Engineering Research Express最新文献

{"title":"Enhancing the functionality of sugar palm (arenga pinnata) fibre reinforced polylactic acid composite filament of fused deposition modelling through taguchi method","authors":"Hazliza Aida C.H., Mastura M.T., Abdul Kudus S.I., Muhd Mufqi A.","doi":"10.1088/2631-8695/ad6396","DOIUrl":"https://doi.org/10.1088/2631-8695/ad6396","url":null,"abstract":"\u0000 Constructing functional components using Fused Deposition Modelling (FDM) is challenging due to various processing factors that influence the quality of the final product. The main reason for this is the many processing parameters involved, which have the ability to impact the quality of the produced components. The aim of this research is to use the Taguchi technique in attempt to improve the printing variables for attaining the best possible mechanical and physical qualities in the three-dimensional (3D) printed product made from sugar palm fibre reinforced polylactic acid (SPF/PLA). The layer thickness, infill density, and printing speed are characteristics that directly affect the mechanical qualities, surface roughness, and dimensional accuracy of FDM products. The research applied Taguchi’s L9 array, consisting of 9 experimental trials, with each trial including 5 duplicated specimens. Thus, a total of 45 specimens were generated by altering various processing settings. The most effective printing settings for FDM using SPF and PLA were found to be a layer thickness of 0.1 mm, infill density set to 100%, and a printing speed of 25 mm/s. The microscopic images reveal a significant rise in the number of voids as the layer thickness is raised. Additionally, the printing speed has a substantial impact on the nead structure, making it more resilient. Overall, the results will provide a significant collection of data in the area of 3D printing, improving the utilization of indigenous plant fibres in additive manufacturing technology.","PeriodicalId":505725,"journal":{"name":"Engineering Research Express","volume":"37 42","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141644919","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}

{"title":"Stochastic eigenvalue computation for cantilever beam dynamics using eigenvector-based polynomial chaos expansion.","authors":"rakesh kumar","doi":"10.1088/2631-8695/ad6393","DOIUrl":"https://doi.org/10.1088/2631-8695/ad6393","url":null,"abstract":"\u0000 This paper presents a innovative technique for ascertaining the eigenfrequencies of beams characterized by a random elastic modulus. Our method leverages Polynomial Chaos Expansion (PCE), uniquely focusing on the expansion of eigen vectors rather than the conventional approach of expanding both eigenvalues and eigenvectors. An exceptional aspect of our proposed methodology lies in its seam- less integration with the widely-utilized MATLAB ’eig’ tool, offering a more accessible and efficient solution. To validate the accuracy of our proposed method, we performed comparisons against Monte Carlo simulations, showcasing excellent agreement with both benchmarks. Notably, the mean of our method demonstrates consistent alignment with Monte Carlo simulations, further affirming its precision. We further investigated the computational cost of our method and contrasted it with Monte Carlo simu- lations, demonstrating its efficiency and computational advantages. Keywords: Eigen frequencies, Monte Carlo, Polynomial Chaos, Stochastic FEM, Vibration,","PeriodicalId":505725,"journal":{"name":"Engineering Research Express","volume":"81 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141647333","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}

