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/ Indicative Syllabus Introduction to Airport Operations and Management: Overview of airport infrastructure, stakeholders, and the role of airports in the aviation industry. Airport Design and Capacity Management: Factors influencing airport design, capacity planning, and strategies to optimize space and resources. Airport Security Management: Security regulations, risk
/ Indicative Syllabus Introduction to Aviation Finance: Overview of aviation finance and its importance in the aviation industry; Roles and responsibilities of treasury and finance departments in aviation organisations. Financial Risk Management in Aviation: Identification and
/ Indicative Syllabus Airline Fleets, Growth and Demand - Aircraft fleet delivery history; Aircraft order forecasts; Aircraft types and markets segmented and Lessor market share. Airline Markets and Segments - Airline categories; Airline business by market (geography); Airline market trends; Airline costs and Airline revenues. Aircraft Lessors - Aircraft leasing, background and history; Aircraft lessors by size, shape, portfolio, shareholder; Aircraft leasing – key performance factors and Aircraft leasing – habitual base jurisdictions. Aircraft Leasing Economics - Individual aircraft lease financial modelling; Aspects of portfolio aircraft lease financial modelling and Accounting and Auditing mark to market valuation. Aircraft Leasing Risk Management - Aircraft general rating; Aircraft specifications and value; Airline risk, not just credit; Aircraft lease transaction risk; Aircraft lease portfolio risk and Aircraft lessor enterprise risk. Aircraft Lease Risk Investment Submission / Committee - Assist to prepare an aircraft lease transaction investment submission for -- 1 of 3 -- discussion, review and approval decision and to conduct the corresponding aircraft lease transaction investment review committee, findings and recommendations.
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暂无评分/ Indicative Syllabus Structures: Fuselage; Wing; Tail; Landing gear; Thin-wall beams; Tapered beams; Ribs; Cut-outs; Loads applied on airframes; Stress analysis of aircraft structural components Materials: Typical aircraft materials and material characteristics; Characteristics of composite materials Non-destructive testing and evaluation of aircraft structures (NDT&E): Finite element method (FEM) for the analysis of aircraft structures -- 1 of 3 --
/ Indicative Syllabus Introduction to Aircraft Design: Design process and basic aircraft requirements; Evolution of aircraft design and its performance: a brief history; Overview of aircraft design iteration cycle Modern Aircraft Configuration: Advantages and drawbacks of conventional and modern configurations; Considerations for special aircraft; Primary considerations for the fuselage, wing, and tail design Aerodynamic Consideration of Aircraft Design: Fundamentals of aerodynamic; Friction and pressure drag; Airfoil; Finite wings; Drag and lift; Dependence of lift and drag on the angle of attack; End effects of wingtips; Induced drag Sizing and Costing: Internal layout; Structures and weight; Geometry constraints; Sizing equation; Weight fraction method; Weight and balance; Cost analysis; Elements of life-cycle cost; Cost-estimating methods; Operations and maintenance costs; Cost measures of merit Main Components Selection and Design: Selection and design of main components such as fuselage, wing, tail and landing gear; Calculation and design of control surfaces such as aileron, elevator and rudder Multi-disciplinary Design Optimization (MDO): uses optimization methods to solve design problems incorporating a number of disciplines Aircraft certification and Airworthiness: Airworthiness requirements; Load factor determination; Aircraft safety; Airframe loads; Designing against fatigue; Prediction of aircraft fatigue life
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暂无评分/ Indicative Syllabus Aircraft Six Degrees of Freedom (6-DOF) Equations of Motion: Aircraft coordinate systems; Kinematic model; Dynamic model; Propulsion system model; Model linearization method Longitudinal and Lateral Flight Dynamics and Control: Longitudinal motion and mode approximations; Lateral motion and mode approximations; Handling quality Classic and Modern Flight Control System: Classic flight control system; Modern flight control system; State space modelling; Stability, controllability and observability; State feedback design and optimal control Planning for Autonomous Flight: Global path planning methods including search-based methods and sample-based methods; Local smooth trajectory generation methods Autopilot System Integration and Flight Simulation: Open-source flight controller; Flight simulation platform; Programming and hardware -- 1 of 3 -- interface; Implementation of control and planning algorithms; Introduction to autonomous aerial robotic system
