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With the enhancement in science and technology, necessity of complex shapes in manufacturing industries have become essential for more versatile applications. This leads to the demand for lightweight and durable materials for applications in aerospace, defense, automotive, as well as sports and thermal management. Wire electric discharge machining (WEDM) is an extensively utilized process that is used for the exact and indented shaped components of all materials that are electrically conductive. This technique is suitable in practically all industrial sectors owing to its widespread application. The present investigation explores WEDM for LM6/fly ash composites to optimize different process variables for attaining performance measures in terms of maximum material removal rate (MRR) and minimum surface roughness (SR). Taguchi’s L27 OA design of experiments, grey relational analysis, and analysis of variance (ANOVA) were employed to optimize SR and MRR. It has been noted from ANOVA that reinforcement (R) percentage and pulse on time are the most influential aspects for Grey Relational Grade (GRG) with their contributions of 28.22 and 18.18%, respectively. It is found that the best process variables for achieving the highest MRR and lowest SR simultaneously during the machining of the composite are gap voltage of 30 V, pulse on time of 10 µs, pulse off time of 2 µs, wire feed of 8 m/min, and R of 9%. The predicted GRG is 0.84, and the experimental GRG value is 0.86. The validation experiments at the optimized setting show close agreement between predicted and experimental values. The morphological study by optical microscopy revealed a homogenous distribution of reinforcement in the matrix which enhances the composite’s hardness and decreases the density.

Using a cutting-edge net-shape manufacturing technique called Additive Layer Manufacturing (ALM), highly complex components that are not achievable with conventional wrought and cast methods can be produced. As a result, the aerospace sector is paying closer attention to using this technology to fabricate superalloys based on nickel to develop the holistic gas turbine. Because of this, there is an increasing need for the mechanical characterisation of such material. Conventional mechanical testing is hampered by the limited availability of material that has been processed, especially given the large number of process factors that need to be assessed. Thus, the present study focuses on manufacturing CM247LC Ni-based superalloy with exceptional mechanical characteristics by laser powder bed fusion (L-PBF). This study evaluates the effect of input process variables such as laser power, scan speed, hatch distance and volumetric energy density on the mechanical performance of the LPBF CM247LC superalloy. The maximum value of as-built tensile strength obtained in the study is 997.81 MPa. Plotting Pearson's heatmap and the Feature importance (F-test) was used in the data analysis to examine the impact of input parameters on tensile strength. The accuracy of the tensile strength data classification by machine learning algorithms, such as k-nearest neighbours, Naïve Baiyes, Support vector machine, XGBoost, AdaBoost, Decision tree, Random forest, and logistic regression algorithms, was 92.5%, 83.75%, 83%, 85%, 87.5%, 90%, 91.25%, and 77.5%, respectively. [ABSTRACT FROM AUTHOR]

The research introduces an innovative method for creating a digital twin (DT) of heat energy storage and retrieval system (HESRS) for real-time monitoring and performance analysis. The HESRS, type of HVAC system, is evaluated based on parameters like stored heat energy, heat extraction via heat transfer fluid (HTF), and Phase Change Material (PCM) temperatures. Data from temperature sensors is sent to the cloud in real-time. A reduced-order model (ROM) analyses it on the cloud and sends results to an Android app. The DT is then simulated in augmented reality through our app, Twin-X, marking distinctive approach to digital twin development. [ABSTRACT FROM AUTHOR]

This paper proposes a convolutional neural network (CNN) model of the signal distribution control algorithm (SDCA) to maximize the dynamic vehicular traffic signal flow for each junction phase. The aim of the proposed algorithm is to determine the reward value and new state. It deconstructs the routing components of the current multi-directional queuing system (MDQS) architecture to identify optimal policies for every traffic scenario. Initially, the state value is divided into a function value and a parameter value. Combining these two scenarios updates the resulting optimized state value. Ultimately, an analogous criterion is developed for the current dataset. Next, the error or loss value for the present scenario is computed. Furthermore, utilizing the Deep Q-learning methodology with a quad agent enhances previous study discoveries. The recommended method outperforms all other traditional approaches in effectively optimizing traffic signal timing. [ABSTRACT FROM AUTHOR]

This article details the existing wearable assistive devices that could mimic a human's active range of motion and aid individuals in recovering from stroke. The survey has identified several risk factors associated with musculoskeletal pain, including physical factors such as engaging in high-intensity exercises, experiencing trauma, aging, dizziness, accidents, and damage from the regular wear and tear of daily activities. These physical risk factors impact vital body parts such as the cervical spine, spinal cord, ankle, elbow, and others, leading to dysfunction, a decrease in the range of motion, and diminished coordination ability, and also influencing the ability to perform the activities of daily living (ADL), such as speaking, breathing and other neurological responses. An individual with these musculoskeletal disorders requires therapies to regain and restore the natural movement. These therapies require an experienced physician to treat the patient, which makes the process expensive and unreliable because the physician might not repeat the same procedure accurately due to fatigue. These reasons motivated researchers to develop and control robotics-based wearable assistive devices for various musculoskeletal disorders, with economical and accessible solutions to aid, mimic, and reinstate the natural active range of motion. Recently, advancements in wearable sensor technologies have been explored in healthcare by integrating machine-learning (ML) and artificial intelligence (AI) techniques to analyze the data and predict the required setting for the user. This review provides a comprehensive discussion on the importance of personalized wearable devices in pre- and post-clinical settings and aids in the recovery process. [ABSTRACT FROM AUTHOR]

An engine bracket is one of the most critical components of the engine used for mounting and supporting the engine in the vehicles. Today, the automobile industry requires lightweight components, which will reduce the car's overall weight when fitted into the vehicle. Topology optimization is a technique with the help of which the surface of a component is optimized to get the required shape for having reduced weight. The weight is reduced by optimizing the material on the surface of the details. In this paper, the work done is the application of topology optimization on the surface of the engine bracket arm. Then the optimized model is tested computationally using realistic conditions. Bi-directional evolutionary structural optimization is used as a technique for topology optimization. With the help of the BESO method, the material optimization is done, and then the weights are compared with the original component. A new algorithm is developed using MATLAB codes. The sensitivity ratio is considered using the von Mises strength as a critical parameter for the BESO method for optimization. The optimized bracket model is then assembled with the hub of the component, and then the assembly is simulated for verification using standard conditions. A comparison of weight reduction is there using topology optimization.

