Mechanical Engineering

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Research Topic Summary.

Adaptive composite structures represent a significant advancement in engineering, holding the potential to create more efficient, sustainable, and safer systems across various industries. By incorporating smart materials, sensors, and actuators, these structures can dynamically respond to environmental changes, optimizing performance while minimizing energy consumption and reducing maintenance requirements. The scientific problems at the core of this topic lie in selecting suitable smart materials, modelling their performance under different conditions, integrating them into composite structures, and ensuring their long-term durability, responsiveness, and efficiency in real-world applications.

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Research Topic Summary.

The objective of the proposed work is to investigate the influence of specimen size and geometric parameters on fracture mechanic parameters and crack growth. Both experimental and numerical modelling studies are planned. The finite element method will be used for numerical modelling. A comparison between numerical modelling and experimental results is planned in order to validate the developed methodology. The novelty of the proposed study lies in the development of a methodology for research fracture behaviour using numerical modelling methods.

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Research Topic Summary.

Biomimetic materials are synthetic or modified natural materials inspired by biological systems to replicate their structure, function, and properties for technological applications. These materials use nature's solutions to solve problems in fields such as medicine, construction, and engineering. The topic of the dissertation research covers the development of biomimetic materials, their characterization and application in real mechanical systems.

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Research Topic Summary.

Diverse drone platforms (ground/aerial/marine robotic vehicles) are increasingly used in defense and civilian applications such as surveillance, environmental monitoring, infrastructure inspection, etc. However, the platforms are mostly produced with passive structural components (chassis, supports, covers, wings, etc.) that lack monolithic integration of electronic subsystems to improve compactness, reliability and multifunctionality. High-performance platform architectures rely on 3D Mechatronic Integrated Devices (3D-MID) to reduce wiring, weight and bulkiness. More advanced 3D-MID components also contain embedded active devices such as multi-modal sensors and nanogenerators. They enable self-diagnostics and vibration energy harvesting to make platforms more robust and energy efficient. Highly customized 3D-MIDs may be rapidly fabricated using multi-material extrusion-based additive manufacturing (MEX AM) to print both soft and hard structural or electronic materials (e.g. composites with conductive, ferroelectric, dielectric, magnetic and other performance-enhancing active fillers). Easily configurable MEX AM process would enable direct co-integration of diverse sensors and nanogenerators into platform components. Development of such monolithic additive process will contribute to faster development of easily customizable, more autonomous and resilient drone platforms, promoting sustainability via reduced material and energy use. The PhD project aims to develop an effective MEX AM process for monolithic additive fabrication of 3D-MID components with structure-integrated sensors and nanogenerators. Key objectives include: i) qualification of co-printed heterogeneous electronic materials for durable 3D-MID components; ii) development and validation of integrated FFF/FGF/DIW-based workflow for monolithic rapid fabrication; iii) implementation of DfAM methodology, 3D-MID prototyping and performance optimization of structure-embedded sensors and nanogenerators.

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Research Topic Summary.

Research focuses on the advanced design and optimisation of laser-textured surfaces to improve the performance of materials under challenging conditions. By combining advanced experimental techniques, state-of-the-art computer modelling and AI-driven optimisation, this multidisciplinary effort aims to substantially change the application of laser surface texturing (LST) in various industries.

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Research Topic Summary.

Robotized production lines are becoming increasingly complex, yet many non-standard failures are still resolved by humans. This research will examine how operators use creative problem-solving to handle unexpected robot malfunctions and how these insights can be integrated into new, smarter diagnostic and support technologies. The study aims to improve human–robot cooperation, reduce production downtime, and enhance the reliability of modern automated manufacturing lines.

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Research Topic Summary.

