Engineering Science and Technology-An International Journal-Jestech最新文献_第3页

Evaluation of a sustainable dye-exhausted resin regeneration method for cost-effective decolorization and detoxification of textile wastewater

IF 5.1 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering Science and Technology-An International Journal-Jestech

Pub Date : 2025-01-30 DOI: 10.1016/j.jestch.2025.101973

Amel Taher Moh Rabti , Akin Emrecan Gok , Burak Yuzer , Huseyin Selcuk

Despite the efficiency of the ion exchange (IEX) process in eliminating color and toxicity from textile wastewater, its extensive application is hindered by the challenges associated with recovering dye-exhausted resin using conventional regeneration methods. Thus, hazardous polymer-based decolorants are currently used to meet color standards and produce vast amounts of hazardous sludge. This study focuses on the hydrothermal alkaline regeneration (HTAR) method for regenerating exhausted strong-base anionic ion resin as an alternative to the hazardous decolorization method. It mainly emphasizes its application with trademarked regenerant (Veritas Regenerant®) after the resin was employed for decolorization and detoxification of biologically treated textile wastewater (BTTWW), aiming at sustainable treatment and reuse of such wastewater without producing hazardous sludge. The performance of the regenerated resin was assessed through various parameters, including toxicity (Microtox® test), color, chemical oxygen demand (COD), and total dissolved organic carbon (DOC). On average, the anionic IEX process achieved the removal of 96 % of color, 74 % of DOC, 43 % of COD, and 60 % of toxicity from BTTWW. Complete recovery of the resin was successfully attained using the HTAR method at 40 °C. Notably, the performance of the resin remained consistent over 50 multiple exhaustion/regeneration cycles, indicating the viability of HTAR for regenerating color-exhausted resin for repeated utilization in the treatment and reuse of biological textile wastewater. These results underscore the potential of trademarked regenerant in HTAR to improve the pre-treatment of textile wastewater before membrane wastewater reuse systems while also potentially reducing operational color removal costs in the textile sector, estimated at approximately 0.26–0.50 €/m³, to around 0.08 €/m³.

{"title":"Evaluation of a sustainable dye-exhausted resin regeneration method for cost-effective decolorization and detoxification of textile wastewater","authors":"Amel Taher Moh Rabti , Akin Emrecan Gok , Burak Yuzer , Huseyin Selcuk","doi":"10.1016/j.jestch.2025.101973","DOIUrl":"10.1016/j.jestch.2025.101973","url":null,"abstract":"<div><div>Despite the efficiency of the ion exchange (IEX) process in eliminating color and toxicity from textile wastewater, its extensive application is hindered by the challenges associated with recovering dye-exhausted resin using conventional regeneration methods. Thus, hazardous polymer-based decolorants are currently used to meet color standards and produce vast amounts of hazardous sludge. This study focuses on the hydrothermal alkaline regeneration (HTAR) method for regenerating exhausted strong-base anionic ion resin as an alternative to the hazardous decolorization method. It mainly emphasizes its application with trademarked regenerant (Veritas Regenerant®) after the resin was employed for decolorization and detoxification of biologically treated textile wastewater (BTTWW), aiming at sustainable treatment and reuse of such wastewater without producing hazardous sludge. The performance of the regenerated resin was assessed through various parameters, including toxicity (Microtox® test), color, chemical oxygen demand (COD), and total dissolved organic carbon (DOC). On average, the anionic IEX process achieved the removal of 96 % of color, 74 % of DOC, 43 % of COD, and 60 % of toxicity from BTTWW. Complete recovery of the resin was successfully attained using the HTAR method at 40 °C. Notably, the performance of the resin remained consistent over 50 multiple exhaustion/regeneration cycles, indicating the viability of HTAR for regenerating color-exhausted resin for repeated utilization in the treatment and reuse of biological textile wastewater. These results underscore the potential of trademarked regenerant in HTAR to improve the pre-treatment of textile wastewater before membrane wastewater reuse systems while also potentially reducing operational color removal costs in the textile sector, estimated at approximately 0.26–0.50 €/m<sup>3</sup>, to around 0.08 €/m<sup>3</sup>.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"63 ","pages":"Article 101973"},"PeriodicalIF":5.1,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143131180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Long-term forecasting of shield tunnel position and attitude deviation using the 1DCNN-informer method

