Mask-Guided Vision Transformer for Few-Shot Learning.

Learning with little data is challenging but often inevitable in various application scenarios where the labeled data are limited and costly. Recently, few-shot learning (FSL) gained increasing attention because of its generalizability of prior knowledge to new tasks that contain only a few samples. However, for data-intensive models such as vision transformer (ViT), current fine-tuning-based FSL approaches are inefficient in knowledge generalization and, thus, degenerate the downstream task performances. In this article, we propose a novel mask-guided ViT (MG-ViT) to achieve an effective and efficient FSL on the ViT model. The key idea is to apply a mask on image patches to screen out the task-irrelevant ones and to guide the ViT focusing on task-relevant and discriminative patches during FSL. Particularly, MG-ViT only introduces an additional mask operation and a residual connection, enabling the inheritance of parameters from pretrained ViT without any other cost. To optimally select representative few-shot samples, we also include an active learning-based sample selection method to further improve the generalizability of MG-ViT-based FSL. We evaluate the proposed MG-ViT on classification, object detection, and segmentation tasks using gradient-weighted class activation mapping (Grad-CAM) to generate masks. The experimental results show that the MG-ViT model significantly improves the performance and efficiency compared with general fine-tuning-based ViT and ResNet models, providing novel insights and a concrete approach toward generalizing data-intensive and large-scale deep learning models for FSL.

Physicomechanical, Wettability, Corrosion, Thermal, and Microstructural Morphology Characteristics of Carbonized and Uncarbonized Bagasse Ash Waste-Reinforced Al-0.45Mg-0.35Fe-0.25Si-Based Composites: Fabrications and Characterizations.

An effort was being made to incorporate waste bagasse ash (WBA) both in carbonized and uncarbonized form into the formulation of Al6063 matrix-based metal matrix composites (MMC's) by partially substituting ceramic particles for them. In the process of developing composites, comparative research on carbonized WBA and uncarbonized bagasse powder was carried out in the role of reinforcement. Microstructure investigations revealed that carbonized WBA particles were properly distributed throughout the aluminum-base metal matrix alloy. They also had the appropriate level of wettability. The reinforcement of carbonized WBA particles in AA6063-based matrix material had a maximum tensile strength of 110 MPa and a maximal hardness of 39 BHN when 3.75 wt % of the particles were used. The deterioration in tensile strength (6.25 wt % of WBA) and the appearance of porosity and blowholes can be enumerated by tensile fractography-based scanning electron microscopy (SEM) analysis. The reinforcement of carbonized WBA particles in AA6063-based matrix material was found to have a maximal percent elongation of 14.42% and the highest fracture toughness of 15 Joules when 1.25 wt % of the particles were employed. For AA6063/3.75 wt % carbonized WBA-based MMC's, the minimum percent porosity was determined to be 5.83, and the minimum thermal expansion was found to be 45 mm3. As the percentage of reinforcement in bagasse-reinforced composites increases, the density of the material, the amount of corrosion loss, and the cost all decrease gradually. The AA6063 matrix, with a composition of 3.75 wt % carbonized WBA-based MMC's, had satisfactory specific strength and corrosion loss. The AA6063 alloy composite's microstructure analysis revealed that carbonized WBA enhanced the material's mechanical characteristics, contributing to its excellent mechanical capabilities. The results of the corrosion test showed that carbonized WBA-reinforced composites exhibited reduced weight loss due to corrosion, whereas uncarbonized bagasse powder was an inappropriate reinforcement. The SEM analysis of AA6063 alloy/3.75 wt % carbonized WBA ash reinforcement-based MMC's exposed to a 3.5 wt % NaCl solution has exhibited the development of corrosion pits as a result of localized attack by the corrosive environment. The thermal expansion test showed that the composite with uncarbonized bagasse powder as reinforcement have a high shrinkage rate in comparison with the composite with 3.75 wt %. The composite's mechanical characteristics and thermal stability were enhanced by the presence of hard phases like SiO2, Al2O3, Fe2O3, CaO, and MgO, as revealed by X-ray diffraction analysis. This made it suitable for use in a variety of applications.

Exploring Microstructural, Interfacial, Mechanical, and Wear Properties of AlSi7Mg0.3 Composites with TiMOVWCr High-Entropy Alloy Powder.

This study explored the impact of varying weight percentages of TiMoVWCr high-entropy alloy (HEA) powder addition on A356 composites produced using friction stir processing (FSP). Unlike previous research that often focused on singular aspects, such as mechanical properties, or microstructural analysis, this investigation systematically examined the multifaceted performance of A356 composites by comprehensively assessing the microstructure, interfacial bonding strength, mechanical properties, and wear behavior. The study identified a uniform distribution of TiMoVWCr HEA powder in the composition A356/2%Ti2%Mo2%V2%W2%Cr, highlighting the effectiveness of the FSP technique in achieving homogeneous dispersion. Strong bonding between the reinforcement and matrix material was observed in the same composition, indicating favorable interfacial characteristics. Mechanical properties, including tensile strength and hardness, were evaluated for various compositions, demonstrating significant improvements across the board. The addition of 2%Ti2%Mo2%V2%W2%Cr powder enhanced the tensile strength by 36.39%, while hardness improved by 62.71%. Similarly, wear resistance showed notable enhancements ranging from 35.56 to 48.89% for different compositions. Microstructural analysis revealed approximately 1640.59 grains per square inch for the A356/2%Ti2%Mo2%V2%W2%Cr processed composite at 500 magnifications. In reinforcing Al composites with Ti, Mo, V, W, and Cr high-entropy alloy (HEA) particles, each element imparted distinct benefits. Titanium (Ti) enhanced strength and wear resistance, molybdenum (Mo) contributed to improved hardness, vanadium (V) promoted hardenability, tungsten (W) enhanced wear resistance, and chromium (Cr) provided wear resistance and hardness. Anticipating the potential applications of the developed composite, the study suggests its suitability for the aerospace sector, particularly in casting lightweight yet high-strength parts such as aircraft components, engine components, and structural components, underlining the significance of the investigated TiMoVWCr HEA powder-modified A356 composites.

A novel study on the influence of graphene-based nanofluid concentrations on the response characteristics and surface-integrity of Hastelloy C-276 during minimum quantity lubrication.

In present investigation, the impact of nanoparticle concentration on the machining accomplishment of Hastelloy C-276 has been examined in turning operation. The outputs like temperature, surface roughness, chip reduction coefficient (CRC), tool wear, and friction coefficient along with angle of shear have been estimated. The graphene nanoparticles (GnP) have been blended into soybean oil in distinct weight/volume ratio of 0.5, 1 and 1.5%. The experimental observations revealed that higher concentration of nanoparticles has enhanced the heat carrying capacity of amalgamation by 12.28%, surface roughness (27.88%), Temperature (16.8%), tool wear (22.5%), CRC (17.5%), coefficient of friction (46.36%) and shear angle (15%). Scanning electron microscopy identified nose wear, abrasion, adhesion and loss of tool coating. Further, lower tool wear has been noticed at 1.5% concentration, while the complete failure of insert has been reported during 116 m/min, 0.246 mm/rev having 0.5% concentration. ANOVA results exhibited that surface roughness is highly influenced by speed rate (41.66%) trailed by feed rate (28.16%) and then after concentration (13.68%). Temperature is dominated by cutting speed (69.31%), concentration (14.53%) and feed rate (13.25%). Likewise, tool wear was majorly altered by cutting speed (67.2%) accompanied by feed rate (23.90%) and thirdly concentration of GnP (5.03%).

Performance investigations for sustainability assessment of Hastelloy C-276 under different machining environments.

