Advances in Mechanical Engineering and Material Science

Two biggest problems in present Indian pulverized coal combustion (PCC) power plants are that large capacity of PCC plants has reached retirement due to age limit and huge coal import from outside countries. Increasing the utilization of circulating fluidized bed combustion (CFBC) technology in India is the best solution for renovating old PCC boilers to extend their life to 20–25 years and reducing coal import by increasing the utilization of local low-grade coals in effective manner. Even though CFBC technology is economically sound, technically feasible and environmentally friendly than PCC technology, CFBC technology utilization in India is still in the nascent stage. To increase the utilization of CFBC technology in India, more design models are needed to come out on Indian low-grade fuels such as Indian lignite and high ash coal for predicting thermal and environmental performance, analysing design and optimizing processes in operation at wider range of operating parameters. In this paper, a CFBC boiler design modelling which is developed by programming code of visual basics for applications (VBA) software is explained. To check the accuracy, the design methodology is applied to validate the practical data of different CFBC units on various aspects such as thermal performance model (boiler efficiency, flow rates), hydrodynamic model (solids volume fraction), heat transfer model (water wall heat transfer coefficient) and sulphur capture model (SO₂ emissions). The design procedure which is applied for validation process gives satisfactory results on different aspects, and the qualitative agreement is found between predicted values and actual measurements.

We explore the subtle role of surface tension on condensate drainage onto a horizontal cylinder. Our study considers a subcooled cylindrical surface exposed to a pool of saturated water vapour. The condensate film flow is assumed to be  steady and laminar. We appropriately reduce the Navier–stokes equations in the cylindrical coordinate system invoking certain assumptions and build a simplified mathematical theory. We model the effects of surface tension by the well-known Laplace formula. We have used the temperature- dependent thermos-physical properties of liquid water for generalisation. The Reynolds’ correlation is used to predict the viscosity of the liquid water. The model governing equations are solved for a suitable set of boundary conditions by the Runge–Kutta method. It is observed that the role of surface tension is predominant near the bottom of the cylinder, whereas it is reasonably weak in the upper part of the cylinder. We found that the film dynamics strongly depend on the cylinder radius. Furthermore, we develop correlations for predicting the local and average Nusselt number, which would be useful for engineering applications.

A solar chimney power plant (SCPP), consisting of four essential components: a chimney, a collector, a turbine and an energy storage layer, is a typical kind of thermal power plant that converts solar radiation into electricity using natural convection. The collector is the most important part of an SCPP, where the air is heated up due to solar radiation. The heated air finds its path through the chimney, resting vertically at the central portion of the collector. Thus, a better collector design always ensures greater effective buoyancy, considered as the driving mechanism of the turbine. Here, we utilize artificial roughness elements either at the roof or at the ground of the collector to enhance the effective heat transfer and, thereby, the net buoyancy. We consider rectangular roughness elements, the height varying from 4 to 25 mm. The parametric study is performed by computational fluid dynamic (CFD) simulations incorporating conjugate heat transfer effects. The fluid and solid domains of the SCPP are resolved separately in the simulations by solving the Navier–Stokes equations and the Laplace equation, respectively. The standard k–Ɛ model resolves the turbulence within the fluid domain. Finally, we obtain that the ground roughness yields better performance than the roof roughness. The maximum overall performance is achieved at a ground roughness height of 11 mm.

The size of utility-scale wind power plants and number of installations are increasing constantly due to growing demand for wind power and to combat climate change. One of key issues posed with large size turbines is longer blades with higher blade tip speeds which generate higher aerodynamic noise levels and cause deleterious health effects such as annoyance and stress for inhabitants near turbines. In this paper, the effect of log-law and power law wind shear profiles on the sound power level is investigated when turbines operate in neutral atmospheric boundary layer conditions. Brooks et al. [1] and Moriarty & Migliore [2] models have been implemented for predicting turbulent boundary layer trailing edge noise and inflow broadband noise levels from blades of 2 MW wind turbine. Results demonstrate that using power law exponent range of 0.05–0.2, inflow noise increased by 2–5 dB for entire frequency spectra, while trailing edge noise increased by 2 dB for f < 1 kHz. With log-law profile, the trailing edge noise showed a change of 10 dB while for inflow noise showed change up to 5 dB when surface roughness varied from 0.01 to 0.1. The overall noise levels predicted by both models using power and log-law have been validated with measured data of GE 1.5sle and Siemens SWT turbines at wind speed of 11 m/s. It was found that overall noise levels obtained using power law agreed with experiment data within 2 dBA, while log-law predictions deviate by 4–7 dBA for f < 1 kHz and within 1 dBA for f > 1 kHz in the frequency spectra.

