Aggregate Specimens Research Articles

An explorative analysis on the optimal cryo-passes and freezing time of the ultrathin cryoprobe in endobronchial ultrasound-guided transbronchial mediastinal cryobiopsy

EBUS-guided transbronchial mediastinal cryobiopsy (TBMC) has emerged as a promising biopsy tool for diagnosing hilar and mediastinal pathologies. However, several fundamental technical aspects of TBMC remain unexplored. This study aims to determine the optimal number of cryo-passes and freezing time of the ultrathin cryoprobe in EBUS-TBMC concerning specimen size and procedural diagnostic yield. We conducted a retrospective chart review of patients with mediastinal and hilar lesions who underwent EBUS-TBMC between January 2021 and April 2023 across three hospitals in Malaysia. A total of 129 EBUS-TBMC procedures were successfully completed, achieving an overall diagnostic yield of 88.4%. Conclusive TBMC procedures were associated with larger specimen sizes (7.0 vs. 5.0 mm, p < 0.01). Specimen size demonstrated a positive correlation with diagnostic yield (p < 0.01), plateauing at specimen size of 4.1–6.0 mm. A significant positive correlation was also observed between the number of cryo-passes and both specimen size (p < 0.01) and diagnostic yield (p < 0.05). Diagnostic yield plateaued after 2–3 cryo-passes. In contrast, longer freezing times trended towards smaller specimens and lower diagnostic yield, though not reaching statistical significance. The highest diagnostic yield was recorded at the 3.1–4.0 s freezing time. The safety profile of TBMC remains favourable, with one case (0.8%) of pneumothorax and nine cases (7%) of self-limiting bleeding. In our cohort, TBMC performance with 2–3 cryo-passes and a 3.1–4.0 s freezing time to achieve a total aggregate specimen size of 4.1–6.0 mm appeared optimal. Further prospective studies are needed to validate these findings.

EVALUATING THE STRUCTURAL EFFICACY OF ANGLE AND CHANNEL SHEAR CONNECTORS IN BRICK AGGREGATE CONCRETE AND STONE AGGREGATE CONCRETE AND COMPARISON

Composite structure is becoming prominent for its economy, less time consumption, and higher stiffness-mass ratio. Composite action of the steel-concrete composite structure mainly depends on the connector's geometry and materials. Proper choice of shear connector could make steel beam and concrete slab cross-section minimal. This study carries out push-out tests to evaluate the structural efficiency of channel and angle shear connectors in brick aggregate concrete and stone aggregate concrete. It specifically looks at the failure mode, ductility, load-slip behavior, and energy absorption capacity. In brick aggregate concrete, results show that under monotonic loading, channel connectors have been found to have 15.27% more shear capacity &amp; 28.38% more slip than angle connectors. Similarly, in stone aggregate concrete, channel connectors have been found to have 14% more shear capacity &amp; 12.97% higher slip than angle connectors. On average, stone aggregate concrete has been found to have 34.84% higher shear capacity and 6.7% greater slip than brick aggregate concrete. Strain energy and plastic energy were found 78% and 17.6% less in brick aggregate specimens than those in stone aggregate specimens, respectively. Experimental results were slightly lower for both shear connectors than the empirical values.

Compaction and shear characteristics of recycled construction & demolition aggregates in subgrade: Exploring particle breakage and shape effects

Recycling construction and demolition (C&D) wastes into useable aggregates in subgrade applications offers significant sustainability benefits. However, the characteristics of recycled aggregates, including particle morphology, crushing strength, and shear behavior, differ substantially from natural aggregates. This paper presented an extensive experimental study on the compaction and mechanics performances of recycled concrete and brick aggregates, with a particular focus on the effects of particle breakage and shape characteristics. The compaction of recycled aggregate specimens comprising three structural types was evaluated using heavy Marshall compaction (HMC) and Superpave gyratory compaction (SGC). The compaction characteristics and particle breakage were examined, enabling a profound understanding of the compaction mechanisms associated with both methods. Furthermore, triaxial shear tests were performed to scrutinize the influences of particle shape, compaction degree, and confining pressure on shear characteristics. Results showed that after 80 gyratory rotations in SGC, the compaction degree of recycled aggregates aligned with the targeted results obtained from HMC. Changes in fractal dimension after compaction exhibited direct correlations with the two-dimensional shape distribution. Axial coefficient, fractal dimension and confining pressure most strongly influenced shear strength. In light of these insights, prediction models for shear strength parameters were proposed using multiple regression analysis. Overall, the study provides valuable insights into the relationships between aggregate morphology, compaction response, breakage behavior, and shear performance. These findings can facilitate optimized design and construction using recycled aggregates to advance sustainable infrastructure development.

