Behavior Of Concrete Research Articles

Experimental Study on Concrete Strength Behavior Using Plastic Waste as a Partial Replacement of Fine Aggregate

Waste from plastic materials is outstripped due to the growth of industrialization and urbanization. Plastic materials are non-biodegradable; decomposition is not possible all the time. The recycling of plastic materials by using them in concrete will be a great deal for plastic management. This research investigation aims to measure the optimum percentage of plastic in concrete without a reduction in concrete strength and shear behavior of reinforced concrete. Using the provision of Mix Design ACI 211.1-91, the M28 concrete grade was created. Plastic materials have been collected and passed through a No-4 sieve (4.76mm). The combination of fine aggregates and ground plastic materials (RPET, PP) in the weight fraction of fine aggregate mix (0%, 2%, 4%, 6%, 8%, 10%) was used in the concrete. Concrete beams (750´150´150 mm) are reinforced with two 12 mm longitudinal steel bars in the tension zone, with proper clear cover for testing the shear capacity. In order to conduct the compressive and tensile splitting test, concrete specimens with a diameter of 100 mm and a height of 200 mm were used. The experimental findings demonstrate guidelines for using plastic as a partial replacement within 2% to 4% of fine aggregate to produce the best outcomes.

Study on crack propagation behaviors of three-point bending concrete beams with small span-depth ratios

Three-point bending (TPB) beams with small span-depth ratios, i.e. TPB beams with the same span of 400 mm but various depths (100 mm, 150 mm and 200 mm), were tested to study the crack propagation behaviors of concrete. The evaluations of crack extension resistance curve (KR-curve), fracture process zone (FPZ) length, lFPZ, and crack tip opening displacement (CTOD) were studied. The digital image correlation (DIC) technique was utilized to monitor the entire loading process. Moreover, the effects of strain rates (10−5/s, 10−4/s, 10−3/s and 10−2/s) on the fracture process of TPB beams with small span-depth ratios (2, 2.5 and 3) were discussed based on findings in literature. The results shown that (1) with the increase of specimen depth from 100 mm to 200 mm, the obtained KR-curves and initial fracture toughness were not influenced by the small span-depth ratios, while different increase trends were observed for the unstable fracture toughness, the average maximum value of lFPZ and the value of CTOD. (2) With the loading rate increasing from 10−5/s to 10−2/s, the obtained KR-curve and the maximum length of FPZ increased slightly, while the evolution of CTOD was not affected by the loading rate.

Microscopic interface deterioration mechanism and damage behavior of high-toughness recycled aggregate concrete based on 4D in-situ CT experiments

High-toughness recycled aggregate concrete (HTRAC), as an innovative green building material, showcases outstanding performance and environmental attributes. To investigate its microscopic structural characteristics and the mechanisms of damage evolution under loading, a series of 4D in-situ X-ray computed tomography (CT) experiments were conducted under uniaxial compression conditions. During the experimental process, detailed scans were performed on six key loading points (0 %, 30 %, 60 %, and 100 % of the peak load, 70 % and 40 % of the post-peak load of the specimen). Advanced three-dimensional image processing techniques were utilized to conduct a comprehensive analysis of internal features within the specimen, including pores, steel fibers, and cracks. The evolution of damage in HTRAC was characterized by both qualitative 2D crack slice analysis and quantitative 3D reconstruction analysis of cracks. Changes in the average grayscale values of CT cross-sectional images were also examined. The deterioration mechanism of recycled aggregate concrete interface cracks was elucidated by the combination of CT images and modeled HTRAC. Furthermore, a statistics model illustrating the interaction mechanism between damage, cracks, and strain was proposed. This study provides technical and theoretical support for the further promotion and application of high-toughness recycled aggregate concrete.

