Rodolfo Javier Williams Moises will presented his doctoral theses with the title "Computational Modeling and Design of Artificial Soil Freezing in Tunneling" on 6th November 2025 at 2PM.

Abstract:
This thesis presents a computational framework for modeling and designing frozen soil structures formed using the artificial ground freezing (AGF) method in tunneling. AGF is a ground improvement technique that uses freeze pipes installed in the soil to form a frozen body over days to months. In tunneling, it provides temporary ground support and watertightness. The framework integrates computational geomechanics modeling with AGF design principles, enabling the optimal design of frozen soil structures in tunneling projects. It includes tools for geomechanical analysis of AGF, simulation of conventional and mechanized tunneling in frozen ground, and optimization of freeze pipe layouts. The backbone of the framework is a thermo-hydro-mechanical (THM) finite element model for soil freezing and thawing, enhanced with constitutive models for pore pressure coefficients, strength, and creep of frozen soils, and is computationally robust for high seepage flow simulations. In a case study under high seepage flow and a fixed number of pipes, the framework uses machine learning to design an optimized pipe layout that outperforms a conventional layout with uniform spacing in reducing freezing time. Overall, the thesis advances computational modeling and data-driven optimization methods for AGF in tunneling, demonstrating potential for integration into the design phases of ground-freezing engineering.

On Friday, 24. October 2025 at 2:30 PM, Nicola Gottardi will presented his doctoral theses with the title "Real-time Structural Health Assessment of Segmental Tunnel Linings".

Abstract:
The underground network has been constantly expanding, and one of the challenges is ensuring safety, operability, and durability of tunnels throughout their service life. In this context, structural health monitoring (SHM) plays a crucial role for the evaluation of the tunnel lining performance and safety. Tunnel lining health assessment faces unique challenges due to limited accessibility to critical areas and a sparse availability of measurement data compared to the complexity of the structural system. The objective of this thesis was to develop a framework to accomplish comprehensive SHM of segmental tunnel linings, by leveraging the benefits of computational and surrogate models to accommodate a limited monitoring of the structure. Numerical simulations are employed to generate synthetic data, which are used to train surrogate models capable of reconstructing the lining structural state, accounting for possible damage, and its loading conditions based on limited measurements. The SHM framework proposed in this thesis, validated on experiments and a tunnel project, represents a flexible approach adaptable to various monitoring configurations, enabling real-time evaluations of the structural health of segmental linings to ensure tunnel operability and safety in a cost-effective manner.

"Discrete modeling of cracking in reinforced concrete structures: formulation, size effect, and parameter sensitivity" an open access article recently published by Vladislav Gudzulic and Günther Meschke. It was released by Springer Nature in the journal "Materials and Structures".

Abstract:
This paper presents a discrete fracture modeling approach for simulating cracking in reinforced concrete (RC) structures. Cracks are represented using cohesive zero-thickness interface elements, with a traction-separation law by Snozzi and Molinari (Int J Numer Meth Eng 93(5):510–526, 2013.). extended to account for frictional sliding and crack-roughness-induced dilatancy. An effective failure surface is derived from the extended constitutive relation. Reinforcement is modeled using elastoplastic Timoshenko beam elements, and bond behavior is modeled using coupling elements governed by an elastoplastic bond-slip law. The model is validated through simulations of size effect experiments on RC beams under four-point bending (Syroka-Korol and Tejchman in Eng Struct 58:63–78, 2014.). These tests exhibit consistent shear failure modes across all sizes and serve as a reference for evaluating fracture models proposed by Bažant and Nguyen (J Eng Mech 149(8):04023047, 2023.). Simulations reproduce size-dependent peak loads, crack patterns, and failure modes using material parameters derived from design codes and literature. A mesh sensitivity analysis and a parametric study on mixed-mode fracture parameters (shear strength, friction coefficient, and dilatancy) are conducted. The results highlight the importance of these parameters in capturing shear-dominated failure mechanisms and reveal the possible impact of uncertainties linked to material property identification on the model predictions. The proposed approach provides a robust, physically motivated, and modular framework for analyzing both serviceability and failure in RC structures. The model demonstrates good predictive capability, but also shows sensitivity to mixed-mode fracture properties. This result highlights the importance of advancing and more widely applying experimental methods for characterizing these parameters, which are currently difficult to obtain and rarely addressed in standard testing protocols.

Bartłomiej Łazorczyk and Roger A. Sauer are the authors of the newly open access publication "Nonlinear elastodynamic material identification of heterogeneous isogeometric Bernoulli-Euler beams", which appears in the Elsevier journal "Computer Methods in Applied Mechanics and Engineering".

Abstract
This paper presents a Finite Element Model Updating framework for identifying heterogeneous material distributions in planar Bernoulli–Euler beams based on a rotation-free isogeometric formulation. The procedure follows two steps: First, the elastic properties are identified from quasi-static displacements; then, the density is determined from modal data (low frequencies and mode shapes), given the previously obtained elastic properties. The identification relies on three independent discretizations: the isogeometric finite element mesh, a high-resolution grid of experimental measurements, and a material mesh composed of low-order Lagrange elements. The material mesh approximates the unknown material distributions, with its nodal values serving as design variables. The error between experiments and numerical model is expressed in a least-squares manner. The objective is minimized using local optimization with the trust-region method, providing analytical derivatives to accelerate computations. Several numerical examples exhibiting large displacements are provided to test the proposed approach. To alleviate membrane locking, a hybrid discretization approach is employed when necessary. Quasi-experimental data are generated using refined finite element models with random noise applied up to 4 %. The method yields satisfactory results as long as a sufficient amount of experimental data is available, even for high measurement noise. Regularization is used to ensure a stable solution for dense material meshes. The density can be accurately reconstructed based on the previously identified elastic properties. The proposed framework can be straightforwardly extended to shells and 3D continua.

The lecture dates for the winter term 2025/2026 are online: