Modulus Of Concrete Research Articles

Effects of Initial Defects on Effective Elastic Modulus of Concrete with Mesostructure

Effects of Initial Defects on Effective Elastic Modulus of Concrete with Mesostructure

Laboratory and Field Evaluation of Asphalt Concrete Modulus &Critical Strain Inputs for M-E Flexible Pavement Design in the State of Illinois

This study aims to update the current algorithm for modulus prediction of hot mix asphalt in the state of Illinois-USA. Numerically, laboratory, and field-obtained modulus and strain levels were connected to advances in asphalt materials and current design criteria. Four mix designs were selected and combined with seven different binders for modulus measurements. The reference experimental results were compared to: the current Illinois Department of Transportation (IDOT) modulus algorithm, traditional regression models, a Bayesian Neural Network (BNN) model, and field measurements obtained using the Traffic Speed Deflectometer. Results showed that the current IDOT algorithm under-predicts modulus and BNN (840 data points, R^2 = 0.986) outperformed the Witczak and Hirsch models. Field modulus and critical strains were sensitive to temperature and showed considerable variability, but confirmed that HMA in perpetual pavement sections performs under low strain levels. These findings guided considerations for an updated design method: realistic modulus prediction can be achieved using data-driven methods and less conservative strain criterion might be considered.

Effect of nonlinear stress-dependency and cross-anisotropy on the backcalculation outputs from the TSD deflection slopes and the effect on estimated pavement performance

ABSTRACT The Traffic Speed Deflectometer (TSD) is a mobile vehicle that measures deflection slopes. Deflection slopes have been utilised in previous studies to backcalculate pavement layers’ moduli. However, the nonlinear stress-dependency and cross-anisotropy of unbound granular materials and fine-grained soils were overlooked in those studies. Utilising the Finite Element Method (FEM) based on static analysis in this study to evaluate a three-layered flexible pavement system with specific material properties and layer thicknesses revealed that neglecting the nonlinear stress-dependency of base and subgrade layers underestimated the permanent deformation life of the backcalculated pavement by more than 45%. Neglecting the cross-anisotropy of the base layer with the design anisotropy ratio of 0.5 increased the backcalculated Asphalt Concrete (AC) modulus by more than 21%, increased the estimated permanent deformation life of the pavement by more than 160%, and decreased the backcalculated base modulus by around 28%. Neglecting the cross-anisotropy of the subgrade with the design anisotropy ratio of 0.5 almost increased the estimated permanent deformation life of the pavement by 15%. The results underscore the necessity to consider the nonlinear stress-dependency and cross-anisotropy of unbound granular materials and fine-grained soils in backcalculating pavement layers’ moduli from TSD deflection slopes.

Ensemble machine learning models for compressive strength and elastic modulus of recycled brick aggregate concrete

This study delivers an in-depth analysis of predicting the compressive strength and elastic modulus of recycled brick aggregate concrete (RBAC). It assembles an extensive database of 633 compression test results and develops five ensemble learning models—random forest (RF), gradient boosting regression trees (GBRT), extreme gradient boosting (XGB), light gradient boosting machine (LGBM) and stacking (St). These models are evaluated against existing empirical formulas with respect to their effectiveness. The findings reveal that machine learning (ML) models outperform existing formulas: for compressive strength prediction, traditional models achieve a maximum determination coefficient R² of 0.38, whereas ML models attain an R² range of 0.91–0.94. For elastic modulus, the highest R² values are 0.44 for traditional models and 0.97 for ML models. Notably, the LGBM and St models excel in predicting compressive strength and elastic modulus, respectively. The study also identifies critical parameters influencing RBAC’s compressive behavior and highlights their impact trends. Remarkably, while the mass-weighted water absorption of coarse aggregates and the replacement ratio of recycled brick aggregates (RBAs) have less impact on compressive strength compared to the effective water-to-cement ratio, they become more influential for elastic modulus. Additionally, the decrease in elastic modulus due to higher RBA replacement ratios or increased mass-weighted water absorption of coarse aggregates exceeds the corresponding reduction in compressive strength. This research not only deepens the understanding of RBAC’s mechanical properties but also provides valuable predictive tools for civil engineering applications.

