Pub Date : 2025-03-01DOI: 10.1016/j.jer.2023.08.013
Imran Ali , Muhammad Zia Ur Rahman , Abid Hussain , Asim Ghaffar , Saqib Zafar
The non pneumatic castors (NPCs) exhibit various advantages over pneumatic castors such as, higher load bearing capacity, lower rolling resistance and less occurrence of the blowouts in harsh environments. We have conducted an FEA based design optimization study of wheel chair non-pneumatic castors (NPC); and compared its mechanical properties with a Pneumatic castor of same characteristics. NPCs with different number of holes and hole diameter, were subjected under vertical load and rolling along a discrete rigid road. Based on results; the NPC with 25 no. of holes and 8.75 mm hole diameter is considered as the optimal design, because the stiffness and rolling resistance of the castor with 8.75 mm diameter hole size overlapped the characteristics of Pneumatic castor. In order to avoid failures due to stress concentration, the stress distribution at various locations was also investigated for the NPCs as well as pneumatic castors. The stress concentration in NPC was observed “along the circumference that passes through the hole centers”. The minimum stress is induced in any individual hole when it’s not in contact with the ground, while as the castor rolls from 0 to 360°, stress changes in a sinusoidal form for every individual hole.
{"title":"A finite element analysis based design of a non-pneumatic wheel chair castor","authors":"Imran Ali , Muhammad Zia Ur Rahman , Abid Hussain , Asim Ghaffar , Saqib Zafar","doi":"10.1016/j.jer.2023.08.013","DOIUrl":"10.1016/j.jer.2023.08.013","url":null,"abstract":"<div><div>The non pneumatic castors (NPCs) exhibit various advantages over pneumatic castors such as, higher load bearing capacity, lower rolling resistance and less occurrence of the blowouts in harsh environments. We have conducted an FEA based design optimization study of wheel chair non-pneumatic castors (NPC); and compared its mechanical properties with a Pneumatic castor of same characteristics. NPCs with different number of holes and hole diameter, were subjected under vertical load and rolling along a discrete rigid road. Based on results; the NPC with 25 no. of holes and 8.75 mm hole diameter is considered as the optimal design, because the stiffness and rolling resistance of the castor with 8.75 mm diameter hole size overlapped the characteristics of Pneumatic castor. In order to avoid failures due to stress concentration, the stress distribution at various locations was also investigated for the NPCs as well as pneumatic castors. The stress concentration in NPC was observed “along the circumference that passes through the hole centers”. The minimum stress is induced in any individual hole when it’s not in contact with the ground, while as the castor rolls from 0 to 360°, stress changes in a sinusoidal form for every individual hole.</div></div>","PeriodicalId":48803,"journal":{"name":"Journal of Engineering Research","volume":"13 1","pages":"Pages 351-360"},"PeriodicalIF":0.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123122265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01DOI: 10.1016/j.jer.2023.10.033
Jie Sun, Ruipu Wang
In many construction projects, the delivery of raw materials from the warehouse to the project place and the return of waste materials from the project place to the warehouse are planned simultaneously. This issue has many complexing assumptions. Accordingly, in this research, the multi-objective two-echelon vehicle routing with simultaneous pickup and delivery is investigated. For this purpose, a multi-objective mathematical model has been developed. Objective functions include economic, environmental and social criteria to achieve sustainability. Moreover, as the problem is known as a hard-NP problem, two meta-heuristic algorithms, NSGA-II and MOPSO, are proposed to solve this problem. In order to evaluate the performance of the proposed meta-heuristic algorithms, 10 test problems of different sizes were generated. The solutions obtained with the proposed algorithms for each of these example problems were evaluated using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method in eight indicators. The achieved numerical results show that the proposed model and the applied algorithms have sufficient efficiency. Moreover, it is revealed that the NSGAII and MOPSO algorithms have a desirability weight of 0.4321 and0.5679, respectively. Therefore, it can be concluded that the MOPSO algorithm has higher efficiency for solving the model.