In our present analysis, we explore the impact of the magnetic field on the Couette flow occurring within a duct that contains a porous material. This investigation incorporates considerations of viscous dissipation and local thermal non-equilibrium (LTNE). The lower plate experiences movement and is exposed to isoflux boundary conditions, whereas the upper plate remains stationary and adiabatic. To describe the one-directional flow within the porous region, we utilize the Darcy–Brinkman (DB) model. The investigations also aim to quantify the effects of the Hartmann number (M_W), thermal conductivity ratio (κ), Brinkman number (Br_W), and Biot number (Bi_W) on enhancing heat transfer. Analytical solutions are derived for the governing equations, providing fully developed profiles of Nusselt numbers and dimensionless temperatures for both the fluid and solid phases. In the Couette flow model, the presence of a magnetic field impacts the temperature distribution in both phases. Furthermore, irrespective of the Hartmann number (M_W) in the Couette flow, the temperature in the solid phase is consistently higher than that in the fluid phase, thereby confirming the existence of local thermal non-equilibrium (LTNE).

Thermoacoustic cooling is a method that converts acoustic power to temperature differential, which is then utilized to reduce the temperature of a hot body via heat exchangers. A typical thermoacoustic cooling system consists of a resonator, stack, driver and heat exchangers. Any thermoacoustic cooling system is categorized based on the frequency at which it operates which again controls the geometry of the resonator. A half-wavelength resonator will have two pressure antinodes, where stacks can be placed to obtain the temperature difference. The main objective of the present work is to design a half-wavelength resonator with two-stack arrangement and to analyse and compare the refrigerator’s performance for various types of stacks. The resonator’s length for the cooling system is chosen as 1 m, and it operates at a frequency of 500 Hz with helium as a working fluid at a temperature and pressure of 288.05 K and 10 bar, respectively. The drive ratio of the refrigerator is 0.03. The stacks are 4.295 cm in length with a thickness of 0.5 and 1 mm spacing between the adjacent stack plates. The placement of stack 1 is 35 mm from the driver end and of stack 2 is 35 mm from the closed end of the resonator. DeltaEC is an open-source tool used by many researchers for thermoacoustic problems. DeltaEC simulations for parallel, rectangular and circular type stacks show a temperature difference of 37.27 °C, 40.05 °C and 53.05 °C at stack 1, whereas a temperature difference of 8.07 °C, 12 °C and 20 °C at stack 2, respectively. Introducing ambient and cold heat exchangers adjacent to each of the stacks makes it possible for the refrigerator to take two heat loads at the same time. This increases the net cooling capacity of the refrigerator.

Liquid fuel injection in the intake manifold is the source of fuel supply in the case of a gasoline engine equipped with a port fuel injection (PFI) system. The injected fuel breaks into small droplets which increases the vaporization rate and leads to proper mixing with the intake air. The amount of the injected fuel significantly influences the air–fuel ratio and as a result controls the combustion and emission formation. In the present work, a low-cost system is developed to measure the fuel flow rate of a PFI injector. The effect of fuel injection pressure, injection pulse width, off time between pulses, and fuel properties on the mass flow rate are studied. A solenoid-operated port fuel injector is taken for the study. A high-pressure chamber is designed and manufactured to control the injection pressure. An Arduino Uno board is used to control the pulse duration of the solenoid valve of the PFI Injector. Two fuels, diesel and petrol, and three different injection pressures (2, 4, and 6 bar) are considered for the study. The solenoid opening timings or the pulse width is varying from 2 to 10 ms. The off time between the two pulses is also varied. The experimental results show that increasing the injection pressure or opening time of the solenoid (pulse duration) increases the mass flow rate, but there is no effect of the off time between the two pulses on the mass flow rate. It is also noticed that different fuels show different mass flow rates at the same injection pressure and pulse duration.

