Recent Advances in Mechanical Engineering

A two-dimensional numerical simulation was performed on a 3 mm internal diameter, one-turn pulsating heat pipe (PHP) to perceive the flow velocity and thermal performance of PHP at varying gravity conditions. All the simulations are carried at the stable wall temperature of 300 K at condenser and 373 K at evaporator sections. Obtained numerical results at microgravity PHP is compared with the PHP at earth’s gravity. Based on the average flow velocity, power spectrum density analysis results found that flow velocity during the microgravity PHP is low in comparison with PHP operating at g = 9.8 m/s. The mean heat transfer coefficient of microgravity PHP is 4.2 times lower than that of normal PHP, heat transfer in microgravity PHP is mainly due to the effective thermal conductive nature.

A computational study is performed on natural convection heat transfer from a hollow vertical tube with annular fins. The tube thickness is negligible, and it is suspended in stagnant air. This study has been carried out within the laminar regime by varying Rayleigh number $$\left({10}^{4}\le Ra\le {10}^{7}\right)$$ 10 4 ≤ R a ≤ 10 7 . In addition, various influencing input parameters, namely, aspect ratio $$\left(L/D\right)$$ L / D , and spacing between fins $$\left(S/L\right)$$ S / L are considered to delineate the thermofluidic behaviour around the heated finned tube. The net heat loss rate is estimated to be greater at the lower value of $$S/L$$ S / L for particular Ra and L/D. However, the Nusselt number is predicted to be lower in the same condition. Lastly, velocity vectors are employed to understand the fluidic behaviour and stronger fluid circulations are found at the greater value of $$S/L$$ S / L .

Fluid elastic instabilities are common phenomena in fluid-conveying pipes. The current paper investigates the chaotic behavior of fluid conveying pipe simply supported at both the ends. The pipe is considered as an Euler–Bernoulli beam and accounts for the geometric nonlinearity due to the midplane stretching of pipe. The nonlinear integro-partial differential equation of motion is nondimensionalized and then truncated through the Galerkin approach. The fluid velocity has a periodically varying component over a steady mean velocity. The velocity amplitude and fluctuation frequency are the control parameters. The dynamic behavior is investigated numerically through phase plane trajectory and time history via fourth-order Runge–Kutta integration technique. The evolution of chaotic oscillations in a double well potential is observed for higher values of amplitude and frequency of fluctuation of velocity.

In many fields, such as agriculture (irrigation), chemical, pharmaceutical, food processing, and chillers uniform flow from each outlet of the distributor is prime important. The static head in the manifold is changing due to skin friction and momentum changed along the length and at the close end. Therefore, the study of pressure gradient and flow distribution plays a critical part in the prediction of efficiency and performance of manifold. In this paper, various findings on the manifold design are studied. The paper also explains the theoretical design, along with various methods used to arrive for solution, and highlighted the milestone of previous research along with a brief description of parameters affecting the even flow distribution. The governing equation and its solution can be obtained using mass, energy, and momentum theory with discrete and analytical methodology. Different studied generalized models are stated here that can be utilized for the optimization of manifold design. The rise and fall in pressure along the length of the manifold due to friction and momentum are adjusted by the geometry of the manifold.

Rotary regenerative heat exchangers or rotary regenerators are used extensively in many industries for heat recovery applications. Many researchers have studied different operating conditions in order to improve the effectiveness as a key performance parameter of rotary regenerators. However, few of them have worked for optimizing the design parameters that affect the performance of this heat exchanger. Moreover, the parameters, like pressure drop, are also need to be analysed in detail. In the current work, the numerical investigation of rotary regenerator is carried out using CFD and the effect of important design parameters like regenerator core dimensions and width of separator gap on effectiveness as well as pressure drop is studied. It is revealed that regenerator core dimensions such as length and diameter have a considerable effect on performance and pressure drop. The width of the separator gap between hot and cold fluid sections also plays a crucial role in predicting the performance of a rotary regenerator.

A shell and tube heat exchanger is analyzed numerically to determine the effect of the baffle angle on the heat transfer coefficient and the pressure drop. Heat exchangers that use shells and tubes benefit greatly from baffles because they allow for more effective heat transfer with less pressure drops. CATIA and ANSYS—Workbench Flow Simulation software is used to construct heat exchangers with baffle angles of 0, 10, 20, 30 and 40°, and fluid dynamic simulations are also performed. The greatest heat transfer occurred at a baffle angle of 40°, assuming a constant heat transfer coefficient between the baffle and shell. It has been shown that a 40° baffle angle produces the least amount of pressure drop. Our heat exchanger features a combination of rotational and helical baffle patterns, which greatly improves its heat transfer coefficient per unit pressure drop.

Heating Ventilation and Air-Conditioning System (HVAC) is very much essential for proper human health and well-being of domestic environment as well as office buildings and industries. Air-conditioning system for comfort conditions used to be very expensive and extensively used only by a few people, but these days, it has become a necessity and not a luxury anymore. Air-conditioning in small spaces like domestic homes and small office buildings, etc. use split or window air conditioners, while large multiplexes and buildings use Central air-conditioning system because there the cooling load required is very high. In Central Air-conditioning, the central plant is installed away from the space to be conditioned where water and air are to be cooled. The air which is cooled through the central plant is not directly supplied to the spaces or areas to be conditioned rather they are carried away through ducts. The cool air is carried by the ducts from the air-conditioning system to the rooms and again air returning from the rooms is directed back to the conditioning equipment to be conditioned and circulated again. Proper design of a duct is essential to avoid frictional losses, noise, uneven distribution of cool air inside the cooling space, higher power consumption and more capital. In this research, a numerical study with comparative analysis is carried out about duct insulation. It also showcases the cumulative comparison of different filters and different types of insulation provided inside the duct which analyses their efficiency and workability for indoor air quality.

Because it can create 3D physical prototypes without being constrained by geometric complexity, fused deposition modelling is acquiring unique advantages. However, when it comes to accuracy and efficiency, these advantages are not as obvious, therefore, it is important to investigate how to increase them. The antibacterial polylactic acid is chosen as the material for developing the specimens by fused deposition modeling. The layer thickness, printing speed, and infill density are chosen as input parameters and compression is designated as the output constraint. The L9 orthogonal array is utilized to find the combination of input constraints to print the specimens and the Taguchi approach is adopted to exploit the compression of printed specimens. The optimized process constraints for maximizing the compressive strength are a printing speed of 80 mm/sec, infill density of 60%, and layer thickness of 0.12 mm.