IF 5.1 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering Science and Technology-An International Journal-Jestech

Pub Date : 2025-01-30 DOI: 10.1016/j.jestch.2025.101957

Jiajie Zhen , Ming Huang , Shuang Li , Kai Xu , Qianghu Zhao

Accurate prediction of shield machine position and attitude is crucial for ensuring the quality of tunnel construction. However, current machine learning models for predicting the position and attitude deviations of shield machines encounter significant challenges in achieving reliable long-term forecasting during shield tunneling. This study introduces a novel deep learning model, termed 1DCNN-Informer, which integrates the one-dimensional convolutional neural network (1DCNN) and the Informer model. The model was trained and validated using datasets from the Nanjing Metro shield tunnel project in China. Furthermore, the 1DCNN-Informer model was transferred to datasets from both similar and different geological conditions using the domain adversarial neural network (DANN) transfer learning method. The importance of input features was analyzed using the Shapley additive explanations (SHAP) method, complemented by experiments with various input parameter combinations. Results demonstrate that the 1DCNN-Informer model achieves superior performance compared to the Informer model and surpasses other comparative models, such as PatchTST, iTransformer, and Dlinear, in the majority of input sequence length and prediction sequence length combinations. Additionally, the DANN transfer learning method significantly enhances the 1DCNN-Informer model’s performance in the target domains dataset. The cutterhead rotation speed, advance speed, and chamber pressure are of critical importance in the prediction of shield position and attitude deviation. The proposed model not only represents a significant advancement in intelligent shield tunneling but also holds potential for broader application in automated equipment operations and multi-domain transfer learning studies in the field of engineering.

{"title":"Long-term forecasting of shield tunnel position and attitude deviation using the 1DCNN-informer method","authors":"Jiajie Zhen , Ming Huang , Shuang Li , Kai Xu , Qianghu Zhao","doi":"10.1016/j.jestch.2025.101957","DOIUrl":"10.1016/j.jestch.2025.101957","url":null,"abstract":"<div><div>Accurate prediction of shield machine position and attitude is crucial for ensuring the quality of tunnel construction. However, current machine learning models for predicting the position and attitude deviations of shield machines encounter significant challenges in achieving reliable long-term forecasting during shield tunneling. This study introduces a novel deep learning model, termed 1DCNN-Informer, which integrates the one-dimensional convolutional neural network (1DCNN) and the Informer model. The model was trained and validated using datasets from the Nanjing Metro shield tunnel project in China. Furthermore, the 1DCNN-Informer model was transferred to datasets from both similar and different geological conditions using the domain adversarial neural network (DANN) transfer learning method. The importance of input features was analyzed using the Shapley additive explanations (SHAP) method, complemented by experiments with various input parameter combinations. Results demonstrate that the 1DCNN-Informer model achieves superior performance compared to the Informer model and surpasses other comparative models, such as PatchTST, iTransformer, and Dlinear, in the majority of input sequence length and prediction sequence length combinations. Additionally, the DANN transfer learning method significantly enhances the 1DCNN-Informer model’s performance in the target domains dataset. The cutterhead rotation speed, advance speed, and chamber pressure are of critical importance in the prediction of shield position and attitude deviation. The proposed model not only represents a significant advancement in intelligent shield tunneling but also holds potential for broader application in automated equipment operations and multi-domain transfer learning studies in the field of engineering.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"63 ","pages":"Article 101957"},"PeriodicalIF":5.1,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143131107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Thermohydraulic performance evaluation of a heat exchanger mounted with oval inclined twisted rings

IF 5.1 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering Science and Technology-An International Journal-Jestech

