The course ‘Digital Twins for Engineering Structures’ is aimed at providing an overview of the development of digital twin technology for application to the design, synthesis and optimisation of engineering structures, specifically lightweight aerospace composite structures and additive manufactured structures. The course outlines the efficiency and benefits of Digital Twin Technology (DTT) for the design, optimisation, and predictive maintenance of lightweight engineering strictures in aerospace, transport, marine, and machinery sectors. Several case studies, for example, damage tolerance optimisation of aircraft structures, structural health monitoring and diagnostics, predictive maintenance for a bridge or aircraft component, and fatigue assessment of additive manufactured components, are incorporated to demonstrate the real-life application of digital twin technology. Learning Objectives • Introduce the overview of Digital Twin Technology (DTT) in the context of engineering design of structures. • Describe the steps in setting up digital twins for engineering structures, including system models, sensor data collection, real-time integrations, and visualisation of virtual models. • Understand the theory and operating principles of commonly used structural modelling and simulation tools for multi-physics analysis of components and their integration for system analysis. • Describe current and emerging applications of digital twins for the design and analysis of engineering structures, including lightweight composite and additively manufactured structures, • Describe the transformative approach to managing engineering composite structures throughout their lifecycle, improving their design, performance, and sustainability that combines real-time data, advanced simulations, and predictive analytics. • Demonstrate awareness of the relationship between digital twins and recent technological developments in aerospace, transport, automotive and marine industries.

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The course ‘Digital Twins for Engineering Structures’ is aimed at providing an overview of the development of digital twin technology for application to the design, synthesis and optimisation of engineering structures, specifically lightweight aerospace composite structures and additive manufactured structures. Guest lecturer: - Raj Das ( Professor at Royal Malbourne Institute of Technology): He is a Full Professor of Applied Mechanics and Aerospace Engineering and the Group Leader of the Simulation of Advanced Materials and Structures (SAMS) Group at the Sir Lawrence Wackett Defence and Aerospace Centre, School of Engineering, RMIT University, Melbourne, Australia. His research interests focus on computational mechanics, finite element methods, additive manufacturing, structural optimization, composite materials, and damage tolerance analysis, among other topics. He completed his Ph.D. in Mechanical Engineering (Solid Mechanics) at Monash University, Australia, in 2005, where he developed a structural optimization formulation based on damage tolerance. He earned his Bachelor of Engineering in Mechanical Engineering from Jadavpur University, India, with First Class Honours. Prior to joining RMIT University in 2021, he served as a Senior Lecturer at the University of Auckland, New Zealand, and held research and senior roles at CSIRO in Melbourne, Australia, and the University of Manchester in the UK. Dr. Das has also contributed to defence research with the Defence Research and Development Organisation (DRDO) in India. His current research includes a wide range of topics such as fracture mechanics, fatigue, impact mechanics, and the study of metamaterials, auxetic materials, and functionally graded materials.

On site

Oral presentation

P.D.1-1 - January

Timetable : Day 1: Lecture 1 (2 hours): 8 January (10:00 – 12:00) - Sala DIMEAS P.T. Module 1: Introduction to Digital Twins in Engineering 1.1 What are Digital Twins? • Definition and overview of digital twins. • Evolution of digital twins: From static models to dynamic digital counterparts. • Key components of a digital twin: Data, models, simulations, and real-time feedback loops. 1.2 Digital Twins in Engineering and Structures • Applications of digital twins across industries. • Benefits of digital twins for structural analysis and lifecycle management. • Key challenges and limitations. Day 1: Lecture 2 (2 hours): 8 January (14:00 – 16:00) - Sala Ferrari Module 2: Fundamentals of Engineering Structural Design – Composite Structures and Damage Tolerance Analysis 2.1 Structural Design Considerations for Composites • Design principles specific to composite structures. • Load paths, stress concentration, and fatigue behavior in composites. • Failure mechanisms and degradation of composite materials over time. 2.2 Basic Concepts of Airframe Damage Tolerance • Damage tolerance philosophy • Damage tolerance (civil aviation) FAR regulations • Damage tolerance (military) MIL standard 2.3 Design Approaches for Structural Integrity • Static strength, Fatigue (safe-life design versus damage tolerance), • Damage tolerance: slow crack growth and fail-safe • Safety-by inspection using examples Day 2: Lecture 1 (2 hours): 9 January (10:00 – 12:00) -Sala Ferrari Module 3: Building a Digital Twin for Structural Systems 3.1 Conceptual Framework for Digital Twins in Structures • How to model structures: Physical and digital environments. • Role of sensor data and real-time updates in a digital twin. 3.2 Integrating Digital Twins with Structural Systems • Connectivity: Edge computing, IoT platforms, and cloud infrastructure. • Simulation tools and FEM (Finite Element Method) integration. • Challenges in real-time data integration and processing. 3.3 Virtual Testing and Simulations • Simulating real-world loading conditions and environmental factors. • Failure prediction in composite materials using simulations. • Optimizing the design and performance of structures through iterative testing. Day 2: Lecture 2 (2 hours): 9 January (14:00 – 16:00) - Sala Ferrari Module 4: Simulation and Modeling for Digital Twins 4.1 Finite Element Analysis (FEA) for Structural Simulations • Introduction to FEA principles and applications. • Simulating structural behavior under different load conditions: Static, dynamic, thermal, and impact loading. • Case study: FEA of an aircraft wing. 4.2 Testing and Optimizing Structural Design with Digital Twins • Iterative design using digital twins: Optimizing material use, load-bearing capacity, and safety factors. • Virtual prototyping and testing to enhance structural resilience. • Case study: Optimizing the design of a composite structure using a digital twin. Day 3: Lecture 1 (2 hours): 10 January (10:00 – 12:00) Sala Ferrari Module 5: Artificial Intelligence, Machine Learning, and Digital Twins 5.1 Machine Learning Basics for Structural Applications • Introduction to machine learning techniques relevant to digital twins. • Supervised vs. unsupervised learning for anomaly detection. 5.2 Predictive Analytics in Structural Engineering • How AI and machine learning analyze structural health data. • Predicting fatigue, crack propagation, and failure in composite materials. • Data-driven decision-making and optimization for maintenance and repairs. 5.3 Artificial Intelligence and Machine Learning in Digital Twin Development • Introduction to AI techniques for digital twins. • Supervised vs. unsupervised learning for predictive modeling. • Applications of AI in structural health monitoring and optimization. • Case study: Machine learning-driven maintenance for an industrial structure. Day 3: Lecture 2 (2 hours): 10 January (14:00 – 16:00) Sala Ferrari Module 6: Applications and Industry Case Studies 6.1 Aerospace Structures and Digital Twins • Aircraft fuselage, wings, and composite components. • Using digital twins to predict and mitigate structural failure. 6.2 Automotive and Transportation • Lightweight composite parts and their lifecycle management. • Digital twin models for vehicle crash testing, durability, and repair optimization. ASSESSMENT : A quiz on day 3 with multiple choice and/or short answer questions. A basic report on ‘Future developments in digital twins for composite structures’. The student can write their own perspectives.