Pub Date : 2025-06-30Epub Date: 2025-04-08DOI: 10.1088/2631-8695/adc77e
Matthew T Spidell, Gaylon W Partain, Alan G Jaffe, Malcom G White, John H Lehman
DC voltage references are typically based on calibrated Zener Diodes which are subject to drift and therefore require periodic recalibration against a Primary Standard. Since it is preferable to maintain constant power to such references, the shipping and handling logistics involved in such a recalibration can present an unacceptable burden. Validation is therefore preferred, and typically accomplished by comparison against other local Zener Diodes. However, these Zener Diodes are all subject to correlated aging mechanisms. Voltage to frequency conversion represents an alternative mechanism for validation and accordingly, is not subject to aging highly correlated with the system being validated. Voltage to frequency conversion using a low space, weight, and power Voltage Controlled Oscillator offers a mechanism for identifying voltage reference drift by comparing the voltage-controlled frequency to primary frequency, typically available through GPS. This technique can validate voltage references when comparison against a primary voltage standard is impractical due to system deployment, away from a robust logistics chain. Voltage to frequency conversion may be accomplished by a Voltage Controlled Ovenized Crystal Oscillator. Using commercial-off-the-shelf hardware we constructed a test to evaluate the stability of such an oscillator for 258 days of continuous run-time, without age acceleration measures. Long-term drift was consistent with a aging model. Sequestering 2/3 of the data to construct an aging model, then comparing sequestered data, yielded a model-to-data difference of 35 ppm (35 μV/V) which may prove acceptable in supporting instruments in the 6.5-digit voltmeter class.
{"title":"Application of voltage controlled crystal oscillators to DC voltage reference validation.","authors":"Matthew T Spidell, Gaylon W Partain, Alan G Jaffe, Malcom G White, John H Lehman","doi":"10.1088/2631-8695/adc77e","DOIUrl":"https://doi.org/10.1088/2631-8695/adc77e","url":null,"abstract":"<p><p>DC voltage references are typically based on calibrated Zener Diodes which are subject to drift and therefore require periodic recalibration against a Primary Standard. Since it is preferable to maintain constant power to such references, the shipping and handling logistics involved in such a recalibration can present an unacceptable burden. Validation is therefore preferred, and typically accomplished by comparison against other local Zener Diodes. However, these Zener Diodes are all subject to correlated aging mechanisms. Voltage to frequency conversion represents an alternative mechanism for validation and accordingly, is not subject to aging highly correlated with the system being validated. Voltage to frequency conversion using a low space, weight, and power Voltage Controlled Oscillator offers a mechanism for identifying voltage reference drift by comparing the voltage-controlled frequency to primary frequency, typically available through GPS. This technique can validate voltage references when comparison against a primary voltage standard is impractical due to system deployment, away from a robust logistics chain. Voltage to frequency conversion may be accomplished by a Voltage Controlled Ovenized Crystal Oscillator. Using commercial-off-the-shelf hardware we constructed a test to evaluate the stability of such an oscillator for 258 days of continuous run-time, without age acceleration measures. Long-term drift was consistent with a <math> <msqrt><mrow><mi>t</mi></mrow> </msqrt> </math> aging model. Sequestering 2/3 of the data to construct an aging model, then comparing sequestered data, yielded a model-to-data difference of 35 ppm (35 μV/V) which may prove acceptable in supporting instruments in the 6.5-digit voltmeter class.</p>","PeriodicalId":11753,"journal":{"name":"Engineering Research Express","volume":"7 2","pages":"025308"},"PeriodicalIF":1.5,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11977046/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143989816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1088/2631-8695/ad7939
Anita Kumari and Bappa Acherjee
Metal-cutting is indispensable in manufacturing, enabling precise component fabrication for industries like construction, automotive, aerospace, and shipbuilding, where accurate, efficient cutting of thick steel plates is crucial. This paper introduces a novel case study to strategically determine the optimal metal-cutting process for thick steel plates utilizing a hybrid MOORA-PSI approach. The use of the hybrid MOORA-PSI method simplifies decision-making by integrating weight assignment and ranking of alternatives. Five prominent metal-cutting processes, including oxygen flame, plasma arc, laser, wire EDM (wire electro-discharge machining), and abrasive water jet cutting, are commonly used for cutting thick steel plates, each with unique capabilities and limitations, and are considered potential alternatives. Eight evaluation criteria, capital cost, running cost, accuracy, edge quality, kerf width, maximum thickness, production flexibility, and production rate, are used to assess these metal-cutting alternatives. Wire EDM ranks as the optimal choice for cutting thick steel plates based on defined evaluation criteria, with laser cutting closely trailing, followed by oxygen flame, abrasive water jet, and plasma cutting successively. The results are validated by comparing them with those of other MCDM approaches and by conducting a Spearman’s rank correlation coefficient test, yielding consistent results. Additionally, sensitivity analysis, employing criteria weight exchange and dynamic variations in the decision-making matrix, further confirms the accuracy and reliability of the findings.