Pub Date : 2025-01-30 DOI: 10.1016/j.jestch.2025.101981

P. Samruaisin , V. Chuwattanakul , P. Thapmanee , M. Kumar , P. Naphon , N. Maruyama , M. Hirota , S. Eiamsa-ard

This research examines the effects of oval inclined twisted rings (I-TRs) on thermal performance characteristics. Heat transfer enhancement, friction factor, and thermal enhancement factor tests were conducted under uniform wall heat flux with Reynolds numbers (Re) varying from 6000 to 20,000. A systematic investigation was carried out to examine the influence of different pitch ratios (p/D) and oval-ring inclination angles (θ) on thermal enhancement factor (TEF). The experimental results reveal that the Nusselt number increases with decreasing pitch ratio (p/D) and inclination angle (θ) of the I-TRs. At p/D = 1.5, the Nusselt numbers are approximately 8.59 % to 18.78 % higher than those for I-TRs with p/D values of 2.0 and 2.5. At the smallest inclination angle, θ = 30°, the Nusselt numbers are approximately higher than those at θ = 45°, 60°, 75°, and 90° by around 1.56 %, 7.21 %, 13.74 %, and 27.14 %, respectively. At a p/D ratio of 1.5 and an inclination angle of θ = 30°, the resulting thermal enhancement factor (TEF) consistently exceeds unity across the entire Reynolds number (Re) range. In contrast, for other geometries and configurations, some TEF values fall below unity at higher Re. Within the studied range, the highest TEF of 1.12 is achieved at θ = 30°, p/D = 1.5, and Re = 6,000. The key finding suggests that the performance of the thermal system is highly dependent on both the configuration and operational conditions.

{"title":"Thermohydraulic performance evaluation of a heat exchanger mounted with oval inclined twisted rings","authors":"P. Samruaisin , V. Chuwattanakul , P. Thapmanee , M. Kumar , P. Naphon , N. Maruyama , M. Hirota , S. Eiamsa-ard","doi":"10.1016/j.jestch.2025.101981","DOIUrl":"10.1016/j.jestch.2025.101981","url":null,"abstract":"<div><div>This research examines the effects of oval inclined twisted rings (I-TRs) on thermal performance characteristics. Heat transfer enhancement, friction factor, and thermal enhancement factor tests were conducted under uniform wall heat flux with Reynolds numbers (<em>Re</em>) varying from 6000 to 20,000. A systematic investigation was carried out to examine the influence of different pitch ratios (<em>p/D</em>) and oval-ring inclination angles (<em>θ</em>) on thermal enhancement factor (<em>TEF</em>). The experimental results reveal that the Nusselt number increases with decreasing pitch ratio (<em>p/D</em>) and inclination angle (<em>θ</em>) of the I-TRs. At <em>p/D</em> = 1.5, the Nusselt numbers are approximately 8.59 % to 18.78 % higher than those for I-TRs with <em>p/D</em> values of 2.0 and 2.5. At the smallest inclination angle, <em>θ</em> = 30°, the Nusselt numbers are approximately higher than those at <em>θ</em> = 45°, 60°, 75°, and 90° by around 1.56 %, 7.21 %, 13.74 %, and 27.14 %, respectively. At a <em>p/D</em> ratio of 1.5 and an inclination angle of <em>θ</em> = 30°, the resulting thermal enhancement factor (<em>TEF</em>) consistently exceeds unity across the entire Reynolds number (Re) range. In contrast, for other geometries and configurations, some <em>TEF</em> values fall below unity at higher <em>Re</em>. Within the studied range, the highest <em>TEF</em> of 1.12 is achieved at <em>θ</em> = 30°, <em>p/D</em> = 1.5, and <em>Re</em> = 6,000. The key finding suggests that the performance of the thermal system is highly dependent on both the configuration and operational conditions.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"63 ","pages":"Article 101981"},"PeriodicalIF":5.1,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143131178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Characterization and analysis of Ca-Zn ferrite nanoparticles based flexible metamaterial for sensing applications

IF 5.1 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering Science and Technology-An International Journal-Jestech

Pub Date : 2025-01-29 DOI: 10.1016/j.jestch.2025.101974

Md.Zikrul Bari Chowdhury , Mohammad Tariqul Islam , Iskandar Yahya , Abdulmajeed M. Alenezi , Mohamed S. Soliman , Md. Samsuzzaman

This study presents a flexible Ca-Zn ferrite-based metamaterial designed for microwave sensing application, particularly in the detection of dairy products. The design incorporates a split-ring resonator (SRR) unit cell fabricated on a flexible substrate synthesized through a sol–gel process, integrating PVA glue with Ca-Zn ferrite nanoparticles. Structural characterization through X-ray diffraction (XRD) and field emission scanning electron microscopy (FESEM) confirmed the composite’s structural integrity and electromagnetic suitability. The MTM exhibited multi-frequency resonance at 2.4 GHz, 3.68 GHz, and 7 GHz, with the C-band resonance demonstrating high sensitivity for sensing applications. A key advantage of the design is its flexibility maintaining stable performance under bending angles up to 90 degrees without degrading performance. This work highlights the versatility and adaptability of the proposed metamaterial, making it a promising solution for microwave sensing technologies.