Durability analysis of metakaolin recycled concrete under sulphate dry and wet cycle

This study aims to enhance the durability, cost-effectiveness, and sustainability of recycled fine aggregate concrete (RFAC) subjected to the combined effects of wet-dry cycles and sulfate erosion. Dry–wet cycle tests were conducted in RFAC with different admixtures of biotite metakaolin (MK) and 15% fly ash (FA) mix (M) under 5% sulfate erosion environment. The effect of 0%, 30%, 60% and 90% recycled fine aggregate (RFA) replacement of natural fine aggregate on mass loss, cubic compressive strength, relative dynamic modulus test of RFAC, damage modeling and prediction of damage life of concrete were investigated. The results showed that the concrete cubic compressive strength and relative dynamic modulus were optimal for recycled concrete at 15% MK biotite dosing and 60% RFA substitution, and its maximum service life was accurately predicted to be about 578 cycles under 5% sulfate dry–wet cycling using Weibull function model. This study is pioneering in addressing the durability of RFAC under sulfate attack combined with wet-dry cycling, employing a novel approach of incorporating MK and FA into RFAC. The findings highlight the practical application potential for using MK and FA in RFAC to produce durable and sustainable construction materials, particularly in sulfate-exposed environments. This research addresses a critical challenge in the construction industry, providing valuable insights for developing more durable and eco-friendly construction materials and contributing to long-term sustainability goals.

Stress–strain characteristics of fire‐exposed recycled coarse aggregate concrete

AbstractConcrete sustainability and performance under extreme conditions are of growing interest in construction engineering. This study delves into the influence of recycled coarse aggregate (RCA) content and elevated temperatures on normal‐strength concrete containing RCA. Five different concrete compositions, featuring varying content of RCA (ranging from 0% to 100%), were examined. The heating and subsequent cooling followed the ISO‐834 temperature–time graph up to 800°C. The primary objective was to evaluate residual properties, including the stress–strain behavior, compressive and tensile strength, secant elastic modulus, peak strain, and bond strength of RCA concrete. The findings reveal a consistent decrease in both strength and stiffness parameters of RCA concrete with rising temperatures, while peak strain exhibits a rapid increase at elevated temperatures. Interestingly, RCA content had a negligible impact on the relative deterioration of high‐temperature exposed RCA concrete compared to that at ambient conditions. Moreover, the bond behavior closely resembled that of natural aggregate concrete when used in moderate proportions. Degradation models based on regression analysis of the data were used to quantify the bond strength reduction for RCA‐based concrete and the slip of rebar concerning various temperatures. Importantly, these models demonstrated consistency with those applicable to conventional concrete.

Comparative analysis of microdamage-affected chloride transport in concrete under static and dynamic hydraulic pressure

Concrete structures in marine environments frequently encounter the adverse impacts of hydraulic pressure, leading to a decrease in their durability. This study aims to conduct a comparative analysis of the internal microdamage in concrete when subjected to static and dynamic hydraulic pressure of equal intensity, and to examine the influence of such damage on chloride transport. By employing potentiometric titration, MIP, N2 adsorption, and AFM tests, the chloride concentration, pore structure parameters, and microscale elastic modulus of concrete under static and dynamic hydraulic pressure were analyzed. The results indicate that dynamic hydraulic pressure accelerates chloride transport in concrete. Compared with static hydraulic pressure, dynamic hydraulic pressure — sustained at the same intensity—results in an elevated threshold pore size along with an increased most probable pore size of the concrete. Furthermore, dynamic hydraulic pressure induces the expansion of microcracks, consequently decreasing the microscale elastic modulus of concrete. The use of mineral admixtures can effectively mitigate the damage evolution of concrete microstructure subjected to dynamic hydraulic pressure. Besides, a model is developed for relative chloride diffusion based on the principle of energy conservation and from the evolution law of the microscale elastic modulus gleaned from AFM tests. Through calculations, it can be found that the crack propagation rate and the decline rate of the relative chloride diffusion coefficient Df1Df2 increase markedly when dynamic hydraulic pressure intensity surpasses 40,000 Pa. The propagation of the crack length is moderated by a larger initial crack width.