{"title":"Strategic selection of metal-cutting processes for thick steel plates using a hybrid decision methodology","authors":"Anita Kumari and Bappa Acherjee","doi":"10.1088/2631-8695/ad7939","DOIUrl":"https://doi.org/10.1088/2631-8695/ad7939","url":null,"abstract":"Metal-cutting is indispensable in manufacturing, enabling precise component fabrication for industries like construction, automotive, aerospace, and shipbuilding, where accurate, efficient cutting of thick steel plates is crucial. This paper introduces a novel case study to strategically determine the optimal metal-cutting process for thick steel plates utilizing a hybrid MOORA-PSI approach. The use of the hybrid MOORA-PSI method simplifies decision-making by integrating weight assignment and ranking of alternatives. Five prominent metal-cutting processes, including oxygen flame, plasma arc, laser, wire EDM (wire electro-discharge machining), and abrasive water jet cutting, are commonly used for cutting thick steel plates, each with unique capabilities and limitations, and are considered potential alternatives. Eight evaluation criteria, capital cost, running cost, accuracy, edge quality, kerf width, maximum thickness, production flexibility, and production rate, are used to assess these metal-cutting alternatives. Wire EDM ranks as the optimal choice for cutting thick steel plates based on defined evaluation criteria, with laser cutting closely trailing, followed by oxygen flame, abrasive water jet, and plasma cutting successively. The results are validated by comparing them with those of other MCDM approaches and by conducting a Spearman’s rank correlation coefficient test, yielding consistent results. Additionally, sensitivity analysis, employing criteria weight exchange and dynamic variations in the decision-making matrix, further confirms the accuracy and reliability of the findings.","PeriodicalId":11753,"journal":{"name":"Engineering Research Express","volume":"46 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142268372","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 : 2024-09-17DOI: 10.1088/2631-8695/ad78aa
Zheng Bin Pang, Saiful Amri Mazlan, Ubaidillah Ubaidillah, Nur Azmah Nordin, Norzilawati Mohamad, Mohd Aidy Faizal Johari, Shahir Yasin Mohd Yusuf, Muntaz Hana Ahmad Khairi and Siti Aishah Abdul Aziz
This research explores the effects of dilution oils on the storage stability of magnetorheological grease (MRG) by studying the effect of dilution oil viscosity on the microstructure of carrier fluids medium for MRG, which can help address practical challenges encountered in the development and deployment of MRG. Three samples of MRG with 70 wt% CIP are prepared; a control, and 2 samples diluted until 10 wt% hydraulic fluid and kerosene respectively. The resulting samples were analysed using a modular compact rheometer (MCR) for oscillatory strain sweep and rotational current sweep. Rheological analyses were repeated after one year in storage. Fourier-Transform Infrared (FTIR) spectroscopy and Atomic Force Microscopy (AFM) results show significant microstructural and performance deterioration of grease thickener in the sample with kerosene, which concludes that kerosene had a very significant effect on the degradation of the grease thickener. From this study, it was revealed that low viscosity oils disrupt the reconstruction of the thickener of lithium grease, which in turn causes deteriorating shear rheological performance of MRG at off-state conditions. This comprehensive analysis explains the relationships between MRG composition, microstructural characteristics, and performance parameters, offering a foundational framework for further exploration and advancement in this scientific field.