Analysis of the effect of aggregate type on the dynamic behaviour of concrete

This paper focuses on how different aggregate types affect the dynamic response of concrete. While Split Hopkinson Pressure Bar (SHPB) is commonly used to assess dynamic behaviour through the dynamic increase factor (DIF), the specific influence of aggregate type, a major component of concrete, remains unclear. This influence is investigated using fast Fourier transform analysis of strain signals. Two different types of aggregates, sandstone and schist, with distinct geological origins and mineral compositions, are used to examine this effect. Energy analysis is performed to understand how aggregate type affects energy absorption. The fineness modulus of fractured specimens is also determined which allow the comparison of post-fracture grain sizes. A crucial link between aggregate type and dynamic response of concrete is observed. Stiffer aggregates lead to stiffer concrete, which influence the frequency of energy responsible for damage initiation. At lower strain rates, concrete with stiffer aggregates absorbs lower-frequency energy. However, as strain rate increases, the frequency of absorbed energy becomes more dependent on the extent of damage within the aggregates themselves. The type of aggregate also significantly affects the size distribution of the fractured material. To analyse the stress distribution under dynamic loading, numerical simulations are carried out. These simulations showed that the maximum stress in concrete is related to the stiffness of the aggregate.

Effects of high temperatures on the behavior of reactive powder concrete based on recycled brick powder

Effects of high temperatures on the behavior of reactive powder concrete based on recycled brick powder

Mechanical properties, hydration behavior and shrinkage deformation of ultra-high performance concrete (UHPC) incorporating MgO expansive agent

To reduce the extremely high autogenous shrinkage deformation of ultra-high performance concrete (UHPC) caused by low water-to-binder ratio and high binder materials content, this work aimed to designed and prepared low shrinkage UHPC containing MgO-based expansive agents (MEA). The effects of UHPC with different reactivity of MEA (R-MEA and S-MEA) were compared in terms of fluidity, mechanical properties, hydration characteristics, shrinkage deformation, pore structure and microstructure. The results indicated that the incorporated of MEA decreased the fluidity and mechanical properties of UHPC, while the autogenous shrinkage deformation was compensated significantly. When 6 % R-MEA was incorporated, the flow and compressive strength decreased by 16 % and 7.9 %, respectively, but the autogenous shrinkage at 7 days also decreased by 70.1 % at the same time. The same amount of S-MEA showed lower compensation for the autogenous shrinkage of UHPC than R-MEA, but with the same reduction in compressive strength loss. This was due to the highly reactive R-MEA showed higher hydration degree and larger swell increment, which caused more compensation for shrinkage in UHPC, while it had slight adverse effect on the strength development. It is worth noting that the compensation effect of autogenous shrinkage is very limited when the doping is higher than 6 % for either MEA, but the loss of mechanical properties is serious. In addition, the microstructure showed that the crystal growth pressure of brucite forced the pastes to expand and thus resulted in increase on the porosity for UHPC. This study provides a feasible and effective way for mitigating the autogenous shrinkage of UHPC.

Modeling the effect of material heterogeneity on the thermo-mechanical behavior of concrete using mesoscale and stochastic field approaches

The adverse impact of high temperatures on concrete is a well-recognized issue that can lead to significant mechanical deterioration and structural integrity loss. Factors such as aggregate type, cement composition, temperature, duration of exposure, and moisture content can substantially influence the fire resistance of concrete. To simulate and better understand the effects arising from the heterogeneity of concrete in a fire situation, a mesoscale approach is proposed, using the Mesh Fragmentation Technique (MFT) to assess the complex thermo-mechanical behavior of concrete. The MFT introduces high aspect ratio interface elements to model crack propagation and interfacial transition zones by means of an appropriated tensile damage constitutive law. In this extended framework, a fully-coupled thermo-mechanical model is proposed. The modeling approach includes considerations of both macroscopic and mesoscopic scales, in which the coarse aggregate, mortar matrix and interfacial transition zones are represented. Besides, a stochastic distribution is assumed for the material properties to account for the lower scale heterogeneity. The main novelty proposed in this study consists in the synergy of mesoscale and stochastic approaches that are herein combined to model the effect of heterogeneity on the concurrent macro-mesoscale thermo-mechanical behavior of concrete. To validate the numerical model’s capabilities in capturing thermally induced cracks, benchmark cases and a simulation of a bending beam exposed to elevated temperatures are presented. The results demonstrate the potential of the proposed approach in predicting the behavior of concrete subjected to thermal loading and the role played by heterogeneity in the thermally induced cracking.