Adding a small concentration of surfactant additive in pure water considerably decreases the surface tension of the aqueous solution at the liquid–vapor interface and decides the asymptotic limit of reduction in surface tension with increasing additive concentration. The present investigation is to pool boiling heat transfer enhancement of aqueous carrageenan solution with and deionized water with and without carrageenan additive. Firstly different concentrations of carrageenan with deionized water has prepared, i.e., 100, 200 ppm. All experiments were carried out in saturated solutions at atmospheric pressure. Bubble behavior was studied using a Canon camera operating at 100 frames per second. The investigation was conducted at variable heat fluxes to check the effect of heat flux on bubble growth. The higher concentration of additive (carrageenan) 200ppm shows a 54% increment in HTC. The tiny bubble was observed at a higher heat flux of 854 kW/m², whereas additive bubbles could not be captured due to the milky color of the solution. The present study relieved the effect of additives on the heat transfer coefficient due to the change in thermal properties.

Streamlining and boosting the effectiveness of Morse code communication are a major challenge that limits the application of Morse code in real-life and secure and flawless communication. The main objective of this research is to automate and increase the efficiency of short-range Morse code communication by using multiple laser diodes which allow each message character to be encrypted and transmitted simultaneously in place of the laborious and time-consuming traditional method of Morse communication. In the present approach, message characters are transmitted as a whole, one character at a time instead of a dot (.) or dash (–) at a time. The light rays are projected onto a screen at the transmitter side, and a camera on the descriptor end captures the projected rays and decrypts them using image processing. This reduces the time taken to transmit messages by a significant amount, enabling faster and more reliable Morse communication. Upon entering the desired message on the transmission side, it is encrypted using multiple layers of pangram cryptography. This message is transmitted letter by letter via the Arduino Mega ports onto the screen. The encryption uses a randomized set of pangram keys at each level, making it robust to interceptions and decryption by third parties.

Visual impairment affects approximately 285 million people worldwide, the profound challenge faced by those who are visually impaired or blind lies in the intricate task of maneuvering through different surroundings. The intricate nature of navigating both indoor and outdoor spaces poses significant difficulties for people with visual impairments. This paper presents an innovative undertaking that strives to address this very challenge by developing a cutting-edge robot dedicated to guiding the blind securely through various environments. Employing a sophisticated amalgamation of diverse sensors and a high-resolution camera, the robot adeptly identifies obstacles and furnishes the user with real-time information pertaining to their immediate surroundings. Remarkably, this state-of-the-art robot can be seamlessly operated through voice commands, facilitated by a bespoke mobile application, thereby enabling users to effortlessly guide it to their desired destinations. Equipped with comprehensive audio feedback capabilities, the robot effectively communicates crucial details to the user, encompassing obstacles, directions, and more. This robot can help blind people to navigate unfamiliar environments and travel independently.

Any machine component or structure can fracture due to the presence of cracks. With the assistance of finite element tools, we can only dissect the stable crack growth that requires much computational time and is vulnerable. This work developed several ML models using supervised machine learning algorithms and compared their performance. These models have shown decent precision in detecting the crack growth behavior of a pre-defined semi-elliptical crack embedded in a cantilever bar. The correlation coefficient R squared (R²), mean squared error (MSE), root mean squared error (RMSE), and mean absolute error (MAE) were used to evaluate and compare the performance of the developed ML models. The accuracy of the crack growth forecast is found to be ~ 86.47%, ~ 93.68%, ~ 91.50%, ~ 92.04%, and ~ 94.64% for linear regression (LR), quadratic polynomial regression (QPR), decision tree (DT), random forest (RF), and k-nearest neighbor (KNN), respectively; among them, KNN had the best prediction accuracy.

Air travel has seen some rapid changes and development since the dawn of human flight in 1914. Scientists and researchers have since been in the lookout for new and better technology to help humans fly in a more efficient and comfortable way. Us, humans, have adopted the Traditional Aircraft Wing Body (TAW) as the basis of aircraft design. But it has its own cons, namely drag produced by the body, vortex generation at the wing tips and the fuselage generating little to no lift. Hence, we bring forth a concept design—Closed Blended Wing Body, with which we can minimize the vortex generation by incorporating fuselage made up of wing section, eliminating wing tips, giving the vertical connectors the ability to help with the directional stability, thus giving a higher L/D ratio and making a more efficient aircraft. This paper aims at testing the structural stability of the design concept.

