Shape Of Aggregates Research Articles

Image processing and artificial neural network based determination of surface mean texture depth on lab-controlled chip seal pavement samples.

Because surface texture is nearly the sole indicator of pavement functional properties and highly correlated with critical operational characteristics of roadways like traffic noise and safety, the change in pavement surface texture because of traffic loadings and environment has to be evaluated routinely. There are numerous direct or indirect evaluation techniques in the market. However, most of these methods have some limitations like requiring lane closure or being expensive. In this study, a 2D image processing method was established to estimate the surface mean texture depth (MTD) of chip sealed pavements. We produced chip sealed pavement samples in the laboratory with different aggregate type, shape, and size ranging between 2 and 19mm to cover wide range of live conditions. Two well-known conventional test methods, Sand Patch (SP) and Hydrotimer (HT), were used to determine MTDs of chip seal samples. Subsequently numerous photos were taken on surface of the samples with a camera for 2-D image processing that was done based on surface void ratio (SVR) approach. With the image processing, SVR of all samples were determined. At the point of whether there is a relationship or not, correlation analysis was made between the MTDs obtained with SP and HT and the data obtained by SVR approach with the artificial neural network method. The results show that the proposed SVR approach construed on 2D image processing method can be a reliable alternative to evaluate the surface texture of pavements.

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.

Research on the random generation model of 2D irregular aggregates in concrete based on fast grid region division method and its ground penetrating radar characteristics

Concrete can be regarded as a composite material with aggregates embedded in hardened slurries. The size, shape and distribution of aggregates directly affect multiple properties of concrete, including mechanical properties, ultrasonic field characteristics of concrete and ground penetrating radar (GPR) wave field characteristics. Therefore, conducting in-depth research on the random generation model of two-dimensional irregular aggregates is particularly important. This article introduces a fast grid region division method (FGRDM), which is an efficient reconstruction algorithm designed for two-dimensional concrete aggregate models. The algorithm takes into consideration the random micro-aggregate structure of concrete. A two-dimensional random distribution model of irregular aggregates in concrete was successfully established by generating concrete models with different particle size distributions and aggregate contents. Furthermore, the finite difference time domain method was used to analyze the GPR wave field of the random model. The significant influence of aggregate shape and distribution on the GPR wave field was discussed. Compared with existing two-dimensional irregular aggregate random generation models, the FGRDM proposed in this paper avoids computational redundancy and generates irregular aggregates at an increasingly fast speed. In the analysis of GPR data, electromagnetic waves are greatly affected by the shape and distribution of aggregates, highlighting the critical role of two-dimensional random distribution models in GPR data analysis. The paper uses FGRDM to generate random irregular aggregates to simulate the distribution of aggregates in actual concrete. Different diameter glass fiber reinforced polymer (GFRP) bars are inserted into the actual concrete and the numerical model to investigate the effect of aggregate size on the recognition of different diameter GFRP bars. The simulation results are generally consistent with the experimental results.

Experimental and 3D mesoscopic numerical simulation study of kinetic projectile penetrating into concrete

Concrete is a multiphase composite material composed of mortar, aggregate, and interface transition zone (ITZ). The mesoscopic components of concrete have an important influence on its anti-penetration performance. In this study, a series of penetration experiments with large-caliber ogive-nosed projectiles penetrating concrete targets are carried out. The test results show that the damage to the concrete target consists of crater and tunnel zones and increases with increasing impact velocity. Then, a local background grid method is proposed to establish a 3D mesoscopic model of concrete, based on the arrangement characteristics of the sequence number of the finite elements. Compared with the traditional 3D mesoscopic concrete modeling method, the proposed method can effectively improve the modeling efficiency. Subsequently, numerical simulations are performed based on the 3D mesoscopic model, with the simulation and experimental results in good agreement, verifying the effectiveness of the model. Finally, the verified 3D mesoscopic model is employed to investigate the effects of shape, volume fraction, size interval, and strength of the concrete aggregates on the depth of penetration (DOP) and deflection of the projectile. The simulation results indicate that the shape of the aggregate has a negligible effect on both uniaxial compressive strength and DOP. Therefore, spherical aggregates are used to improve modeling efficiency. Increasing the volume fraction and strength of the aggregates can significantly enhance the anti-penetration performance of concrete. The influence of aggregate size interval on DOP is slight, but it has a significant impact on projectile and trajectory deflection at the same aggregate volume fraction. The uneven lateral resistance on both sides of the projectile, caused by the random distribution of aggregates, is a major factor in deflection.