A Laboratory-Scale Evaluation of Smart Pebble Sensors Embedded in Geomaterials.

This paper introduces a novel approach to measure deformations in geomaterials using the recently developed 'Smart Pebble' sensors. Smart Pebbles were included in triaxial test specimens of unbound aggregates stabilized with geogrids. The sensors are equipped with an aggregate particle/position tracking algorithm that can manage uncertainty arising due to signal noise and random walk effects. Two Smart Pebbles were placed in each test specimen, one at specimen's mid-height, where a geogrid was installed in the mechanically stabilized specimen, and one towards the top of the specimen. Even with simple raw data processing, the trends on linear vertical acceleration indicated the ability of Smart Pebbles to assess the geomaterial configuration and applied stress states. Employing a Kalman filter-based algorithm, the Smart Pebble position coordinates were tracked during testing. The specimen's resilient deformations were simultaneously recorded. bender element shear wave transducer pairs were also installed on the specimens to further validate the Smart Pebble small-strain responses. The results indicate a close agreement between the BE sensors and Smart Pebbles estimates towards local stiffness enhancement quantification in the geogrid specimen. The study findings confirm the viability of using the Smart Pebbles in describing the resilient behavior of an aggregate material under repeated loading.

Investigation of tensile strength performance of green concrete incorporating steel slag

This study examined the compressive and tensile strength performance of steel slag-containing concrete composites in a sulphate environment. Steel slag sourced locally was mechanically crushed and sieved into aggregates ranging in size from 20 to 1 mm. The control concrete of grade 20 and other five (5) batches of concrete with 10 to 50% steel slag at a step of 10% as replacement for natural coarse aggregate were produced. The physical properties of the aggregate specimens (steel slag and granite) were evaluated in the laboratory, as well as the concrete workability and the 7- and 28-day compressive and tensile strengths after exposure to 50 g/l of magnesium and sodium for 7 and 28 days. According to the results, the concrete workability decreased as the steel slag content increases. The 20 N/mm2 desire strength with rise in compressive and split tensile strengths as the steel slag contents increased from 0 to 50% after curing in water for 28 days. The concrete compressive and tensile strengths improved with steel slag content ranging from 0 to 40% but decreased with increase in steel slag content from 30 to 50% after exposure to Na2SO4 for 28 days. For the concrete exposed to MgSO4, the compressive and split tensile strengths increased when the steel slag content increased from 0 to 40% before it decreased with further increase in steel slag from 40 to 50% after 28 days. The experimental findings revealed that up to 40% steel slag is sufficient as replacement for natural coarse aggregate in concrete work exposed to aggressive sulphate climate. Thus, for improved compressive and tensile performance, the optimum of 40% steel slag is suggested as replacement for natural coarse aggregate substitution for healthier sulphate attack resistance.

Investigation on the temperature distribution characteristics of steel slag asphalt mixture under different microwave heating and cooling methods

The utilization of steel slag aggregate (SSA) can enhance the microwave absorption efficiency of asphalt mixture, thus increasing its temperature and self-healing capability. In this study, the temperature distribution of basalt porous asphalt concrete (PAC-B), ordinary steel slag porous asphalt concrete (PAC-US), and modified steel slag porous asphalt concrete (PAC-MS) under the influence of different microwave heating and cooling methods were investigated through laboratory tests and numerical simulations. The heating methods including continuous heating, and two intermittent heating methods were used. Using the Monte Carlo method, three-dimensional mesoscopic numerical models were developed to simulate the microwave heating and cooling processes. The temperature of both the aggregates and asphalt mortar were analyzed, considering the influence of particle size on the aggregate temperature. The results revealed that the average inner heating rate of the three specimens is higher than the average surface heating rate. The average surface and inner heating rates of PAC-MS were higher than those of PAC-US and PAC-B. The average surface temperature and inner temperature during the heating process changed linearly, while nonlinear temperature variations were observed during the subsequent cooling phase. Increasing the number of cooling intervals during heating resulted in a more uniform temperature distribution within steel slag aggregate specimens. The results of numerical simulation indicated that the maximum temperature of aggregate was greater than that of asphalt mortar. During the cooling process, the highest temperature of the aggregate continuously decreased, whereas the lowest temperature initially increased before decreasing. The highest average volume temperature for various particle sizes was observed within the range of 4.75–9.5 mm. The laboratory test results were effectively validated by the numerical simulations.