Effect of recycled concrete aggregates on the punching strength of slab-column connections without shear reinforcement

This paper presents the results of tests on six reinforced concrete slab-column connections. The slabs were octagonal, centrally supported on square columns, and concentrically loaded at their borders. The tests investigated the effects of replacing natural coarse aggregates with recycled concrete aggregates. The experimental results were also compared to resistance estimates from ACI 318 (2019) and Eurocode 2 (2004) and results from a database with tests on slabs without recycled concrete aggregates. The results show that using RCA reduces the concrete's modulus of elasticity and tensile strength but has little effect on its compressive strength. Furthermore, using RCA has little impact on the flexural response and punching resistance of the slabs. The findings suggest that RCA has potential for use in concrete applications, but further tests are required to draw definitive conclusions.

Effect of Polypropylene Fibre on Self- Compacting High-performance Concrete

This study conducted tests on the design mixture of Polypropylene Fibre Reinforced Self-Compacting High-performance Concrete (PFRSCHPC) and Self-Compacting high-performance concrete (SCHPC) to determine the mechanical properties of the concrete, and the beams behaviour under bending loads. The composition of the mixtures of PFRSCHPC and SCHPC refer to Oesman, et al. (2022), which conducted research on UHPC (ultra-high-performance concrete) using natural sand and crushed stone through a 4.75mm sieve. PFRSCHPC and SCHPC compositions using Portland Slag Cement (PSC); 1% superplasticizer and 30% silica fume of the total binder; 1% Polypropylene fibre (PP); the ratio of� sand to crushed stone 45%: 55%; and the w/b was 0.23. However, SCHPC as the control concrete mixture does not contain PP. The testing results of the PFRSCHPC showed compressive strength, tensile strength, flexural strength, and modulus of elasticity were 42.73 MPa; 4.33 MPa; 8.98 MPa; 45.51 GPa, respectively. When compared to SCHPC, PP has an influence in increasing tensile strength by 2.38 MPa (122.05%), flexural strength by 2.67 MPa (42.77%), and concrete elasticity modulus by 6.67 GPa (17.32%). However, 1% PP decreased compressive strength of PFRSCHPC, lower by 4.93 MPa (10.34%) compared to SCHPC. PFRSCHPC beam reached a peak load of 27.5 kN; initial stiffness of 5.32 kN/mm; ductility of 5.6; and toughness of 1606.08 kNm. PFRSCHPC beam with PP fibre content of 1% are able to increase 17.02% of peak load; 14.75% of ductility, and 113.91% of toughness.

Using ensemble machine learning and metaheuristic optimization for modelling the elastic modulus of geopolymer concrete

Geopolymer concrete emerges as a sustainable and durable alternative to conventional concrete, addressing its high carbon footprint and enhanced durability. The distinct properties of geopolymer concrete, governed by supplementary cementitious materials and alkaline activators, promise reduced environmental impact and improved structural resilience. However, its complex composition complicates the prediction of mechanical properties such as the elastic modulus, crucial for structural applications. This study introduces an innovative approach using the eXtreme Gradient Boosting (XGBoost) technique integrated with the multi-objective grey wolf optimizer to model the elastic modulus of geopolymer concrete. By dynamically selecting influential features and optimizing model accuracy, this methodology advances beyond traditional empirical models, which fail to capture the nonlinear interactions intrinsic to geopolymer concrete. Utilizing a comprehensive database gathered from extensive literature, 22 potential variables were examined that influence geopolymer concrete’s elastic modulus. After mitigating multicollinearity and optimizing hyperparameters via Bayesian optimization, six XGBoost models were developed with different combinations of input variables, revealing compressive strength and total water content as pivotal predictors. The findings illustrate the models’ precision, with the trade-off between prediction accuracy and model simplicity visualized through the relationship between the number of input variables and prediction error. The study culminates in a user-friendly graphical user interface that enables easy prediction of geopolymer concrete’s elastic modulus and fosters educational engagement. This interface, available online, underscores the practicality and accessibility of advanced machine learning predictions. Overall, this research not only provides a robust predictive framework for geopolymer concrete’s elastic modulus using optimized input variables but also enhances the understanding of its underlying determinants, contributing to the advancement of sustainable construction materials.

