Ain Shams Engineering Journal最新文献

英文中文

Modified pervious concrete containing biomass aggregate: Sustainability and environmental benefits

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-24 DOI: 10.1016/j.asej.2025.103324

Akram M. Mhaya , Shahiron Shahidan , Sharifah Salwa Mohd Zuki , S.J.S. Hakim , Mohd Haziman Wan Ibrahim , Mohamad Azim Mohammad Azmi , Ghasan Fahim Huseien

Pervious concrete (PC) can be called porous concrete or no fine concrete that has a high rate of permeability and low compressive strength. In general, compressive strength is inversely related to the void ratio. In this research, PC incorporating biomass as a coarse aggregate replacement (0 %–10 %) was assessed utilizing compressive strength tests in a systematic way. Here, response surface methodology (RSM) was utilized in designing the experimental works. This study focused on the effect with respect to biomass aggregate (BA) on the compressive strength and the void ratio of PC. Three groups of mixtures with 0 %, 5 % and 10 % of BA were experimented with. The first group was a control mix without additives. The second group contained gellan gum (GG) and silica fume (SF) as additives. The third group comprised rice husk ash (RHA), fly ash (FA) and SF as blended cement. Compressive strength, permeability, void ratio as well as water absorption tests were conducted. The test results showed that BA, as a partial replacement of natural aggregate, tends to reduce the compressive strength of PC. Specimens with blended cement containing 5 % of BA achieved 12.10 MPa, which is 46.7 % higher than the control mix, which achieved 6.45 MPa, after 28 days of curing. Note that the compressive strength of the specimens modified with pozzolanic materials (FA, SF, and RHA) and containing 10 % of BA was 42.5 % higher than the control mix. In contrast, specimens with GG and SF achieved almost the same compressive strength compared with the control mix. This is expected to reignite the interest in PC containing BA for sustainable construction. However, it was also deduced that the outcomes of both the mathematical and experimental models of RSM were accurate and consistent. Strong correlation and minimum error were indicated by the correlation statistical indicators (R²), which were higher than 0.98, and the error was less than 0.2.

{"title":"Modified pervious concrete containing biomass aggregate: Sustainability and environmental benefits","authors":"Akram M. Mhaya , Shahiron Shahidan , Sharifah Salwa Mohd Zuki , S.J.S. Hakim , Mohd Haziman Wan Ibrahim , Mohamad Azim Mohammad Azmi , Ghasan Fahim Huseien","doi":"10.1016/j.asej.2025.103324","DOIUrl":"10.1016/j.asej.2025.103324","url":null,"abstract":"<div><div>Pervious concrete (PC) can be called porous concrete or no fine concrete that has a high rate of permeability and low compressive strength. In general, compressive strength is inversely related to the void ratio. In this research, PC incorporating biomass as a coarse aggregate replacement (0 %–10 %) was assessed utilizing compressive strength tests in a systematic way. Here, response surface methodology (RSM) was utilized in designing the experimental works. This study focused on the effect with respect to biomass aggregate (BA) on the compressive strength and the void ratio of PC. Three groups of mixtures with 0 %, 5 % and 10 % of BA were experimented with. The first group was a control mix without additives. The second group contained gellan gum (GG) and silica fume (SF) as additives. The third group comprised rice husk ash (RHA), fly ash (FA) and SF as blended cement. Compressive strength, permeability, void ratio as well as water absorption tests were conducted. The test results showed that BA, as a partial replacement of natural aggregate, tends to reduce the compressive strength of PC. Specimens with blended cement containing 5 % of BA achieved 12.10 MPa, which is 46.7 % higher than the control mix, which achieved 6.45 MPa, after 28 days of curing. Note that the compressive strength of the specimens modified with pozzolanic materials (FA, SF, and RHA) and containing 10 % of BA was 42.5 % higher than the control mix. In contrast, specimens with GG and SF achieved almost the same compressive strength compared with the control mix. This is expected to reignite the interest in PC containing BA for sustainable construction. However, it was also deduced that the outcomes of both the mathematical and experimentalmodels of RSM were accurate and consistent. Strong correlation and minimum error were indicated by the correlation statistical indicators (R<sup>2</sup>), which were higher than 0.98, and the error was less than 0.2.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 3","pages":"Article 103324"},"PeriodicalIF":6.0,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143474143","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

Advanced techniques for decomposing recurrent curvature tensors in Tachibana spaces and generalized geometric structures

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-24 DOI: 10.1016/j.asej.2025.103326

Sukh Pal Singh , Indiwar Singh Chauhan , T.S. Chauhan , Nikhil Kumar , Anshul Kumar

This paper presents a comprehensive analysis of advanced techniques for decomposing recurrent curvature tensors across diverse geometric frameworks. By integrating classical methodologies with modern approaches, we develop novel methods that enhance the understanding of recurrent tensors within complex geometric settings. Our study extends the mathematical foundations of tensor decomposition with a focus on its implications for Kählerian and Tachibana structures. Through rigorous theoretical analysis and computational simulations, we demonstrate the efficacy of these methods, offering precise and meaningful results. This investigation specifically addresses the recurrent and bi-recurrent behaviors of curvature tensor fields in these spaces, providing new insights into their geometric structures. We also explore the implications of the Bianchi identity and introduce the concept of Weyl-concircular curvature tensor field and tri-recurrent Tachibana spaces. A detailed analysis of the decomposition of curvature tensors and covariant tensor fields is presented, utilizing advanced mathematical tools and techniques.

