Full-time study

4 years

prof. Ing. Martin Hartl, Ph.D.

Chairman :
prof. Ing. Martin Hartl, Ph.D.
Councillor internal :
prof. Ing. Petr Stehlík, CSc., dr. h. c.
prof. Ing. Josef Štětina, Ph.D.
prof. Ing. Jiří Pospíšil, Ph.D.
doc. Ing. Petr Blecha, Ph.D., FEng.
prof. Ing. Pavel Hutař, Ph.D.
prof. Ing. Radomil Matoušek, Ph.D.
doc. Ing. Jaroslav Katolický, Ph.D.
doc. Ing. Jaroslav Juračka, Ph.D.
Councillor external :
Ing. Jan Čermák, Ph.D., MBA

The main goal of the doctoral study programme is, in accordance with the Higher Education Act, to train highly qualified and educated professionals who are capable of independent scientific, research and creative activities in the field of design and process engineering. The graduates are equipped with knowledge and skills that enable them to work at Czech or international academic institutions or research institutes. The programme focuses on theoretical knowledge as well as practical experience in the field of doctoral studies. Cooperation with international research institutes is highly supported. The study programme is designed to fulfil demands and meet societal and industry requirements for highly educated and qualified professionals in the fields of design and process engineering.
Doctoral study programme is primarily based on research and creative activities of doctoral students. These activities are intensively supported by student participation in national and international research projects. Research areas include design (analysis, conception, design of machinery, vehicles, machine production and energy) and process engineering (analysis, design and projection of processes in the engineering, transport, energy and petrochemical industries).

A graduate of the doctoral study programme is a highly qualified expert with broad theoretical knowledge and practical skills, which enables him/her to carry out creative and research activities both independently and/or in a scientific team. The graduate is acquainted with current findings in the field of design and process engineering and is able to apply the knowledge in his/her research or creative activities. The graduate is also able to prepare a research project proposal and to oversee a project. At the same time, the graduate is able to make use of theoretical knowledge and transfer it in practice. Moreover, the graduate can adapt findings from related disciplines, cooperate on interdisciplinary tasks and increase their professional qualifications. The graduate participation on national and international researches and cooperation with international research institutions contributes to higher level of their professional competences. This experience allows graduates not only to carry out their own scientific activities, but also to professionally present their results, and to take part in international discussions.
The graduate can demonstrate knowledge and skills in three main areas and the synergy produces great outcomes.
1. Broad theoretical knowledge and practical skills closely related to the topic of the dissertation (see below).
2. Professional knowledge and skills necessary to carry out scientific work, research, and creative activities.
3. Interpersonal and soft skills and competencies - the graduate is able to present their ideas and opinions professionally, is able to present and defend the results of their work and to discuss them and work effectively in a scientific team or to lead a team.
According to the topic of the dissertation, the graduate will acquire highly professional knowledge and skills in mechanical engineering, in particular in design and operation of machines, machinery, engineering processes and vehicles and transport vehicles. Thanks to the broad knowledge and skills, graduates can pursue a career in research institutes in the Czech Republic and abroad, as well as in commercial companies and applied research.

A graduate of the doctoral study programme is a highly qualified expert with broad theoretical knowledge and practical skills, which enables him/her to carry out creative and research activities both independently and/or in a scientific team. The graduate is acquainted with state-of-the-art findings in the field of design and process engineering and is able to apply the knowledge in his/her research or creative activities. The graduate is also able to prepare a research project proposal and to oversee a project. At the same time, the graduate can make use of theoretical knowledge and transfer it in practice. Moreover, the graduate can adapt findings from related disciplines, cooperate on interdisciplinary tasks and increase their professional qualifications. The graduate typically finds a job as a researcher, academic personnel, computer scientist or designer. The graduate is also well equipped with skills and competences to perform well in managerial positions.

See applicable regulations, DEAN’S GUIDELINE Rules for the organization of studies at FME (supplement to BUT Study and Examination Rules)

The rules and conditions of study programmes are determined by:
BUT STUDY AND EXAMINATION RULES
BUT STUDY PROGRAMME STANDARDS,
STUDY AND EXAMINATION RULES of Brno University of Technology (USING "ECTS"),
DEAN’S GUIDELINE Rules for the organization of studies at FME (supplement to BUT Study and Examination Rules)
DEAN´S GUIDELINE Rules of Procedure of Doctoral Board of FME Study Programmes
Students in doctoral programmes do not follow the credit system. The grades “Passed” and “Failed” are used to grade examinations, doctoral state examination is graded “Passed” or “Failed”.