{"title":"Microstructural analysis on the compatibility of various dilution oils on magnetorheological grease performance","authors":"Zheng Bin Pang, Saiful Amri Mazlan, Ubaidillah Ubaidillah, Nur Azmah Nordin, Norzilawati Mohamad, Mohd Aidy Faizal Johari, Shahir Yasin Mohd Yusuf, Muntaz Hana Ahmad Khairi and Siti Aishah Abdul Aziz","doi":"10.1088/2631-8695/ad78aa","DOIUrl":"https://doi.org/10.1088/2631-8695/ad78aa","url":null,"abstract":"This research explores the effects of dilution oils on the storage stability of magnetorheological grease (MRG) by studying the effect of dilution oil viscosity on the microstructure of carrier fluids medium for MRG, which can help address practical challenges encountered in the development and deployment of MRG. Three samples of MRG with 70 wt% CIP are prepared; a control, and 2 samples diluted until 10 wt% hydraulic fluid and kerosene respectively. The resulting samples were analysed using a modular compact rheometer (MCR) for oscillatory strain sweep and rotational current sweep. Rheological analyses were repeated after one year in storage. Fourier-Transform Infrared (FTIR) spectroscopy and Atomic Force Microscopy (AFM) results show significant microstructural and performance deterioration of grease thickener in the sample with kerosene, which concludes that kerosene had a very significant effect on the degradation of the grease thickener. From this study, it was revealed that low viscosity oils disrupt the reconstruction of the thickener of lithium grease, which in turn causes deteriorating shear rheological performance of MRG at off-state conditions. This comprehensive analysis explains the relationships between MRG composition, microstructural characteristics, and performance parameters, offering a foundational framework for further exploration and advancement in this scientific field.","PeriodicalId":11753,"journal":{"name":"Engineering Research Express","volume":"28 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142247710","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 : 2024-09-17DOI: 10.1088/2631-8695/ad7938
Hari Bhaskaran Anangapal and Kirubakaran Victor
India’s pursuit of offshore wind energy development, particularly along the Tamil Nadu coastline within its Exclusive Economic Zone (EEZ), faces significant spatial and economic challenges due to existing industrial activities and water depth limitations. Motivated by the need to optimize offshore wind resources and bridge the gap between onshore and offshore wind energy achievements, this study hypothesizes that ERA5 reanalysis wind data can be relied upon for assessing offshore wind resources and optimizing wind farm layouts, especially in the absence of measured data. The research employs methods such as comparing ERA5 data with empirical wind measurements, generating wind rose diagrams for layout optimization, and conducting a comprehensive financial analysis to estimate the Levelized Cost of Energy (LCoE). The results confirm the efficacy of ERA5 data, identifying an optimal wind farm layout with a capacity density of 5.17 MW per square kilometer, turbine spacing of 7.22 meters, and an LCoE of Rs. 8.84 per kWh. The study concludes that significant financial support and strategic policy interventions are essential for minimizing wake losses, optimizing capacity density, and fostering the long-term growth of India’s offshore wind energy sector, providing critical insights for policymakers, developers, and investors. The novelty of this research lies in its detailed exploration of spatial optimization and cost-effective strategies to enhance the techno-economic viability of offshore wind projects in India.
