Computational and Experimental Methods in Mechanical Engineering

The application of Lamb waves is gaining attention in the scientific community for diagnosing defects in the thin-walled structures. The lamb waves have also been extensively employed in the aerospace, civil, and mechanical industries for detection of damage especially in the thin-walled plate or cylindrical structures. In the same direction, we have explored the application of Lamb waves in crack detection of chicken’s egg. Eggshell is primarily composed of calcium carbonate (CaCO3) stabilized by a protein matrix. This protein matrix provides mechanical strength to the CaCO3 layer. The eggshell damage while laying and transportation is a major problem faced by the poultry industry. Eggshell damage also results in major economic loss as the cracked eggs must be discarded while sorting and selling. The cracked eggshells have been identified manually which is a laborious and time-consuming process. Thus, for rapid and efficient detection of eggshell cracks various digital imaging-based algorithms, X-ray and gamma, optical transmission, nuclear magnetic resonance (NMR) and electrical properties-based techniques have been developed. However, the application of Lamb waves for the detection of eggshell crack has not been explored till now. This is the first study that reports the application of Lamb waves for detecting cracks in the eggshell. This technique is economical compared to other available techniques. We have carried out finite element (FE) modelling and simulations on the chicken eggshells. In order to capture the wave passing through the shell, we have calculated the minimum element size requirement for a given FE mesh and the time increments required to capture the wave in the shell. The simulation results show the accurate detection of eggshell cracks. This technique has a great potential to be employed at an industrial scale for sorting of the cracked and intact eggs.

In small towns and cities, we need a lightweight vehicle to travel from one place to another. Every time we use a vehicle that has complex component assembly which uses a lot more amount of fuel because of the overall weight, and also because of complex steering systems, we have to put up some extra steering effort to give direction to our vehicle. Using a simple steering mechanism/system results in overall weight reduction, low manufacturing cost and low maintenance cost for the user. In this paper, the focus has been put on the simple design of the steering system based on Ackerman steering mechanism considering the factors that are related to the overall weight of the vehicle, driver’s safety, easy maintenance and low cost.

In the new era, the development of composite materials and alloy is very demanding for the fulfilment of the present demand of industries and society. The thermal analysis of composite materials and alloy is requiring its thermal properties like thermal conductivity, specific heat, etc. before their uses. The main focus of this research work is to study the effect of different parameters on the thermal conductivity of composite material and alloy based upon the experimental and analytical data available in the literature. Furthermore, a different method of finding the thermal conductivity of composite materials and alloy like finite element method, finite volume method, statistical model, non-conventional laser flash technique, machine learning method, spatially varying relaxation parameter lattice Boltzman method using melting process, equivalent inclusion method, hot plate method cut bar method, etc. also has been presented in this work. The machine learning method is a very fast, accurate and efficient method for predicting the conductivity of composites and alloy. From the intensive studies, it was found that temperature, particle size, density of materials and composition are generally affecting the thermal conductivity of composite materials. Furthermore, it was found that conductivity of composites material increases with an increase in the composition of filler material and a decrease in particle size of the filler.

There are various ways of enhancing the thermal efficiency of an LPG gas stove like variation of gas pressure, varying loading weight or loading height. This paper deals with the improvement of the thermal efficiency of LPG gas stoves by varying the loading height. Loading height is defined as the distance between the burner top and the bottom surface of the vessel when the vessel is kept on the stove. The experiment was performed as prescribed by the Bureau of Indian Standard (BIS). It was found that with an increase in the loading height there was an increase in thermal efficiency up to the optimum loading height of 17.5 mm at which maximum thermal efficiency was achieved. Further increase in the loading height resulted in a decrease in the thermal efficiency. A mathematical analysis was carried, and a correlation is developed which is compared with the experimental results. The maximum efficiency achieved was comparable to the value predicted from correlation. Uncertainty analysis was also computed for the efficiency obtained.

Functionally graded materials are tailor-made materials. In the present work, the theoretical study of Al–Cu functionally graded material through gradation laws is investigated. The properties like density, Young’s modulus, shear modulus, specific heat and thermal conductivity are taken into consideration. The gradation laws such as power law, exponential law and sigmoid law gradation laws are applied to evaluate the behavior of these parameters at varying index numbers from one to three. It has been concluded that increasing the value of power law index (n), variation in all the effective material properties (mechanical and physical) of Al–Cu FGM, changing from linear into a polynomial way. Al (material at the bottom surface) properties are becoming more predominant up-to a larger range of z/h ratio with increasing value of power law index (n). At the value of n = 1, power law and Sigmoid law both are predicting the same results which are simply the rule of mixture.

The thermodynamic analysis to improve the energetic performance of N2O transcritical cycle using dedicated mechanical subcooling is done for three different evaporator temperatures 5, −5 and −30 °C. The analysis is done for the environment temperature ranging from 30 to 40 °C. Propane is used as a refrigerant in mechanical subcooling cycle. It has been found that if combined cycle is used, the maximum increments in COP and specific cooling capacity (SCC) are 22% and 30%, respectively. It has also been found that using mechanical subcooling cycle, the reduction in optimum heat rejection pressure is higher at lower evaporator temperature, i.e. −30 °C and power consumption ratio is higher at higher evaporator temperature, i.e. 5 °C. Further, COP increment using different refrigerants in mechanical subcooling cycle has been presented, where no significant differences have been found. The increment indicates that this cycle is more efficient if the environment temperature is more than 30 °C.