Classification of geogrid reinforcement in aggregate using machine learning techniques

The present study proposes a novel ML methodology for differentiating between unstabilized aggregate specimens and those stabilized with triangular and rectangular aperture geogrids. This study utilizes the compiled experimental results obtained from stabilized and unstabilized specimens under repeated loading into a balanced, moderate-sized database. The efficacy of five ML models, including tree-ensemble and single-learning algorithms, in accurately identifying each specimen class was explored. Shapley’s additive explanation was used to understand the intricacies of the models and determine global feature importance ranking of the input variables. All the models could identify the unstabilized specimen with an accuracy of at least 0.9. The tree-ensemble models outperformed the single-learning models when all three classes (unstabilized specimens and specimens stabilized by triangular and rectangular aperture geogrids) were considered, with the light gradient boosting machine showing the best performance—an accuracy of 0.94 and an area under the curve score of 0.98. According to Shapley’s additive explanation, the resilient modulus and confining pressure were identified as the most important features across all models. Therefore, the proposed ML methodology may be effectively used to determine the type and presence of geogrid reinforcement in aggregates, based on a few aggregate material properties and performance under repeated loading.

Comparison of diagnostic outcomes, safety, and cost of Franseen-tip 19G versus 22G needles for endoscopic ultrasound-guided liver biopsies.

Background and study aims Favorable outcomes were noted with refinement in newer endoscopic ultrasound-guided liver biopsy (EUS-LB) needle tips. Still, the overall usefulness and benefit are yet to be well explored. Patients and methods This was a retrospective analysis of patients with EUS-LB (Franseen-tip 19G versus 22G FNB needle) over 2 years. EUS-LB was obtained in a one-pass, two-actuation, modified wet suction technique. Diagnostic yield, fragmentation rate, aggregate specimen length (AL), number of complete portal tracts (CPT), length of longest intact core (LIC), adverse events (AEs) (early), and cost of the procedure (1USD = 82 INR) were compared. Results Fifty-four patients (33 [61.1%], female) successfully underwent EUS-LB with a median age of 46 years (interquartile range [IQR] 34-54); the majority 32 (59.2%) underwent 19G biopsies. There was a significantly increased median (IQR) AL in the 19G compared with 22G (20 mm [19-21] vs. 15 [14-15], P < 0.001), respectively. Similarly, significantly lengthier median LIC and CPT were seen, respectively. A nonsignificant diagnostic yield was noted (100% vs. 90.9%, P = 0.082), respectively. The fragmentation rate was higher in 22G FNB needles (36.4% [95% CI 16-56] vs. 12.5% [95% CI 1-24], respectively; P = 0.038). Seven patients (12.9%) had mild AEs with no difference between groups. The average procedure cost with 19G was INR 63000 (768$), and with 22G needle was INR 54500 (664$). Conclusions The Franseen-tip 19G outperforms 22G with a significantly lower fragmentation rate, longer AL, LIC, and a higher number of CPT with a marginal increase in the procedure cost, without any difference in diagnostic yield and safety.

Durability, Capillary Rise and Water Absorption Properties of a Fiber-Reinforced Cement-Stabilized Fly Ash–Stone Dust Mixture