在许多建设项目中，原材料从仓库运送到项目地点和废料从项目地点返回仓库是同时计划的。这个问题有许多复杂的假设。在此基础上，本文研究了同时取货的多目标两梯队车辆路径问题。为此，建立了一个多目标数学模型。目标功能包括实现可持续性的经济、环境和社会标准。此外，由于该问题被称为硬np问题，提出了两种元启发式算法NSGA-II和MOPSO来解决该问题。为了评估所提出的元启发式算法的性能，生成了10个不同大小的测试问题。采用TOPSIS (technical for Order of Preference by Similarity to Ideal Solution)方法对八个指标进行评价。数值结果表明，所提出的模型和应用的算法具有足够的效率。此外，NSGAII和MOPSO算法的理想权值分别为0.4321和0.5679。由此可见，MOPSO算法求解模型的效率更高。
{"title":"Multi-objective optimization of a sustainable two echelon vehicle routing problem with simultaneous pickup and delivery in construction projects","authors":"Jie Sun, Ruipu Wang","doi":"10.1016/j.jer.2023.10.033","DOIUrl":"10.1016/j.jer.2023.10.033","url":null,"abstract":"<div><div>In many construction projects, the delivery of raw materials from the warehouse to the project place and the return of waste materials from the project place to the warehouse are planned simultaneously. This issue has many complexing assumptions. Accordingly, in this research, the multi-objective two-echelon vehicle routing with simultaneous pickup and delivery is investigated. For this purpose, a multi-objective mathematical model has been developed. Objective functions include economic, environmental and social criteria to achieve sustainability. Moreover, as the problem is known as a hard-NP problem, two meta-heuristic algorithms, NSGA-II and MOPSO, are proposed to solve this problem. In order to evaluate the performance of the proposed meta-heuristic algorithms, 10 test problems of different sizes were generated. The solutions obtained with the proposed algorithms for each of these example problems were evaluated using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method in eight indicators. The achieved numerical results show that the proposed model and the applied algorithms have sufficient efficiency. Moreover, it is revealed that the NSGAII and MOPSO algorithms have a desirability weight of 0.4321 and0.5679, respectively. Therefore, it can be concluded that the MOPSO algorithm has higher efficiency for solving the model.</div></div>","PeriodicalId":48803,"journal":{"name":"Journal of Engineering Research","volume":"13 1","pages":"Pages 39-46"},"PeriodicalIF":0.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136058767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the advancements in IIoT tools and applications, real-time monitoring systems with remote access capabilities are gaining great interest. The use of these instruments in monitoring manufacturing processes can lead to enhanced performance and increased efficiency. In this paper, a real-time monitoring system using Raspberry Pi is developed for monitoring the maximum temperature and axial force during friction stir spot welding (FSSW). There are two sensors used in this experiment: a thermocouple and a load cell connected to a microcontroller via Node-RED. Through the use of the system and response surface methodology (RSM), three factors (tool rotation speed, plunge rate, and dwell time) were examined in relation to maximum temperatures and axial forces during FSSW. Models of maximum welding temperature and force were constructed based on multivariate regression and adaptive network fuzzy inference system (ANFIS). The monitoring system proved effective at measuring and tracking temperature and axial force in real time across multiple platforms.