Hastelloy is categorized as difficult to cut superalloy widely used in aerospace, nuclear reactor components and chemical industry because of its magnificent strength and higher heat efficiency. Since, the machining of this material is quite difficult and hence suitable cooling systems are required to achieve sustainable manufacturing goals. The present investigation has been focused on the machining performance and sustainability assessment of turning Hastelloy C-276 in dry, flood and minimum quantity lubrication (MQL) environments. Taguchi L-9 array has been utilized to conduct and record the experimental output along with TOPSIS approach to evaluate the sustainability. The output responses viz. cutting forces, surface roughness, cutting temperature, energy consumption and carbon emission have been recorded at various levels of input variables. The experimental results revealed that MQL has minimized the cutting forces, surface roughness and temperature by margin of 20-38%. Likewise, energy expenditure and carbon emission was declined by 9-27% respectively compared to other conditions. Sustainability analysis explored best performance index during equal weightage criteria at 125 m/min, 0.246 and 0.8 mm doc under MQL. However, implementing assigned weightage system evaluated best condition for dry machining as 88 m/min and 0.246 mm/rev having same doc. SEM analysis of insert reported mainly abrasion and adhesion type of tool wear at all parametric range and machining conditions.

On Nonstationary Gaussian Process Model for Solving Data-Driven Optimization Problems.

In data-driven evolutionary optimization, most existing Gaussian processes (GPs)-assisted evolutionary algorithms (EAs) adopt stationary GPs (SGPs) as surrogate models, which might be insufficient for solving most optimization problems. This article finds that GPs in the optimization problems are nonstationary with great probability. We propose to employ a nonstationary GP (NSGP) surrogate model for data-driven evolutionary optimization, where the mean of the NSGP is allowed to vary with the decision variables, while its residue variance follows an SGP. In this article, the nonstationarity of GPs in the tested functions is theoretically analyzed. In addition, this article constructs an NSGP where the SGP is a degenerate case. Performance comparisons of the NSGP with the SGP and the NSGP-assisted EA (NSGP-MAEA) with the SGP-assisted EA (SGP-MAEA) are carried out on a set of benchmark problems and an antenna design problem. These comparison results demonstrate the competitiveness of the NSGP model.

An Uncertainty Measure for Prediction of Non-Gaussian Process Surrogates.

Model management is an essential component in data-driven surrogate-assisted evolutionary optimization. In model management, the solutions with a large degree of uncertainty in approximation play an important role. They can strengthen the exploration ability of algorithms and improve the accuracy of surrogates. However, there is no theoretical method to measure the uncertainty of prediction of Non-Gaussian process surrogates. To address this issue, this article proposes a method to measure the uncertainty. In this method, a stationary random field with a known zero mean is used to measure the uncertainty of prediction of Non-Gaussian process surrogates. Based on experimental analyses, this method is able to measure the uncertainty of prediction of Non-Gaussian process surrogates. The method's effectiveness is demonstrated on a set of benchmark problems in single surrogate and ensemble surrogates cases.

Prediction of cognitive scores by joint use of movie-watching fMRI connectivity and eye tracking via Attention-CensNet.

Background: Brain functional connectivity under the naturalistic paradigm has been shown to be better at predicting individual behaviors than other brain states, such as rest and doing tasks. Nevertheless, the state-of-the-art methods have found it difficult to achieve desirable results from movie-watching paradigm functional magnetic resonance imaging (mfMRI) -induced brain functional connectivity, especially when there are fewer datasets. Incorporating other physical measurements into the prediction method may enhance accuracy. Eye tracking, becoming popular due to its portability and lower expense, can provide abundant behavioral features related to the output of human's cognition, and thus might supplement the mfMRI in observing participants' subconscious behaviors. However, there are very few studies on how to effectively integrate the multimodal information to strengthen the performance by a unified framework. Objective: A fusion approach with mfMRI and eye tracking, based on convolution with edge-node switching in graph neural networks (CensNet), is proposed in this article. Methods: In this graph model, participants are designated as nodes, mfMRI derived functional connectivity as node features, and different eye-tracking features are used to compute similarity between participants to construct heterogeneous graph edges. By taking multiple graphs as different channels, we introduce squeeze-and-excitation attention module to CensNet (A-CensNet) to integrate graph embeddings from multiple channels into one. Results: The proposed model outperforms those using a single modality and single channel, and state-of-the-art methods. Conclusions: The results indicate that brain functional activities and eye behaviors might complement each other in interpreting trait-like phenotypes.