The management of unutilized fly ash poses challenges due to concerns about storage and its potential groundwater contamination. Within the road industry, where the bulk utilization of fly ash is feasible, its unsuitability for use in the base and sub-base layers of pavements due to its low strength and a high proportion of fine particles has been a limitation. The incorporation of stone dust alongside fly ash, treated with lime or cement, yields superior strength and stiffness. Apart from strength, the stabilized mix’s durability, capillary rise, and water absorption properties are crucial for determining its suitability for pavement applications. Observations from this study reveal that fiber-reinforced cement-stabilized fly ash–stone aggregate specimens treated with 4% and 6% cement, with and without fibers, met the limiting mass loss of 20%, as specified in IRC SP: 89. The mass loss decreases with an increase in cement and fiber content. However, the capillary rise in the mixes increases with a higher percentage of fly ash and fiber content but decreases with increased cement content. Cement addition results in a reduction in water absorption; however, the addition of fibers results in an increase in water absorption. A linear correlation has been established between mass loss and UCS and IDT, which can be used to evaluate the suitability of materials for the structural layer without conducting a wet–dry durability test, which typically takes one month. This study proposes that cement-stabilized fly ash and stone aggregate mixtures with 4% and 6% cement can be used as the subbase and base of pavement based on wet–dry mass loss criteria and water absorption criteria. Observations from this study reveal that fiber-reinforced cement-stabilized fly ash–stone aggregate specimens treated with 4% and 6% cement, with and without fibers, met the limiting mass loss of 20%, as specified in IRC SP: 89. The mass loss decreases with an increase in cement and fiber content. However, the capillary rise in the mixes increases with a higher percentage of fly ash and fiber content but decreases with increased cement content. Cement addition results in reduction in water absorption. However, the addition of fibers results in increase in water absorption. A linear correlation is established between mass loss and UCS and IDT, which can be used to evaluate the suitability of materials for the structural layer without conducting wet–dry durability tests, which take one month. This study proposes that cement-stabilized fly ash and stone aggregate mixtures with 4% and 6% cement can be used as the subbase and base of pavement based on wet–dry mass loss criteria and water absorption criteria.

Bender element sensor technology to quantify local stiffness enhancement of geogrid-stabilized aggregate specimens

Geogrids improve pavement performance and extend lifespan by making the unbound aggregate base/subbase course stiffer. Extruded (i.e., punched and drawn) geogrids are widely used in pavement applications. This paper presents an experimental evaluation of multi-axial extruded geogrids with various aperture shapes for pavement applications. The study quantified modulus enhancement ratio and identified the extent of the geogrid-stiffened zone. Two types of aggregates (i.e., crushed limestone and partially crushed gravel), commonly used in Illinois for base or subbase course, were utilized. Repeated load triaxial tests were conducted on 6-in. diameter and 12-in. height cylindrical specimens instrumented with embedded shear wave transducers in the form of Bender Element (BE) sensors. The BE pairs were horizontally placed at three different heights above the geogrid. Resilient moduli of the aggregate samples were determined following the AASHTO T 307 standard test procedure. Concurrently, the localized small-strain moduli at different heights above the midheight of the specimen were determined from the shear wave velocities computed according to the first arrival times from the BE sensors recorded at the end of the application of each stress state. The results reveal that resilient modulus tests do not capture the geogrid effects, while BE sensors can quantify the local stiffness enhancement due to a geogrid, and the extent of the geogrid-stiffened zone. Results show that the multi-axial geogrids provided a 45% increase in small strain modulus for both aggregate types in the vicinity of the geogrid.

Evaluation of Nepali Aggregates for Alkali-silica Reactivity Using Accelerated Mortar Bar Test Method

In many countries, large concrete structures needed to be replaced by new structures because treatment of Alkali Silica Reaction (ASR) was not feasible. Availability of amorphous or poorly crystalline silica is a necessary condition for ASR and it has been a common problem in several countries located in cold geographical regions. Some Nepali rocks also comprise amorphous silica as detected in Sanjen Hydropower Project (SHP) and Tanahu Hydropower Project (THP) during the examination of aggregate through various tests. ASR kinetics and the resulting expansion are observed to be enhanced with an increase in temperature and humidity. Accordingly, the risk of ASR is expected to be prominent in Nepal where temperature and humidity are relatively high. However, systematic research on ASR in Nepal is scarce and the possibility of ASR is little known. This paper determines the reactivity of potential aggregate sources considered for some large infrastructures in Nepal. Accelerated mortar bar test based on the guidelines of ASTM C1260 was performed on aggregate specimens collected from the Pokhara Regional International Airport Project (PRIAP), THP, and SHP. 14-day longitudinal expansion of the mortar bar prepared from the aggregated collected from PRIAP, THP, and SHP was 0.1%, 0.17%, and 0.06% respectively. The aggregate collected from THP is deleterious, whereas aggregate collected from PRIAP and SHP is non-reactive. This study demonstrates that Nepal may have many sources of aggregates that are reactive.

