Pub Date : 2023-09-15DOI: 10.24191/jmeche.v20i3.23899
Atiqah Zolpakar
Surface finish and temperature rise are the crucial machining outcomes since it determines the quality of the machining and the tool life. During machining operations, choosing optimal machining parameters is critical since it affects the machining outcome. In this work, Multi-Objective Genetic Algorithm (MOGA) optimization is used to find the combination of machining parameters at different levels of hardness of 20, 36, and 43 to obtain minimum surface roughness and minimum cutting temperature in turning operation. Cutting depth, cutting speed, and feed rate are the machining variables that are used in the process of optimization. From the results, it shows that the minimum temperature rise is 243.333 ℃ with a surface roughness of 1.975 μm during machining of 20 hardness. It also observed that the hardness of the material significantly affects the surface roughness and temperature rise. The outcome shows that as the hardness of the material is increasing the temperature is increasing while the surface roughness is decreasing. This research also revealed that using a MOGA to optimize multi-objective replies produces positive outcomes.
{"title":"Optimization of Machining Parameters in Turning for Different Hardness using Multi-Objective Genetic Algorithm","authors":"Atiqah Zolpakar","doi":"10.24191/jmeche.v20i3.23899","DOIUrl":"https://doi.org/10.24191/jmeche.v20i3.23899","url":null,"abstract":"Surface finish and temperature rise are the crucial machining outcomes since it determines the quality of the machining and the tool life. During machining operations, choosing optimal machining parameters is critical since it affects the machining outcome. In this work, Multi-Objective Genetic Algorithm (MOGA) optimization is used to find the combination of machining parameters at different levels of hardness of 20, 36, and 43 to obtain minimum surface roughness and minimum cutting temperature in turning operation. Cutting depth, cutting speed, and feed rate are the machining variables that are used in the process of optimization. From the results, it shows that the minimum temperature rise is 243.333 ℃ with a surface roughness of 1.975 μm during machining of 20 hardness. It also observed that the hardness of the material significantly affects the surface roughness and temperature rise. The outcome shows that as the hardness of the material is increasing the temperature is increasing while the surface roughness is decreasing. This research also revealed that using a MOGA to optimize multi-objective replies produces positive outcomes.","PeriodicalId":16332,"journal":{"name":"Journal of Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135485921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-15DOI: 10.24191/jmeche.v20i3.23915
Bikkavolu Joga Rao
Hazardous emissions majorly NOx and the poor performance of alternative fuels (biodiesel/its blends) are global concerns, as fossil fuel depletion and rising energy prices encourage researchers to rely on alternative energy sources with the addition of nano additives in the recent decade. The current experimental study investigates the performance, combustion, and emission characteristics of biodiesel-diesel mixtures dispersed with titanium dioxide (TiO2) as a fuel additive on a 1-cylinder diesel engine. TiO2 was dispersed in a Tamarind Oil Methyl Ester (TOME)-diesel blend (B20) in three concentrations of 40, 80, and 120 ppm via ultrasonication in the presence of QPAN80 surfactant to enhance the stability of the prepared fuel sample. A ratio of 1:4 TiO2:QPAN80 was found to produce the highest stability and homogeneity which is evidenced by the characterization of TiO2. The engine tests revealed that the greatest decrement in BSFC, CO, HC, and NOx was observed as 15.2%, 15.2%, 11.10%, and 9.06%, and the maximum BTE, HRR,and CP were improved by 9.76%, 50.32 J/degree, and 50.32 bar for the B20T80 blend correlated with B20 blend. Thus, the inclusion of TiO2 nano additives improved overall engine performance and decreased emissions of CI engines significantly.