{"title":"Characterization and analysis of Ca-Zn ferrite nanoparticles based flexible metamaterial for sensing applications","authors":"Md.Zikrul Bari Chowdhury , Mohammad Tariqul Islam , Iskandar Yahya , Abdulmajeed M. Alenezi , Mohamed S. Soliman , Md. Samsuzzaman","doi":"10.1016/j.jestch.2025.101974","DOIUrl":"10.1016/j.jestch.2025.101974","url":null,"abstract":"<div><div>This study presents a flexible Ca-Zn ferrite-based metamaterial designed for microwave sensing application, particularly in the detection of dairy products. The design incorporates a split-ring resonator (SRR) unit cell fabricated on a flexible substrate synthesized through a sol–gel process, integrating PVA glue with Ca-Zn ferrite nanoparticles. Structural characterization through X-ray diffraction (XRD) and field emission scanning electron microscopy (FESEM) confirmed the composite’s structural integrity and electromagnetic suitability. The MTM exhibited multi-frequency resonance at 2.4 GHz, 3.68 GHz, and 7 GHz, with the C-band resonance demonstrating high sensitivity for sensing applications. A key advantage of the design is its flexibility maintaining stable performance under bending angles up to 90 degrees without degrading performance. This work highlights the versatility and adaptability of the proposed metamaterial, making it a promising solution for microwave sensing technologies.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"63 ","pages":"Article 101974"},"PeriodicalIF":5.1,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143131109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A hybrid approach for the detection of images generated with multi generator MS-DCGAN

IF 5.1 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering Science and Technology-An International Journal-Jestech

Pub Date : 2025-01-28 DOI: 10.1016/j.jestch.2025.101969

Selim Sürücü , Banu Diri

Over the past few years, there have been significant advances in remote sensing technology that have considerably expanded the range of research that can be conducted using remote sensing systems. Various fields, from agriculture to defense applications, use remote sensing imagery, primarily acquired by sensors mounted on vehicles like satellites and UAVs. In addition to advances in remote sensing technology, there have also been major advancements in deep learning. In recent years, there has been a substantial increase in the studies on these two topics. Generative Adversarial Networks (GAN) technology, another area of artificial intelligence and deep learning research, has taken the generation of fake satellite images to a new level. Users can use these artificial images for a variety of purposes, including information concealment and data expansion. Malicious uses of the generated fake images could trigger international crises. In this paper, we propose a new method for the generation and detection of fake satellite images. The MultiSpectral Deep Convolutional GAN (MS-DCGAN) model is developed to generate fake multispectral images, and the TransStacking model is proposed to distinguish between fake images and real images. This model is tested both as a single generator and multi generator model. The TransStacking (DenseNet201+stacking) model showed a very high success rate achieving 100% accuracy for single generator and 98% accuracy for multi generator MS-DCGAN, respectively. The proposed model is an advanced hybrid model that provides the best results in multi-spectral images and can be applied in diverse domains. Since the TransStacking model is a modular hybrid model, it can be used with many different old and new models. Furthermore, the effect of the models in the base part of the stacking module on the results was also analyzed by performing ablation analysis on the DenseNet201+stacking model, where the best results were obtained.