Comparing a 19-gauge fine-needle biopsy needle with a 22-gauge fine-needle biopsy needle for EUS-guided liver biopsy sampling: a prospective randomized study

EUS-guided liver biopsy (EUS-LB) sampling is being increasingly used. We performed a prospective randomized trial to compare specimen adequacy of a 19-gauge fine-needle biopsy (FNB) needle with a 22-gauge FNB Franseen tip needle for EUS-LB sampling. Forty-two consecutive patients referred for EUS-LB sampling were prospectively randomized to a 19-gauge or 22-gauge FNB needle. When the specimen with the 22-gauge needle was macroscopically inadequate, an additional pass with the 19-gauge needle was done. Bilobar EUS-LB sampling was performed with heparinized wet suction using 1 pass and 3 actuations per lobe. Descriptive statistics were computed for all variables. Biopsy sampling was performed for abnormal liver enzymes in 95.5% of patients (57% women; average age, 51 years). Five patients undergoing sampling with the 22-gauge FNB needle had macroscopically inadequate specimens and required additional biopsy sampling with the 19-gauge FNB needle. Mean preprocessing length of the longest tissue core was 21.5 ± 6.3mm with a 19-gauge FNB needle compared with 9.4 ± 5.5mm with the 22-gauge FNB needle (P< .001). Postprocessing specimens were significantly longer with 19-gauge than with 22-gauge FNB needles (17.4mm vs 6.8, P< .001). There were no adverse events, and postprocedure pain and discomfort was similar in both groups (14% for 19-gauge vs 10% for 22-gauge, P= .99). Liver core biopsy sampling using the 19-gauge FNB needle is superior to the 22-gauge FNB needle in terms of length of longest core and aggregate specimen length. Considerably more fragmentation of the 22-gauge cores occurs during tissue processing. No increased postprocedure pain or AEs were found with the 19-gauge needle. A 19-gauge FNB needle is preferred to the 22-gauge FNB needle for EUS-LB. (Clinical trial registration number: NCT04806607.).

Experimental and Analytical Investigation of Fracture Characteristics of Steel Fiber-Reinforced Recycled Aggregate Concrete

AbstractFracture parameters of fiber concrete (FC) are currently a hot research area. Fracture mechanics is the field of solid mechanics that helps to study the type and propagation of cracks in materials. It uses methods of calculating the driving force on a crack and characterizes the material's resistance to fracture. Behavioral characteristics are determined by crack mouth opening displacement and the load–deflection method. This research identifies the fracture parameters of 33 notched simply supported beams made by recycled aggregate cement concrete with steel fiber. The recycled aggregate ratio in concrete has been altered to determine the effect on the mechanical and fracture properties. For determining fracture parameters, a 3-point bending single-edge notched fracture test was used. The results indicated that the steel fiber-reinforced concrete made with recycled aggregate showed similar performance and fracture characteristics compared to normal concrete. Thus, adding steel fibers to various concrete mixes considerably improved the fracture characteristics, while the brittleness was reduced with increased steel fiber content. Linear regression analysis also showed the accuracy of mechanical strength results as the value of R-square was close to unity. Displacement, ultimate load, brittleness (B), fracture toughness (KIC), crack mouth opening displacement (CMOD), fracture energy (GF), modulus of elasticity (E), and characteristic length (lch), were determined for both conventional and recycled aggregate specimens. The “work of fracture"—by definition the formula—is the most reliable to calculate the fracture energy as the nonlinearity is related to the performance of FC.

Modeling geogrid-stabilized aggregate base courses considering local stiffness enhancement

Lateral restraint is the primary stabilization mechanism associated with the interlocking of aggregate particles in the geogrid apertures. This paper presents findings from a laboratory study which quantifies the local stiffness enhancement of aggregates through micromechanical interlocking provided by two different types of geogrids. These findings are applied to model the resilient response characteristics of geogrid-stabilized base course composite systems. Using three pairs of bender elements as shear wave transducers, horizontal stiffness profiles were determined above mid-heights of aggregate specimens. For two types of geogrids with square- and triangular-shaped apertures, the shear modulus profiles decreased moving away from the geogrid location. Based on a relationship for aggregates, resilient modulus was estimated from the shear modulus. Considering the variations in resilient moduli with distance from the geogrid location, the local stiffness enhancements provided by the two geogrid types were assigned to modulus profiles of a geogrid-stabilized aggregate base course in flexible pavement mechanistic analysis and modeling. The modeling results demonstrate the effect of geogrid base stabilization on the computed pavement resilient responses for both geogrid types. The sublayering approach which properly considers modeling of the geogrid influence zone could be effectively used in mechanistic analysis of a geogrid-stabilized pavement system.

