Aggregate Gradation Research Articles

Effect of Aggregate Gradation on the Properties of 3D Printed Recycled Coarse Aggregate Concrete

Effect of Aggregate Gradation on the Properties of 3D Printed Recycled Coarse Aggregate Concrete

Micro-Scale Fracture Characteristics of Emulsified Asphalt Cold Recycled Mixture Based on Discrete Element Method

Asphalt pavement often experiences structural failure due to repeated vehicle loading. The discrete element method (DEM) model was established based on the semicircle bending test (SCB) to investigate the fracture damage mechanism of emulsified asphalt cold recycled mixture (CRME) under loading. The micro-mechanical parameters of CRME were determined through a reliable validation process using the uniaxial compression static creep test. The microscopic fracture characteristics of CRME were investigated through the load-displacement curve, stress distribution, and force chain distribution. The fracture energy was used as the evaluation index to analyze the influence of prefabricated notch length and aggregate gradation on the fracture performance of CRME. The results indicate that the emulsified asphalt mortar-aggregate interface was the critical weak position of the mixture fracture; the failure of the tension chain was the main destructional form of the SCB test. The development of cracks affected the stress concentration phenomenon and stress concentration level of the mixture. Fine-grained mixture exhibited crack resistance. The number and length of cracks were affected by gradation. As the prefabricated notch length increased, the influence gradually diminished. The research results could provide theoretical and data support for the design of CRME.

Geosynthetic-stabilized aggregate: quantitative modulus evaluation via Bender Element

Geosynthetics, mainly geogrids and geotextiles, are commonly used to mechanically stabilize unbound aggregate layers in paved road applications. They provide lateral restraint to aggregates to initially increase the layer modulus during construction and minimize its time-dependent decrease under vehicular traffic loading. Different types of geosynthetics may provide different improvement mechanisms and stiffness enhancement levels. Quantitative evaluation of various stabilization geosynthetics is presented herein to compare modulus improvement trends and help incorporate geosynthetic benefits into state-of-the-art mechanistic-empirical (M-E) pavement design procedures. Five geogrids (three extruded, one woven, and one welded) and two geotextiles (one woven and one nonwoven) were studied with a dense graded aggregate in laboratory triaxial testing. Geosynthetics were placed at specimen mid-height and three pairs of Bender Element (BE) sensors were placed at various heights above the geosynthetic to collect shear waves and quantify the degree of mechanical stabilization during resilient modulus testing. While resilient moduli did not distinguish effectiveness of different geosynthetics, shear wave measurements could clearly show local stiffness increases achieved with geosynthetic inclusions. Meanwhile, trends observed in shear modulus profiles at various distances from the geosynthetic, when compared to that of control specimen, properly established the modulus enhancement level achieved in mechanical stabilization with geosynthetics.

An Exploratory Study of Small-Group Learning Interactions in Pre-Clerkship Medical Education: Uncovering a Mismatch Between Student Perceptions and Real-Time Observations

Small-group learning is a mainstay of medical education, and group functioning can have a major influence on these learning experiences. Our objective was to explore verbal exchange patterns within small-group learning sessions and examine how different patterns related to tutor involvement, tutor expertise, and participants’ perceptions. A non-participant observer collected group interactivity data using a real-time mobile device-based system. Verbal interaction patterns were visualized and analyzed using social network analysis and correlated with participant survey data and aggregate course grades. There were 46 observations across 30 separate groups. Group interactions clustered into four patterns defined by (1) tutor involvement (high vs. low) and (2) interactivity (high vs. low). Interaction patterns were largely stable for a given group and groups with content expert facilitators were generally less interactive. Students reported objectively fewer interactive groups as more interactive and enjoyable. There were no significant intergroup differences in aggregate course grades. Paradoxically, student perceptions were not aligned with observed interactivity data, and tutor content expertise influenced group interactivity. These findings suggest the need to better manage learner expectations of small-group learning, and to explicitly reflect on and develop skills for effective collaborative learning with both faculty and students.