{"title":"A hybrid approach for the detection of images generated with multi generator MS-DCGAN","authors":"Selim Sürücü , Banu Diri","doi":"10.1016/j.jestch.2025.101969","DOIUrl":"10.1016/j.jestch.2025.101969","url":null,"abstract":"<div><div>Over the past few years, there have been significant advances in remote sensing technology that have considerably expanded the range of research that can be conducted using remote sensing systems. Various fields, from agriculture to defense applications, use remote sensing imagery, primarily acquired by sensors mounted on vehicles like satellites and UAVs. In addition to advances in remote sensing technology, there have also been major advancements in deep learning. In recent years, there has been a substantial increase in the studies on these two topics. Generative Adversarial Networks (GAN) technology, another area of artificial intelligence and deep learning research, has taken the generation of fake satellite images to a new level. Users can use these artificial images for a variety of purposes, including information concealment and data expansion. Malicious uses of the generated fake images could trigger international crises. In this paper, we propose a new method for the generation and detection of fake satellite images. The MultiSpectral Deep Convolutional GAN (MS-DCGAN) model is developed to generate fake multispectral images, and the TransStacking model is proposed to distinguish between fake images and real images. This model is tested both as a single generator and multi generator model. The TransStacking (DenseNet201+stacking) model showed a very high success rate achieving 100% accuracy for single generator and 98% accuracy for multi generator MS-DCGAN, respectively. The proposed model is an advanced hybrid model that provides the best results in multi-spectral images and can be applied in diverse domains. Since the TransStacking model is a modular hybrid model, it can be used with many different old and new models. Furthermore, the effect of the models in the base part of the stacking module on the results was also analyzed by performing ablation analysis on the DenseNet201+stacking model, where the best results were obtained.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"63 ","pages":"Article 101969"},"PeriodicalIF":5.1,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143131108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

State-of-the-art review of contact and friction analysis with a spherical hinge and structural stability research on horizontal rotating bridges

IF 5.1 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering Science and Technology-An International Journal-Jestech

Pub Date : 2025-01-01 DOI: 10.1016/j.jestch.2024.101917

Yuanxun Zheng , Shuaijie Zhang , Junjie Ma , Meng Sun , Jingjiang Wu

Horizontal rotation is the most commonly used method for constructing rotating bridges. A spherical hinge is a critical component in a horizontal rotation system of bridges, and the hinge has a complex stress state that directly affects security and stability during rotation construction. This paper takes spherical hinge as the research object, and sorts out the logical relationship between the contact and frictional behavior of spherical hinges and the stability of rotary structures. It systematically summarizes the current research status on the mechanical behavior of spherical hinges in the contact and friction processes and the structural stability of horizontal rotating bridges. The contact problem of a spherical hinge is investigated in terms of elasticity mechanics and contact mechanics theory. Research studies that utilize mechanical analytical models to solve contact stress and numerical simulation methods to analyze contact problems are summarized. The vertical friction moment of the spherical hinge is obtained based on a weighing test, the intrinsic connection between the contact and friction forces during the rotation of the spherical hinge is explored, and the friction force model and calculated traction force during the process of horizontal rotation are discussed. Finally, the form of instability and the mechanism for overturning the resistance of the rotating structure are analyzed. Research on the unbalanced factor of the rotating system and the effect of external loads on the stability of the structural anti-overturning are also discussed. This paper summarizes the research studies on the contact and friction analysis and the structural stability of the horizontal rotating process of bridges to provide theoretical guidance for optimizing spherical hinges and constructing rotating bridges.

{"title":"State-of-the-art review of contact and friction analysis with a spherical hinge and structural stability research on horizontal rotating bridges","authors":"Yuanxun Zheng , Shuaijie Zhang , Junjie Ma , Meng Sun , Jingjiang Wu","doi":"10.1016/j.jestch.2024.101917","DOIUrl":"10.1016/j.jestch.2024.101917","url":null,"abstract":"<div><div>Horizontal rotation is the most commonly used method for constructing rotating bridges. A spherical hinge is a critical component in a horizontal rotation system of bridges, and the hinge has a complex stress state that directly affects security and stability during rotation construction. This paper takes spherical hinge as the research object, and sorts out the logical relationship between the contact and frictional behavior of spherical hinges and the stability of rotary structures. It systematically summarizes the current research status on the mechanical behavior of spherical hinges in the contact and friction processes and the structural stability of horizontal rotating bridges. The contact problem of a spherical hinge is investigated in terms of elasticity mechanics and contact mechanics theory. Research studies that utilize mechanical analytical models to solve contact stress and numerical simulation methods to analyze contact problems are summarized. The vertical friction moment of the spherical hinge is obtained based on a weighing test, the intrinsic connection between the contact and friction forces during the rotation of the spherical hinge is explored, and the friction force model and calculated traction force during the process of horizontal rotation are discussed. Finally, the form of instability and the mechanism for overturning the resistance of the rotating structure are analyzed. Research on the unbalanced factor of the rotating system and the effect of external loads on the stability of the structural anti-overturning are also discussed. This paper summarizes the research studies on the contact and friction analysis and the structural stability of the horizontal rotating process of bridges to provide theoretical guidance for optimizing spherical hinges and constructing rotating bridges.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"61 ","pages":"Article 101917"},"PeriodicalIF":5.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143138048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design, fabrication, and performance analysis of a silicon solar cell integrated transparent antenna for wireless communications

