Магистр наук в области механической и аэрокосмической инженерии

This graduate level course focuses on technical communication related to the stylistic conventions of writing in science and engineering disciplines, with a focus on clarity, conciseness, and coherence as well as integration of relevant graphics. Students will employ process writing to produce genre specific writing familiar to their academic disciplines, including research-related documents designed for specific audiences. This course also trains students to deliver effective and appealing professional and scientific presentations, with attention to best practices in the use of technical English and oral communication.

The mathematical sub-discipline of differential equations is foundational in the study of applied mathematics for engineers. Differential equations arise in a variety of contexts, some more theoretical and some of practical interest. The qualitative and quantitative study of differential equations incorporates an elegant mixture of linear
algebra and advanced calculus. For this reason, it is expected that the student has already completed courses in (i) linear algebra; (ii) multivariable calculus; and (iii) introductory differential equations.

The course will cover advanced topics of first order and second order ODEs like initial and boundary value problem and stability of solutions and phase portrait of them. A classification will be provided of the various existing types of methods for exploring solutions in connection with the various types of scientific and technological mathematical models that utilize them. The content of the course includes power series techniques as well as the Laplace transformation method for acquiring solutions of ODEs.

Furthermore, PDEs will be studied to model problems involving functions of several variables, and are either solved by hand, or used to create a relevant computer model. PDEs categories will be connected with a wide variety of interesting and important phenomena such as sound, heat, electrostatics, electrodynamics, fluid dynamics, elasticity, or quantum mechanics. All these seemingly distinct physical phenomena can be formalized similarly in terms of PDEs. The content of the course will cover techniques that refer to Elliptic, Parabolic Partial Differential Equations and Hyperbolic Partial Differential Equations as well as Initial and Boundary Conditions. The course will be delivered with lectures that will deliver the necessary theoretical background. However, all the lectures and the tutorials will encapsulate many examples with a software capable to perform symbolical calculations in order to capture the interest and motivate engineers.

This course enables students to gain and apply basic research knowledge and skills to select their research projects in Mechanical and Aerospace Engineering. The course develops the following knowledge and skills:

1. Identifying the area of research interest;
2. Surveying of state of the art for the area of interest;
3. Identifying the research topic and associated issues;
4. Understanding of the social, cultural, global and environmental issues associated with chosen research topic;
5. Writing a research paper based on the literature survey under the supervision of a faculty member;
6. Presentation of a seminar and being assessed by a panel.

This course reviews classical control systems and introduces advanced conventional control methods, state-space representation, and the design of optimal, adaptive, and robust controllers. It introduces the application of Machine Learning and Artificial Intelligence in Modern Control Engineering. The course also introduces hands-on experience and project-based learning techniques. 

This module presents an advanced approach to Computational Fluid Dynamics (CFD) and Heat Transfer (CHT), focusing in problem-solving with applications in Mechanical Engineering. The course will pay especial attention to the overview of fundamental principles, verification and validation of CFD models and deep immersion in applications with scientific and engineering interest, including turbulence, multiphase, heat transfer and interfacial (i.e., microfluidics) phenomena.

This module aims to provide deep understanding of advanced manufacturing terminology and introduces principles, techniques and applications of abrasive and non-conventional machining processes as well as additive manufacturing. Course topic also includes philosophies, and practices developed by world-class manufacturers to meet current manufacturing challenges, such as lean production, push and pull, just in time, continuous flow manufacturing, kanban, plant-floor quality assurance, warehousing, life cycle assessment and ISO-9000 certification. Theory is integrated with hands-on, computational and laboratory modeling of 3D product using specific processes, including the concepts of failure and improved performance. Students are expected to carry out an independent study by project and term paper on the related topics.

This course addresses the primary need for graduate students to undertake formal training that will help them in understanding how to conduct their research. The course will develop students’ understanding of research planning and engender skills enhancement for reading, interpreting, writing about and presenting key ideas. The course will also instill an understanding of a variety of research methods and ethics, as well as implementation of appropriate strategies in lecture and workshop settings.