{"title":"Towards sustainable energy: integrating ERA5 data for offshore wind farm planning in India","authors":"Hari Bhaskaran Anangapal and Kirubakaran Victor","doi":"10.1088/2631-8695/ad7938","DOIUrl":"https://doi.org/10.1088/2631-8695/ad7938","url":null,"abstract":"India’s pursuit of offshore wind energy development, particularly along the Tamil Nadu coastline within its Exclusive Economic Zone (EEZ), faces significant spatial and economic challenges due to existing industrial activities and water depth limitations. Motivated by the need to optimize offshore wind resources and bridge the gap between onshore and offshore wind energy achievements, this study hypothesizes that ERA5 reanalysis wind data can be relied upon for assessing offshore wind resources and optimizing wind farm layouts, especially in the absence of measured data. The research employs methods such as comparing ERA5 data with empirical wind measurements, generating wind rose diagrams for layout optimization, and conducting a comprehensive financial analysis to estimate the Levelized Cost of Energy (LCoE). The results confirm the efficacy of ERA5 data, identifying an optimal wind farm layout with a capacity density of 5.17 MW per square kilometer, turbine spacing of 7.22 meters, and an LCoE of Rs. 8.84 per kWh. The study concludes that significant financial support and strategic policy interventions are essential for minimizing wake losses, optimizing capacity density, and fostering the long-term growth of India’s offshore wind energy sector, providing critical insights for policymakers, developers, and investors. The novelty of this research lies in its detailed exploration of spatial optimization and cost-effective strategies to enhance the techno-economic viability of offshore wind projects in India.","PeriodicalId":11753,"journal":{"name":"Engineering Research Express","volume":"8 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142247727","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 : 2024-09-17DOI: 10.1088/2631-8695/ad7230
Eliazar Elisha Audu, Akaa Agbaeze Eteng, Iyemeh Uchendu and Bourdillon O Omijeh
Metasurfaces are two-dimensional artificially engineered structures capable of manipulating the phase, direction and orientation of electromagnetic waves by exhibiting simultaneously negative values of permittivity and permeability. These unconventional properties have been tailored and explored in many applications such as in bio-sensors, waveguides and antennas. The split ring resonators are the commonly used constituent meta-atoms of metasurfaces whose design and analysis rely on commercially available numerical electromagnetic fields (EM) solvers and experimental analysis. These numerical EM solvers are based on meshing and partitioning of graphical structures into the desire grids or patches to solve Maxwell equations in discrete form. However, graphical rendering and meshing of 3D objects requires significant space-time computational resources to analyze the structure. With the cost of licenses of EM solvers being very expensive, analytical solution were explored. The use of LC resonant frequency analytical formula provides an approximate value of resonant frequency which is less accurate and does not gives information about the current characteristics induced on the constinuent meta-atom of a metasurface. This paper presents an analytical approach to the design and analysis of a doubly split double rings (DSRR) using lumped element equivalent circuit that can be solved by mesh network analysis. The resonant frequency is extracted from the induced current characteristics which agrees with simulations and experimental results. The resonant frequency errors for a single DSRR unit cell ranged from1.05% to 7%, and for two coupled DSRR unit cells, they ranged from 1.4% to 11%.