The present design of a set of worm gears used in a soot blower produced by a certain manufacturer has an efficiency of 68.8%. A soot blower is one of the most critical components in industrial applications for removing the large amounts of soot generated by boilers and is required to be operational 24×7. The energy consumption of the soot blower depends on its working efficiency and ultimately the design of its set of worm gears. This paper focuses mainly on the design and analysis of available industrial worm-gear sets used in soot blowers. The theoretical, experimental, and finite-element analysis approaches are validated for the stability of the worm gear set under typical input conditions. This paper also describes an analytical design of experiments (DOE) approach to identify the most significant factor for performance (efficiency) improvement and suggests some design improvements for the worm gear set using the profile modification approach. These ensure the efficiency improvement of the current industrial design of the set of worm gears used in a soot blower. The analytical DOE approach helped identify that the number of worm wheel teeth (Z2) and gear module (m) are the two most significant factors affecting performance. Accordingly, based on the improved design, the final efficiency increased from 68.8% to 74.6% (~8.5% increment), resulting in lower power consumption during industrial application. [ABSTRACT FROM AUTHOR]

The piping system connected with the shipboard equipment may be subjected to excessive vibration due to harmonic base excitation produced by hydrodynamic force imposed on the propeller blades interacting with the hull and by other sources. Vibration design aspects for shipboard pipework are often ignored, which may cause catastrophic fatigue failures and, consequently, leakage and spillage in the sea environment. Without dedicated design codes, the integrity of shipboard equipment against this environment loading can be ensured by testing as per test standard MIL-STD-167-1A (2005). However, in many cases, testing is not feasible and economically viable. Hence, this study develops an FE-based vibration analysis methodology based on MIL-STD-167-1A, which can be a valuable tool to optimize the testing requirement without compromising the integrity of these piping systems. The simulated model dynamic properties are validated with experimental modal testing and Harmonic response analysis result confirm that a mitigating solution option can be verified by a FE based vibration analysis to mitigate the vibration problem. [ABSTRACT FROM AUTHOR]

Introduction: The demand for improved small arms ammunition has led to exploring advanced materials and manufacturing techniques. This research investigates the machining characteristics of CM and WNF alloy bullets, aiming to enhance ballistic performance and durability. Methods: Bullet profile-making trials were conducted to evaluate the impact of machining parameters such as cutting speed and feed. The study also considered variables including surface roughness, cutting temperature, and hardness, alongside a detailed morphological analysis, The evaluation utilized an orthogonal array and MCDM approach, incorporating the TOPSISmethod for decision-making processes. Results: The findings reveal that WNF alloy bullets exhibit 3.01% to 27.95% lower machining temperatures, 24.88%-61.85% reduced surface roughness, and 19.45%-34% higher microhardness compared to CM bullets. Moreover, CM bullets demonstrated higher machining temperatures, resulting in 47.53% increased tool flank wear. WNF bullets showed a 24.89% reduction in crater wear and a 38.23% decrease in compressive residual stress in bullet profiles, indicating superior machining performance. Discussion: The superior machining performance of WNF alloy bullets suggests their potential to improve the ballistic performance and durability of small arms ammunition. The reduced tool wear and favorable machining parameters highlight WNF alloy's advantages for military and defense applications. A ballistic impact analysis using a finite element method (FEM) model in Abaqus software further supports the potential of WNF alloy bullets, providing a solid foundation for future advancements in bullet manufacturing technologies. [ABSTRACT FROM AUTHOR]

Surface integrity is one of the key elements used to judge the quality of machined surfaces, and surface roughness is one such quality parameter that determines the pass level of the machined product. In the present study, AISI D2 steel was machined with electric discharge at different process parameters using Jatropha and EDM oil. Titanium dioxide (TiO2) nanopowder was added to the dielectric to improve surface integrity. Experiments were performed using the one variable at a time (OVAT) approach for EDM oil and Jatropha oil as dielectric media. From the experimental results, it was observed that response trends of surface roughness (SR) using Jatropha oil are similar to those of commercially available EDM oil, which proves that Jatropha oil is a technically and operationally feasible dielectric and can be efficiently replaced as dielectric fluid in the EDM process. The lowest value of S.R. (i.e., 4.5 microns) for EDM and Jatropha oil was achieved at current = 9 A, Ton = 30 μs, Toff = 12 μs, and Gap voltage = 50 V. As the values of current and pulse on time increase, the S.R. also increases. Current and pulse-on-time were the most significant parameters affecting S.R. Machine learning methods like linear regression, decision trees, and random forests were used to predict the surface roughness. Random forest modeling is highly accurate, with an R2 value of 0.89 and an MSE of 1.36% among all methods. Random forest models have better predictive capabilities and may be one of the best options for modeling complex EDM processes. [ABSTRACT FROM AUTHOR]