The usage of solid polymer electrolytes is gaining popularity because of their safe and good performance in various batteries, especially in lithium-ion batteries. However, all these electrolytes have some limitations such as lower ionic conductivity at room temperature and deprived mechanical properties. In the present research, the electrolytes are prepared with PVDF, PEO and LATP blends to address all the mentioned issues. During the preparation of electrolytes, the contents of PEO are varied from 5 to 20% with PVDF. To improve the electrochemical properties of electrolyte, 10% (to the weight of PVDF and PEO mixture) of LATP is added to the electrolyte. The effect of variation in the proportion of PVDF and PEO contents on the electrical and mechanical properties of electrolytes is analysed in the present research. The addition of PEO in the electrolyte improves the ionic conductivity of the solid electrolyte. However, the yield strength of the electrolyte is decreased with an increase in PEO proportion. The detailed results are provided in this research article.

The present study aims to provide a single platform for various researches on the mechanical properties of polymer composites reinforced with the banana fiber. The study also aims to spread awareness among future researchers, academicians, and practitioners regarding the potential use of the banana fiber to prepare the reinforced hybrid composites as a suitable material for various engineering and industrial applications.

Wire and arc additive manufacturing (WAAM) technology is quite impressive and investigated in the last 30 years of development. It fascinates the scientists and manufacturers as it can produce densely deposited metal parts, and the objects produced are almost similar to the desired one. It is a process that includes the deposition of material layer-by-layer. It is gaining importance at a very fast pace as manufacturing industries find it cost- and time-efficient. Here, in this review paper, the mechanism of WAAM techniques, its type, and various components produced by WAAM have been discussed. It also includes the discussion on different surface deposit properties and microstructural properties of the products produced by WAAM. At last, the industrial application and future scope of this technique are also explored.

Bi1-x Lax FeO3 ceramics with (x = 0.0, 0.025, 0.050, 0.075, 0.100) is prepared using citrate precursor-based sol–gel method. X-ray diffraction patterns reveal phase purity of all samples with rhombohedral crystal structure indexed to the R3c space group. FE-SEM micrographs confirm the average crystallite size to be ~57 nm. FTIR spectrum justifies structural distortion in BiFeO3 crystal lattice with La3+ increasing composition. EDAX analysis confirms proper substitution of La3+ at bismuth site. Remanent magnetization (Mr) ranges from 5 × 10–3 to 9 × 10–3 emu/g, whereas Coercivity (Hc) ranges from 252 to 875 Oersted with La3+ increasing content. Moreover, doping of La3+ at the bismuth site causes an appreciable reduction in electrical leakages, resulting in clear observation of the ferroelectric polarization loop. Electrical polarization loops convert to a typical concave nature from an oval pattern with increasing La3+ ions, yielding remanence polarization (Pr) and coercive polarization (Pc) of the order 0.15 μC/cm2 and 7.5 kV/cm, respectively.

Aluminium metal matrix composites have picked up significance in different industries due to their great mechanical properties. Aluminium metal matrix composites are favoured in the fields of aviation, military, car, marine and other homegrown applications. The various reinforcements with Aluminium metal matrix composites by powder metallurgy procedure brings about improved mechanical properties, for example, ultimate tensile strength, compressive strength, hardness, wear rate. Powder metallurgy is an ideal technique for manufacture for MMCs on account of the capacity to create close to net shapes and minimal material waste related with this cycle. In this paper, an endeavour has been made to unite a portion of the parts of mechanical properties of Aluminium MMCs manufactured by utilizing Powder Metallurgy Technique. This paper is also focused on the comparative analysis of different parameters on the AMCs.

Structural health monitoring (SHM) is an inspection study that deals with the diagnosis and prognosis of damages/faults in structures. SHM plays a crucial role in diagnosing the metallic and composite-based thin/shell structure. In this paper, critical analysis and discussion are provided on the SHM methods focusing on state of the art Lamb waves. The sensors and actuators, especially piezoelectric sensors, are explained from the viewpoint of health monitoring on thin structures. A tabular survey of the findings from the literature and existing lacunas are reported for the last 5 research years. It becomes evident from the research work that SHM methods with piezoelectric material-based sensors and actuators are more pronounced techniques in comparison to optic sensors, electrical resistance, electromagnetic techniques, and capacitive methods.

