Journal of Mechanical Engineering and Sciences

Sustainable considerations in additive manufacturing processes: A review

Sat, 30 Mar 2024 00:00:00 +0000

Efficient waste management practices are becoming increasingly necessary due to the negative environmental and health impacts of waste generation and disposal. One type of waste that has received particular attention is electronic waste (e-waste). This category of waste has the potential to cause significant environmental harm if not disposed of properly. The management of e-waste is crucial in the electrical/electronic industry which has led to the creation of models and institutional legislature to promote sustainable production processes. Among these processes, Additive manufacturing otherwise referred to as 3D printing is particularly effective in reducing waste generation and energy requirements by reusing spent parts and products as feedstock. Sustainability in the manufacturing and production sectors can be promoted through the inculcation of certain practices. Of these practices, reusing e-waste that would otherwise be disposed of in landfills has the potential to promote environmental cost savings. This article introduces the potential of e-waste being integrated into the manufacturing sector to promote sustainable production. The article also addresses the problem of geometric e-waste generation and suggests an efficient way of reusing waste from the electrical and electronic industries.

Review of path planning of welding robot based on spline curve

Guan He, Teo Hiu Hong, Moey Lip Kean — Sat, 30 Mar 2024 00:00:00 +0000

This paper assesses the efficacy of intelligent path planning for welding robots utilizing splines. Traditional path planning methods can result in inefficient and inaccurate welding operations. The study reviews current research and case studies to appraise the practical application of spline-based path planning across diverse industrial scenarios. It underscores the benefits of discovering the shortest path and reducing cycle time while acknowledging challenges such as calibration accuracy and sensitivity to sensor data noise. The introduction of artificial intelligence algorithms in automobile welding path planning enables a more precise replication of the body's design curve, ensuring the continuity and smoothness of the welding process. This, in turn, fosters further automation and optimization of the automotive welding manufacturing process. The current research concentrates on integrating intelligent optimization algorithms and spline curves to provide an efficient and intelligent method for welding path planning. Intelligent path planning based on spline curves demonstrates significant potential in enhancing welding efficiency, determining the shortest path, and holds promising applications in the broader research field of welding path planning.

The influence of helmet certification in motorcycle helmets protective performance

Sat, 30 Mar 2024 00:00:00 +0000

The convenience of online shopping has increased access to a vast array of helmet options and deals for motorcyclists. However, the e-commerce enables an influx of unverified and potentially hazardous helmets lacking the rigorous quality control into the market, hence, placing unaware bargain seekers at risk. The non-certified variants questions in terms of impact protection abilities because they visually look similar to certified helmets. This study compared certified full face and open face helmets against their non-certified counterparts by analysing injury predictor metrics. Using a test rig simulating 5.58 ± 0.29 m/s impacts, an anthropomorphic test device wearing both helmet types and certification statuses measured peak resultant linear and angular accelerations, head injury criterion alongside brain injury criteria scores. The data revealed comparable side and rear impact performance between non-certified and certified helmets. However, frontal impacts exposed deficiencies without certification. The non-certified full face helmets registered over twice the peak linear acceleration of certified while open face types still exceeded certified by 40% in frontal impacts. Additionally, non-certified full face helmets indicated up to 100% predicted concussion risks in side and frontal crashes based on the angular accelerations. The poorer frontal impact and elevated injury odds demonstrate certification's key safety advantages that certification should not be ignored while it still providing more protection than no helmet. However, individual needs to carefully select helmets due to performance differences of helmets. Riders should ultimately prioritize proven protection given the severe consequences of head trauma though non-certified may suffice for some low-risk environments.

Effect of cutting clearance in shear-slitting process on the residual stress and cut surface quality of AA6111-T4 aluminum alloy

Łukasz Bohdal — Sat, 30 Mar 2024 00:00:00 +0000

The paper presents the problem of the correct selection of the cutting clearance during the cutting process of aluminum alloys on circular shears. Currently, production lines lack correct guidelines on how to set the cutting clearance depending on the type of aluminum alloy and its thickness. This causes defects in the products and accelerated wear of the cutting tools.The paper presents the results of experimental and numerical research related to the process of shear-slitting of t = 1 mm AA6111-T4 aluminum alloy. During the experimental studies, it was determined how the value of the clearance affects the characteristic features of the cut edge and deviations of the shape of the product. Using numerical tests, the influence of the clearance value on the stress values in the cutting zone was determined. For the AA6111-T4 aluminum alloy, the highest product quality was obtained using clearances h_c = 0.09 mm and h_c = 0.12 mm. The conducted experimental research can be useful on production lines in the aspect of the correct selection of technological parameters of the process due to the adopted energy and quality criteria.

