Coarse Aggregate Particles Research Articles

A coarse aggregate particle size classification method by fusing 3D multi‐view and graph convolutional networks

A coarse aggregate particle size classification method by fusing 3D multi‐view and graph convolutional networks

Optimizing multi-recycled concrete for sustainability: Aggregate gradation, surface treatment methods and life cycle impact assessment

Utilizing demolished waste as recycled aggregate in concrete is a sustainable practice, however, the concerns over inconsistent quality, such as hardened mortar content and water absorption, hinder global adoption. This study evaluates the physical, microstructural properties and gives insights into Life Cycle Impact Assessment of three generations of recycled aggregate concrete. The microstructure analysis yielded compelling insights into the role of Interfacial Transition Zone (ITZ) of reclaimed aggregate on concrete. The study demonstrated that the effective proportioning of coarse and fine aggregate particles using Compressible Packing Model (CPM), resulted in a reduction of dosage of cement in concrete volume, reducing the Binder Intensity Index (BII), and an improvement in the strength and stability of concrete. Additionally, surface treatment methods, including water soaking, mechanical, and thermo-mechanical treatments, were explored. The thermo-mechanical treatment method proved to be effective in reducing 40–60 % of residual mortar. Life cycle assessment of treated and untreated recycled aggregate concrete was performed, considering five environmental impact indicators viz., Global Warming Potential (GWP), Acidification Potential (AP), Eutrophication Potential (EP), Abiotic Depletion Potential (ADP) and Human Toxicity (HT). These indicators illustrated that CPM method of mix proportioning accompanied with thermo-mechanical treatment of repurposed aggregate resulted in lowering environmental impact. These findings underscore the potential for sustainable concrete construction through the use of treated recycled aggregate, offering valuable insights into methods for augmenting its quality and performance.

Effects of coarse aggregate size on thickness and micro-properties of ITZ and the mechanical properties of concrete

This research delves into the impact of coarse aggregate particle size on the mechanical properties of concrete. Nano-indentation and scanning electron microscope (SEM) techniques were applied to characterize the micro-properties and thickness the Interfacial Transition Zone (ITZ). The effect of coarse aggregate size on concrete's compressive strength (σc) and elastic modulus (E) and the relationship between the micro properties of the ITZ and the macro properties of concrete were discussed. In addition, Griffith's microcrack theory was adopted to explain related mechanisms. The relationship between the microscopic properties of the ITZ and the macroscopic properties of concrete was discussed. The results show that, in concrete with a low water cement-ratio w/c (0.3), thickness of ITZ increased with the coarse aggregate size and concrete properties decreased. While, in concrete with a higher w/c (0.4), there exists an optimum coarse aggregate size for the lowest thickness of ITZ and highest strength. Taking the ITZ as the initial crack in concrete failure, concrete properties can be linked to ITZ thickness from Griffith's microcrack theory.

Development of new numerical approach to the flow and segregation behaviors of fresh concrete considering rebar restraint and its application in reinforced lightweight aggregate concrete

Although there are many studies on flow simulation methods for fresh concrete, there are very few studies on casting simulation of reinforced concrete, and in these studies the reinforcing bars are treated only as static boundaries without their restraining effect on the concrete flowing between them. In this study, we first developed a new numerical method based on the MPS method for simulating the flow and segregation behaviors of fresh concrete during casting reinforced member, considering the restraint of reinforcing bars by applying a normal stress to the concrete. Fresh concrete was treated as the double-phase granular fluid that follows a non-linear rheological model, and was represented by matrix mortar, and coarse aggregate particles with actual sizes and random shapes. Then, as an application of this numerical method, the flow and segregation behaviors of lightweight aggregate concrete (LWAC) in an L-shaped box with rebars were numerically investigated in addition to measurement. The comparison of the numerical and experimental results shows that this numerical method allows the LCA volume fraction to be calculated within 3 % error in predicting the segregation behavior of LCA in reinforced LWAC, and improves the accuracy of the flow simulation of LWAC by about 1.5 times. Furthermore, this numerical method can double the accuracy of concrete flow prediction, compared to treating the reinforcement as a static boundary.

