ABSTRACT
Cardiovascular diseases, particularly coronary artery disease, pose big challenges to human life. Deployment of the stent is a preferable treatment for the above-mentioned disease. However, stents are usually made up of shape memory alloy called Nitinol. The poorer surface finish on the machined nitinol stents accelerates the migration of Nickel ions from the implanted nitinol stent, which is considered toxic and can lead to stenosis. The current study deals with controlling surface quality by minimising surface roughness and improving corrosion resistance. Femtosecond laser (fs-laser 10-15 s) micromachining was employed to machine the Nitinol surface to achieve sub-micron surface roughness. The Grey relational analysis (GRA)-coupled design of the experimental technique was implemented to determine optimal levels of four micromachining parameters (laser power, pulse frequency, scanning speed, and scanning pattern) varied at three levels to achieve minimum surface roughness and to maximise the volume ablation. The results show that to yield minimum surface roughness and maximum volume ablation, laser power and scanning speed are in a higher range. In contrast, the pulse frequency is lower, and the scanning pattern is in a zig-zag manner. ANOVA results manifest that scanning speed is the predominant factor in minimising surface roughness, followed by pulse frequency. Furthermore, the corrosion behaviour of the machined nitinol specimens was evaluated, and the results show that specimens with lower surface roughness had lower corrosion rates.
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Integration of photovoltaic (PV) systems, desalination technologies, and Artificial Intelligence (AI) combined with Machine Learning (ML) has introduced a new era of remarkable research and innovation. This review article thoroughly examines the recent advancements in the field, focusing on the interplay between PV systems and water desalination within the framework of AI and ML applications, along with it analyses current research to identify significant patterns, obstacles, and prospects in this interdisciplinary field. Furthermore, review examines the incorporation of AI and ML methods in improving the performance of PV systems. This includes raising their efficiency, implementing predictive maintenance strategies, and enabling real-time monitoring. It also explores the transformative influence of intelligent algorithms on desalination techniques, specifically addressing concerns pertaining to energy usage, scalability, and environmental sustainability. This article provides a thorough analysis of the current literature, identifying areas where research is lacking and suggesting potential future avenues for investigation. These advancements have resulted in increased efficiency, decreased expenses, and improved sustainability of PV system. By utilizing artificial intelligence technologies, freshwater productivity can increase by 10 % and efficiency. This review offers significant and informative perspectives for researchers, engineers, and policymakers involved in renewable energy and water technology. It sheds light on the latest advancements in photovoltaic systems and desalination, which are facilitated by AI and ML. The review aims to guide towards a more sustainable and technologically advanced future.
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The investigation focuses on determining the effects of canola oil-based cutting fluid with three different volume percentages of boric acid additives over the machining forces and surface roughness while turning hardened AISI 1018 mild steel. Experiments were carried out under Taguchi's design of the experiment concept. The minimum quantity lubrication (MQL) technique was followed to minimize the cutting fluid consumption. The homogeneity of the additives dispersed in the fluid has been validated through a zeta potential study. Machining forces and surface roughness were considered as chief machining objectives. The hybrid mathematical model, grey relational analysis (GRA)-artificial neural network (ANN), has been implemented to assess the performance of developed cutting fluid. The results explored that the canola oil cutting fluid with 5 wt% of boric acid additive exhibits lesser cutting forces and surface roughness. The optimal machining parameters identified by the hybrid modeling are 665 rpm of cutting speed, 35 mm/min of feed rate, and 0.3 mm of depth of cut, along with 5 wt% of boric acid composition in cutting fluid. The results explore the 2.677 times improvement in machining objective in comparison with a non-optimal set of parameters. The implementation of hybrid modeling is considered to be a novel attempt to minimize the machining objectives. It has been recorded a negligible error percentage of 0.66% between GRA and ANN prediction.
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Recently, most service or product-oriented industries have been focusing on their activities to uphold the green and sustainable environment protocol owing to the increased environmental pollution. Concerning this issue, industries are now concentrating on developing recyclable or waste materials products. This research advocates developing and validating a banana fiber sandwich composite to promote the beneficial usage of bio-waste. The composite sandwich specimens were fabricated with resin-impregnated woven banana fiber mat as a skin, and the core was reinforced with three different weight percentages (5, 7.5 and 10%) of chopped banana fiber. The sandwich specimens were pressed into a three-point bending test to validate the structural integrity. The flexural characteristics like flexural strength and modulus were examined experimentally, whereas the key strength indices like flexural stiffness and core shear modulus were evaluated analytically. Post-fracture surfaces were studied through a scanning electron microscope to investigate the failure mechanism. The experimental and analytical results indicate that 10% banana fiber content in the sandwich core increases the flexural strength and flexural modulus to 225% and 147%, respectively, compared to the neat epoxy core. The numerical simulation was also performed through FEA to validate the experimental findings. The numerical results are in good concurrence with the experimental one.