{"title":"Influence of Nano Additives on Performance, Combustion, and Emission Characteristics of Diesel Engine using Tamarind Oil Methyl Ester-Diesel Fuel Blends","authors":"Bikkavolu Joga Rao","doi":"10.24191/jmeche.v20i3.23915","DOIUrl":"https://doi.org/10.24191/jmeche.v20i3.23915","url":null,"abstract":"Hazardous emissions majorly NOx and the poor performance of alternative fuels (biodiesel/its blends) are global concerns, as fossil fuel depletion and rising energy prices encourage researchers to rely on alternative energy sources with the addition of nano additives in the recent decade. The current experimental study investigates the performance, combustion, and emission characteristics of biodiesel-diesel mixtures dispersed with titanium dioxide (TiO2) as a fuel additive on a 1-cylinder diesel engine. TiO2 was dispersed in a Tamarind Oil Methyl Ester (TOME)-diesel blend (B20) in three concentrations of 40, 80, and 120 ppm via ultrasonication in the presence of QPAN80 surfactant to enhance the stability of the prepared fuel sample. A ratio of 1:4 TiO2:QPAN80 was found to produce the highest stability and homogeneity which is evidenced by the characterization of TiO2. The engine tests revealed that the greatest decrement in BSFC, CO, HC, and NOx was observed as 15.2%, 15.2%, 11.10%, and 9.06%, and the maximum BTE, HRR,and CP were improved by 9.76%, 50.32 J/degree, and 50.32 bar for the B20T80 blend correlated with B20 blend. Thus, the inclusion of TiO2 nano additives improved overall engine performance and decreased emissions of CI engines significantly.","PeriodicalId":16332,"journal":{"name":"Journal of Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135486722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-15DOI: 10.24191/jmeche.v20i3.23901
Mohd Hazri Mohd Rusli
The automotive industries in Malaysia have grown well and developed many suppliers in their supply chain including Small Medium Enterprise (SME). The order handling process at a supplier's factory has become one of the most critical areas in the supply chain. Adaptation to technology such as IoT enables the automotive supplier to better manage their customer orders and avoid mistakes that affect the supply chain. In order to improve the order processing activities, a study has focused on developing a mobile device application using Google Appsheet and Google Sheets as a cost-effective system for managing supply orders. A study was conducted in one of Malaysian SME automotive companies, which manages the orders manually by using a log book with a lot of recording and redundant work. By using Google Sheets, all the information and data involved in order processing activities is imported and digitized. Then, a mobile application is created using Appsheet so that the ordering activities and processing can be completed on a mobile device. All information gathered by the mobile app (Google Appsheet) is immediately saved in Google Sheets on an Excel-based database, allowing for further data analysis. The research conducted has managed to integrate these two applications into a system for Malaysia's SME factory to manage the ordering activities in the automotive supply chain. This system enables the user to shorten their order processing time since data is captured in real time and mistakes due to manual error can be avoided.
{"title":"Development of an Order Processing System using Google Sheets and Appsheet for a Malaysian Automotive SME Factory Warehouse","authors":"Mohd Hazri Mohd Rusli","doi":"10.24191/jmeche.v20i3.23901","DOIUrl":"https://doi.org/10.24191/jmeche.v20i3.23901","url":null,"abstract":"The automotive industries in Malaysia have grown well and developed many suppliers in their supply chain including Small Medium Enterprise (SME). The order handling process at a supplier's factory has become one of the most critical areas in the supply chain. Adaptation to technology such as IoT enables the automotive supplier to better manage their customer orders and avoid mistakes that affect the supply chain. In order to improve the order processing activities, a study has focused on developing a mobile device application using Google Appsheet and Google Sheets as a cost-effective system for managing supply orders. A study was conducted in one of Malaysian SME automotive companies, which manages the orders manually by using a log book with a lot of recording and redundant work. By using Google Sheets, all the information and data involved in order processing activities is imported and digitized. Then, a mobile application is created using Appsheet so that the ordering activities and processing can be completed on a mobile device. All information gathered by the mobile app (Google Appsheet) is immediately saved in Google Sheets on an Excel-based database, allowing for further data analysis. The research conducted has managed to integrate these two applications into a system for Malaysia's SME factory to manage the ordering activities in the automotive supply chain. This system enables the user to shorten their order processing time since data is captured in real time and mistakes due to manual error can be avoided.","PeriodicalId":16332,"journal":{"name":"Journal of Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135486818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-15DOI: 10.24191/jmeche.v20i3.23910
Mudhar A. Al-Obaidi
The low density, low expansion coefficient, and strong corrosion resistance at room temperature of Aluminium alloys have made them a popular choice for engineering applications. In this study, Aluminium AA2024 alloys are prepared with different weight contents of ceramic material, titanium oxide (TiO2) nanoparticles (0%, 2.5%, 5%, and 7.5% wt.) of a particle size of 30 nm using the metal stir casting method. The hardness property and wear resistance with the effect of heat treatment are investigated using a pin-on-disc wear device for both the base alloy and the reinforced alloys. The result shows the prosperity of 5wt.% of TiO2 to attain the optimum hardness and wear resistance. Using the optimum content of TiO2 and heat treatment, the hardness and wear resistance of 5wt.% TiO2-AA2024 nanocomposite has been significantly improved after heat treatment over the unreinforced Aluminium matrix. Statistically, the hardness and wear resistance are improved by 68% and 22%, respectively. This is due to an increased number of fine precipitates besides their uniformly distributed after heat treatment. Furthermore, casting AA2024 Aluminium alloy material mainly has S (Al2CuMg) and Al3TiCu phases. The appearance of a large number of S phases causes a significant improvement in the properties of the alloy.