Influence of mortar thickness on the dynamic segregation of high-fluidity concrete

The properties of concrete are related to the mesostructure decided by the constituents. This study aims to establish a quantitative relationship between the dynamic stability of fresh concrete and the mesoscopic parameters. A novel method named the declined table test is used to evaluate the dynamic segregation tendency of fresh concrete continuously. With the VSI method provided by ASTM C1611 in contrast, it is demonstrated that using the ratio of the flow angle of mortar to the flow angle of concrete (Am/Ac) obtained from the declined table test is credible as the dynamic segregation index. The concrete with an Am/Ac ratio lower than 1.5 is regarded to be in a stable state. According to the mortar filming ability test, the mortar in concrete can be divided into stable mortar and free mortar. Stable mortar saturation degree is proposed to reveal the mechanism of dynamic stability from the mesoscopic view, which is defined as the specific value of the volume fraction of stable mortar and total mortar (SDv) or the specific value of stable mortar thickness and mortar thickness between coarse aggregate particles (SDt). In contrast, SDt has a better correlation to the Am/Ac ratio and the SDt value should be higher than 1.14 to guarantee enough stability of fresh concrete.

A novel method for predicting coarse aggregate particle size distribution based on segment anything model and machine learning

Particle size distribution (PSD) is an important index property of granular materials. The conventional mechanical sieve analysis for PSD determination is labor-intensive, time-consuming, and inefficient. With the development of computer vision, image-based gradation prediction methods gradually emerge. However, previous studies mainly focused on images where individual aggregate particles are separated from each other without overlapping (i.e., not densely packed together), thus limiting their applicability. This study proposed a novel framework to predict the PSD of densely packed coarse aggregate particles, which is based on visual foundation model and machine learning with appropriate feature engineering. First, the segment anything model, which is one of the visual foundation models, was used for the instance segmentation of the densely packed aggregate particles. Then, the feature engineering was implemented with the segmentation result. The major quantitative indicators related to particle sizes were extracted from each mask, such as the area, the diameter of minimum enclosing circle, and the major axes of the equivalent ellipse of particle contours. Subsequently, the cumulative distribution curves of these indicators were plotted, followed by the data sampling operation on these curves to generate the feature vectors. The artificial neural network (ANN) model was then trained for gradation prediction with each of the feature vectors and the data points extracted from PSD curves used as the inputs and data labels, respectively. The model-training dataset consisted of 8160 different sets of digitally generated particle samples with known PSDs. Finally, verification test results of additional five different groups of digital particle samples and real coarse aggregate samples with known PSDs show that the root mean squared error (RMSE) of predicted aggregate sizes is 1.79 mm and 1.86 mm for digital and real aggregate particle samples, respectively. Therefore, the efficacy and feasibility of the proposed method was validated in terms of predicting the PSD of densely packed coarse aggregates from two-dimensional image information. As compared to the Mask RCNN combined with empirical formula of which the RMSE values were 5.12 mm and 5.84 mm for digital and real aggregate particle samples, respectively, the proposed framework demonstrates improved particle segmentation applicability and better PSD prediction accuracy.

Computer Vision-Based Estimation of The Effects of Vibration in Slipform Paving

Slipform paving is a complex multistep process encompassing concrete pouring, vibration, consolidation, correction, and curing. One of the most critical aspects in the process is that the frequency and duration of vibration can influence the distribution of coarse aggregate particles in the cured concrete. However, there is still a fundamental lack of methodologies to formally characterize the interrelationships between vibration characteristics and the quality of the cured pavement. This study aims to address this issue by proposing a novel toolset for the assessment of the spatial features of coarse aggregate distribution in doweled pavements. This system is based on paver consolidation simulations and employs computer vision as the primary tool for analysis. The experimental protocol, recently developed by the authors, employs coarse aggregate particles color-coded by gradation to aid in recognizing the distribution of different granulometric sizes within the specimens. High-resolution, two-dimensional digital images obtained from cured specimens were used to analyze aggregate characteristics, orientation, and dispersion, with particular emphasis on quantifying the effect of the distance from the vibrator head on such parameters. The results showed that the proposed digital imaging processing techniques were capable of quantitatively characterizing the distribution of coarse aggregate particles in the specimens. Moreover, novel metrics were proposed to characterize the quality of the consolidation based on the digital image data.