Brno University of Technology acknowledges the need for equal access to higher education. There is no direct or indirect discrimination during the admission procedure or the study period. Students with specific educational needs (learning disabilities, physical and sensory handicap, chronic somatic diseases, autism spectrum disorders, impaired communication abilities, mental illness) can find help and counselling at Lifelong Learning Institute of Brno University of Technology. This issue is dealt with in detail in Rector's Guideline No. 11/2017 "Applicants and Students with Specific Needs at BUT". Furthermore, in Rector's Guideline No 71/2017 "Accommodation and Social Scholarship“ students can find information on a system of social scholarships.

1. Additive manufacturing of high temperature alloys strenghten by nanoparticle dispersion

   The main goal of the work will be to develop and optimize the parameters of 3D printing of precipitation-hardened nickel superalloys with added incoherent boride-based nanoparticles and to determine the relationship between the microstructure and the basic mechanical properties of the newly prepared alloys. Among the sub-objectives of the work will be the preparation of powder mixtures of nickel superalloys using a three-axis electromagnetic vibrating mixer with a graded proportion of reinforcing nanoparticles. Subsequent microstructural analysis using electron microscopy of both powders and 3D printed materials before and after uniaxial mechanical loading at temperatures up to 1000 °C is expected.

   Tutor: Koutný Daniel, doc. Ing., Ph.D.

2. Advanced bearing diagnostics for wind farms

   Wind power (WPP) is one of the world's most widespread alternative sources of electricity. The desire to maximize the efficiency of the plant leads to high demands on the mechaniocal design and high reliability of all structural components. Critical components include the driveline bearings. Due to the time-varying loads, it is difficult to reliably determine their service life. At the same time their failure during operation must be prevented, as the entire turbine can be heavily damaged and high reapair cost will be required. The aim of this work is to develop an advanced predictive diagnostic method for monitoring the technical condition of the wind turbine bearings using non-destructive testing methods.

   Tutor: Klapka Milan, doc. Ing., Ph.D.

3. Advanced downhill bike suspension

   The goal of the thesis will be to develop an intelligent suspension system for electric mountain bikes. Current commercially available electrically controlled wheel suspension systems do not utilize the potential of rapid semi-active control. Current systems only enable automatic valve control, which has to be adjusted manually in older dampers and is not able to ensure better-driving characteristics. Fast semi-active damping with magnetorheological dampers enables a qualitative shift in achievable driving comfort and wheel grip on the road. Demonstrators of individual components are currently being developed. However, these components will have to be integrated into the entire functional system and experimentally verify the functionality. The work will focus mainly on identifying the limiting properties of real system elements (dampers, sensors, etc.) and the subsequent design of optimal system control.

   Tutor: Kubík Michal, doc. Ing., Ph.D.

4. Artificial intelligence methods for design and control of robotic systems

   Contemporary applications of robotic systems often require complex adaptation of their designs and control strategies. The thesis will aim to research various artificial intelligence techniques (such as deep reinforcement learning, evolutionary algorithms, or neuroevolution) for solving complex problems in this area.

   Tutor: Kůdela Jakub, doc. Ing., Ph.D.

5. Ball screw durability prediction of a CNC milling machining center

   During the operation of the CNC machining center, especially when machining the customer's workpiece, its feed axis is often heavily stressed. This stress is not only caused by cutting forces, but also by the place of clamping the workpiece. It happens that only a certain part of the working part of the ball screw is stressed and excessive wear is identified here, which significantly affects the durability of the ball screw. The goal of the work is to determine the prediction of the residual durability of the ball screw using a system approach and thereby prevent the production of non-conforming parts.

   Tutor: Holub Michal, doc. Ing., Dipl.-Ing, Ph.D.

6. Compensation of movement distortions in hyperspectral imagining

   Colour cameras separate the visible part of the electromagnetic spectrum into three spectral bands. Cameras that can separate the spectrum into tens to hundreds of bands are called hyperspectral cameras. Hyperspectral cameras with a high number of bands work similarly to line cameras, i.e. it is necessary to ensure movement of the camera or of a scanned object so that the entire object is gradually captured. Any additional movement (either of the scanned object or of the camera) leads to unwanted distortions of the resulting image. The main aim of the work is to design methods that suppress or eliminate this type of distortions.