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The present work is focused on the nano-Hydroxyapatite (nHAp) synthesis with two different Indian breed Aseel and Kadaknath eggshells. The alloplast implants were developed through the foam replica method with polyurethane 45-PPI as a porous template. The synthesized nHAp was characterized by Field Emission Scanning Electron Microscopy (FE-SEM), X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR). The FE-SEM images of the nHAp showed the one dimensional clustered nanoparticles and the X-ray diffraction spectrum confirms that the major phase was hydroxyapatite with a small trace of ß-tricalcium phosphate. The maximum compression strength of the sample was 5.49 ± 0.12 MPa which is in the range of the compression strength of human trabecular bone. The thermal and degradability studies results confirmed that these are highly stable and provides necessary a resorption needed for new bone tissue formation. Besides, the antimicrobial activity against tested human microbiome are satisfactory and the cell viability towards MG 63 human osteoblast-like cells provides a potential pathway for developing the nHAp implants for bone tissue engineering.
Subject(s)
Durapatite , Orthopedics , Animals , Humans , Durapatite/chemistry , Egg Shell , Arthroscopy , Bone and Bones , Tissue Engineering/methods , X-Ray Diffraction , Dentistry , Spectroscopy, Fourier Transform Infrared , Tissue Scaffolds/chemistryABSTRACT
A limited experimental work was on multi-walled carbon nanotube (MWCNT)-water nanofluid with surfactant in the solar parabolic collector at low volume concentrations. At high-volume concentrated nanofluid, the pressure drop was more due to an increase in the viscosity of the working fluid and an increase in the nanoparticle cost; hence it is not economical. This report attempted to use Sodium Dodecyl Benzene Sulfonate (SDBS) surfactant in the low-volume concentrated MWCNT-water nanofluid to establish effective heat transfer in solar parabolic collector applications. The stable MWCNT-water nanofluid was prepared at 0.0158, 0.0238, and 0.0317 volume concentrations. The experiments were conducted from 10:00 to 16:00 at 6, 6.5 and 7 L/min flow rates concerning ASHRAE Standards. At the 7 L/min flow rate of the working fluid, having a minimum temperature difference between the working fluid and absorber tube leads to better heat transfer. The increased volume concentration of MWCNT in the water enhances the surface area interaction between water and MWCNT nanoparticles. This results in maximum solar parabolic collector efficiency at 0.0317 vol% with a 7 L/min flow rate and 10-11% higher than the distilled water.
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Recently, solar photovoltaic (PV) technology has shown tremendous growth among all renewable energy sectors. The attractiveness of a PV system depends deeply of the module and it is primarily determined by its performance. The quantity of electricity and power generated by a PV cell is contingent upon a number of parameters that can be intrinsic to the PV system itself, external or environmental. Thus, to improve the PV panel performance and lifetime, it is crucial to recognize the main parameters that directly influence the module during its operational lifetime. Among these parameters there are numerous factors that positively impact a PV system including the temperature of the solar panel, humidity, wind speed, amount of light, altitude and barometric pressure. On the other hand, the module can be exposed to simultaneous environmental stresses such as dust accumulation, shading and pollution factors. All these factors can gradually decrease the performance of the PV panel. This review not only provides the factors impacting PV panel's performance but also discusses the degradation and failure parameters that can usually affect the PV technology. The major points include: 1) Total quantity of energy extracted from a photovoltaic module is impacted on a daily, quarterly, seasonal, and yearly scale by the amount of dust formed on the surface of the module. 2) Climatic conditions as high temperatures and relative humidity affect the operation of solar cells by more than 70% and lead to a considerable decrease in solar cells efficiency. 3) The PV module current can be affected by soft shading while the voltage does not vary. In the case of hard shadowing, the performance of the photovoltaic module is determined by whether some or all of the cells of the module are shaded. 4) Compared to more traditional forms of energy production, PV systems offer a significant number of advantages to the environment. Nevertheless, these systems can procure greenhouse gas emissions, especially during the production stages. In conclusion, this study underlines the importance of considering multiple parameters while evaluating the performance of photovoltaic modules. Environmental factors can have a major impact on the performance of a PV system. It is critical to consider these factors, as well as intrinsic and other intermediate factors, to optimize the performance of solar energy systems. In addition, continuous monitoring and maintenance of PV systems is essential to ensure maximum efficiency and performance.