Tensile properties and dynamic mechanical analysis of kenaf/epoxy composites

Sat, 30 Mar 2024 00:00:00 +0000

Kenaf fibre-reinforced polymer composites could offer low-cost, biodegradable, recyclable, and renewable materials. The hydrophilic kenaf fibres exhibit poor compatibility with the hydrophobic epoxy matrix as compared to their synthetic counterparts and ultimately, this may severely constrain their potential as a green composite material. This work aims to evaluate the tensile properties and dynamic mechanical analysis (DMA) of kenaf fibre composites reinforced with two epoxy systems as matrices, B and M resins. Neat epoxy samples and kenaf-reinforced composites with varying fibre loading, 15% and 45% were fabricated in the study. It was found that the tensile properties of kenaf composites are dependent on the epoxy resin systems and higher with reinforcement content. The tensile strength of M-15% and M-45% are 16.3% and 12.0% stronger than their counterparts. Determination of interfacial shear strength using a modified micromechanical model was employed showing that M-45 has a higher value than B-45%, 107.09 kPa and 90.28 kPa respectively. By DMA, in general, an increase in the storage modulus and peak height in the loss modulus was always higher with kenaf composites that were manufactured with the M resin system. The adhesion factor, A calculated from tan delta curves and cole-cole plot has shown the state of fibre/matrix adhesion level in each epoxy resin system. The SEM analysis indicates the presence of void spaces around fibres and matrix may attributed to the lower compatibility of the B resins system used in kenaf composites fabrication.

Optimizing ageing conditions for commercial NiTi archwires: Insights from thermal phase transformation and tensile deformation analysis

Sat, 30 Mar 2024 00:00:00 +0000

Superelastic nickel-titanium (NiTi) archwires are now commonly used as the standard archwire during the orthodontic alignment and levelling stage. They are preferred due to their ability to apply minimal force on teeth while allowing for a wide range of tooth movements. During orthodontic treatment, the orthodontist assesses the dimension and shape of the NiTi archwire to determine the amount and direction of force required to align misaligned teeth. The main contribution of this study is the parametric analysis and establishment of a set of optimal ageing temperatures and duration for the investigation of functionally graded nickel-titanium archwire using differential scanning calorimetry (DSC) and tensile deformation testing. The mechanical and thermal phase transformation behavior after ageing at six temperatures for duration of 15 minutes have been investigated using tensile deformation test and differential scanning calorimetry (DSC) test in this paper. Experimental results reveal that in thermal analysis as the ageing temperatures increase from 400 °C to 490 °C, the austenite finish temperature rises to a value between 9.53 °C and 35.48 °C, and subsequently decreases to 520 °C. The archwire specimen aged for temperature of 490 °C exhibited the austenite finish temperature of around 35.48 °C, and it is highest among the aged wire specimens closest to oral temperature. In tensile deformation, the ideal ageing temperature for orthodontic applications was determined to be 490 °C for 15 minutes, resulting in relatively low plateau slope 13.73 GPa with high superelatic ratio 12.04, and maximum plateau strain of 7 %.

Performance of tri-tubular conical energy absorber under axial compression

Asad Khalid, S. M. Rohaizan — Sat, 30 Mar 2024 00:00:00 +0000

Quasi static axial compression loading on tri-tubular cone (TC) has been carried out using LS-DYNA finite element analysis method. Tri-tubular cones of three arrangements; the first arrangement (model TC-1) consists of cone heights of 50 mm, 75 mm and 100 mm where the inner cone is the maximum height. The second arrangement (model TC-2) consists of cone heights of 100 mm, 75 mm, and 50 mm where the outer cone is the maximum height. The third arrangement (model TC-3) consists of three cones of the same height of 100 mm. Cone semi vertex angle of 20^o was maintained for all tri-tubular cones tested. Materials used for this research are glass, jute and jute-glass/epoxy. Crashworthiness analyses were performed to investigate the effect of material used, and tri-tubular cone arrangement on peak load. Crush efficiency, and absorbed energy were drawn and discussed. Failure mechanism of the fractured specimens was also discussed. Effect of number of layers and fiber stacking sequence were also investigated. Results show that the cone arrangement TC-3 gives better performance than the cone arrangement TC-2 followed by the cone arrangement TC-1. Maximum load obtained by tri-tubular cone type TC-3 was found higher 7.09% and 14.96% than TC-2 and TC-1 respectively for glass/epoxy. Material saving was achieved by using tri-tubular cones of different heights under compression. Material used has significant influence on the absorbed energy. Failure mode of tri-tubular conical energy absorber was presented and discussed.