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暂无评分/ Indicative Syllabus Introduction to propulsion – Brief history of propulsion, aircraft piston engines, aircraft gas turbine engines, performance parameters of turbofan engines, other air-breathing engines; Aircraft engine subsystems – Nacelle, inlet, nozzle, fan, compressor, turbine, combustor, afterburner, fluid system (air, oil, and fuel), control system, engine test and maintenance, engine start; Introduction to combustion – Brief history of combustion science, combustion modes, and flame types Thermochemistry – Review of thermodynamics, stoichiometry, chemical equilibrium, adiabatic flame temperatures; Mass transfer – Stefan problem, droplet evaporation and burning; Chemical kinetics – Global/elementary reactions, rates of reaction; Mass transfer – Stefan problem, droplet evaporation; Chemical kinetics – Global/elementary reactions, rates of reaction, some important chemical mechanisms, four types of reactors, simplified conservation equations for reacting flows; Flames – Laminar premixed flame, laminar diffusion flame, turbulent premixed flame, turbulent diffusion flame Fuels and low-carbon combustion – Hydrogen/ammonia, combustion instabilities -- 1 of 3 --
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暂无评分/ Indicative Syllabus Foundations of Mathematics and Programming for Aerospace AI: Introduction to the mathematical and coding essentials for aerospace AI. Topics include linear algebra, probability theory, optimization methods, hands-on Python and PyTorch exercises. Emphasis on translating theoretical concepts into functional models, fostering confidence in implementing algorithms for aerospace challenges. Classical Supervised Algorithms for Aerospace Data Analysis: Exploration of classical supervised learning techniques for aerospace data analysis. Includes concept learning, regression and classification algorithms (SVM, k-NN, decision trees, and naïve Bayes), with hands-on implementation. Developing proficiency in algorithm selection and performance analysis for aerospace data interpretation. -- 1 of 4 -- 2 Deep Spatial Learning in Aerospace Applications: Introduces deep learning architectures for extracting and interpreting spatial information in aerospace contexts. Covers multilayer perceptrons for feature embedding, convolutional neural networks for satellite imagery and grid-based analysis, and graph neural networks for unstructured data processing. Emphasis on leveraging spatial correlations to enhance pattern recognition and mapping fidelity. Temporal Sequence Modeling for Aerospace Systems: Exploration of advanced neural techniques for capturing temporal relationships in aerospace sensor data. Topics include recurrent neural networks, LSTM and GRU cells, and attention-based models, applied to control-signal forecasting and anomaly detection. Discussion on modeling time-dependent patterns to support accurate trajectory prediction, real-time monitoring, and adaptive control strategies. Data Analytics and Machine Learning Applications in Aerospace: Application of data analytics and machine learning in aerospace. Covers pattern discovery, topic modeling, genomics, and prediction in aerospace contexts. Discussion on scalability, interpretability, and legal/social/ethical considerations in aerospace data analytics.
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暂无评分/ Indicative Syllabus One-dimensional and quasi-one-dimensional flows – Normal shock relations; Area-velocity relation; Nozzles. Oblique shock and expansion waves – Oblique shock relations; Conical flow; Prandtl-Meyer expansion waves. Linearized flow – Velocity potential equation; Linearised subsonic flow; Compressibility corrections; Linearised supersonic flow. Transonic and hypersonic flows –Full velocity potential equation; Newtonian theory; Mach Number independence. Boundary-layer flows – Boundary-layer theory; Self-similar solutions. Case studies – Theoretical analysis of canonical flow problems in aerospace engineering.
