Syllabus

Overview

Nowadays, machine learning methods are increasingly used in many engineereing branches, such as mechanical and aerospace, for data analysis, modelling, identification, and prediction. This course provides an introductory overview of machine learning and deep learning methods, with particular emphasis on their application to vibroacoustic problems.
The course first introduces the main concepts of supervised machine learning, including data preparation, training, validation and testing, model evaluation, and overfitting. Artificial neural networks are then presented, starting from multi-layer perceptrons and extending to convolutional and recurrent neural networks. Transformer architectures are introduced at a conceptual level, with particular attention to encoder-based models.
The final part of the course focuses on representative vibroacoustic applications and practical examples implemented in Python using commonly adopted machine-learning libraries.
By the end of the course, participants will be familiar with the main machine learning workflows and neural-network architectures used in engineering applications and will be able to approach basic machine-learning problems using existing Python tools.

Learning objectives

• Fundamentals of machine learning: supervised learning, data preprocessing, training, validation, testing, overfitting, and model evaluation.
• Artificial neural networks and the main characteristics of multi-layer perceptrons, convolutional neural networks, recurrent neural networks, and transformers.
• Basic machine learning workflows implemented in Python using libraries such as Scikit-Learn and PyTorch.

Target Audience

Master students, doctoral students, non-academic professionals

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Syllabus

Overview

This webinar provides a focused introduction to hydrogen combustion for aeronautical propulsion, addressing the main scientific and engineering challenges associated with the use of hydrogen in future aircraft engines. The course is intended to offer a compact but rigorous framework for understanding how hydrogen differs from conventional aviation fuels and how these differences affect combustion behaviour, ignition, emissions, operability, and system integration.
The webinar covers the main combustion-related properties of hydrogen relevant to aeronautics, including high flame speed, wide flammability limits, low ignition energy, diffusivity, flashback tendency, and NOₓ formation issues under high-temperature conditions. These aspects are linked to practical design implications for combustors and propulsion systems, with emphasis on lean combustion strategies, flame stabilization, ignition reliability, and low-emission operation.
The course is structured to include both hard technical content and practical engineering reasoning. Participants will be guided through simplified examples comparing conventional and hydrogen-fueled combustion systems, with attention to performance–emissions trade-offs, safety aspects, and aircraft-level integration constraints. A short hands-on section will involve discussion of design-oriented case studies, encouraging participants to reason critically on the opportunities and limitations of hydrogen-powered aviation. The webinar is especially suitable for PhD students, but is also relevant for graduate students, researchers, and professionals interested in sustainable aerospace propulsion.

Learning objectives

At the end of the webinar, attendees will be able to:

• understand the main combustion properties of hydrogen relevant to aeronautics;
• identify the key technical challenges of hydrogen-fueled aircraft propulsion;
• explain the main trade-offs between operability, emissions, safety, and performance;
• apply structured engineering reasoning to simplified hydrogen-combustion case studies.

Target Audience

• PhD students in aerospace propulsion, combustion, and energy engineering
• MSc students interested in sustainable aviation
• Researchers and professionals working on hydrogen and advanced propulsion systems

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Syllabus

Overview

The aim of this webinar is to deal with the main criticisms related to acoustic simulation and noise suppression in the aerospace sector. This objective is achieved by initially introducing and discussing the state-of-the-art methods and technologies that are relevant to this field. Subsequently, the fundamentals of analytical (Transfer Matrix Method) and numerical (Wave Finite Element Method) approaches are illustrated, which constitute powerful and efficient techniques to estimate the absorption and transmission properties of a sound package. Lastly, some innovative acoustic meta-material configurations are presented, based on a periodic pattern of porous unit cells, whose main homogenization models are defined and discussed too. These topics address different applications not only in the aerospace industry, but more generally in transportation (automotive, railway), energy and civil engineering sectors, where both weight and space, as well as vibroacoustic comfort, still remain as critical issues.

Learning objectives

• Aircraft noise: methods and technologies
• Transfer Matrix and Wave Finite Element Methods in acoustics
• Acoustic characterization of porous meta-materials

Target Audience

Master students, doctoral students, non-academic professionals

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Composites’ design cannot use extensions of the methodologies adopted for metals. Such a strategy may lead to oversizing, let alone the risks arising from a wrong design. Composites are more complex material systems than metals due to their multiscale nature. Brittle orthotropic fibers, ductile isotropic matrices, and soft cores coexist.  Such complexity leads to challenging predictive models, e.g., to detect composite structures’ damage and failure mechanisms, which is still far from reliable predictions via virtual models and needs high computational costs, precluding structural engineering calculations. Uncertainties in the models lead to safety factors and tests. Therefore, the full spectrum of composites’ advantages is not exploitable, and costly experimental tests are necessary.