Utilizing Machine Learning (ML) to oversee the status of hobbing cutters aims to enhance the gear manufacturing process's effectiveness, output, and quality. Manufacturers can proactively enact measures to optimize tool performance and minimize downtime by conducting precise real-time assessments of hobbing cutter conditions. This proactive approach contributes to heightened product quality and decreased production costs. This study introduces an innovative condition monitoring system utilizing a Machine Learning approach. A Failure Mode and Effect Analysis (FMEA) were executed to gauge the severity of failures in hobbing cutters of Computer Numerical Control (CNC) Hobbing Machine, and the Risk Probability Number (RPN) was computed. This numerical value aids in prioritizing preventive measures by concentrating on failures with the most substantial potential impact. Failures with high RPN numbers were considered to implement the Machine Learning approach and artificial faults were induced in the hobbing cutter. Vibration signals (displacement, velocity, and acceleration) were then measured using a commercial high-capacity and high-frequency range Data Acquisition System (DAQ). The analysis covered operating parameters such as speed (ranging from 35 to 45 rpm), feed (ranging from 0.6 to 1 mm/rev), and depth of cut (6.8 mm). MATLAB code and script were employed to extract statistical features. These features were subsequently utilized to train seven algorithms (Decision Tree, Naive Bayes, Support Vector Machine (SVM), Efficient Linear, Kernel, Ensemble and Neural Network) as well as the application of Bayesian optimization for hyperparameter tuning and model evaluation were done. Amongst these algorithms, J48 Decision tree (DT) algorithm demonstrated impeccable accuracy, correctly classifying 100% of instances in the provided dataset. These algorithms stand out for their accuracy and efficiency in building, making them well-suited for this purpose. Based on ML model performance, it is recommended to employ J48 Decision Tree Model for the condition monitoring of a CNC hobbing cutter. The emerging confusion matrix was crucial in creating a condition monitoring system. This system can analyze statistical features extracted from vibration signals to assess the health of the cutter and classify it accordingly. The system alerts the operator when a hobbing cutter approaches a worn or damaged condition, enabling timely replacement before any issues arise. [ABSTRACT FROM AUTHOR]

Purpose. The present study aimed to improve the aqueous solubility, permeability, bioavailability, and nootropic potential of standardized Emblica officinalis extract (EOE) by developing a novel phytosomal formulation. Method. Emblica officinalis extract-loaded phytosomes (EOPs) were prepared using solvent evaporation. The EOP was prepared at different molar ratios of extract and phospholipid. Herein, the effects of phospholipid extract ratio (A), temperature (B), and reaction time (C) were systematically investigated on entrapment efficiency using Box-Behnken design. In vitro and in vivo characterizations of the optimized formulation were performed. Results. Optimized EOP formulation (89.90 ± 0.24 μg/ml) exhibited improved aqueous solubility than plain EOE (11.85 ± 0.25 μg/ml). The optimized formulation's particle size and Zeta potential were 198.4 ± 0.20 nm and −39.0 ± 0.40 mv. DSC and XRD studies confirmed the partial amorphization of EOE in phytosomes. Optimized formulation exhibited 69.82 ± 0.17% of EOE release at 12 h and followed zero-order release kinetics. Moreover, the phytosomal formulation of EOE exhibited its rationality with an improvement of bioavailability by 2.7 folds compared with pure EOE. Compared to EOE, EOP showed significantly ( p < 0.05 lower escape and transfer latencies on both days in MWMT and EPMT, indicating more effective memory-enhancing activity. Furthermore, EOP-treated rats exhibited improved acetylcholine (Ach) levels than EOE. Brain tissue concentrations measured following EOP oral administration (1.06 ± 0.04 μg/ml) were substantially greater (p < 0.05) than those following EOE (0.32 ± 0.07 μg/ml). The brain dopamine and serotonin concentration were found to be higher (16.27 ± 1.209 and 43.28 ± 1.550 ng/ml) in the EOP-treated group as compared to the pure extract-treated group (10.40 ± 1.185 and 32.79 ± 1.738 ng/ml). Conclusion. Improvement of aqueous solubility, permeability, dissolution, bioavailability, and narrower particle size distribution could facilitate enhancement in the nootropic potential of EOE phytosomal formulation. [ABSTRACT FROM AUTHOR]

This article provides a comprehensive overview of the performance evaluation of looped tube thermoacoustic power generators using numerical and experimental analysis. The study focuses on small-scale generators operating at atmospheric pressure and utilizing low-cost linear alternators. The analysis considers factors such as temperature variation, pressure fluctuation, volume flow rate, and acoustic power distribution. The results show that the generators produce maximum acoustic power at a frequency of 78 Hz, with an overall thermal to electric efficiency of approximately 8.3%. The article also includes references to other research papers and articles that cover various aspects of thermoacoustic engines and generators, providing valuable insights into the field. [Extracted from the article]

Introduction: This study presents a comprehensive design and analysis of a 300L steel fuel tank intended for heavy off-road vehicles. The design process integrates numerical simulations and experimental investigations to optimize the tank's performance and durability under various operating conditions. Methods: The design methodology involves CAD model optimization, numerical analysis setup, and experimental validation. CAD model optimization simplifies the tank geometry while retaining structural integrity. Numerical analysis setup includes defining boundary conditions, meshing strategies, and simulation parameters. Experimental validation entails testing the tank under dynamic loading conditions to assess its structural response. Results: Numerical simulations reveal insights into stress distribution, deformation behavior, and fluid dynamics within the tank. Experimental tests confirm the numerical predictions and provide valuable data for model validation. Key results include stress concentrations in critical areas, deformation patterns under different loading conditions, and fluid flow characteristics. Discussion: The integrated approach combining numerical simulations and experimental tests offers a comprehensive understanding of the fuel tank's behavior. Findings highlight areas for design improvement, such as reinforcement of stress-prone regions and optimization of fluid flow dynamics. The study contributes to enhancing the performance, reliability, and safety of fuel tanks for heavy off-road vehicles. [ABSTRACT FROM AUTHOR]