Enhancing mechanism of mechanical properties of lightweight and high-strength concrete prepared with autoclaved silicate lightweight aggregate

Lightweight aggregate concrete (LAC) possesses the merits of low density, excellent thermal insulation performance and outstanding seismic performance. However, the practical application in structural engineering is limited because its mechanical properties are weaker than those of ordinary aggregate concrete. It was found that the compressive strength of high-strength concrete prepared by autoclaved silicate lightweight aggregate (cloud concrete stone) was higher than that of ordinary aggregate high-strength concrete, and it showed significant lightweight and high-strength characteristics. To reveal the enhancing mechanism of the mechanical properties of high-strength concrete prepared by cloud concrete stone (CCS), this research examines the internal curing effect of CCS and the mechanical performances of the interfacial transition zones (ITZ). The influences of the elastic modulus of CCS, the shape of aggregate and fracture patterns on the mechanical properties of concrete are simulated via the discrete element method. The findings suggest that the internal curing effect of CCS delays the onset of capillary stress and mitigates autogenous shrinkage. The homogeneousness, elastic modulus, and fracture toughness of ITZ around CCS aggregate are superior than that ITZ around ordinary gravel in high-strength concrete. Furthermore, the small difference in elastic modulus between CCS aggregate and cement matrix is advantageous for preventing microcracks during compression tests. The round shape of the aggregate also mitigates the development of microcracks caused by the stress concentration effect. These three reasons contribute to the enhancement of mechanical properties in lightweight and high-strength concrete. The innovation of this research is that the intrinsic relationship between CCS aggregate and concrete’s mechanical properties is thoroughly revealed from the aspects of the characteristics of the interface transition zone, the morphology of the aggregate and the elastic modulus of aggregate. That provides a theoretical basis for the application of light aggregate in high-strength structural concrete.

Investigation and prediction of impact of aggregate size and shape on porosity and compressive strength of pervious concrete

ABSTRACT Pervious concrete is proven to environmentally benefit urban pavement construction. Optimising compaction energy evidently reduces uncertainty in the mass production of pervious concrete with uniform characteristics. The distribution of compaction energy in wet mix and rearrangement of binder-coated aggregate particles are affected by the size and shape of aggregates. This study analyses the impact of aggregate size and shape on porosity and compressive strength prediction from mix-design parameters. Aggregate-to-cement ratio (3, 4 and 5), compaction (0, 30 and 60 blows from standard Proctor rammer), aggregate sizes (5–12 mm, 12–18 mm and 18–25 mm) and aggregate shape (0, 200 and 1000 revolutions of milling in Los Angeles Abrasion Value) were used to cast a total number of 486 samples. Constituents were mixed in an electrically powered drum of capacity 96 L, for 20 min. Porosity was computed from constituent ratios (theoretical porosity) and apparent weight (measured porosity). The compressive strength of samples was recorded using a Universal Testing Machine. The measured porosity and theoretical porosity relationship was significantly affected by the shape of the aggregate and not by the size. Modified Ryshkewitch’s model predicted compressive strength from porosity, aggregate-to-cement ratio, compaction and aggregate size and shape with an accuracy of 0.92 (R2). Two of six arbitrary constants depended on aggregate shape and size.