Environmental concerns around the world necessitate manufacturing firms to embrace new practices that may lessen the negative environmental effect. These days, green supply chain management (GSCM) is gaining more popularity in the manufacturing sector from material acquisition to product delivery to the customers. Adoption of GSCM by Indian manufacturing firms is comparatively slow due to a lack of identification of different barriers and drivers of GSCM. To this end, the present study aims at the identification of barriers and drivers of GSCM, typical to the Indian scenario. Individual groups of six barriers and eight drivers have been identified for this research by industry experts. In addition, the study prioritizes these enabling factors using multi-criteria decision-making (MCDM) processes such as the analytic hierarchy process (AHP) approach and the technique for order of preference by similarity to ideal solution (TOPSIS) approach. In order to handle the ambiguity in decision-making, the data have been extracted from the experts using linguistic terms. A case of an Indian paper manufacturing firm is considered for this study. The fuzzy AHP (F_AHP) model indicates financial implication and lack of awareness/participation in GSCM as first and last ranked barriers, respectively, whereas the fuzzy TOPSIS (F_TOPSIS) model indicates economic consideration and customer, market and societal pressure as first and last ranked drivers, respectively. Finally, to encapsulate the robustness of the final result, sensitivity analysis has been carried out. This research will undoubtedly assist policymakers in developing policies that will facilitate GSCM implementation.

The artificial bee colony (ABC) algorithm is first used to forecast the best operating parameters for a liquefied petroleum gas (LPG) refrigeration system. LPG has been employed as a refrigerant to minimize the global warming problem. An experimental setup has been made up of an evaporator (cooling box), gas burner, LPG supply unit, capillary tube length, and a pressure regulator. The running time (top), coil diameter (D), and inner diameter (di) of the capillary tube are considered as operating parameters to examine their influences on the evaporated temperature (TE) by full factorial design. The best mathematical equation for TE has been developed by regression analysis. The best values of process parameters (top = 50 min, D = 190 mm, and di = 0.8 mm) for the maximum evaporating temperature (TE = 11.9 °C) have been estimated by ABC MATLAB code.

For improving the overall efficiencies of the photovoltaic energy systems, it is very important to model the photovoltaic cells and modules accurately. This necessitates the parameters of the photovoltaic systems to be extracted correctly. Then only it can serve the aforementioned purpose. Different methodologies and techniques are proposed by different authors in the past. But to overcome slow convergence in some of the techniques, a Generalized Oppositional Differential Evolution Algorithm is proposed for cell and module parameters extraction. It has a proper equilibrium between the intensification and diversification of candidate solutions within the search space. Basically, the root-mean-square error of experimental and simulated current for a model is considered as an objective function that undergoes minimization. For evaluating the performance of the projected approach, the parameters of a photovoltaic cellcand-a-module are extracted and compared with those extracted with other techniques proposed earlier. The simulation results are obtained in Matlab. The experimental and simulated I-V graphs of each model are superimposed to test the accuracy further.

Social Networking site data have emerged as an important source for identifying and tracking disasters. According to a number of recent research, the utilization of social networking data streams to extract meaningful data for emergency workers so that rescue operations are possible. If the information gathered is successfully utilized, it can reduce casualties and aid in the provision of basic requirements and medical care. The data gathering and evaluation procedure for the intended building of real-time catastrophes-related communication. The features of tweets during the Kerala Floods of 2018 were examined for this purpose. About 154,524 tweets were collected using the API during the period between July 2018 and January 2019. They were categorized on the basis of location, Kerala, with the help of MS Excel, and finally obtained 10,704 tweets. The data being posted was analyzed. Data visualization has been done with the help of Tableau and the most commonly used words were identified using a data set of 10,704 tweets in this study.

Network on Chip (NoC) is a communication subsystem between various IPs interconnected through an on-chip router inside a single chip. The on-chip interconnection infrastructure connects the different intellectual property (IP) with the help of various industry-standard high-performance (HPC) interconnection topologies. Also, the on-chip interconnection network facilitates the connection of more Processing Elements (PE) to enable deadlock-free scheduling and parallel processing. The present work addresses one important aspect of NoC which is “Optimal Mapping” which allows the participation of cores in an optimal way for achieving low bandwidth requirement, low latency hence greater throughput. To achieve the optical mapping, a Genetic Algorithm is proposed here for the optimization of NoC performance by employing 2D Mesh topology. The genetic algorithm produces consistent and comparable results at par with standard algorithms. A deterministic seeding and successive seeding would yield better results and consume less CPU time. The proposed result is marginally better than NMAP and PSMAP.

Resistance spot welding is a supreme noteworthy joining practice exploited in various engineering. To circumvent welding failures and the quality of some materials, optimization of welding parameters turns out to be vital for forecasting upright welded joints. This study targets at scrutinizing the impact of spot welding variables on dissimilar lap joints for 50HS Stainless Steel; AA1200 Aluminum Alloy. Experimentation is planned as per Taguchi’s L9 orthogonal array. Expectations of ANOVA are conversed and carefully scrutinized. Measurement Alternatives and Ranking according to Compromise Solution (MARCOS)-based Taguchi methods are applied to investigate the output responses of resistance spot welding operation. The results revealed that welding current is the main affecting parameter of nugget diameter and tensile-shear strength. After performing confirmatory tests.

Creating and disseminating a protected successful COVID-19 vaccine has accumulated huge worldwide interest. Early in 2020, when COVID-19 was affirmed as a pandemic, few vaccine entities had expected urgent situation usage approval through India. In spite of this logical leap forward, the excursion from immunization disclosure to herd immunity against the virus keeps on introducing huge arrangement challenges that need cooperative effort. In this work we have developed a framework to address the difficulties in parameters which affects for use of vaccine against COVID-19. A well-known technique Fuzzy-AHP is introduced in our work for prioritization. The overall weights are calculated with the help of the Fuzzy-AHP technique to determine the effect of different parameters. This work will be helpful to the boniest industry and research health laboratory.

