Publications at the division of Concrete Structures

Latest publications from the division of Concrete Structures

• Interaction dynamics of a cavitation bubble and an air bubble entrapped in a cavity

  In this study, a fully compressible, two-component, three-phase cavitation model was employed to investigate the interaction between cavitation bubbles and air bubbles confined within a finite-volume cavity. The focus was on understanding how an entrapped gas bubble influences cavitation dynamics, including bubble morphology, collapse intensity, the evolution of the secondary Bjerknes force, and the Kelvin impulse. Results show that at smaller wall-to-bubble distances (L), cavitation bubbles exhibit asymmetric growth due to interface intrusion into the air bubble, leading to earlier micro-jet formation and severe air bubble deformation. Rebound of the air bubble during collapse accelerates the micro-jet, enhancing jet velocity, though this effect weakens with increasing L. Larger cavity radius and depth reduce air bubble fragmentation and bottom pressure while maintaining collapse pressure. A power-law relationship was observed between the maximum collapse pressure and velocity and the dimensionless parameter ζ, highlighting the roles of cavity geometry and wall distance. Additionally, the secondary Bjerknes force exhibits significant fluctuations at smaller L, indicating strong mutual coupling between cavitation and air bubbles. These findings offer insights into optimizing gas-containing, cavitation-resistant structures through geometry control.

• Shear-type failure of deep, short and slender impact-loaded reinforced concrete beams

  Previous research on statically loaded reinforced concrete beams has shown a clear influence of the shear span-to-depth ratio on the resulting shear failure mode. Large shear spans relative to the depth typically lead to capacities governed by the breakdown of beam action, whereas low ratios result in capacities governed by the remaining or full arch. Experimental tests with static loading have determined limits for these ratios and the corresponding failure mode. However, no corresponding limits exist for reinforced concrete beams subjected to high strain rates. This is especially true for deep and short beams, for which test data remain scarce. Impact tests were conducted to study shear span-to-depth ratio limits and corresponding shear-type failure modes at high strain rates. Deep, short, and slender beams were tested to study differences in response. Crack development and deformations were analysed using high-speed photography and digital image correlation (DIC). The series consisted of 27 scaled beams tested under static and impact loading, with varying amounts of transverse reinforcement. Results indicated similar shear failure modes for static and impact-loaded beams across the tested shear span-to-depth ratios. For slender beams, inertial forces and undamaged direct struts dominated early, resulting in higher reaction and internal forces for impact-loaded beams. As deformation developed, the response during both load types was similar, with stiffness dominating and flexural and flexural-shear capacities governing the resistance. Strut and tie models generally aligned with the experimental results, while sectional models were over-conservative. A design procedure based on strut and tie modelling was proposed to capture both early transient and quasi-static phase capacities.

• A digital ecohydraulic twin for riverine habitat prediction and optimization

  Rivers sustain aquatic ecosystems by providing suitable physical habitats. Ecohydraulic models are commonly used to assess ecological suitability; however, they are computationally intensive. Data-based models are efficient but often lack spatial resolution, which restricts the spatially explicit management of environmental issues. To bridge the gap, this study develops a reduced-order digital ecohydraulic twin (RETwin), a novel framework that delivers rapid, accurate, and spatially resolved habitat prediction and optimization. The model couples physically informed dimensionality reduction with machine learning (ML)-driven compressive sensing to preserve dominant hydraulic patterns and improve computational efficiency. It represents a practical decision-support tool for sustainable river management and ecosystem conservation. The RETwin is tested using a real-world river reach, targeting European grayling (Thymallus thymallus) and brown trout (Salmo trutta). It generates accurate and fast habitat predictions at both local and reach scales. For the habitat suitability index (HSI), the model achieves a mean coefficient of determination of 0.81, with a root mean square error of 0.13 and a mean absolute error of 0.07. The model produces reliable estimates with mean errors of less than 1 % for the normalized weighted useable area. Habitat optimization experiments demonstrate that the RETwin can identify near-optimal operating conditions within minutes of computation. Training time is reduced from hours for benchmark ML models to minutes, and predictive times per scenario are on the order of seconds (∼300 times faster than physics-based simulations). This combination of accuracy and efficiency makes the model valuable for ecological modeling and operational decision-making.

• Dataset of high-speed camera measurements from impact-tested reinforced concrete beams

  Impact-loaded reinforced concrete beams often fail in shear. This becomes relevant for shelter design against ballistics or fragment impact, for instance. An experimental campaign was conducted to study the different types of shear failure and governing parameters. Eighteen reinforced concrete beams were tested by a 70 kg steel striker dropped from a 2.4 m height. The beams were loaded at different positions from the support with different amounts of transverse reinforcement. The beams were of reduced scale with a length of 0.80 m and a square 0.15 m × 0.15 m cross-section. The drop weight tests were monitored with shock accelerometers on the striker and beam centre, load cells under the supports measuring reaction forces, and a high-speed camera (HSC). High-speed camera measurements were recorded orthogonal to the surface with the aim of performing high-quality digital image correlation (DIC) analyses. The beams and striker were painted with a speckled pattern prior to testing for the DIC analyses. Camera recordings were conducted with a 1024 × 512 px resolution and 6 kHz sampling, resulting in a time resolution of about 0.17 ms. Accelerometer and load cell measurements were sampled at 19.2 kHz. The accelerometer on the striker was used to approximate the impact force, and beam acceleration can be used to synchronize the camera and DAQ recordings. The data may be used to calibrate finite element models, study the impact response of beams, or develop new mechanical models.

• Simulation of near-wall explosion bubble with non-condensable gas evolution via a modified multicomponent and multiphase lattice Boltzmann model

  In the present study, an improved thermal multi-component multiphase (MCMP) lattice Boltzmann model is proposed by introducing a non-orthogonal transformation matrix and multi-range inter- and intra-particle interaction forces to enhance numerical stability. The model successfully captures multiple oscillation cycles of a vapor bubble with non-condensable gas (NCG) and resolves the immiscibility problem between vapor and air commonly observed in macroscopic MCMP bubble models. Additionally, the model is applied to investigate bubble dynamics near a solid wall, with a focus on the effects of NCG content on collapse intensity. Results show that higher NCG content leads to increased initial internal pressure, resulting in a larger maximum radius and prolonged collapse time. However, the compressibility of the bubble during the collapse stage decreases, weakening the collapse strength. The NCG mass inside the bubble exhibits a decrease–increase–decrease trend during the first oscillation cycle, which is influenced by interfacial mass transfer. Besides, the existence of the NCG concentration ensures non-zero vapor content at the bubble's minimum radius, significantly affecting the phase change behavior during the bubble evolution process.