{"title":"Production of paver blocks from polyethylene terephthalate solid waste as partial replacement of sand.","authors":"Getahun Demeke Worku, Assamen Ayalew Ejigu","doi":"10.1088/2631-8695/ad6392","DOIUrl":"https://doi.org/10.1088/2631-8695/ad6392","url":null,"abstract":"\u0000 Plastic waste management is an international concern. The amount of plastic trash produced globally is increasing at a rapid rate, and this pollution is caused by improper disposal, the waste's non-biodegradability, and the harmful gases released during incineration pose a hazard to human health. Because it's used in so many commonplace items, such as bottles and containers for the food and beverage sectors, polyethylene terephthalate, or PET, is one of the most widely used consumer polymers. Because of its many characteristics, including its inability to biodegrade and the gasses it releases when burned, it has grown to be a significant environmental problem. Waste made of polyethylene terephthalate (PET) must therefore be recycled and used efficiently. The purpose of this study was to produce paver blocks by partially replacing sand with waste Polyethylene Terephthalate (PET) material. Preparing the raw materials, mixing, vibrating, molding, curing, testing the flexural and compressive strengths, and curing are the steps in theproduction process. Design-Expert 13.0.0 Three-level Three factor Box–Behnken design was usedfor experimental design and statistical analysis of results based on the outcome and discussion. Atotal of 17 trials were carried out with the following parameters: 10, 20, and 30% of polyethylene terephthalate; 0.52, 0.55, and 0.58 as the water-to-cement ratio; and 7, 14, and 28 days for the curing period. The interaction effects were examined based on the examination of the experimental data. The physio-mechanical properties of the generated Paver Blocks, including water absorption, compressive strength, and flexural strength, were examined. When the water-tocement ratio was 0.55, the maximum flexural strength was 4.92 MPa, and the maximum compressive strength was 29.74 MPa, the ideal process variables for polyethylene terephthalate percentage were 10 and 28. The paver blocks' average and maximum water absorption rates were 3.39% and 3.95%, respectively. Compared to regular blocks, the resultant Paver Blocks are lighter and have superior physical and mechanical qualities. These are excellent illustrations of planned paver applications that can make use of prefabricated paver blocks","PeriodicalId":505725,"journal":{"name":"Engineering Research Express","volume":"32 40","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141645550","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}

{"title":"Dynamic pricing strategy for efficient electric vehicle charging and discharging in microgrids using multi-objective jaya algorithm","authors":"Swati Sharma, Ikbal Ali","doi":"10.1088/2631-8695/ad6394","DOIUrl":"https://doi.org/10.1088/2631-8695/ad6394","url":null,"abstract":"\u0000 The rising demand for electric vehicle (EV) charging is spurring their increased integration into microgrids. With significant advancements, EVs have become widely adopted and integrated into various settings for charging/discharging. EVs integrated with the microgrids possess the capability to serve as variable loads and the various energy suppliers present it as a dual opportunity. However, a primary challenge in EV deployment lies in efficiently managing charging stations (CSs) to minimize waiting times for users and reduce charging costs for EV owners. In addressing these challenges require consideration of dynamic pricing mechanisms and the diverse characteristics of EVs to achieve optimal scheduling. A novel approach that combines dynamic pricing strategies with optimized scheduling for effective EV charging operations using multi-objective Jaya algorithm. To evaluate its performance, we conducted a numerical experiment using real-time data and the Nissan Leaf model EV. The results demonstrate that our multi-objective Jaya-based approach outperforms existing methods by achieving a remarkable cost saving rate of 16.013 % and an average profit of ₹ 243.6331 per kilowatt-hour with a network convergence time of 112 seconds. Also, our proposed algorithm provides a correlation between minimized EV charging costs and maximized EV aggregator profits. These findings validate the effectiveness and practical applicability of our proposed EV scheduling algorithm in real-world scenarios.","PeriodicalId":505725,"journal":{"name":"Engineering Research Express","volume":"29 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141647981","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}

{"title":"Comparison of Si and SiC MOSFETs responses to electrical stress and the observation of parameter recovery in SiC MOSFET by stress superposition","authors":"Xinyu Wang, Osama O Awadelkarim","doi":"10.1088/2631-8695/ad6395","DOIUrl":"https://doi.org/10.1088/2631-8695/ad6395","url":null,"abstract":"\u0000 In this study we examined the effects of room temperature DC and AC electrical stress on Si and SiC n-channel metal-oxide-semiconductor field effect transistors (MOSFETs). Measurement of threshold voltage, transconductance, subthreshold swing, charge pumping, and gate oxide breakdown are used to compare the impact of stress on Si MOSFETs and SiC MOSFETS, as well as to understand the processes of carrier injection and trapping at oxide and interface defects. DC stress is observed to promote negative charge buildup in the gate oxide and interface in Si MOSFETs. However, in SiC MOSFETs the net charge buildup sign alternates between negative and positive as the DC stress polarity is changed from positive to negative, respectively. This change of charge buildup sign explains our observation that degradation in SiC MOSFETs subjected to AC bipolar stress is insignificantly small, whereas AC stressing of Si MOSFETs is observed to be much more severe. Also, the superposition of alternating DC stress polarity eliminates the stress induced degradation in SiC MOSFETs thus enabling a simple process for parameter reconfiguration and recovery.","PeriodicalId":505725,"journal":{"name":"Engineering Research Express","volume":"27 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141649085","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}