This webinar reviews the mechanical behavior of composites and highlights modeling challenges. It highlights limitations of standard finite element techniques and presents approaches to improving solutions. It also introduces structural theories and detailed methods for developing them. Numerical examples concerning linear analysis, failure index evaluations, and structural dynamics provide guidelines on the proper modeling. Extensions to nonlinear analysis, process simulation, and multiscale analyses are also presented.

Learning objectives:

• Mechanical behavior of composite structures
• Review of theories of structures
• Structural theories for composites
• 1D and 2D finite elements
• Guidelines for modeling
• Basics of multifield analysis, multiscale modeling, failure analyses, and process simulation

Target audience: doctoral students, non-academic professionals, and undergraduate students.

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Overview and General Information:

Dynamic testing is essential in the design and qualification of aerospace hardware. It serves diverse purposes, from characterizing dynamic responses at different system levels to evaluating hardware performance under operational loads. Vibration testing is fundamental for correlating and updating numerical models used in aerospace product design and validation. Environmental dynamic testing aims at replicating real conditions, such as in-flight or transport scenarios, in laboratory settings to ensure systems will perform as expected throughout their operational lifetime. With the emergence of disruptive aerospace systems and increasingly competitive markets, the industry demands innovations in practices that have remained mostly unchanged for decades.

This webinar presents recent advances in dynamic testing of aerospace hardware. It provides an overview of the topic and explores key innovations that address industry demands. The presentation covers various testing practices including vibration control, multi-axis testing, shock testing, virtual shaker technology, ground vibration testing, and flight testing. Additionally, it describes how digital twins can improve and de-risk test campaigns in these applications.

Learning Objectives:

• Overview of dynamic testing practices of aerospace hardware
• Vibration testing in shaker platforms: current practices and new trends
• Testing of aircraft structures: from GVT to flight testing
• The role of Digital Twins in dynamic testing

Target audience

Master’s students, doctoral students, academic and non-academic professionals

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The course offers a thorough overview on the emerging topic of deep learning for computer vision and egomotion estimation. Such technique is extremely useful to carry out the task of spacecraft relative navigation in proximity operations, e.g. during planetary approaches, landing or rendezvous. The course is intended to provide a solid theoretical knowledge together with the exploration of the latest state-of-the-art techniques.

The seminar is organized in lectures, demos and small workshops. Lectures are passive (from the student’s point of view). Demo sessions are used to demonstrate and run state-of-the-art implementation of some algorithms. Workshop sessions are used to get acquainted with the most famous CV and DL libraries (openCV, pyTorch, etc.).

Learning objectives: Introduction to Computer Vision, Introduction to Deep Learning, Convolutional Neural Networks, Multi-view geometry and Relative Navigation

Target audience: doctoral and master students, non-academic professionals.

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Spacecraft attitude equations are usually given by nonlinear equations. However, spacecraft attitude control laws are often designed using a linear approximation of those equations about an operating condition. Thus, the effectiveness of the control laws can be guaranteed only for attitude angles and angular velocities close to the operating condition. There are occasions when the spacecraft motion involves attitude angles and angular velocities that are far from the operating condition. For those motions, the full nonlinear attitude equations must be used for evaluating the effectiveness of the control laws. This course presents the design of attitude control laws for two typical spacecraft operations along with basic tools that are useful to validate the design with nonlinear attitude equations.

Learning objectives: Learning control laws for spacecraft detumbling and spacecraft attitude regulation. Learning mathematical tools for validating attitude control laws using nonlinear attitude equations.

Target audience: doctoral and master students, non-academic professionals.

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Participation

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Overview and General Information:

The aim of this webinar is to deal with the main criticisms related to acoustic simulation and noise suppression in the aerospace sector. This objective is achieved by initially introducing and discussing the state-of-the-art methods and technologies that are relevant to this field. Subsequently, the fundamentals of analytical (Transfer Matrix Method) and numerical (Wave Finite Element Method) approaches are illustrated, which constitute powerful and efficient techniques to estimate the absorption and transmission properties of a sound package. Lastly, some innovative acoustic meta-material configurations are presented, based on a periodic pattern of porous unit cells, whose main homogenization models are defined and discussed too. These topics address different applications not only in the aerospace industry, but more generally in transportation (automotive, railway), energy and civil engineering sectors, where both weight and space, as well as vibroacoustic comfort, still remain as critical issues.

Learning Objectives:

• Aircraft noise: methods and technologies
• Transfer Matrix and Wave Finite Element Methods in acoustics
• Acoustic characterization of porous meta-materials

> Download Course Brochure

Participation

You need to buy one of the package list available here and use the Order ID assigned to you after purchase.
You need to Login for registration.