NAO brake friction materials with 4%, 5%, and 6% (w/v) sodium hydroxide treated hemp fiber reinforcement having 25% wt. fiber loading and fixed percentage of phenol formaldehyde resin content (20% wt.) along with other fillers have been studied and reported by the authors earlier. However, the effect of variations in the resin content on the tribological performance has been studied and reported in the present paper. Five variants were prepared with varying percentages of phenol formaldehyde resin from 12% wt. to 22% wt. with incremental steps of 2% wt, along with the optimum of 6% (w/v) sodium hydroxide treated hemp fibers and other fillers. The prepared test variants' tribological characterization was done using Taguchi's L25 orthogonal array on a pin-on-disc experimental setup, as per ASTM G99, at room temperature and compared with the best of the earlier studied friction composite. Fade and recovery tests of the best of the earlier studied and present ones were performed on a chase tribology tester per SAE J661 standards. The results revealed moderate coefficient of friction of 0.4496, lower wear rate of 0.57 gm, and better fade recovery for the HF25P20 variant compared to its counterparts studied here. [ABSTRACT FROM AUTHOR]

Nowadays, research has shown the emergence of the 3D printing method for printing a functionalized component. Graphene nanomaterial has an enormous conducting property that can compete with conducting materials like copper and silicon. This paper describes the electrical conductivity investigation of 3D-printed graphene nanomaterial in extrusion-based 3D printing methods. In extrusion, two different approaches of the 3D printing method were used to print the graphene-based structure: the fused deposition modeling (FDM) method and the direct ink writing (DIW) method. Both printing methods follow the two printing processes and select material forms. Selection of testing was made to analyze the characterization variations in the printed material, such as XRD, TGA, viscosity, Raman shift, and Scanning Electron Microscopy analyses, which shows the changes of effect in the conductivity due to various parameter differences in both the printing methods. A four-point probe technique was used to analyze the electrical conductivity of the two different methods. These analysis results prove that the characterization variations differ in the FDM and DIW printed models. [ABSTRACT FROM AUTHOR]

This research focuses on the relationship between the tensile strength of PLA material and several 3D printing parameters, such as infill density, layer height, print speed, and extrusion temperature, utilizing the Fused Deposition Modeling (FDM) method of Additive Manufacturing (AM). Tensile strength of the samples was determined in compliance with ASTM D638 standard, and the experiments were carried out according to a planned arrangement. Six distinct methods were used to optimize the tensile strength: Particle Swarm Optimization (PSO), Teaching Learning Based Optimization (TLBO), Genetic Algorithm (GA), Simulated Annealing (SA), and Cohort Intelligence (CI). Several runs of the optimization methods demonstrated their consistency in producing the same values of tensile strength, indicating their reliability. The optimization results showed that JAYA performed better than the other algorithms, resulting in a material with the maximum tensile strength of 55.475 N/mm². Validation experiments were carried out to confirm the efficacy of these algorithms. The results showed that the ideal input parameters produced tensile strength values that closely matched the anticipated values with a low percentage error. The benefits of applying these algorithms to improve the tensile strength of PLA materials for 3D printing are demonstrated by this study, which also offers insightful information about how to optimize FDM procedures. [ABSTRACT FROM AUTHOR]

A highly advanced thermo-electric machining technique called wire electrical discharge machining (WEDM) can effectively produce parts with varying hardness or complicated designs that have sharp edges and are very difficult to machine using standard machining procedures. This useful technology for the WEDM operation depends on the typical EDM sparking phenomena and makes use of the commonly used non-contact material removal approach. Since its inception, WEDM has developed from a simple approach for creating tools and grown to an outstanding option for creating micro-scale components having the greatest degree of dimensional precision and surface finish characteristics. The WEDM method has endured over time as an efficient and affordable machining alternative that can meet the stringent operating specifications enforced by rapid manufacturing cycles and increasing expense demands. The possibility of wire damage and bent, nevertheless, has severely hindered the process' maximum potential and decreased the precision as well as effectiveness of the WEDM process. The article examines the wide range of investigations that have been done; from the WEDM through the EDM process' spin-offs. It describes WEDM investigation that required variables optimization and an assessment of the many influences on machining efficiency and accuracy. Additionally, the research emphasizes adaptive monitoring and control of the process while examining the viability of multiple approaches to control for achieving the ideal machining parameters. Numerous industrial WEDM applications are described with the advancement of hybrid machining techniques. The paper's conclusion examines these advancements and identifies potential directions for subsequent WEDM research. The investigation on WEDM of metal matrix composites (MMCs) is also reviewed; along with the impacts of various cutting variables like wire feed rate (F), voltage (V), wire tension (WT), and dielectric flow rate on cutting processes outcomes like material removal rate (MRR), kerf width (Kw) and surface roughness (SR). In the present article, future directions for WEDM research were also suggested. [ABSTRACT FROM AUTHOR]

