Civil Engineering

Module aim

To develop students' pedagogical competence, adapted to the individual educational practice, successful and modern planning, organizing and managing the study process.

Description

The subject reveals close connections between subject, scientific and educational competencies of a teacher. During lectures, seminars, and independent work, higher education didactics is analyzed, emphasizing student-centered studies, international and national higher education space, forms and methods of communication, methodologies in academic environment with different groups of society. The basis of studies consists of reflexive experiential learning, which helps to develop doctoral students' analytical and critical thinking, ability to evaluate their own and others' decisions, promotes a holistic and responsible approach to their activities.

Module aim

To introduce the most innovative research methods and methodologies providing specialized knowledge for the solutions to the scientific research and other areas problems.

Description

Science philosophy. Prevention of plagiarism. Search for scientific information. Scientific information bases. How to write and publish a paper in a journal indexed in Web of Science. Modern software tools for research planning and scientific results publishing. Modern software tools for research planning and scientific results publishing Knowledge transfer, commercialization and patenting.

Module aim

To introduce the most innovative research methods and methodologies providing specialized knowledge for the solutions to the scientific research and other areas problems.

Description

Science philosophy. Search for scientific information. How to write and publish a paper in a journal indexed in Web of Science. Big data and its analytics. Modern software tools for research planning and scientific results publishing. Quantitative methods for cross-sectional data analysis. Modern software tools for processing and vizualization of experiments results. Statistical processing of the research data and development of empirical models. Knowledge transfer, commercialization and patenting.

Module aim

To introduce the most innovative research methods and methodologies providing specialized knowledge for the solutions to the scientific research and other areas problems.

Description

Science philosophy. Prevention of plagiarism. Search for scientific information. Scientific information bases. How to write and publish a paper in a journal indexed in Web of Science. Modern software tools for research planning and scientific results publishing. Modern software tools for research planning and scientific results publishing Knowledge transfer, commercialization and patenting.

Module aim

To enhance existing and gain new knowledge about the necessary input data for transport communication pavement structures, their interfaces and the impact on digital model accuracy and automated pavement design.

Description

The module is intended to provide knowledge and skills related to the automated design of pavement structure. Pavement structure model is based on the components of mechanistic-empirical method - specific data and functional properties of materials, determined by laboratory tests. The use of an automated design model ensures computation speed, accuracy, repeatability and reproducibility.

Module aim

The main goals of studies is to give to the students an overview of contemporary problems driven by global urbanisation and main challenges in town planning. To

Description

Sustainable town planning history and development. Contemporary sustainable development concepts and movements, common urban sustainability criterias. Town planning in accordance with the principles of sustainability. Implementation of sustainability concepts in general town plans. Land right and land owners, health and higiene norms and other restrictions in sustainable urban planning. Foreseeing the development of urban territories, regeneration of derelict land versus consuming new areas. Planning the sustainable urban transportation system. Types of built-up territory, their use and characteristics in terms of sustainability.

Module aim

To introduce PhD students to the theory, practice, and latest data analytics trends.

Description

The leading global trends in big data analytics are growing IoT networks, more approachable AI, the rise of predictive analytics, cloud migration of dark data, the rise of chief data officers, quantum computing, smarter and tighter cybersecurity, endpoint security, cloud security, open-source data, data democratization, data ethics. Practical application of big data analytics: construction, real estate, cities, banking and securities, communications, media and entertainment, healthcare providers, education, manufacturing and natural resources, government, insurance, retail and wholesale trade, transportation, energy, and utilities, big data & auto-driving car, big data in IoT, big data in marketing, big data in business insights. Big data. Wearable devices. The Internet of Things. Smart technologies. Standards and data integration. Data mining and its practical uses. Data mining problems, methods and systems. Text analytics. Video analytics. Biometric analytics. Affective computing.

Module aim

Introduction with principals of experimental and numerical modelling of soil mechanics problems, application possibilities.

