A short description of this session will be provided soon.

Materials adopted in civil, mechanical, automotive, naval, aerospace, and industrial engineering applications are rarely subjected to constant amplitude loading. While standard fatigue assessment is often based on simplified loading assumptions, the structural strength and durability under real-world service conditions, specifically variable amplitude and spectrum loading, remain a major concern in the design of engineering structures. In order to fully optimize design and ensure reliability, understanding and estimating the mechanical performance of materials and structures under complex, random, or block loading histories is of paramount importance. Therefore, the special session entitled “State of the art approaches for fatigue analysis of materials and structures subjected to variable amplitude and spectrum loading” will focus on state-of-the-art theoretical, numerical, and experimental approaches to investigate the fatigue behaviour of materials and structures under variable amplitude loading. Special attention will be dedicated to emerging technologies, specifically the application of Machine Learning (ML) algorithms for life prediction and Digital Twin frameworks for real-time structural health monitoring and prognosis.
 

Structural Health Monitoring (SHM) methods and architectures for damage detection and localization in structural components and assemblies (metallic, composite or hybrid). Techniques based on analytical or/and numerical modeling procedures. Statistical pattern recognition and Machine Learning based methods. Uncertainty quantification in the SHM problem accounting for environmental and operational variability. Approaches for generating structural digital twins. 
 

Additive manufacturing (AM) continues to transform the design and production of materials and components, enabling complex geometries, lightweight structures, and bespoke designs that were previously impossible to achieve with traditional manufacturing methods. However, these new possibilities also bring unique challenges in understanding and predicting the fracture and failure behavior of AM materials, components, and the novel structures and metamaterials being developed for advanced applications.

This special session will focus on the fracture and failure mechanisms of additively manufactured materials, components, structures, and metamaterials. It will explore both the scientific foundations and the practical challenges associated with ensuring the structural integrity of AM-produced parts. 

Topics of interest include:
 

• Fracture mechanics of AM materials and structures: Investigating the influence of microstructure, defects, and residual stresses on fracture behavior, with a particular focus on the unique characteristics of AM-produced parts.
• Failure analysis in AM components: Exploring the different failure modes (e.g., brittle, ductile, fatigue) in various AM processes such as powder bed fusion, directed energy deposition, and material extrusion, and their implications for part reliability.
• Fatigue and durability of AM components/structures: Examining the performance of AM components under cyclic loading and long-term use, and developing strategies to improve the durability of additively manufactured parts.
• Designing for failure resistance in AM structures: Best practices for improving the strength and resilience of AM parts, including material selection, process optimization, and post-processing techniques.
• Metamaterials and innovative structures in AM: The role of advanced materials and structures, such as lattice structures and metamaterials, in improving performance and creating lightweight, high-strength components. Understanding how the unique properties of these materials impact fracture and failure behavior.
• Non-destructive testing (NDT) and in-situ monitoring for AM parts: Investigating the latest techniques for detecting and characterizing defects, cracks, and fractures in AM components during production and service life.
• Case studies and real-world applications: Insights from industries such as aerospace, automotive, biomedical, and energy, where AM materials and metamaterials are being integrated into high-performance and safety-critical components.
• Optimisation and improvements based on case failures identification, 
• other related.

The session aims to bring together researchers, engineers, and industry experts to share the latest advancements in the understanding of fracture and failure mechanisms in AM materials and components, with a special emphasis on the challenges and opportunities presented by new structures and metamaterials. Attendees will gain valuable insights into the state-of-the-art techniques for enhancing the reliability, performance, and safety of additively manufactured parts in demanding applications.

We invite contributions that present new experimental data, theoretical models, or innovative design strategies aimed at improving the fracture resistance and performance of AM structures and metamaterials, as well as addressing the growing need for reliable, high-performance AM components in industry.
 

The session will be a focused discussion on life prediction approaches and models for multiaxial fatigue, fatigue under variable amplitude loading, and fatigue of gradient materials. It will cover both the fundamental fatigue mechanisms and engineering prediction approaches for real world applications.
 

Understanding the fatigue behavior and properties of materials and structures is essential for ensuring their safety in engineering applications. Fatigue studies often require complex simulations, which can be resource-intensive and time-consuming. Recently, machine learning (ML) techniques have demonstrated significant potential in advancing fatigue analysis through accurate and efficient predictions. 
This session seeks to present cutting-edge research on applying machine learning approaches to investigate mechanical behaviors and properties related to fatigue. Topics of interest include, but are not limited to the following:

• Development of machine learning models for predicting fatigue life and damage evolution
• Data-driven analysis of mechanical properties under complex loading conditions
• Fracture surface and microstructure analysis utilizing machine learning methods
• Case studies demonstrating successful machine learning applications in fatigue analysis of components and structures 

We invite submissions from academia and industry that highlight innovative strategies and practical applications of machine learning in the field of fatigue research. We look forward to fostering discussions on the latest advancements and future directions in this exciting area. 
 