One-Dimensional Modeling of the Pressure Loss in Concrete Pumping and Experimental Verification

An accurate formula for calculating the pressure loss in concrete pumping plays a significant guiding role in the design and service process of pump trucks. Based on the flow characteristics of concrete pumping, a straight pipe one-dimensional model for the pressure loss is developed, in which both the viscous force of the mortar in the lubrication layer and the blocking effect of coarse aggregate particles are considered. First, the complex geometrical shapes of the aggregate particles are geometrically reconstructed by using a HandySCAN noncontact scanner and the reverse modeling software Geomagic Design X (v.19.0.2). Then, the equivalent spherical size of nonspherical aggregate particles is calculated according to the equal hydraulic radius principle. The blocking effect of the aggregate particles is converted into the wall roughness. Finally, an explicit expression for the pressure loss in concrete pumping is deduced by using Modi’s equation, Bernoulli’s equation, and Darcy’s formula, and the calculated value is compared with the measured value at a corresponding experimental site. The results indicate that the pressure loss values calculated with the one-dimensional flow model are closer to the actual pumping pressure loss values. The relative error between the results and the actual pumping pressure loss value is about 20.2%.

Bond strength model between steel rebar and ultrahigh performance concrete containing coarse aggregates

To clarify the bond performance between steel rebar and ultrahigh performance concrete containing coarse aggregates (UHPC-CA), a total of 33 pull out specimens was cast. The effects of coarse aggregate particle size, coarse aggregate content, and steel fiber content on the failure modes and bond stress-slip curves of the specimens were studied. Based on the virtual crack model, considering the tensile contribution of steel fibers and the bridging effect of coarse aggregates, a model for the bond strength between UHPC-CA and steel rebar was established. The research findings indicated that there was a corresponding matching relationship between coarse aggregate particle size and the spacing of steel rebar ribs. In the 5–8 mm particle size group, the specimens showed 7.95% and 9.01% increases in bond strength compared to the 3–5 mm and 8–10 mm particle size groups, respectively. When the coarse aggregate content of UHPC-CA was 20%, the bond strength was the highest, increasing by 11.39% compared to specimens without coarse aggregates. The bond strength first increased and then decreased with increasing steel fiber content. Excessive steel fiber content could lead to the clustering of steel fibers, reducing the effective number of steel fibers contributing to toughening. The calculated results from the established bond strength model were compared with experimental and literature results, yielding an average ratio of 0.993 and a standard deviation of 0.166. This model effectively predicts the bond strength between UHPC-CA and steel rebar.

The dam that fly ash built.

When the first concrete was poured in 1949 for the Hungry Horse Dam (Montana, USA), pozzolan cements had already been used in several major North American dams, including Grand Coulee on the Columbia River (diatomaceous earth explored but ultimately not used), Friant on the San Joaquin River and Altus on the North Fork Red River (pumicite) and Bonneville on the Columbia River and Davis on the Colorado River (calcined clay). But Hungry Horse Dam stands out as the first dam constructed using coal combustion fly ash. Utilising 2.4 million cubic metres of concrete, the dam is located on the South Fork Flathead River, one of the tributaries feeding one of the nation's major waterways, the Columbia River, and closely related to the adjacent Glacier National Park. In this respect, Hungry Horse is directly connected to two momentous periods in modern history - the massive adoption in the 1950s of coal as fuel for power plants, and the ongoing threats to fresh water supply and the rapid retreat of alpine glaciers due to global warming. Two concrete cores from this dam, one with fly ash and one without fly ash, are examined microscopically to explore the long-term suppression of alkali-aggregate reaction by fly ash. The core without fly ash exhibits clear evidence of alkali-aggregate reaction, manifested by sandstone coarse aggregate particles with darkened reaction rims. Sandstone coarse aggregate particles of the same lithology in the core with fly ash are without signs of alkali-aggregate reaction. A detailed examination of the darkened rims indicates that alkali-silica reaction products fill the narrow gaps between adjacent sand grains in the sandstone. This alkali-silica gel infilling allows for optical continuity between adjacent sand grains and is responsible for the classic darkened rim associated with the alkali-aggregate reaction.