Carbon-emission reduction is one of the great challenges emitted by fossil fuels during power generation. This can be mitigated at a large scale by using solar photovoltaic technology, which is one of the unmatched electrical energy generation techniques with the help of solar energy. Energy crises are increasing day by day as the demand for electrical energy is increasing, and hence to meet the global demand, we need to expand the capacity of PV generation at a large scale. The increased capacity of the solar photovoltaic system may vary from few megawatts (MWs) to few kilowatts (KWs) depending upon the types of level of generation. A traditional generating plant emits carbon and to eliminate this carbon emission, solar PV penetration in the power system can be done at a large scale. Since solar energy is a daily phenomenon and due to this uncertainty in PV power generation, electrical energy storage (EES) systems need to be installed to enhance system capacity and performance. Due to advanced technological development in the electrical storage system, such as Li-ion batteries, lead acid, and nickel–cadmium batteries, has given increasing energy sector participants by providing a cost-effective approach, quality improvement, and energy management. This paper focuses on the PV system penetration at a large scale to the existing grid system and a complete and comprehensive overview of the electrical storage system. Forecasting of new technologies and recent development in EES has been discussed. The current scenario and basic building block of the PV solar system have also been focused. Different gaps in recent work have been identified and indicated about the future development of EES for large-scale PV systems.

The automotive chassis work to support the body and various parts of the vehicle. Additionally, it needs to withstand the stun, contort, vibration, and different anxieties caused because of unexpected braking, speeding up, stunning street condition, radiating power while cornering, and powers initiated by its segments. The undercarriage goes about as the foundation of a substantial vehicle which conveys the most extreme burden for all planned working conditions. This paper depicts the plan and examination of weighty vehicle frames as the prime goal of any car business in the present quick evolving world. In the current paper, the relevant data of a current substantial vehicle suspension supplanting materials of high explicit load with lower thickness materials without decreasing inflexibility and solidness. Supplanting of steel with aluminum, magnesium, composites are taken for displaying. Planning utilizing PC helped plan programming Catia and investigation by exposed to the indistinguishable burden as that of a frame. The mathematical outcomes are approved with expository figuring thinking about the pressure dissemination and distribution utilizing the ANSYS programming.

Gas sensors have drawn the researchers’ community’s attention for a few decades due to their numerous applications in different areas of environmental monitoring, biomedical devices, and pharma industries, etc. Normally gas sensing research includes polymers, metal-oxide-based semiconducting materials, porous silicon, etc. The performance of gas sensors is characterized by considering various scientific parameters, such as its sensitivity, lowest detection value, response time, recovery time, selectivity, and working temperature. Polymers are known for their sensitive thermal, electrical, mechanical, and dielectric properties. Due to such characteristics, they have gained a wide interest in theoretical research as well as practical applications in sensor technology and devices. This paper reveals a wide research review about the gas sensor structure as a sensing device in the field of the sensor. In the end, the current status, future perspectives as well as advantages of particular polymer-based sensors are summarized.

In this paper, two-dimensional numerical analysis of airflow over an airfoil has been done. Profile of airfoil has been generated from a fabricated prototype, and the analysis is carried out using computational fluid dynamics software in ANSYS 14.0 workspace. An in-built standard $$k - \varepsilon$$ k - ε model has been used for simulation work and the results show good aerodynamic properties of the airfoil with 0.18 coefficients of lift and a lift to drag ratio as 8.38 at an air speed of 44 m/s at 5-degree angle of attack.

A tunable optical filter at the second transmission window containing a superconductor/dielectric one-dimensional ternary photonic crystal is designed using the TMM method. The thermal tenability of the structure is controlled by an external temperature of the superconductor Yttrium Barium Copper Oxide (YBCO). The defect layer of the YBCO superconductor plays an important role in designing an optical filter within a bandgap of the structure. The designed structure can be used as a tunable optical filter at the second transmission window in optical fiber communication.

A singular boundary value problem arises in the conduction of heat through a solid and having other important applications is solved using a novel spline method. The removal of the singularity is done before applying a cubic B-spline and then a B-spline with a free parameter. The numerical examples show that the results have a very close agreement with exact solutions.

In any organization the ultimate result for growing its wealth depends upon how wealthy the organization's environment is. Though the main objective of any organization is profit maximization but in further stages of stability and growth, wealth becomes the ultimate objective. No doubt, if interpersonal relations between employer and employee are good, the financial productivity would be maximum. This concept will be better explained with the help emotional intelligence in context with financial outcome. The main objective of this paper is to study the factors of emotional intelligence which are responsible for affecting financial productivity of an organization from the previous studies. The Library research approach is being used to carry this study. It has been observed from the literature review that not only technical skills are important to grow for an organization but the emotional ability of people to connect with their peer group is more crucial. The purpose of the study is to bring previous research on Emotional Intelligence from the past with the current models and explanations in this context. Through this study, we are trying to look for the prospects and trials with which the financial effectiveness through emotional intelligence has been increased through various factors. These factors will be discussed further in detail in order to provide the viewpoint and expected outcome. As the study is conceptual and is being carried out from the previous studies, its critical and crucial aspects would also be examined.

Covered composites have different preferences over customary materials, for example, high explicit solidness and lightweight. The significant disadvantage is a shortcoming of boundaries among contiguous films, known as the de-lamination phenomenon. Because of de-lamination, a disappointment for the structure of composite can be seen because of the impacts of bury laminar burdens developed, that is once overlapped composites are exposed to outrageous temperatures. If the unforeseen difference in material properties of the covered composite structure is anticipated these issues can be decreased. along with specific bearings in a controllable manner, the individual material organization differs consistently practically reviewed material (FGM) is that sort of material. Consequently, this article presents the limited component displaying and examination of practically reviewed (FG) shell structures under various stacking, for example, mechanical and warm. Moreover, the introduction of investigation of free vibration of structure of FG circular shell. Further, various kinds of shells are considered to contemplate the impacts of significant boundaries on the reactions of FG shell structures. The reactions were acquired for standardized shells of unadulterated metal (EN 31 steel) shells and FG Functionally graded shells which are contrasted. Besides, both modular and static investigations are done to decide the characteristic frequencies, miss happening, strain, longitudinal pressure, and circumferential pressure, individually.

Wind, solar, fuel cell, small hydro, etc., are emerging technologies for renewable energy and can be built in the future as feasible electricity generation options. This paper introduces the load frequency control (LFC) in the presence of renewable energy resources. The study considers Wind turbine generator (WTG), Solar thermal power system (STPS), Photovoltaic (PV), Diesel source (DEPS), Fuel cell (FC), Battery storage system (BESS), Flywheel (FWES), Ultra capacitor (UC) and Aqua electrolyzer (AE), for sudden load/generation shifts, or both, the power system frequency deviates. The addition of a renewable system also results in a difficult task for an efficient controller design to be realized. With random load variance, the complexity to design an efficient and optimal control scheme is further enhanced. In this study, as an LFC control scheme, a PID controller is used. Two evolutionary approaches named as Big Bang Big Crunch (BBBC) and Harmony Search (HS) have been used to obtain optimal parameters. The performance of the control scheme has been checked two area and three area thermal-hydro system in the presence of other generation and energy storage sources. A comparative assessment of various quantities has been carried out on the basis of different time-domain parameters.

Wear of a material is one of the most undesirable processes experienced in practical applications. It results in energy loss, material degradation and life-shortening of machine components. This study aims to investigate the behavior of wear rate as a function of different operating parameters. The experiments were conducted on reciprocating tribometer, with three different tribopairs, of ball-on-disc configuration. The 52,100 chromium steel ball was allowed to slide with gun metal, mild-steel and EN-31 steel discs under different conditions. The wear rate for the specimens for each test was calculated by weight loss method. The effect of time, sliding distance and material hardness on the wear rate was examined there off. The Power Law and ANN models were developed for the estimation of wear rate. The model outputs were compared with the observed experimental results. The accuracy of the models was assessed using statistical parameters viz, coefficient of determination (R2), mean absolute percentage error (MAPE) and mean square error (MSE). It was observed that ANN model was more accurate compared to power law. Further, ANOVA analysis, with 5% p-value, was performed to enunciate the dominant factor affecting the wear rate. It was concluded that the load was the dominant factor influencing the wear rate and was succeeded by the velocity and hardness.

The absorption and fluorescence spectra of 3-methyl 7-hydroxyl Coumarin (C4) dye in presence of divalent metal ions (Ni+2, Co+2and Sn+2) were investigated. The fluorescence quenching of dye C4 molecule is found to be of second-order and second-order fluorescence quenching rate constant varies in order of Ni+2 > Co+2 > Sn+2 in methanol. The Stern Volmer Plots show that the quenching efficiency increases in Ni+2 < Co+2 < Sn+2. These results are explained based on the paramagnetic and diamagnetic behavior of the said ions.

This paper aims to improve the output voltage of solar panels by using graphene. The objective of this work is to analyze the absorption coefficient for improvisation in the efficiency of graphene. Various parameters viz. current density, absorption coefficient, wavelength of sun spectrum, Fermi and Dirac point level, and carrier generation rate have been computed and analyzed. The chosen parameters and their characteristics can demonstrate the necessity of solar energy by using graphene. GaAs is used as substrate and graphene layers are used to make junction and gate contact. The obtained graphs indicate that the power conversion efficiency of the solar panel is increased from 10.69 to 11.5%.

Wind, solar, fuel cell, small hydro, etc., are emerging technologies for renewable energy and can be built in the future as feasible electricity generation options. This paper introduces the load frequency control (LFC) model in the presence of renewable energy resources for a hybrid system. The study considers hybrid generation system comprising Wind turbine generator (WTG), Solar thermal power system (STPS), Photovoltaic (PV), Diesel source (DEPS), Fuel cell (FC), Battery storage system (BESS), Flywheel (FWES), Ultra-capacitor (UC) and Aqua electrolyzer (AE). For sudden load/generation shifts, or both, the power system frequency deviates. The addition of a renewable system also results in a difficult task for an efficient controller design to be realized. In this study, as an LFC control scheme, a PID controller is used. Two evolutionary approaches named as Big bang big crunch (BBBC) and Harmony Search (HS) have been used to obtain optimal parameters. The performance of the control scheme has been checked in two area and three area thermal-hydro system in the presence of other generation and energy storage sources. A comparative assessment of various quantities like frequency deviation, generation change, etc., has been carried out on the basis of different time-domain parameters.