Micro-perforated panel (MPP) combined with desired cavity depth is considered as a next-generation sound absorber and a better alternative due to the improved acoustic performance in low-to-medium frequency range and sustainable features in hostile environments compared to the traditional porous materials. A single-layer MPP absorber facilitates absorption in one to two octaves, which can be improved using multiple MPPs in the absorber structure. The acoustic impedance of the single-layer MPP absorber is estimated using Maa model and equivalent electro-acoustical circuit (EAC) analysis. The predicted absorption coefficients of the single-layer MPP absorber were validated through measurement in two microphone impedance tubes or numerical analysis in which the actual experimental conditions were simulated. In this study, the absorption characteristics of double-layer MPP absorbers are better predicted through the transfer matrix method (TMM), in which individual transfer matrices of constituting elements of the absorbers are considered. The predicted results are validated through a finite element analysis (FEA) which incorporates the determination of acoustic impedance through a pore and the effect of pore–pore interaction for MPP. The sound absorption characteristics of double-layer MPP absorbers obtained from FEA show good agreement with the predicted results, thus making the proposed FEA reliable. Moreover, the variation in the sound pressure level of the double-layer MPP absorber along the propagation direction is illustrated, justifying the sound absorption phenomena.

As electric cars (EVs) become more widespread, research into battery life is becoming highly significant. Electric car batteries are now constantly connected and transmit information on a massive scale. The huge amounts of data produced, quite apart from the widespread use of the internet by these battery packs, provide new challenges for researchers and regulators. A unique deep learning model with use of internet of things (IoT) is suggested in this paper to produce a universal and accurate Li-ion battery aging prediction. On the other hand, deep learning (DL) is an efficient strategy for handling IoT problems including data analysis, prediction, and categorization. However, it is challenging to get the best data for deep learning in IoT for real-time prediction. The accuracy and robustness of prediction will be determined by data collecting components such as sensors and cameras. In this article, deep learning model Long Short-Term Memory (LSTM) method is used to training and testing of the deep learning architecture. Root Mean Square Error (RMSE) value for the deep learning model is 0.69, which will accurately predict vehicle battery pack data. Numerous articles have been published on improving deep learning models for RUL estimate of battery packs; however, there is no research of capacity degradation of battery pack estimation using IoT and deep learning approaches in the literature. In this research, a strategy for estimating the RUL of an electric car battery pack is described using deep learning and IoT.

Chilies and their products have become popular in everyday life. However, in Vietnam today, their care and harvesting of them are done mainly by manual methods. As a part of the project to develop an automatic harvesting robot, this research focuses on detecting and locating chili fruits in three-dimensional space. First, the Yolov5 model is fine-tuned and trained to detect the fresh chili fruit object. Then, a stereo camera is used to capture an image and determine the disparity of the fruits in the left/right images using matching methods. The distance and 3D location are estimated by the triangle method via the disparity. In addition, an image calibration method is also implemented to obtain the camera's focal length parameters as well as to reduce the camera's fisheye effect, increasing estimation accuracy. The model can detect a chili at a size of 9.4 × 55 mm up to a distance of 600 mm and an image resolution of 480 × 480 pixels. In further studies, this position data will be transferred to the robotic arm to perform necessary operations such as harvesting and avoiding obstacles. The positioning accuracy as well as the ability to detect small fruits would be improved to enhance the working ability of the whole system.

In orthopedic surgery, various implants, such as screws, plates, and nails, are used to fix fractured bones. Often the fracture pattern influences the use of such implants, which facilitates the union. The conventional screw used mainly depends on the significant structure of the thread design. However, screws are used independently or with plates for the fixation of fractures of bones. Axial compressive load, bending load, and rotational load (Torsion) are experienced by the bone of the human body. Therefore, the orientation of screws in the bone is exposed to such limitations. Hence, it has been pertinent to analyze the efficacy of the direction of the screw being fixed in bone concerning immobilization of the fracture site for the union. In this study, the effect of axial compressive and rotational loading has been given prime importance since the bone has been minimally exposed to bending load. Further comparative analysis of maximum deformations and stresses for two different orientations of screws subjected to other limitations and torques simultaneously have been performed. A cortical section of the femur bone of a middle-aged man has been modeled, and subsequent finite element method (FEM) analysis was conducted subjected to comprehensive axial and rotational loads. It has been observed that the maximum deformation (8.1252 mm) and maximum stress (3179.9 Mpa) have been more in the case of the screws placed at 45° to the long bone axis than the screws normal to the long bone axis.

Over the last few years, unmanned aerial vehicles (UAVs) have been widely used for various purposes such as payload dropping, thermal imaging scanning, and spraying of agricultural pesticides. This report focuses on the design of a multirotor UAV with the primary objective of picking up and releasing a payload. The vehicle is a quadcopter and uses electronic servo motors for the payload release mechanism, which is accomplished by the quadcopter's landing gears using a four-bar mechanism. This paper highlights the various possible technologies used to minimize human efforts in payload-dropping operations using quadcopters. The payload release mechanism demonstrates innovation in design. The discussed system involves designing and building a simple and cost-effective prototype. The promising results of this method pave the way for future research on using quadcopters for product delivery.