{"title":"Predictive modeling of specific fuel consumption in compression ignition engines using neural networks: A comparative analysis across diesel and polymer-based fuels","authors":"Maulik A. Modi, Tushar M. Patel","doi":"10.1088/2631-8695/ad62b5","DOIUrl":"https://doi.org/10.1088/2631-8695/ad62b5","url":null,"abstract":"\u0000 The study utilized neural network modeling to forecast the fuel consumption in compression ignition engines fueled by diesel, HDPE PO, PP PO, and LDPE PO. Using empirical data, a Neural Network model was constructed and used to estimate specific fuel consumption (SFC). Employing orthogonal arrays and parameter adjustments ensured accurate prediction of SFC, which was validated through experimentation. The multilayer perception network coupled with traditional backpropagation facilitates the nonlinear mapping of inputs to outcomes. In the LM10TP architecture, the key metrics from the training set included an impressive R-squared value of 1, indicating a perfect fit with a root mean square error (RMSE) of 0.0012 and a mean square error (MSE) of 1.5143E-06. Similarly, the validation set exhibited robust performance metrics with an R-squared value of 0.9999, RMSE of 0.0011, and MSE of 1.2185E-06. These metrics underscore the efficacy of neural networks in both the training and validation phases, affirming their utility as reliable predictive tools for SFC. Overall, this study highlights the effectiveness of neural network modeling for accurately predicting fuel consumption in compression ignition engines across diesel and polymer-based fuels. By leveraging empirical data and sophisticated modeling techniques, this study contributes to advancing the predictive capabilities in the field, offering valuable insights for optimizing engine performance and fuel efficiency.","PeriodicalId":505725,"journal":{"name":"Engineering Research Express","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141653472","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}

{"title":"Mechanical and physical properties of epoxy/SiC composites simulated","authors":"Nuha Hadi Jasim Al Hasan","doi":"10.1088/2631-8695/ad62af","DOIUrl":"https://doi.org/10.1088/2631-8695/ad62af","url":null,"abstract":"\u0000 This study aimed to predict the mechanical properties of SiC-reinforced epoxy. The cross-linked reinforced epoxy was simulated using Material Studio 7.0 (Accelrys, Inc.). Various percentages of SiC (0%, 4%, 6%, 8%, and 10%) were used in the simulations. A density curve and cell size diagram are obtained from MD simulations of SiC-epoxy nanocomposites. Under a 0.5 GPa pressure, Forcite dynamic simulations showed that amorphous cells have densities that are close to epoxy density (1.2g/cm3). Simulations have shown that epoxy/SiC composites respond well to a variety of mechanical strains. Increasing the SiC weight percentage increases the stiffness matrix coefficient of epoxy composites, which is demonstrated by increased stiffness matrix coefficients. Computational studies of epoxy/SiC composites have suggested up to 10% SiC nanoparticles by weight will maintain the epoxy matrix's density in industrial applications.","PeriodicalId":505725,"journal":{"name":"Engineering Research Express","volume":"49 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141654674","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}