Recent developments in the design, development, and analysis of the influence of external magnetic-field on gas-metal arc welding of non-ferrous alloys: review on optimization of arc-structure to enhance the morphology, and mechanical properties of welded joints for automotive applications.

"External magnetic-field (EMF)" has been proved as an additional process parameter like voltage and current affecting the weld arc form, molten metal-flow, microstructure, and characteristics of the weld joint. This article analyzed the research work that has been done to promote EMF application in welding and discussed the recent development trends and research in the design and fabrication of EMF setup to the controlled arc welding process. It is found that even after the successful application of EMF in welding. Still, there is no mass level initiation to integrate EMF with welding machines that hinder researchers and manufacturers to accept it as a regular process parameter to control weld quality.

Progressive developments and challenges in dissimilar laser welding of steel to various other light alloys (Al/Ti/Mg): A comprehensive review.

In recent days, the utilization of lightweight alloys for various applications has been increased massively. Starting from the automobile industry, aerospace industry, and even in the biomedical field, there is a need for dissimilar precise joining of steel to other light alloys (magnesium alloy, aluminum alloy, titanium alloy). However, those alloys are characterized by different melting temperatures, machinability, strength, thermal conductivity, and oxygen reactivity. Considering this welding to challenge ongoing laser welding efforts to improve laser welding quality by altering the welding techniques, modes, proper use of shielding gasses, using suitable process parameters, and even proper joint and surface preparations are discussed. The feasibility of implementing all those things in the industrial setup can be understood only after analyzing recent works. Changes in microstructure and the defects (solidification cracking, intermetallic components formation, porosity) arrived during and after laser welding of these materials are reviewed. The paper also highlights the effect of shielding gas, welding speed, laser power, defocusing position, etc. during laser welding of lightweight materials. The critical issues related to dissimilar laser welding of these combinations and some remedial measures are discussed. The purpose of this review is to emphasize and understand the recent trends of dissimilar laser welding and explore the scope of industry level applications.

Scaffold Fabrication Techniques of Biomaterials for Bone Tissue Engineering: A Critical Review.

Bone tissue engineering (BTE) is a promising alternative to repair bone defects using biomaterial scaffolds, cells, and growth factors to attain satisfactory outcomes. This review targets the fabrication of bone scaffolds, such as the conventional and electrohydrodynamic techniques, for the treatment of bone defects as an alternative to autograft, allograft, and xenograft sources. Additionally, the modern approaches to fabricating bone constructs by additive manufacturing, injection molding, microsphere-based sintering, and 4D printing techniques, providing a favorable environment for bone regeneration, function, and viability, are thoroughly discussed. The polymers used, fabrication methods, advantages, and limitations in bone tissue engineering application are also emphasized. This review also provides a future outlook regarding the potential of BTE as well as its possibilities in clinical trials.

Identification of localized defects and fault size estimation of taper roller bearing (NBC_30205) with signal processing using the Shannon entropy method in MATLAB for automobile industries applications.

