B. Šavija
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This study systematically investigates the role of lattice–matrix stiffness contrast in governing confinement and mechanical performance of cementitious composites reinforced by 3D-printed auxetic (negative Poisson's ratio) lattices. Through combined compression testing, numerical simulations, and representative volume element (RVE) analysis, the mechanistic link between stiffness ratio and macroscopic response is established. The results demonstrate that sufficient stiffness contrast is a prerequisite for activating auxetic-induced confinement, enabling the translation of lattice lateral contraction into effective confinement on the cementitious matrix. Auxetic cementitious composites with 3D-printed steel lattice achieved a compressive strength exceeding 80 MPa (nearly 300% higher than plain mortar and polymer lattice reinforced composites). The specific energy absorption was 90% greater than the theoretical sum of the steel lattice and matrix, owing to the strong confinement and synergy enabled by the stiffness contrast. In contrast, polymer lattice reinforced composites, despite possessing the same geometry and similar negative Poisson's ratios, exhibited limited confinement efficiency as the low stiffness suppressed the transfer of auxetic deformation to matrix. RVE analyses revealed that the stiffness contrast between the lattice and matrix governs the mesoscale confinement behavior, which in turn influences the macroscopic strength, ductility, and energy dissipation capacity of auxetic cementitious composites. These findings establish stiffness contrast as the governing design parameter for auxetic cementitious composites and provide a basis for tailoring architected cementitious composites.
Auxetic cementitious cellular composites (ACCCs) offer high deformability that is attractive for mechanical energy harvesting when integrated with flexible piezoelectric materials. However, the intrinsic brittleness of cement-based materials and the complex coupling between auxetic geometry and damage evolution hinder the efficient design of ACCC energy harvesters. This study proposes a novel learning-driven design framework that, for the first time, integrates a physics-based energy harvesting model with Bayesian Optimization (BO) to directly optimize the recoverable hinge-like strain capacity of ACCCs for enhanced electrical output. The optimization maximizes the voltage generated by piezoelectric materials bonded at hinge regions, while using constraints to prevent splitting failure and non-auxetic behavior under compression. The energy harvesting model combines the concrete damage plasticity (CDP) model for pre-compression damage with a secondary elastic model for cyclic loading, enabling prediction of recoverable strain in generalized ACCC geometries. The learning-driven approach proved far more efficient than random generation in identifying optimal ACCC configurations. Experimental validation of the optimized design achieved a peak-to-peak voltage of nearly 15.0 V per cycle, about 2.7 times higher than a reference design. This study provides a learning-driven approach to designing enhanced compliant auxetic cementitious energy harvesters for smart infrastructure applications.
The use of Additive Manufacturing (AM) to create reinforcements for cementitious composites has become a popular research topic in recent years. One illustrative example is the integration of 3D-printed auxetic reinforcements into cementitious matrices, which exhibit superior energy absorption due to their negative Poisson's ratio. This presents the opportunity to tailor the Poisson's ratio of reinforcements to align with local stress distributions and enhance structural efficiency. In this study, Tailored Poisson's Ratio-reinforcements (TPR) were proposed, characterized by a linear gradient of Poisson's ratios along the height of the reinforcement to accommodate varying stress profiles within beams. Specifically, the top chords of TPR exhibit negative Poisson's ratios (auxetic), undergoing lateral contraction under compression and providing confinement to the surrounded matrix. Conversely, the bottom chords possess positive Poisson's ratios, contributing to lateral contraction under tension. These lateral deformations cause a shift in the principal stress state of the confined matrix, extending the loading path in stress space and actively delaying failure. Three novel Tailored Poisson's Ratio-reinforced Cementitious Composite (TPRCC) designs are developed and tested under four-point bending in this study. Experimental recordings indicate increases in load capacity and toughness of up to 191% and 6900% with respect to plain mortar, respectively.
Filament stitching
An architected printing strategy to mitigate anisotropy in 3D-Printed engineered cementitious composites (ECC)
Anisotropy in 3D-printed concrete structures has persistently raised concerns regarding structural integrity and safety. In this study, an architected 3D printing strategy, “stitching”, was proposed to mitigate anisotropy in 3D-printed Engineered Cementitious Composites (ECC). This approach integrates the direction-dependent tensile resistance of extruded ECC, the mechanical interlocking between three-dimensional layers, and a deliberately engineered interwoven interface system. As a result, the out-of-plane direction of the printed structure can be self-reinforced without external reinforcements. Four-point bending tests demonstrated that the “stitching” pattern induced multi-cracking and flexural-hardening behavior in the out-of-plane direction, boosting its energy dissipation to 343 % of the reference “parallel” printing and achieving 48.6 % of cast ECC. Additionally, micro-CT scanning and acoustic emission tests further validated the controlled crack propagation enabled by the engineered interface architecture. The proposed strategy has been proven to substantially alleviate anisotropy and enhance structural integrity.