Laboratory Testing of Ferrochrome Slag as an Aggregate in Porous Pavements

Abstract Porous asphalt (PA) is a bituminous mixture that is preferred in surface wearing courses because of its comparably better skid resistance and reduced spraying and hydroplaning risk, leading to improved driving quality compared with dense-graded hot mix asphalt mixtures. Use of recycled materials with satisfactory strength and durability properties as an aggregate in PA mixtures would provide both economic and environmental benefits because natural resources would be preserved, and transportation costs, and consequently CO2 emissions, would be reduced, and the stockpiled recycled material would be employed instead of occupying scarce landscape. However, because of the high air void content and exposure of a larger surface area to atmosphere in PA mixtures, the potential for raveling and rapid aging for any proposed aggregate material needs to be evaluated carefully. This study was conducted to investigate the performance of ferrochrome slag (FS), a by-product of ferrochromium industries, as an aggregate in porous asphalt. Air voids content, permeability, particle loss, tensile strength, and moisture susceptibility were measured on three different gradations of FS and the results were compared with the limits given in construction specifications. The gradation of the slag aggregates along with the bitumen content played a key role on performance of the PA mixtures. The FS specimens prepared at an optimum bitumen content of 6.5 % performed significantly better than limestone (LS) aggregate specimens at the same gradation; the air void content, permeability, and tensile strength of the FS mixtures were 2 %, 50 %, and 16 % higher than the LS mixtures, respectively.

Predicting permanent strain accumulation of unbound aggregates using machine learning algorithms

The objective of this study is to propose a machine learning-based framework for predicting the permanent strain accumulation of unbound aggregates. To develop the machine learning-based framework, material properties of 15 crushed aggregates determined at two different gradations are combined with the applied stress states on aggregate specimens during repeated load triaxial testing by considering the aggregate shear strength characteristics. Three single machine learning algorithms (K-nearest neighbor, neural network, and decision tree) and two ensemble learning algorithms (random forest and extreme gradient boosting) are used in this study. Based on the dataset obtained from 90 permanent deformation tests, hyperparameters, which are used to control the learning process, are optimized. The numerical results demonstrate that all five of the tuned machine learning models exhibit good generalization capacity and performance with the coefficient of determination exceeding 0.99. Among the five models, the extreme gradient boosting model outperforms the others, accurately predicting permanent strain accumulation even for load cycles of 10,000. The contributions of individual input features to the performance of each learning model depend on the dataset. The strength characteristics and the applied deviatoric stress are the two most important features. Therefore, the machine learning-based framework introduced in this study may be effectively used for predicting the permanent strain accumulation of unbound aggregate layer.

Evaluation of Steel Slag Optimal Replacement in Asphalt Mixture under Microwave Heating Based on 3D Polyhedral Aggregate Electromagnetic-Thermal Meso-Model

Replacing conventional aggregate with steel slag waste can boost the microwave absorption properties of asphalt mixtures and reduce pollution to protect the environment. In order to achieve the best healing in steel slag asphalt mixture, the optimum particle size and content of steel slag are essential. For this purpose, a high-efficiency algorithm for the random growth and placement of convex polyhedron aggregate is proposed in this paper. The limestone aggregate is replaced with an equal volume of steel slag, and a three-dimensional mesoscale random model of steel slag asphalt mixture is developed. The process of microwave heating is simulated by FEM. The numerical simulations are compared with the reported experimental data, which proves that the model is reliable (R2 = 99.40%). Both the volume average temperature and the uniformity of temperature distribution indicate that the steel slag replacement rate of 60% at 4.75–9.5 mm and 60% at 9.5–13.2 mm is optimal, among which the heat transfer of 4.75–9.5 mm steel slag is more uniform, and the temperature gradient is lower. Steel slag can dramatically increase the heating rate of an asphalt mixture, and the peak of the temperature gradient is around the boundary of steel slag. The reflection properties of steel slag may be related to the dielectric constant, permeability, and particle size. Excess steel slag will cause overheating in most zones of the specimen and will also depress the absorption efficiency of microwaves. The coefficient of variance for spherical (0.36) and polyhedral (0.32) aggregate specimen temperatures indicates that the aggregate’s shape has a negligible effect on the heat transfer of asphalt mixtures.