   Tutor: Škrabánek Pavel, doc. Ing., Ph.D.

7. Computational Performance Optimization of Heuristic Algorithms for Transportation Systems

   The dissertation will focus on improving the computational efficiency of heuristic algorithms, with a particular emphasis on transportation problems addressed at the Institute of Process Engineering. The initial part of the work will include an analysis of the characteristics of these problems to identify key factors affecting their computational complexity. Based on this analysis, modifications to existing algorithms will be proposed and implemented, with a focus on code optimization and increasing efficiency and scalability. Another important part of the dissertation will be the development of methods for parallelizing computations, enabling the effective use of available computational resources. These methods will include procedures for coordinating parallel processes and their application to solving large and complex problems. In the process of generating new solutions, crossover strategies will be designed, incorporating the selection of a limited number of representative solutions suitable for individual algorithmic steps. For each examined problem, the computational purpose will also be considered to establish an optimal trade-off between solution quality and acceptable computation time. The results of this dissertation will contribute to more efficient solutions for practical transportation problems and expand the applicability of heuristic algorithms to complex problem-solving.

   Tutor: Šomplák Radovan, doc. Ing., Ph.D.

8. Control Algorithms for Systems with Fractional-Order Differential Equations Elements

   Approaches that use the apparatus of differential equations with fractional-order derivatives (FOE, Fractional-Order Elements) for modelling are becoming more and more common in electrical circuit synthesis and controller design. In this dissertation, the aim will be to implement control algorithms for systems described by such type of differential equations and to demonstrate the applicability in practical applications.

   Tutor: Šeda Miloš, prof. RNDr. Ing., Ph.D.

9. Cooperation with industry partners in the field

   The aim is to describe friction principles and develop a methodology for modeling static and kinetic friction in contact between rigid bodies with surface roughness and engineering plastics. The work combines FEM modeling with experiments.

   Tutor: Hartl Martin, prof. Ing., Ph.D.

10. Design of Decomposition Strategies for Efficient Solving of Complex Transportation Problems

    The dissertation will focus on the decomposition of complex problems solved using heuristic algorithms, with particular attention to transportation problems addressed at the Institute of Process Engineering. The study will include an analysis of the key characteristics of these complex problems and their impact on computational complexity. Emphasis will be placed on understanding the problem structure and identifying parts suitable for decomposition into smaller, more manageable subproblems. Based on this analysis, a decomposition methodology will be designed and developed to enable more efficient problem-solving. This approach will be tailored to the specifics of transportation problems, including their dynamic nature, interdependencies between problem components, and the need for rapid decision-making. The dissertation will also include the design and implementation of algorithms utilizing parallel processing to maximize the efficient use of available computational resources. The implementation will be adapted to the specific requirements of individual problems, aiming to optimize both the accuracy of results and computational time. The findings of this dissertation will contribute to the development of new methods for solving complex transportation problems and support the more effective integration of heuristic algorithms into practical applications.

    Tutor: Šomplák Radovan, doc. Ing., Ph.D.

11. Developing Depth Estimation Methods from Two-Dimensional Image Data

    Image data captured by a conventional camera with a matrix sensor provides only a two-dimensional representation of three-dimensional reality. However, for some applications, knowledge of the third dimension—depth—is also crucial. To address this, several methods have been developed to estimate depth from two-dimensional image data. These methods differ in how they collect data and in their subsequent processing, with both aspects significantly affecting their practical usability. There are notable differences between methods in terms of the amount of data required, estimation accuracy, computational complexity, and acquisition costs. No existing method is definitively the best solution across all these parameters. Thus, the field of depth estimation from two-dimensional image data offers significant room for innovation, whether through modifying existing solutions to enhance their key properties or by developing entirely new methods. Both approaches could represent the focus of further research.

    Tutor: Škrabánek Pavel, doc. Ing., Ph.D.

12. Development of a magnetorheological shock attenuation system for military applications

    In military applications, effective shock attenuation is an important requirement. This may include damping of gun recoil, damping of seats in the event of a vehicle explosion or fall, and more. Current scientific contributions reveals that the combination of a magnetorheological (MR) suspension system together with semi-active control can be a significant advance in this area. Typically, piston velocities are in the units of m/s and high damping forces are achieved. These are therefore quite extreme operating conditions for dampers. The main focus of this work will be study of the behaviour of MR fluid at high velocities and the subsequent application of this knowledge to the design of a magnetorheological damper. The design of sensors and damper control will be important as well. The main focus of the work will be the development and experimental verification of MR suspension systems operating at high piston velocities.