Machine learning-based classification of quality grades for concrete vibration behaviour

The vibration behaviour of the vibrating rods is one of the key factors for the quality of concrete vibration that is essential for the long-term safety of concrete structures. Although many vibration operation regulations have been widely applied, evaluating method for concrete vibration samples is relatively rare. To fill this gap, this paper proposes a concrete vibration data acquisition system and attempts to perform a quality analysis of samples employing machine learning that amalgamates various parameters. The experimental results demonstrate that the data collection system to identify the vibration state achieves an accuracy of 93.75% and an accuracy of 90.3% in classifying vibration quality levels. The proposed method can classify and evaluate concrete quality levels, which strongly supports the visualization of concrete vibration process and the implementation of autonomous robot vibration. In the future, improving the reliability of the system and enhancing the accuracy of algorithms will be the focused.

Spatio-Temporal Compressive Behaviors of River Pebble Concrete and Sea Pebble Concrete in Island Offshore Engineering

Obtaining river or sea pebbles from local resources for concrete production is considered an economical and eco-friendly alternative, particularly in marine and island-offshore engineering. However, the resulting changes in the mechanical properties of these concrete have attracted attention. This study investigates the compressive behavior of concretes where river or sea pebbles partially (i.e., 33% and 67%) or fully (i.e., 100%) replace traditional gravel as coarse aggregate, using a noncontact full-field deformation measurement system based on digital image correlation (DIC). Compared to the traditional gravel concrete (GC), compressive strengths of the river pebble concrete (RPC) at constitution rates of 33%, 67%, and 100% decreased by 6.5%, 29.8%, and 38.9% while those values of the sea pebble concrete (SPC) decreased by 13.1%, 32.7%, and 44.3%, respectively. Meanwhile, SPC exhibited slightly lower compressive strength than RPC. The peak strains of both SPC and RPC decreased at lower substitution rates, although their stress-strain curves resembled those of GC. In contrast, RPC and SPC at higher substitution rates exhibited a noticeable stage of load hardening. Full-field deformation data and interfacial characteristics indicated that the compressive failure modes of both RPC and SPC showed significant interfacial slipping between pebbles and mortar with increasing coarse aggregate substitution rates. In comparison, fractures in coarse aggregate and mortar were observed in damaged GC. The study demonstrated that the spatio-temporal compressive deformation response and failure modes of SPC and RPC were distinct due to the introduction of pebbles, providing insights for engineering applications of river/sea pebble concrete in practical offshore or island construction projects.

Influence of fire severity and concrete properties on the thermo‐hygral behavior of concrete during fire exposure

AbstractSince the world is transitioning toward performance based design, the study of thermo‐hygral behavior of concrete when subjected to real fire becomes crucial. Fire accidents have revealed that nominal fire curves cannot be applied because of varying severity of real fire. In 2008, traveling fire concept was developed in which severity is dependent on heat release rate and fire size. This study explores the effect of fire severity and other concrete properties like strength, aggregate type, and relative humidity. The proposed model has been developed by combining the principles of mechanics and thermodynamics and upon validation with the experimental results, a reasonable agreement has been observed. It can be concluded that severity of fire is directly related to thermo‐hygral behavior of concrete. On the other hand, this study also highlights the influence of type of aggregate and moisture content in addition to the traditional variables like volume fraction of solid and permeability. On studying the influence of type of aggregate, it can be concluded that recycled aggregate concrete performed better than conventional concrete. The integration of proposed model in the performance based design is a leap toward development of resilient structure subjected to dynamic fire conditions.

Optimization of Hybrid Fiber-Reinforced Concrete for Controlling Defects in Canal Lining.