Rotating machine is a common class of machinery in most of the industry and the main root cause of machinery failure is a faulty bearing. Bearings are most widely used in various types of machine elements ranging from small to heavy machinery and the common cause of machinery failure is a fault in bearings. Bearing faults can be external or internal which mainly depends on different operating conditions and these faults may cause severe damage to rotating components in machinery. Signal processing methods have traditionally been used to diagnose faults in tapered roller element bearings. A wavelet transform is the most common and effective tool for understanding and analyzing the vibration signal of bearings as it is responded quickly and observed sudden changes along with the transient impulses in the signal caused by faults in the different parts of bearing elements. In this article, localized fault's position and size on the outer ring of tapered roller bearing were investigated. Three different real values wavelets (DB2, Meyer, and Morlet) are analyzed as per Simple Sensitivity index criteria. Finally, experiments are carried out with four sets of bearing having fault on outer racing of bearing, and for the estimation of fault size, the setup was misaligned at ranging (0.00mm-1.50 mm) with a uniform deviation of 0.50 mm for each experiment. Shannon entropy was calculated for the identification of localized size of the faults with wavelets nomenclature, the result of DB2, Morlet, and Meyer wavelets at high-frequency zone are presented.The scanning electron microscope (SEM) has been taken for the estimation of size of the fault. The proposed method has been successfully implemented for measuring defect width and size. Also, it has been observed that with increased magnification level from 0.00 mm to 0.50 mm, the crack width of the faulty bearing was increased by 0.813 mm, and whenever on further increase in magnification level of 0.50, 1.00 mm and 1.50 mm the crack width of the faulty bearing was increased by 2.568 mm and 3.856 respectively.

An Intelligent Logic-Based Mold Breakout Prediction System Algorithm for the Continuous Casting Process of Steel: A Novel Study.

Mold breakout is one of the significant problems in a continuous casting machine (caster). It represents one of the key areas within the steel production facilities of a steel plant. A breakout event on a caster will always cause safety hazards, high repair costs, loss of production, and shutdown of the caster for a short while. In this paper, a logic-judgment-based mold breakout prediction system has been developed for a continuous casting machine. This system developed new algorithms to detect the different sticker behaviors. With more algorithms running, each algorithm is more specialized in the other behaviors of stickers. This new logic-based breakout prediction system (BOPS) not only detects sticker breakouts but also detects breakouts that takes place due to variations in casting speed, mold level fluctuation, and taper/mold problems. This system also finds the exact location of the breakout in the mold and reduces the number of false alarms. The task of the system is to recognize a sticker and prevent a breakout. Moreover, the breakout prediction system uses an online thermal map of the mold for process visualization and assisting breakout prediction. This is done by alerting the operating staff or automatically reducing the cast speed according to the location of alarmed thermocouples, the type of steel, the tundish temperature, and the size of the cold slab width. By applying the proposed model in an actual steel plant, field application results show that it could timely detect all 13 breakouts with a detection ratio of 100%, and the frequency of false alarms was less than 0.056% times/heat. It has the additional advantage of not needing a lot of learning data, as most neural networks do. Thus, this new logical BOPS system should not only detect the sticker breakouts but also detect breakouts taking place due to variations in casting speed and mold level fluctuation.

Study of Wear, Stress and Vibration Characteristics of Silicon Carbide Tool Inserts and Nano Multi-Layered Titanium Nitride-Coated Cutting Tool Inserts in Turning of SS304 Steels.

Cutting tool characterization plays a crucial role in understanding the behavior of machining operations. The selection of a suitable cutting material, the operating conditions for the work piece, is necessary to yield good cutting-tool life. Several pieces of research have been carried out in cutting-tool characteristics for turning operation. Only a few pieces of research have focused on correlating the vibrations and stress with wear characteristics. This research article deals with stress induced in silicon carbide tool inserts and coated tool inserts while machining SS304 steel. Since this material is much less resistant to corrosion and oxidation it is widely used in engineering applications such as cryogenics, the food industry and liquid contact surfaces. Moreover, these materials have much lower magnetic permeability so they are used as nonmagnetic engineering components which are very hard. This article focuses on the machining of SS304 by carbide tool inserts and then, the cutting forces were observed with a tool dynamometer. Using observed cutting forces, the induced stress in the lathe tool insert was determined by FEA investigation. This research also formulates an idea to predict the tool wear due to vibration. Apparently, the worn-out tool vibrates more than new tools. Using the results, the relation between stress, strain and feed rate, depth of cut and speed was found and mathematically modeled using MINI TAB. It was observed that carbide tool inserts with coating withstand better than uncoated tools while machining SS304. The results were anticipated and correlation between the machining parameters furnished the prediction of tool life and obtaining the best machining outcomes by using coated tool inserts.