Description

Overview of in situ and laboratory soil experiments. Probabilistic evaluation of experiments. Modeling experiments via numerical methods. Finite elements in geotechnics. Physical models for soil modeling - elastic, elastoplastic, Mohr-Coulomb, Hardening soil, Hardening soil small with strain stiffness, Soft soil, Hypoplastic. Discrete element method for modelling soli behavior.

Module aim

To provide a wider knowledge on fire processes and effects of these processes on structures and humans

Description

Physics and chemistry properties of fire geneses. Quantitative evaluation of fire process. Analises of general fire factors and parameters. Burning pecualiarity of diferent materials. Stage development of fire. Analises of smoke factors.

Module aim

To be able to choose soil testing methofs, get parameters for the chosen soil model.

Description

Soil formation peculiarities and experimental researches needed for determination of the soil finite elements parameters for ground material model. Probabilistic evaluation of experimental data. Soil material models: elastic, elastic-plastic, Moro-Coulomb, Hardening Soil (HS), Hardening Soil with small strain stiffness (HSsmall), Soft Soil Creep models. Discrete element method used for soil simulation.

Module aim

Mastering of micro transport modelling at the level of road strech and intersection. Evaluation of transport and pedestrian flow interaction, impact of traffic flows on traffic safety.

Description

The main analyzed subjects are as follows: increase of transport traffic flow and generated problems in the European Union and Lithuania. Modelling of traffic flows on highways and national roads. Modelling of traffic flows on city streets. Simulation of conflict situations caused by transport traffic and pedestrian flows at intersections. Use of simulation results in road and/or street network development and reconstruction projects.

Module aim

To provide a theoretical background of developing physical models of composites; to teach solving physically nonlinear design problems.

Description

Current technologies enable of synthesising polymers with exceptional mechanical characteristics. Such materials are widely used in medicine, automotive, and spacecraft industries. However, conservative approaches to new materials are predominant in the design of building structures. The purpose of this module is to identify efficient structural solutions implementing fibre-reinforced polymers with exceptional mechanical properties. In this context, the "efficiency" criterion is understood as the ability of the element to withstand the design loads with the lowest material cost (taking into account the production technology).

Module aim

To introduce PhD students to the nonlinear analysis of reinforced concrete structures.

Description

Material and geometrical nonlinearity. Nonlinear problems in structures. Physical-mechanical properties of concrete at curing state. Shrinkage and creep of concrete. Deformation analysis methods of reinforced concrete structures accounting for concrete creep and shrinkage. Calculation examples and analysis of results. Analysis of concrete structure at meso-level. Analysis of concrete structure at micro-level. Stress-strain relationships for steel and concrete at uniaxial stress state. Strength and strain of concrete at bi-axial and tri-axial stress state. Influence of temperature on deformations of reinforced concrete constructions. Basics of theory of plasticity. Models of concrete cracking. Discrete and smeared cracks models. Cracks width calculation methods. Deflections calculation methods. Bond between steel and concrete and models. Stress- strain analysis using layer model. Basic principles of direct and iterative calculation methods.

Module aim

To analyze theoretical and applied methods of calculation of high strength and stainless steel and aluminum advanced structures.

Description

Advanced structures in high strength steel, stainless steel and aluminum. Scope, properties, requirements, behavior, theoretical and applied background of these materials.

Module aim

Provision of knowledge on the risk oriented design of safe objects belonging to critical infrastructures, namely, principal buildings, key components of transportation and energy delivery systems.

Description

Physics and chemistry properties of fire geneses. Quantitative evaluation of fire process. Analises of general fire factors and parameters. Burning pecualiarity of diferent materials. Stage development of fire. Analises of smoke factors.

Module aim

To introduce students to the theoretical and practical framework of digital construction and building information modelling.