    Tutor: Klapka Milan, doc. Ing., Ph.D.

13. Development of the measuring system for monitoring and protection of plant grow

    The trend towards efficient use of natural resources affects a wide range of sectors, including agriculture. For proper plant growth, it is essential to choose the right irrigation method to avoid underwatering or overwatering the plant and possibly wasting water. To decide whether a plant needs watering, it is necessary to know its current condition. As previous research has shown, plant condition can be reliably monitored using the acoustic emission (AE) method, which has emerged as a sensitive method for diagnosing fatigue damage to bearings. Based on the data obtained from AE sensors, decisions can be made about watering and possibly the dosage of additional soil nutrients, etc. AI control can also be used to make decisions. Automated control can then be used for automated irrigation systems for greenhouses or for hydroponics, etc. The aim of the work is then to develop a suitable measurement method that allows reliable monitoring and to develop an algorithm for evaluating the data obtained.

    Tutor: Klapka Milan, doc. Ing., Ph.D.

14. Digital twin of an electric vehicle powertrain including thermal management

    The dissertation focuses on advanced modelling of the powertrain of modern electric vehicles with emphasis on the combination of 0D, 1D and 3D models and analysis of their thermal behaviour. This approach enables a comprehensive understanding of the dynamics and efficiency of the powertrain of electric vehicles, which is crucial for optimizing their performance and durability. A strategy is proposed to optimize the thermal management and drivetrain efficiency based on the results. Translated with www.DeepL.com/Translator (free version)

    Tutor: Štětina Josef, prof. Ing., Ph.D.

15. Digital twin of the production process to optimise the energy efficiency of production

    The topic is focused on the development of the production process digital twin, which will include tools for predicting the energy consumption of the production process and assessing the energy efficiency of production assets. The focus will be on the use of renewable energy sources, taking into account market behaviour and customer requirements.

    Tutor: Blecha Petr, doc. Ing., Ph.D., FEng.

16. Digital twin of wheel-rail contact

    The aim of the work is to use experimental methods to develop a model that will describe the frictional behavior of the wheel-rail contact in the presence of lubricants. The model will use real-track data to predict contact friction, allowing the lubrication system to recognize when re-application of lubricant is necessary. The result of the work will have an effect on a more efficient process of lubrication of the contact between the wheel and the rail. Lubricant consumption will be optimized while the wear of contact bodies is reduced.

    Tutor: Omasta Milan, doc. Ing., Ph.D.

17. Energy efficient electric motors

    The goal of the topic is the design development of an electric motor using a structured magnetic circuit produced by the method of 3D metal printing. It is expected that a suitable design of the structured magnetic circuit should increase the efficiency of the electric motor, reduce its weight and at the same time improve cooling. The design of the magnetic circuit will be based on the patented technology of the Department of Technical Diagnostics (EP3373311).

    Tutor: Kubík Michal, doc. Ing., Ph.D.

18. Heat exchangers with controlled non-uniformity of refrigerant distribution

    The topic is focused on the creation of a methodology for designing a new generation of additively produced heat exchangers, using structured materials, meeting all strength requirements while minimizing weight and at the same time allowing to control the distribution of the cooling medium according to the needs of a specific application. As part of the solution to the topic, it is assumed that the existing algorithms of multi-level topological optimization for the purposes of heat exchange will be modified. In addition to changing the stiffness within one component, the algorithm should also allow local control of the cooling performance. Experimental samples as well as functional parts will be realized through metal additive SLM technology, and information on the flow and thermal properties of the structures will be obtained from cooperation with the Institute of Process Engineering.

    Tutor: Koutný Daniel, doc. Ing., Ph.D.

19. Increasing the accuracy of horizontal milling and boring CNC machine tools

    The topic of the thesis is focused on the system analysis of the behaviour of horizontal milling and boring CNC machine tools, which will be treated as mechatronic systems. In particular, the problem of corrections and compensations based on spatial maps and the method of identification of geometric errors will be addressed. From the above points, a design of measures will be made and a systematic approach to the selection of a suitable measurement method, data analysis and the method of entering compensation into the control system for horizontal milling and boring machines will be set up.