Image-driven prediction system: Automatic extraction of aggregate gradation of pavement core samples integrating deep learning and interactive image processing framework

Aggregate gradation plays a crucial role in determining the asphalt pavement performance, necessitating assessment post-construction. Additionally, efficient gradation measurement is vital for the design and construction of reclaimed pavement. This study proposes a methodology for predicting gradation based on imagery. Initially, a scanning device is devised to capture unfolded side surface images of pavement core samples. Subsequently, an interactive software named PyImageJ is developed for image post-processing and acquiring aggregate feature information. A morphological model is then introduced to determine the mass ratios among various grading levels of coarse aggregates with nominal particle sizes greater than 2.36 mm. Finally, sequence prediction models are established to forecast the mass ratios among different grading levels of fine aggregates with nominal particle sizes smaller than 2.36 mm. Simple conversion of the mass ratios can yield the gradation. Experimental results indicate that the Long Short-Term Memory (LSTM) network offers more accurate predictions for the mass ratios of fine aggregates in stone mastic asphalt (SMA-13), with an R-squared value of 0.8985. Conversely, one-dimensional convolutional neural networks (1D CNN) are better suited for predicting the fine aggregate mass ratios in asphalt concrete (AC-20 and AC-25), with R-squared values of 0.9010 and 0.8824, respectively. Visualization results demonstrate that the predicted complete gradation closely aligns with the actual values (R-squared > 0.99), opening a new avenue for evaluating pavement quality.

Permeability Measurement of Pervious Concrete by Constant and Falling Head Methods: Influence of Aggregate Gradation and Cement-to-Aggregate Ratio

Permeability Measurement of Pervious Concrete by Constant and Falling Head Methods: Influence of Aggregate Gradation and Cement-to-Aggregate Ratio

Early age time-dependent mechanical properties of 3D-printed concrete with coarse aggregates

Incorporating coarse aggregate into 3D-printed concrete is essential for promoting its practical application, yet the impact on the early age time-dependent mechanical properties, crucial for the multilayer structure stability and quality, is underexplored. In this study, 3D-printed concrete with coarse aggregate (3DPCA) with varying mortar-to-coarse aggregate ratios (M/A) and coarse aggregate gradations were prepared, of which uniaxial unconfined compression and direct shear performance were experimentally investigated. The fundamental formulations between the early age mechanical parameters and the resting time of 3DPCA were characterized and then utilized in a digital model simulating actual printing. Results indicated that the 3DPCA early age mechanical properties, including compressive strength, Young's modulus, cohesion, and friction angle, increased with longer resting time and decreasing M/A, and higher proportions of aggregates above 9.5 mm. High coarse aggregate content caused three distinct compressive strength-displacement curve stages and complicated strength eigenvalue extraction. Coarse aggregate gradation affected shear properties more than content, with larger aggregates improving cohesion and friction angles. The failure mode prediction model based on ABAQUS could accurately predict the maximum collapse layer of 3DPCA that occurred in overall unstable collapse and over-expansion failure but was incapable of localized deformation.

Investigations on the rheological properties of cement mortar based on fine aggregate characteristic and its extended prediction model

The rheological property of mortar is significantly influenced by its contained fine aggregate morphology characteristic and capable predictive models are limited. This work aims to expand the film thickness theory by developing an index that integrally represents variations in grain shape, gradation, and mix proportions, and elucidates the impact and the mechanism of these multifactorial differences on rheological performance. The quantitative analysis of the aggregate gradation and particle shape differences were performed, which was used to assess the impact of these variations and different mix ratios on the rheological performance of mortars. A correlation between aggregate differences and film thickness was established using specific surface area and void ratio. The result shows that variations in aggregates are accurately assessed by image analysis and consistently reflected in specific surface area and void ratio metrics. Since variations in rheological performance are predominantly governed by differences in film thickness, the disparities among aggregates can be quantified in terms of their impact on rheological properties by considering specific surface area and void ratio, thus translating into variations of film thickness. The differences in rheological properties due to variations in grain shape, gradation, and mix proportions can be comprehensively represented and controlled through an expansion of the film thickness model.

A Hybrid Strategy Two‐Dimensional Concrete Aggregate Filling Algorithm

ABSTRACTAccurate and highly efficient construction of numerical concrete models with different gradations is important to analyze the acoustic properties of ultrasonic waves in concrete. The random aggregates‐based method is a classic approach to meso‐structural modeling of concrete and is particularly suitable for generating models with low‐density aggregates. However, when facing the simulation requirements of concrete models with large volumes, small particle sizes, and high aggregate content, traditional random aggregates‐based methods encounter challenges in satisfying aggregate packing density and modeling efficiency. In order to improve the efficiency of aggregate placement in modeling concrete meso‐models, we proposed a hybrid‐strategy point cloud placement algorithm that combines the re‐placement and sedimentation strategies. Then, the algorithm's effectiveness in improving the modeling efficiency is verified by reconstruction experiments on random aggregate models with different aggregate grades. Finally, the model's reliability and validity is further confirmed by simulation analysis of the ultrasonic attenuation characteristics of the model. The results show that the algorithm can rapidly generate more than 75% aggregate packing density concrete specimens and significantly outperforms similar algorithms regarding aggregate placement efficiency and model generation time. In addition, the model generated by the proposed algorithm can accurately simulate the attenuation characteristics of ultrasonic waves in concrete.