{"title":"Open-source real-time monitoring system of temperature and force during friction stir spot welding","authors":"Adham E. Ragab , Abdulrahman Alsaty , Ali Alsamhan , Abdulsalam Abdulaziz Al-Tamimi , Abdulmajeed Dabwan , Abdelaty Sayed , Waleed Alghilan","doi":"10.1016/j.jer.2023.08.020","DOIUrl":"10.1016/j.jer.2023.08.020","url":null,"abstract":"<div><div>With the advancements in IIoT tools and applications, real-time monitoring systems with remote access capabilities are gaining great interest. The use of these instruments in monitoring manufacturing processes can lead to enhanced performance and increased efficiency. In this paper, a real-time monitoring system using Raspberry Pi is developed for monitoring the maximum temperature and axial force during friction stir spot welding (FSSW). There are two sensors used in this experiment: a thermocouple and a load cell connected to a microcontroller via Node-RED. Through the use of the system and response surface methodology (RSM), three factors (tool rotation speed, plunge rate, and dwell time) were examined in relation to maximum temperatures and axial forces during FSSW. Models of maximum welding temperature and force were constructed based on multivariate regression and adaptive network fuzzy inference system (ANFIS). The monitoring system proved effective at measuring and tracking temperature and axial force in real time across multiple platforms.</div></div>","PeriodicalId":48803,"journal":{"name":"Journal of Engineering Research","volume":"13 1","pages":"Pages 84-96"},"PeriodicalIF":0.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79593633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Compressing medical images to reduce their size while maintaining their clinical and diagnostic information is crucial. Because medical images can be large and demand a lot of storage and transmission capacity, effective compression methods aid medical institutions in better storing and transmitting medical images, reducing costs, speeding up data transfer, and simplifying managing image databases. However, it is essential to note that image compression in medical imaging can also introduce drawbacks, such as loss of information and poor output image quality. Therefore, a suitable compression algorithm and parameter must be chosen to balance file size and visual fidelity. This paper suggests an effective image compression method employing the Discrete Wavelet Transform (DWT), followed by a reduction operation and Huffman coding to produce a mere lossless encoding to transmit the images over a channel. The extracted DWT coefficients are mapped to the nearest integral value. All four sub-bands of DWT are joined, and then a window of 3 × 3 is selected for reduction operation by choosing the origin as the pivot element. The Huffman coding algorithm is used to compress the processed image. The pivot origin element is used in the reversible reduction while uncompressing the image. When sending compressed data across an unreliable route, the window size and pivot element selection keep the compressed data secure. Standard measures such as bits per pixel (BPP) and compression ratio (CR) are used to assess the suggested approach. The efficiency of the suggested course of action is supported by the research's findings, which use a peak signal-to-noise ratio (PSNR) of 54.66 dB.
{"title":"A novel image compression method using wavelet coefficients and Huffman coding","authors":"Shiju Thomas , Addapalli Krishna , Sabeen Govind , Aditya Kumar Sahu","doi":"10.1016/j.jer.2023.08.015","DOIUrl":"10.1016/j.jer.2023.08.015","url":null,"abstract":"<div><div>Compressing medical images to reduce their size while maintaining their clinical and diagnostic information is crucial. Because medical images can be large and demand a lot of storage and transmission capacity, effective compression methods aid medical institutions in better storing and transmitting medical images, reducing costs, speeding up data transfer, and simplifying managing image databases. However, it is essential to note that image compression in medical imaging can also introduce drawbacks, such as loss of information and poor output image quality. Therefore, a suitable compression algorithm and parameter must be chosen to balance file size and visual fidelity. This paper suggests an effective image compression method employing the Discrete Wavelet Transform (DWT), followed by a reduction operation and Huffman coding to produce a mere lossless encoding to transmit the images over a channel. The extracted DWT coefficients are mapped to the nearest integral value. All four sub-bands of DWT are joined, and then a window of 3 × 3 is selected for reduction operation by choosing the origin as the pivot element. The Huffman coding algorithm is used to compress the processed image. The pivot origin element is used in the reversible reduction while uncompressing the image. When sending compressed data across an unreliable route, the window size and pivot element selection keep the compressed data secure. Standard measures such as bits per pixel (BPP) and compression ratio (CR) are used to assess the suggested approach. The efficiency of the suggested course of action is supported by the research's findings, which use a peak signal-to-noise ratio (PSNR) of 54.66 dB.</div></div>","PeriodicalId":48803,"journal":{"name":"Journal of Engineering Research","volume":"13 1","pages":"Pages 361-370"},"PeriodicalIF":0.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87267413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01DOI: 10.1016/j.jer.2023.08.006
Narendranathan S.K. , Pandiyarajan R. , Purushothaman Panneerselvam , Sabarish S.