One of the most deadly diseases in humans is brain tumor. For clinicians, MRI scan plays a key role in diagnosing and treating tumor. For brain tumor diagnosis, surgical approaches are usually suggested. But the radiologist's analysis of the medical image is time-consuming and also accuracy totally relies upon their skill. Now, Deep learning-based models have gained considerable interest in the diagnosis and treatment of diseases in medical field. As the medical images are limited, so it is a daunting task to train CNN from start and to implement deep learning. In this paper, we develop an automatic brain tumor detection method based on the pre-trained convolutional neural network architectures such as VGG-16, VGG-19, InceptionV3, ResNet50, ResNet101 and EfficientNetB1. The test accuracy achieved with VGG16 and ResNet101 gives highest performance accuracy among all other pretrained network.

Structuring items for recyclability is driven by ecological and monetary objectives. A few Design for Assembly (DFA) rules and boundaries can be used to check the recyclability plans. These lists can be utilized for near examination of the recyclability of various items. This helps the designers in settling on structure decisions identified with the item's finish of life. In the present research work, the boundaries will be explored from the existing DFA time gauge tables. The aftereffects of the examination showed the recyclability of the item, as characterized by set up recyclability metrics. A contextual analysis is performed to decide whether DFA boundaries could be used to decide product/part recyclability. A TODIM approach is applied to evaluate the recyclability of a tractor’s engine component based on the data obtained from “X” company. Furthermore, TODIM results were examined using MATLAB software. This exploration investigates how designers can utilize the (DFA) boundaries to foresee the recyclability list of an item. The recyclability list will be created utilizing the standards of plan for dismantling and material recyclability. The examination prompted the advancement of a method that an expert could use to decide item recyclability during the reasonable plan period of the fabrication process.

Face recognition has a large extent of applications from individual recognizable proof and reconnaissance to electronics showcasing and publicizing for chosen clients. There are various advances in facial recognition, for example, pre-processing, feature extraction, and grouping, where feature extraction and grouping are utilized to acquire the greatest precision. In this paper, diverse feature extraction methods, for example, A.A.M, A.S.M, template-based, Gabor-features, and a few are basically surveyed. Aside from these, the various kinds of neural classification systems, for example, backpropagation, convolutional, radial-basis-function, and so on in the space of face recognition, are investigated. The method and calculations created in the present writing are examined, and it is uncovered that every system is one of a kind and has ideal execution. This assessment further makes a relative examination of these frameworks reliant on their focal points and imperatives.

In this era of automation, our lives are surrounded by machines, be it a mobile phone or an elevator. We humans become careless when it comes to the maintenance of the machine. From the customer’s perspective, until an elevator is not working, nobody tends to care. This carelessness, in the long run, can result in loss of human life as well as financial losses. Elevators require maintenance and safety. To overcome both, the machine requires timely maintenance, and it can be executed with the precise product vision with the help of predictive maintenance. It not only predicts future failure but also pinpoints the issues in complex machinery and gives better results in terms of preventive maintenance. The conventional predictive maintenance machine learning techniques are established on feature engineering. It is the manual formation of precise features using domain proficiency and similar methodologies. Due to this, models are hard to reuse because feature engineering is specific to the problem structure and the data available, which can vary from one place to the other. Deep learning methodologies provide better results due to the extraction of new deep features from the dataset compared with the existing features. This work reviews the extant literature as well as showcases the implementation of random forest classifiers on the open-sourced dataset. In our model, an average accuracy of 91.50% was obtained. The dataset consisted of sensor data, which were recorded on the basis of maintenance actions being taken.

Groundwater is one of the most significant assets for giving water for all purposes but due to new trends of living, it is seriously misused for mechanical and homegrown use. In India, groundwater is a basic asset of water, which represents practically 85% of drinking water supplies [1]. The quality and amount of groundwater are being debased at a high rate predominantly because of increment in populace, urbanization, unnecessary abuse and lacking contamination control measures. Groundwater recharge is a hydrologic cycle where water descends from surface toward ground and after getting filtered through various soil media, meets the groundwater. This cycle typically happens in the vadose zone underneath plant roots and is frequently communicated as a motion of the water table surface. Energization happens both normally (through the water cycle) and through anthropogenic cycles (i.e., ‘counterfeit groundwater revive’), where water and additionally recycled water are directed to the sub-processes. These exercises can bring about loss of dirt, decreased water penetration, improved surface overflow and decrease in energization. The utilization of groundwater, particularly for water system, may likewise bring down the water table [2]. This study is to provide an efficient arrangement for rejuvenating the waste and polluted water to be used to improve the groundwater table. The study provides an efficient way to effectively remove unwanted particles present in the surface water, which can be further used for various other activities. The experimental study used here is to provide a practical and natural state of water pollution and the efficiency level of the artificial filter.

In this paper, a computational technique to generate the equation of coupler point for a prescribed 6-bar, 1-DOF Watt-I mechanism has been described. All the dimensional parameters of the prescribed mechanism, including link length along with orientation, are known. The modeling of the mechanism find out the successive crank rotational positions and, therefore, helps determine the intermediate coordinates of the coupler curve. By applying the mathematical concept of Lagrange’s polynomial, the required equation of the coupler curve is generated. The results obtained are supported by graphical plotting, verifying and demonstrating the computational technique for the prescribed 6-bar mechanism. This concept of generating a coupler curve equation is helpful in the analysis of any prescribed mechanism. Moreover, it helps to establish a relationship between prescribed dimensional parameters and desired performance of the mechanism.

