Rapid Preliminary Sailplane Design using Regression Method

Mohamad Yamin; Ahmad Fakhri Giyats

doi:10.56741/jnest.v1i02.143

Rapid Preliminary Sailplane Design using Regression Method

Authors

Mohamad Yamin Universitas Gunadarma
Ahmad Fakhri Giyats Universitas Gunadarma

DOI:

https://doi.org/10.56741/jnest.v1i02.143

Keywords:

rapid preliminary design, regression method, sailplane, XRLF5

Abstract

The article describes a new method for the preliminary design of a Sailplane based on technical data from similar Sailplanes, enabling quick design using regression methods. The authors chose FX 66-168 as the main wing airfoil for a new sailplane with a gross weight of 602 kg with a flight parameter Angle-of-Attack (AoA) 0⁰ in minimum velocity of 49.5 m/s to cruise. As an example, we illustrate the proposed regression method. Our method allows for improving the effective preliminary design of the sailplane. The effectiveness evaluation validation of the new model is conducted with the numerical calculation using XFLR Opensource software. The research results improve design techniques and could be used as a manual for an aircraft designer.

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Author Biographies

Mohamad Yamin, Universitas Gunadarma

Mohamad Yamin is the Head of Center for Automotive Research at Gunadarma University, Jakarta, Indonesia. His undergraduate degree is in Aeronautics from ITB University, Bandung, Indonesia (1993), and his doctorate (2003) is in Aerodynamics, ILR, TUBerlin, Germany. His research interests are CFD, Aerodynamics, Dynamics & Control, EV, and Machine learning. (email: mohay@staff.gunadarma.ac.id).

Ahmad Fakhri Giyats, Universitas Gunadarma

Ahmad Fakhri Giyats was born in Jakarta, Indonesia, in 1999. He received the B.S in mechanical engineering from Gunadarma University, Indonesia in 2021. In 2022 he received the master’s degree in mechanical engineering from Gunadarma University. He was a Research Assistant with the Center for Automotive Research Laboratory. Since 2021 he is a Research fellow in Mechanical Engineering Department, Gunadarma University, Indonesia. His research interest includes fluids mechanic and applied artificial intelligence. (email: afgiyats@gmail.com).

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