This experimental study investigated the abrasive wear behaviour of pure copper-based and multi-walled carbon nanotube (MWCNT) doped composites synthesized by the powder metallurgy technique. Composite structures were formed by reinforcing MWCNT at different ratios between 1% and 8% in 99.9% pure copper by powder metallurgy. The microstructures of the nanocomposite samples were analyzed by X-ray diffraction. Then, density and hardness measurements and abrasive wear tests were performed to determine their mechanical properties. The collected data were evaluated with scanning electron microscopy images. It has been determined that copper's nano-sized carbon reinforcement material has a dry lubricant effect up to a specific ratio, reducing wear losses. On the contrary, wear losses increase as the MWCNT reinforcement ratio increases between 4% and 8%. The best results in lowering wear losses were obtained from the sample with 1% MWCNT reinforcement. Depending on the increase in the amount of nanomaterial reinforcement in the composite structure, it was observed that pore formation enlarges with reinforcement agglomeration. It was concluded that the dense porosity in the composite structure neglects the lubricating properties of the MWCNT reinforcement material and increases the wear losses by having a negative effect. [ABSTRACT FROM AUTHOR]

In the last few years, due to the superior mechanical qualities of Additive Manufacturing (AM) AlSi10Mg alloy to those of traditional casting process AlSi10Mg alloys, the application of AM technology has significantly increased. The ballistic impact research has a wide range of uses, notably in the mining, construction, spacecraft and defence sectors. This work focuses on analyzing the behavior of different projectile nose shapes on the AlSi10Mg alloy fabricated by AM. There are several projectile nose forms to consider, including blunt, hemispherical, conical, and ogive shapes. The impact of various projectile shapes on the ballistic limit of the additively created AlSi10Mg alloy is carefully examined in this study. All numerical simulations were carried out using LS-DYNA software, and the Johnson-Cook material and damage model were considered to assess the ballistic resistance behavior. The ballistic limit for various projectile shapes is computed using the Jonas-Lambert model, which describes the connection between residual velocity and starting projectile velocity. The results showed that, the ogive-shaped Projectile offers the highest ballistic limit, and the blunt projectile shows the lowest ballistic limit for a 5 mm thin target plate. The ballistic impact phenomenon showed plugging failure for the blunt nose projectile, the formation of plug and small fragments were observed in the case of hemispherical nose projectile, fragmenting failure is observed with radial necking in the case of conical nose projectile and petals are formed at the impacted zone in ogive nose shape projectile. Moreover, the ballistic limit of AM AlSi10Mg alloy was slightly higher compared to the ballistic limit of the die-cast AlSi10Mg alloy for the 7.62 mm AP bullet (core). Therefore, AM AlSi10Mg alloy may have equal or good ballistic properties compared to die-cast AlSi10Mg alloy. [ABSTRACT FROM AUTHOR]

The findings of the experimental study into optimizing the heat transfer rate of a PCM-based heat sink for high-power LEDs are presented in this work. The study investigated five heat sink types, with and without PCM. The LED case and junction temperatures, LED module temperatures, heat storage and release rate analyses, analyses of three types of cyclic operation modes, luminous flux, and heat sink thermal resistance were all examined independently. The results indicated that the PCM-based LED heat sink had improved thermal performance. The LED junction temperature of the PCM-equipped E-20 heat sink is nine degrees Celsius lower at 10 W than that of the heat sink without PCM. Furthermore, the E-20 heat sink with PCM extends the LED module's critical lifespan. As a bonus, the E-20 with PCM had a 38.19 percent lower thermal resistance at 10 W than the E-20 without PCM. According to these results, the heat sink E-20 emits 715 lm at 10 W when operated without a phase-change material (PCM). With the same input power, the luminous flux of an E-20 equipped with a heat sink and a phase-change material (PCM) is 750 lm, a gain of 4.7%. Finally, clearly recommend the heat E-20 sink with PCM suitable for high-power LED thermal management system. [ABSTRACT FROM AUTHOR]

The abrasive characteristics of LM6 alloys are difficult to machine, so designing a technology that allows for effective machining is essential. This paper aims to evaluate the effect of process variables, namely feed rate, spindle speed and drill material, towards the responses like Thrust force, Surface roughness and burr height when drilling of LM6 alloy. LM6 aluminium alloy was fabricated by the stir casting process. Experiments were conducted using L9 orthogonal array in a Vertical Machining Centre coupled with a dynamometer for measuring thrust force. Surface roughness was found by Surface roughness tester and burr height was measured using Vision Measuring System. The findings show that the created model can accurately estimate the thrust force (TF), surface roughness (SR) and burr height (BH) in LM6 alloy drilling within the parameters examined.

This study performed a steady-state numerical analysis to understand the temperature in different heat sink configurations for LED applications. Seven heat sink configurations named R, H-6, H-8, H-10, C, C3, and C3E3 were considered. Parameters like input power, number of fins, heat sink configuration were varied, and their influence on LED temperature distribution, heat sink thermal resistance and thermal interface material temperature were studied. The results showed that the temperature distribution of the H-6 heat sink decreased by 46.30% compared with the Cheat sink for an input power of 16 W. The result of the H-6 heat sink shows that the heat sink thermal resistance was decreased by 73.91% compared with the Cheat sink at 16 W. The lowest interface material temperature of 54.11 °C was achieved by the H-6 heat sink when the input power was used 16 W. The H-6 heat sink exhibited better performance due to more surface area with several fins than other heat sinks.