{"title":"The Effects of Titanium Dioxide (TiO2) Content on the Dry Sliding Behaviour of AA2024 Aluminium Composite","authors":"Mudhar A. Al-Obaidi","doi":"10.24191/jmeche.v20i3.23910","DOIUrl":"https://doi.org/10.24191/jmeche.v20i3.23910","url":null,"abstract":"The low density, low expansion coefficient, and strong corrosion resistance at room temperature of Aluminium alloys have made them a popular choice for engineering applications. In this study, Aluminium AA2024 alloys are prepared with different weight contents of ceramic material, titanium oxide (TiO2) nanoparticles (0%, 2.5%, 5%, and 7.5% wt.) of a particle size of 30 nm using the metal stir casting method. The hardness property and wear resistance with the effect of heat treatment are investigated using a pin-on-disc wear device for both the base alloy and the reinforced alloys. The result shows the prosperity of 5wt.% of TiO2 to attain the optimum hardness and wear resistance. Using the optimum content of TiO2 and heat treatment, the hardness and wear resistance of 5wt.% TiO2-AA2024 nanocomposite has been significantly improved after heat treatment over the unreinforced Aluminium matrix. Statistically, the hardness and wear resistance are improved by 68% and 22%, respectively. This is due to an increased number of fine precipitates besides their uniformly distributed after heat treatment. Furthermore, casting AA2024 Aluminium alloy material mainly has S (Al2CuMg) and Al3TiCu phases. The appearance of a large number of S phases causes a significant improvement in the properties of the alloy.","PeriodicalId":16332,"journal":{"name":"Journal of Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135352906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-15DOI: 10.24191/jmeche.v20i3.23902
Banta Cut Sutardi
Studies on flow through cylinders have been widely carried out, both experimentally and numerically. The purpose of those studies is to obtain information about flow phenomena around the cylinder arrangement, such as aerodynamic forces, vortex shedding, and vortex-induced vibration. This study aims to evaluate the flow characteristics that pass through three circular cylinders arranged in a stagger and reduce the drag force (CD) by adding 3 disturbance bodies (DB) around the upstream cylinder. The longitudinal distance L/D varies from 1.5 to 4.0, while the transversal distance T/D is kept constant. Next, the diameter ratio d/D is set to 0.16. The diameter of cylinder 1, D=25 mm, and the diameter of the DB, d=4 mm. The DB is placed around cylinder 1 at three angle locations with a gap, δ=4 mm. The study is performed using Ansys fluent® 19.1 software in 2-D unsteady RANS with the transition k-kl-omega turbulence model. The flow Reynolds number based on D is22x104. The results showed that the L/D and the use of DB affect the cylinderdrag coefficient (CD). There is a CD reduction for cylinder 1 up to 20% atL/D=3.0. For cylinders 2 and 3, the reduction in CD occurred at L/D=4.0 upto approximately 13% and 17%, respectively.