/ Indicative Syllabus Introduction to Satellite Engineering: Overview of satellite engineering, including its history and the state-of-the-art development, the satellite missions and applications, the mathematical tools and skills used in the satellite engineering course. Space Environment: Space vacuum conditions and the earth atmosphere, the impact of space environment on satellite orbits, attitude, structure and materials, electrostatic charge and discharge, etc. Orbital Mechanics: Newton's laws of motion and gravitation, Kepler’s laws, orbit types, orbital transfers and manoeuvres, orbital perturbations. Attitude Determination and Control (ADCS): Coordinate systems, satellite attitude dynamics, actuators and sensors, attitude control systems. -- 1 of 3 -- 2 Telemetry, Tracking and Control Subsystems (TT&C): TT&C functions, command systems, telemetry system, coverage and link analysis, modulation/demodulation. Other Satellite Subsystems: On-board data handling system (OBDH), electric power system, the propulsion system, ground system, etc. Satellite Software Engineering: Software lifecycle, cost, design, test, maintenance; Component-based software engineering Satellite Integration and Test: Facilities and procedures for integration and test, including vibration test, thermal vacuum test, antenna deployment test, electromagnetic compatibility and interference test, etc. Satellite Mission Analysis and Program Management: Mission objectives; Top-level requirements and the flowdown; Preliminary design review (PDR); Interface Control Documents (ICDs), Critical Design Review (CDR); System and mission simulations; Scheduling; Cost; Documentation, etc. Nanosatellite design project: Nanosatellite mission analysis and design with the NASA GMAT software and/or the CubeSat Toolbox for MATLAB ®
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暂无评分/ Indicative Syllabus Revisit to flow governing equations – Material derivative; Reynolds transport theorem; Derivation of Navier-Stokes equations. Turbulent flows – Kolmogorov scales; Reynolds-averaged Navier-Stokes simulations; Large-eddy simulation. Introduction to numerical methods – Errors; Consistency; Accuracy; Stability; Convergence. Finite-difference methods – Discretisation of temporal and spatial derivatives; Explicit and implicit formulations; Stability analysis; Fourier error analysis. Time-marching techniques – Lax–Wendroff technique; MacCormack’s technique; Crank-Nicolson technique; Range-Kutta method. Finite-volume methods – Principles of finite volume method (FVM); FVM for diffusion and convection problems; Application to Navier-Stokes equations, SIMPLE algorithm, PISO algorithm. Modern CFD techniques – Shock-capturing techniques; Upwind schemes; Limiters; Total variation diminishing; Implicit methods. Case studies – Application of the numerical techniques to canonical flow problems in aerospace engineering. -- 1 of 3 -- 2
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暂无评分/ Indicative Syllabus Introduction to propulsion: Air-breathing engines and rockets, applications of rocket propulsion Fundamentals of thermodynamics and compressible flows: Mass, momentum and energy conservation laws; First Law and second law of Thermodynamics; Ideal gas law; Entropy; Isentropic processes; Stagnation properties; Shock waves; Nozzle flows. Fundamentals of rocket propulsion: Thrust; Exhaust Velocity; Energy and Efficiencies; Multiple Propulsion Systems; Typical Performance Values; Variable Thrust. Liquid Propellant Rocket Engine: Types of Propellants; Tanks; Feed Systems; Gas Pressure Feed Systems; Tank Pressurisation; Turbopump Feed Systems and Engine Cycles; Rocket Engines for Maneuvering, Orbit Adjustments, or Attitude Control; Engine -- 1 of 3 -- 2 Families; Valves and Pipelines; Engine Support Structure; Liquid Propellant Combustion and Its Stability Solid Propellant Rocket Motor: Basic Relations and Propellant Burning Rate; Performance Issues; Propellant Grain and Grain Configuration; Propellant Grain Stress and Strain; Attitude Control and Side Manoeuvres with Solid Propellant Rocket Motors; Solid Propellants; Solid Propellant Combustion and Its Stability; Solid Rocket Motor Components and Design Hybrid Propellants Rocket Propulsion: Applications and Propellants; Design Example; Combustion Instability Electric Propulsion: Ideal Flight Performance; Electrothermal Thrusters; Nonthermal Electrical Thrusters; Optimum Flight Performance; Mission Applications; Electric Space-Power Supplies and Power-Conditioning Other Space Propulsion Systems: Nuclear Propulsion; Solar Sail Propulsion; Propellantless Propulsion (e.g., Space Elevator, Momentum Wheels)
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暂无评分/ Indicative Syllabus Introduction to Spacecraft Dynamics: Overview of spacecraft dynamics principles; Coordinate systems and transformations used in spacecraft dynamics; Basic concepts of rigid body dynamics and kinematics applicable to spacecraft. Spacecraft Kinematics and Dynamics: Position, velocity, and acceleration in space; Relative motion and reference frames; Forces and moments acting on spacecraft; Rotational kinematics; Dynamic differential equations of spacecraft; External torques on spacecraft. Orbit Determination and Propagation: Orbit determination techniques using ground-based and onboard sensors; Propagation of orbital elements and trajectory prediction. Attitude Dynamics and Control: Attitude representation and dynamics; Attitude control systems and stabilisation techniques. Guidance and Navigation: Principles of guidance and navigation in space; Orbit transfer manoeuvres and rendezvous operations. -- 1 of 3 -- 2 Spacecraft Formation Flying: Dynamics of multiple spacecraft formations; Control strategies for maintaining formation configurations; Mission Design and Analysis: Mission requirements and constraints; Trajectory optimisation and mission analysis techniques; Case Studies and Applications.