Subject(s)
Greenhouse Gases , Solar Energy , Dust/analysis , HumidityABSTRACT
Spar caps, which cover 50% of the cost of windmill blades, were made of unidirectional and biaxial glass/carbon reinforcements of 600 gsm with thicknesses ranging from 100 to 150 mm for blades 70-80 m long. The significance of this study was to utilize an economical biodegradable material i.e bamboo fabric of 125 gsm to fabricate a lightweight composite and study its behavior for spar caps applications. The aim of this research was to investigate the effect of weave pattern and composite size at coupon level under thermal, dynamic, water absorption, and flammability conditions. Composites comprising 125 gsm plain and twill weave bamboo as reinforcements/AI 1041 Phenalkamine bio-based hardener with epoxy B-11 as matrix were tested. Thermo-Gravimetric Analysis revealed that the weave pattern and composite thickness had an effect on the rate of weight loss and sustenance until 450 °C. The pattern had an effect on the glass transition temperature, as seen by Differential Scanning Calorimetry. The weave pattern and size thickness had an effect on energy storage and dissipation, displaying the damping behavior in DMA. The weave pattern and size had an effect on the rate of water absorption, which saturated after a few hours. The wettability and thickness of composites hampered the burning rate, with 5.4 mm thickness resulting in a 30% decrease.
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In recent decades, researchers have begun to investigate innovative sustainable construction materials for the development of greener and more environmentally friendly infrastructures. The main purpose of this article is to investigate the possibility of employing date palm tree waste as a natural fiber alternative for conventional steel and polypropylene fibers (PPFs) in concrete. Date palm fibers are a common agricultural waste in Middle Eastern nations, particularly Saudi Arabia. As a result, this research examined the engineering properties of high-strength concrete using date palm fibers, as well as the performance of traditional steel and PPF concrete. The concrete samples were made using 0.0%, 0.20%, 0.60%, and 1.0% by volume of date palm, steel, and polypropylene fibers. Ten concrete mixtures were made in total. Compressive strength, flexural strength, splitting tensile strength, density, ultrasonic pulse velocity (UPV), water absorption capability, and water permeability tests were performed on the fibrous-reinforced high-strength concrete. With a 1% proportion of date palm, steel, and polypropylene fibers, the splitting tensile strength improved by 17%, 43%, and 16%, respectively. By adding 1% fiber, flexural strength was increased by 60% to 85%, 67% to 165%, and 61% to 79%. In addition, date palm fibers outperformed steel and PPFs in terms of density, UPV, and water permeability. As a result, date palm fibers might potentially be employed in the present construction sector to improve the serviceability of structural elements.
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The development of aluminium composite with the inclusion of advanced materials is a continuous research process due to the increasing industrial demand for advanced hybrid materials. To cater for this need, this research work focuses on the development of Al 7075 alloy reinforced with TiB2 and graphene and on the evaluation of its strengthening mechanism. Two different modes of improving the strength of the hybrid composite have been followed; one is by the inclusion of graphene at three levels of 0.1, 0.2 and 0.3%, and another by the processing route, squeeze casting technique by compression of the molten hybrid composite slurry before casting. The microstructure and characterisation of the composite material are examined and analysed with the help of XRD, SEM, EDAX and chemical spectroscopy. A microstructure evaluation is employed to justify the homogenous dispersal and the existence of reinforced particles. A tensile test is conducted at room temperature and high temperature environments to assess the tensile strength. The research outcome affirms that a significant improvement in tensile and hardness has been noted in comparison with base alloy. The fracture-morphology results affirm the change in fracture mode from brittle to ductile when the tensile testing environment changes from room temperature to high temperature. Finally, the dispersion strengthening mechanism is validated with an empirical approach.