Automated Guided Vehicle (AGV) is the material handling equipment that is utilized broadly in a maximum manufacturing company nowadays as it gives more flexibility to the system. The fundamental perception of AGV includes driverless and battery-powered vehicles with programming abilities for path selection and locating. They are equipped to navigate a flexible guide-path network, which might be simply changed and extended. This project may be concentrating on model, unloading and loading mechanism for AGV have been required to define specific criteria, which is automatic operated, lightweight and capable of transporting acrylic. This unloading and loading system worked utilizing ball screw as a development system and suction cup with a vacuum pump as adhering instrument. The outline and fundamental material to manufacture this AGV model would utilize aluminum to decrease the AGV weight. The AGV application in a real-world application is supported human and decreasing price in repetitive movement transportation actions. This manuscript suggests a survey on the control and design of AGV frameworks. We locate many key-related problems incorporating guide-path design, vehicle scheduling, assessing the number of vehicles, battery management, conflict determination, idle-vehicle positioning, and vehicle routing. Furthermore, we suggest a decision system for the design and execution of AGV frameworks, and propose few fruitful study directions. It will be designed for an importantly less price and exorbitant efficiency. The expenditure of the overall build is Rs. 90,000/- which is cost worthy.

The current study deals with the self-balancing two-wheeler; those vehicles cannot be staying in adjusting condition with no outer support. This assertion is relevant in each condition when it is very still or gradually moving. It includes an arrangement dependent upon gyroscopic component to settle 2-wheeled vehicles (such as bicycles, bike, mopeds and so forth) in each condition (it is possible that they are very still or moving). This idea likewise can be visualizing fabricating 2-wheeler based vehicles. Adjustment of a two vehicle assumes a huge part inside the muddled transportation. Whenever twist is applied to relate degree hub conventional to the turn hub, causing the gyro to strategy, a moment is made a couple of third pivot, symmetrical to each the twist and turn tomahawks. Since the vehicle slants from vertical, a precession affectation twist is applied to the gyro get together and subsequently the contradicting pivoting component response second can will in general gets back the vehicle in its position. The key arrangement is that movement of the gyro comparative with the body is effectively controlled to concoct dependability in vehicle.

In today’s era, mobile communication is the fastest-growing application in the field of wireless communication. In mobile communication received signal strength of radio waves at the receiver end plays an important role in network planning. When the radio waves travel from the transmitter to receivers end through the wireless channel, it has to face many challenges due to varying environment conditions or due to the presence of some obstacles, such as high-rise buildings, some vegetation, water body, etc. All these factors may affect the received signal strength of these radio waves. So for proper mobile network planning, it is required to have complete knowledge of how these parameters effects the received signal strength. So keeping this aspect in mind, this research work was focused on studying the variation in received signal strength for GSM signal with respect to four input parameters, that is, varying atmospheric temperature, Relative Humidity, Air quality index (particulate matter 2.5) and the distance from the base station and optimization of received signal strength was carried out by using response surface methodology.

An axial-flow compressor (AFC) will be the flow that enters the compressor in the axial direction and exits from the axial direction and in the gas turbine. The AFC compresses its attempting liquid by initial accelerating the liquid and then dispersing it to acquire a pressure expansion. Presently examination and developmental deliberations in the region of AFC for gas turbine application have been intended to enhancing its operating range without sacrificing effectiveness. An increment in aspect ratio is noticed to have an adverse impact on the execution of single-stage flow compressors. In this manuscript, AFC is planned and simulated in 3D designing software Pro/E. The current patterns get changed on varying aspect ratios. The current work utilized chromium steel, which could be substituted by nickel and titanium alloy. Full compressor methods with steel, nickel and titanium alloy are used for structural testing to validate compressor strength using finite element analysis using software Ansys. CFD examination is also being complete to define fluid performance in ANSYS Fluent.

Facial emotion recognition is a challenging task to capture and analyze. This paper presents an intelligent approach to detect different facial expressions of a person. In this context, a noval deep learning vgg 19 convolutional neural network architecture is used. Seven different emotions (anger, disgust, fear, happiness, sadness, surprise, and neutral) are considered to recognize emotions. The FER 2013 dataset contains 35,887 different images with these emotions. Results were obtained by using various activation functions. A comparative study of various activation functions has been done.

There are a lot of carbon emissions from cement which demands the usage of other alternatives as its replacement. Research is undoubtedly conveying crazy on the usage from claiming waste items to cement. Likewise, a reinstatement of characteristic sand. Because of that unreasonable utilization for waterway sand Likewise fine aggravator, the availability of the fine aggregate has become scanty. So, it demands the search for other alternative replacements for fine aggregates and cement additives that enhance the properties of fresh and hardened concrete like durability, strength, etc. In our study, we are going to experiment on the effects on mechanical assets of material by moderate replacement of cement by feldspar. Since Quartz is one of the greatest plentiful materials available on earth’s crust and being highly siliceous, these materials are being employed as additives for cement and fine aggregate. This study mainly concentrates on the assets of toughened concrete properties, which is the compressive strength of concrete. Here, cement is partially replaced using feldspar up to 25% at regular intervals of 5%. In addition to that, the river sand is completely replaced with quartz sand as fine aggregate. The above materials are being tested for M40 grade of concrete.