Wear characteristics of the pipeline transporting cemented paste backfill containing coarse aggregate

Cemented paste backfill (CPB) offers unique advantages for managing tailings and underground mining voids, sometimes incorporating coarse aggregate. The pipeline is crucial for transporting CPB that contains coarse aggregate (CPBC), and excessive wear can compromise safety and continuity of transportation. However, the wear characteristics of the pipeline that transports CPBC are not well understood. In this study, wear tests were conducted using a novel self-designed instrument to investigate the impact of CPBC mass fraction (76–84%), flow velocity (1.0–2.5 m/s), coarse aggregate content (0–35%), and coarse aggregate particle size (1.05–7.34 mm). The results indicate that the wear rate increases in a power-law manner with both flow velocity and the size of coarse aggregate particles. The wear rate exhibits a non-monotonic trend with increasing CPBC concentration, initially rising, then declining before sharply increasing. With an increase in coarse aggregate content, the wear rate initially decreases slowly and then increases rapidly. The inflection point in the wear rate is associated with the interconversion between abrasion and erosion, which is governed by the yield stress of CPBC. Given the same material composition and wear type, and minimal variation in aggregate particle size, a higher yield stress of CPBC results in a higher wear rate. Abrasion and erosion dominate the total wear, contributing an average of 71.3%. The findings facilitate the selection of CPBC recipes and pipe materials to mitigate excessive pipe wear, while also providing significant potential for predicting pipe wear based on yield stress of paste.

Effects of the particle morphology and volume fraction of coarse aggregate on the mechanical properties of concrete

The morphology and volume fraction of coarse aggregate particles significantly influence the mechanical characteristics of concrete. This paper presents the development of a numerical model for pebble concrete by combining experiments with the discrete element method. The mesoscopic parameters between mortars and the contact surface between mortars and aggregates in the model were calibrated by comparing simulated stress–strain relationships with experimental data from pebble concrete. Subsequently, the model and mesoscopic parameters were validated by comparing them with experimental results. The obtained mesoscopic parameters were then utilized in the numerical modeling of uniaxial compression for single-shaped coarse aggregate concrete. Results showed that the peak stress of the elliptical aggregate concrete was 2.8 MPa higher than that of the oblate spherical aggregate concrete, leading to more cracks and severe damage in the former. Thus, elliptical aggregates proved more suitable as coarse aggregates for concrete than oblate spherical aggregates. Furthermore, the study investigated the influence of ellipsoidal aggregate volume fraction on concrete strength. The compressive strength reached the highest when the volume fraction of ellipsoidal aggregate was 57%. Therefore, the ideal coarse aggregate volume fraction was determined to be 57%. These results offer valuable insights into designing concrete mix proportions.

Mechanistic evaluation of segregation in HMA mixtures

Segregation in hot mix asphalt (HMA) mixtures is defined as the separation of the coarse aggregate particles in the mixtures from the rest of the mass. Segregation can be a result of aggregate stockpiling and handling, production, storage, truck loading practices, construction practices, and equipment adjustments. Segregation is usually evaluated visually, which is considered as a subjective method with no definite limits and depends on the evaluator’s opinion.This study uses two mechanistic surface texture indicators, i.e., mean texture depth (MTD) that is measured using sand patch method and mean profile depth (MPD) using laser texture profilometer to evaluate if a road section is segregated or not.The sand patch method is standardized in ASTM E965 -15 (2019) “for Measuring Pavement Macrotexture Depth Using Volumetric Technique”. MPD is covered by the international standards ASTM E1845-15 “Standard Practice for Calculating Pavement Macrotexture Mean Profile Depth”.Using both measured MTD values at grid point crossings, and average MPD values at 25 m intervals in the wheel paths, in addition to the use of statistical analysis of the obtained data, assuming that the obtained data are normally distributed and finding the 95% probability limits of the MTD and MPD values, it is possible to prove the closeness of the obtained texture depth indicator data, homogeneity of the road section, and that the segregation is only present at very limited localized locations.

