Ranjith Mohan

Bio: Ranjith Mohan is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Dynamic soaring & Floquet theory. The author has an hindex of 3, co-authored 19 publications receiving 62 citations. Previous affiliations of Ranjith Mohan include Indian Institutes of Technology.

Trajectory optimisation of six degree of freedom aircraft using differential flatness

Abstract: The flatness of a six-degree-of-freedom (6DoF) aircraft model with conventional control surfaces – aileron, flap, rudder and elevator, along with thrust vectoring ability is established in this work. Trajectory optimisation of an aircraft can be cast as an inverse problem where the solution for control inputs that yield desired trajectories for certain states is sought. The solution to the inverse problems for certain systems is made tractable when they exhibit differential flatness. Flatness-based trajectory optimisation has a significant advantage over an equivalent collocation-based method in terms of computational efficiency and viability for real-time implementation. An application for the flatness of 6DoF aircraft is shown in the trajectory optimisation for dynamic soaring, and its connection with an equivalent 3DoF flatness-based implementation is also brought out. The results are compared with that from a collocation-based approach.

Mixed convection in a partially heated triangular cavity filled with nanofluid having a partially flexible wall and internal heat generation

Abstract: Numerical study of mixed convection in a partially heated nanofluid-filled lid driven cavity with internal heat generation and having a partial flexible wall was performed. The bottom wall of the triangular enclosure is moving with constant speed and left vertical wall is partially heated. The inclined wall of the cavity is cooled and partially flexible. The governing equations are solved with Galerkin weighted residual finite element method. The effects of Richardson number (between 0.05 and 50), internal Rayleigh number (between 10 4 and 10 8 ), size and elastic modulus of the partial flexible wall and nanoparticle volume fraction (between 0 and 0.04) on the fluid flow and heat transfer were numerically investigated. It was observed that the local and averaged heat transfer reduce as the value of the Richardson number and internal Rayleigh number increase. As the value of the elastic modulus of the inclined wall and nanoparticle volume fraction increase, local and average heat transfer enhance. The discrepancy between the averaged Nusselt number increase for different sizes for the lower values of elastic modulus of the flexible wall. When heat transfer process is effective adding nanoparticles to the base fluid is advantageous.