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Polymer-based nanocomposites are being considered as replacements for conventional materials in medium to high-temperature applications. This article aims to discover the synergistic effects of reinforcements on the developed polymer-based nanocomposite. An epoxy-based polymer composite was manufactured by reinforcing graphene nanoplatelets (GNP) and h-boron nitride (h-BN) nanofillers. The composites were prepared by varying the reinforcements with the step of 0.1 from 0.1 to 0.6%. Ultrasonication was carried out to ensure the homogenous dispersion of reinforcements. Mechanical, thermal, functional, and scanning electron microscopy (SEM) analysis was carried out on the novel manufactured composites. The evaluation revealed that the polymer composite with GNP 0.2 by wt % has shown an increase in load-bearing capacity by 265% and flexural strength by 165% compared with the pristine form, and the polymer composite with GNP and h-BN 0.6 by wt % showed an increase in load-bearing capacity by 219% and flexural strength by 114% when compared with the pristine form. Furthermore, the evaluation showed that the novel prepared nanocomposite reinforced with GNP and h-BN withstands a higher temperature, around 340 °C, which is validated by thermogravimetric analysis (TGA) trials. The numerical simulation model is implemented to gather the synthesised nanocomposite's best composition and mechanical properties. The minor error between the simulation and experimental data endorses the model's validity. To demonstrate the industrial applicability of the presented material, a case study is proposed to predict the temperature range for compressor blades of gas turbine engines containing nanocomposite material as the substrate and graphene/h-BN as reinforcement particles.
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Effect of parameters affecting solid particle erosion of crumb rubber epoxy composite is investigated. Five important process parameters-impact velocity, impingement angle, standoff distance, erodent size, and crumb rubber content-are taken into consideration. Erosion rate and erosion efficiency are included as the chief objectives. The Taguchi coupled gray relational analysis type statistical model is implemented to study interaction, parameters' effect on responses, and optimized parameters. ANOVA and regression model affirmed impingement angle and crumb rubber content play a significant role to minimize the erosion. Validity of the proposed model is justified with the standard probability plot and R2 value. A confirmation experiment conducted with A2B2C3D3E3 condition registers noticeable enhancement in GRG to the tune of 0.0893.
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The effect of crump rubber on the dry sliding wear behavior of epoxy composites is investigated in the present study. Wear tests are carried out for three levels of crump rubber (10, 20, and 30 vol.%), normal applied load (30, 40, and 50 N), and sliding distance (1, 3, and 5 km). The wear behavior of crump rubber-epoxy composites is investigated against EN31 steel discs. The hybrid mathematical approach of Taguchi-coupled Grey Relational Analysis (GRA)-Principal Component Analysis (PCA) is used to examine the influence of crump rubber on the tribological response of composites. Mathematical and experimental results reveal that increasing crump rubber content reduces the wear rate of composites. Composites also show a significant decrease in specific wear values at higher applied loads. Furthermore, the coefficient of friction also shows a decreasing trend with an increase in crump rubber content, indicating the effectiveness of reinforcing crump rubber in a widely used epoxy matrix. Analysis of Variance (ANOVA) results also reveal that the crump rubber content in the composite is a significant parameter to influence the wear characteristic. The post-test temperature of discs increases with an increase in the applied load, while decreasing with an increase in filler loading. Worn surfaces are analyzed using scanning electron microscopy to understand structure-property correlations. Finally, existing studies available in the literature are compared with the wear data of the present study in the form of a property map.
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This study investigated the engine performance and emission characteristics of biodiesel blends with combined Graphene oxide nanoplatelets (GNPs) and 10% v/v dimethyl carbonate (DMC) as fuel additives as well as analysed the tribological characteristics of those blends. 10% by volume DMC was mixed with 30% palm oil biodiesel blends with diesel. Three different concentrations (40, 80 and 120 ppm) of GNPs were added to these blends via the ultrasonication process to prepare the nanofuels. Sodium dodecyl sulphate (SDS) surfactant was added to improve the stability of these blends. GNPs were characterised using Scanning Electron Microscope (SEM) and Fourier Transform Infrared (FTIR), while the viscosity of nanofuels was investigated by rheometer. UV-spectrometry was used to determine the stability of these nanoplatelets. A ratio of 1:4 GNP: SDS was found to produce maximum stability in biodiesel. Performance and emissions characteristics of these nanofuels have been investigated in a four-stroke compression ignition engine. The maximum reduction in BSFC of 5.05% and the maximum BTE of 22.80% was for B30GNP40DMC10 compared to all other tested blends. A reduction in HC (25%) and CO (4.41%) were observed for B30DMC10, while a reduction in NOx of 3.65% was observed for B30GNP40DMC10. The diesel-biodiesel fuel blends with the addition of GNP exhibited a promising reduction in the average coefficient of friction 15.05%, 8.68% and 3.61% for 120, 80 and 40 ppm concentrations compared to B30. Thus, combined GNP and DMC showed excellent potential for utilisation in diesel engine operation.