The prediction of material failure, encompassing fatigue, fracture, and progressive damage, remains a cornerstone of engineering design and structural integrity assessment. While traditional physics-based models have laid a solid foundation, they often struggle with complexity, multi-scale phenomena, and material uncertainties. The emergence of machine learning (ML) offers a powerful paradigm shift.

However, purely data-driven approaches can lack physical consistency and generalizability.
This session aims to spotlight the latest advancements in integrating mechanistic understanding with ML techniques to create robust, predictive models for failure analysis. We encourage submissions that leverage ML not as a black box, but as a tool to discover, enhance, or accelerate physics-based models. 

Topics of interest include, but are not limited to:

• Physics-informed neural networks (PINNs) for predicting crack propagation and fatigue life.
• ML-enhanced constitutive models for damage and plasticity.
• Multi-scale modeling bridged by machine learning.
• Discovery of failure-related governing equations from experimental or simulation data.
• Fusion of heterogeneous data (e.g., from digital image correlation, acoustic emission, microscopy) for damage state diagnosis and prognosis.
• Uncertainty quantification in ML-predicted failure modes.
   

We seek contributions that demonstrate a synergistic coupling between data-driven methods and the underlying physics of material deformation and failure, ultimately leading to more reliable and trustworthy engineering solutions against failure.
 

Aluminium is widely valued for its light weight, strength, durability, and exceptional recyclability—making it a cornerstone material for sustainable development and circular economy strategies. Unlike many materials, aluminium can be recycled repeatedly without loss of properties, enabling closed-loop material flows for green products across sectors such as construction, automotive, aerospace, offshore structures, and renewable energy.
 

his session will explore the evolving challenges and opportunities in recycled aluminium alloys, focusing on how increased alloying element concentrations from multiple recycling loops influence mechanical properties (strength, ductility, impact toughness), damage tolerance (fracture, fatigue, corrosion-fatigue), and environmental resistance (corrosion behaviour). Furthermore, the session will address how these compositional changes affect manufacturing processes, including casting, forming, extrusion, and joining technologies, and their implications for structural integrity and lifecycle performance.

Key topics include:

• Effect of impurity build-up and alloying variations on microstructure and performance.
• Corrosion, fatigue, and fracture behaviour of recycled aluminium alloys.
• Impact toughness and damage tolerance in demanding applications.Processing challenges: casting defects, formability, extrusion quality, and weldability.
• Recycling-oriented alloy design and optimization strategies for high-performance applications."
   

The occurrence of failures has a major impact on quality, production and environmental health and safety areas of human and industrial activity. Understanding, analyzing and preventing failures result undoubtedly in the reinforcement of expertise and deep knowledge that constitute significant contributors of continuous quality improvement and society benefit.  The scope of this session aims to address and report several paradigms and case studies, where the investigation of fracture and failure of materials and components lead to the exploration and understanding of the failure process as a series of logical/natural stages and interactions of microstructure, properties, processing and environmental/operation conditions, exhibiting a “cause-and-effect” type relationships. The study areas of the Session are mainly focused (but not limited) on critical industrial sectors, such as metallurgical, mining, chemical, manufacturing and automotive. 
The following (but not limited) representative topics are included in the

Session: 

1. Failure and microstructure relationships
2. Genesis of damage at nano-, micro- and meso-scale level
3. Fractography as failure investigation method
4. Texture-failure interactions  
5. Modeling of degradation processes with experimental validation
6. Failures in modern manufacturing
7. Innovative approaches in failure investigation and failure analysis (e.g. AI, machine learning, etc.)
8. Corrosion and environmentally assisted damage
9. Degradation of historical materials and components
10. Process based philosophy and lessons learned approach
     

Fracture-mechanical properties of materials in micro- and nanoscale dimensions have become an important area of fundamental research, including the development and introduction of new techniques for micro- and nanomechanical testing as well as for high-resolution 3D imaging of features in opaque objects. At the same time, there is an increasing need for industry to establish new risk-mitigation strategies based on the understanding of microcrack evolution at small length scales that can cause catastrophic failure in 3D-structured systems and materials, such as leading-edge integrated circuits, advanced battery electrodes, and composites. New design concepts for bio-inspired materials, crack-stop engineering, and the controlled steering of microcracks into regions with high fracture toughness will be discussed.

Sub-topics of the session will be:

• Materials design and modeling/simulation
• Micromechanical tests, microcrack growth, fatigue in metals and composites
• Microcrack imaging using microscopy and tomography techniques
• Interaction of microcracks with materials’ microstructure, energy dissipation mechanisms
• Controlled microcrack steering into toughened regions
• Design of crack-stop structures
• Size and microstructure-dependent metal plasticity
• Natural systems and bio-inspired materials.