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暂无评分/ Indicative Syllabus Introduction to Computational Tools: Overview of computational software packages such as MATLAB, Python, and C++; Basic programming concepts and syntax. Numerical Methods: Root finding methods (e.g., bisection, Newton-Raphson); Numerical integration and differentiation techniques; Solving systems of linear equations. Curve Fitting and Interpolation: Least squares fitting; Interpolation methods (e.g., Lagrange interpolation, spline interpolation). Differential Equations and Modelling: Introduction to ordinary and partial differential equations; Modelling physical systems using differential equations; Numerical solution methods for differential equations (e.g., Euler's method, Runge-Kutta methods). -- 1 of 3 -- 2 Fundamentals of Finite Element Analysis (FEA): Basics of finite element method; Mesh generation and discretisation; Solving linear and nonlinear FEA problems. Fundamentals of Computational Fluid Dynamics (CFD): Introduction to computational fluid dynamics; Governing equations of fluid flow; Numerical solution methods for CFD simulations. Optimisation Techniques: Introduction to optimisation problems; Gradient-based and gradient-free optimisation algorithms; Application of optimisation techniques in engineering design and analysis. Statistical Analysis and Data Visualisation: Descriptive statistics and probability distributions; Hypothesis testing and regression analysis; Data visualisation techniques.
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暂无评分/ Indicative Syllabus Operations management in low-altitude transport: Decisions on helipad and vertiport locations, construction of service networks, fleet assignments, flight timetable design, queueing analysis, and vehicle routing for drones, electric vertical take-off and landing (eVTOL) aircraft, and other aerial vehicles. Multi-modal transportation: Game theory analysis, analysis of collaboration and competition between different transport modes, synchronization of timetables, and strategies for demand analysis and pricing in low-altitude transport. Service design in special context: Complex network theory, point-to- point/hub-and-spoke, network model; helipad/miniport for eVTOL; Derivation of objectives and constraints for drone applications in parcel delivery and rescue logistics, model construction, and implementation. -- 1 of 3 -- 2 Moreover, the background knowledge of the business planning and project management will also be introduced.
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暂无评分/ Indicative Syllabus Introduction: Overview and basic concepts in U-space, including components in U-space, U-space infrastructure, factors influence the capacity or demand of the U-space, prospects and drawbacks for introducing emerging UAM, and potential solutions. Low-altitude airspace structure and design: The definition, design, and categorization of low-altitude airspace for UAM. Different types of proposed low-altitude airspace structure (e.g. layered, corridor, freemix). The operating environments include airspaces, types of operations, regulations, and procedures necessary to support an operation. -- 1 of 3 -- 2 Low-altitude airspace capacity analysis based on different airspace design: The definition of UAV traffic demand and capacity in low- altitude airspace. Introduce the models used to estimate airspace capacity. Airspace capacity analysis of different airspace structure type. Introduce demand-capacity balancing technique when the requested resources cannot support the collective UAM Operational Intent demand. UAS traffic management: Air traffic management, air traffic control strategies for UAM. Introduce new ATC tactical deconfliction techniques, including the formulation of new separation standards that would rely on enhanced aircraft performance and air traffic management system fidelity may be utilized. U-Space Utilisation: U-space ecosystems, services, frameworks; e- VTOL flight and automation technologies; overall U-space system safety, route duration, and route distance decisions; key areas to be addressed by the U-space program (CONOPs, datalinks, UAV information management, ground technology). Congestion management and resource allocation: Introduce air traffic service in the low-altitude airspace. The design and component of the service network. Based on air traffic management strategies, introduce resource allocation models for efficient use of airspace. Existing challenges and opportunities: Terrain concerns, weather hazard concerns, airspace design in urban complex structures, wind field constraints, and noise control. Characterize different problems such as air corridor constraints and natural environment to address the complex and variable airspace, complicated obstacles, low altitude flights, noise and meteorology faced by their path planning to make finer planning and management.