This PhD topic focuses on smart polymers that allow mechanical structures not only to withstand loads, but also to “sense” their environment, damp vibrations or even harvest energy. The doctoral student will work with advanced testing equipment, design and test polymer elements, and apply measurement techniques such as digital image correlation. A substantial part of the work will involve developing and validating finite element models, providing an excellent opportunity to strengthen numerical modelling and programming skills. The research outcomes will be relevant to lightweight structures, robotics, biomechanics, transportation and other engineering fields where mass, reliability and adaptivity are crucial. The topic is well suited for a motivated student willing to combine experimental work with numerical simulations and to contribute to the development of the next generation smart mechanical structures.

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Research Topic Summary.

Additive manufacturing (AM) technologies enable the production of complex, lightweight components with tailored material properties. However, rapid thermal cycles and high temperature gradients during layer-by-layer fabrication induce significant residual stresses, which may critically affect the mechanical performance, dimensional stability, and fatigue life of additively manufactured materials and structures. The main objective of this research is to investigate and quantify the influence of process-induced residual stresses on the fatigue behaviour and structural integrity of AM materials, focusing on metallic and composite components. The study will combine experimental and numerical methods to evaluate how residual stresses evolve during manufacturing and how they contribute to crack initiation and propagation under cyclic loading. Experimental investigations will include residual stress measurement using digital image correlation (3D-DIC), and mechanical testing under various loading conditions. Finite element models incorporating residual stress distributions will be developed to simulate stress–strain response and predict fatigue life. The results will be compared with experimental fatigue data to validate the predictive capability of the models. Expected outcomes include a comprehensive understanding of the relationship between manufacturing parameters, residual stresses, and fatigue performance; improved numerical models for life prediction; and guidelines for reducing detrimental residual stresses to enhance the durability and reliability of additively manufactured components.

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Research Topic Summary.

The proposed topic aims to develop an intelligent biomechatronic system that uses magnetorheological fluids (MRF) and muscle activity (EMG) signals to adapt to human movements in real time. This technology can be applied in rehabilitation trainers, exoskeletons, and human–machine interfaces, ensuring improved treatment efficiency, comfort, and personalization.

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Research Topic Summary.

Development of versatile physical field-activated additive manufacturing (FAAM) technology for multi-process 3D printing of monolithic (assembly-free) smart structures with structural and electronic composites is a key driver of several disruptive technologies: multi-material 3D/4D printing, integrated soft robotics and piezoelectronics, 3D-MID with structure-embedded sensors/nanogenerators for structural health monitoring (SHM). FAAM process may be implemented by augmenting multi-process 3D printing (FFF/FGF/DIW) with field-activated processing, e.g. applying photonic or electric fields to enhance print properties via sintering, poling, etc. The process should be optimized to ensure repeatable manufacturability of durable self-sensing lightweight structures with directly embedded functional layers (electro-/magneto/thermo-active, conductive, etc.). To achieve scalability and environmental sustainability, electronic composites should be fabricated as filaments or granules using solvent-free melt extrusion of (bio)polymers filled with tailored fractions of ceramic, metal or nanocarbon particles. Durability of self-sensing lightweight structures is crucial in performance-critical applications such as autonomous systems or medtech devices. Therefore, FAAM process should provide design freedom to enable consistent and cost-effective on-demand printing of customizable and resilient smart structures with embedded electronic functions (e.g. vibration sensing and energy harvesting). The aim of the PhD project is to develop FAAM process for fully additive fabrication of monolithic multi-composite self-sensing structures. Key objectives include: i) development of composite feedstock (filaments, granules) with tailored multifunctional properties; ii) implementation of multi-process 3D printing workflow augmented with photonic and/or electrical processing steps; iii) design, prototyping and performance testing of 3D-printed electronic composites and self-sensing structures.

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Research Topic Summary.

The effectiveness and competitiveness of engineering enterprises largely depend not just on the main technological processes but also on the utility processes used to ensure a reliable supply of energy, materials and other resources and reliability and quality of technological equipment and other assets. The aim of this research will be to create a methodology that enables the use of big-data analytics and decision support systems, and prognosing the effects of company’s internal and external events on utility processes, with the objective of improving their resilience to changes together with the effectiveness of the whole enterprise.