{"title":"Equivalent circuit technique for designing split ring resonator based metasurfaces","authors":"Eliazar Elisha Audu, Akaa Agbaeze Eteng, Iyemeh Uchendu and Bourdillon O Omijeh","doi":"10.1088/2631-8695/ad7230","DOIUrl":"https://doi.org/10.1088/2631-8695/ad7230","url":null,"abstract":"Metasurfaces are two-dimensional artificially engineered structures capable of manipulating the phase, direction and orientation of electromagnetic waves by exhibiting simultaneously negative values of permittivity and permeability. These unconventional properties have been tailored and explored in many applications such as in bio-sensors, waveguides and antennas. The split ring resonators are the commonly used constituent meta-atoms of metasurfaces whose design and analysis rely on commercially available numerical electromagnetic fields (EM) solvers and experimental analysis. These numerical EM solvers are based on meshing and partitioning of graphical structures into the desire grids or patches to solve Maxwell equations in discrete form. However, graphical rendering and meshing of 3D objects requires significant space-time computational resources to analyze the structure. With the cost of licenses of EM solvers being very expensive, analytical solution were explored. The use of LC resonant frequency analytical formula provides an approximate value of resonant frequency which is less accurate and does not gives information about the current characteristics induced on the constinuent meta-atom of a metasurface. This paper presents an analytical approach to the design and analysis of a doubly split double rings (DSRR) using lumped element equivalent circuit that can be solved by mesh network analysis. The resonant frequency is extracted from the induced current characteristics which agrees with simulations and experimental results. The resonant frequency errors for a single DSRR unit cell ranged from1.05% to 7%, and for two coupled DSRR unit cells, they ranged from 1.4% to 11%.","PeriodicalId":11753,"journal":{"name":"Engineering Research Express","volume":"24 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142247729","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 : 2024-09-17DOI: 10.1088/2631-8695/ad78a5
Ibrahim Haruna Umar, Ibrahim Mu’azzam Salisu, Hang Lin and Jubril Izge Hassan
Road construction projects require a thorough understanding of soil properties to ensure the stability and longevity of the infrastructure. This study investigates soil properties along a proposed 34 km road alignment in Yobe State, Nigeria, to characterize soil variability for road construction and develop a predictive model for California Bearing Ratio (CBR). Of the 34 soil samples analyzed, 30 were classified as A-3(1) and four as A-1(1) according to the AASHTO system. Geotechnical testing, including particle size distribution (grading percentages: gravel 0.02%–75.34%, sand 15.5%–90.88%, fines 8.92%–34.84%), Atterberg limits (liquid limits 17%–33%, plastic limits 14%–27%, plasticity index <12%), specific gravity (2.01 to 2.73), compaction (maximum dry density 1.83–2.19 Mg m−3, optimum moisture content 7.29%–14.42%), and CBR tests (values ranging from 5%–62%), were conducted. Correlation analyses revealed strong positive relationships between maximum dry density (r = 0.82) and specific gravity (r = 0.89) with CBR values. Cluster analysis segmented the samples into four distinct groups: Cluster 0 (11 samples), Cluster 1 (9 samples), Cluster 2 (5 samples), and Cluster 3 (9 samples). A linear regression model predicted CBR using maximum dry density and specific gravity (mean squared error = 9.82, R2 = 0.92). Based on CBR criteria, 8 out of 34 samples (CBR 20%–53%) satisfied subbase requirements, while none met the recommended minimum CBR of 80% for base course materials. This study enhances road construction planning through soil variability analysis, effective soil categorization via cluster analysis, and a reliable CBR prediction model. While on-site materials are unsuitable for subgrade and subbase layers, alternative materials or ground improvement techniques are recommended for the base course layer to enhance bearing capacity.
{"title":"Soil characterization, CBR modeling, and spatial variability analysis for road subgrade: a case study of Danchuwa – Jajere Road, Yobe State, Nigeria","authors":"Ibrahim Haruna Umar, Ibrahim Mu’azzam Salisu, Hang Lin and Jubril Izge Hassan","doi":"10.1088/2631-8695/ad78a5","DOIUrl":"https://doi.org/10.1088/2631-8695/ad78a5","url":null,"abstract":"Road construction projects require a thorough understanding of soil properties to ensure the stability and longevity of the infrastructure. This study investigates soil properties along a proposed 34 km road alignment in Yobe State, Nigeria, to characterize soil variability for road construction and develop a predictive model for California Bearing Ratio (CBR). Of the 34 soil samples analyzed, 30 were classified as A-3(1) and four as A-1(1) according to the AASHTO system. Geotechnical testing, including particle size distribution (grading percentages: gravel 0.02%–75.34%, sand 15.5%–90.88%, fines 8.92%–34.84%), Atterberg limits (liquid limits 17%–33%, plastic limits 14%–27%, plasticity index <12%), specific gravity (2.01 to 2.73), compaction (maximum dry density 1.83–2.19 Mg m−3, optimum moisture content 7.29%–14.42%), and CBR tests (values ranging from 5%–62%), were conducted. Correlation analyses revealed strong positive relationships between maximum dry density (r = 0.82) and specific gravity (r = 0.89) with CBR values. Cluster analysis segmented the