On Friday, 14 August 2026, at 2:00 PM Giao Vu holds her PhD defense, titled 'A Virtual Coda Wave Interferometry Laboratory for Damage Assessment in Reinforced Concrete Structures'.

Abstract:
Concrete infrastructure ages long before it fails visibly. Detecting that deterioration early – while repairs are still cheap – is one of the central challenges in structural health monitoring. Coda Wave Interferometry (CWI) offers a promising solution by exploiting the late-arriving portion of ultrasonic measurements. Having travelled repeatedly through the material, these waves sample a far larger volume than conventional methods and are sensitive to microstructural change. Embedded ultrasonic sensors are inexpensive, making CWI an attractive basis for permanent monitoring systems. The obstacle is interpretation: a measured signal change tells us that something has happened inside the concrete, but not what, where, or how severe.

This thesis closes that gap with a virtual CWI laboratory. Meso-scale models simulate the cracking process and the ultrasonic waves travelling through it, linking a structure‘s internal state directly to its measured response. The framework was validated against real experiments from material specimens up to reinforced concrete beams, across varying mixtures, structural layouts, and sensor configurations.

The result is a quantitative map from velocity change to what engineers care about: crack width, reinforcement strain, stiffness degradation. The synthetic data then trained a transformer-based classifier which, after domain adaptation, predict damage states from real measurements with good accuracy.

Together, the framework provides scalable tool for designing sensor networks, generating validated training data, and translating monitoring signals into decisions.

'Measurements of Fiber and Load-rate Effects on Micro- and Macro-fracture of Ultra-High- Performance Concrete' is the title of the lecture given by Prof. Eric N. Landis (University of Maine, USA) on Friday, 14 August 2026.

Abstract:
Advances in 3D imaging have opened up different ways to observe the internal mechanisms that dictate how a material dissipates energy under extreme loading conditions. Specifically, quantitative analysis of such 3D images allow us to measure fracture and damage in new ways. In the study presented here, several new analysis techniques were applied to an ultra-high-performance concrete subjected to different loading rates. The cylindrical specimens were subjected to x-ray CT scans to create 3D images of the material‘s internal structure. Using a combination of digital volume correlation and discrete crack measurements we were able to break total damage down in macro-cracking and micro-cracking. Here the micro-cracking is defined as that due to the residual strain measured through DIC that is not visible as a macro-crack. While this definition is somewhat arbitrary and dependent on the resolution of the images, it allows us to quantify the effects of both loading rate and micro-structure on the distribution of cracking and damage in the material. Such quantitative information can be used to tune and validate computational models for these materials.

The Faculty of Civil and Environmental Engineering has nominated Lennart Stöttelder for the 2026 RUB Student Award in recognition of his outstanding thesis, 'Computationally Simple and Efficient Locking Alleviation in Isogeometric Thin Shells.' This prestigious prize is conferred annually by the Rectorate of Ruhr University Bochum.

The master thesis presents an improved version of the hybrid membrane-bending interpolation method of Sauer et al. (2024) for isogeometric thin shells. The proposed modifications reduce computational cost through reduced integration and a single-element formulation while preserving the locking-free behavior and accuracy of the original method. Extensive L2-error convergence studies demonstrate the superior performance of the proposed B2M1-formulation compared to classical isogeometric shell formulations.

We congratulate Lennart on his award.

The open access article with the title "A Survey of Interlayer Interaction Models for Graphene and Other 2D Materials in Advanced Materials Interfaces" written by Gourav Yadav, Shakti S. Gupta, Roger A. Sauer, is now published in "Advanced Materials Interfaces" by Wiley.

Abstract:
This work presents a survey of mechanical models describing van der Waals interactions between 2D materials, encompassing both continuous elastomer-like materials and discrete (crystalline) 2D materials such as graphene. These interactions give rise to a range of physical phenomena, including contact instabilities, Moiré patterns, surface reconstructions, and superlubricity. The underlying contact forces follow from the variation of an interfacial interaction potential. The presentation first discusses normal contact models, and then tangential contact models. Both atomistic and continuum approaches are considered. In addition, the influence of external loading and changes in length scale on the ground state configuration and frictional contact behavior are analyzed. A particular emphasis is placed on discussing strategies that reduce computational cost in multiscale modeling.

The article "Transformer model for sensitivity analysis of steel and steel-fiber reinforced concrete beams", written by Stefanie Schoen, Steffen Freitag, Vladislav Gudzulic, and Günther Meschke, has been published in "Advances in Engineering Software" by Elsevier.

Abstract:
Due to inherent uncertainties, it is essential to quantify both aleatory and epistemic uncertainties when assessing the structural behavior and reliability of reinforced concrete (RC) and steel-fiber reinforced concrete (SFRC) structures, as these uncertainties can significantly impact load-bearing capacity and crack development. To enable fast predictions during the design process, circumventing time consuming finite element simulations, and considering implicitly material and structural uncertainties, a novel Transformer-based surrogate model is proposed in this paper. The surrogate model efficiently predicts the history-dependent response of RC and hybrid RC-SFRC beams, specifically, load–displacement and maximum crack width-displacement curves. Unlike conventional feedforward neural networks, the Transformers captures long-range dependencies across the entire loading process in parallel, making it well-suited for path-dependent structural behavior. To assess the influence of key uncertainties, the surrogate model is applied within a systematic sensitivity analysis. Results show that the concrete cover dominates the influence on the load–displacement behavior in RC beams, while the fiber properties govern the response in hybrid RC-SFRC beams. The findings demonstrate the potential of Transformer models as a computationally efficient tool for reliability assessment in structural engineering.

Before May 21, 2026 this share link provides a 50 days' free access to the article:
https://authors.elsevier.com/c/1msaE3Rf7bHSTK.

Alternatively, try this link to gain access: