Cold thermal energy storage using phase changing materials is being researched to find freezing and thawing points. The use of inorganic hydrated salts, a type of phase changing material (PCM) used in cold energy storage systems without the use of existing renewable energy systems, allows for a longer cooling effect and saves energy. A high volumetric storage density and relatively high thermal conductivity make hydrated salts suitable materials for thermal energy storage. They can be used only as inorganic mixtures or else they can also be used as eutectic mixtures, which involve mixtures of inorganic–inorganic salts or simply a combination of two or more inorganic salts. This research deals with eutectic mixtures, which are 4% KNO3 + 96% H2O, 4% NaHCO3 + 96% H2O, and 2% KNO3 + 2% NaHCO3 + 96% H2O. Three different novel eutectic mixtures were examined and found a suitable mixture for a cold thermal energy system. An efficient phase change approach involving 2% KNO3 + 2% NaHCO3 + 96% H2O may result in stable phase change behavior and moderate temperature change, increasing versatility.

In the welding of materials, metal inert gas (MIG), gas tungsten arc welding (GTAW), and tungsten inert gas (TIG), are typical welding technologies. Welding titanium alloys involves several challenges due to their susceptibility to oxidation phenomena. Shielding arrangements of a relatively new type are tested to overcome this contamination. A proposed design and configurations are used to join commercially pure titanium sheets with variations in ARC, GMAW, and GTAW process parameters along with travel speed and welding current. Variations were made to process parameters toward full penetration butt joints in experimental bead-on plate (BoP) trials with a sheet thickness of 5 mm. Macrostructure images were subsequently captured. Analysing the microstructure of the heat-affected zone, base metal, and fusion zone is done using optical microscopy. TIG welding is 7.39

Rising demand for fuel will now pose a significant risk for global pollution levels in various applications. The biodiesel of Karanja oil methyl ester (KOME), an alternative to diesel fuel, is a potential source of unspent fuel in India. Karanja oil contains fatty acid esters, which are environmentally friendly fuel. This experiment aimed to research low heat rejection using Karanja oil methyl ester with retarded injection timing diesel-fueled. The piston, cylinder walls, and engine valves were coated with a 0.5 mm thickness of partially stabilized zirconium (PSZ) without affecting the engine compression ratio. Experiments in the engine with and without coating were carried out using Karanja oil methyl ester. The results showed that Karanja oil methyl ester's specific fuel consumption a retarded timing (RT) with coated engine decreased by 7.4 percent and the brake thermal efficiency improved by 5.5 percent compared to the conventional engine with diesel fuel. CO and UBHC emissions on the LHR with RT engine are lower, whereas the zirconia coating has increased NOx emissions.

Porous ceramics offer excellent mechanical, abrasion, chemical, and thermal characteristics. In addition, these porous network ceramic structures have a less density, mass, and thermal conductivity. In this work an attempt has been made to develop a porous ceramic material based on pure aluminium added with fly ash based cenosphere added with suitable binder bentonite. Bubble type melt gas injection method is adopted for production of porous ceramic foams. Aluminium powder percentages are varied for 60, 65, 70 and 75 wt.% and the porous structure obtained is assessed using macrostructure evaluation. Also, the percentage porosity of the fabricated ceramic foam is evaluated as per ASTM guidelines. It is found that with higher aluminium percentage the percentage porosity obtained higher with a dendritic like structure.

Internet of Things (IoT) become an emergent platform in wireless technologies in design of electric vehicles (EVs) and hybrid electric vehicles (HEVs). Dynamic energy storage systems, batteries can be damaged due to overcharging/discharging and their mass penetration deeply affects the grid. For circumventing the likelihood of damage, the EVs and HEVs require an accurate state of charge (SOC) estimation approach for improving the lifetime and safety. An efficient battery management system (BMS) remains a challenging problem in HEVs, commonly utilized to indicate the battery state-of-charge (SOC). As over-charge and over-discharge outcome from predictable damage to the batteries, precise SOC estimation model is needed for HEVs. In this aspect, this study presents an improved wild horse optimizer with deep learning enabled battery management system (IWHODL-BMS) for IoT based HEVs. The presented IWHODL-BMS employs attention based bidirectional long short-term memory (ABiGRU) approach to accurately estimate SOC in HEVs. For enhancing SOC estimation performance of the ABiGRU technique, the IWHO algorithm is utilized as hyperparameter optimizer. The application of the ABiGRU model results in simpler and accurate representation of the input. A comprehensive simulation result portrayed the enhanced outcomes of the IWHODL-BMS model over the other methods under varying measures.