Market basket analysis, or MBA, is a technique for determining the strength of an association rule between two or more products purchased at the same time, as well as patterns of when two or more occurrences occur at the same time. If the item “One” is purchased, then item “Two” is most likely to be purchased, according to Market Basket Analysis. The rules are hypo-thetical because they are developed from the data's co-occurrence frequencies. Frequency is the percentage of baskets that include the objects of interest. Pricing, product placement, and product suggestions to customers based on their purchases can all be influenced by these ideas. The goal of this research is to compare the performance of the Apriori and FP-growth algorithms. The Apriori approach generates candidate frequent itemsets, while the FP-growth algorithm bypasses candidate generation and builds a tree using a cost-effective and efficient ‘divide and conquer’ strategy.

The present-day industries demand products with high surface finish and greater accuracy. EDM is the most sought operation in many industries for material removal, and the process is governed by many controlling parameters. To increase the process performance, optimization of process parameters is done. In the current study, the influence of process variables like “peak current (Ip), pulse on time (Ton), pulse off time (Toff), gap voltage (Vg), and Flushing Pressure (FP) on Material Removal Rate (MRR), Tool Wear Rate (TWR), and Surface Roughness (SR)” has been investigated for EDM of TiBT20 alloy. The work material possesses exotic mechanical properties and has diverse industrial applications in aerospace industries. Taguchi’s L27 orthogonal array was used for the optimization of input parameters. “Analysis of variance (ANOVA)” was performed to analyse the impact of parameters on the output response. Grey Relational Analysis determines the preferable set of input variables for high MRR, low TWR, and SR. The confirmation test with the optimum set of process parameters shows an enhancement of 0.3128 in the preferred value. The most suitable set of process variables is Ip = 4 Amp, Ton = 100 µs, Toff = 15 µs Vg = 4 V, and FP = 0.1 (Kgf/cm2).

A process by which latex (an emulsion of polymer microparticles in water) is collected from a rubber tree is called rubber tapping. Uncomfortable postures which include extension, twisting, and flexion of arms, neck, trunk, and wrist are demanded by the operation of rubber tapping for more than 300 trees in a day with the traditional knife. Musculoskeletal disorders (MSDs) have increased in prevalence among rubber tappers as a result of these uncomfortable postures. In order to understand the frequency of MSDs, a survey using the Standard Nordic Questionnaire was completed by 38 tappers from Kerala’s northern and southern districts, and videos of each tapper’s tapping procedure were recorded. In order to comprehend the degree of deviation, flexion, and extension of various body parts and analyse the degree of threatening postures while rubber tapping poses to tappers over the long term, a posture assessment technique known as the RULA was used. It has been understood from the posture analysis by RULA that 85% of the tappers require immediate attention and solution to prevent them from getting diagnosed with permanent MSDs. Around 95% of the tappers are at great risk of getting affected with at least one MSD. The study concludes by recommending necessary or immediate design improvements which would benefit the rubber tappers by preventing them to work in awkward postures during tapping reducing the risk of MSDs.

The cranked beam is commonly used to support sloping roofs and has the advantage of lower bending moments owing to its shape. The notch reinforcement of the cranked beam requires special detailing to lower the stress concentration. In this study, the goodness of the reinforcement details of the cranked beam given in Indian Code, SP 34 (1987), is put to test through Finite Element Analysis (FEA). The basic proportions of the beam were traced in AutoCAD. A design spreadsheet was developed based on the limit state design philosophy of IS: 456 (2000) for the cranked beam. The finalized dimensions of the cranked beam along with the reinforcements were modelled in ABAQUS. The preliminary model after validation was analysed for the central point load of the base case for M20 concrete, then the model was modified for other grades of concrete and loads. From the analysis results and stress contours, the stress concentrations and deflection of the cracked beam with constant cross-section were determined and the ideal proportion of the cross-section and reinforcement detailing were arrived at.

In today’s world demand for durability and recyclability is among the main factors considered when choosing a material for any product to be made. In the automobile sector apart from exterior parts of the vehicles, the interior parts should also be durable as it faces different types of loads in various situation. The internal door panel is considered one of the most important interior parts of the vehicle as it has to undergo different forces from the user side and also are meant to reduce the impact force on the passenger in an accident. Natural fiber-reinforced polymer composites are considered to be very durable and are lighter than a lot of other materials present in the market. They have higher impact strength and higher tensile strength than a regular material. Young’s modulus of coir fibers usually lies between 4–6 GPa. In this work coir fiber-reinforced polypropylene was used as the material for the internal door panel. It has an elastic modulus of 1.9 GPa and has a tensile strength of 34 MPa. An FEA was done on the door panel to determine whether it is going to be a suitable replacement for the current material which is being used. The deformation seen was around 1.036 mm with the maximum stress being $$3.877X10^{ + 07} \frac{N}{{m^{2} }}$$ 3.877 X 10 + 07 N m 2 , which is an acceptable value for protecting the occupant. When a load of 100N was put on the armrest it showed a deformation but not more than Young’s modulus meaning it can handle a load on the armrest when someone put their hand on it. The maximum deformation in the armrest was only $$6.490X10^{ - 4} mm$$ 6.490 X 10 - 4 m m , showing it is suitable as a material for the internal car door panel.

This paper describes the design procedure for a new passive prosthetic foot using topology optimization. The proposed procedure can provide an improved optimized patient-specific foot design. The procedure works by reducing the weight of the prosthetic foot using topology optimization. This process can be utilized for patients with one leg amputation, whose other foot is used for capturing pressure plate data from a gait cycle. As nature has created every human being differently, the pressure pattern of an individual obtained using pedobarography or pressure plate data is also unique patient specific. Six varieties of materials along with seven cases of optimization are used to get optimized foot models. Based on their comparison final foot optimization is used to define the methodology. Finally, 42 different foot-optimized models are developed for the combination of different materials and cases of optimization. The developed optimized models are illustrated and their masses are compared with their masses before optimization. Strategy to improve methodology and necessary materials for Additive Manufacturing are discussed.

Mechanical legs are important elements of robotic walking platforms. They give the platforms excellent ability to traverse irregular and uneven terrains. There has been a lot of development in robotics for locomotion and operational purposes in the last few decades. This work is an exploration based on the extensive literature survey of walking machines. A multitude of leg mechanisms was analyzed from patents and their topological structures have been investigated for the generation of novel mechanisms using creative design theory. An Atlas of 22 novel leg mechanisms has been generated. Also, a study of foot point coupler curves of biped human, quadruped mammal, reptiles and insect’s feet have been given here to find out the common aspect of walking mechanisms with generated coupler curves in this research work. The mechanically generated coupler curves are comparable with the animal foot trajectories. The DLTdv7 digitizing tool from MATLAB was used for the extraction of foot trajectories by video graphic analysis.