samples into four distinct groups: Cluster 0 (11 samples), Cluster 1 (9 samples), Cluster 2 (5 samples), and Cluster 3 (9 samples). A linear regression model predicted CBR using maximum dry density and specific gravity (mean squared error = 9.82, R2 = 0.92). Based on CBR criteria, 8 out of 34 samples (CBR 20%–53%) satisfied subbase requirements, while none met the recommended minimum CBR of 80% for base course materials. This study enhances road construction planning through soil variability analysis, effective soil categorization via cluster analysis, and a reliable CBR prediction model. While on-site materials are unsuitable for subgrade and subbase layers, alternative materials or ground improvement techniques are recommended for the base course layer to enhance bearing capacity.","PeriodicalId":11753,"journal":{"name":"Engineering Research Express","volume":"1 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142247709","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 : 2024-09-17DOI: 10.1088/2631-8695/ad78a8
Fatima L Shubber, Saad Hameed Al-Shafaie and Nabaa Sattar Radhi
Iron aluminide is used in many industrial applications such as valve of piston; In this work, the mechanical and thermal properties of samples made of functionally graded materials (FGMs) were studied. These specimens were manufactured by powder metallurgy, consisting of different chemical composition layers of (40–50) at% aluminum. The specimens consist of: single layers (B1, B2, B3) consisting of (40, 45, and 50) at% of aluminum and the rest of iron; FGMs (double-layer) (B4, B5, B6); and FGMs (three-layer) (B7). All results of FGM were compared with its constituent layers in all tests, including the x-ray diffraction examination, and they all showed the same phases with differences in intensity (Fe3Al, FeAl, Al13Fe4, FeAl2, Fe2Al5). From the mechanical compression test, the yield point, ultimate stress, and Young’s modulus results indicated that the FGMs have an average value compared with the layer that contained them. Thermal test: FGMs have the lowest values of thermal conductivity and thermal diffusivity compared with single-layer specimens. The specific heat of FGMs has the highest value. Thermal conductivity was recorded to range from 8.08 to 6.376 W mK−1 for single and FGM specimens, respectively; thermal diffusivity from 4.6 to 0.72 mm2 S−1; and specific heat from 1.77 to 8.84 MJ/m3K.
{"title":"Investigation of the mechanical and Thermal properties of functionally graded iron aluminide","authors":"Fatima L Shubber, Saad Hameed Al-Shafaie and Nabaa Sattar Radhi","doi":"10.1088/2631-8695/ad78a8","DOIUrl":"https://doi.org/10.1088/2631-8695/ad78a8","url":null,"abstract":"Iron aluminide is used in many industrial applications such as valve of piston; In this work, the mechanical and thermal properties of samples made of functionally graded materials (FGMs) were studied. These specimens were manufactured by powder metallurgy, consisting of different chemical composition layers of (40–50) at% aluminum. The specimens consist of: single layers (B1, B2, B3) consisting of (40, 45, and 50) at% of aluminum and the rest of iron; FGMs (double-layer) (B4, B5, B6); and FGMs (three-layer) (B7). All results of FGM were compared with its constituent layers in all tests, including the x-ray diffraction examination, and they all showed the same phases with differences in intensity (Fe3Al, FeAl, Al13Fe4, FeAl2, Fe2Al5). From the mechanical compression test, the yield point, ultimate stress, and Young’s modulus results indicated that the FGMs have an average value compared with the layer that contained them. Thermal test: FGMs have the lowest values of thermal conductivity and thermal diffusivity compared with single-layer specimens. The specific heat of FGMs has the highest value. Thermal conductivity was recorded to range from 8.08 to 6.376 W mK−1 for single and FGM specimens, respectively; thermal diffusivity from 4.6 to 0.72 mm2 S−1; and specific heat from 1.77 to 8.84 MJ/m3K.","PeriodicalId":11753,"journal":{"name":"Engineering Research Express","volume":"3 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142268371","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 : 2024-09-17DOI: 10.1088/2631-8695/ad780d
Jun Li and Hong Xu
The use of microvaristor layers is an electric field control method for composite insulators. It can reduce the electric field stresses to prevent the extension of the composite insulator surface discharges and the complete flashover caused by the subsequent development of arcing. In order to improve the performance of composite insulators, a 500 kV double grading ring suspension composite insulator structure with ZnO microvaristor layers is proposed and optimized by Variable Step Crow Search Algorithm (VSCSA). A 2D axisymmetric simulation model is constructed by COMSOL, and then VSCSA is used to optimize the geometric dimensions of insulators, grading rings and microvaristors through the joint simulation of COMSOL and MATLAB. The electric field of composite insulators under clean and uniform contaminated conditions before and after optimization is studied. The results show that the optimized design can reduce the electric field strength of composite insulators under clean and uniform contaminated conditions. It is also proved that the injection of ZnO microvaristor layers into the double grading ring suspension composite insulator can improve the performance of the insulator. The research provides a new method for the design and optimization of high voltage composite insulators, which is of great significance.