IF 5.1 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering Science and Technology-An International Journal-Jestech

Pub Date : 2025-01-01 DOI: 10.1016/j.jestch.2024.101915

Emraul Islam Emon , Afia Mubassira Islam , Muhammad Shahriar Bashar , Anis Ahmed

The solar cell integrated transparent antenna will serve the purpose of power generation as well as an antenna for satellites and can act as an asset to expand the possibilities of green technology. The goal is to enhance antenna characteristics without hampering solar cell performance. In this work, a super solar integrated optically transparent microstrip patch antenna has been studied using CST Microwave Studio along with Lumerical FDTD and DEVICE solutions. The optically transparent antenna has a Soda-lime glass substrate, with Indium Tin Oxide patch and ground plane. The fabricated antenna is integrated with a 25

\times

40 mm² thin-film silicon solar cell via epoxy resin. UV–Vis spectroscopy results revealed more than 90% transmissivity over a significant visible wavelength range. It has an operational bandwidth of 80 MHz (@5.48 GHz) and solar simulator results indicate that the photovoltaic performance of the proposed device is similar to that of a standalone solar cell.

{"title":"Design, fabrication, and performance analysis of a silicon solar cell integrated transparent antenna for wireless communications","authors":"Emraul Islam Emon , Afia Mubassira Islam , Muhammad Shahriar Bashar , Anis Ahmed","doi":"10.1016/j.jestch.2024.101915","DOIUrl":"10.1016/j.jestch.2024.101915","url":null,"abstract":"<div><div>The solar cell integrated transparent antenna will serve the purpose of power generation as well as an antenna for satellites and can act as an asset to expand the possibilities of green technology. The goal is to enhance antenna characteristics without hampering solar cell performance. In this work, a super solar integrated optically transparent microstrip patch antenna has been studied using CST Microwave Studio along with Lumerical FDTD and DEVICE solutions. The optically transparent antenna has a Soda-lime glass substrate, with Indium Tin Oxide patch and ground plane. The fabricated antenna is integrated with a 25 <span><math><mo>×</mo></math></span> 40 mm<sup>2</sup> thin-film silicon solar cell via epoxy resin. UV–Vis spectroscopy results revealed more than 90% transmissivity over a significant visible wavelength range. It has an operational bandwidth of 80 MHz (@5.48 GHz) and solar simulator results indicate that the photovoltaic performance of the proposed device is similar to that of a standalone solar cell.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"61 ","pages":"Article 101915"},"PeriodicalIF":5.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143138049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Millimeter-wave monopole antenna with circular polarization utilizing FSS polarizer for 5G communications

IF 5.1 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering Science and Technology-An International Journal-Jestech

Pub Date : 2025-01-01 DOI: 10.1016/j.jestch.2024.101931

Meshari D. Alanazi , Wael A.E. Ali , M.A. Abdelhady , Ahmed A. Ibrahim

A wide-band circularly polarized (CP) and small-size monopole antenna for millimeter wave (mm-wave) communication is presented in this paper. The monopole antenna consists of a Mickey Mouse-shaped radiator fed by a 50 Ω microstrip line on the top view of 0.203 mm RO4003C (εr = 3.5) substrate and a partial ground plane on the other side. The antenna has wide band operation extended from 24 GHz up to 38 GHz. The frequency selective surface (FSS) cells are employed to convert the linear polarization (LP) to CP. The unit cell of the FSS is composed of a dual rectangular strip with chamfered edges layout and printed on one side of a 1.575 mm RO5880 (εr = 2.2) substrate. The 3 × 3 FSS converts the illuminated LP wave to CP transmitted wave by utilizing two equally amplitude and 90° phase difference wave components. The suggested antenna is combined with the FSS cells to achieve wide-band operation from 24 GHz to 38 GHz (45.16 %). As well, the 3-dB axial ratio (AR) is extended from 27 GHz to 30.3 GHz (11.5 %) with a gain ranging from 4.2 dBi to 6.3 dB. From the outcomes, the antenna can be utilized for 5G communication.