    Tutor: Holub Michal, doc. Ing., Dipl.-Ing, Ph.D.

20. Increasing the accuracy of industrial robots

    With the advent of new technologies such as additive technologies, but also with the advent of new eco-friendly materials or the deployment of modern measuring equipment on industrial robots, questions about the accuracy of the end-effector path are increasingly being asked. This thesis will discuss the possibilities of increasing the accuracy according to the requirements of the chosen technology with possible approaches to compensate for deviations in the desired path.

    Tutor: Marek Jiří, prof. Dr. Ing., Ph.D., DBA, FEng.

21. Innovative Approaches to Measurement and Quality Assessment of Industrial Products Using Image Data

    The aim of this dissertation is to design and develop an industrial system for precise measurement and quality assessment of products using image data. The research will focus on exploring new approaches that enable effective analysis of medium-sized to large-scale objects, where traditional methods based on the arrangement of the object, camera, and lighting may be insufficient. The study will investigate potential innovations in the areas of imaging, lighting, or subsequent image data processing to ensure high accuracy and reliability of the system. The dissertation will include an analysis of existing approaches, the design of suitable methods, and their implementation, including experimental validation.

    Tutor: Škrabánek Pavel, doc. Ing., Ph.D.

22. Integration of Artificial Intelligence in Industrial Operations: Data-Driven Approaches for Control Optimization, Diagnostics, and Predictive Maintenance

    This thesis addresses the highly topical issue of integrating artificial intelligence into industrial operations. Modern industries, fueled by the exponential growth of digital data, now have unprecedented opportunities to enhance control, diagnostics, and predictive maintenance through advanced data analysis. With the ongoing digitalization and automation of processes, there is increasing pressure to optimize operational efficiency and reduce both operational and maintenance costs. The work focuses on the utilization of operational data collected from various sensors and measurement systems, applied across several key areas: Control Optimization: Implementing automated, real-time adjustments of operational parameters to maximize efficiency and reduce energy consumption. Predictive Maintenance: Leveraging machine learning techniques to forecast potential equipment failures and schedule timely preventive interventions, thereby minimizing unplanned downtime. Diagnostics: Developing sophisticated diagnostic tools that analyze both historical and real-time data to quickly detect anomalies and potential malfunctions. Additionally, the thesis explores the potential of creating a digital twin—a virtual replica of a real-world system—to simulate and test various operational scenarios, further enhancing control strategies and maintenance planning. Overall, the research investigates the potential and benefits of integrating artificial intelligence into industrial operations through data-driven approaches, aiming to contribute to the modernization of industrial processes and the development of innovative, sustainable solutions.

    Tutor: Máša Vítězslav, doc. Ing., Ph.D.

23. Lubrication of contacts with real conformity by greases

    The aim is to determine, through experiments and modelling, the effect of contact conformality and lubricant properties on the amount of lubricant available for lubricating point contacts with conformity close to real applications.

    Tutor: Hartl Martin, prof. Ing., Ph.D.

24. Lubrication of point contacts with natural lubricants

    The aim is to describe the formation of lubricating film and friction in point contacts lubricated with natural fatty acids and other substances used as additives.

    Tutor: Hartl Martin, prof. Ing., Ph.D.

25. Modelling of hydrostatic bearings control elements to ensure lubrication layer stability

    The aim is to develop an experimentally verified numerical model of flow control elements ensuring the stability of thin lubrication films of hydrostatic bearings.

    Tutor: Svoboda Petr, doc. Ing., Ph.D.

26. Non-exhaust emissions from motor vehicl

    Your dissertation will address a timely and important topic that has a direct impact on the environment and public health. Emissions from tyres and braking systems represent a significant source of pollution that is often neglected alongside traditional emissions from vehicle exhaust systems. These particles can vary in size and chemical composition, making them difficult to monitor and control. The main challenge will be to develop predictive models for the release of these particles. Translated with www.DeepL.com/Translator (free version)

    Tutor: Štětina Josef, prof. Ing., Ph.D.

27. Online monitoring of LPBF process

    The aim of this work is to clarify the relationship between the laser powder bed fusion (LPBF) process setup (scanning strategy, speed, power...), defects and specific microstructure in the processed material by means of continuous observation of the process.

    Tutor: Koutný Daniel, doc. Ing., Ph.D.