The analysis of a curved box-girder bridge is quite complicated as it experiences additional torsional moments compared to a straight bridge. Also, the behaviour of such bridges is different for different curve angles. This paper studies the effect of curve angle on simply supported single-cell trapezoidal prestressed concrete box-girder bridges using CSiBridge v.20 software. To identify the appropriate mesh, a convergence study is performed. The present approach is validated with the published results. The variation of forces, stress and deflection with curve angle for a single-cell bridge under dead load and IRC live load is evaluated. Further, the equations are deduced using the statistical approach so that the results may be estimated for different curved bridges. This study may be useful for the designers to analyse curved prestressed bridges.

A utility vehicle, usually motorized, is designed to do a particular purpose more efficiently than a passenger vehicle. Utility trucks can easily navigate rugged terrain. They are used to convey things in various environments such as farms, industrial sites, and parks. The chassis provides the strength required to sustain the various vehicular components and the cargo and contributes to the vehicle's rigidity and stiffness. As a result, the chassis is an integral component of the entire safety system. Our team relentlessly worked towards the objective from square one. This paper shows the details of design considerations and methodology used in modeling the design and development. SOLIDWORKS 2021 and ANSYS 2020 R1 are used to design and evaluate the medium. The chassis is designed to run on human power and green energy.

The transmission system used in an automobile transmits power from engine to wheels. The automated transmission system has no clutch pedal and gear lever while the manual transmission system incorporated the same. To modify the conventional transmission system into the automated transmission system a selector and a shifter mechanism is required which needs a minimum of 2 actuators, one for selection and other for shifting. But since this mechanism is interlinked with each other it is required to develop a complex method which could both shift and select the gears. In this paper have used a single linear actuator which could both shift and select the gears with the help of a selector sleeve. INDICA V2 car with manual transmission is selected, designed, modelled and the gear shifter mechanism fabricated. Gear engaging algorithms are developed for designed shifter mechanism. INDICA V2 engine is taken out of the car and assembled with the gear box with a designed shifter mechanism and tested for gear shifting leads to provide plug in solution to modify manual transmission.

Connected buildings are gaining popularity due to increase in accessibility, improved aesthetics and touristic value attached to the connecting bridge. However, the structural impact of connecting two buildings/towers needs a careful study especially if there is irregularity/asymmetry in one which may affect the structural behavior of the other. In this study, two symmetrical buildings with nine stories and nine bays along each direction connected with a 4.5 × 7 m sky bridge at its 7th floor is analyzed using ETABS. After design checks as per IS codes and validation of the base model, one building was modified to bring in irregularities. Five different types of irregularities viz., geometric irregularity, mass irregularity, re-entrant irregularity, torsional irregularity and weak story irregularity were introduced in the building, with two levels of irregularities for each of the irregularities. The overall building response was observed based on the results of the time period and lateral displacement and inferences drawn.

In this present study, combustion is investigated in a micro-scale channel with an internal triangular wall fin numerically. Numerical simulations have been performed for micro-combustion with triangular wall fin for fin-inclination angles of 40°, 50°, and 60° at different inlet velocities. Two small-sized recirculation zones are formed one behind each wall fin so that the flame is anchored and offers more residence time for stable reaction. The average combustion efficiency is observed to be greater than 97% for all the inclination angles in the considered range of inlet velocities. Though the effect of the inclination angle on the mean temperature on the outer wall is insignificant in terms of magnitude, the uniformity in its distribution is affected by the fin-inclination angle. The uniformity measured in terms of the uniformity index (UI) and standard deviation (SD) is better for higher inclination angles or lower inlet velocities. It is also demonstrated that the 50° inclination angle gives the highest average and maximum wall temperature in most inlet velocities.

This study investigated the safety parameters of a water-water research (VVR) reactor core containing VVR-M2 type fuel during a severe hypothetical loss of coolant accident (LOCA). A pool-type water-water research reactor was studied. The reactor was assumed to be operational with a nominal thermal power of 200 kW. A beyond-design basis accident was considered where the LOCA was accompanied by a station blackout (SBO). To simulate the most severe loss of the coolant scenario, only natural circulation of air was considered for removing decay heat from the core. The risk for the reactor core meltdown was identified by observing whether the maximum fuel or cladding temperature of the hot rod crosses the melting temperature or not. The scenario was simulated using the MELCOR severe accident analysis code. Results revealed that the maximum fuel temperature is around 212.45 °C, far below the melting point of the U-Al fuel. The peak was observed around 3000 s into the accident’s inception. On the other hand, the maximum cladding temperature reached 212.40 °C, which was below the melting point of Al but crosses the designed safety limit of 200 °C for the SAV-1 alloy. Nevertheless, it is opined that if the reactor is brought to a subcritical state with an emergency protection system, the decay heat removal with the natural circulation of air is sufficient to prevent a core meltdown under the specified operating parameters.

Thermoelectric coolers are the solid-state devices which have ability to convert electrical energy to thermal energy producing cooling effect without use of refrigerants. The cooling performance of the device at higher temperatures decreases and can be improved by attaching heat sinks on either side of the device with the application of nanofluids as a heat dissipation fluid. Nanofluids are utilized in this study to cool the hot side of thermoelectric cooler, when the thermoelectric module temperature rises above the maximum temperature. Both ANSYS Fluent and Thermal-Electric models were used to visualize heat transfer between nanofluids and the thermoelectric thermal side. Thermoelectric cooling is a technique used for thermal control of electrical equipments, such as processors, electronic cooling etc. In heat transfer applications, nanofluid has received attention as new and efficient heat transfer liquid due to its high thermal properties compared to conventional thermo fluids such as water. Different nanofluids like Al2O3-water, SiO2-water, TiO2-water, SiC-water and CuO-water were used to flow in the minichannel at different concentrations and Reynold numbers. The input voltage applied across the terminals of the thermoelectric module and COP is optimised using least input power. It is concluded from the study that the greatest COP achieved in the thermoelectric refrigerator for CuO-water nanofluid as a coolant is 1.57 for the nanoparticle concentration of 0.05%. The results show that using nanofluids improve the system's overall performance. The maximum COP obtained for nanofluid CuO-water with minimum power input of 60 W using 40 nm particle size.