This subject deals with various numerical techniques to solve ordinary and partial differential equations, especially containing non-linear terms and of relevance in Mechanical Engineering. Emphasis will be placed on the solution of systems of ordinary differential equations, boundary and initial value problems, and, partial differential equations. The use of several types of boundary conditions will be explored, as will several solution methods. The student will need to develop working numerical algorithms on a programming platform (e.g., Matlab, Mathematica, Excel, etc., as indicated by instructor) to solve a variety of engineering applications. Numerical solution will be compared with analytical and experimental results when available and students will explore the principles of validity, accuracy and computational efficiency of their numerical solutions.

This course intends to give students the opportunity to develop the research proposal. The course develops the following knowledge and skills: 1. Preparation of a thorough and comprehensive literature review to support the research proposal; 2. Formulation of the research hypothesis; 3. Developing and justifying the methods to conduct the research. By the 4th week of the semester, the student must submit his/her MSc thesis proposal which will be evaluated by an academic panel, comprising your two supervisors and a third faculty from the Department of Mechanical and Aerospace Engineering appointed by the MSc MAE Committee and approved by the Head of Department. This panel will decide on the appropriateness of your proposed thesis topic and the scientific concreteness of the methodologies you are aiming to apply.

This course intends to give students the opportunity to fully implement the research proposal and bring it to a conclusion. The course develops the following knowledge and skills: 1. Planning and conducting, independently, research at an advanced level. 2. Critically analyzing research results. 3. Effectively presenting their results to a wide audience. 4. Effectively compiling their results in the form of an authoritative thesis.

The concepts of probability theory and statistics contribute extensively to the solutions of many types of engineering problems. According to an analysis conducted by LinkedIn, ‘Statistical Analysis and Data Mining’ is one of the most sought-after skills in the job market. Graduates must have a fundamental knowledge of probability theory and statistics to be competitive in the world market. Advanced Statistics and Probability Theory course will best serve graduate students in all engineering disciplines. The main part of this course aims at bringing the students, who arrive with quite varying backgrounds in statistics and probability, up to the same advanced level. The other part discusses advanced topics (e.g. biomedical statistics).

Unmanned Aerial Vehicle (UAV) Design is a design course that covers the aspects of modern aircraft design for small unmanned and autonomous vehicles. It covers the design of fixed wing and multi-rotor aerial vehicles that can be used for a variety of applications such as parcel delivery, surveillance, environmental monitoring, and mapping. The course integrates the students’ knowledge of aerodynamics and control and introduces the concepts of static and dynamic stability. Students design, build and test conceptual models to affirm the concepts of flight and control. This course aims to:

1. Classify different design concepts for fixed wing (wing/tail, canard/wing, tail-sitter, VTOL, tilt rotor, …) and multi-rotor aerial vehicles
2. Determine appropriate sizing for a vehicle of given specifications using statistical and physics-based methods for a conceptual design
3. Apply principles of static stability for fixed wing to design a stable aerial vehicle and verify the aerodynamic forces and moments to determine the operating envelope using software such as XFLR5
4. Determine aerial vehicle dynamic stability and control effectiveness in Matlab/Simulink for fixed wing and multi-rotor design
5. Assemble conceptual aerial vehicle to determine static and dynamic response, and implement an autopilot controller using an Arduino board

In-depth understanding of fluid mechanics basics and principles. Advanced topics in fluid mechanics delve into the complex and often nonlinear behavior of fluids under a wide range of conditions. These include turbulence, a chaotic and unpredictable flow regime that remains one of the most challenging problems in physics and engineering, and compressible flow, where changes in fluid density, especially at high speeds, become significant, as seen in aerodynamics and supersonic flight. Multiphase flows, involving mixtures of gases, liquids, and solids (e.g., bubbles, droplets, or slurries), are vital in chemical processing and environmental studies. Computational Fluid Dynamics (CFD) is a key tool for simulating these complex flows using numerical methods to solve the Navier-Stokes equations. Other advanced areas include non-Newtonian fluid behavior, where viscosity depends on stress or strain rate (common in biological and industrial fluids), magnetohydrodynamics (MHD), which examines electrically conducting fluids in magnetic fields, and microfluidics, which studies fluid behavior at the microscale, with applications in lab-on-a-chip technologies and biomedical devices. These topics require a deep understanding of mathematics, physics, and numerical modeling.