In order to overcome the self-starting issues in vertical axis wind turbines (VAWT), it is proposed to introduce the deflector plates as a power augmenter. In this study, a computational analysis on a wind turbine rotor with three-bladed NACA 25112 has been performed to understand the significance of power augmenters and their impact on the overall performance of the wind energy conversion system. The rotor motion of the proposed model has been simulated by introducing a sliding mesh technique with reference to the SST-turbulence model. The simulation has been performed at different flow velocities ranging from 4 to 7 m/s to understand the effects of power augmenters with respect to the enhancement in the initial torque. The observed results showed a significant improvement in the enhancement of initial torque, the aerodynamic behavior of the airfoils, and the power coefficient of the wind turbine.

Tennis players frequently practice from one side of the court without an opponent on the other side to return by hitting many balls. During practice sessions, personally collecting the balls took more time. The aim of this project is to design and construct a tennis ball-collection robot that can automatically gather the balls from one half of the court, releasing the player to rest rather than physically collecting the balls. This work includes a detailed design, a background data, prototypes, and concept models. We developed a novel autonomous or semiautonomous mobile robot for the purpose of gathering tennis balls for our capstone project. Two independently operating wheels help the robot move, while a castor serves to stabilize it. Tennis balls are pushed into a basket on top of the robot by a rotating brush, which serves as the novel collection mechanism. The drum spins with the help of a motor at a speed that has been confirmed through trial. To ensure that the adopted concepts and conceptual designs are practical and solid, three subsequent functional prototypes have been conceived, constructed, and tested. Tennis players can also use Arduino programming to direct the robot to move and collect the balls if it is unable to locate, identify, and gather tennis balls on its own. All tennis balls on the court will be recognized and localized in future using global cameras and a centralized image-processing system. Furthermore, it is believed that this system will handle navigation for mobile robots as well as path planning for the best possible outcome.

A new method to desalinate water by making use of swollen hydrogels under externally applied pressure-difference-driven diffusion is being proposed. The swelling process of hydrogel involves diffusion, polymer–solvent interaction, and mechanical deformation. The present research aims to investigate the use of FEA model to simulate hydrogel as a semi-permeable membrane. Diffusion of water molecules in hydrogel is modelled using Fick’s law, polymer–solvent interaction described by the Flory–Huggins mixing theory and mechanical deformation reported with the theory of rubber elasticity. The FEA model yielded a set of partial differential equations with ordinary differential equations for which COMSOL Multiphysics 5.5 is selected as the simulation software. A parametric analysis is conducted to evaluate the overall significance of the model parameters on hydrogel’s behaviour. Reproduction of the hydrogel’s poroviscoelastic behaviour to the exterior incentives and the transport phenomena of species through hydrogel has been successfully demonstrated and validated for a new methodology of water desalination considering NaCl (salt) as a permeate. The salt rejection ratio has been estimated, and it is found to be 40% with an average salt volume fraction reducing from 0.5 M to 0.3 M. The suggested model may also be explored to design and optimize hydrogels for biological separations.

All living things have the fundamental need to consume safe drinking water on a daily basis; therefore, it is essential to have an understanding of the shortage of water and the primary freshwater supplies. With the rising levels of pollution caused by both industry and people, the amount of potable water that is available is coming under growing threat. The present work makes use of latent and sensible materials to maximize the distillate yield of a single basin solar still. Utilizing latent and sensible material enhances the production of distillates yield and overall performance of solar still. Latent material paraffin wax enhanced nocturnal distillates, while suspended wicks increased the rate of evaporation for daytime productivity. The experimental investigation utilizes 5,500 g of paraffin wax because it provides the highest cumulative efficiency. The overall productivity of paraffin wax and paraffin wax with suspended wicks increased by 27.65% and 30.12%, respectively. In a modified solar still, the overall maximized distillate yield was recorded as 4.24 kg/m² and the cumulative efficiency was 78.62%. The single component temperatures of solar still show significant changes in temperature throughout the day. It was determined that the utilization of wicks as a sensible material enhanced the evaporation rate and the quantity of distillate produced. 32.8 g of maximum distillates were obtained by using wicks with a length of three inches and a depth of 3 cm.