The requirements for more efficient and easily modifiable techniques have provoked the fast advancement in the domain of robotics. The improvement of canny robots prompts the capacity of them to turn into an administrator profoundly proficient and ready to adjust to a wide scope of issues. In any case, notwithstanding the few automated arrangements accessible, most of the current modern robots do not utilize the Robotic Operative System (ROS) and have restrictions as far as self-sufficiently right mistakes during their assignments. Controlling a robotic arm for applications such as object segmentation with the utilization of vision sensors would require vigorous picture processing and calculation to perceive and distinguish the object when using an image processing heavy approach, while a more traditional approach relies on sensors and partial automation in most cases. This paper is coordinated toward compiling the important computer vision techniques for pick and place operation along with the underlying factors that make them better than traditional techniques.

In the past years, so many developments and innovations are made to increase the performance of the welding machine by reducing the power consumption, cost, labor skills, and many more. In a row, the MIG welding process is one of the welding processes that increase a material’s welding properties at the same consumption of power and resources. A-MIG welding is wildly used to optimize the parameter of MIG welding. A steady flow welding powerfully delivers electrical vitality, directed over the bend through a segment of exceptionally ionized gas and metal fumes known as plasma. Metal idle gas (MIG) welding is most regularly used to welder thick segments of tempered steel and non-ferrous metals, such as aluminum, magnesium, and copper compounds. Three sorts of oxides, Fe2O3, SiO2, and MgCO3, were utilized to research the impact of initiating transition helped gas metal bend welding (GMAW) on weld dab math, precise twisting, and mechanical properties. The most noteworthy impact on the inward structure factor was knowledge about an instance of MnO dynamic transition, which diminished the inside structure factor by 20%. If there should arise an occurrence of the outside structure factor, the applied SiO2 dynamic transition caused the greatest increment, which is 37%. In the hardness dispersion and the microstructure of the joints, including the weld metal and the heath-influenced zone, no critical contrasts were experienced contrasted with the example welded with no transition material.

In this paper, computational determination of heat transfer features of TiO and CuO2, mixed with aqua, as a base fluid for heat exchanger application, is conducted using ANSYS® Fluent software. The parameters like Nusselt number, heat transfer and skin friction coefficients are dealt with in detail. The computed results were then compared with the results of Al2O3/water mixture. The results revealed that with an increased flow rate, the value of Nusselt number, and consequently the rate of heat transfer, improves significantly by using TiO and CuO2 particles in aqua. However, the fluid’s inlet temperature has insignificant effect on the radiator performance. The TiO concentration in water showed highest rate of heat transfer compared to Al2O3 and CuO2. Furthermore, CuO2 exhibited highest skin friction coefficient when compared with Al2O3 and TiO. In addition, Al2O3 executed least Nusselt number and skin friction coefficient compared to CuO2. The rate of heat transfer gets enhanced by about 4–5 times by using TiO and CuO2 in place of Al2O3 under all operating conditions. On the other hand, the heat transfer characteristics of TiO and CuO2 do not vary much and are in close match with each other.

This investigation is based on the practical experience reported in the case history, research papers and reported cases of automobile burning at the police and fire stations. Since the fire outbreak in automobiles creates harmful effects to the automobile owner and as well as to other people, it is necessary to detect the fire in the automobile and develop some device for the instant control of the fire.

The steam evaporator may shut holder where water or different liquids are warmed under tension and the steam discharged by the kettle is utilized for different warming applications. The fundamental contemplations in planning a kettle for a specific application are structure and warm investigation, structure for creation, physical measurements and cost. In this postulation, the progression of steam in the steam kettle (without diverters and with redirectors) is displayed utilizing the CREO parametric plan programming. The postulation will concentrate on warm and CFD examination with various info speeds (20, 30, 40 and 50 m/s). In this theory, CFD investigation decides the warmth move coefficient, the warmth move rate, the figure stream rate and the weight drop. Warm inspection to choose the temperature movement, the warmth stream for the two models of steam kettle without diverters and steam evaporator with redirectors. Discover which model is the best. 3D displaying in the parametric CREO programming and dissects acted in ANSYS.

In vehicles, zero-emission production and wheels propelled with their own battery energy is possible only through electric vehicles. The long-term maintenance cost is very low as well as the lower center of gravity gives better cornering and turning stability. These advantages have influenced and have made electric vehicles as a new generation transport both in India and internationally in the automobile engineering sector. From the time EVs came into picture, there have been a lot of modifications in their design and some major components like battery pack and motor. In spite of these advancements and advantages, EVs are still not much popular in the automobile market, if we look at their growth, there is an increase but it is still less as compared to S.I and C.I engine automobiles. If we look at the reason behind that, there are some major setbacks in EVs like charging time, mileage, support of electrical components like headlights and air conditioners while driving. It’s very essential to look at the issues in EVs and their causes and to find out the ways how to overcome them with few modifications keeping the pocket friendly cost in mind. A number of companies all around the globe are rigorously working on improving the performance of EVs, India is also actively participating in promoting and providing a better platform for EVs. As everyone knows those EVs are the future of automobiles and hence their development is a necessity. So, it will be very intriguing to see the future of EVs in India and around the globe.