Herein, a three-dimensional numerical model based on computational fluid dynamics (CFD) for fresh concrete is developed to predict the slump and slump flow. Fresh concrete is considered as a non-Newtonian fluid, and its rheological behaviour is characterised by the Bingham and Herschel-Bulkley (H-B) models, respectively. Experiments are also conducted to validate the reliability and accuracy of this model. Through parametric investigations, the influence mechanisms of relevant factors on the flow characteristics of fresh concrete are analysed and discussed. The results show that the model predictions agree well with the experimental results. The predicted results obtained using the H-B rheological model are more accurate compared to the Bingham model, with average relative errors of 1.73 %, 2.03 % and 3.95 % for slump, slump flow and T500, respectively. The flowability of fresh concrete is negatively correlated with power index, yield stress and consistency, while it is positively correlated with density. Grey relational analysis indicates that density has the greatest effect on the results of slump and slump flow, followed by yield stress and consistency, and finally the power index. The CFD-based numerical model presented in this study provides an important approach for better understanding the flow behaviour of fresh concrete from a rheological perspective.
This paper aims at enhancing tensile properties of strain-hardening alkali-activated composite (SHAAC) by using a flow-induced casting approach. Ca(OH)2-activated ground granulated blast-furnace slag (GGBS) was used as binder material and viscosity modifying admixture (VMA) was applied to adjust the rheology. Combined X-ray computed tomography (X-CT) scanning and image analysis were proposed to obtain the spatial distribution of polyvinyl alcohol (PVA) fibers in hardened SHAAC prepared with various VMA dosages using different (i.e. conventional and flow-induced) casting approaches. The results revealed optimal rheological properties (yield stress of 192 Pa, plastic viscosity of 17.6 Pa·s) of paste for fiber distribution and alignment. The SHAAC with fiber distribution and orientation factors of 0.91 and 0.83 was prepared using the flow-induced casting approach with a WMA dosage of 1.0 %. Its ultimate tensile stress and tensile strain capacity reached 6.1 MPa and 5.5 %, respectively, which was 37 % and 36 %, more than the conventionally cast SHAAC. In the end, an empirical equation for ultimate tensile strength and strain capacity prediction with high determination coefficient was proposed based on fiber distribution, orientation, and porosity.
The article ‘Improving mechanical properties and sustainability of high-strength engineered cementitious composites (ECC) using diatomite’, written by Xuezhen Zhu, Minghu Zhang, Jinyan Shi, Yiwei Weng, Çağlar Yalçınkaya, and Branko Šavija, was originally published in volume 57, issue 1, Article 11 without open access.
The extensive use of Ordinary Portland cement (OPC) in foamed lightweight concrete (FLC) contributes significantly to its carbon footprint. Concurrently, the disposal of industrial by-products carbide residue slag (CRS) and ground granulated blast furnace slag (GGBS) poses challenges. This study developed a sustainable foamed lightweight concrete system employing CRS-activated GGBS as a complete OPC substitute to address both engineering performance and environmental concerns. An optimal CRS/GGBS ratio (10/90) was determined for achieving the maximum compressive strength in the binder system. Compared to OPC, the CRS/GGBS binder exhibits remarkably low heat of hydration, enabling safer large-volume placements and effectively mitigating the risk of early-age thermal cracking. The prepared CRS/GGBS foamed concrete has much higher compressive strength than those made with cement due to refined air void structure with increased sphericity and improved flexural strength of the solid matrix. The life cycle assessment demonstrated that CRS/GGBS foamed concrete has the ability to decrease carbon emissions by as much as 80 % when compared to cement foamed concrete. This work establishes CRS/GGBS as a technically viable and environmentally superior binder for foamed lightweight concrete, offering enhanced compressive strength, lower thermal cracking risk, and a reduced carbon footprint compared to conventional cement systems in civil engineering.
Foamed cementitious composites with 3D-printed auxetic lattice reinforcement
Enhancing static and cyclic performance
This study develops a novel class of 3D-printed auxetic lattice reinforced foamed cementitious composites, aimed at overcoming the brittleness and low strength of conventional foamed cement while maintaining lightweight characteristic. Polymeric auxetic lattices (mechanical metamaterials with negative Poisson's ratio) were 3D printed and embedded in foamed cement matrix. Static and cyclic compression tests were conducted to evaluate load-bearing capacity, energy absorption, and failure mechanisms. X-ray computed tomography (CT) analysis was performed to examine interfacial behavior between the lattice and cement matrix. Results indicate that 3D auxetic lattices significantly enhance strength and ductility through multidirectional lateral confinement, where the energy absorption increased by up to 2.8 times compared to unreinforced foamed cement at a density of 550 kg/m3. Specifically, the 3D auxetic lattices reinforced composites showed pronounced resilience under cyclic loading, exhibiting gradual and ductile damage evolution while sustaining performance beyond 700 cycles. In comparison, 2D auxetic lattices which provide negative Poisson's ratio only in-plane are less effective in reinforcing foamed cement matrix. Additionally, although non-auxetic lattice increased load-carrying capacity to some degree, the corresponding composites structure showed localized shear failure and premature structural degradation under cyclic loading. Overall, the active reinforcement effect of auxetic lattices enables the development of advanced foamed cementitious composites for impact mitigation, blast protection, and buoyant components requiring energy absorption and repeated-load resilience.