Wire arc additive manufacturing (WAAM) is presently growing as the major hub of research bodies throughout the universe. This is straightly noticeable in an enormous paper published recently pertaining to a myriad of distinct matters. Additive manufacturing is the quickest technique for the development of a product, and this is indicated by scientific industrial sections. It reinstated conventional ways in a few industrial circumstances by bringing down material utilisation. WAAM is much closer to welding in the process as it makes use of stratified deposition to design huge portions with less intricacy. Numerous experiments and estimates have evolved to ameliorate material properties concerning the remaining deformities like crackling and spattering. WAAM has acquired popularity as it has many benefits and very high efficiency. It increases the efficiency of the material and has a rate of deposition which is again very high and the lead time is shorter, the performance of the components is better, and the inventory cost is very low. This review is proposed to provide an appropriate summary of the field of WAAM. The inscribed matter in this review is embraced but not restricted to the materials. Various processes like monitoring, path planning, and modelling fall into the operations and techniques of WAAM. The alliance of detecting numerous authors into a consolidated form is the essence of this review. It is proposed to discover various fields in which the work is mislaid and in what ways the distinct topics can be manually integrated. A crucial estimation of introduced research along with welding research and a remarkable focus on additive manufacturing will accomplish this review.

Expulsion is a familiar occurrence in the resistance spot welding process, which deteriorates the weld quality. Among various parameters, applied pressure significantly impacts in the expulsion of molten metal, which is undesirable. To understand the influence of electrode pressure on joint strength and mode of failure, thin sheets of Ti-6Al-4 V and SS316L are welded together in overlapped conditions using the RSW process at varying electrode pressure of 3, 4, 5, and 6 kg/cm², keeping other parameters constant. Further, joint strength and mode of failure are investigated. The results showed that with an increase in electrode pressure to an optimum value, i.e., 3–5 kg/cm², the strength of the weld joint is enhanced. In contrast, increasing electrode pressure beyond the optimum value leads to the expulsion of material, which restricts the nugget growth, leading to a reduction in joint strength.

The current work describes the development of a numerical model to accurately predict the occurrence of various defects during FSW of pure copper using thermomechanical responses. The developed numerical model examines the effect of varying tool dimensions on thermomechanical responses and defect formation. The tool traverse and rotation speed are kept constant at 30 mm/min and 1200 rpm. The shoulder diameter is varied between 14 and 28 mm. The 14 mm tool produces an imperfect weld with surface and sub-surface tunnel defects, whereas the 18 mm tool eliminates the surface tunnel defect. An increase of the shoulder diameter to 28 mm further reduces the extent of sub-surface tunnel defect. The increase in the shoulder diameter eliminates the surface tunnel and reduces the height of the sub-surface tunnel by about 50%. Significant material velocity, strain rate, and temperature on the retreating side (RS) produces the sub-surface tunnel defect on the advancing side (AS). The model can predict the initiation and advancement of the tunnel defect along the welding length. The velocity profile indicates that the material is equally distributed between the AS and RS behind the tool at the conclusion of the dwell stage. Alternatively, the material deposition becomes unequal between the AS and RS as the tool starts traversing. The tool–workpiece interface observes less stress and alternatively high strain, strain rate, and velocity distribution compared to the rest of the workpiece.

Selective laser melting (SLM) is an additive manufacturing (AM) process suited for printing three-dimensional metallic components. Throughout the SLM process, the thermal characteristics are crucial in ensuring the build quality of the print. Therefore, it becomes essential to determine the temperature distribution of the SLMed parts. Experimental approaches to address this issue are capital and time intensive. Numerical modelling studies for temperature distribution generally simulate single tracks, which cannot be extrapolated for the whole SLMed part. In this study, the multi-track, multi-layer SLM builds of IN718 were simulated using a three-dimensional finite element model. The temperature-dependent material properties were considered in modelling, and the laser scanning beam was described as a moving volumetric heat source. The temperature distribution on printed layers was evaluated, after which thermal profiles from simulated layers were extracted, and the permissible limit exercise was performed to identify potential hotspots. The predicted thermal history can also be used to optimise SLM process parameters. Further, the effects of scan strategy (layer start and rotation angle) on the temperature distribution were studied. It is evident from the results that the layer rotation angle affects the thermal history as the length of the scan vector changes depending upon the scan strategy used in a layer. This modelling approach can be utilised to further develop the microstructure evolution based on the simulated thermal history for SLMed parts.