{"title":"Optimization design of 500 kV double grading ring suspension composite insulator with ZnO microvaristor layers based on VSCSA","authors":"Jun Li and Hong Xu","doi":"10.1088/2631-8695/ad780d","DOIUrl":"https://doi.org/10.1088/2631-8695/ad780d","url":null,"abstract":"The use of microvaristor layers is an electric field control method for composite insulators. It can reduce the electric field stresses to prevent the extension of the composite insulator surface discharges and the complete flashover caused by the subsequent development of arcing. In order to improve the performance of composite insulators, a 500 kV double grading ring suspension composite insulator structure with ZnO microvaristor layers is proposed and optimized by Variable Step Crow Search Algorithm (VSCSA). A 2D axisymmetric simulation model is constructed by COMSOL, and then VSCSA is used to optimize the geometric dimensions of insulators, grading rings and microvaristors through the joint simulation of COMSOL and MATLAB. The electric field of composite insulators under clean and uniform contaminated conditions before and after optimization is studied. The results show that the optimized design can reduce the electric field strength of composite insulators under clean and uniform contaminated conditions. It is also proved that the injection of ZnO microvaristor layers into the double grading ring suspension composite insulator can improve the performance of the insulator. The research provides a new method for the design and optimization of high voltage composite insulators, which is of great significance.","PeriodicalId":11753,"journal":{"name":"Engineering Research Express","volume":"46 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142247708","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 : 2024-09-16DOI: 10.1088/2631-8695/ad78ab
Maulik A Modi and Tushar M Patel
Background. Diesel engines play a crucial role in ensuring human comfort and well-being across residential, commercial, transportation, and emergency response sectors because of their reliability and versatility. However, identifying alternative fuels remains a significant challenge. Objective. This study aims to develop a comprehensive mathematical model using Response Surface Methodology (RSM) to optimize the performance of Compression Ignition (CI) engines utilizing different types of plastic pyrolysis oil. Methods. Through systematic data collection and analysis, this study examines the importance of design parameters, specifically injection pressure, compression ratio, engine load, and type of plastic pyrolysis oil, which are important for specific fuel consumption. A prediction model was developed to identify the complex correlations between these factors and the fuel use. Results. The developed model serves as an effective tool for optimizing the CI engine performance under diverse operational conditions. Experimental validation involved testing diesel engines with conventional diesel fuel and various plastic pyrolysis oils, followed by optimization using RSM to achieve optimal engine performance. The engine load was identified as the most significant parameter affecting the specific fuel consumption, followed by the fuel type, injection pressure, and compression ratio. The high R-squared (99.35%) and adjusted R-squared (98.02%) values indicate that the proposed model effectively fits the experimental data. Conclusion. The RSM-based model effectively optimizes CI engine performance under varied operational conditions. It significantly reduces the time and effort required to optimize engine design variables, thus enhancing engine performance and sustainability.