Description

After completing this course, you will have the information and abilities necessary to successfully implement Building Information Modeling (SS-BIM) and digital construction in the construction industry. Knowledge of SS-BIM enhances the effectiveness and efficiency of operations throughout the construction sector. The core topics include the origin, components, definition, and application of SS-BIM, as well as its role throughout the project life cycle. The course also analyzes the latest global digital construction technologies-such as Chat GPT, digital twins, virtual and augmented realities, wearables, and IoT (including equipment monitoring and repair, inventory management and ordering, energy efficiency, and security)-across the building life cycle, with a focus on their potential implementation in Lithuania. Additionally, the course will feature presentations on real-world examples of the latest SS-BIM applications in real estate and construction both in Lithuania and globally.

Module aim

To analyze layered structure theory and computational methods, to present their analysis of the pros and cons

Description

Types of sandwich structures, composition and related methods of analysis. Analysis of sandwich structures with mild and rigid internal layers. Effect of ties for joint action of layers. Evaluation of regidity of joints.

Module aim

To give general fundamentals of digital and information modeling of buildings and its application for the development of an integrated AEC project.

Description

Modern computer-aided design technology in AEC is based on Building Information Modelling (BIM) concept. According to this concept building design project or its separate parts have to be created within three-dimensional object oriented parametric graphical-information model context covering all stages and parts of the project. Therefore, it is very important that all project participants (architects, constructors, engineers, technologists, etc.) successfully collaborate at all parts and stages of the project. The basis for such successful collaboration is the knowledge of standards and rules in the integrates project, and the ability to manage project data using a common data environment.

Module aim

To introduce PhD students to the life cycle of the built environment and its theory of analysis and its practical application in various fields.

Description

Life cycle of a built environment and its analysis (the life cycle of a building; phases of a life cycle assessment; integration of a LCA in green building rating systems; model for a complex analysis of the life cycle of a built environment with emphasis on the building's life cycle assessment; quantitative and qualitative aspects for analyzing the life cycle of a built environment; environment at micro-, meso- and macro-levels; model for a complex analysis of the life cycle of a built environment; practical realization of the model for a complex analysis of the life cycle of a built environment; stakeholders in various stages of the life cycle of a built environment; criteria system to describe the life cycle of a built environment systematically). Building LCA databases and tools (LCA databases; life cycle assessment software and databases; multipe variant design and analysis of a building's life cycle and selection of the most efficient options.

Module aim

To provide theoretical background and to teach how to develop multi-criteria discrete optimization models and apply decision support systems in order to solve problems of sustainable construction.

Description

Basics of Multi-Criteria Discrete Optimization: goal formulation, data types, problem-solving models, and types of utility functions. Expert data processing and expert selection. Intelligent Decision Support Systems (IDSS), their classification and components; integration of multi-criteria IDSS with recommendation, consulting, expert, data, and text analytics systems; practical examples of decision support systems and their application to sustainable construction tasks. Latest Global Trends in Multi-Criteria Optimization and IDSS in the Built Environment include Generative AI, AI and Personalization, AI in Construction and Real Estate, Democratization of AI, Multimodality, AI in Transportation, AI in Climate Change Solutions, Digital Twins, Predictive Analytics, Shadow AI, Conversational AI, Augmented Reality, augmented work, and customized AI models revolutionizing construction, responsible AI.

Module aim

To give general fundamentals of theory and its practical use of statistical investigation and multiple criteria evaluation of building and building structures.

Description

Trends of development and application of statistical investigation in civil engineering codes of developed European countries. Application of random values, processes and areas and probalistic investigation models. Statistical control and evaluation of members and systems. All-round quality analysis of projects. Influence of micro-factors on efficieney of projects. Fundamental theory, methods and models for multiple criteria evaluation of projects. Optimality criteria. Theoretical methods for determination of weight values of criteria. Integration of multiple criteria decision making methods with recommender, advisory, expert, data and text mining methods. Combination of multiple criteria decision making systems with recommender, advisory, expert, data and text mining systems.