{"title":"Dynamic Behaviour of Flow Through Three Circular Cylinders in Staggered Arrangement with Three Disturbance Bodies Around the Upstream Cylinder","authors":"Banta Cut Sutardi","doi":"10.24191/jmeche.v20i3.23902","DOIUrl":"https://doi.org/10.24191/jmeche.v20i3.23902","url":null,"abstract":"Studies on flow through cylinders have been widely carried out, both experimentally and numerically. The purpose of those studies is to obtain information about flow phenomena around the cylinder arrangement, such as aerodynamic forces, vortex shedding, and vortex-induced vibration. This study aims to evaluate the flow characteristics that pass through three circular cylinders arranged in a stagger and reduce the drag force (CD) by adding 3 disturbance bodies (DB) around the upstream cylinder. The longitudinal distance L/D varies from 1.5 to 4.0, while the transversal distance T/D is kept constant. Next, the diameter ratio d/D is set to 0.16. The diameter of cylinder 1, D=25 mm, and the diameter of the DB, d=4 mm. The DB is placed around cylinder 1 at three angle locations with a gap, δ=4 mm. The study is performed using Ansys fluent® 19.1 software in 2-D unsteady RANS with the transition k-kl-omega turbulence model. The flow Reynolds number based on D is22x104. The results showed that the L/D and the use of DB affect the cylinderdrag coefficient (CD). There is a CD reduction for cylinder 1 up to 20% atL/D=3.0. For cylinders 2 and 3, the reduction in CD occurred at L/D=4.0 upto approximately 13% and 17%, respectively.","PeriodicalId":16332,"journal":{"name":"Journal of Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135486711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-15DOI: 10.24191/jmeche.v20i3.23904
Mohamad Yamin
Recently, large amounts of data from experimental measurements and simulations with high fidelity have extensively accelerated fluid mechanics advancement. Machine learning (ML) offers a wealth of techniques to extract data that can be translated into knowledge about the underlying fluid mechanics. Backward-Facing Step (BFS) is well-known for its application to fluid mechanics, particularly flow turbulence. Typically, a numerical approach can be used to understand the flow phenomena on BFS. In some instances, numerical investigations have a computational time limitation. This paper examines the application of ML to predict reattachment length on BFS flow. The procedure begins with a simulated meshing sensitivity of 1.27 cm in step height. This numerical analysis was conducted in the turbulent zone with a Reynolds number between 35587 and 40422. OpenFOAM® was used to perform numerical simulations using the turbulence model of k-omega shear stress transport. ML employed information in the form of Velocity and Pressure at every node to represent the type of turbulence. Using Recurrent Neural Networks (RNNs) as the most effective model to predict reattachment length values, the reattachment length was predicted with a Root Mean Square Error of 0.013.
{"title":"Applied Machine Learning to Estimate Length of Separation and Reattachment Flows as Parameter Active Flow Control in Backward Facing Step","authors":"Mohamad Yamin","doi":"10.24191/jmeche.v20i3.23904","DOIUrl":"https://doi.org/10.24191/jmeche.v20i3.23904","url":null,"abstract":"Recently, large amounts of data from experimental measurements and simulations with high fidelity have extensively accelerated fluid mechanics advancement. Machine learning (ML) offers a wealth of techniques to extract data that can be translated into knowledge about the underlying fluid mechanics. Backward-Facing Step (BFS) is well-known for its application to fluid mechanics, particularly flow turbulence. Typically, a numerical approach can be used to understand the flow phenomena on BFS. In some instances, numerical investigations have a computational time limitation. This paper examines the application of ML to predict reattachment length on BFS flow. The procedure begins with a simulated meshing sensitivity of 1.27 cm in step height. This numerical analysis was conducted in the turbulent zone with a Reynolds number between 35587 and 40422. OpenFOAM® was used to perform numerical simulations using the turbulence model of k-omega shear stress transport. ML employed information in the form of Velocity and Pressure at every node to represent the type of turbulence. Using Recurrent Neural Networks (RNNs) as the most effective model to predict reattachment length values, the reattachment length was predicted with a Root Mean Square Error of 0.013.","PeriodicalId":16332,"journal":{"name":"Journal of Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135486721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-15DOI: 10.24191/jmeche.v20i3.23916
Irnie Azlin Zakaria
Efficient thermal management is essential for the optimal performance and durability of the Proton Exchange Membrane Fuel Cell (PEMFC). However, the conventional passive cooling methods require a larger heat exchanger for better heat dissipation. Alternatively, nanofluids as a coolant have gained attention recently due to their enhanced heat transfer properties. This investigation aims to evaluate the thermal performance of hybrid nanofluids in a distributor type of PEMFC cooling plate. In this investigation, 0.5% volume concentration of mono Al2O3, mono SiO2 nanofluids, and hybrid Al2O3:SiO2 nanofluids with a mixture ratio of 10:90, 30:70, 50:50, and 70:30 in 60:40 W:EG were investigated. The cooling plate was modelled and a fixed heat flux of 6500 w/m2 was applied to replicate the actual working parameter of PEMFC. The study shows that the heat transfer coefficient was improved by 61% in 10:90 hybrid nanofluids of Al2O3:SiO2 in W:EG in comparison to the base fluid. Meanwhile, the accompanied pressure drops in 10:90 hybrid nanofluids of Al2O3:SiO2 in W:EG show a reduction up to 4.38 times lower as compared to single Al2O3 nanofluids at Re 1800. This is advantageous since it will reduce the parasitic loss related to the PEM fuel cell.
