Search Results (9)

Understanding the transient properties of cementitious pastes is crucial for construction materials engineering. Computational modeling, particularly through Computational Fluid Dynamics (CFD), offers a promising avenue to enhance our understanding of these properties. However, there are several numerical uncertainties that affect the accuracy of the simulations using CFD. This study focuses on evaluating the accuracy of CFD simulations in replicating slump flow tests for cementitious pastes by determining the impact of the numerical setup on the simulation accuracy and evaluates the transient, viscosity-dependent flows for different viscous pastes. Rheological input parameters were sourced from rheometric tests and Herschel–Bulkley regression of flow curves. We assessed spatial and temporal convergence and compared two regularization methods for the rheological model. Our findings reveal that temporal and spatial refinements significantly affected the final test results. Adjustments in simulation setups effectively reduced computational errors to less than four percent compared to experimental outcomes. The Papanastasiou regularization was found to be more accurate than the bi-viscosity model. Employing a slice geometry, rather than a full three-dimensional cone mesh, led to accurate results with decreased computational costs. The analysis of transient flow properties revealed the effect of the paste viscosity on the time- and shear-dependent flow progress. The study provides an enhanced understanding of transient flow patterns in cementitious pastes and presents a refined CFD model for simulating slump flow tests. These advancements contribute to improving the accuracy and efficiency of computational analyses in the field of cement and concrete flow, offering a benchmark for prospective analysis of transient flow cases. Full article

The expected lifespan of cement-based materials, particularly concrete, is at least 50 years. Changes in the pore structure of the material need to be considered due to external influences and associated transport processes. The expansion behaviour of concrete and mortar during freeze–thaw attacks, combined with de-icing salt agents, is crucial for both internal and external damage. It is essential to determine and simulate the expansion behaviour of these materials in the laboratory, as well as detect the slow, long-term expansion in real structures. This study measures the expansion of mortar samples during freeze–thaw loading using a high-resolution hand-held 3D laser scanner. The specimens are prepared with fully or partially saturated pore structures through water storage or drying. During freeze–thaw experiments, the specimens are exposed to pure water or a 3% sodium chloride solution (NaCl). Results show contraction during freezing and subsequent expansion during thawing. Both test solutions exhibit similar expansion behaviour, with differences primarily due to saturation levels. Further investigations are required to explore the changing expansion behaviour caused by increasing microcracking resulting from continuous freeze–thaw cycles. A numerical analysis using a 3D coupled hygro-thermo-mechanical (HTM) model is conducted to examine the freeze–thaw behaviour of the mortar. The model accurately represents the freezing deformation during the freeze–thaw cycle. Full article

Damage induced by repetitive freezing and thawing processes is one of the critical factors that affect concrete durability in cold climates. This deterioration process manifests as surface scaling and internal damage. The damage processes are governed by physicochemical mechanisms that are active across multiple scales. In this contribution, we present a novel multiscale theoretical framework for estimating the critical pressure required for microcrack initiation during freezing and thawing of cementitious mortar. Continuum micromechanics and fracture mechanics is used to model the phenomena of microcrack initiation and growth. Damage at the microscale is upscaled to the level of the specimen using multilevel homogenization. The critical pressure is estimated using poromechanics at the microscopic scale. A theoretical analysis shows that in the frozen state, the material can resist higher pressures. As a consequence, the material is more susceptible to damage during thawing. The micromechanical predictions are within the range of the predictions obtained by electrokinetic theory. Full article

In this paper, the flow of concrete in a reinforced bored pile is analysed using computational simulations. In order to reduce the computational time, a porous medium that equally mimics the presence of the reinforcement is used. Experimental measurements are used as bounds on the material parameters describing the flow of fresh concrete. The influence of rheological properties of fresh concrete and the thickness of the porous medium that represents the reinforcements is analysed with a classical U-box simulation. Finally, casting of a bored pile is analysed using computational simulation implementing a porous medium representing the reinforcement cage. The concrete flow behavior and especially the filling of the concrete cover zone is analyzed for casting scenarios with different concretes varying in their rheological behavior. Simulations using the porous medium approach is 10x faster than simulations that explicitly model the reinforcements. Simulation results show that a good workability (low viscosity and low yield stress) of the initial batches of concrete must be maintained throughout pouring to avoid the risk of defect formation in the cover zone. Full article