Losses in irrigation canals occur during the process of water transportation. In irrigation conveyance water losses, seepage loss is the main contributor to total water loss. The most problematic factors are cracks and settlement of the lined canal in canal lining structures. Water loss occurs in earth channels, mainly due to erosion and the permeability of the material. The concrete, as it does not present cracks, will have a less impermeable layer. Usually, seepage loss comprises 20-30% of the total water loss, and it can be reduced to 15-20% with canal linings. By enhancing the flexure and split tensile strength of concrete, the rate of cracking in the canal lining can be controlled. Concrete's split tensile strength is one of the most important factors in crack control. The behavior (compressive, flexural, and split tensile properties, water absorption, linear shrinkage mass loss, etc.) of hybrid polypropylene and jute fiber-reinforced concrete (HPJF-RC) for the application of canal linings was studied. In this experimental work, a total of nine mixes were made with different lengths and contents of hybrid polypropylene and jute fiber-reinforced concrete (HPJF-RC) and a control mix. The SEM analysis was performed to explore the hybrid fiber cracking mechanism and the bonding of fibers with the concrete. The crack arresting mechanism of the HPJF-RC will help to reduce water losses in concrete canal linings. With this modern material, the water losses in canal linings can be minimized. The results of this experimental work would be helpful as a reference for both industry experts and academic researchers interested in the advancement of HPJF-RC composites.

Optimizing pervious concrete with machine learning: Predicting permeability and compressive strength using artificial neural networks

This study makes a significant contribution to the field of pervious concrete by using machine learning to innovatively predict both mechanical and hydraulic performance. Unlike existing methods that rely on labor-intensive trial-and-error experiments, our proposed approach leverages a multilayer perceptron network. To develop this approach, we compiled a comprehensive dataset comprising 271 sets and 3,252 experimental data points. Our methodology involved evaluating 22,246 network configurations, employing Monte Carlo cross-validation over 20 iterations, and using 4 training algorithms, resulting in a total of 1,779,680 training iterations. This results in an optimized model that integrates diverse mix design parameters, enabling accurate predictions of permeability and compressive strength even in the absence of experimental data, achieving R² values of 0.97 and 0.98, respectively. Sensitivity analyses validate the model's alignment with established principles of pervious concrete behavior. By demonstrating the efficacy of machine learning as a complementary tool for optimizing pervious concrete mix designs, this research not only addresses current methodological limitations but also lays the groundwork for more efficient and effective approaches in the field.

Influence of calcined sediment inputs on the mechanical behavior of fiber-reinforced concrete in an aggressive environment

Dredged sediments and granite waste seriously threaten the environment and the oceans. In this work, we evaluated the Fergoug dam deposits as mineral materials for partially replacing Portland cement. The sediments were fired in a convection kiln at 450 degrees Celsius. This study aims to discover a sustainable cementitious material extracted from recycling residual sediments and granite, which can be an alternative to metakaolin (MK), usually used to reinforce cement compositions. Three concrete formations partially replaced Portland cement (CEM I 42.5 N). The first content was applied at 10% calcined sediment (CS), the second was 10% granite powder (GP), and the third was a mixture of 5% CS and 5% GP. Formations are detected and compared to vibrating concrete by placing them in aggressive media such as sulfuric acid and seawater solutions and evaluating their compressive strength and weight loss properties. SCCCSGP showed similar durability performance to the CV reference mix, including weight loss and electrical resistance. At the same time, using 10% CS gave good results regarding compressive strength and mass loss compared with using 10% GP alone. As for aggressive media, the results presented for the seawater solution were less aggressive than those of the sulfuric acid solution.

Development of a learner model tool for predicting strength and embodied carbon for lightweight concrete production

The demand for sustainable concrete in meeting the net zero carbon target places a burden in optimizing concrete response to structural strength that satisfy acceptable embodied carbon. In most cases, a low carbon concrete is deficient in structural requirement and vice versa. This dilemma informs the need for a tool that can predict compressive strength as well as embodied carbon using the same input data. Since the use of alternative materials as cement replacement to enhance sustainability is emerging in the quest for a sustainable concrete, an optimal material that satisfy both conditions of structural integrity and sustainability is still lacking. Paucity of data in the emerging lightweight low carbon concrete using alternative materials, portends an upheave in the bias for prediction of the behaviour of lightweight low carbon concrete. This study therefore uses concrete data of lightweight low carbon concrete from laboratory experiment for the prediction of compressive strength and embodied carbon with their performance evaluated using eight machine leaning regression models. The results obtained indicates that the XG boost regression model exhibited excellent performance with a low Mean Squared Error (MSE) of 50.15, Mean absolute error(MAE) = 5.26, Mean absolute percentage error(MAPE) = 11.76 %, Explained variance score = 0.97, Root mean square error(RMSE) = 7.08 and a high R squared value of 0.96. The tool predicted compressive strength and embodied carbon for lightweight carbon concrete using multiple output regression such that the output can be limited to the yearly structural embodied carbon threshold to achieving 2050 net zero target. The developed tool when compared with concrete of similar mix ingredients performed more than 95 % in predicting concrete compressive strength and associated embodied carbon. In line with the inclusion of embodied carbon in carbon regulations of buildings in the UK as suggested by the professionals in the construction industry, the developed learner model and prediction tool has integrated concrete strength and embodied carbon to initiate a holistic approach to design and construction, balancing performance, cost, and environmental impact.