Optimisation of recycled concrete aggregates for cement-treated bases by response surface method

ABSTRACT Sustainability is a primary concern that needs to be addressed since infrastructure development requires significant natural resources. Using Recycled Concrete Aggregates (RCA) for road construction has numerous benefits in saving natural resources and the environment. In the present investigation, the demolition waste is being used for road construction, partially/fully replacing natural aggregates. The Cement Treated Recycled Concrete Aggregate (CTRCA) specimens were prepared at 3%, 5%, and 7% cement with various blends of RCA and Natural Coarse Aggregates (NCA) ranging from 0 to 100%. The strength characteristics in terms of Unconfined Compressive Strength (UCS), Flexural Strength (FS), Elastic Modulus, Indirect Tensile Strength (ITS) and durability tests were conducted on cured samples. Microstructural analysis using Scanning Electronic Microscope (SEM) revealed that the pores and cracks in the old mortar have a detrimental influence on the mechanical properties of CTRCA mixes. However, Energy Dispersive Spectroscopy (EDS) and durability tests have shown positive results. The Response Surface Method (RSM) was utilised to optimise the RCA and cement content in CTRCA mixes. The research resulted in the maximum possible RCA of up to 70% with a cement content of 5.8%, which met the Indian Road Congress (IRC) specifications for Cement Treated Bases (CTB).

Torsional Strength of Recycled Coarse Aggregate Reinforced Concrete Beams

This study discusses the torsional capacity of recycled coarse aggregate (RCA) reinforced concrete beams under pure torsion based on the experimental findings available in the literature. The experimental data on RCA specimens were collected and compared with the conventional concrete specimens with key variables, such as compressive strength and longitudinal and transverse reinforcement ratios, as those variables affect the torsional capacity of reinforced concrete beams. Overall, the database consisted of experimental results from 30 RCA specimens and 256 natural coarse aggregate (NCA) specimens. The result shows that specimens with a 100 % replacement ratio have the lowest strength. In addition, as the structural mechanism of torsion is similar to the shear mechanism in reinforced concrete beams, a comparative analysis was performed with RCA specimens subjected to shear force. It was concluded that the RCA has a similar effect in strength reduction for the specimens subjected to torsion or shear with a 100% replacement ratio. However, further study and experimental evidence are required to confirm the applicability of the recycled aggregate to produce and design the structural members.

Digital Morphology: The Final Frontier

Morphology is central to biological anthropology and its allied fields of anatomical sciences, forensics, and other related disciplines. Many biological anthropology students have their first real foray into the discipline after completing a course in osteology, craniometry, or vertebrate morphology. Unfortunately, the natural history collections that support this type of research and training have not grown. Many countries have strict rules about natural history specimen collections, and these collections seem to be concentrated in a few developed countries, regardless of where the specimens had been collected. Thus, access to comparative material can be problematic where such collections are not readily available. Even if collections are available, accessing them can be severely restricted due to external circumstances, as the prolonged pandemic has shown. Luckily, digital morphology has emerged over the last decade as a new field that stands to change the landscape of specimenbased research and training. Concerted 2D and 3D digitization efforts, the emergence of online aggregate specimen repositories, and availability of comprehensive open-source software tools (such as 3D Slicer) for utilizing these resources has conveniently transformed the field of quantitative and comparative morphology. In this brief review, I will focus explicitly on the 3D Slicer ecosystem and how it can be leveraged as part of a curriculum or research program on digital morphology. In a nutshell, the primary differentiator of the 3D Slicer is not that it is just free but that it is open-source and extensible, making access to digital data more equitable for everyone. I will particularly focus on the 3D Slicer’s SlicerMorph extension, which facilitates 3D geometric morphometric data collection and analysis within the Slicer ecosystem, so all the steps in the digital morphology workflow from import, visualization, and data collection to visualizing the morpho-space can be achieved in a single, well-documented environment.