A comparative assessment of uncrushed-river concrete mix of Hari-River, and Kamar-Kalaq: the two widely used concrete mix in Herat, Afghanistan

Concrete, as a cornerstone of modern construction, heavily relies on the quality of its constituent materials, particularly aggregates. Among the critical factors contributing to high-quality concrete are proper gradation, absence of clay particles, and angular shape of aggregates. Adhering to these standards typically results in concrete with superior strength. However, aggregates sourced from riverbeds often possess a natural gradation, contain clay particles, and have rounded shapes. This study delves into a comparative analysis of aggregates sourced from two widely utilized riverbed regions, namely Hari-River and Kamar-Kalaq, situated within Herat province, Afghanistan. Given that over 90% of concrete in Herat province is sourced from these two riverbeds, the findings of this study carry immense significance. The research meticulously examines key parameters, including clay content, gradation, aggregate shape, and compressive strength, to determine the optimal choice for concrete production. Methodologically, samples were acquired following ASTM standards, and rigorous testing procedures were conducted, encompassing clay particle analysis, sieve analysis, and strength testing. The results reveal significant disparities between the two regions, with Hari-River demonstrating superior characteristics across various metrics. Particularly noteworthy is Hari-River’s lower clay content of 2.7% compared to Kamar-Kalaq’s 3.7%. The gradation of Hari-River for both coarse and fine aggregates is superior to that of Kamar-Kalaq when compared to size 67 aggregate range. Additionally, the average 28 days concrete compressive strength of Hari-River aggregates is 27.8 MPa, while that of Kamar-Kalaq is 23.4 MPa.

Effects of coarse aggregate morphology on Asphalt mixture’s flowability: Parametric and prediction study

Morphological characteristics of aggregates affect the flowability and workability of asphalt mixtures during pavement construction. To quantify the effects of coarse aggregate morphological characteristics on its flow performance, aggregates were artificially smoothened through abrasion to different levels of angularity and then evaluted based on Angle of repose (AOR)tests in laboratory. Moreover, morphological characteristics of aggregates with different sizes were scanned and rebuilt based on Particle Flow Code (PFC). 61 sets of virtual Angle of repose tests were further conducted in order to get statistical results and help to develop a predictive model of aggregates’ flowability. The study results indicate that within the commonly used particle size range of 2.36–13.2 mm in pavement, the larger the particle size, the greater the AOR test results. Within 500 cycles of abrasion, most morphological parameters of aggregates show a clear positive correlation with its flowability. Variables based on the aggregate shape scale (Ellipse ratio and Aspect ratio), and angular scale variables(Circularity and 3D Angularity), can well predict the flowability of aggregates. The significance of their contribution to the flowability are shown as follow: Aspect ratio > 3D Angularity > Circularity > Ellipse ratio. Thus, it is important to control the morphological characteristics of aggregates within a reasonable range in order to improve the flowability and workability of asphalt mixtures during pavement construction phase.

Employing 3D laser scanner for automated morphological assessment of aggregates produced from diverse sources and by different crushing methods

This study introduced an automated approach employing 3D scanner for quick and precise aggregates shape analysis. Recognizing existing gaps, there is still an industry demand to propose a standardized method for measuring material characteristics using 3D scanning. By addressing the limitations of previous studies, this research considered unexplored aspects of 3D scanning to improve the speed and efficiency of that. This research comprehensively examined nearly 1500 aggregates from five natural sources and five types of slag. Four statistical tests named Mann-Whitney U, Kolmogorov-Smirnov, Bootstrap, and Permutation were utilized to determine the optimal sample size for scanning. The findings suggest that scanning just 100 aggregates from each source is sufficient to be a small representative of the whole dataset and it can significantly reduce resource use while maintaining data integrity. As a practical insight, it has tried to scan a batch of 25 aggregates simultaneously in one session which could improve efficiency of scanning by reducing the processing time to just 0.6 min per particle. In MATLAB® software, some common bounding volume techniques such as Axis-Aligned, Oriented, Ellipsoid, and Sphere Bounding Box were used to analyze morphological properties. The findings showed that the aggregates sourced from Basalt, Moraine, and most of slags have more cubical shapes, while Porphyrit and Diabase aggregates are more elongated, flaky, and angular. This study also provided a comparative study of how various techniques for stone crushing affect the morphology of aggregates. The results indicate that a combination of jaw, cone, and horizontal impact crusher produces more spherical and cubical aggregates. Replacing of the cone crusher with a gyratory crusher in the same combination can improve elongation and sphericity slightly but may increase flaky particles. These insights offer valuable guidelines for future research and practical applications in construction material optimization.