Active suspension for all-terrain vehicle with intelligent control using artificial neural networks

Anis Hamza, Issam Dridi, Kamel Bousnina, Noureddine Ben Yahia — Sat, 30 Mar 2024 00:00:00 +0000

The automotive industry focuses on developing advanced protection and stability control systems, particularly for suspension and steering, to enhance vehicle comfort, luxury, and safety. This research presents an intelligent controller for all-terrain vehicle (ATV) suspension systems based on Artificial Neural Network (ANN) technology. The controller leverages ANN capabilities to optimize system performance. MATLAB simulations were conducted to evaluate its effectiveness under various disturbances. A comparative analysis compared the ANN regulator, classic ANFIS regulator, and passive performance in different disturbance scenarios. The simulation results demonstrate exceptional performance of the ANN-based controller in displacement reduction, speed, acceleration, and robustness. The controller effectively mitigates disturbances, enhancing overall suspension system performance. These findings highlight the advantages of employing ANN technology in ATV suspensions. This research contributes to intelligent control systems advancement in the automotive industry, specifically in ATV suspensions. The demonstrated improvements have the potential to enhance passenger comfort, vehicle stability, and safety across terrains. By implementing ANN-based controllers, automotive manufacturers can optimize suspension systems, leading to improved vehicle performance. Several indicators, including RMSE, MRE, and R², were utilized to test and validate the models. The R² values for the three quality parameters ranged from 0.989 to 0.999, indicating a high level of consistency in the predictions made by the ANN, a "5-12-1" structure is employed. The results of this study add to the expanding body of knowledge endorsing the efficacy of ANNs in simulating and optimizing quarter-vehicle dynamics.

Effect of substrate’s surface roughness on corrosion and wear rate of Ni-GO nanocomposite coating

Sat, 30 Mar 2024 00:00:00 +0000

Corrosion is a natural process that occurs when refined metal is converted into a more stable form, such as oxide, hydroxide, or sulfide. Wear is the failure of a surface due to dynamic contact between two surfaces. In offshore operations and environments, corrosion and wear are major problems due to the presence of corrosive and abrasive elements. The coating is a common surface protection method that enhances corrosion resistance and prolongs lifespan. In this work, a Ni-Graphene nanocomposite coating was fabricated using the electrodeposition method. This work aimed to fabricate a Ni-GO nanocomposite coating on mild steel with different surface roughness, to characterize the physical, mechanical, and chemical properties of the coating, and to investigate its corrosion and wear rate. The fabrication process involved preparing substrates coated with Ni-GO nanocomposite through a 45-minute constant current electrodeposition process. The coated specimens were characterized using X-Ray Diffraction Machine (XRD), Scanning Electron Microscope (SEM), Alicona Infinite Focus, Vicker’s Hardness Test, Raman spectroscopy, and Adhesion test. The corrosion and wear rate of the coatings were investigated using a Slurry Erosion tester and Salt Water spray, respectively. The results showed that the Ni-Go nanocomposite coating on a smooth surface roughness substrate achieved the highest microhardness, wear resistance, and corrosion resistance, with values of 468.8 HV, 0.182% weight loss, and 0.03% weight gain, respectively. This indicates that the specimen coated with a smooth surface roughness substrate provided better coating performance than the rough and medium surface roughness substrates.