{"title":"Performance of Hybrid Al2O3:SiO2 W:EG in PEM Fuel Cell Distributor Plate","authors":"Irnie Azlin Zakaria","doi":"10.24191/jmeche.v20i3.23916","DOIUrl":"https://doi.org/10.24191/jmeche.v20i3.23916","url":null,"abstract":"Efficient thermal management is essential for the optimal performance and durability of the Proton Exchange Membrane Fuel Cell (PEMFC). However, the conventional passive cooling methods require a larger heat exchanger for better heat dissipation. Alternatively, nanofluids as a coolant have gained attention recently due to their enhanced heat transfer properties. This investigation aims to evaluate the thermal performance of hybrid nanofluids in a distributor type of PEMFC cooling plate. In this investigation, 0.5% volume concentration of mono Al2O3, mono SiO2 nanofluids, and hybrid Al2O3:SiO2 nanofluids with a mixture ratio of 10:90, 30:70, 50:50, and 70:30 in 60:40 W:EG were investigated. The cooling plate was modelled and a fixed heat flux of 6500 w/m2 was applied to replicate the actual working parameter of PEMFC. The study shows that the heat transfer coefficient was improved by 61% in 10:90 hybrid nanofluids of Al2O3:SiO2 in W:EG in comparison to the base fluid. Meanwhile, the accompanied pressure drops in 10:90 hybrid nanofluids of Al2O3:SiO2 in W:EG show a reduction up to 4.38 times lower as compared to single Al2O3 nanofluids at Re 1800. This is advantageous since it will reduce the parasitic loss related to the PEM fuel cell.","PeriodicalId":16332,"journal":{"name":"Journal of Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135486388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-15DOI: 10.24191/jmeche.v20i3.23908
Fauziah Jerai
Underfloor air distribution system (UFAD) mesh flow velocity was simulated using Computational Fluid Dynamics (CFD). Three mesh sizes were used to explore the domain's core x-y plane velocity contour and profiles. Compared to medium and fine, the coarse mesh underestimated the velocity significantly. A slight discrepancy occurred where the shear flow was dominant. The symmetrical flow velocity for both sides of the room length was shown in the xy-plane at the centre of the inlet. The mean error for coarse and medium mesh was larger than for the medium and fine mesh. It shows that the difference between the medium mesh and the fine was accepted. The computational time for medium mesh was acceptable for simulation, and it will not vary substantially even if the grid is refined further. The normalised mean square error (NMSE), the factor of two observations (FAC2), the factor of 1.3 observations (FAC1.3), and the fractional bias (FB) are used to measure the performance of the models and the value of the outcomes was exceptional. As a result, the accuracy of the finding can be improved by conducting additional research with manikins and in a fully occupied room under real-world conditions. In addition, this study could analyse and anticipate the optimal scenario regarding ventilation performance, etc.
{"title":"Accuracy of CFD Simulations on Indoor Air Ventilation: Application of Grid Convergence Index on Underfloor Air Distribution (UFAD) System Design","authors":"Fauziah Jerai","doi":"10.24191/jmeche.v20i3.23908","DOIUrl":"https://doi.org/10.24191/jmeche.v20i3.23908","url":null,"abstract":"Underfloor air distribution system (UFAD) mesh flow velocity was simulated using Computational Fluid Dynamics (CFD). Three mesh sizes were used to explore the domain's core x-y plane velocity contour and profiles. Compared to medium and fine, the coarse mesh underestimated the velocity significantly. A slight discrepancy occurred where the shear flow was dominant. The symmetrical flow velocity for both sides of the room length was shown in the xy-plane at the centre of the inlet. The mean error for coarse and medium mesh was larger than for the medium and fine mesh. It shows that the difference between the medium mesh and the fine was accepted. The computational time for medium mesh was acceptable for simulation, and it will not vary substantially even if the grid is refined further. The normalised mean square error (NMSE), the factor of two observations (FAC2), the factor of 1.3 observations (FAC1.3), and the fractional bias (FB) are used to measure the performance of the models and the value of the outcomes was exceptional. As a result, the accuracy of the finding can be improved by conducting additional research with manikins and in a fully occupied room under real-world conditions. In addition, this study could analyse and anticipate the optimal scenario regarding ventilation performance, etc.","PeriodicalId":16332,"journal":{"name":"Journal of Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135486831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-15DOI: 10.24191/jmeche.v20i3.23919
Sy Le Van
In this study, a dynamic model of the operating equipment and the hydraulic drive system of the remote-controlled explosive disposal machine were built to ensure both kinetic accuracy of digging path and the effective cutting angle. The Ruppel's control approach was applied to study the dynamics of the whole system and the influence of the arm-controlled signal, the soil digging resistance on the digging control process. In addition, a simulation model of the entire system is also performed to deeply understand the dynamic behaviour.