The materials used in engineering have seen a significant transformation in the contemporary world. Numerous composites are employed to overcome these problems because conventional materials are unable to meet the needs of current applications. For quite some time, professional engineers and researchers have been captivated by the problem of choosing the best machining parameters for new composite materials. Wire electrical discharge machining is a popular unconventional machining process that is often used for making complex shapes. Numerous process parameters influence the WEDM process. Thus, to achieve affordable and high-quality machining, the right set of process parameters must be provided. Finding the wire cut EDM optimized settings for the fabricated LM5/ZrO2/Gr composite is the main aim of this research. The chosen input parameters are the wire feed, pulse on and pulse off times, the gap voltage, and the reinforcing percentage. In this study, LM5/ZrO2/Gr composites were made from stir casting with 6-weight percent ZrO2 as the reinforcement and varying graphite percentages of 2, 3, and 4 wt%. Then they were machined in WEDM using L27 OA to seek the best parameters for machining by adjusting the input parameters. The findings were analysed by means of grey relation analysis (GRA) to achieve the supreme material removal rate (MRR), lowest surface roughness (SR), and a smaller kerf width (Kw) simultaneously. GRA determines the impact of the machining variables on the standard characteristics and tests the impact of the machining parameters. Confirmation experiments were performed finally to acquire the best findings. The experimental findings and GRA show that the ideal process conditions for achieving the highest grey relational grade (GRG) are 6% ZrO2 with 2% graphite reinforcement, a wire feed of 6 m/min, a pulse off time (Toff) of 40 µs, a pulse on time (Ton) of 110 µs, and a gap voltage (GV) of 20 V. The gap voltage (22.87%) has the greatest impact on the GRG according to analysis of variance (ANOVA), subsequent to the interaction between the pulse on time and the gap voltage (16.73%), pulse on time (15.28%), and pulse off time (14.42%). The predicted value of the GRG is 0.679; however, the experimental GRG value is 0.672. The values are well-aligned between the expected and the experimental results. The error is only 3.29%, which is really little. Finally, mathematical models were created for each response. [ABSTRACT FROM AUTHOR]

Titanium–silicon oxynitride sulfite (TiSiNOS) is a coating material that is deposited on H13 tool steel using the scalable pulsed power plasma (S3P) technique, where the coating deposition is a hybrid process consisting of a mix of sputtering and arc evaporation. The maximum hardness and coating thickness measured on TiSINOS-coated H13 tool steel are 38 GPa and 3.1 µm, respectively. After implementing the L9 orthogonal array, nine samples were coated with TiSiNOS, which consists of the same properties. The nine coated and uncoated samples were tested separately based on the L9 pattern to achieve accurate results. The experimental results indicate that the wear loss can be reduced by minimizing the load at 25 N even if the temperature rises to 250 °C. SEM analysis reveals that the uncoated sample has higher wear loss when compared with the coated samples, and material pullout is visible from the uncoated sample. Based on these results, it can be concluded that TiSINOS coating in H13 tool steel helps in improving the tool life during the drilling process. Taguchi was used in this research to evaluate the wear behavior. The data observed from the experiment were analyzed using the Minitab tool. The most crucial factor is to determine the effects of process parameters. A higher temperature influenced the wear behavior of the tool. [ABSTRACT FROM AUTHOR]

This study was designed to examine the effects of a trimethylolpropane trioleate (TMPTO)-based lubricant on thrust force and torque under the high-speed drilling of Al-6061 as an effective environmentally friendly cutting fluid. The tribological performance of three lubricant blends was evaluated based on ASTM standards. TMPTO base oil, notably enhances load-carrying capacity under extreme pressure conditions, with a seizer load of 7848 N. The best-performing oil was further optimized using a Taguchi-based design experiment to investigate the effect of different additive concentrations on thrust force and torque under actual contact conditions. Experiments were conducted using three critical machining parameters: additive concentration, spindle speed, and feed rate. The results of the ANOVA analysis reveal that spindle speed contributes most substantially (62.99%) to torque, with feed rate (23.72%) and additive concentration (7.74%) also showing significant impacts. On the other hand, thrust force is primarily influenced by feed rate (73.52%), followed by spindle speed (16.82%), and additive concentration (6.28%). Furthermore, a machine learning model was developed to predict and compare a few significant aspects of high-speed drilling machinability, including thrust force and torque. Three different error metrics were utilized in order to assess the performance of the predicted values, namely the coefficient of determination (R2), mean absolute percentage error (MAPE) and mean square error (MSE), which are all based on the coefficient of determination. Compared to other models, decision tree produces more accurate prediction values for cutting forces. The present study provides a novel approach for evaluating the most promising biodegradable lube oils and predicting cutting forces by formulating a perfect blend. [ABSTRACT FROM AUTHOR]

Aluminum matrix composites (AMCs) are largely used in defense, maritime, and space applications for their excellent properties. LM5 is used where very high resistance to corrosion from seawater or marine atmospheres is required, for equipment used for the manufacture of foodstuffs, cooking utensils, and chemical plants. Zirconia is preferred over other reinforcements as it shows comparatively great refractory properties, high scratch resistance, and thermal shock resistance. Utilizing the stir casting technique, an attempt was made to produce AMCs of LM5 aluminum alloy strengthened with ZrO2. The weight percentage of ZrO2 was changed to 0%, 3%, 6%, and 9%. The specimens were prepared and tested as per ASTM standards to find the density, micro and macro hardness, impact, tensile, and compressive strength. The micrographs and SEM images confirm the uniform distribution of ZrO2 particles in the aluminum matrix. LM5/9%ZrO2 AMC has the highest density value of 2.83 g/cm3 and LM5/3%ZrO2 has the least porosity of 2.55%. LM5/9% ZrO2 has the highest hardness values of 78 VHN and 72 HRE. LM5/6% ZrO2 AMC has the highest tensile strength of 220 MPa, compressive strength of 296 MPa, and toughness of 12 J. LM5/6% ZrO2 AMCs may be used for many structural applications. [ABSTRACT FROM AUTHOR]