背景。柴油发动机因其可靠性和多功能性，在确保人类在住宅、商业、交通和应急响应等领域的舒适和福祉方面发挥着至关重要的作用。然而，确定替代燃料仍然是一项重大挑战。研究目的本研究旨在利用响应面方法 (RSM) 建立一个综合数学模型，以优化使用不同类型塑料热解油的压燃 (CI) 发动机的性能。研究方法。通过系统的数据收集和分析，本研究考察了设计参数的重要性，特别是喷射压力、压缩比、发动机负荷和塑料热解油的类型，这些参数对具体的燃料消耗量非常重要。开发了一个预测模型，以确定这些因素与燃料使用量之间的复杂关联。结果。所开发的模型是在各种运行条件下优化 CI 发动机性能的有效工具。实验验证包括使用传统柴油和各种塑料热解油测试柴油发动机，然后使用 RSM 进行优化，以实现最佳的发动机性能。结果表明，发动机负荷是影响比耗油量的最重要参数，其次是燃料类型、喷射压力和压缩比。高 R 平方（99.35%）和调整 R 平方（98.02%）值表明，所提出的模型有效地拟合了实验数据。结论。基于 RSM 的模型有效优化了 CI 发动机在不同运行条件下的性能。它大大减少了优化发动机设计变量所需的时间和精力，从而提高了发动机的性能和可持续性。
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Pub Date : 2024-09-16DOI: 10.1088/2631-8695/ad78a6
Yong Ge, Hiu Hong Teo, Lip Kean Moey and Walisijiang Tayier
To address the issues of sample scarcity and insufficient recognition accuracy in existing deep learning models for tool wear monitoring, this study developed a milling tool wear monitoring model that combines transfer learning (TL) and deep residual networks (ResNet). The model uses continuous wavelet transform to convert vibration signals into time-frequency maps, which are then fed into the network model for analysis. ResNet50 was selected as the base feature extraction model, and transfer learning techniques were employed to update the classification layer’s weights, enabling tool wear detection. The model based on ResNet-TL achieved a detection accuracy of 94%, significantly exceeding the threshold for intelligent tool wear recognition. This accomplishment markedly improves the precision and stability of tool wear state monitoring, providing more reliable technical support for tool management in manufacturing processes. Additionally, the method demonstrated superiority in addressing the small sample problem, paving the way for future research in tool wear monitoring. By integrating advanced deep learning techniques with transfer learning, the model not only enhances detection capabilities but also improves adaptability and robustness in practical industrial applications.
{"title":"Research on tool wear condition monitoring based on deep transfer learning and residual network","authors":"Yong Ge, Hiu Hong Teo, Lip Kean Moey and Walisijiang Tayier","doi":"10.1088/2631-8695/ad78a6","DOIUrl":"https://doi.org/10.1088/2631-8695/ad78a6","url":null,"abstract":"To address the issues of sample scarcity and insufficient recognition accuracy in existing deep learning models for tool wear monitoring, this study developed a milling tool wear monitoring model that combines transfer learning (TL) and deep residual networks (ResNet). The model uses continuous wavelet transform to convert vibration signals into time-frequency maps, which are then fed into the network model for analysis. ResNet50 was selected as the base feature extraction model, and transfer learning techniques were employed to update the classification layer’s weights, enabling tool wear detection. The model based on ResNet-TL achieved a detection accuracy of 94%, significantly exceeding the threshold for intelligent tool wear recognition. This accomplishment markedly improves the precision and stability of tool wear state monitoring, providing more reliable technical support for tool management in manufacturing processes. Additionally, the method demonstrated superiority in addressing the small sample problem, paving the way for future research in tool wear monitoring. By integrating advanced deep learning techniques with transfer learning, the model not only enhances detection capabilities but also improves adaptability and robustness in practical industrial applications.","PeriodicalId":11753,"journal":{"name":"Engineering Research Express","volume":"23 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142247728","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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