Effect of aggregate type on strength and deformation properties of high-strength concrete during heating

Introduction. High-strength concrete is widely used in contemporary construction. Expanded introduction of high-strength concrete necessitates the need for studying its behavior at high temperatures (in case of fire) in order to ensure the required fire resistance of load-bearing reinforced concrete structures made of high-strength concrete in terms of fire safety of buildings and structures.Aim. To determine the effect of aggregate types on strength and deformation characteristics of high-strength B100 concrete when heated to temperatures from 100 °C to 800 °C with a step of 100 °C.Materials and methods. Laboratory tests of prism strength and elastic modulus of basalt and granite high-strength concrete were carried out on prism samples in a heated state according to standard methods using special heating equipment combined with laboratory pressure equipment.Results. The authors determined structure behavior factors of basalt and granite high-strength concrete during heating, specifying the decrease in compressive strength and elastic modulus. Deformation diagrams during axial compression of high-strength granite and basalt concretes under heating were drawn.Conclusions. The dynamics of reduction in strength and deformation properties is similar for granite and basalt high-strength concrete under heating and is specific for silicate aggregate concretes. The elastic moduli of basalt high-strength concrete are higher than those of granite high-strength concrete, both at 20 °C and when heated, thereby determining the dependence of high-strength concrete deformation properties on the types of aggregates. Deformation diagrams during the axial compression of high-strength granite and basalt concretes showed specific character: unilinear – when heated to temperatures of about 300–400 °C, bilinear – at higher heating temperatures, therefore differing from traditional ideas and theoretical recommendations.

Research on axial compressive performance of ceramic concrete reinforced with HTPP fibers

This study investigates the influence of High-Toughness Polypropylene (HTPP) fiber content (0 %, 0.3 %, 0.6 %, 0.9 %) on the axial compressive performance of ceramsite concrete. Four sets of ceramsite concrete cube and prism specimens were prepared, and the cube compressive strength and full stress-strain curves for each set were tested. Based on the experimental results, it analyzed the variation characteristics of HTPP fibers on the stress-strain curve of ceramic concrete at different stages, studied the peak stress, peak strain, elastic modulus, toughness, and energy absorption capacity of ceramic concrete. Finally, the stress-strain curve has been fitted. The results indicate that: HTPP fibers can significantly enhance the strength and toughness of ceramic concrete, the compressive strength of the cube increased by 23.8 %, the axial compressive strength increased by 19.0 %, the residual stress increased by 143.0 %, the absolute modulus increased by 164.1 %, the toughness increased by 51.5 %, and the energy dissipation coefficient increased by 9.4 %. By fitting the experimental curve, the mathematical expression for the uniaxial compressive stress-strain curve of ceramic concrete reinforced with high tenacity polypropylene (HTPP) fibers has been proposed. The model matches well with the experimental results, which provides a theoretical basis for the structural analysis and design of this type of concrete.

An Experimental Study on Compressive Properties of Composite Fiber Geopolymer Concrete

Background: The production process of Portland cement (OPC) consumes energy and releases carbon dioxide, which affects the environment. It has been found that geopolymer cementing material is a better substitute for it. The strength effect of fiber on geopolymer materials is the basis of the application of fiber geopolymer concrete in structural beams, slabs, and other components. Methods: Geopolymer concrete was prepared with fly ash, slag, and water glass as the main raw materials, and the effects of fiber type, quality, and blending method on the compressive properties and elastic modulus of geopolymer concrete were compared to explore the working mechanism of fiber-reinforced geopolymer concrete. Results: Through experimental research, the results showed that in 0.2% flocculent lignin fibers, when the mass ratio of carbon fibers was increased, the strength of the geopolymer concrete decreased. Due to the increased mass ratio of wavy steel fibers, comprising 0.2% flocculent lignin fibers, the strength enhancement effect was not apparent. Moreover, with regard to enhancing the modulus of elasticity of geopolymer concrete, blending fibers exerted the most significant effect. The fiber was added to geopolymer concrete to form a three-dimensional supporting frame system. When cracks occurred under the action of force, the development of cracks was limited due to the fibers, and the bonding slip delayed the propagation of cracks. The composite fiber could make full use of the advantages of each material and improve the strength of geopolymer concrete. Conclusion: The compressive properties of geopolymer concrete could be enhanced by blending single-fiber or mix-fibers, and the effect of mix-fibers was more optimal than that of others. The above research results provide a theoretical reference for the design of geopolymer concrete and a theoretical basis for the application of fiber geopolymer concrete in structural beams, slabs, and other components.