Research on the factors affecting the compressive strength of rubber powder modified cement-stabilized crushed stone based on orthogonal experiments

Based on an orthogonal experimental design, this study introduces rubber powder particle size alongside rubber powder content, aggregate gradation, and cement content as factors. A total of 16 mix proportions were formulated. For each mixture, compaction tests and unconfined compressive strength (UCS) tests were conducted. Using Statistical Product and Service Solutions (SPSS) software, a multifactor variance analysis was performed to determine the influence levels of the four factors on maximum dry density and compressive strength. The optimal mix proportion was selected based on compressive strength. The results indicate that aggregate gradation and rubber powder content significantly affect the maximum dry density of the mixture, with aggregate gradation having the greatest impact. Rubber powder content has the most substantial effect on compressive strength, while rubber particle size has the least influence. The optimal formulation is 7% cement content, 30-mesh rubber powder, 0.5% rubber powder content, and a skeletal dense gradation close to the median.

The screening effect of coarse aggregate on the air void structure and durability of air-entrained concrete

The control of air void structures introduced by air-entraining agents (AEAs) has long been a crucial problem. However, the mechanism through which the air void structure is refined by the extrusion of the slurry and the cutting of the aggregate remains insufficiently studied. This study aims to investigate the screening effect of coarse aggregate on the air void structure. The gradations of coarse aggregates were controlled by the fractal dimension (D). For casting air-entrained concrete, multiple continuously graded aggregates with D of 2.1, 2.3, 2.5 and 2.7 as well as two single graded aggregates with D=1.8 and 3.0 were used. Various parameters such as air content, air void structure, freeze-thaw durability, chloride ion permeability and water absorption were measured. Various air void structure parameters were compared to macroscopic properties. To evaluate the screening effect of coarse aggregate, the bubble rising and splitting behavior when passing through a single simulated aggregate (SA) and SA layer were observed. The findings indicate that finer and continuously graded coarse aggregates lead to higher air content and promoted air bubble trapped rate, which suggests a stronger screening effect. This results in a smaller bubble spacing coefficient and stronger frost resistance.

Research on Design Parameters for Fatigue Performance of Asphalt Mixtures.

The fatigue performance of the asphalt mixture was the main focus of this study, with five typical factors-phase angle, cumulative dissipated energy, failure strain, failure stiffness modulus, and strain rate-identified as potential design indexes. The effect of asphalt content on the parameters under different gradation and stress ratios was tested. It was observed that the selected parameters exhibited varying levels of sensitivity and relevance to the fatigue behavior of asphalt mixtures under cyclic loads. By comparison, the strain rate proved sensitive to the asphalt content and independent of the other parameters, namely aggregate gradations and stress ratio, thus establishing the strain rate as a critical design index based on fatigue performance. On this basis, a design method based on the fatigue performance for the asphalt mixtures is herein proposed. It was confirmed that the asphalt mixture formulated using the proposed method exhibited enhanced fatigue endurance compared to those designed using the conventional method.

Performance Study of Stabilized Recycled Aggregate Base Material with Two-Gray Components.

This article studies the practical road performance of recycled materials from construction waste, relying on the paving test section of the supporting project for the Qingdao Cross-Sea Bridge. The research focuses on the construction technology and road performance of using recycled construction waste materials in urban road sub-base construction. Through indoor tests such as sieving and unconfined compressive strength tests, relevant technical indicators were obtained and analyzed. Additionally, periodic core sampling, compaction tests, and rebound deflection tests were conducted on-site according to relevant standards to thoroughly investigate the specific effects of using construction waste in practice and to analyze and evaluate the actual feasibility of the materials for road use. The results indicate that the particle gradation of the construction mix in the test section aligns well with the target gradation, and the dosage of the mixing agent meets the design requirements. The 7-day unconfined compressive strength already satisfied the technical requirements for heavy and extremely heavy traffic on highways as specified in the "Technical Specifications for Construction of Highway Pavement Subbase" (JTG/T F20-2015), with the 14-day strength generally reaching 7 MPa. Core sampling revealed good aggregate gradation, smooth and straight profiles, and the thickness and strength of all parts meet the specifications. The compaction levels met the testing requirements, the surface deflection values showed a decreasing trend, and the deformation resistance was good, consistent with the general development patterns of semi-rigid sub-bases.