Rapid Prototyping is a type of Additive Manufacturing (AM) process, which deals with the fast manufacturing of parts. Fused Deposition Modeling (FDM) is one of the most appreciated AM process, which uses thermoplastic material as filament feed. The part quality, durability and mechanical strength also gets severely affected because of the undesirable effect taking place during the part fabrication process. It is already known that the FDM works on layer by layer mechanism and the heated nozzle extrudes the semi-molten thermoplastic filament at a high temperature. So during the fabrication of each layer, there is a working mechanism of forced convection due to the non-uniform cooling of the deposited layer, between the semi-molten hot material and the chamber temperature. This may sometime leads to shrinkage and warps deformation in the built parts. Minimization of these issues can result in better part accuracy, strength and quality as well. Here in this paper four input process parameters are considered such as Raster Width, Raster Angle, Layer Thickness and Air Gap, and their effects on warpage deformation are calculated mathematically using MATLAB R2017a. Design of Experiments (DOE) approach is made to get experimental sets. ANOVA is used to analyze the significance of each parameter on warpage. Response Surface Methodology (RSM) technology is used to generate the response plots. The regression equation for the total number of lines establishing a relation between process parameters and the response is generated.

Slurries, basically regarded as two–phase (solid–liquid) mixtures of ore and the carrier medium, generally water, are transported through underground pipelines. The rheological properties of the slurry also do play an important role in defining the salient parameters of hydraulic transport such as head loss and pressure drop in slurry pipelines. CFD has provided an upper hand in mathematical modelling and flow simulation, as it provides accurate and dependable flow simulation results. This article primarily focuses on determining the pressure drop across the ends of the pipeline, as the slurry flows through it, and to establish a graphical depiction of the various simulations made using different set of conditions. The pressure drop was found to be ranging between 4.27 and 6.53% when the angles of bend of the pipeline system was increased, while the same was found to be hovering around 4.91−8.3% when the inlet velocity was increased. 4.12−7.65% was the range amid which the values of pressure drop varied when the concentration of solids in the slurry were increased, while for an increasing diameter of cross section of the pipeline, the pressure drop was in the range of 5.15−12.91%.

People having an average income find owning a car to be a dicey socio-economic problem. Thus, to avoid the risk of taking a wrong decision in the selection, people often resolve it qualitatively through different Multi Criteria Decision Making (MCDM) methods. Machine Learning and Recommendation Engines have made the prediction easier as to which should be selected. The algorithm proposed in the paper works by hybridizing the MCDM algorithm, Analytic Hierarchical Process (AHP) and Recommendation algorithm, Collaborative Filtering (CF), which finally recommends a single car out of a large amount of cars from the dataset which makes the decision easier. The user satisfaction and preferences are satisfactorily mapped with the results.

The concept of Vital Signs (VS) has given a simplistic yardstick for detecting structural irregularities in a building which is the cause of many failures in destructive earthquakes. In this study, three parameters, namely time period, story displacement and mode shape are examined for their goodness as VS for the buildings by studying the effect on them due to two plan and three vertical irregularities. Static analysis is carried out on 20 circular shaped buildings with 9 stories using ETABS. After validation studies on the two base models (regular building), the effect of the VS is studied upon by gradual introduction of torsional irregularity, re-entrant corner irregularity, mass irregularity, vertical geometric irregularity and weak story. For each type of irregularity, three levels of models were analyzed (with increasing order of irregularity) except for torsional irregularity for which six levels were considered. From the study, it is observed that the time period of the building changes in a definite pattern with increasing level of irregularity which justifies its use as a vital sign. However, displacement for the models compared for two extreme points on the plan does not show a definite pattern for all the cases. Based on the study, symptomatic rules are arrived at on how the effect of the irregularities considered is captured in the VS which aids in their detection in building design processes.

The accuracy of wind speed forecasting is essential for a power system's long-term stability. In this research, a random vector functional link neural network (RVFLN) with a kernel function is suggested for short-term wind speed forecasting. Even if the traditional RVFLN has a quick learning rate, simple design, high generalization capabilities, and direct connections between the input nodes and output nodes give a better result. However, determining the number of hidden nodes and their activation function, on the other hand, remains a difficult challenge. So to avoid this disadvantage a kernel function is introduced with RVFLN, which also improves the accuracy of regression, generalization, and stability of forecasting. In addition to this, one data decomposition method named variational mode decomposition (VMD.) is used to decompose wind speed data and remove noise signals and extract the key features of the actual series. To justify the accuracy of the proposed method VMD-KRVFLN, the data is collected at a different time intervals from the Sotavento wind farm located in Spain. The result analysis also shows the improved prediction of wind speed among other benchmark techniques.

Brain tumors must be detected accurately and early in order to be treated successfully. Early detection not only aids in the development of new drugs, but it can also save a life if caught early enough. The introduction of Biomedical informatics and computer-assisted diagnosis has benefited neuro-oncologists in a variety of ways. In comparison to manual tumor detection, which is a time-consuming procedure prone to human mistake, machine learning algorithms have lately been used to evaluate medical imaging and data. When compared to manual traditional diagnosing procedures, computer-aided mechanisms produce better results. This research does a comparison between convolutional neural network (CNN) and artificial neural network (ANN) to extract features and then classify them. To determine whether the MRI as “TUMOR SPOTTED” or “TUMOR NOT SPOTTED,” the suggested work uses a deep neural network technique which also includes a CNN-based model.

In this current scenario, one of the most promising sustainable power source is solar power. More vitality can be created when the solar rays will fall opposite to the solar panels. Therefore, to improve the efficiency of solar energy conversion, new photovoltaic materials are being developed. To monitor the course of study of the sun throughout the day there is a need for an appropriate technology, for preserving the maximum possible amount of solar energy. In this paper a model has been proposed based on the dual axis solar tracking system that would have the potential of connecting with the smart grid through the Power Line Communication system. The main objective behind the paper is to track the sun such that the sun rays would always hit the solar panel perpendicularly. In order to make the system cost effective, cheap substitutes for the same has been stated in this paper. Also the proposed model is developed on a solar ray tracking system which drastically improves the solar panel efficiency.

