Aerospace Engineering

Multidisciplinary design optimization of long endurance unmanned aerial vehicle wing

by Ranjan Ganguli

Rajagopal, S., and Ganguli, R., "Multidisciplinary design optimization of long endurance unmanned aerial vehicle wing", CMES - Computer Modeling in Engineering and Science

The preliminary wing design of a low speed, long endurance UAV is formulated as a two step optimization problem. The... more The preliminary wing design of a low speed, long endurance UAV is formulated as a two step optimization problem. The first step performs a single objective aerodynamic optimization and the second step involves a coupled dual objective aerodynamic and structural optimization. During the first step, 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. Leading edge curvature, trailing edge radius, zero lift drag coefficient and zero lift moment coefficient are taken as constraints. Once the airfoil geometry is finalized, the wing planform parameters are optimized with minimization of wing weight and maximization of endurance. Four design variables from aerodynamics discipline namely taper ratio, aspect ratio, wing loading and wing twist are considered. 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. Constraints are stall speed, maximum speed, rate of climb, strength and stiffness. The 2D airfoil and 3D wing aerodynamic analysis is performed by the XFLR5 panel method code and the structural analysis is performed by the MSC-NASTRAN finite element code. In the optimization process, a multi-objective evolutionary algorithm named NSGA-II (non-dominated sorting genetic algorithm) is used to discover 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 UAV wing.

Design and Optimization Method for Inertial Particle Separator Systems

by Eyas Alfaris

When the Chick Hits the Fan: Representativeness and Reproducibility in Technological Tests

by John Downer

Downer, John 2007 ‘When the Chick Hits the Fan: Representativeness and Reproducibility in Technological Testing’, Social Studies of Science 37 (1): 7-26.

Before a new turbojet engine design is approved, the Federal Aviation Administration (FAA) must assure themselves... more Before a new turbojet engine design is approved, the Federal Aviation Administration (FAA) must assure themselves that, among many other things, the engine can safely ingest birds. They do this by mandating a series of well-defined - if somewhat Pythonesque - ‘birdstrike tests’ through which the manufacturers can demonstrate the integrity of their engines. In principle, the tests are straightforward: engineers run an engine at high speed, launch birds into it, and watch to see if it explodes. In practice, the tests rest on a complex and contentious logic. In this paper I explore the debate that surrounds these tests, using it to illustrate the now-familiar idea that technological tests - like scientific experiments - unavoidably contain irreducible ambiguities that require judgments to bridge, and to show that these judgments can have real consequences. Having established this, I then explore how the FAA reconciles the unavoidable ambiguities with its need to determine, with a high degree of certainty, that the engines will be as safe as Congress requires. I argue that this reconciliation requires a careful balance between the opposing virtues of reproducibility and representativeness - and that this balance differs significantly from that in most scientific experiments, and from the common perception of what it ought to be.

Multidisciplinary Design Optimization of Long Endurance

by Ranjan Ganguli

Rajagopal, S., and Ganguli, R., “Multidisciplinary Design Optimization of Long Endurance Unmanned Aerial Vehicle Wing”, Computer Modeling in Engineering and Science, Vol. 81, No. 1, 2011, pp. 1-34.

Robotic Lake Lander Test Bed for Autonomous Surface and Subsurface Exploration of Titan Lakes

by Ramaprasad Kulkarni

"Co-authored with Wolfgang Fink, Markus Tuller, Alexander Jacobs, Mark Tarbell, R Furfaro, V R Baker","published in 'IEEE Aerospace Proceedings',2012"

We introduce a robotic lake lander test bed that can be operated either stand-alone or as part of a Tier-Scalable... more We introduce a robotic lake lander test bed that can be operated either stand-alone or as part of a Tier-Scalable Reconnaissance mission architecture to study and field test an integrated hardware and software framework for fully autonomous surface and subsurface exploration and navigation of liquid bodies. The lake lander is equipped with both surface and subsurface sensor technologies. Our particular focus is on Saturn's moon Titan with its hydrocarbon lakes with respect to future missions involving lake landers (e.g., Titan Mare Explorer (TiME) mission), potentially in conjunction with balloons/airships and orbiter-support overhead. This test bed serves as an analog to a Titan unpiloted surface vessel equipped with its own onboard realtime navigation and hazard avoidance system, surface and subsurface exploration sensor suite, and autonomous science investigation software system. As such the test bed helps map out a technical path toward true autonomy for the robotic exploration of the Solar System.