The course will cover:

Transport Energy: Introduction of the ideas of energy security; the impact of shortages; transport policy.

Transport and the Urban Environment: Emerging issues, territorial occupation, economic systems, social preferences, environmental system, impacts and activities.

Internal Combustion Engines (IC): Will concentrate on Petrol and Diesel engines. How these engines work plus their advantages and disadvantages
Emissions due to IC Engines: A description of typical emissions and their impact. How a lower emission impact can be achieved. A summary of how each stage in a vehicle’s life-cycle influences emissions.

Cleaner Conventional Vehicle Technologies: Introduction of the concept of hybrid technologies and fuel consumption reduction. Advantages and disadvantages will be highlighted.

Fuels with less Carbon: A review of compressed natural gas (CNG), liquefied petroleum gas (LPG) and bio-fuel systems for vehicular transport.

Electric Vehicles: An overview of the current status of electric vehicles (EVs), ‘plug-in’ hybrid electric vehicles (HEVs) and fuel-cell powered vehicles (FCPVs). The need for a substantial supply infra-structure is included.

De-carbonized Transport: A review of the various pathways for de-carbonization of several transport scenarios. This will include looking at the lowest tail-pipe emissions and the various life-cycle emissions which each technology accrues.
Recycling and Disposal: Methods of recycling and disposing of the scrappage originating from vehicular transport will be investigated.

The course will involve considerable laboratory work and five major projects (Group and Individual). The assessment strategy will lie mainly in assessing these projects.

The course aims to introduce students to the fundamentals of optimization theory. Specifically, the course aims to introduce students to the dynamic field of finding the local and/or global extrema of functions. The students will be able to learn concepts such as unconstrained and constrained optimization, convex and nonconvex optimization, gradient-based, stochastic, and mixed optimization, single shooting, multiple shooting, collocation, differential inclusion methods, homotopy optimization, direct and indirect methods, dynamic programming, linear and quadratic programming problems, etc.

After completion of the course, the students will be able to:

1. Explain the importance of optimization theory in engineering and science.
2. Know different methods of solving an optimization problem.
3. Understand the necessary and sufficient conditions for optimal solution.
4. Formulate and solve constrained and unconstrained optimization problems.
5. Interpret the obtained solution and be aware of its shortcomings.

The presented methods and techniques may be applied in a great number of fields, including aerospace engineering, automotive design, naval architecture, modern architecture, financing, electronics, computers, and electricity distribution and thus, equips the graduate student with a global perspective and tools that can be applied in the competitive, multidisciplinary engineering world.

The course covers classical optimization formulations & methods, heuristic search methods (simulated annealing, genetic algorithms, particle swarm optimization, and others) and multi-objective optimization along with Pareto optimality.

"The course provides deeper knowledge of applied aerodynamics by focusing on computational methods and unsteady flows. During the course, students first review fundamentals of ideal aerodynamics and then extend the scope to include computation of aerodynamic forces for arbitrary streamlined bodies using different panel methods. The course also covers boundary layer corrections to account for viscous drag. Corrections for high speed are also discussed by introducing various compressibility corrections. Unsteady ideal aerodynamics is introduced to examine the effects of sudden plunging, periodic heave and pitching of airfoils.