Fiber-reinforced additive manufacturing components have been used in various industrial applications in recent years, including in the production of aerospace, automobile, and biomedical components. Compared to conventional methods, additive manufacturing (AM) methods can be used to obtainin lighter parts with superior mechanical properties with lower setup costs and the ability to design more complex parts. Additionally, the fabrication of onyx composites using the conventional method can result in delamination, which is a significant issue during composite machining. To address these shortcomings, the fabrication of onyx composites via additive manufacturing with the Mark forged 3D-composite printer was considered. Machinability tests were conducted using abrasive water jet machining (AWJM) with various drilling diameters, traverse speeds, and abrasive mass flow rates. These parameters were optimized using Taguchi analysis and then validated using the Genetic algorithm (GA) and the Moth Flame Optimization algorithm (MFO). The surface morphology (Dmax) and the roughness of the drilled holes were determined using a vision measuring machine with 2D software (MITUTOYO v5.0) and a contact-type surface roughness tester. Confirmation testing demonstrated that the predicted values werenearly identical to the experimental standards. During the drilling of an onyx polymer composite, regression models, genetic algorithms and the Moth-Flame Optimization algorithm were used to estimate the response surface of delamination damage and surface roughness. [ABSTRACT FROM AUTHOR]

Fused deposition modeling (FDM) is utilized to fabricate continuous fiber‐reinforced thermoplastic composites (CFRTPCs) and can be considered an alternative to conventional processes. In present study, the specimens are 3D printed in Markforged Mark Two composite 3D printer by considering Onyx as matrix material and fiberglass as reinforcing material. Thermal gravimetric analysis (TGA) and Fourier transform infrared spectroscopy (FTIR) of Onyx and fiberglass materials are done to investigate their thermal stability and composition. The effect of infill pattern and fiber orientation on tensile and drop impact properties are examined. The TGA results show that the initial decomposition in Onyx is higher compared to fiberglass due to more evaporation of moisture content in Onyx. The FTIR analysis confirmed that the spectrum for both materials is same within the range of wave number from 4000 to 1500 cm−1. The tensile test results represent that the specimen with triangular infill pattern and 0°/90° fiber orientation resulted in maximum tensile strength of 148.01 MPa and the drop impact test results showed that the triangular infill pattern with 0°/90° fiber orientation absorbs maximum impact energy which is 14.90% and 8.98% higher compared to honeycomb and rectangular pattern respectively. Further, the fracture behavior study is carried out based on the optical images of fractured specimens. [ABSTRACT FROM AUTHOR]

Heating of the electrode at the work–piece interface zone in spot welding, leading to degradation of the tip, becomes a significant concern in the high-volume production automotive industry. By recognizing the interrelationship between hardness, wear resistance, and thermal conductivity, the authors emphasize the importance of selecting electrode materials with suitable alloying elements desirable for achieving optimal performance in spot welding applications. This paper studies the wear behaviour of three types of spot-welding electrode materials under dry sliding contact conditions. A pin-on-disc tester was used to investigate Cu–Cd, Cu–Be and Cu–Cr–Zr alloys' wear behaviour under variable parametric load, temperature and time conditions. Taguchi L9 orthogonal array was used to investigate the significance of parameters and their effect on linear wear. The ranking of the parameters was performed using SN ratio analysis. The wear mechanism was also studied using SEM analysis. Abrasive wear was observed at lower loads, while adhesion, oxidation and plastic deformation were observed under high-load and -temperature conditions. This study suggests an alternative to the presently used electrolytic tough pitch (ETP) Cu electrode involving equally good wear-resistance material. However, a detailed investigation on the effect of plasma on the metallurgical characteristics of selected material is suggested. [ABSTRACT FROM AUTHOR]

Incremental sheet forming (ISF) is an emerging technology that has shown great potential in forming customized three-dimensional (3D) parts without the use of product-specific dies. The forming force is reduced in ISF due to the localized nature of deformation and successive forming. Forming force plays an important role in modeling the process accurately, so it needs to be evaluated accurately. Some attempts have been made earlier to calculate the forming force; however, they are mostly limited to empirical formulae for evaluating the average forming force and its different components. The current work presents a mathematical model for force prediction during ISF in a 3D polar coordinate system. The model can be used to predict forces for axis-symmetric cones of different wall angles and also for incremental hole flanging. Axial force component, resultant force in the r-θ plane, and total force have been calculated using the developed mathematical model appearing at different forming depths. The cone with the same geometrical parameters and experimental conditions was modeled and simulated on ABAQUS, and finally, experiments were carried out using a six-axis industrial robot. The mathematical model can be used to calculate forces for any wall angle, but for comparison purposes, a 45° wall angle cone has been used for analytical, numerical, and experimental validation. The total force calculated from the mathematical model had a very high level of accuracy with the force measured experimentally, and the maximum error was 4.25%. The result obtained from the FEA model also had a good level of accuracy for calculating total force, and the maximum error was 4.89%. [ABSTRACT FROM AUTHOR]