Mesoscale simulation method for preplaced aggregate concrete based on physics engine

Preplaced aggregate concrete (PAC) has up to 60 % aggregate volume content, making mesoscale modelling difficult. A novel mesoscale simulation method based on physics engine was proposed in this study to accurately simulate the coarse aggregate skeleton of PAC. Unlike in conventional mesoscale simulations, point-to-point contacts between aggregates were formed due to virtual gravity in the physics engine. To verify this novel method, mechanical property and shrinkage behavior tests of PAC were conducted under different aggregate gradings and with different expansive agents. For the mechanical property test, the simulation results were compared with the test results in terms of the aggregate stacking state, failure mode, stress–strain curve, and mechanical property parameters. Repeatability and aggregate shape analyses were performed using finite element (FE) model. A similar comparison between the simulation and test results was also performed for the shrinkage behavior. A shrinkage coefficient reflecting the relationship between grout and PAC shrinkage was proposed. This novel mesoscale simulation method based on physics engine is particularly suitable for PAC. However, it is not limited to PAC and can be applied to the simulation of conventional concrete, thus solving the problem of traditional simulation methods that struggle to achieve a high aggregate fraction.

Mesoscale modeling of recycled aggregate concrete: A parametric analysis of the quality and shape of aggregate

AbstractRecycled aggregate concrete (RAC) is a multi‐phase material, and it is meaningful to investigate the effect of the properties of each phase. However, a comprehensive parametric analysis of these properties is still lacking, which limits a full understanding of the behavior of RAC. This paper uses numerical mesoscale models and contributes to knowledge on this topic. It focuses on the effects of the quality and shape of aggregate since they are relevant to the behavior of concrete but have scarcely been studied for RAC. Their effects on the mechanical response and fracture behavior of RAC were analyzed based on a validated two‐dimensional numerical model. In addition, this paper also justified the choice of the range of the parameters as well as benchmarked the numerical results with the state‐of‐the‐art. The main findings of the paper are: (1) stiffer aggregates decrease the tensile (by up to 29%) and compressive strength of RAC (by up to 7%); (2) aggregate shape moderately influences these properties by up to 10% and 8%; (3) the modulus of elasticity of RAC is considerably influenced by the stiffness of the aggregates (15%), while it is almost unaffected by the shape of the aggregates; (4) both stiffer and elongated aggregates tend to cause micro‐cracking in the interface and premature failure of concrete.

Meso-crack propagation of RC induced by non-uniform rebar corrosion and the predictive model of time to concrete cover cracking

Non-uniform corrosion expansion in reinforced concrete (RC) structures will lead to concrete cracking, bond degradation, and an overall reduction in load-bearing capacity, severely threatening structural safety and durability. Accordingly, meso-crack propagation of RC induced by non-uniform rebar corrosion and the predictive model of time to concrete cover cracking are investigated in this paper, and the theoretical solutions for the critical corrosion rate and the corresponding time are proposed for structural durability evaluation and design. Firstly, based on the mesh-mapping technique of multi-shape random aggregates, a finite-element generation method for three-dimensional concrete three-phase meso-scale model is proposed, with modeling corrosion-expanded cracking of RC, reproducing the crack morphology and propagation process of concrete cracking due to non-uniform rebar corrosion. Subsequently, single factor influence analysis and multi-factor orthogonal test were employed to reveal the degrees of influence of various factors on the critical corrosion rate as follows: concrete strength > cover thickness > interface layer strength > aggregate content > aggregate grading > aggregate shape. A theoretical predictive model for the corrosion expansion cracking time of the RC cover was proposed, considering the influence of key factors including concrete strength and cover thickness. Finally, the validity of theoretical prediction method and the numerical model’s damage mode are verified through accelerated corrosion tests of RC.