The current investigation examined how the combined use of Modified Operating Parameter (MOP) and Thermal Barrier Coating (TBC) enhanced the performance, combustion, and emission characteristics of a diesel engine running on Punnai oil fuel. In this study, it was found that the Punnai oil blended with diesel could effectively increase engine efficiency and decrease emissions under MOP and TBC. Based on the results of the testing, the 60 P (where P denotes the blend percentage of Punnai oil in Diesel) fuel blend proved to be the most efficient fuel blend for the engine in terms of Cylinder Pressure, Heat Release Rate (HRR), and Brake Thermal Efficiency (BTE) in comparison with the 70 P and 80 P fuel blends. Furthermore, the 60 P blend demonstrated lower emissions of Carbon Dioxide (CO2) and Hydrocarbons (HC) than the other blends, although it produced higher levels of Nitrous Oxide (NOx) and Smoke Opacity. The study indicates that utilizing a 60 P Punnai oil fuel could result in improved engine performance and reduced emissions.
{"title":"Influence of modified operating parameters and thermal barrier coating on diesel engine performance using punnai oil mixture","authors":"Narendranathan S.K. , Pandiyarajan R. , Purushothaman Panneerselvam , Sabarish S.","doi":"10.1016/j.jer.2023.08.006","DOIUrl":"10.1016/j.jer.2023.08.006","url":null,"abstract":"<div><div>The current investigation examined how the combined use of Modified Operating Parameter (MOP) and Thermal Barrier Coating (TBC) enhanced the performance, combustion, and emission characteristics of a diesel engine running on Punnai oil fuel. In this study, it was found that the Punnai oil blended with diesel could effectively increase engine efficiency and decrease emissions under MOP and TBC. Based on the results of the testing, the 60 P (where P denotes the blend percentage of Punnai oil in Diesel) fuel blend proved to be the most efficient fuel blend for the engine in terms of Cylinder Pressure, Heat Release Rate (HRR), and Brake Thermal Efficiency (BTE) in comparison with the 70 P and 80 P fuel blends. Furthermore, the 60 P blend demonstrated lower emissions of Carbon Dioxide (CO<sub>2</sub>) and Hydrocarbons (HC) than the other blends, although it produced higher levels of Nitrous Oxide (NOx) and Smoke Opacity. The study indicates that utilizing a 60 P Punnai oil fuel could result in improved engine performance and reduced emissions.</div></div>","PeriodicalId":48803,"journal":{"name":"Journal of Engineering Research","volume":"13 1","pages":"Pages 218-228"},"PeriodicalIF":0.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89287052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01DOI: 10.1016/j.jer.2023.09.002
Khaled M.S. Gad El Mola
The study aims to develop a framework for the integration of green supply chains at energy production using fuzzy-QFD. The study will identify green requirements (GR) and green factors (GF), propose a multi-criteria decision-making model to determine GR's priority weights and determine the relationships between GRs and GFs in the energy sector. The study also calculates absolute technical importance ratings and normalized ratings by using a fuzzy-quality function deployment approach. To validate the proposed framework, sensitivity analysis was performed which revealed that the adoption of GCM increased the cost by 20%, environmental quality by 25% and the efficiency level by 20%. These results will help to reduce carbon footprints and ensure sustainability in the process of energy transportation and energy value chain including all activities necessary for the production, distribution and consumption of electrical energy. The present study suggests developing internal operations in the light of green supply chain management in the energy sector. Moreover, the subjectivity of the developed framework needs to be assessed more in other sectors.