{"title":"Millimeter-wave monopole antenna with circular polarization utilizing FSS polarizer for 5G communications","authors":"Meshari D. Alanazi , Wael A.E. Ali , M.A. Abdelhady , Ahmed A. Ibrahim","doi":"10.1016/j.jestch.2024.101931","DOIUrl":"10.1016/j.jestch.2024.101931","url":null,"abstract":"<div><div>A wide-band circularly polarized (CP) and small-size monopole antenna for millimeter wave (mm-wave) communication is presented in this paper. The monopole antenna consists of a Mickey Mouse-shaped radiator fed by a 50 Ω microstrip line on the top view of 0.203 mm RO4003C (εr = 3.5) substrate and a partial ground plane on the other side. The antenna has wide band operation extended from 24 GHz up to 38 GHz. The frequency selective surface (FSS) cells are employed to convert the linear polarization (LP) to CP. The unit cell of the FSS is composed of a dual rectangular strip with chamfered edges layout and printed on one side of a 1.575 mm RO5880 (εr = 2.2) substrate. The 3 × 3 FSS converts the illuminated LP wave to CP transmitted wave by utilizing two equally amplitude and 90° phase difference wave components. The suggested antenna is combined with the FSS cells to achieve wide-band operation from 24 GHz to 38 GHz (45.16 %). As well, the 3-dB axial ratio (AR) is extended from 27 GHz to 30.3 GHz (11.5 %) with a gain ranging from 4.2 dBi to 6.3 dB. From the outcomes, the antenna can be utilized for 5G communication.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"61 ","pages":"Article 101931"},"PeriodicalIF":5.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143138055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sample selection using multi-task autoencoders in federated learning with non-IID data

IF 5.1 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering Science and Technology-An International Journal-Jestech

Pub Date : 2025-01-01 DOI: 10.1016/j.jestch.2024.101920

Emre Ardıç, Yakup Genç

Federated learning is a machine learning paradigm in which multiple devices collaboratively train a model under the supervision of a central server while ensuring data privacy. However, its performance is often hindered by redundant, malicious, or abnormal samples, leading to model degradation and inefficiency. To overcome these issues, we propose novel sample selection methods for image classification, employing a multi-task autoencoder to estimate sample contributions through loss and feature analysis. Our approach incorporates unsupervised outlier detection, using one-class support vector machine (OCSVM), isolation forest (IF), and adaptive loss threshold (AT) methods managed by a central server to filter noisy samples on clients. We also propose a multi-class deep support vector data description (SVDD) loss controlled by a central server to enhance feature-based sample selection. We validate our methods on CIFAR10 and MNIST datasets across varying numbers of clients, non-IID distributions, and noise levels up to 40%. The results show significant accuracy improvements with loss-based sample selection, achieving gains of up to 7.02% on CIFAR10 with OCSVM and 1.83% on MNIST with AT. Additionally, our federated SVDD loss further improves feature-based sample selection, yielding accuracy gains of up to 0.99% on CIFAR10 with OCSVM. These results show the effectiveness of our methods in improving model accuracy across various client counts and noise conditions.