The consumption of a significant quantity of energy in buildings has been linked to the emergence of environmental problems that can have unfavourable effects on people. The prediction of energy consumption is widely regarded as an effective method for the conservation of energy and the improvement of decision-making processes for the purpose of lowering energy use. When it comes to the generation of positive results in prediction tasks, the Machine Learning (ML) technique can be considered the most appropriate and applicable strategy. This article presents a Modified Wild Horse Optimization with Deep Learning approach for Energy Consumption Prediction (MWHODL-ECP) model in residential buildings. The MWHODL-ECP method that has been provided places an emphasis on providing an up-to-date and precise forecast of the amount of energy that residential buildings consume. The MWHODL-ECP algorithm goes through several phases of data preprocessing in order to achieve this goal. These steps include merging and cleaning the data, converting and normalising the data, and converting the data. A model known as deep belief network (DBN) is used here for the purpose of predicting energy consumption. In the end, the MWHO algorithm is utilised for the hyperparameter tuning procedure. The results of the experiments demonstrated that the MWHODL-ECP approach is superior to other existing DL models in terms of its performance. The MWHODL-ECP model has improved its performance, with effective prediction results of MSE-1.10, RMSE-1.05, MAE-0.41, R-squared-96.28, and Training time-1.23.

Towards environmental sustainability, recycling and effective usage of sea wastes are encouraged to develop novel materials in engineering applications by sustainable waste management. In this research, impact of seashell (SS) particles (75 μm) of varying weight fractions (0, 3, 6, 9, 12,15 and 18%) reinforced in nylon-6 matrix is investigated experimentally by studying its thermal properties viz., vicat softening temperature (VST), heat deflection temperature (HDT), coefficient of linear thermal expansion (CLTE), and melt flow index (MFI) and thermo-mechanical properties by thermo-gravimetric analysis (TGA), dynamic mechanical analysis (DMA), and differential scanning calorimetry (DSC) according to ASTM guidelines. The polymer matrix composite (PMC) is prepared by blending the pellets of nylon-6 and seashell particles with the help of twin-screw extruder and fabricated into the required shape and size in an injection moulding machine. Outcomes of the experimental investigation show that CLTE decreases with increase in SS content, whereas VST and HDT deflection temperature increases along with the weight % of SSs due to the reduction in plasticity of the thermoplastic until 15% addition. This makes it more resistance to load and deflection along with heat resistivity whereas MFI decreases with addition of SSs in nylon-6 matrix. From DMA analysis it is observed that with inclusion of SSs the glass transition temperature tends to increase along with loss and storage modulus. Thermal and thermo-mechanical features tend to improve until 15% addition of SS in nylon-6 matrix. With further addition, the properties tend to be lowered because of poor adhesion of SSs with Nylon-6.

A study into pool boiling heat transfer with nanofluids particularly aluminum silicate and cerium (IV) oxide was used to prepare nanofluids. A review of existing nanofluid implementations done previously in multiple literature and research journals was taken into consideration while determining their effects as nanoparticles in necessary base fluids. The nanofluids were prepared with two-step method by dispersing Al2SiO5 and CeO2 nanopowders in water and were analyzed at base temperatures of 50-75°C and peak flux readings taken at saturation temperature. An inference between these and surface modifications due to settlement of nanoparticles on heater surface was studied by SEM imaging, and dispersion was studied with TEM imaging. The volume concentrations of Al2SiO5 and CeO2 nanofluids are varied from 0.1 % ≤ φ ≤ 0.3 % . Readings taken at temperatures varied by 5°C between 50°C to 75°C and at 100°C. The improvement of q ″ for Al2SiO5/H2O and CeO2/H2O nanofluids is about 120.5 ± 0.6 % in PHF over water as base fluids for 0.3% volume concentration solutions.

In this work we investigated the friction wear of a thermoplastic polymer (nylon-6) reinforced with particles of seashell. Seashells are made of calcium carbonate in the mineral form of calcite or aragonite, which makes them one of the most robust materials known. A twin-screw extruder was used to blend the seashell particles (SPs) and nylon-6, and an injection molding machine was used to fabricate the composite. Various proportions of SPs (12%, 15%, and 18%, by weight) were added to the nylon-6. We studied the wear of the polymer composites as per the standard ASTM G99, focusing on the loss of material due to wear, the friction coefficient, and the interface temperature. We used a response surface methodology (RSM) based Box–Behnken method (BBD) for our experimental design, and multiobjective analyses were performed incorporating desirability analysis. Our results show the following: the interface temperature was highly influenced by rotational speed (41.61%); the reinforcement with SPs (%) significantly (35.71%) affected the loss of material due to wear; and, the coefficient of friction (CoF) was significantly affected by rotational speed (41.48%) and reinforcement with SPs (18.18% w/w). A novel metaheuristic algorithm (Grey Wolf Optimizer) was used to constrain our optimizations, and the results showed that with CoF = 0.3 and an interface temperature of 25 °C as constraints, the loss due to wear was 35.77 μm for 15.09% w/w reinforcement with SPs, but at CoF = 0.3 and an interface temperature of 30 °C, the loss due to wear was 28.99 μm for 18% w/w reinforcement with SP.

Recent researchers developed unique materials by the method of electroless coating for the various industrial applications. Electroless coating is a simple way to produce various metals with high impact and enhanced mechanical properties. In this article an experimental investigation on optimizing characteristics parameters of electroless coating of Nickel-Phosphorous and Silicon carbide nano coating on aluminium alloy LM25. A comprehensive experimental characterization of electroless nickel-phosphorous coating and Silicon carbide nano coating on aluminium alloy LM25 under specific coating conditions is reported. At present nickel -phosphorous and Silicon carbide was coated over aluminium alloy LM25 using electroless coating method. The surfactant SLS was added into solution before EN deposition. The stabilizer thiourea (1 ppm) was added into the bath when the reaction is stable. Characterization parameters such as pH and Temperature were varied and the corresponding coating thickness, rate of deposition, surface roughness and microhardness were to be measured. The level of pH and Temperature varied and their influence on coating process was studied. An observed value of pH in the range of 4-5, 6-7, 8-9 and observed temperature was diversely at different values such as 70 degrees C, 85 degrees C, and 90 degrees C. The result showed that the coating thickness and microhardness was maximum when pH was 6-7, temperature was 85 degrees C. Scanning electron microscope was imaged a surface morphology of aluminium alloy LM25. (c) 2020 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Conference on Mechanical, Electronics and Computer Engineering 2020: Materials Science.

Artificial Intelligence (AI) covers many areas related to mechanical, electrical, psychology and philosophy. GSM IoT is the new method and idea in a simple application of fire detection. In our project, we are using IR sensor to detect a fire and it sends the information to a microcontroller, which is programed based on a fuzzy logic algorithm that helps to detect the fire and moves the nozzle head of the Fire Fighting Robot. The stepper motor is used for a 360 degree clockwise and anticlockwise rotation. The D.C motor controls the valve opens of the nozzle. The fuzzy logic algorithm is helps to detect the fire and to turn the nozzle in the direction of fire.

In this work, influence of seashell particulate reinforcement on nylon 66 polymer matrix composite is investigated experimentally by determining the thermo-mechanical properties of the composite viz., Differential scanning calorimetry (DSC), Dynamic Mechanical Analysis (DMA) and Thermal Gravimetric Analysis (TGA). Seashell particulates of size 75 mu m size is reinforced in the matrix of nylon 66, a thermoplastic polymer, to improve its properties by forming a polymer matrix composite. From the seashores of Marakkanam, Tamil Nadu, India, seashells were collected, which are dried in sunlight to remove the moisture and is cleaned properly to remove the sludge present. Seashell are grounded to powder through mechanical ball milling method and the required size is obtained from the sieve machine. Various proportions of seashells such as: 3, 6 and 9% by weight is added to the required amount of nylon 66, mixed and compounded in twin screw extruder and specimens of required dimension is obtained in injection moulding machine. As per ASTM standards, thermo-mechanical properties were studied and reported.