{"title":"Developing a framework for integration of a green supply chain at energy production using fuzzy-QFD","authors":"Khaled M.S. Gad El Mola","doi":"10.1016/j.jer.2023.09.002","DOIUrl":"10.1016/j.jer.2023.09.002","url":null,"abstract":"<div><div>The study aims to develop a framework for the integration of green supply chains at energy production using fuzzy-QFD. The study will identify green requirements (GR) and green factors (GF), propose a multi-criteria decision-making model to determine GR's priority weights and determine the relationships between GRs and GFs in the energy sector. The study also calculates absolute technical importance ratings and normalized ratings by using a fuzzy-quality function deployment approach. To validate the proposed framework, sensitivity analysis was performed which revealed that the adoption of GCM increased the cost by 20%, environmental quality by 25% and the efficiency level by 20%. These results will help to reduce carbon footprints and ensure sustainability in the process of energy transportation and energy value chain including all activities necessary for the production, distribution and consumption of electrical energy. The present study suggests developing internal operations in the light of green supply chain management in the energy sector. Moreover, the subjectivity of the developed framework needs to be assessed more in other sectors.</div></div>","PeriodicalId":48803,"journal":{"name":"Journal of Engineering Research","volume":"13 1","pages":"Pages 14-26"},"PeriodicalIF":0.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135248757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01DOI: 10.1016/j.jer.2023.10.030
K. Siva Prasad , S. Srinivasa Rao , V.R.K. Raju
The fast depletion of fossil fuels and the hazardous emissions associated with the use of fossil fuels in IC engines is driving the research in the area of renewable fuels. Homogeneous charge combustion ignition (HCCI) is a new mode of engine combustion technology, used for reducing the emissions without compromising the engine performance. The combination of HCCI and alcohol/diesel blends has the potential to simultaneously address the twin problems of depletion of fossil fuels and engine emissions. Butanol is an attractive biofuel, which is produced from agriculture wastes such as sugar cane bagasses and corn stalk etc. This paper presents numerical and modeling analysis on the emission and performance characteristics of a direct injection- compression ignition (DI-CI) engine operated with butanol/diesel blends. Numerical analysis was carried out using CONVERGE CFD software. Response surface methodology (RSM) was used in developing the response models for three output parameters, viz., nitrogen oxides (NOx), soot emissions and indicated specific fuel consumption (ISFC), in terms of the four input parameters, viz., compression ratio (CR), start of injection (SOI), fuel injection pressure (FIP) and exhaust gas recirculation (EGR). Numerical experiments were conducted by varying these four input parameters, i.e., CR from 14 to 19, FIP from 200 to 280 bar, EGR from 0% to 30% and SOI from 17° to 29° CA bTDC, and with four butanol/diesel blends (0, 20%, 30% and 40% of butanol-by volume, designated as Bu00, Bu20, Bu30 and Bu40). The optimum combination of the input parameters for the four test fuels were found with the objective of minimizing the three output parameters (i.e., ISFC, soot and NOx) using desirability approach. The homogeneity of the air-fuel mixture was estimated using equivalence ratio distribution index, i.e., Target fuel distribution index (TFDI). From the numerical analysis, it was found that the TFDI improved for the optimized case by 20.5%, 21.5%, 24.4% and 27.2% for Bu00, Bu20, Bu30 and Bu40 respectively as compared to their respective baseline configuration.
化石燃料的快速消耗和与内燃机中使用化石燃料相关的有害排放正在推动可再生燃料领域的研究。均质装药燃烧点火(HCCI)是一种新型的发动机燃烧技术，用于在不影响发动机性能的情况下减少排放。HCCI和酒精/柴油混合物的组合有可能同时解决化石燃料枯竭和发动机排放的双重问题。丁醇是从甘蔗、甘蔗渣、玉米秸秆等农业废弃物中提取的一种有吸引力的生物燃料。本文对使用丁醇/柴油混合燃料的直喷压缩点火发动机的排放特性和性能特性进行了数值分析和建模。采用CONVERGE CFD软件进行数值分析。采用响应面法(RSM)，根据压缩比(CR)、启动喷射(SOI)、燃油喷射压力(FIP)和废气再循环(EGR)四个输入参数，建立了氮氧化物(NOx)、烟尘排放和指示油耗(ISFC)三个输出参数的响应模型。数值实验通过改变这四个输入参数进行，即CR从14到19,FIP从200到280 bar, EGR从0到30%，SOI从17到29°CA bTDC，并使用四种丁醇/柴油混合物(按体积计算丁醇含量为0、20%、30%和40%，分别称为Bu00、Bu20、Bu30和Bu40)。四种测试燃料的输入参数的最佳组合，目标是使用可取性方法最小化三个输出参数(即ISFC，烟灰和NOx)。采用等效比分布指数，即目标燃料分布指数(Target fuel distribution index, TFDI)来估计空燃混合气的均匀性。通过数值分析发现，优化后的Bu00、Bu20、Bu30和Bu40的TFDI分别比各自的基线配置提高了20.5%、21.5%、24.4%和27.2%。