28. Optimisation of Serviceability in Network Applications

    n applications that serve locations deployed in a large area for certain customer service, it is a typical task to minimise these locations so that each customer has at least one of the centers at the available distance. The problem of coverage for this task has O (2 ^ n) complexity, where n is the number of given places and it is necessary to solve it by heuristic methods for the "large" instances of the problem. However, the task has even more complex formulations considering service capacities and customer requirements. In the dissertation the aim is to apply a general problem solving in the problems of communication of 5G mobile networks and data storage in NoSQL databases.

    Tutor: Šeda Miloš, prof. RNDr. Ing., Ph.D.

29. Particle emissions from the wheel-rail interface

    The work deals with experimental research on the emission of particulate matter from the wheel-rail interface, especially when applying lubricants and materials for traction enhancement or as a result of the wear process. The aim is to describe the critical factors influencing their formation and effect on the environment and to propose suitable measures.

    Tutor: Omasta Milan, doc. Ing., Ph.D.

30. Physical and virtual testing of vehicles

    The dissertation focuses on the field of physical and virtual vehicle testing. Currently, the need for vehicle testing is growing significantly, particularly in connection with the development of autonomous technologies and their communication with surrounding vehicles and infrastructure. This evolution not only increases the volume of testing but also changes its nature. It is no longer sufficient to test a single vehicle in isolation – its integration into the entire transportation system, as well as testing individual infrastructure components, plays a crucial role. This brings a number of research challenges, both in the field of vehicle modeling, including sensors and driver assistance systems, and in the simulation of virtual environments and infrastructure. Other key aspects include the creation of test scenarios, automation of testing, and the development of supporting tools. A closely related research area is measurement technology and the development of new sensors, as well as the integration of physical and virtual testing through technologies such as "Vehicle-in-the-Loop" (a physical vehicle moving in a virtual environment). Equally important are software and hardware tools for identifying the parameters of modeled systems.

    Tutor: Porteš Petr, doc. Ing., Ph.D.

31. Prediction of wear of dental filling materials during tooth cleaning

    The research focuses on the analysis of the wear of dental filling materials due to toothbrushing and toothpaste during daily oral hygiene. This is an experimental work in which the effects of the tooth filling material, the shape of the end and hardness of the toothbrush fibres, the abrasiveness of the toothpaste and the effect of the use of manual and electric toothbrushes will be discussed. Attention will also be paid to the effectiveness of plaque removal.

    Tutor: Vrbka Martin, prof. Ing., Ph.D.

32. Processing of advanced materials by Electron Beam Melting

    The aim of the work is to verify the possibilities and strategies of processing materials such as tungsten, tantalum, copper or intermetallic alloys TiAl by means of electron beam in vacuum and to evaluate their applicability in industrial applications.

    Tutor: Koutný Daniel, doc. Ing., Ph.D.

33. Reconfigurable mechanical metamaterials

    The aim of the work is to describe the mechanisms of purposefully controlled changes in the morphology of mechanical metamaterials due to changes in external force action using advanced computational modelling methods.

    Tutor: Koutný Daniel, doc. Ing., Ph.D.

34. Reducing wear on railway bogies using electronic suspension

    The aim of the topic is the development of an electronically controlled suspension system for a railway unit that reduces wear on the bogie and infrastructure. The work includes experimental verification of the benefits of this system using a measuring wheelset on the InterPanter railway unit.

    Tutor: Kubík Michal, doc. Ing., Ph.D.

35. Research on noise generation and propagation in rail transport

    Noise generated by the operation of rolling stock is an ongoing social problem. One of the main sources of strong noise is wheel-rail contact. In the case of abnormal operating conditions, excessive lateral vibration of the wheel can occur, leading to the emission of a strong acoustic signal. Although some hypothetical mechanisms of wheel-rail contact noise behaviour have been described, a number of phenomena have still not been satisfactorily investigated. Especially in the context of the modern approach of adhesion management on risky track sections through the application of liquid or solid substances to the surface or sides of the rail. The aim of this thesis is to investigate the influence of operating conditions in modified contact on the occurrence of unwanted noise and its propagation to the surroundings.

    Tutor: Klapka Milan, doc. Ing., Ph.D.