This course aims to:

• Derive governing laws for fundamental of ideal irrotational flows for ideal aerodynamics.
• Apply singularity models to determine the flow fields for simple flows and introduce the concepts of lift generation and circulation.
• Apply panel methods (source and vortex) for simple geometries to compute the aerodynamic forces for arbitrary streamlined shapes and to compare results with published experimental data.
• Implement unsteady panel codes to investigate unsteady aerodynamic forces for sudden motion caused by plunging, flapping, or pitching
• Apply boundary layer theory to determine significance of viscous drag forces and predict results for laminar and turbulent flow regimes and investigate benefits of flow control by coding simple interactions of boundary layer flows with mean inviscid flows using Polhausen techniques."

This course will immerse students in a Concurrent Engineering Design environment (Machine Design Laboratory), where they will be working on the design of various Space Structures in the context of running research projects in a workshop-project format. Students will become intimately acquainted with bleeding edge space technologies, such as gyroscopic systems, vibration damping systems, satellite structures, composites, honeycombs, truss-cores and nanomaterials. By the end of the course students will be able to perform design of these kinds of space structures.

Students will make advanced use of engineering software COMSOL, ANSYS, Mathematica, etc and rapid prototyping facilities provided by FabLab.

The concepts of probability theory and statistics contribute extensively to the solutions of many types of engineering problems. According to an analysis conducted by LinkedIn, ‘Statistical Analysis and Data Mining’ is one of the most sought-after skills in the job market. Graduates must have a fundamental knowledge of probability theory and statistics to be competitive in the world market. Advanced Statistics and Probability Theory course will best serve graduate students in all engineering disciplines. The main part of this course aims at bringing the students, who arrive with quite varying backgrounds in statistics and probability, up to the same advanced level. The other part discusses advanced topics (e.g. biomedical statistics).

This course is designed to provide graduate students with fundamental knowledge and modeling techniques in the most important fields of space flight dynamics, namely, orbital mechanics, rocket vehicle dynamics, and spacecraft attitude dynamics. The whole course will be delivered through a mathematical software package capable of performing symbolical and numerical calculations. With a strong emphasis on scientific problem-solving using programming, this course equips students with the knowledge and skills necessary to become specialists in the field of space engineering.

The course aims to introduce the students to an important and complicated topic in engineering: Fluid Structure interaction (FSI) and its analysis by computational simulation. The students will learn to understand the physics, methods and models available for the study of FSI and how to apply them in engineering applications.

Digital transformation of manufacturing industry is essential to gain competitive advantages. This course aims to provide a systematic understanding and knowledge of key concepts and principles for digital transformation and its current practices, tools and processes and future development. The course will also provide hands-on experience using digital transformation tools and methods to enhance product development and enterprises. The course topics include digital tools, methods to support continuous improvements, design for Industry 4.0, enterprise systems, smart product, virtual and augmented reality (VR&AR), digital twin for product development, model based definition/enterprise, lean digital workflow for product development, and digital transformation industrial case studies.

This course teaches the latest advances in engineered materials, with a particular focus on high-performance nanomaterials. Their applications in electronics, aerospace, automotive and human-machine interaction are being studied. The course discusses the properties and characteristics of nanomaterials, their integration with polymers, metals and fibre metal laminates and improving their mechanical performance and functional properties. It also teaches how to use machine learning tools and numerical modeling methods to predict mechanical behavior of composite materials.

Advanced Systems Engineering is essential in developing complex mechanical and aerospace systems in Industry 4.0 environment. Systems engineering process starts at the early stages of a system life cycle including requirements, design, manufacturing, operation and recycling. This course aims to provide mechanical and aerospace engineering graduates with the essential knowledge of advanced systems engineering and its methods, process and tools needed to address the challenges of designing and developing today’s complex engineering systems.

This course is designed to introduce fundamental aspects of rocket propulsion to graduate students. The course builds on a basic knowledge of thermodynamics, including combustion and gas dynamics, all of which are initially reviewed. This is followed by the basic elements of rocket propulsion, introducing performance parameters and important components of a rocket propulsion system. Different types of propellants will be introduced and discussed, including the important non-chemical propellants. The performance of space flight for several flight regimes, namely atmospheric flight, near-space flight and deep-space flight are analysed.