The sensitivity of the solar photovoltaic (PV) arrays for the unavoidable partial shading have elevated a serious concern related to the efficiency of the PV systems. Various methodologies are proposed in the wide range of literature for partial shading mitigation to limit the losses in PV arrays. The most simple and costless mitigation technique is reconfiguration of the arrays on the basis of the position or electrical connection alteration concept. However, most of these techniques are limited to the symmetrical size array that adds demerit to those techniques mainly while implementation in roof-top and large PV systems. Hence, a reconfiguration technique established via physical relocation of the modules (MR) for unsymmetrical PV arrays under shading for power generation improvement is proposed in this work. The proposed technique has been tested for an 8 × 4 array under various shading cases in the MATLAB environment and compared with conventional configurations. From the analysis, it has been concluded that the MR technique shows excellent performance as compared to conventional configurations during all the shading scenarios.

Nowadays, renewable-based power generation attained more attention due to its enough advantages. Among various renewables, Photovoltaic (PV) attained more popularity due to its availability. However, the reliable output power from PV is mainly depending on the weather conditions and internal faults. Therefore, this paper presents a PV-battery-based DC microgrid to supply uninterrupted power under uncertainties of weather conditions. To overcome the power loss, which is caused by internal faults i.e., arc faults, a variational mode decomposition (VMD) based discrete Teager energy operator (DTEO) is presented. Initially, VMD is used to decompose the derivative fault current signals into different intrinsic mode functions (IMFs). Among different IMFs, the most significant IMFs are obtained by using the sparse kurtosis index. Further, those IMFs are subjected to DTEO for accurate detection and isolation of the fault under different operating conditions by issuing a trip signal to the breaker based on the threshold value. Finally, to evidence the superiority of the proposed VMD-DTEO is compared with existing methods and the overall operation is carried out in the MATLAB/SIMULINK environment.

In the present scenario, the most challenging issues are power balance and integration of distributed generations (DGs) in micro grid system (MG), which produces instability and power quality issues. Many control strategies have been developed in order to take care of these issues. However, there are many unsolved problems still challenging like the robustness and reliability of the controllers. In this paper, two solar PV cells are integrated with the primary grid with a rating of 25 kV. Solar energy is chosen because of the demand, cost-effective, and abundant availability. The primary purpose of this research is about the performance of three controllers like PID, fuzzy, and nonlinear auto regressive neural network with exogenous output (NARX-NN) in two case studies like PCC voltage sag/swell improvement and stability analysis in case of load change and partial shading condition with DC voltage and current. The entire simulation is performed with MATLAB/SIMULINK software.

Wildfires are among the most urgent environmental challenges affecting various parts of the globe. Uncontained wildfires interrupt transport, communication networks, supply of power and gas, and irrigation/water supply systems. They adversely affect air quality and cause property loss, crop destruction, and kill main animals as well as people. Climate change has caused various ecosystems to progressively dry out thereby increasing the risk of wildfires. Wildfires cause the emission of huge amounts of carbon and its oxides and fine particulate matter and worsen the factors that lead to further wildfires. The impact of wildfires can be diminished by early and accurate detection. There are many commercial fire detection sensor systems but most suffer from performance issues when used to monitor broad open tracts of land and forests—response time, maintenance requirements, high cost, etc. Our study estimates the probability of wildfire occurrence by retrieving and analysing the colours of forest images using image processing—specifically, the RGB values. Our focus is on estimating the risk of wildfire occurrence and highlighting spots that are most vulnerable thereby to achieve wildfire prevention.

Robotics, the engineering science and technology of robots, involves the design, manufacture and application of robots. Nowadays soft robotics is replacing conventional robots especially in poultry and vegetable industries which involve interaction with fragile and delicate objects. The majority of the egg exports in India are managed by the poultry farms in the Namakkal district of Tamil Nadu. Also, India is one among the largest producers of vegetables in the world. Kerala, being a consumer state as far as vegetables are concerned, is fostering an organic farming revolution where automated farms are necessary. This paper discusses the design and analysis of a 4-axes RRPR SCARA robot with a specially designed end effector with rubber pads which could process and palletize the eggs and ultimately reduces the processing time and human labor. This design could also be used in handling vegetables which would lead to a rapid growth in automated farms. The design, analysis and the kinematics and dynamic aspects of the designed SCARA Robot along with the control design are provided in this paper. The developed design was found out to be stable and effective, even in overloaded conditions.

This paper incorporates the frequency stability of an automatic generation control (AGC)-based four-area system. The rate of generation (GRC) is subjected to emulate a practical system. Two controllers of a classical type named PID and fractional order PID (FOPID) controllers are proposed. To design the controllers, a bio-inspired algorithm named symbiotic search algorithm (SOSA) is enticed. Sometimes, the secondary controller is not enough to deal with a sharp load variation and is also less assertive to provide high-quality power. So, an energy-storing element named redox flow battery (RFB) is injected in all four areas to compensate the required active power. Here, the effectiveness of RFB in the presence of an FO controller has been explicated extensively. Besides this, the profound performance of FOPID is confirmed by injecting a random step load in the presence of RFB.

Villages are home to the great majority of Indians. True India, according to Mahatma Gandhi, is located in villages, and we must work hard to develop our own. Energy use is a vital component of every country’s socioeconomic development (World Energy Resources: 2013 Survey. World Energy Council. https://www.worldenergy.org/publications/entry/world-energy-resources-2013-survey . Accessed 18 July 2022). Energy is the foundation of today’s industrial economy (ibid.). Agriculture, industry, transportation, businesses, and households all need energy to satisfy their basic needs. Energy availability is required to improve health, agricultural productivity, and educational outcomes (United Nations. Human Development Report 2001. Human Development Reports. https://hdr.undp.org/content/human-development-report-2001 . Accessed 18 July 2022). The increased need for energy has led to a reliance on large-scale fossil fuel extraction and use. As a result, environmental degradation, pollution, and ecological imbalance have occurred. In order to find a solution, clean energy is vital. As a result, focusing on the shift from conventional to clean energy sources is critical. This paper is divided into two sections. The first section is divided into two parts. It begins by discussing clean energy and clean energy products. Second, it focuses on mapping potential clean energy products in rural settings with various activities. The second section focuses on a circulation and profits compilation model that can aid clean energy product dissemination in rural areas followed by strategies for the adoption of clean energy products in rural areas and policy implications.