Performance Evaluation of Pebble Concrete for Pavement: A Study on the Sucre Highway Project

Bolivia has abundant pebbles, while the supply of crushed stone is limited and unstable. Thus, the resource utilization of local pebble as a coarse aggregate and the guarantee of concrete durability are the key scientific issues in the Sucre Highway Project. In this paper, a comparative analysis was conducted of the performance of crushed stone concrete and pebble concrete. Additionally, the impact of fly ash on the water permeability resistance of concrete was investigated. The results indicate that the apparent density, bulk density, and void ratio of pebbles are lower than those of crushed stone, and the aggregate gradation of pebbles is dispersed. The type of aggregate is the primary factor influencing the splitting tensile strength of concrete, with the main failure modes of pebble concrete being slurry cracking, aggregate crushing, and interface debonding. While aggregate and fly ash have a minor effect on compressive strength, they significantly impact flexural tensile strength; however, all concretes meet the requirements for extra-heavy, very heavy, and heavy traffic load levels. In terms of impermeability, fly ash effectively mitigates the negative impact of aggregate type on the impermeability of concrete. These findings support the application of pebble concrete in the highway project.

Investigation of Performance Specifications for Marshall Mixes Using Performance-Based Mix Design Methodology

This paper presents a comprehensive study for developing the performance specifications for the Marshall mixes using the performance-based mix design (PMD) methodology. The specification describes the desired levels of fundamental engineering properties for predicting performance during mix design or quality assurance checks at the time of construction. In this study, the bituminous concrete mixture was designed through complementing volumetric criteria with performance tests such as dynamic creep and the indirect tensile asphalt cracking test for evaluating resistance against rutting and fatigue cracking, respectively. This study considers different factors such as five different types of design aggregate gradations (mid-gradation, fine-coarse gradation, coarse gradation, coarse-fine gradation, and fine gradation), three binder types (VG-30, VG-40, and PMB-40), and five levels of compactive efforts (35, 50, 75, 90, and 110 blows on each face). The study finds the effect of design aggregate gradation, binder type, and compactive effort on the rutting and cracking resistance of bituminous mixes. The research study also comprehends the influence of volumetric properties on the performance parameters. Further, it establishes the initial performance criteria for rutting and cracking for Marshall mixes. The performance space diagram (PSD) has also been plotted, portraying the overall performance (acceptable, desirable, or unsatisfactory performance regions) of bituminous mixtures based on rutting resistance and cracking resistance. This paper highlights and advocates the integration of these performance-based specifications into the Marshall mix design specifications for improving pavement characteristics and extending overall service life.

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.

Effect of coarse aggregate concentration on the bond properties between steel rebar and concrete within low and medium strength range

Most of the current rules and practices employ medium and high-strength concrete with ribbed rebar. However, there are still many structures that are of low concrete class with non-standard aggregate gradation and also contain plain rebar. In this study, to better understand the behavior of such structures, concrete mixtures with 3 different water-to-cement (W/C) ratios (0.6–0.9–1.2) and 4 different coarse aggregate concentrations (CAC) (0 %-20 %-40 %-60 %) were produced. Compressive strength (CS), elasticity modulus (MOE), and splitting tensile strength (STS) tests were performed on the concrete samples, and the stress-strain relationship was determined. Bond-slip behavior was examined on samples containing both plain and ribbed rebars. The results showed that 40 % CAC mixtures had the highest CS and 60 % CAC mixtures had the highest MOE. Adding coarse aggregate increased STS, bond strength (τu), and residual bond stress (τr). The results obtained from this study were also combined with a similar study conducted on medium and high-strength concrete, and models were proposed for CS, MOE, and τu, τr. It was determined that similar to compressive strength, the MOE was also effective on bond strength significantly. A machine learning method (random forest regression) and feature importance analysis were performed to support the results. The results revealed that CS has the most significant effect on τu and τr, but the effect of MOE and STS was also very significant. Additionally, τr/τu and the s1 (slip value at τu), which is proposed as a constant value in existing studies, increased with increasing CS.

