DIN Department of Industrial Engineering School of Engineering and Architecture

Transcription

1 DIN Department of Industrial Engineering School of Engineering and Architecture Elective Courses of the Master s Degree in Aerospace Engineering (MAE) Forlì, 08 Nov 2013

2 Master in Aerospace Engineering at DIN-Fo Course Structure

3 Master in Aerospace Engineering at DIN-Fo STAFF Spacecraft Orbital Dynamics and Control Radio Communication and Radar Systems Experimental Methods in Aerodynamics Simulation and Modelling in Fluid Dynamics

4 Spacecraft Orbital Dynamics and Control Learning Outcomes The student learns in details the dynamics of the centre of mass of an artificial satellite, both in the case of motion around a planet or for interplanetary trajectories. Also, the strategies and control laws for orbital maintenance, rendezvous, injection into an interplanetary trajectory and around a target planet are explained, as well as techniques for trajectory design using classical impulsive or low-thrust manoeuvres.

5 Spacecraft Orbital Dynamics and Control Course contents - Elements of Keplerian orbital mechanics - Equations of Astrodynamics - Lagrange planetary equations - Euler-Hill equations - Effect of the main orbital perturbations - Earth flattening (J20) - Ellipticity of the 'Equator (J22) - effect on e and i due to J3 - Atmospheric Drag, overview of atmospheric models - Solar radiation pressure (bodies with high AMR) - third body effect - Station keeping maneuvers for geostationary satellites (North-South) - Station keeping maneuvers for geostationary satellites (East-West) - Lifetime, deorbiting and reorbiting of LEO satellites

6 Spacecraft Orbital Dynamics and Control Course contents (cont d) - Identification and tracking of objects in Earth orbit - Observation Systems (Optical and Radar) - Methods of position determination - Methods of orbit determination - Lambert theorem - Rendez-vous - Interplanetary Trajectories (impulsive and low-thrust maneuvers) - Gravity-assist and Aero-Gravity-assist maneuvers - Circular Restricted Three-Body Problem

7 Radiocommunications and Radar Systems Motivation: Space-to-Earth or space-to-space communication through electromagnetic waves is fundamental for flying objects such as spacecrafts, satellites, ISS, etc. Remote sensing capabilities are also very important. Main objective of the course: To acquire knowledge about the main design criteria of wireless communication systems (with particular emphasis on digital satellite communications) and the main metrics to evaluate their performances, such as bit error probability and spectral efficiency. To acquire knowledge about the main approaches to tackle detection and tracking problems in radar systems.

8 Radiocommunications and Radar Systems Most problems in digital communication systems and in radar systems are decision-making or estimation problems which may be regarded as applications of detection and estimation theory. Examples: (Decision-making problem) What is the most likely transmitted symbol given a noisy observation of it? (Decision-making problem) Is an intruder present in some air space? (Estimation problem) If so, which are its position and velocity?

9 Radiocommunications and Radar Systems Detailed organization of the course: Mathematical instruments (probability, signals, Fourier transform, random processes) Detection and estimation theory (detection criteria, estimation criteria) Analysis of digital communication systems (digital modulation and demodulation, constellations, matched filtering, intersymbol-interference, spectral efficiency, bit error probability) Parameter estimation (phase, frequency) Detection and tracking problems in radar systems (optimum detection approaches, misdetection and false alarm, Bayesian filtering, Kalman filtering)

10 Experimental Methods in Aerodynamics Learning Outcomes The student becomes familiar with main experimental measurement techniques and aerodynamic apparatus. He/She will approach modern and advanced experimental techniques especially developed for wall bounded turbulent flows. By applying these concepts the student will be capable of: 1) designing an experiment, 2) acquiring and processing the data, 3) validating the results by means of an uncertainty analysis 4) writing a scientific report.

11 Experimental Methods in Aerodynamics Course contents - INTRODUCTION: Measurement chain. Sensor and transducers. Resolution and frequency response. Noise. - UNCERTAINTY ANALYSIS: Errors and Uncertainties in the Measured Variable. Taylor Series Method for propagation of uncertainties. Monte-Carlo methods. General and Detailed Uncertainty Analysis. Experiment planning. Repetition and replication. Data Analysis, Regression and Reporting. - WIND TUNNELS: Different types and features. The basic elements of a wind tunnel. The aerodynamic design. Wind tunnels for special applications.

12 Experimental Methods in Aerodynamics Course contents (cont d) - MEASUREMENT METHODS: Pressure measurements. Velocity measurements using pressure. Hot-wire anemometry. Laser- Doppler anemometers. Particle Image Velocimetry. Elements of Stereo-PIV, time resolved and holographic. Skin friction methods - SIGNAL ANALYSIS: Frequency Analysis. Spectrum and Fourier analysis. Wavelet analysis. POD decomposition. - THE CICLoPE PROJECT: Issues related to the measurement of wall turbulence. Problems connected with the measurement of flows at high Reynolds number. Corrections for pressure measurements and hot-wire. Measurements of shear stress at the wall. Oilfilm technique.

13 Simulation and Modelling in Fluid Dynamics Numerical simulations Given the ever increasing performances of super computers, the numerical simulation in fluid dynamics is increasingly used for the design and development of engineering systems and for the prediction of natural phenomena.

14 Simulation and Modelling in Fluid Dynamics Discretization approaches Numerical techniques for the solution of the equations of fluid dynamics (Newton equation for continuum mechanics). Turbulence Multiscale phenomenon, many degrees of freedom. The Reynolds number of the applications cannot be handled by any super computer of the world by DNS. Modelling Aim to reduce the degrees of freedom of the problem. Introduction of models in the equations of fluid dynamics based on the current physical knowledge of turbulence.

15 Simulation and Modelling in Fluid Dynamics Aim of the course Providing basic knowledge to the student to analyze, simulate and model turbulent flows. Topics Basics of numerical analysis. Discretization and solution techniques for the Navier-Stokes equations; Statistical analysis of turbulence. Turbulence models. Tutorials: The students will be asked to carry out a statistical analysis of turbulent fields obtained under different forcing conditions.