The general objective of this research is to determine the level of use of avocado waste in agroindustrial companies to obtain biodiesel in the Lambayeque Region, Peru. The type of research is quantitative, based on a non-experimental correlational design between the variables for obtaining biodiesel and avocado waste, applying a Pearson correlation. Likewise, a population and sample represented by the agroindustrial companies of the Lambayeque Region that export frozen avocado were taken, and waste data during the years 2015–2021 using a documentary analysis guide as an instrument was compiled. One of the main results shows that the transesterification technique is the method that is best suited for obtaining biodiesel. On the other hand, using this method, for each kilo of waste, half a liter of biodiesel is obtained, which is estimated to produce 485,200.67 L of biodiesel per year in the Lambayeque Region. Finally, through the Pearson correlation, it is verified that the variables obtaining biodiesel and waste have a direct correlation.

Mg alloy possesses established immense importance as a promising biomaterial for the substitution of damaged bones and other solid tissues within the body, because of biocompatibility alongside physical characteristics that are matching to the human bone. The present investigation is rooted in corrosion rate estimation for the AZ31 Mg alloy. To evaluate the corrosion rate, two different methods like weight loss analysis and electrochemical test were employed. The corrosion rate of Mg alloy is significantly high at the beginning, and it gradually becomes stable over a period of time as obtained from the open circuit potential curve of the electrochemical corrosion test. The electrochemical corrosion analysis results showed further negative OCP development for AZ31 alloy. It shows their lively performance, perhaps oxidation of Mg2+ ion by varying stability potential further negative. SEM micrograph of corroded surface conforms presence of oxides as a result of corrosion reaction in the solution. To further this research work, surface coating will be done in an attempt to reduce the corrosion to the desired level, which has been a critical issue associated with magnesium alloy. EDS analysis of the alloy specimen confirms that throughout the processing, about 84.75% (wt.) of Mg stays present in reheated AZ31 alloy. Moreover, throughout the processing, the average grain size of reheated AZ31 Mg alloy stays nearly 75 µm as against 50 µm for casted AZ31 alloy.

The automotive industry is majorly focusing on low and zero-pollution vehicles including Electric Vehicles (EVs) and Solar EVs. Green Hydrogen Fuel Cell Electric Vehicle (FCEV) also plays a major role in sustainable development as it stands out for several runtime and economic advantages. This manuscript is focused on a novel study of hybrid energy solar-assisted FCEV with the parametric optimization of the modeled vehicle. A real-time Solar EV is developed in-house and retrofitted into a solar-assisted FCEV. The model is developed for FCEV and is validated under various power sources for operation, and the simulated solar EV values are correlated with the actual vehicle. The aim of the work is to obtain the best operating parameters that account for the maximum runtime efficiency of the newly developed Solar FCEV. The optimized vehicle with Solar panels and Fuel Cell Stack turns out to be the best among the studied vehicles and observed a 35% increment in the vehicle’s range and the battery pack size is reduced by about 70%.

Recently, Mg alloy has received considerable attention as a potential biomaterial for replacement of damaged bones and other hard tissues inside the body, because of biocompatibility alongside physical characteristics that are matching to the human bone. It is important to acquire a detailed understanding of the corrosion performance of Mg alloy in aggressive biological environments. To evaluate the corrosion rate, two different methods like weight loss analysis and electrochemical test are employed. Therefore, the present investigation is rooted in corrosion rate estimation for AZ91 Mg alloy in a technically relevant 3.5% sodium chloride (NaCl) solution. The pH of the NaCl solution is kept at 7.4, equal to that of blood in order to mimic the actual body fluid environment. Immersion test and electrochemical corrosion study of the alloy were carried out at atmospheric conditions. The bio-corrosion rates of AZ91 samples are estimated at different intervals (3, 15, 32, 48, 72, and 86 h) of exposure to the solution. Corrosion rate of Mg alloy is significantly high at the beginning, and it gradually becomes stable over a period of time as it is obtained from the open circuit potential curve of electrochemical corrosion test. Microstructure evaluation of the corrode surfaces is done through a scanning electron microscope (SEM). The micrograph of the corroded surface conforms presence of oxides as a result of the corrosion reaction in the solution. EDS analysis of the alloy sample shows that during processing around 86.1% (wt.) of Mg remains present in as-cast AZ91 alloy. Additionally, during processing the average grain size of as-cast AZ91 Mg alloy remains nearly about 60 µm.

This experimental study represents the determination of optimum operating parameters of diesel engines powered by different low-percentage Mahua biodiesel-diesel blends for the improvement of performance characteristics. Different mixes of Mahua biodiesel-diesel, engine loading, and fuel injection pressure were considered as input operating restrictions with varying degrees of severity, and severity was determined. The Box-Behnken approach, which is centred on Response Surface Methodology, was utilised for experimental design, and for evaluation of brake thermal efficiency and exhaust gas temperature, along with the brake-specific fuel consumption. The usage of the weighted aggregated sum product assessment technique in conjunction with the Simulated Annealing Algorithm and the Genetic Algorithm was to optimise engine-operating parameters in a hybrid manner.

Ammonium picronitrate (APN), an organic crystal is grown by slow solvent evaporation method and characterized using XRD, FTIR, SEM, AFM, Chemical etching, VSM, TG–DTA, Laser damage threshold, and Luminescence studies. According to single-crystal XRD studies, the APN belongs to the Orthorhombic crystal system. SEM, AFM, and Chemical etching analysis has been carried out to study the surface characteristics. LDT studies have been carried out using Nd-YAG laser. The conditions like melting point and decomposition of sample have been studied by thermal analysis. The peak wavelength from Photo-luminescence spectra was found to be 552.60 nm. VSM studies have been carried out to record the magnetic response.

Micro-Grid concept in the electrical power system has improved efficiency, flexibility, and efficiency. The nature of Renewable Energy Source (RES)-based distributed generations like nonlinearity, intermittent in generation uncertain prediction and control application invites some technical challenges. Power quality issues are some of these technical issues which can be investigated through sag/swell, frequency, and power factor in AC Micro-Grid (MG). These Power Quality issues can be improved by the use of some custom device or by application of some controllers. Here in this study an Adaptive Backstepping Sliding Mode (ABSSMC) controller is designed to improve the power quality (PQ) problems in an AC Micro-Grid (MG). There are three types of Distributed Generators (DGs) like photo voltaic (PV), wind generating system (WG), fuel cell (FC), and super magnetic storage are integrated with the micro-grid. The model included with popular distribution FACTS such as D-STATCOM. The model is simulated by controlling the D-STATCOM parameters with the proposed controller and the result obtained are compared with that of PI controller.