{"title":"Sample selection using multi-task autoencoders in federated learning with non-IID data","authors":"Emre Ardıç, Yakup Genç","doi":"10.1016/j.jestch.2024.101920","DOIUrl":"10.1016/j.jestch.2024.101920","url":null,"abstract":"<div><div>Federated learning is a machine learning paradigm in which multiple devices collaboratively train a model under the supervision of a central server while ensuring data privacy. However, its performance is often hindered by redundant, malicious, or abnormal samples, leading to model degradation and inefficiency. To overcome these issues, we propose novel sample selection methods for image classification, employing a multi-task autoencoder to estimate sample contributions through loss and feature analysis. Our approach incorporates unsupervised outlier detection, using one-class support vector machine (OCSVM), isolation forest (IF), and adaptive loss threshold (AT) methods managed by a central server to filter noisy samples on clients. We also propose a multi-class deep support vector data description (SVDD) loss controlled by a central server to enhance feature-based sample selection. We validate our methods on CIFAR10 and MNIST datasets across varying numbers of clients, non-IID distributions, and noise levels up to 40%. The results show significant accuracy improvements with loss-based sample selection, achieving gains of up to 7.02% on CIFAR10 with OCSVM and 1.83% on MNIST with AT. Additionally, our federated SVDD loss further improves feature-based sample selection, yielding accuracy gains of up to 0.99% on CIFAR10 with OCSVM. These results show the effectiveness of our methods in improving model accuracy across various client counts and noise conditions.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"61 ","pages":"Article 101920"},"PeriodicalIF":5.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143138052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhanced fault diagnosis of rolling bearings using attention-augmented separable residual networks

IF 5.1 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Engineering Science and Technology-An International Journal-Jestech

Pub Date : 2025-01-01 DOI: 10.1016/j.jestch.2024.101930

Chuang Liang , Xuelin Mu , Xiaoguang Zhang , Fanfan Lu , Chengcheng Wang , Yubo Shao

Recently, with the quick development of industrial equipment automation, convolutional neural networks (CNN) have been broadly applied to the intelligent fault diagnosis of rolling bearings. In order to solve the problems of gradient vanishing, gradient explosion, and too many training parameters in deep convolutional networks that lead to low diagnostic accuracy and training efficiency of network models, a bearing fault diagnosis method based on an attention-augmented separable convolutional residual network (ASResnet) is proposed. First, the bearing vibration signal data is converted into a 2D grayscale map as an input to the network. Then, residual blocks with separable convolutions were constructed, allowing automatic learning of high-level representations from input images by stacking multiple separable convolutional residual blocks. Separable convolution effectively reduces the number of network parameters and improves computational speed. Finally, a feature extractor based on the Convolutional Block Attention Module (CBAM) is constructed so that the network focuses on the key feature regions to further improve the diagnostic performance. Validation was conducted using a Case Western Reserve University bearing dataset and three actual engineering datasets of production equipment in a cement plant. The experimental results show that ASResnet is able to improve the diagnostic accuracy and reduce the network training time of the CWRU dataset, and it also obtains a high accuracy rate in fault diagnosis for engineering applications in the cement production equipment industry.

{"title":"Enhanced fault diagnosis of rolling bearings using attention-augmented separable residual networks","authors":"Chuang Liang , Xuelin Mu , Xiaoguang Zhang , Fanfan Lu , Chengcheng Wang , Yubo Shao","doi":"10.1016/j.jestch.2024.101930","DOIUrl":"10.1016/j.jestch.2024.101930","url":null,"abstract":"<div><div>Recently, with the quick development of industrial equipment automation, convolutional neural networks (CNN) have been broadly applied to the intelligent fault diagnosis of rolling bearings. In order to solve the problems of gradient vanishing, gradient explosion, and too many training parameters in deep convolutional networks that lead to low diagnostic accuracy and training efficiency of network models, a bearing fault diagnosis method based on an attention-augmented separable convolutional residual network (ASResnet) is proposed. First, the bearing vibration signal data is converted into a 2D grayscale map as an input to the network. Then, residual blocks with separable convolutions were constructed, allowing automatic learning of high-level representations from input images by stacking multiple separable convolutional residual blocks. Separable convolution effectively reduces the number of network parameters and improves computational speed. Finally, a feature extractor based on the Convolutional Block Attention Module (CBAM) is constructed so that the network focuses on the key feature regions to further improve the diagnostic performance. Validation was conducted using a Case Western Reserve University bearing dataset and three actual engineering datasets of production equipment in a cement plant. The experimental results show that ASResnet is able to improve the diagnostic accuracy and reduce the network training time of the CWRU dataset, and it also obtains a high accuracy rate in fault diagnosis for engineering applications in the cement production equipment industry.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"61 ","pages":"Article 101930"},"PeriodicalIF":5.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143138496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0