Optimizing aggregate grading and residual mortar coefficient in low-cement concrete by using crushed coal mine waste rock as base layers for low-traffic roads

In the context of depleting natural resources and environmental challenges posed by large-scale extraction and use of natural aggregates, this study investigates the use of crushed coal mine waste rock (CCMWR) as a sustainable alternative for low-cement concrete in the base layers of low-traffic roads. The primary goal is to optimize the aggregate grading and the residual mortar coefficient (RMC) to enhance the performance and durability of low-cement concrete. Utilizing the I-optimal design methodology and curve of Fuller for particle size distribution, this research evaluates the mechanical properties, workability, and environmental impact of incorporating CCMWR in low-cement concrete. The findings demonstrate that with the appropriate optimization, CCMWR can effectively replace natural aggregates, significantly reducing the ecological footprint and providing an effective solution for sustainable road construction. This research holds substantial engineering application significance by offering an innovative approach to classify and reuse waste from the coal mining industry while addressing the urgent need for sustainable infrastructure development.

Exploration of medical students’ approach to progress test preparation

Introduction: Medical students are expected to develop competencies in applying clinical knowledge. Progress testing is an assessment for learning and is intended to assist in knowledge acquisition and to promote ongoing recall. This study explored student preparation for progress tests (PTs), relationships between approach and performance, and patterns that could assist with targeting learning support. Methods: A cross-sectional survey exploring study approach and learning context, comprising multi-choice and open-ended responses, was administered to students during their clinical years (n = 297). Quantitative data was analysed using descriptive statistics and comparative analysis, and qualitative data was categorised. Results: One hundred twenty-nine students responded (43.4%), with most demonstrating a stable PT performance over time. Twenty-two students had dynamic changes in their aggregate grades. Poor early PT performance was associated with developing an improvement strategy (χ2 6.954, p = 0.008). Students never falling below satisfactory were less likely to have a strategy (χ2 10.084, p = 0.001). All poorly performing students were using practice question banks, but this was not true for students who scored satisfactorily. The need for pastoral care was associated with poorer performance (χ2 4.701, p = 0.030). Conclusions: Student approaches to PT preparation are diverse, however there are correlations between preparation factors and performance outcomes. Students with poor early performance demonstrated improved results over time that may be attributed to targeted support and preparation strategies. Widespread use of practice questions may not be sufficient to impact results without additional strategies. External impacts to performance were common, and barriers to accessing pastoral care were evident. The feedback dashboard was underutilised, suggesting a need to improve feedback literacy and ensure this is fit for purpose.

Gradation optimization of AC-20 asphalt mixture based on the fuzzy analytic hierarchy process and comprehensive evaluation method

The aggregate gradation of asphalt mixture is one of the most important factors affecting the service life of asphalt pavement. In order to study the gradation of asphalt mixture with the best comprehensive performance, this study puts forward a new method of mineral aggregate gradation optimization based on the fuzzy analytic hierarchy process and comprehensive evaluation method, aiming at the multi-level and multi-index evaluation of the road performance of asphalt mixture. First, the orthogonal test design method is applied to design nine target gradations with coarse aggregate (>4.75 mm) and fine aggregate (<4.75 mm) of AC-20 (asphalt concrete) mixture serving as two factors and the upper, middle, and lower positions of the gradation curve as three levels, and then the road performance test research is carried out. Second, a comprehensive model for evaluation of road performance of mineral aggregate gradation is established. A fuzzy complementary judgment matrix is constructed, and the index weights of each level and the hierarchical total ranking weight are calculated. Then, the membership function is introduced into the comprehensive evaluation model for the road performance of mineral aggregate gradation, and the membership values of each index of asphalt mixture road performance are obtained. Finally, the fuzzy comprehensive evaluation method is used to find out the comprehensive evaluation value of the road performance of the nine graded asphalt mixtures, and the mineral aggregate gradation is optimized. The research results show that the 1# gradation of the asphalt mixture has the highest comprehensive road performance evaluation value, and the combination of the fuzzy hierarchical analysis process and comprehensive evaluation method can more objectively and comprehensively evaluate the comprehensive road performance of the asphalt mixture and provide a useful reference for the optimal selection of asphalt mixture mineral gradation.