Novel insights on different treatment of magnesium alloys: A critical review.

Magnesium alloys are extensively used for weight reduction in automotive and aircraft applications. This research presents the effect of heat and cryogenic treatment on aluminium-zinc-based Mg alloys. Both treatments can improve the mechanical and corrosion properties of the AZ series Mg alloy. The review deals with a broad understanding of the microstructure changes that occur during heat and cryogenic treatment of Mg alloy. The mechanical and corrosion characteristics of heat and cryogenic treated AZ31, AZ91, AZ63, and AZ80 Mg alloys are discussed. The essential strengthening mechanisms of heat and cryogenic treated AZ series Mg are discussed with microstructure changes. This review has also shown a few gaps in research on the selection of suitable pre- and post-treatment processes for Mg alloy. The effects on grain refinement and the formation of secondary phase particles are discussed in detail. The related crystallographic plane, twining, and dislocation changes are out of the scope of this review. Finally, the correlations of the above changes to mechanical properties are the directions of the future.

A Critical Review on Hygrothermal and Sound Absorption Behavior of Natural-Fiber-Reinforced Polymer Composites.

Increasing global environmental problems and awareness towards the utilization of eco-friendly resources enhanced the progress of research towards the development of next-generation biodegradable and environmentally friendly material. The development of natural-based composite material has led to various advantages such as a reduction in greenhouse gases and carbon footprints. In spite of the various advantages obtained from green materials, there are also a few disadvantages, such as poor interfacial compatibility between the polymer matrix and natural reinforcements and the high hydrophilicity of composites due to the reinforcement of hydrophilic natural fibers. This review focuses on various moisture-absorbing and sound-absorbing natural fiber polymer composites along with the synopsis of preparation methods of natural fiber polymer composites. It was stated in various studies that natural fibers are durable with a long life but their moisture absorption behavior depends on various factors. Such natural fibers possess different moisture absorption behavior rates and different moisture absorption behavior. The conversion of hydrophilic fibers into hydrophobic is deemed very important in improving the mechanical, thermal, and physical properties of the natural-fiber-reinforced polymer composites. One more physical property that requires the involvement of natural fibers in place of synthetic fibers is the sound absorption behavior. Various researchers have made experiments using natural-fiber-reinforced polymer composites as sound-absorbing materials. It was found from various studies that composites with higher thickness, porosity, and density behaved as better sound-absorbing materials.

Effect of particle size and weight fraction of SiC on the mechanical, tribological, morphological, and structural properties of Al-5.6Zn-2.2Mg-1.3Cu composites using RSM: fabrication, characterization, and modelling.

Stir-casting was employed to create Al-5.6Zn-2.2Mg-1.3Cu composites with particle sizes ranging from 30 to 90 µm and a weight fraction of 5-15 SiC articles. The mechanical and wear properties of the material have been assessed. The wear-behaviour of Al-5.6Zn-2.2Mg-1.3Cu composites was investigated using dry pin-on-disc wear testing. Various loads (20 N-60 N), speeds (2 m/s-6 m/s), and sliding-distances were used in the sliding wear experiments (2000 m-4000 m). In the experimental process, XRD, SEM, and EDX were used to characterize the microstructures and materials of diverse composites. Uniform dispersion of the SiC particles is clearly observed in the SEM image. The micro hardness of SiC particles increases by 13% when the weight percent of SiC particles is increased from 5% to 15%. SiC particles outperform tiny SiC particles in terms of wear-resistance. With increasing load, the particular wear-rate showed an increasing trend (20-60 N). The wear-rate of the composite lowers as the weight percentage reinforcement increases (wt. 5% to wt. 15%), and the wear-rate of the composite increases when the particle-size (30 µm-90 µm) increases. The results demonstrated that composites supplemented with coarse SiC particles outperform tiny SiC particles in terms of wear resistance.