/ Indicative Syllabus Advanced Sensing Technologies for Low-Altitude Aerial Vehicles: Overview of Sensory Technology: Detailed study of various sensory technologies such as GNSS, LiDAR, visual sensors, mmWave radars, thermal cameras, and depth sensors, emphasizing their role in enhancing vehicle navigation and obstacle detection. Operational Integration: Techniques for the integration and calibration of these instruments to achieve optimal functionality in various environmental conditions, including urban and rural landscapes. Data Integration and Analysis Techniques for Aerial Systems: Data Handling Techniques: Exploration of methods for managing large volumes of data from multiple sensors, focusing on synchronization, -- 1 of 4 -- 2 alignment, and real-time processing challenges. Advanced Analysis: Use of sophisticated algorithms for noise reduction, feature extraction, and the combination of data sources to create comprehensive environmental models, enhancing decision-making processes. Computational Tools and Methodologies for Aerial Systems: Toolset Proficiency: In-depth training in the use of modern programming language for developing and testing machine learning models. Introduction to software environments and libraries specifically suited for aerial data analysis. Learning Techniques: Detailed examination of supervised, unsupervised, and reinforcement learning paradigms and their applicability to tasks such as predictive modeling, anomaly detection, and adaptive perception in low-altitude contexts. Robust Scene Perception in Dynamic Environments: Scene Analysis: Comprehensive coverage of algorithms for dynamic scene understanding, including visual odometry for tracking vehicle movement and 3D mapping to create detailed environmental representations. Algorithmic Challenges: Discussion of the challenges in implementing these algorithms in low-altitude scenarios, such as dealing with variable lighting conditions, weather impacts, and moving obstacles. Practical Applications in Low-Altitude Aerial Systems: Data-Driven Solutions: Focuses on applying techniques such as pattern discovery, topic modeling, and predictive analytics to enhance navigation and operational decisions in low-altitude environments. Practical Considerations: Discusses scalability and interpretability of machine learning models that are crucial for real-time applications in low-altitude systems. Also, addresses legal, social, and ethical considerations in deploying data analytics in this context.
/ Indicative Syllabus Lower Airspace Regulation and Policy - introduce the lower airspace environment, explore legal and regulatory frameworks governing operations, delve into international standards and best practices, examine airspace management and access, and analyse policy and economic considerations. Stakeholder Interests and Collaboration - focus on analysing the diverse interests of stakeholders involved in lower airspace activities, including operators, manufacturers, regulators, and communities. Students will explore industry perspectives, regulatory perspectives, community concerns, and collaboration strategies for successful integration. Certification and Manufacturing in UAV/eVTOL Development -introduce overview of manufacturing techniques of low- altitude aerial vehicle, understand regulatory frameworks and type certification requirements Reliability and Maintainability Analysis – introduce Reliability analysis -- 1 of 3 -- 2 techniques: Failure Mode and Effects Analysis (FMEA), Weibull Analysis and Reliability Block Diagram approach. Students will be able to determine the life behaviour of a low- altitude aerial vehicle component , calculate the failure rate of a low-altitude aerial vehicle system and provide a cost effective predictive maintenance solutions. Safety
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暂无评分/ Indicative Syllabus Dynamics models: Coordinate systems; Kinematic model; Dynamic model; Six Degrees of Freedom (6-DOF) Equations of Motion; Propulsion system model; Model linearization method. Controller design: Classic flight control system; Modern flight control system; State space modelling; Stability, controllability and observability; State feedback design and optimal control. Planning for autonomous flight: Global path planning methods including search-based methods and sample-based methods; Local smooth trajectory generation methods. -- 1 of 3 -- 2 Autopilot system integration and flight simulation: Open-source flight controller; Onboard computer; Robot operating system; Flight simulation platform; Programming and hardware interface; Implementation of key approaches onboard.
/ Indicative Syllabus 1. Advanced Electronics and System Design for Low-Altitude Systems • Circuit design and optimization for low-altitude vehicles • Embedded systems and microcontroller programming for UAS • Power management and energy efficiency in low-altitude electronics 2. Information Technologies for Low-Altitude Systems • Data processing, storage, and transmission in low-altitude systems • Cybersecurity and data protection in low-altitude applications • Cloud computing and edge computing for low-altitude informatics • Sensor principles and mathematical models: GPS/GNSS, LiDAR, cameras, and IMU • Statistical analysis and mathematical foundations of sensor fusion • Error modeling, uncertainty propagation, and stochastic processes • LiDAR SLAM algorithms and point cloud registration techniques 3. Practical Implementation and Applications • Data collection methodologies and statistical analysis techniques • Non-linear optimization theory and numerical methods • Implementation of SLAM/Navigation algorithm • Practical sensor integration and system validation • Electronic system design for harsh environmental conditions • Regulatory compliance and certification for low-altitude systems • Robot Operating System (ROS) architecture and implementation 4. Challenges and Innovations in Low-Altitude Electronics and Informatics • Harsh environmental conditions and ruggedization • Electromagnetic interference and compatibility • Regulatory compliance and certification • Emerging technologies and future trends in low-altitude electronics and informatics
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