{"title":"Numerical investigation for enhancing HCCI combustion characteristics in DI-CI engine fueled with butanol/diesel blends","authors":"K. Siva Prasad , S. Srinivasa Rao , V.R.K. Raju","doi":"10.1016/j.jer.2023.10.030","DOIUrl":"10.1016/j.jer.2023.10.030","url":null,"abstract":"<div><div>The fast depletion of fossil fuels and the hazardous emissions associated with the use of fossil fuels in IC engines is driving the research in the area of renewable fuels. Homogeneous charge combustion ignition (HCCI) is a new mode of engine combustion technology, used for reducing the emissions without compromising the engine performance. The combination of HCCI and alcohol/diesel blends has the potential to simultaneously address the twin problems of depletion of fossil fuels and engine emissions. Butanol is an attractive biofuel, which is produced from agriculture wastes such as sugar cane bagasses and corn stalk etc. This paper presents numerical and modeling analysis on the emission and performance characteristics of a direct injection- compression ignition (DI-CI) engine operated with butanol/diesel blends. Numerical analysis was carried out using CONVERGE CFD software. Response surface methodology (RSM) was used in developing the response models for three output parameters, viz., nitrogen oxides (NOx), soot emissions and indicated specific fuel consumption (ISFC), in terms of the four input parameters, viz., compression ratio (CR), start of injection (SOI), fuel injection pressure (FIP) and exhaust gas recirculation (EGR). Numerical experiments were conducted by varying these four input parameters, i.e., CR from 14 to 19, FIP from 200 to 280 bar, EGR from 0% to 30% and SOI from 17° to 29° CA bTDC, and with four butanol/diesel blends (0, 20%, 30% and 40% of butanol-by volume, designated as Bu00, Bu20, Bu30 and Bu40). The optimum combination of the input parameters for the four test fuels were found with the objective of minimizing the three output parameters (i.e., ISFC, soot and NO<sub>x</sub>) using desirability approach. The homogeneity of the air-fuel mixture was estimated using equivalence ratio distribution index, i.e., Target fuel distribution index (TFDI). From the numerical analysis, it was found that the TFDI improved for the optimized case by 20.5%, 21.5%, 24.4% and 27.2% for Bu00, Bu20, Bu30 and Bu40 respectively as compared to their respective baseline configuration.</div></div>","PeriodicalId":48803,"journal":{"name":"Journal of Engineering Research","volume":"13 1","pages":"Pages 302-319"},"PeriodicalIF":0.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135325440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01DOI: 10.1016/j.jer.2023.10.011
Selman djeffal , Abdelhamid Ghoul
This paper presents a comprehensive exploration of two meta-heuristic optimization techniques, Teaching Learning-Based Optimization (TLBO) and Particle Swarm Optimization (PSO), applied to solve the inverse kinematic problem of continuum robots. The study encompasses both theoretical investigations and realistic simulations, including tracking a spiral trajectory and utilizing real measurements to follow a trajectory. TLBO demonstrates exceptional precision in solving the inverse kinematic problem for continuum robots, consistently outperforming PSO in terms of accuracy. On the other hand, PSO showcases notable advantages in terms of computational efficiency, exhibiting faster convergence and reduced time consumption. The research findings suggest promising avenues for the application of meta-heuristic approaches in real-world scenarios involving continuum robots, particularly in domains such as medical devices and industrial automation. However, the challenge remains to develop modified algorithms that strike a balance between accuracy and efficiency to address the diverse requirements of practical applications in this field. Nevertheless, the versatility of meta-heuristic methods in handling complex robotic systems offers exciting prospects for the future of continuum robotics.