Analytical and Experimental Study on Cold-Formed Steel Built-Up Sections for Bending.

In the construction of steel structures, the two most common types of structural members are hot-formed and cold-formed members. This paper mainly describes the analytical and experimental research on the strength and characteristics of CFS bolted built-up sigma sections having different structural arrangements under bending. The cross-sectional dimensions for the parametric study were selected by the sizes available in the market. In this paper, ANSYS workbench software was used to perform FE modeling and observe the local, flexural, and interaction of these buckling. Then, experimental study was performed by varying the arrangement of open section beams between face-to-face and back-to-back, connected using bolts or fasteners different spacings. Further, we conducted bending tests on cold-formed steel built-up members having simple edge stiffeners in the middle. Comparing both analytical and experimental studies, the results indicate that the back-to-back connected built-up beam section provides a flexural capacity higher than the face-to-face built-up section. Moreover, increasing the bolt spacing enhanced the load-carrying capacity of back-to-back sigma section built-up beams. It has also been discovered that the flexural strength of beams is primarily determined by bolt spacing or itsposition.

Parametric Optimisation of Friction-Stir-Spot-Welded Al 6061-T6 Incorporated with Silicon Carbide Using a Hybrid WASPAS-Taguchi Technique.

Friction stir spot welding (FSSW) is one of the most popular fusion joining processes. The process is a solid-state welding process that allows welding of weldable as well as non-weldable materials. As a part of this investigation, weld samples of Al6061-T6 were reinforced with silicon carbide (SiC) powder with an average particle size of 45 µm. Initially, a Taguchi L9 orthogonal array was developed with three factors, i.e., rotational speed of the tool, pre-dwelling time, and diameter of the hole that was filled with SiC before welding. The effects of the SiC particles and process parameters were investigated as tensile-shear load and micro-hardness. The optimisation of parameters in order to maximise the output responses-i.e., strength and hardness of the welded joints-was performed using a hybrid WASPAS-Taguchi method. The optimised process parameters obtained were a 3.5 mm guiding hole diameter, 1700 rpm tool rotation speed, and 14 s of pre-dwelling time.

Investigation on Carbonation and Permeability of Concrete with Rice Hush Ash and Shop Solution Addition.

The goal of this study was to determine the coefficient of permeability as well as the rate of carbonation of concrete constructed with rice husk ash (RHA) as a partial replacement for cement (i.e., 5%, 10%, and 15%) and two different concentrations of soap solutions (i.e., 1 percent and 2 percent). The microstructural studies of RHA, and carbonated samples have been conducted by using Scanning Electron Microscope (SEM) and X-Ray Diffraction (XRD) analysis. According to this study, the carbonation depth of concrete made with 1% and 2% soap solution concentration and without rice husk ash decreased by 11.89% and 46.55%, respectively. From the results, it may also be observed that the carbonation depth of concrete made with up to 10% replacement of cement by rice husk ash led to maximum carbonation resistance, while more than 10% replacement of cement showed higher carbonation depth. It is also observed that the coefficient of permeability of concrete with 2% soap solution significantly decreased as compared to the 1% soap solution and control mix. It may be observed from the SEM images that 0% soap solution (M1) concrete has a very rough concrete surface which may indicate more voids. However, 2% soap solution concrete has a much smoother surface, which indicates a smaller number of voids. Furthermore, the SEM images showed that the soap solution helps in filling the voids of concrete which ultimately helps in reduction in permeability. Energy Dispersive X-Ray Analysis (EDX) of concrete with 0% (M1) and 2% (M6) soap solution disclosed that the concrete with 2% soap solution (M6) exhibited more silica element formation than the concrete with no soap solution (M1).