36. Software-Defined Vehicle

    The dissertation focuses on advanced modeling of Software-Defined Vehicles (SDVs) with an emphasis on integrating multiphysics simulation approaches in 0D, 1D, and 3D modeling environments. The goal is to develop a digital twin of the vehicle, enabling real-time analysis of dynamics, energy efficiency, and operational characteristics. By leveraging advanced algorithms, machine learning, and cloud computing simulations, key aspects of vehicle performance, safety, and longevity can be optimized. This approach reflects current trends in the automotive industry, where software-defined architecture plays a crucial role in transforming vehicles towards greater autonomy, connectivity, and efficiency.

    Tutor: Štětina Josef, prof. Ing., Ph.D.

37. Sustainable Machine Vision

    The dissertation will focus on exploring ways to enhance sustainability in the field of machine vision. Sustainability in machine vision encompasses the optimization of data acquisition, transmission, and processing to reduce energy and material consumption. The specific focus of the dissertation will be determined based on a state-of-the-art analysis conducted by the student. Preference will be given to the direction with the highest research and application potential.

    Tutor: Škrabánek Pavel, doc. Ing., Ph.D.

38. The use of machine learning in the processing of railway vehicle vibrodiagnostic data

    Predictive identification of faults and wear is a key aspect of the safe and efficient operation of railway vehicles. Machine learning methods can be used to train a model from data and generalize it to currently unmeasured data. The goal of the thesis is to train a model using machine learning on data obtained from the chassis of a railway vehicle. The resulting model will then be used for predictive maintenance of the railway bogie.

    Tutor: Omasta Milan, doc. Ing., Ph.D.

39. Water as a trigger for low adhesion problems between wheel and rail

    The aim of the work is to provide experimental evidence of the transient behaviour of wheel-rail contact when contaminated with water and other materials and to explain the nature of this phenomenon based on optical observation of the contact. Emphasis is placed on describing the extent of the problem in terms of operating conditions and parameters of the contaminants. The results will be compared with simulations of a partner organisation.

    Tutor: Omasta Milan, doc. Ing., Ph.D.

40. Water as an ecological method for friction modification between the wheel and the rail

    The aim of the work is to investigate the impact of targeted water application on modifying friction between the wheel and the rail to achieve a desired friction level. A key aspect of this research is the prediction of real friction layer properties on the rail, which interact with the applied water.

    Tutor: Omasta Milan, doc. Ing., Ph.D.

41. 3D metal printing of magnetic circuits

    The aim of the topic is the research and development of structured magnetic circuits produced by the 3D metal printing method. The design of the magnetic circuits will be based on the patented technology of the Research team Technical Diagnostics (EP3373311). This technology will allow the development of highly efficient magnetic circuits. Development can be focused on several areas, such as electromagnetic actuators, valves or sensors.

    Tutor: Kubík Michal, doc. Ing., Ph.D.

42. 3D printed individualised segmental joint implant: biotribology of articular surface

    The aim of the research is to describe the tribological behaviour of 3D printed individualised implants for local replacement of femoral head defects. The aim is to design an implant friction surface that achieves a very low coefficient of friction and minimally wears the opposing articular cartilage. This is an experimental work where suitable biocompatible materials such as titanium alloys produced by additive Selective Laser Melting, CoCrMo alloys and advanced biomaterials such as PEEK or hydrogel will be tested. The result will be a prototype of a local implant for clinical trials.

    Tutor: Vrbka Martin, prof. Ing., Ph.D.

43. 3D-printed metal composites reinforced with 2D nanomaterials for next-generation biomedical implants

    The aim is to research and develop a new generation of joint implants using 2D nanomaterials, which allow superlubricity conditions to be reached and thus ensure the replacement operation under extremely low friction coefficient and nearly zero wear. It is supposed that 2D materials represent a milestone in many engineering disciplines, including biomedical engineering. Cooperation with the academic and private sectors is planned within the topic, while the outcome of the thesis is in a new-generation implant which will be biocompatible and suitable for clinical testing.

    Tutor: Nečas David, doc. Ing., Ph.D.

44. 4D printing of magnetically active elastomers

    Intensive research and development is currently underway in the field of magnetically active elastomers or hydrogels, which can be produced using so-called 4D printing. 4D printing is a new and completely unique technology that allows printing dynamic 3D structures capable of changing their shape over time. This topic aims to develop equipment and methodology for 4D printing of magnetically active elastomers and hydrogels. Part of the work will be the application of this technology to the issue of micro-robotics.

    Tutor: Kubík Michal, doc. Ing., Ph.D.