{"title":"Experimental and theoretical verification of TLBO and PSO for solving the inverse kinematic model of continuum robots","authors":"Selman djeffal , Abdelhamid Ghoul","doi":"10.1016/j.jer.2023.10.011","DOIUrl":"10.1016/j.jer.2023.10.011","url":null,"abstract":"<div><div>This paper presents a comprehensive exploration of two meta-heuristic optimization techniques, Teaching Learning-Based Optimization (TLBO) and Particle Swarm Optimization (PSO), applied to solve the inverse kinematic problem of continuum robots. The study encompasses both theoretical investigations and realistic simulations, including tracking a spiral trajectory and utilizing real measurements to follow a trajectory. TLBO demonstrates exceptional precision in solving the inverse kinematic problem for continuum robots, consistently outperforming PSO in terms of accuracy. On the other hand, PSO showcases notable advantages in terms of computational efficiency, exhibiting faster convergence and reduced time consumption. The research findings suggest promising avenues for the application of meta-heuristic approaches in real-world scenarios involving continuum robots, particularly in domains such as medical devices and industrial automation. However, the challenge remains to develop modified algorithms that strike a balance between accuracy and efficiency to address the diverse requirements of practical applications in this field. Nevertheless, the versatility of meta-heuristic methods in handling complex robotic systems offers exciting prospects for the future of continuum robotics.</div></div>","PeriodicalId":48803,"journal":{"name":"Journal of Engineering Research","volume":"13 1","pages":"Pages 251-266"},"PeriodicalIF":0.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135656760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01DOI: 10.1016/j.jer.2023.09.012
Gözde Keskin , Sachin Salunkhe , Gökhan Küçüktürk , Muharrem Pul , Hakan Gürün , Volkan Baydaroğlu
Materials
With sufficient electrical conductivity can be successfully processed by applying the electrical discharge machining (EDM) method; however, due to the presence of non-conductive particles in composites, which have been produced by adding ceramics particles, problems such as unstable machining, low material removal rate, and high tool wear are observed during the EDM. This study employed powder-mixed electrical discharge machining (PMEDM) by adding electrically conductive nano-size graphite powder into the dielectric liquid to minimize these problems. Moreover, the machinability of AA7075/ B4C and AA7075/ B4C+SiC composites was evaluated using the Taguchi method. The experimental study used L18 orthogonal array (OA) (21 ×32). ANOVA was employed to obtain significant parameters and percent contributions of variable parameters on the material removal rate (MRR). Reinforcement ratio, current and sintering time applied to the workpiece were chosen as variable parameters. The optimum parameters for MRR were obtained at A1B3C3 (reinforcement ratio= 10%, current= 8 A, sintering time=150 min). According to S/N ratio graphs, increasing the reinforcement ratio leads to a decreased MRR. On the contrary, when the applied current increases, MRR increases. Additionally, analysis results show that the discharge current is the most important parameter affecting MRR. In the morphological examinations, it was understood that the amounts of B4C and SiC particles in the composite structure affect the quality of the machined surfaces. It was determined that the surface quality deteriorated with the increase in the amount of SiC and B4C in the composite structure and the increase in the discharge current.
{"title":"Optimization of PMEDM process parameters for B4C and B4C+SiC reinforced AA7075 composites","authors":"Gözde Keskin , Sachin Salunkhe , Gökhan Küçüktürk , Muharrem Pul , Hakan Gürün , Volkan Baydaroğlu","doi":"10.1016/j.jer.2023.09.012","DOIUrl":"10.1016/j.jer.2023.09.012","url":null,"abstract":"<div><h3>Materials</h3><div>With sufficient electrical conductivity can be successfully processed by applying the electrical discharge machining (EDM) method; however, due to the presence of non-conductive particles in composites, which have been produced by adding ceramics particles, problems such as unstable machining, low material removal rate, and high tool wear are observed during the EDM. This study employed powder-mixed electrical discharge machining (PMEDM) by adding electrically conductive nano-size graphite powder into the dielectric liquid to minimize these problems. Moreover, the machinability of AA7075/ B<sub>4</sub>C and AA7075/ B<sub>4</sub>C+SiC composites was evaluated using the Taguchi method. The experimental study used L18 orthogonal array (OA) (21 ×32). ANOVA was employed to obtain significant parameters and percent contributions of variable parameters on the material removal rate (MRR). Reinforcement ratio, current and sintering time applied to the workpiece were chosen as variable parameters. The optimum parameters for MRR were obtained at A1B3C3 (reinforcement ratio= 10%, current= 8 A, sintering time=150 min). According to S/N ratio graphs, increasing the reinforcement ratio leads to a decreased MRR. On the contrary, when the applied current increases, MRR increases. Additionally, analysis results show that the discharge current is the most important parameter affecting MRR. In the morphological examinations, it was understood that the amounts of B<sub>4</sub>C and SiC particles in the composite structure affect the quality of the machined surfaces. It was determined that the surface quality deteriorated with the increase in the amount of SiC and B<sub>4</sub>C in the composite structure and the increase in the discharge current.