Thermal Performance of Lightweight Earth: From Prediction to Optimization through Multiscale Modeling

This study investigates the prediction of the thermal conductivity of lightweight earth and raw earth blocks incorporating plant aggregates. Given the high variability of raw materials, it is not currently possible to predict the thermal performance of this type of material before sample production. This is a major obstacle to using these eco-materials, although their use is widely encouraged to improve building performance under evolving regulatory frameworks such as The French RE2020 standard. The incorporation of plant aggregates into earth-based materials offers improved insulation properties without compromising their mechanical integrity, positioning them as promising sustainable alternatives. Mean-field homogenization techniques, including the Mori-Tanaka as well as double inclusion models, are used to develop predictive tools for thermal behavior, using rigorously selected experimental data. The selected methods are particularly relevant. The Mori-Tanaka model appears to be better suited when the proportion of aggregates is limited, whereas the double inclusion scheme proves its worth when a higher proportion of aggregates is incorporated. This study emphasizes the influence of aggregate types and processing methods on thermal conductivity, highlighting the need for precise formulation and processing techniques to optimize performance. This paper demonstrates the relevance of the applied homogenization techniques applied. It enables the real morphology of the materials studied, such as aggregate shape and intrinsic cracking, to be taken into account. It contributes to the advancement of eco-material modeling toward predictive digital twins, with the goal of simulating and optimizing complex material behavior under various environmental conditions.

A study of fine-scale low-temperature cracking in geopolymer grouted porous asphalt mixtures based on real aggregate profile modeling

At a micro-scale level, grouted porous asphalt mixtures are multiphase composites consisting of aggregates, asphalt mortar, filler, asphalt mortar-aggregate interfacial transition zone, and asphalt mortar-filler interfacial transition zone. It exhibits different mechanical behavior under different temperatures and loading conditions. Compared with aggregate, asphalt mortar, and filler, the interfacial transition zone (ITZ) is more prone to damage at low temperatures, with both the fine structure and the nature of the contact interface having a significant effect on the overall strength and crack resistance of the material. To evaluate the influence of ITZ and filler material properties on the cracking resistance of the material, a grouted porous asphalt mixture model based on the real aggregate shape was established using finite element modeling. A cohesive zone model (CZM) was employed to characterize the internal mechanical behavior of the material, and a mesoscale damage simulation was performed for the grouted asphalt mixture. The study revealed the influence of different interfacial and filler material properties on the low temperature cracking resistance and proposed a design approach for anti-cracking grouted asphalt mixtures. The findings indicated that interfacial transition zone (ITZ) and filler properties play a crucial role on determining the damage characteristics. Increasing the ITZ and filler properties significantly enhanced the low temperature crack resistance of the grouted asphalt mixture.

Salt frost resistance of concrete with crushed asphalt particles: Experiments and modelling

Asphalt coating is widely utilized for its excellent impermeability on marine structure surface. However, in high latitude regions, the coupling effect of freeze-thaw cycles and chemical aging rapidly diminished the protective effect, significantly increasing the risk of structural damage. Therefore, to maximize the impermeability and durability of asphalt, we homogeneously intermixed the crushed asphalt particles into the concrete instead of surface coating. A series of crushed asphalt particles concrete (CAPC) with different asphalt content were prepared and subjected to up to 30 salt freeze thaw cycles (SFTCs) in a 3.5 wt% NaCl solution. Experimental results revealed that addition of asphalt particles improved pore structure and impermeability, mitigating frost damage and chloride diffusion. Optimal performance is observed at 2 % asphalt content, showcasing a notable 22.0 % reduction in porosity, a substantial 47.3 % decrease in chloride concentration at 10 mm depth after 30 SFTCs, with only a 3 % slight reduction in strength. Moreover, a multi-phase chloride diffusion model was proposed, considering matrix/asphalt damage and time-varying porosity. The influence of aggregate shape and volume, data-processing methods, long-term prediction under different regions were discussed. Compared with asphalt coating and classical concrete, the proposed CAPC is recommended for use under marine environment, especially in cold marine regions.

