HCR loiter altitude in m ROC rate of climb in ms -1 t endurance in hrs TC thickness to chord ratio of wing in percentage TR wing taper ratio UAV unmanned aerial vehicle VCR loiter velocity in kmph VMAX maximum speed in kmph VS stall speed in kmph W O all up weight of UAV in kg WL wing loading in kg/m 2 WW wing weight in kg x design variable NOMENCLATURE AR wing aspect ratio g inequality constraint

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This paper investigates the preliminary wing design of Unmanned Aerial Vehicle (UAV) using a two step optimization approach. The first step is a single objective aerodynamic optimization whereas the second step is a coupled dual objective aerodynamic and structural optimization. In the single objective case, airfoil geometry is optimized to get maximum endurance parameter at a 2D level with maximum thickness to chord ratio and maximum camber as design variables. Constraints are imposed on the leading edge curvature, trailing edge radius, zero lift drag coefficient and zero lift moment coefficient. After arriving at the optimized airfoil geometry, the wing planform parameters are optimized with minimization of wing weight and maximization of endurance parameter corresponding to the wing and four more design variables from the aerodynamics discipline namely taper ratio, aspect ratio, wing loading and wing twist are added in the second step. Also, four more design variables from the structures discipline namely the upper and lower skin thicknesses at root and tip of the wing are added with stall speed, maximum speed, rate of climb, strength and stiffness as constraints. The 2D airfoil and 3D wing aerodynamic analysis is performed by the XFLR5 code and the structural analysis is performed by the MSC-NASTRAN software. In the optimization process, a relatively newly developed multi-objective evolutionary algorithm named NSGA-II (non-dominated sorting genetic algorithm) is used to capture the full Pareto front for the dual objective problem. In the second step, in order to reduce the time of computation, the analysis tools are replaced by a Kriging meta-model. For this dual objective design optimization problem, numerical results show that several useful Pareto optimal designs exist for the preliminary design of the UAV wing.

Environmental control system holds vital importance as it is responsible for passenger's ventilation and comfort. This paper presents an analytical design of environmental control systems and represents the estimated design in three-dimensional. Knowledge-based engineering application serves as the base for designing and methodology for the environmental control systems. Flexibility in the model enables the user to control the size and positioning of the system and also sub-systems associated with it. The number of passengers serves as the driving input and threedimensional model gives the exact representation with respect to the volume occupied and dependencies on the number of passengers. It also provides a faster method to alter the system to user needs with respect to the number of air supply pipes, number of ducts and pipe length. Knowledge-based engineering gives the freedom to visualize various options in the conceptual design process.

Environmental control systems hold vital importance as they are responsible for aircraft cabin air ventilation and passenger comfort. This paper presents an analytical design of both Conventional & Electrical environmental control systems. The result of the estimated design is represented in a geometrical model that gives freedom to visualize various options in the conceptual design process, using Knowledge-based engineering application as a base for the design and methodology. Flexibility in the model enables the user to control the size and positioning of the system and sub-systems associated with it. The number of passengers serves as the driving input and the three-dimensional model gives the exact representation concerning the volume occupied and dependencies on the number of passengers. It also provides a faster method to alter the system to user needs with respect to the number of air supply pipes, number of ducts, and pipe length.