Fast prediction of concrete equivalent modulus based on the random aggregate model and image quadtree SBFEM

Abstract To evaluate the mechanical property of concrete materials rapidly, a fast prediction model of the concrete equivalent modulus is proposed based on the random aggregate model and scaled boundary finite element method (SBFEM). First, a random aggregate model of meso-concrete is employed to construct the representative volume element (RVE) according to the aggregate content, gradation, shape, etc. Second, the RVE model is transformed to be a grayscale image and stored as a digital matrix. The quadtree mesh is partitioned automatically for simulation by SBFEM. There are only six types of unique subdomains, and the hanging node does not affect the simulation accuracy. The global stiffness matrix can be assembled directly according to the six subdomain stiffness matrices. Finally, the equivalent modulus is predicted by using the numerical homogenization method. Several numerical examples are employed to verify this model, and the results are compared with that of other methods. The result indicates that the proposed model can efficiently determine the equivalent modulus. Furthermore, the effect of the aggregate gradation, shape, porosity, and pore water are studied and analysed in this work. The proposed model is potential and helpful in predicting the mechanical properties of concrete or other composite materials.

Preparation and Performance Study of Rapid Repair Epoxy Concrete for Bridge Deck Pavement.

With the rapid development of bridge construction, the service life of bridges and traffic volume continue to increase, leading to the gradual appearance of diseases such as potholes and cracks in bridge deck pavements under repeated external loads. These issues severely impact the safety and service life of bridges. The repair of bridge deck potholes and cracks is crucial for ensuring the integrity and safety of bridge structures. Rapid repair materials designed for this purpose play a critical role in effectively and efficiently addressing these issues. In order to address the issues of pavement diseases, this study focuses on the rapid repair of epoxy concrete for bridge deck pavements and its performance is studied using experimental methods. Firstly, carbon black, rubber powder, and other materials were used to improve the elastic modulus and aging resistance of the epoxy concrete. Secondly, the addition of solid asphalt particles provided thermal sensitivity to the repair material. Finally, various properties of the rapid repair epoxy concrete for bridge deck pavements were tested through experiments including compressive strength testing, elastic modulus measurement, thermal sensitivity testing, and anti-UV aging testing. The experimental results show that adding carbon black and rubber powder reduces the elastic modulus of epoxy concrete by 25% compared to normal epoxy concrete, while increasing its aging resistance by 1.8%. The inclusion of solid asphalt particles provided thermal sensitivity to the repair material, contributing to better stress coordination between the repair material and the original pavement material under different temperature conditions. The epoxy concrete has early strength, toughness, and anti-aging properties, making it suitable for rapid repair of bridge deck pavement.

A Comprehensive Literature Review on the Elastic Modulus of Rock-filled Concrete

A Comprehensive Literature Review on the Elastic Modulus of Rock-filled Concrete

РАЗРАБОТКА ЭКСПЕРИМЕНТАЛЬНОГО МЕТОДА ОПРЕДЕЛЕНИЯ ТЕРМОСТОЙКОСТИ ЖАРОСТОЙКИХ БЕТОНОВ

In the article, the authors propose a non-destructive resonance method for assessing the resistance of concrete and destructive processes during their cyclic heating and cooling. The results of experimental studies of changes in the resonant frequency, the limit bending strength, elastic modulus of heat-resistant concrete at cyclic heating.