All-aqueous synthesis of alginate complexed with fibrillated protein microcapsules for membrane-bounded culture of tumor spheroids

Water-in-water (W/W) emulsions provide bio-compatible all-aqueous compartments for artificial patterning and assembly of living cells. Successful entrapment of cells within a W/W emulsion via the formation of semipermeable capsules is a prerequisite for regulating on the size, shape, and architecture of cell aggregates. However, the high permeability and instability of the W/W interface, restricting the assembly of stable capsules, pose a fundamental challenge for cell entrapment. The current study addresses this problem by synthesizing multi-armed protein fibrils and controlling their assembly at the W/W interface. The multi-armed protein fibrils, also known as ‘fibril clusters’, were prepared by cross-linking lysozyme fibrils with multi-arm polyethylene glycol (PEG) via click chemistry. Compared to linear-structured fibrils, fibril clusters are strongly adsorbed at the W/W interface, forming an interconnected meshwork that better stabilizes the W/W emulsion. Moreover, when fibril clusters are complexed with alginate, the hybrid microcapsules demonstrate excellent mechanical robustness, semi-permeability, cytocompatibility and biodegradability. These advantages enable the encapsulation, entrapment and long-term culture of tumor spheroids, with great promise for applications for anti-cancer drug screening, tumor disease modeling, and tissue repair engineering.

Compressive behavior of concrete-filled FRP tubes with FRP solid waste as recycled aggregates: Experimental study and analytical modelling

The disposal and recycling of FRP (Fiber-Reinforced Polymer) solid waste pose significant challenges globally, with a recycling rate of less than 10 %. Current methods of handling FRP solid waste (FSW), including landfill disposal, incineration, chemical treatment, and thermal cracking, face limitations in achieving large-scale recycling and resource utilization. In civil engineering, FRP is widely employed for retrofitting structures and holds promise for new constructions. A new approach has emerged for recycling FSW by using it as aggregates in concrete, offering lower costs and reduced environmental impact. Research on using FSW aggregates in plain concrete shows that optimizing replacement ratios and aggregate shapes can enhance split tensile strength and toughness without significantly lowering compressive strength. To further improve the mechanical performance, this study investigated concrete-filled filament-wound FRP tubes with FSW aggregates (FSW-CFFTs) under axial compression. 35 specimens were tested to evaluate the influence of granular FSW aggregates (i.e., replacement ratio = 0 %, 20 %, 40 %, 60 %, and 80 %) and FRP thickness (i.e., 0 mm, 3 mm, and 5 mm) on their axial compression behavior. The experimental study revealed that: incorporation of FSW aggregates in unconfined concrete cylinders led to a notable decrease in Young's modulus and compressive strength, while concurrently increasing the peak compressive strain; as the replacement ratio of FSW aggregates increased, there was a tendency for the peak stress of FSW-CFFTs to decrease, while their ultimate axial strain tended to increase; compared FSW-CFFTs with unconfined concrete cylinders, the FRP confinement helped to mitigate the reduction ratio in axial compressive strength induced by the inclusion of FSW aggregates in the concrete, particularly at higher FSW aggregate replacement ratios; specimens with a thicker FRP tube exhibited higher secondary stiffness, along with higher strength and larger ultimate compressive strain. The modeling work indicated that accurately predicting axial stress-strain curves requires consideration of the bi-axial stress state of filament-wound FRP tubes.