The hygroscopic properties of natural fibers tend to degrade the mechanical properties of composite materials. It is essential to investigate the influence of water absorption behavior on the mechanical properties of hybrid composite materials. In this study, hybrid laminate materials consisting of two different reinforcement materials, i.e., Kevlar fibers and jute fibers in the same layer, are considered. Hybrid laminates that have four different weaving patterns: plain weave, basket weave, twill weave, and the satin weave, are tested for their water absorption characteristics. The jute fiber is a naturally extracted fiber that is subjected to chemical treatment. A comparison of mechanical properties before and after treatment of the jute fibers is carried out. Mechanical properties such as tensile strength, compressive strength, flexural strength, impact strength, and hardness are tested. It is found that the mechanical properties improved after the treatment of the jute fibers. The twill weave pattern exhibited negligible defects compared to its counterparts. Chemical treatment of the jute fibers enabled less water being absorbed into the hybrid laminate materials. Mechanical properties improved after using chemically treated jute fibers as the reinforcement material in the hybrid laminate materials. It is concluded that the twill weave pattern and chemical treatment of the natural fibers improved the mechanical properties of the hybrid laminate materials. [ABSTRACT FROM AUTHOR]

The goal of this study was to provide a new, easy, accurate, cost-effective, exact, sensitive, specific, robust, and rugged method for quantifying Epigallocatechin 3 gallate in wistar rat plasma using reverse phase high-performance chromatography (RP-HPLC). The stationary phase was a Zorbax SB C18 5µ (4.6*150) mm column, while the mobile phase was water with 0.1 percent formic acid (A) and acetonitrile (ACN) with 0.08 percent formic acid (B). The experiment was conducted at 30°C with a flow rate of 1.0 ml/min with PDA detectors at 274 nm. With an r2 of 0.9999, the method was shown to be linear in the concentration range of 0.2-25 µg/ml. At the same retention time (Rt) of epigallocatechin 3 gallate, no interference of co-eluting peaks of endogenous chemicals from the biological matrix was found. The intraday and interday precision RSD (%) was found to be within acceptable limits (less than 2%). The overall mean recovery percentage was determined to be 96.92 %. The LOD and LOQ were determined to be 0.0682 ± 0.0011 µg/ml and 0.205 ± 0.004 µg/ml, respectively. In short-term and long-term stability tests, auto sampler, bench-top, and freeze-thaw stability tests were found to be stable. The developed approach reported was determined to be well within acceptable limits. As a result, in the future, this method can be successfully employed in clinical laboratories to estimate epigallocatechin 3 gallate alone or in conjunction with other analytes or markers in pharmacokinetic, bioequivalence, and therapeutic drug monitoring. [ABSTRACT FROM AUTHOR]

Plant fibers over the years have succeeded in generating interest among researchers about their use. This is mainly due to several ecological legislations put in place by nations to counter the rise in global warming levels. Although plant fiber-based polymer composites are penetrating various domains, concern regarding their suitability and challenges related to manufacturing techniques needs to be addressed. This review attempts to discuss various aspects of plant fibers, their processing with polymer, and methods to improve the fib-matrix interaction. The article also presents an insight into different 3D printing techniques such as fused deposition modeling, laminated object manufacturing, stereolithography, selective laser sintering, and inkjet printer for processing fiber-based polymer composites. The use of technologically advanced 4D printing of fiber-polymer composites is also discussed. Challenges and futuristic opportunities associated with recent works on 3D printing techniques are analyzed toward the end. The paper is structured in the following manner: the first part focuses on natural fibers with their constituents, their processing, and manufacturing techniques with polymers, while the second part of the paper discusses various 3D printing techniques with their challenges and opportunities. [ABSTRACT FROM AUTHOR]

The design and development of a photovoltaic thermal (PVT) collector were developed in this study, and electrical and electrical thermal efficiency were assessed. To improve system performance, two types of coolants were employed, liquid and liquid-based MnO nanofluid. Flow rates ranging from 1 to 4 liters per minute (LPM) for the interval of 1.0 LPM were employed, together with a 0.1% concentration of manganese oxide (MnO) nanofluid. Various parametric investigations, including electrical power generation, glazing surface temperature, electrical efficiency, and electrical thermal efficiency, were carried out on testing days, which were clear and sunny. Outdoor studies for the aforementioned nanofluids and liquids were carried out at volume flow rates ranging from 1 to 4 LPM, which can be compared for reference to a freestanding PV system. The research of two efficiency levels, electrical and electrical thermal, revealed that MnO water nanofluid provides better photovoltaic energy conversion than water nanofluid and stand-alone PV systems. In this study, three different domains were examined: stand-alone PV, liquid-based PVT collector, and liquid-based MnO nanofluids. The stand-alone PV system achieved a lower performance, the liquid-based MnO performed better, and the liquid-based PVT achieved an intermediate level. [ABSTRACT FROM AUTHOR]

Lightweight aluminum composite is a class of foam material that finds many applications. These properties make it suitable for many industries, such as the transportation, aerospace and sports industries. In the present work, closed-cell foams of an Al-Si12CuFe alloy and its composite are developed by a stir casting process. The optimization of the foaming temperature for the alloy and composite foams was conducted in terms of the ligament and node size of the alloy and also the volatility of the zircon with the melt, to provide strength to the cell walls. CaCO3 as a blowing agent was homogeneously distributed in the molten metal without adding any thickener to develop the metal foam. The decomposition rate of CaCO3 is temperature-dependent, which is attributed to the formation of gas bubbles in the molten alloy. Cell structure, such as cell size and cell wall thickness, is controlled by manufacturing process parameters, and both the physical and mechanical properties are dependent on the foam cell structure, with cell size being the major variable. The results show that the increase in cell wall thickness with higher temperature leads to a decrease in cell size. By adding the zircon to the melt, the cell size of the composite foam first increases, and then the thickening of the wall occurs as the temperature is increased. The uniform distribution of the blowing agent in molten metal helps in the formation of a uniform cell structure. In this work, a comparative structural study of alloy foam and composite foam is presented regarding cell size, cell shape and foam stability at different temperatures. [ABSTRACT FROM AUTHOR]