空气动力学
风洞
计算流体力学
航空航天工程
网格
海洋工程
气动加热
运载火箭
计算机科学
工程类
模拟
物理
传热
地质学
机械
大地测量学
作者
Jubel Kurian,Raj Ajmani,Soham Dedhia,Hanna Kruse,Margee C. Pipaliya,Ben Piper,Rohit Shenoy,Samuel Teolis
摘要
This paper examines the aerodynamic performance, specifically the drag characteristics, of different grid fin geometries to be used to control and maneuver a launch vehicle at low subsonic speeds during a powered landing. The launch vehicle named ‘Zeus’ is conceptually designed to deliver a 200 mt (metric ton) payload to Low Earth Orbit (LEO) per launch for the DoD Space-Based Solar Power Project (SBSP) based on an existing RFP given. Since the vehicle is completely reusable, each stage will be recovered by a powered soft landing. The propellant used for landing the booster is to be minimized and used in the most efficient manner. Controlling the booster using solely thrust vectoring by gimballing the engine consumes a huge amount of propellant. Grid fins present an effective solution in addition to thrust vectoring to control the booster during landing and minimize the use of thrust vectoring. The purpose of the study is to compare the drag force produced by grid fins of different grid geometries and densities at low subsonic speeds during landing. This study was conducted in the Virginia Tech Open Jet Wind Tunnel, where 4 grid fin models with differing grid densities and geometries were placed and the drag force was measured for a range of angles of attack from 0 to 46 degrees. The four grid fin models that were tested were, a control grid fin of the SpaceX Falcon 9, a grid fin with 4 times the grid density as the control, a grid fin with triangular grid shapes, and a grid fin with twice the thickness of the control fin. The findings from this study were that the drag force for the thicker grid fin was the highest, followed by the denser grid fin. The control and triangular grid-shaped fin have very similar drag force results. However, the drag force per unit mass for the control was the highest, followed by the denser grid fin
科研通智能强力驱动
Strongly Powered by AbleSci AI