</div></div>","PeriodicalId":48803,"journal":{"name":"Journal of Engineering Research","volume":"13 1","pages":"Pages 47-56"},"PeriodicalIF":0.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135889258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01DOI: 10.1016/j.jer.2023.10.029
Fatlume Zhujani , Georgi Todorov , Konstantin Kamberov , Fitore Abdullahu
To remain competitive, machining processes must be optimized to provide increased productivity and higher quality products. The aim of most efforts in these machining processes is to establish the optimal parameters to obtain the maximum material removal rate with minimum surface roughness which represents two of the main quality responses. This paper focuses on the optimization of process parameters in dry turning of Inconel 718, a nickel-based superalloy with PVD-coated carbide inserts based on single-objective optimization Taguchi technique, desirability function approach combined with response surface methodology (RSM), which is known as the multi-objective Desirability Optimization Methodology (DOM). Taguchi’s orthogonal-array design L9 (33) and ANOVA analysis of variance are used to study the relationship between cutting parameters (cutting speed, feed rate and depth of cut) and the dependent output variables i.e., the arithmetic mean deviation of the profile's surface roughness (Ra) and material removal rate (MRR). A regression analysis was used to develop a mathematical model based on the first-order model to predict the Ra and MRR model. Using multiple regression analysis, first order linear prediction model was obtained to find the correlation between surface roughness and MRR with independent variables. In the range of parameters investigated, the obtained mathematical models accurately represent the response index, and the results of the experiments demonstrate that the feed rate and the depth of cut are the most important factors influencing Ra and MRR, respectively. Finally, confirmatory tests proved that Taguchi's method, desirability function approach combined with linear regression models was successful in optimizing turning parameters for minimum surface roughness and maximum MRR.
{"title":"Mathematical modeling and optimization of machining parameters in CNC turning process of Inconel 718 using the Taguchi method","authors":"Fatlume Zhujani , Georgi Todorov , Konstantin Kamberov , Fitore Abdullahu","doi":"10.1016/j.jer.2023.10.029","DOIUrl":"10.1016/j.jer.2023.10.029","url":null,"abstract":"<div><div>To remain competitive, machining processes must be optimized to provide increased productivity and higher quality products. The aim of most efforts in these machining processes is to establish the optimal parameters to obtain the maximum material removal rate with minimum surface roughness which represents two of the main quality responses. This paper focuses on the optimization of process parameters in dry turning of Inconel 718, a nickel-based superalloy with PVD-coated carbide inserts based on single-objective optimization Taguchi technique, desirability function approach combined with response surface methodology (RSM), which is known as the multi-objective Desirability Optimization Methodology (DOM). Taguchi’s orthogonal-array design L9 (3<sup>3</sup>) and ANOVA analysis of variance are used to study the relationship between cutting parameters (cutting speed, feed rate and depth of cut) and the dependent output variables i.e., the arithmetic mean deviation of the profile's surface roughness (Ra) and material removal rate (MRR). A regression analysis was used to develop a mathematical model based on the first-order model to predict the Ra and MRR model. Using multiple regression analysis, first order linear prediction model was obtained to find the correlation between surface roughness and MRR with independent variables. In the range of parameters investigated, the obtained mathematical models accurately represent the response index, and the results of the experiments demonstrate that the feed rate and the depth of cut are the most important factors influencing Ra and MRR, respectively. Finally, confirmatory tests proved that Taguchi's method, desirability function approach combined with linear regression models was successful in optimizing turning parameters for minimum surface roughness and maximum MRR.</div></div>","PeriodicalId":48803,"journal":{"name":"Journal of Engineering Research","volume":"13 1","pages":"Pages 320-330"},"PeriodicalIF":0.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136054046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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