Three-Dimensional Angularity Characterization of Coarse Aggregates by the Optimal Ellipsoid Approximation Algorithm

The three-dimensional (3D) angularity of coarse aggregates was investigated in this study by an optimal ellipsoid approximation algorithm. The minimum volume enclosing ellipsoid (MVEE) of the 3D coarse aggregate particle represented by the surface point cloud was computed by a Python program. An algorithm was proposed to compute the optimal ellipsoid that is inscribed in the aggregate particle as far as possible. In the algorithm, a fitting index was proposed and a cycle program was coded to search the optimal ellipsoid. Based on the optimal ellipsoid and the point cloud of the coarse aggregate particle, a 3D angularity index was proposed. The critical discriminant coefficient was introduced into the angularity index to filter out the tiny convex parts on the particle. Six 3D geometric models were generated and five 3D aggregate particles were randomly selected to verify the effectiveness of the angularity index. The results demonstrate that the angularity index proposed in this study can effectively distinguish the angularity of different geometric models. The effect of mesh precision on the angularity index was analyzed and the critical discriminant coefficient was studied by the parameter analysis method and Delphi expert investigation method.

3D-printed concrete permanent formwork: Effect of postcast concrete proportion on interface bonding

Using 3D concrete printing technology to produce permanent formwork for building components is a promising method that maximizes design freedom and material savings. In this study, 3D-printed permanent formwork made of concrete with coarse aggregate is manufactured and post cast with concrete containing different coarse aggregate particle size ratios. The results indicate that the splitting tensile strength of the concrete interface reaches 2.3 ∼ 4.4 MPa, of which the reduction rate range from 12.8%∼35.7% with higher bonding positions. Mesoscopic observation reveals the voids concentration and a lack of coarse aggregate phenomenon in the interface area. Increasing the proportion of small-sized coarse aggregates in the pouring concrete can better fill and improve the splitting strength of the interface area.

Effect of coarse aggregate characteristics on the permeability properties of pervious concrete

This study analyses the effect of the geometric characteristics of coarse aggregate particles on the physical-mechanical properties and durability of hardened permeable concrete prepared by vibropressing compaction method. Four types of coarse aggregate were used to prepare the concrete mixture: gravel and crushed gravel stone of particle size fraction 4/16 and 8/16. The particle size and shape (rounded and rectangular) were considered. Four different concrete mix compositions were tested. The following properties of hardened permeable concrete were analysed in comparison: total porosity, water permeability, density, compressive strength, frost resistance, and abrasion resistance. The findings of this study showed that particle size and shape influence the physical-mechanical properties of permeable concrete. The total porosity and water permeability values were higher in the test specimens where crushed gravel stone of fraction 4/8 mm and 8/16 mm was used as coarse aggregate. The resistance of permeable concrete to volumetric freezing and thawing depends on the frost resistance of the coarse aggregate. It was also found that abrasion resistance of permeable concrete is affected by ravelling, i.e. disintegration of angular coarse aggregate particles from the concrete matrix.

Mechanical and Permeability Analysis and Optimization of Recycled Aggregate Pervious Concrete Based on Response Surface Method

In this paper, the effects of different influencing factors and factor interaction on the compressive strength and permeability of recycled aggregate pervious concrete (RAPC) were studied based on the response surface method (RSM). By selecting the maximum aggregate size, water cement ratio and target porosity as design variables, combined with laboratory tests and numerical analysis, the influences of three factors on the compressive strength and permeability coefficient of RAPC were revealed. The regression equation of compressive strength and permeability coefficient of recycled aggregate pervious concrete were established based on RSM, and the response surface model was optimized to determine the optimal ratio of RAPC under the conditions of meeting the mechanical and permeability properties. The results show that the mismatch item of the model is not significant, the model is credible, and the accuracy and reliability of the test are high, but the degree of uncorrelation between the test data and the model is not obvious. The sensitivity of the three factors to the compressive strength is water cement ratio > maximum coarse aggregate particle size > target porosity, and the sensitivity to the permeability coefficient is target porosity > maximum coarse aggregate particle size > water cement ratio. The absolute errors of the model prediction results and the model optimization results are 1.28 MPa and 0.19 mm/s, and the relative errors are 5.06% and 4.19%, respectively. With high accuracy, RSM can match the measured results of compressive strength and permeability coefficient of RAPC.