Modeling of reinforced-concrete cutting with shield rippers using FEM-DEM-coupling method

With the increase in the number of underground structures, it is common to encounter reinforced concrete (RC) pile foundations of existing buildings or bridges during shield machine tunneling in densely constructed urban areas. The cutting of RC piles with the shield machines is a challenging task due to cutter damage and cutting efficiency issues. In this paper, the interaction between a ripper and an RC was studied based on the FEM-DEM coupling method. A three-dimensional transient dynamic model of two typical rippers (angular ripper and curved ripper) cutting RC piles was established, respectively. In the FEM-DEM coupling model, the mechanical behavior of concrete was described via DEM, and the impact of steel bars in concrete was considered via FEM. In addition, an experimental verification was conducted to validate the effectiveness of the numerical results. The damage characteristics of the steel bars and concrete, and the force patterns of the rippers were analyzed. The influence of the geometric parameters of the ripper, including blade width, blade angle, and blade anterior angle on the cutting performance was also investigated through a parametric study. Some recommendations are made for the geometric design of rippers used for cutting reinforced concrete. The results of this study could provide some references for cutting RC obstacles with a shield machine.

Numerical Simulation for Strength and Stability of RC Tapered Columns

This study investigates the strength and stability of Reinforced Concrete (RC) linearly tapered square columns. Evaluating the slenderness ratio of an RC column requires the radius of gyration of its cross-section, which is well-defined for a prismatic column but not for a non-prismatic one. This study primarily investigates the application of the ACI Code formulae to evaluate the slenderness ratio of RC columns with the studied geometry. Validated numerical models, using Abaqus, were employed to perform nonlinear first- and second-order analyses on the investigated columns subjected to eccentric axial loads. The concrete damaged plasticity model was employed to simulate the nonlinear behavior of concrete. The static Riks solver, available in Abaqus, was utilized for nonlinear analyses: first, with an inactivated geometric nonlinearity for a first-order analysis, and second, with an activated geometric nonlinearity to consider the effects of secondary moments (p-δ effects). The findings indicate the reliability of defining the slenderness ratio of an RC linearly tapered column based on the ACI Code formulae, using the average cross-section of the tapered column.

Numerical Analysis on Fatigue Behavior of Plain Concrete and Alkali-activated Concrete

Abstract Alkali-activated concrete (AAC) has recently gained a lot of potential to become one of the most recommended sustainable replacements for Ordinary Portland cement concrete (OPCC). In the present investigation, an attempt has been made to study the static and fatigue flexural behavior of AAC compared to that of OPCC by using numerical modeling FEA software, ABAQUS. The nonlinear behavior of the stress-strain curve of the concrete has been studied using the concrete damage plasticity (CDP) model. A 2D notched beam was modelled using plane stress condition and three-point bending tests were performed under monotonic loading to obtain the static behavior of concrete. The result obtained has been utilized to fix the loading range for cyclic loads in fatigue analysis and at different loading frequencies. The load-CMOD curves and load-deflection curves were obtained for both static and fatigue loading, and the number of cycles to failure during fatigue. From the results, it has been observed that the Ordinary Portland cement concrete specimens sustain more load than that of Alkali-activated concrete under monotonic loading. However, AAC has shown more resistance to fatigue than that of the OPCC and the frequency of loading significantly influences the fatigue performance.

