd/nihms-1765192-f0012.jpg

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