Professors from national and international universities, technical experts from the industry as well as research associates of the institute of structural engineering (IBK) are invited to present recent research results and specific projects from the practice. This colloquium is adressed to members of universities, practicing engineers and interested persons in general.

Professors from national and international universities, technical experts from the industry as well as research associates of the institute of structural engineering (IBK) are invited to present recent research results and specific projects from the practice. This colloquium is adressed to members of universities, practicing engineers and interested persons in general.

Introduction to non destructive evaluation tools and quantitative structural analyses and verifications for condition assessment of existing structures and subsequent decisions on their rehabilitation.

Current research in machine learning and data science within the research fields of the department. The goal is to learn about current research projects at our department, to strengthen our expertise and collaboration with respect to data-driven models and methods, to provide a platform where research challenges can be discussed, and also to practice scientific presentations.

The course offers an introduction to dynamics of engineering systems. The first part focuses on Newtonian dynamics and energy principle to systems of particles and rigid bodies. The second part focuses on the free and forced response of single- and multi-degrees-of-freedom linear systems. Hands-on exercises, computer-based labs and experimental demos will support the theoretical lectures.

This doctoral seminar organised by the D-BAUG platform on data science and machine learning aims at discussing recent research papers in the field of machine learning and analyzing the transferability/adaptability of the proposed approaches to applications in the field of civil and environmental engineering (if possible and applicable, also implementing the adapted algorithms).

This course is an interdisciplinary colloquium on the engineering of living materials and biosystems. Internationally renowned speakers from academia and industry give lectures about their cutting-edge research, which highlights the state-of-the-art and frontiers in the field of engineering with living materials.

This course introduces the fundamental concepts of the Finite Element Method (FEM), covering element formulations, numerical procedures, and modelling aspects. A key focus is the hands-on implementation of FEM algorithms in Python.Disclaimer: The course is not about commercial software, but about core concepts and numerical foundations.

The Method of Finite Elements II is a continuation of Method of Finite Elements I. Here, we explore the theoretical and numerical implementation concepts for the finite element analysis beyond the linear elastic behavior. This course aims to offer students with the skills to perform nonlinear FEM simulations using coding in Python.*This course offers no introduction to commercial software.

This course offers the foundation to advanced consideration for structural analysis. This includes the solution of indeterminate systems via use of the Deformation Method and Matric Structural Analysis, as well as the solution of systems with nonlinear material behavior (e.g. due to plasticity).

This course introduces fundamental and advanced methods for structural identification and health monitoring. It demonstrates how measurements of structural response—such as strains, deflections, and accelerations—can be exploited to assess structural condition and support the safe, reliable, and resilient operation of civil and mechanical infrastructure.

This course offers the foundation to advanced consideration for structural analysis. This includes the solution of indeterminate systems via use of the Deformation Method and Matric Structural Analysis, as well as the solution of systems with nonlinear material behavior (e.g. due to plasticity).

The course presents fundamental concepts and advanced methodologies for handling and interpreting data in relation with models. It elaborates on methods and tools for identifying, quantifying and propagating uncertainty through models of systems with applications in various fields of Engineering and Applied science.