Field comparison of Antarctic krill (Euphausia superba) backscatter and aggregation types using NORTEK and SIMRAD echosounders

Abstract Temporal distributions of Antarctic krill (Euphausia superba) density and aggregation types were characterized and compared using Nortek Signature100 and SIMRAD Wideband Autonomous Transceiver (WBAT) upward-looking echosounders. Noise varied between the two echosounders. With the Signature100, it was necessary to correct data for background, transient, and impulse noises, while the WBAT data needed to be corrected for background noise only. For selected regions with no visible backscatter, the signal-to-noise ratio of Sv values (i.e. the ratio between the signal and the background noise level) did not vary between the two echosounders. Surface echo backscatter was similar during similar time periods. Descriptive metrics were used to quantify spatial and temporal krill vertical distributions: volume backscatter, mean depth, center of mass, inertia, equivalent area, aggregation index, and proportion occupied. Krill backscatter density differed between the two instruments but was detected at similar mean depths. Krill aggregations were identified at each mooring location and classified in three types based on morphological characteristics. Each type of aggregation shape differed at the two spatially separated moorings, while the acoustic density of each aggregation type was similar. The Signature100 detected a lower number of krill aggregations (n = 133) compared to the WBAT (n = 707). Although both instruments can be used for autonomous deployment and sampling of krill over extended periods, there is a strong caveat for the use of the Signature100 due to significant differences in noise characteristics and krill detection.

Optimisation of pervious concrete performance by varying aggregate shape, size, aggregate-to-cement ratio, and compaction effort by using the Taguchi method

ABSTRACT The porosity and compressive strength of pervious concrete are critical determinants of its suitability for various applications. Therefore, it is necessary to recognise the factors influencing the performance and its ranks to balance porosity and compressive strength ideally. This study evaluates the impact of aggregate shape, size, aggregate-to-cement ratio and compaction effort on previous concrete performance. The research involved varying aggregate sizes (5–12 mm, 12–18 mm and 18–25 mm), aggregate-to-cement ratios (3.0, 4.0 and 5.0), compaction efforts (0, 30 and 60 blows) and aggregates underwent revolutions in a ball mill (0, 200 and 1000) to change their morphological characteristics. A total of 81 mix designs were tested, resulting in 486 cubes for compressive strength and porosity testing. The acquired data underwent analysis using the statistical analysis and Taguchi method to discern the most influential factors and establish their ranking. The results indicate that revolutions, compaction, aggregate-to-cement ratio and aggregate size contribute 29.42%, 26.19%, 29.13% and 0.96%, respectively, to the compressive strength performance. Regarding porosity performance, revolutions and compaction emerge as significant factors, accounting for 39.95% and 26.91%, respectively. The influence of the aggregate-to-cement ratio and aggregate size on porosity performance appears less pronounced.

Towards automated field ballast condition evaluation: Field validation of the ballast scanning vehicle capabilities

Ballast degradation can lead to adverse effects such as inadequate drainage, track settlement and reduced lateral stability, which could compromise track safety, daily functionality, and long-term maintenance. Field inspection of ballast for monitoring degradation and functional performance is a challenging task. Current state-of-the-practice methods for evaluating ballast primarily depend on subjective visual inspection, labor-intensive sampling, laboratory sieve analyses or Ground Penetrating Radar (GPR) technology. These methods fall short in providing an in-depth assessment of ballast, specifically in determining the degradation level and aggregate size and shape characteristics at various depths. In this regard, this research developed an innovative ballast investigation platform, the Ballast Scanning Vehicle (BSV), to automate the processes of acquiring detailed ballast inspection data. The BSV utilizes a deep learning-based pipeline for image segmentation to evaluate task-specific metrics such as coarse aggregate gradation, Fouling Index (FI), and continuous track FI depth profiles. This paper provides a detailed overview of the BSV’s functions as well as the different modules of the deep learning-based pipeline. Validation of the BSV’s capabilities was conducted at the Transportation Technology Center (TTC) and is discussed in detail. Based on the field results, the BSV is capable of providing accurate and near real-time evaluation of in-service ballast conditions, serves as a robust means for inspecting long sections of track, and can be used to investigate persistent trouble-spots related to track performance.