Enhanced asphalt dynamic modulus prediction: A detailed analysis of artificial hummingbird algorithm-optimised boosted trees

This study introduces and evaluates a novel artificial hummingbird algorithm-optimised boosted tree (AHA-boosted) model for predicting the dynamic modulus (E∗) of hot mix asphalt concrete. Using a substantial dataset from NCHRP Report-547, the model was trained and rigorously tested. Performance metrics, specifically RMSE, MAE, and R2, were employed to assess the model's predictive accuracy, robustness, and generalisability. When benchmarked against well-established models like support vector machines (SVM) and gaussian process regression (GPR), the AHA-boosted model demonstrated enhanced performance. It achieved R2 values of 0.997 in training and 0.974 in testing, using the traditional Witczak NCHRP 1-40D model inputs. Incorporating features such as test temperature, frequency, and asphalt content led to a 1.23% increase in the test R2, signifying an improvement in the model's accuracy. The study also explored feature importance and sensitivity through SHAP and permutation importance plots, highlighting binder complex modulus |G∗| as a key predictor. Although the AHA-boosted model shows promise, a slight decrease in R2 from training to testing indicates a need for further validation. Overall, this study confirms the AHA-boosted model as a highly accurate and robust tool for predicting the dynamic modulus of hot mix asphalt concrete, making it a valuable asset for pavement engineering.

Assessment of residual prestress in existing concrete bridges: The Kalix bridge

The direct socio-economic consequences of the deterioration of aging infrastructure systems have triggered a continuous process of revising and updating current design standards and guidelines for critical network components. Specifically, long-term degradation processes demand the analysis and evaluation of vital structural assets such as prestressed concrete bridges. It is crucial to develop theoretically consistent, user-friendly, and non-destructive methodologies that engineering professionals can employ to prevent and mitigate potential catastrophic outcomes during the service life of these bridges. This study provides a thorough review of the available testing methods employed over the years for prestressed concrete bridges and introduces a comprehensive framework for evaluating existing methods for residual prestress force assessment. Through a multi-criteria selection process, the three most feasible tests were designed and carried out on an existing 66-year-old balanced cantilever box girder bridge exposed to freezing temperatures that affected the instrumentation plan and test execution. Finally, predictive models compliant with standard codes were calibrated based on the experimental results and the life cycle loss of prestress forces was evaluated to assess relevant bounding intervals. Findings reveal limited on-site testing and discrepancies between calculated residual forces and predictions by standard codes. The saw cut method showed a 18% difference from the initial applied prestress according to the prestress protocol, suggesting the use of a cover meter and concrete modulus evaluation for improved accuracy. The strand cutting method resulted in a 14% difference, emphasizing the need for stress redistribution assessment. The second-order deflection method showed a 6% difference, indicating a focus on enhanced boundary conditions and thorough sensitivity analysis for future investigations.

УТОЧНЕННЯ РОЗРАХУНКОВОГО ЗНАЧЕННЯ МОДУЛЯ ПРУЖНОСТІ АСФАЛЬТОБЕТОНІВ

Introduction. One of the most important characteristics of asphalt concrete that characterizes its properties is the elasticity modulus. The elasticity modulus of asphalt concrete is used in the design of pavement structures to calculate its permissible elastic deflection, under the condition of shear resistance of the working subgrade layer and the layers of non-cohesive materials, as well as bending tensile strength. Problem statement. Today, the calculated value of the elasticity modulus of asphalt concrete is taken in accordance with Handbook No. 2 «Design Characteristics of Asphalt Concrete» [2]. In this Handbook, the calculated value of the elasticity modulus of asphalt concrete is given depending on the bitumen grade, temperature, type of asphalt mixture, and time of load action. Numerical design values of the elasticity modulus of asphalt concrete are provided only for asphalt concrete type B; for other types of asphalt concrete, it is proposed to reduce or increase the design value of the elasticity modulus by the value that depends on the type of asphalt concrete and temperature. Since 2020, a new standard on technical requirements for bitumen has been in force in Ukraine, which brings bitumen grades in line with the European classification [4]. At the same time, in the Handbook No. 2 [2], the calculated value of the elasticity modulus of asphalt concrete is given in accordance with the previous bitumen grades, which necessitates their adjustment.