Owing to high demand for power and higher utilization of fossil fuel, grid-connected PV Solar power system plays a major role to meet this demand. A substantial advantage of photovoltaic systems is the usage of ample and free energy from the Sun. However, high cost and low efficiency of PV systems are the major obstacles for their usage. This paper deals with an experimental study of 700 kW Solar PV grid-connected system using SCADA system. Based on real-time observation, the data are collected from January 2021 to December 2021. The parameters such as energy supplied to the grid, energy output, and annual performance ratio are considered for analyzing the performance of the solar PV system. The total annually generated electrical energy was 873,640 MWh. The highest and lowest performance ratio was 77.77% for February 2021 and 59.80% for November 2021, respectively. The actual performance ratio of the plant is 74.46%. This study provided an insight into the performance of solar PV plant and ways for improving its efficiency thus aiming to maximize the PV production.

To increase the reliability of hybrid renewable energy system (HRES) with grid, a proportional-integral (PI) controller for a dynamic voltage restorer is suggested in this paper (DVR). Solar PV array, wind, and fuel cells are considered as HRES in this work. Three boost converters, one for each source, connect these three sources to a central DC-link. The MATLAB software tool is used to calculate the best size of the three suggested sustainable power. The DVR control is achieved by adjusting the load voltage under a variety of unusual working scenarios. Voltage sag, three-phase fault, voltage imbalance and voltage swell are the three situations. Two PIs are employed to regulate the D-Q axis voltage signals and modify the Gate pulses of the pulse width modulation (PWM) used to operate DVR. These D-Q axis coordinates represent the inputs to the two PIs at any loading condition. The PWM pulses are represented by the outputs of the two PIs. The input/output data is provided by automatic feature PI controllers, which had been introduced for managing the load voltage by DVR-PWM pulses under various abnormal operating parameters. The suggested PI-DVR controller improves system performance by enhancing the voltage, current and power waveforms of each producing source. The system ensured that the three renewable sources continue to operate during faults by adjusting the defective line voltage, hence enhancing the low voltage ride through (LVRT) capabilities. Furthermore, overall harmonic distortion is minimized.

This work proposes optimally tuned turbine governor parameters of a hydro power station to improve the dynamic stability of a variable wind-penetrated power system network. A four-machine two-area system with four hydro generators is being considered for this study with wind sources. The governors of generators are coordinately controlled by a modified DE with WOA algorithm. The input wind penetrations are varied to create oscillations in power systems, and these oscillations are damped by turbine governor action with an optimally set of their parameters. The variation in angular frequency is taken as input to control action, and Woodward-type governors have been considered for all hydro generators. The objective function has been considered subject to sudden raise in input power to generator by 10%. It is observed that optimized hydro governors can efficiently provide sufficient damping torque to the electromechanical oscillation to enhance dynamic stability of power system due to variable wind source penetration.

In this study, the aim is to generate a modified double circular arc tooth profile for a gear pair. The modified double circular arc gear tooth profile consists of modified double circular arcs and an involute profile joining the circular arcs. The geometrical analysis for the proposed double circular arc is presented with all the geometrical parameters. Further, an external-external gear pair with the proposed double circular arc is modeled for finite element simulation. The results are then compared with that of a gear pair with standard involute profile. The result shows that the maximum bending stress and radial stress developed in modified double circular arc tooth profile is less by 5–6% than the stresses in standard involute tooth profile.

Enhancing the efficiency of plate heat exchangers (PHE) lowers the consumption of energy in the thermal processing of food, beverages, and dairy units. An experimental study is incorporated to analyze the performance of thermal characteristics of PHE using alumina/water (Al2O3/H2O) nanofluid used during the mango juice thermal processing. The setup comprises two flow loops for hot fluid (nanofluid) and cold fluid (mango juice). The inlet temperature of cold fluid is kept constant with a varying inlet temperature of hot fluid from 50 to 60 °C and a mass flow rate from 4 to 7 LPM. The experimental results show an improvement in the thermal performance especially the heat transfer of nanofluid upon increasing the particle concentration. For Re = 350, the improvement in heat transfer coefficient is achieved to be twice for 0.2% and 2.5 times for 0.3% with respect to that of 0.1% particle concentration.

This paper validates the potentiality of WS2 as a solid lubricant at high weight concentration in 78% Al-10% Al2O3-12%WS2 hybrid composite fabricated in powder metallurgy method through tribological and corrosion analysis. Porosity is found to be 1.72% with an average hardness value of 61.46 HV. The wear loss is studied with 5 N and 1.5 m/s sliding load and velocity, respectively. The average wear loss is found to be 0.0095 gms. The coefficient of friction and the minimum corrosion rate is 0.161 and 0.01465 mm/year for 120 h, respectively. Corrosion analysis indicates the decrement in corrosion rate as the exposure duration increases.

Non-traditional machining has become a popular choice for machining of hard and difficult-to-machine materials for generating complex profiles with high dimensional accuracy and surface integrity. In order to improve the performance of the processes, key machining parameters need to be optimized as the costs involved in these processes are comparably high. In this paper, four non-traditional machining processes are considered to optimize using a recently developed metaheuristic technique known as the simple optimization technique (SOPT). The performance of SOPT is compared with the performance of some well-known metaheuristic techniques used to solve the same problems. It is observed that SOPT performs in a superior manner in all these problems as compared to other metaheuristic algorithms. Being one of the simplest algorithms and ability to reach near-optimal solutions for complex, constrained optimization problems makes this algorithm a good choice for solving real-world optimization problems.

For many decades, waste management strategies have been a major source of concern. Waste management strategies consist of hazardous waste and non-hazardous waste. Hazardous waste is defined as waste that poses a significant or potential threat to the environment as well as human health. Hazardous waste handling may be quite difficult. Even on a small scale, improper hazardous waste management can threaten both human health and the environment. The current research is based on the management of radioactive waste generated in ‘Nuclear Medicine Department’ and the Department of ‘Radiation Therapy’ of Siksha ‘O’ Anusandhan (SOA) Deemed to be University, Bhubaneswar. At the hospital, radioactive materials are employed in both therapeutic and diagnostic procedures, and exposure to it is generally harmful to human health. Although radioactive wastes cannot be eliminated, waste minimization, waste reduction, and safe disposal should be implemented by India’s Atomic Energy Regulatory Board (AERB) norms.