Optimization of heat transfer rate and size of heat money changer (condenser) by significant tests met by Refrigeration structure proposals. The heat transfer rate problem is concerned with the determination of total heat transfer rate, and the sizing issue is concerned with the determination of the aggregate high temperature exchange surface range. The key element helping for higher heat exchange rate and base high-temperature exchange zone may be those refrigerant streams out in the condenser coil, likewise those framework lies over indoor of a bureau. The objective of the available task will streamline those outlined of a commercial refrigeration condenser to enhance the heat transfer rate. CFD (Computational Fluid Dynamics) and Condenser software will be used to optimize the design of the components. Structural dissection about parts will be also will be performed to dissect the deformations and anxieties happening because of the weights and temperatures of the stream. The necessary modifications are made to improve the heat transfer rate & reduce the size of the condenser that enhances the overall heat transfer rate.

A low-power pre-processor system is introduced to extract the informatory data from noisy biomedical signal. The proposed systems hardware is executed on ZedBoard (Zynq-7000) evaluation Field Programmable Gate Array (FPGA) board. The proposed methodology is based on the efficient pre-processor system that depletes low power & resources of FPGA: Windows and Wavelet. The comparison has been done among different windows and different wavelet-based pre-processor designs as per resource utilization and on-chip power. The inference has been drawn from the comparison that Haar wavelet consumes only 2.15% of LUTs, 12.19% of slice registers and only 25.45% of DSPs. The selected pre-processor design also consumes only 34mW of dynamic power & 110 mW of static/leakage power. In future, the introduced pre-processing system will be employed in wearable & portable biomedical equipment.

Smart meters are an electronic device to measure energy consumption accurately, at precise time intervals. In India, Britishers introduced electricity firstly in Calcutta in 1879. After the inception of electric power, it took a very long time to become an Act named “The Electricity Act” framed in 1910. Initially, the cost of electricity consumption measured by fixed charges, after that, a measuring device as “Electric Meter” came into the market. This meter has some limitation such as precision value of meter reading, missing of date and time and kilowatt per hour etc. This was the measure concern for both the electric consumer and provider to know the exact value of the electric consumption with other essential information. To overcome these issues, several technologies have been developed and a new concept of measuring device was introduced “smart meter” introduced for an accurate result. In this paper, we discuss things that can overcome the limitations of the existing smart devices.

Leaf springs are an essential part of automobiles because it provides directional stability, ride comfort and improves vibrational characteristics. Fatigue stresses induced in leaf springs directly influenced fatigue life. Fatigue life will increase under low fatigue stress. This is achieved by reducing unsprung weight. In automobiles, leaf springs are contributed 10 to 20% of unsprung weight. Thus, researchers tried to minimize the weight of leaf spring under the same loading conditions. Optimal design and selection of suitable materials are the ways to fulfill this objective. In this paper, double tapered composite leaf spring is selected for optimization using a genetic algorithm. Optimization has been performed for glass fiber, carbon fiber and graphite fiber composite leaf springs. The optimization result reveals that the weight of mono leaf spring made by carbon fiber composite is 91.92% lighter than multi-leaf spring. Thus carbon fiber composite is the most suitable candidate in comparison to glass and graphite fiber composite fiber mono leaf.

As fossils fuels are depleting at a faster rate and from the standpoint of the environmental concept, it is necessary to use alternative sources of energy that could replace fossils fuels in existing engines. Dual fuel engines are economically attractive replacement for traditional diesel engines or obsolete diesel engines with slight variation in engine design. Furthermore, this engine suffers from inferior performance, slow-burning rate and higher levels of carbon monoxide and un-burnt hydrocarbons at lower loads. Various engine experts have also found an increased delay period and knocking tendency while exploring dual-fuel engines. Because of the accompanying reasons, numerous scientists have discovered a different strategy for the substitution of diesel, one of which is the utilization of biofuel as an enhancement for diesel fuel. World over there is growing trends for the generation of bioCNG with proper management of organic waste. The extraction of power from biogas (bioCNG) under dual fuel mode has risen as a potential vitality transporter to address the environmental issue associated with the compression ignition (CI) engine. This review significantly focused on the utilization of gaseous fuel (bioCNG) to CI diesel engine under dual fuel mode with diesel and diesel–biodiesel blend as pilot fuel. Different engine characteristics, such as ignition, performance and exhalations of the dual-fuel engine utilizing gaseous fuels have been gathered and assessed. Findings of various literature suggest that CI engine performance in dual fuel mode slightly deteriorates but the corresponding reduction in harmful pollutants occurs with the introduction of gaseous fuel. Overall, it can be concluded that utilizing bioCNG in pilot diesel and diesel–biodiesel blend results in improved performance with reduced exhalations at higher loads.