{"title":"Influence of Operating Factors on Accurate Digging Depth Control of the Remote-Controlled Explosive Disposal Machine","authors":"Sy Le Van","doi":"10.24191/jmeche.v20i3.23919","DOIUrl":"https://doi.org/10.24191/jmeche.v20i3.23919","url":null,"abstract":"In this study, a dynamic model of the operating equipment and the hydraulic drive system of the remote-controlled explosive disposal machine were built to ensure both kinetic accuracy of digging path and the effective cutting angle. The Ruppel's control approach was applied to study the dynamics of the whole system and the influence of the arm-controlled signal, the soil digging resistance on the digging control process. In addition, a simulation model of the entire system is also performed to deeply understand the dynamic behaviour.","PeriodicalId":16332,"journal":{"name":"Journal of Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135485920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-15DOI: 10.24191/jmeche.v20i3.23911
Koay Mei Hyie
Electroplating is extensively practiced in the industry to fabricate corrosion-protective coatings for steel in large-scale production. Mild steel easily rusts at ambient temperature thus surface pre-treatment is mandatory to eliminate rust and superficial scale from the steel. Pre-treatment ensures that the steel surface is free from contaminants, which may interfere with the surface quality of the protective coating. This research is done to investigate the effect of different pre-treatment methods on the surface quality of mild steel rings and cobalt-nickel-iron coated mild steel rings. These surfaces were achieved by polishing the ring and subjected to alkaline degreasing, followed by immersion in sulfuric acid or sodium chloride at 10 vol % concentration and different immersion times (50 s, 55 s, and 60 s). Direct electroplating was applied to fabricate the cobalt-nickel-iron coating. The surface morphology of metal substrate and coating after electroplating were tested by scanning electron microscope (SEM), energy dispersive X-Ray (EDS), Vickers hardness, and surface roughness tests. Both types of pre-treatments provided lower surface roughness on the metal substrate and resulted in full coatings without voids formation. The results showed that pre-treatment using sulfuric acid exhibited higher hardness and a smoother coating surface. Agglomerates and cracking were observed on the surface coating treated with sodium chloride.
{"title":"Comparison of Different Surface Pre-Treatment on Mild Steel for Cobalt-Nickel-Iron Electroplating","authors":"Koay Mei Hyie","doi":"10.24191/jmeche.v20i3.23911","DOIUrl":"https://doi.org/10.24191/jmeche.v20i3.23911","url":null,"abstract":"Electroplating is extensively practiced in the industry to fabricate corrosion-protective coatings for steel in large-scale production. Mild steel easily rusts at ambient temperature thus surface pre-treatment is mandatory to eliminate rust and superficial scale from the steel. Pre-treatment ensures that the steel surface is free from contaminants, which may interfere with the surface quality of the protective coating. This research is done to investigate the effect of different pre-treatment methods on the surface quality of mild steel rings and cobalt-nickel-iron coated mild steel rings. These surfaces were achieved by polishing the ring and subjected to alkaline degreasing, followed by immersion in sulfuric acid or sodium chloride at 10 vol % concentration and different immersion times (50 s, 55 s, and 60 s). Direct electroplating was applied to fabricate the cobalt-nickel-iron coating. The surface morphology of metal substrate and coating after electroplating were tested by scanning electron microscope (SEM), energy dispersive X-Ray (EDS), Vickers hardness, and surface roughness tests. Both types of pre-treatments provided lower surface roughness on the metal substrate and resulted in full coatings without voids formation. The results showed that pre-treatment using sulfuric acid exhibited higher hardness and a smoother coating surface. Agglomerates and cracking were observed on the surface coating treated with sodium chloride.","PeriodicalId":16332,"journal":{"name":"Journal of Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135486827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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