Effects of cold-bonded artificial aggregate properties on the behaviour of concrete

The study investigates the use of artificial aggregates (AAs), specifically manufactured from ground granulated blast furnace slag (GGBFS) and ordinary Portland cement (OPC), to mitigate environmental harm caused by illegal quarrying due to the scarcity of natural aggregates (NAs). A cold-bonded pelletization technique was employed to produce five types of AAs with varying proportions of GGBFS & OPC as 82.5:17.5, 85:15, 87.5:12.5, 90:10, 95:5. The AAs with maximum OPC content exhibited a density of 1298 kg m−3, water absorption of 4.8%, and crushing and impact values of 28.6% and 26.3%, respectively. The impact of these AAs on concrete properties was assessed, revealing that AAs facilitated the production of workable concrete with low-density ranges between 1700–2337 kg m−3. Despite a decrease in concrete strength with higher AAs content, structural requirements were met, demonstrating AAs’ potential to effectively substitute natural coarse aggregates (NCAs). The concrete microstructure confirmed the formation of a strong interfacial transition zone (ITZ) and strength-developing cement-hydrated products. This research underscores the scientific contribution of AAs to address aggregate scarcity sustainably and recommends its application in structural elements by experimental validation.

Mesoscale modelling and simulation of irradiation-induced expansion in concrete

The effects of irradiation on concrete is a topic of concern in nuclear applications, where for some specific members the material may be exposed at long-term to significant levels of neutron radiation. In this study, the effects of radiation-induced volumetric expansion (RIVE) of aggregates on concrete behaviour are investigated numerically at the mesoscale. Cylindrical concrete specimens constituted of 3 phases, namely mortar matrix, polyhedral aggregates and interfaces between both of these phases, are generated in 3D. Besides RIVE of aggregates, temperature increase due to the energy deposited during the irradiation, drying and damage development are considered in the finite element simulations. A phase-field approach and a cohesive-zone model are applied to describe damage in the matrix and interfaces, respectively. The simulation results are compared to experimental data of concrete specimens exposed to significant neutron fluences exceeding 6 × 10–19 n/cm2, in terms of residual Young modulus, compressive strength, temperatures evolution and overall expansion of the specimens. Globally, with an adequate calibration of parameters and in particular those related to the damage evolution laws, the simulation results of residual mechanical properties are in relatively good agreement with the experimental data. In addition, specimen expansions are well reproduced, providing that RIVE effects are also considered for the mortar phase, which is justified by the significant volume fraction of embedded sand grains. Mortar RIVE is modelled with the same approach as aggregate RIVE by applying a proportionality parameter, whose effect is discussed. Finally, simulations predict an intense drying of the specimens due to temperature increase.

Numerical Study on Static and Fatigue Behavior of Alkali-Activated Fly Ash Concrete Modelled using Concrete Damage Plasticity (CDP) Model

Abstract Alkali-activated concretes (AAC) are considered as an alternative to Portland cement concretes because of their much lower carbon emissions. To study its characteristics is of utmost importance. In the present research, an attempt is made to create a numerical model to analyze the static and fatigue flexural behavior of alkali-activated fly ash concrete (FC) and compare them with ordinary Portland cement concrete (PCC). Three-point bending tests are simulated for the monotonic load to obtain the static behavior of a 2D notched rectangular beam. A 2D beam specimen of size 262.5 mm x 75 mm, with a notch of size 15 mm x 3 mm was provided at the bottom middle. Fly ash-based alkali-activated concrete (FC) and corresponding PCC of similar strength are modeled in ABAQUS CAE using the concrete damage plasticity (CDP) model. The ultimate loads, maximum deflection, and CMOD for each of them were obtained from the history output manager. The results of monotonic tests are utilized for creating a sinusoidal load cycle for fatigue tests with various loading frequencies and stress ratios. Different structural responses are examined under the fatigue test. The results showed that FC performs better than PCC under static and fatigue tests. Fatigue performance of both FC and PCC is influenced by the frequency of loading and fatigue life increases at higher frequencies. It is also found that stress reversal negatively impacts the fatigue life of both FC and PCC.