Co-simulation approach for computational aero-acoustic modeling: Investigating wind-induced noise within two-way radio microphone ports cavity

Sat, 30 Mar 2024 00:00:00 +0000

Wind-induced noise (aeroacoustic) can cause problem with any outdoor microphone applications, notably impacting the performance of telecommunication mobile. One prominent source in two way radios is the microphone port cavity. In this article, the noise characteristics behaviour is studied at scale-up of microphone port cavity through computational aero-accoustics (CAA) numerical simulation and experimental test. This research aims to investigate the wind-induced noise (aeroacoustic) generated inside the microphone port cavity at various wind orientation angles (wind direction) and distance radii, r. A direct-hybrid co-simulation CAA method, utilizing the LES-WALE (Wall-Adapting Local Eddy-viscosity) and Ffowcs William-Hawking (FW-H) models, is employed to obtain the near-field noise source and far-field noise patterns inside a microphone port cavity. The simulations are conducted using the scFLOW2Actran software. Richardson extrapolation and Grid Convergence Index (GCI) are applied to evaluate the accuracy of the grid independency in numerical simulations.The findings reveal that the leading edge, centre and trailing edge are the primary noise sources and generations inside a microphone port. The study indicates that the noise level in the microphone port cavity is characterized by low frequency noise.The results indicates that at an observation of angles of 0° and distance radii of 0.2 m, the wind noise level is higher compared to other orientation angle and distance radii. This can be attributed to the proximity to the noise source at this location. The directivity pattern of noise propagation exhibits a typical dipole pattern observed at observation angles of 0° to 45°. Numerical results align well with the experimental results from the wind tunnel test, demonstrating the feasibility of the proposed approach for flow-acoustic coupling application. This research holds significant value for engineers as it provides a comprehensive understanding of the physical phenomena involved in microphone port design.

Investigation of collision estimation with vehicle and pedestrian using CARLA simulation software

Mohammad Sojon Beg, Muhammad Yusri Ismail — Sat, 30 Mar 2024 00:00:00 +0000

The effectiveness of object detection systems in diverse driving environments is crucial in the growing field of automotive safety. The increasing frequency of traffic accidents, especially at busy intersections with heavy traffic and limited visibility, highlights the pressing requirement for advanced vehicle detection systems. Prior to implementing the real-time experiment, it is advisable first to conduct a simulation in order to gain a deeper understanding of the practical implementation in real-time scenarios. On the other hand, this approach has the potential to reduce both time and cost significantly. The system utilised a software-based solution by implementing the CARLA simulator. This study aims to analyse vehicle detection at T-junctions, cross-junctions, and roundabouts using image data obtained from the CARLA platform. Subsequent analysis differentiates between vehicles and non-vehicle objects in the dataset. The model concludes by proposing Python-based integrative solutions to enhance object detection systems for diverse roads and atmospheric situations. The significance of this study is evaluating the probability of accidents by tracking key factors like vehicle speed, distance, and density on various road types. In future research, it will be essential to investigate how different weather conditions, including rain, haze, and low-light scenarios, affect on sensor performance, specifically LiDAR sensors. Advanced machine learning techniques are proposed to evaluate the effectiveness of the vehicle detection system in collecting key parameters like vehicle count, speed, and distance in junction and roundabout scenarios. These findings have important implications for the advancement of more efficient, context-aware detection systems in the automotive sector.

Optimization of insulation thickness of walls and roofs using energy, exergy, economic and environmental (4E) analyses

Aynur Uçar — Thu, 04 Apr 2024 00:00:00 +0000

Buildings play an important role in consumption of energy and carbon dioxide emissions all over the world. The optimum thickness of each insulation material of wall and roof of residential buildings depending on energy, environment, economy and exergy was determined in this study. For this purpose, an optimization model was established based on four different criteria: energy, environment, economics, and exergy. A function was defined containing these four criteria. It has been seen from the results that the optimum insulation thickness of the wall and roof depends on the weight coefficients of the energy, environment, economic and exergy parameters and insulation material types. The results of the economic analysis indicate that the optimum insulation thickness of wall varies from 1.01 to 7.7 cm and the optimum thicknesses of roof varies from 3.25 to 6.7 cm for XPS, EPS and Glasswool insulation materials. According to the results of the enviromental analysis, the optimum thicknesses of wall for different insulation materials are 6.5, 8.6, 9.4, and 9.55 cm and optimum insulation thicknesses of roof are 7.55, 8.1 and 8.2 cm, respectively. The effect of economic and energy parameters on the optimum thickness of the wall and roof for the three insulation materials was investigated using the sensitivity analysis method. It was seen from the results that impacts of interest rate, inflation rate, electricity cost, fuel cost, insulation material cost, heating and cooling degree-days on the optimum insulation thickness of wall and roof and 4EF optimization function were different.