This study investigates the influence of the deformability and fracture energy of the constituent material on the compressive response of auxetic cellular composites, using the finite element method (FEM) in ABAQUS/Explicit (version 2019). Four constitutive models were implemented: elastic-brittle, ideal elastic-plastic, strain-hardening, and strain-softening. The unit cell model was validated numerically against a larger 4 × 4 cellular structure and experimentally using strain-hardening cementitious composites with various deformability. Results show that auxetic behavior is unattainable with elastic-brittle constituent materials. For ideal elastic-plastic and strain-hardening materials, increasing the deformability and/or fracture energy leads to a larger critical strain, defined as the strain at which Poisson's ratio recovers from negative to zero under compression. Conversely, strain-softening materials exhibit the opposite trend. For structures comprising three ductile constituents, both load-bearing capacity and energy absorption performance improve with enhanced material properties, most notably for the strain-hardening material. However, a key finding is that increasing the deformability or fracture energy of the constituent material causes a significant reduction in the ratio of energy absorption of the structure to that of its constituent material. This indicates that merely enhancing the deformability and fracture energy of the constituent material does not guarantee improved energy absorption of cellular composites, demonstrating that optimal design of cellular composites requires a synergistic balance between the material and structure, rather than solely maximizing material properties. These insights provide critical guidance for designing high-performance auxetic cellular composites.
Auxetic cementitious cellular composites (ACCCs) exhibit hinge-type recoverable deformation during auxetic behavior phase, a rare pseudo-elastic property in cementitious materials. However, their low load-bearing capacity during this phase restricts their use in high-load applications. This study developed ACCCs using strain-hardening cementitious composites (SHCCs) with short (SHCC-SS) and long (SHCC-LS) softening tails, fabricated by additive manufacturing-assisted casting. Uniaxial compression tests employing Digital Image Correlation (DIC) evaluated their compressive behavior, peak strength, Poisson's ratio variation, and energy dissipation. Cyclic tests after pre-compression assessed their recoverable deformation resilience, with fiber bridging at joint cracks examined using digital optical microscope. Results were compared to a reference using fiber-reinforced cementitious materials with strain softening (SS). Compared to the reference (SS), ACCCs using SHCC mixtures exhibit superior load-bearing capacity and stable auxetic behavior under compression. After self-contact, they maintain a negative Poisson's ratio up to a considerably high compressive strain, preventing splitting failure and preserving structural integrity. This is because incorporating SHCC enables greater joint rotation by promoting multiple cracks with strain hardening, which delays primary crack formation and reduces its opening. During cyclic tests, P1-shaped ACCCs with SHCC-LS and SHCC-SS enhance the elasticity modulus of recoverable deformation by 4.8 and 3.0 times, respectively, compared to SS. SHCC-LS outperforms SHCC-SS in compressive resilience due to its prolonged softening tail, which improves fiber bridging in primary cracks and increases rotational stiffness in hinge joints. SHCC mixtures with initial strain hardening and extended softening enable scalable design of advanced auxetic cementitious materials across various load levels.
When serving in the marine environment, reinforced concrete structures are prone to be attacked by chloride ingress, which generally co-occurs with varying humidity and temperature changes. Therefore, considering the interaction between moisture transport and heat transfer, and their individual and coupling effects on chloride transport, this paper presents a novel numerical modelling framework for chloride penetration in concrete under different environmental conditions. In this framework, a novel thermal conductivity model and temperature-depended chloride binding isotherms are also developed, considering the heterogeneous characteristics of concrete. The proposed model is validated against a series of experimental data. By assuming the cyclic humidity and temperature boundary conditions as trigonometric type, this study further discusses the effect of average value, amplitude value and period length of cyclic environmental changes on the chloride transport in concrete. The results indicate that variation in humidity and temperature averages can alter the peak values of chloride content but have less effect on the chloride penetration depth. However, the increased humidity amplitude could significantly promote both the peaks and the penetration depths due to intensive chloride convection caused by moisture transport. This paper is supposed to provide a better understanding of chloride penetration in concrete under a realistic engineering environment.
The microstructure of cement paste determines the overall performance of concrete and therefore obtaining the microstructure is an essential step in concrete studies. Traditional methods to obtain the microstructure, such as scanning electron microscopy (SEM) and X-ray computed tomography (XCT), are time-consuming and expensive. Herein we propose using Denoising Diffusion Probabilistic Models (DDPM) to synthesize realistic microstructures of cement paste. A DDPM with a U-Net architecture is employed to generate high-fidelity microstructure images that closely resemble those derived from SEM. The synthesized images are subjected to comprehensive image analysis, phase segmentation, and micromechanical analysis to validate their accuracy. Findings demonstrate that DDPM-generated microstructures not only visually match the original microstructures but also exhibit similar greyscale statistics, phase assemblage, phase connectivity, and micromechanical properties. This approach offers a cost-effective and efficient alternative for generating microstructure data, facilitating advanced multiscale computational studies of cement paste properties.