Helicopter aeroelastic analysis with spatially uncertain rotor blade properties

by Rajib Chowdhury

Aerospace Science and Technology, 16[1] (2012), pp. 29-39.

This paper investigates the effects of spatially uncertain material properties on the aeroelastic response predictions... more This paper investigates the effects of spatially uncertain material properties on the aeroelastic response predictions (e.g., rotating frequencies, vibratory loads etc.) of composite helicopter rotor. Initially, the spatial uncertainty is modeled as discrete random variables along the blade span and uncertainty analysis is performed with direct Monte Carlo simulations (MCS). Uncertainty effects on the rotating frequencies vary with the higher order modes in a non-linear way. Each modal frequency is found to be more sensitive to the uncertainty at certain sections of the rotor blade than uncertainty at other sections. Uncertainty effects on the vibratory hub load predictions are studied in the next stage. To reduce the computational expense of stochastic aeroelastic analysis, a high dimensional model representation (HDMR) method is developed to approximate the aeroelastic response as functions of blade stiffness properties which are modeled as random fields. Karhunen-Loeve expansion and a lower order expansion are used to represent the input and outputs, respectively, in the HDMR formulation which is similar to the spectral stochastic finite element method. The proposed method involves the approximation of the system response with lower dimensional HDMR, the response surface generation of HDMR component functions, and Monte Carlo simulation. The proposed approach decouples the computationally expensive aeroelastic simulations and uncertainty analysis. MCS, performed with computationally less expensive HDMR models, shows that spatial uncertainty has considerable influence on the vibratory hub load predictions.

Social Network Mapping and Analysis in the Global Aerospace Community

by Matthew Jelavic

Ogilvie, K., & Jelavic, M. (2010). Social network mapping and analysis in the global aerospace community. Canadian Manager, 35(2), 20 – 21.

Use of Parallel Micro-Platform for the Simulation the Space Exploration

by Felipe Lara Rosano

Comparison of Calculated Vibratory Rotor Hub Loads With Experimental Data

by Ranjan Ganguli

Uncertainty Quantification in Helicopter Performance using Monte Carlo Simulations

by Ranjan Ganguli

Optimization of Helicopter Rotor Using Polynomial and Neural Network Metamodels

by Ranjan Ganguli

Neural Network based Feedback Error Controller for Helicopter

by Ranjan Ganguli

Influence of Inflow Models on Helicopter Aeroelastic Optimization

by Ranjan Ganguli

Murugan, S., and Ganguli, R., “Influence of Inflow Models on Helicopter Aeroelastic Optimization”, Computational Fluid Dynamics Journal, Vol. 16, No. 2, 2008, pp. 444-453.

Validation of Comprehensive Helicopter Aeroelastic Analysis with Experimental Data

by Ranjan Ganguli

Fractal Boundaries of Basin of Attraction of Newton-Raphson Method in Helicopter Trim

by Ranjan Ganguli

Uncertainty Analysis of Vibrational Frequencies of an Incompressible Liquid in a Rectangular Tank with and without a Baffle using Polynomial Chaos Expansion

by Ranjan Ganguli

Nonlinear Dynamic Analysis of a Piezoelectrically Actuated Flapping Wing

by Ranjan Ganguli

An Experimental and Numerical Study of Calliphora Wing Structure

by Ranjan Ganguli

A Dragonfly Inspired Flapping Wing Actuated by Electroactive Polymers

by Ranjan Ganguli

Effect of Uncertainty on Helicopter Performance Predictions

by Ranjan Ganguli