Pull-out performance of perfobond rib connectors in steel high-strength concrete composite bridge pylons

Perfobond rib connectors (PBLs) used in steel high-strength concrete composite pylons of cable-bearing bridges are subjected to considerable pull-out forces caused by the local buckling tendency of the steel panels. In order to investigate the pull-out performance of PBLs embedded in high-strength concrete, an experimental study was conducted with twelve single-hole PBL specimens constructed of concrete with a cubic compressive strength of 80 MPa. The test results indicate that the failure of shallowly embedded PBLs was dominated by the concrete breakout. Then a numerical investigation was conducted using the validated finite element method to figure out the failure mechanism of the shallowly embedded PBLs, followed by a parametric study to identify the sensible parameters concerning the pull-out resistance. The numerical results show that increasing the embedded depth, concrete strength, and rib hole diameter can increase the pull-out resistance of the PBLs with an embedded depth smaller than 140 mm. In contrast, the thickness of perforated ribs exhibits a negligible impact on the pull-out resistance. It is recommended that the transverse rebar diameter should not exceed the difference between the rib hole diameter and the maximum coarse aggregate particle size of the concrete to avoid the possible decrease in the concrete strength near the rib hole. Finally, a concrete breakout model was developed to predict the pull-out resistance of PBLs shallowly embedded in high strength concrete with reasonable accuracy.

Research on the intelligent detection technology of multi-objective coarse aggregates

In order to achieve the screening of multi-objective coarse aggregate particles and the detection of needle-like particles, this paper targets the limestone coarse aggregate feature points obtained by Harris corner detection as the research object, using unsupervised clustering technology to intelligently cluster the corner coordinates. To achieve intelligent separation of coarse aggregates and screening of needle-like particles. At the same time, the Harris corners are sensitive to scale, the multi-scale corner information is fitted and the sieving critical value is regressed, and the needle flake determination threshold is integrated. Finally, the intelligent screening system of multi-objective coarse aggregate was integrated, and the correct recognition rate was counted. Studies have shown that the number of feature points of coarse aggregates with different particle sizes has a stable change at different resolutions. Intelligent clustering of feature points of coarse aggregates can replace image segmentation. There is a strong correlation between coarse aggregate texture information and particle size.

Effects of content and size of aggregate on the mechanical responses of concrete at cryogenic temperatures

The meso-structure of concrete, which determines its apparent performance, is closely related to the maximum aggregate size (MAS) and aggregate volume. At cryogenic temperatures, due to the freezing of pore water, the internal structure of concrete is changed, leading to some difference in the role of coarse aggregate particles. In this study, the meso-mechanical modeling method was adopted based on the continuous grading aggregate model to investigate the influence of content and size of aggregate at cryogenic temperatures. The uniaxial compressive and uniaxial tensile behavior of concrete cubic specimens (sized by 150 × 150 × 150 mm3) with various aggregate volumes (15 % ∼ 45 %) and MAS values (12 mm ∼ 36 mm) were simulated with consideration of cryogenic temperatures effects. The variation of compressive strength, tensile strength, elastic modulus, and fracture to energy with maximum aggregate size and aggregate volume fractions at cryogenic temperatures was investigated, and the related influencing mechanism was analyzed. The numerical results demonstrated that the failure patterns of specimens at cryogenic temperature show some differences compared with those at ambient temperature. Besides, it was indicated that the effect of maximum aggregate size and aggregate volume on the elastic modulus and the energy to fracture is consistent with those at ambient temperature. At cryogenic temperatures, the compressive strength is improved with the increase of maximum aggregate size. For the smaller aggregate volume fraction (15 % ∼ 30 %), the tensile strength at cryogenic temperatures tends to increase as the increase of maximum aggregate size, while an opposite trend appeared at larger aggregate volume. Additionally, as the increase of aggregate volume fractions, the compressive strength decreases first and then increases at cryogenic temperatures, while the tensile strength and elastic modulus exhibit a trend of increase. It is concluded that cryogenic temperatures can enhance the influence of maximum aggregate size on tensile strength, but weaken the influence of aggregate volume fractions on strengths.