Comparison of methods for estimating Young's moduli of mortar specimens.

Precisely estimating material parameters for cement-based materials is crucial for assessing the structural integrity of buildings. Both destructive (e.g., compression test) and non-destructive methods (e.g., ultrasound, computed tomography) are used to estimate Young's modulus. Since ultrasound estimates the dynamic Young's modulus, a formula is required to adapt it to the static modulus. For this formulas from the literature are compared. The investigated specimens are cylindrical mortar specimens with four different sand-to-cement mass fractions of 20%, 35%, 50%, and 65%. The ultrasound signals are analyzed in two distinct ways: manual onset picking and full-waveform inversion. Full-waveform inversion involves comparing the measured signal with a simulated one and iteratively adjusting the ultrasound velocities in a numerical model until the measured signal closely matches the simulated one. Using computed tomography measurements, Young's moduli are semi-analytically determined based on sand distribution in cement images. The reconstructed volume is segmented into sand, cement, and pores. Young's moduli, as determined by compression tests, were better represented by full-waveform inversions (best RMSE = 0.34 GPa) than by manual onset picking (best RMSE = 0.87 GPa). Moreover, material parameters from full-waveform inversion showed less deviation than those manually picked. The maximal standard deviation of a Young's modulus determined with FWI was 0.36, while that determined with manual picking was 1.11. Young's moduli from computed tomography scans match those from compression tests the closest, with an RMSE of 0.13 GPa.

The Slump Flow of Cementitious Pastes: Simulation vs. Experiments.

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.

Computational Generation of Virtual Concrete Mesostructures.

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.

Reduced Order Multiscale Simulation of Diffuse Damage in Concrete.

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.

Sensitivity of Ultrasonic Coda Wave Interferometry to Material Damage-Observations from a Virtual Concrete Lab.

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.

Cementitious Composites with High Compaction Potential: Modeling and Calibration.

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.