{"title":"Experimental investigations and finite element simulation for predicting wear life of overrunning clutches","authors":"Karan A. Dutt, Shashikant J. Joshi, Dhaval B. Shah, Dipak Prajapati","doi":"10.1088/2631-8695/ad62b7","DOIUrl":"https://doi.org/10.1088/2631-8695/ad62b7","url":null,"abstract":"\u0000 An overrunning clutch, generally known as a freewheel clutch, is a direction dependent torque transmitting device that works on the principle of wedge friction. The overrunning wear characteristics of freewheels are studied using pin-on-disc tribometry. The wear experiments for freewheels are performed at accelerated loads to promote wear in a short period. The overrunning wear life of the clutch under operating conditions is predicted using an appropriate load-life relationship. A finite element-based Archard’s wear model is implemented as a numerical strategy to evaluate the wear profile. The maximum local wear for various loads is computed using experimentally obtained wear and friction coefficients. The numerical simulation is performed with an adaptive mesh technique utilizing incremental nodal displacements to predict surface wear. The experimental and numerical results are compared in terms of wear characteristics. The numerical wear results are almost 11% higher than the experimental results. The wear life of an overrunning clutch is predicted in terms of overrunning speed based on the wear amount.","PeriodicalId":505725,"journal":{"name":"Engineering Research Express","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141652591","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}

{"title":"TDDAM: Transformer Based Deep Domain Adaptation Methodology for Lithium-ion Battery Prognosis","authors":"Shanzhe Yang, Runda Jia, Xiaoguang Ma, Shuai Li","doi":"10.1088/2631-8695/ad62b2","DOIUrl":"https://doi.org/10.1088/2631-8695/ad62b2","url":null,"abstract":"\u0000 The status of health (SOH) is a vital indicator to characterize the remaining life of lithium-ion batteries (LIBs), and precise prognosis of the SOH is of great importance for battery management systems. In order to prognosis the SOH of LIBs, this paper proposed a Transformer based deep domain adaptation methodology (TDDAM). This paper applies the transformer model, which is widely used in natural language processing and other fields, to the prediction of LIBs. Meanwhile in order to solve the problem of model matching in different types of batteries or different environments, this paper combines domain adaptation method based on the maximum mean discrepancy. Firstly, we extract the data features of LIBs through position encoding and processing of the encoder structure with the multi-head self-attention mechanism as the core. Then, based on the maximum mean discrepancy index, the target domain data and the source domain data features are aligned, and the decoder part of the original transformer model is replaced with a fully connected layer for the prediction of SOH of LIBs in the target domain. This is the first time that a Transformer has been combined with the maximum mean discrepancy to be applied to LIBs prediction. Comprehensive experiments on two CALCE LIBs data showed that the TDDAM achieved smaller prognostic prediction errors over popular SOH diagnostic methods, indicating its great potential as a generic backbone for LIBs prognosis.","PeriodicalId":505725,"journal":{"name":"Engineering Research Express","volume":"1 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141655689","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}

{"title":"Analysis of crack propagation of PLA fabricated by the additive manufacturing technique","authors":"DR. AB Aziz MOHD YUSOF, Abdul Hakim Md Yusop, Haszeme Bin Abu Kasim","doi":"10.1088/2631-8695/ad62ae","DOIUrl":"https://doi.org/10.1088/2631-8695/ad62ae","url":null,"abstract":"\u0000 Understanding crack propagation is crucial for evaluating the structural integrity and reliability of additive manufacturing components, as cracks can compromise mechanical properties and potentially lead to catastrophic failures. The study of crack propagation in additive manufacturing components is used to develop strategies for mitigating crack initiation and growth, improving material properties, and optimising the design and manufacturing processes. Crack propagation in additive manufacturing components can be influenced by various factors, including material properties, design considerations, manufacturing defects, and loading conditions. Due to the identified issue, the study was carried out to investigate the crack propagation of the Fused Deposition Modeling (FDM) component using compact tension fracture testing. The experimental work started with fabricating the samples using PLA material, followed by a fracture test based on the compact tension specimen test to get a response of the structure and its crack propagation under tensile. Material properties were also collected using the dog bone tensile test. The material properties of the testing were then imported to Finite Element Analysis for further investigation of fracture mechanics. It was found that the maximum force of the sample was 141.7±28N at 1.70±0.26mm displacement, and cracks initiated around the tip and propagated upward or downward based on the initial crack location. The deformation patterns of PLA material have shown it to be brittle plastic deformation and low energy absorption before fracture.","PeriodicalId":505725,"journal":{"name":"Engineering Research Express","volume":"8 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141652489","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}