High costs for the repair of concrete structures can be prevented if damage at an early stage of degradation is detected and precautionary maintenance measures are applied. To this end, we use numerical wave propagation simulations to identify simulated damage in concrete using convolutional neural networks. Damage in concrete subjected to compression is modeled at the mesoscale using the discrete element method. Ultrasonic wave propagation simulation on the damaged concrete specimens is performed using the rotated staggered finite-difference grid method. The simulated ultrasonic signals are used to train a CNN-based classifier capable of classifying three different damage stages (microcrack initiation, microcrack growth and microcrack coalescence leading to macrocracks) with an overall accuracy of 77%. The performance of the classifier is improved by refining the dataset via an analysis of the averaged envelope of the signal. The classifier using the refined dataset has an overall accuracy of 90%. Full article

Ultrasonic measurements are used in civil engineering for structural health monitoring of concrete infrastructures. The late portion of the ultrasonic wavefield, the coda, is sensitive to small changes in the elastic moduli of the material. Coda Wave Interferometry (CWI) correlates these small changes in the coda with the wavefield recorded in intact, or unperturbed, concrete specimen to reveal the amount of velocity change that occurred. CWI has the potential to detect localized damages and global velocity reductions alike. In this study, the sensitivity of CWI to different types of concrete mesostructures and their damage levels is investigated numerically. Realistic numerical concrete models of concrete specimen are generated, and damage evolution is simulated using the discrete element method. In the virtual concrete lab, the simulated ultrasonic wavefield is propagated from one transducer using a realistic source signal and recorded at a second transducer. Different damage scenarios reveal a different slope in the decorrelation of waveforms with the observed reduction in velocities in the material. Finally, the impact and possible generalizations of the findings are discussed, and recommendations are given for a potential application of CWI in concrete at structural scale. Full article

Damage in concrete structures initiates as the growth of diffuse microcracks that is followed by damage localisation and eventually leads to structural failure. Weak changes such as diffuse microcracking processes are failure precursors. Identification and characterisation of these failure precursors at an early stage of concrete degradation and application of suitable precautionary measures will considerably reduce the costs of repair and maintenance. To this end, a reduced order multiscale model for simulating microcracking-induced damage in concrete at the mesoscale level is proposed. The model simulates the propagation of microcracks in concrete using a two-scale computational methodology. First, a realistic concrete specimen that explicitly resolves the coarse aggregates in a mortar matrix was generated at the mesoscale. Microcrack growth in the mortar matrix is modelled using a synthesis of continuum micromechanics and fracture mechanics. Model order reduction of the two-scale model is achieved using a clustering technique. Model predictions are calibrated and validated using uniaxial compression tests performed in the laboratory. Full article

Concrete is a heterogeneous material with a disordered material morphology that strongly governs the behaviour of the material. In this contribution, we present a computational tool called the Concrete Mesostructure Generator (CMG) for the generation of ultra-realistic virtual concrete morphologies for mesoscale and multiscale computational modelling and the simulation of concrete. Given an aggregate size distribution, realistic generic concrete aggregates are generated by a sequential reduction of a cuboid to generate a polyhedron with multiple faces. Thereafter, concave depressions are introduced in the polyhedron using Gaussian surfaces. The generated aggregates are assembled into the mesostructure using a hierarchic random sequential adsorption algorithm. The virtual mesostructures are first calibrated using laboratory measurements of aggregate distributions. The model is validated by comparing the elastic properties obtained from laboratory testing of concrete specimens with the elastic properties obtained using computational homogenisation of virtual concrete mesostructures. Finally, a 3D-convolutional neural network is trained to directly generate elastic properties from voxel data. Full article

There is an increasing need for the development of novel technologies for tunnel construction in difficult geological conditions to protect segmental linings from unexpected large deformations. In the context of mechanized tunneling, one method to increase the damage tolerance of tunnel linings in such conditions is the integration of a compressible two-component grout for the annular gap between the segmental linings and the deformable ground. In this regard, expanded polystyrene (EPS) lightweight concrete/mortar has received increasing interest as a potential “candidate material” for the aforementioned application. In particular, the behavior of the EPS lightweight composites can be customized by modifying their pore structure to accommodate deformations due to specific geological conditions such as squeezing rocks. To this end, novel compressible cementitious EPS-based composite materials with high compaction potential have been developed. Specimens prepared from these composites have been subjected to compressive loads with and without lateral confinement. Based on these experimental data a computational model based on the Discrete Element Method (DEM) has been calibrated and validated. The proposed calibration procedure allows for modeling and prognosis of a wide variety of composite materials with a high compaction potential. The calibration procedure is characterized by the identification of physically quantifiable parameters and the use of phenomenological submodels. Model prognoses show excellent agreement with new experimental measurements that were not incorporated in the calibration procedure. Full article