{"title":"Advanced techniques for decomposing recurrent curvature tensors in Tachibana spaces and generalized geometric structures","authors":"Sukh Pal Singh , Indiwar Singh Chauhan , T.S. Chauhan , Nikhil Kumar , Anshul Kumar","doi":"10.1016/j.asej.2025.103326","DOIUrl":"10.1016/j.asej.2025.103326","url":null,"abstract":"<div><div>This paper presents a comprehensive analysis of advanced techniques for decomposing recurrent curvature tensors across diverse geometric frameworks. By integrating classical methodologies with modern approaches, we develop novel methods that enhance the understanding of recurrent tensors within complex geometric settings. Our study extends the mathematical foundations of tensor decomposition with a focus on its implications for Kählerian and Tachibana structures. Through rigorous theoretical analysis and computational simulations, we demonstrate the efficacy of these methods, offering precise and meaningful results. This investigation specifically addresses the recurrent and bi-recurrent behaviors of curvature tensor fields in these spaces, providing new insights into their geometric structures. We also explore the implications of the Bianchi identity and introduce the concept of Weyl-concircular curvature tensor field and tri-recurrent Tachibana spaces. A detailed analysis of the decomposition of curvature tensors and covariant tensor fields is presented, utilizing advanced mathematical tools and techniques.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 3","pages":"Article 103326"},"PeriodicalIF":6.0,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143479308","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

Current transformer saturation detection by cross-correlation with independent target signal

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-24 DOI: 10.1016/j.asej.2025.103314

Mahmoud M. Elgamasy , Mohamed S. Zaky , Ahmed F. Zobaa , Mahmoud A. Elsadd

The saturation of current transformers (CTs) leads to distortion in secondary current, potentially causing malfunction in protective relays within power systems. Detecting the saturated portions in the measured signal and reconstructing the primary reference current are essential to prevent relay malfunctions and ensure sensitivity during faults. Existing methods in the literature still face challenges in improving accuracy, especially in the presence of noise in the measured signal. The proposed method in this paper is more robust under noisy conditions compared to existing signal processing-based methods. It relies on a cross-correlation algorithm that uses an independent target signal. This method is parameter-less and independent of the CT’s specifications. Additionally, no extra hardware equipment is required. The proposed method identifies the saturated portions in the measured secondary current in each cycle, enabling the reconstruction of the saturated current to obtain the reference primary current. A test system has been simulated, and the data are processed using MATLAB. Various test cases are executed, and the results confirm that the proposed method is highly effective in providing fast and accurate detection of CT saturation, with improved robustness against noise.

{"title":"Current transformer saturation detection by cross-correlation with independent target signal","authors":"Mahmoud M. Elgamasy , Mohamed S. Zaky , Ahmed F. Zobaa , Mahmoud A. Elsadd","doi":"10.1016/j.asej.2025.103314","DOIUrl":"10.1016/j.asej.2025.103314","url":null,"abstract":"<div><div>The saturation of current transformers (CTs) leads to distortion in secondary current, potentially causing malfunction in protective relays within power systems. Detecting the saturated portions in the measured signal and reconstructing the primary reference current are essential to prevent relay malfunctions and ensure sensitivity during faults. Existing methods in the literature still face challenges in improving accuracy, especially in the presence of noise in the measured signal. The proposed method in this paper is more robust under noisy conditions compared to existing signal processing-based methods. It relies on a cross-correlation algorithm that uses an independent target signal. This method is parameter-less and independent of the CT’s specifications. Additionally, no extra hardware equipment is required. The proposed method identifies the saturated portions in the measured secondary current in each cycle, enabling the reconstruction of the saturated current to obtain the reference primary current. A test system has been simulated, and the data are processed using MATLAB. Various test cases are executed, and the results confirm that the proposed method is highly effective in providing fast and accurate detection of CT saturation, with improved robustness against noise.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 3","pages":"Article 103314"},"PeriodicalIF":6.0,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143474068","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

Investigation of fluidic oscillator performance improvements by modifying interior chamber with a backward facing step geometry

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-22 DOI: 10.1016/j.asej.2025.103323

Waridho Iskandar , James Julian , Ming-Jyh Chern , Harinaldi

A computational method is used to model the BFSFO with variations in LR and HR to make it more efficient with high frequency and low average pressure drop. BFSFO LR 0.402 HR 0.4 outperformed the other variations with a frequency increase of 33.17% compared to the clean fluidic oscillator. The increase in frequency of BFSFO LR 0.402 HR 0.4 relative to the BFSFO baseline is 8.95%. The average pressure drop is 1.27% higher than clean fluidic oscillator. The decrease in the average pressure drop of BFSFO LR 0.402 HR 0.4 relative to the BFSFO baseline is 15.21%. The oscillation frequency increased due to the fluid flow with higher momentum in the upper and lower feedback channels. The circulation bubble in BFSFO LR 0.402 HR 0.4 is smaller than that in the BFSFO baseline, resulting in a lower average pressure drop.

引用次数: 0

Monitoring the flow patterns of high performance self-compacting concrete in the voids of sloped rock-filled concrete structures

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-21 DOI: 10.1016/j.asej.2025.103313

Ahmed A. Nasr , Baizhi Wang , Songgui Chen , Feng Jin

Rock-filled concrete (RFC) integrates rocks with high-performance self-compacting concrete (HSCC), combining rock stability with superior concrete properties. Effective HSCC cementation, especially in concealed areas, is critical for RFC’s structural integrity, but flow through intricate rock interstices poses challenges in quantifying filling performance. This study investigates HSCC flow on inclined rock surfaces using a real-time monitoring system to track behavior and efficiency. Key factors such as slope, flowability, rock size, and coarse aggregate size were analyzed. Results show that improved flowability enhances cavity filling, smaller rocks increase granular interlocking, and greater slopes accelerate flow velocity but do not ensure uniform filling. Optimal parameters for effective casting are a slump flow of 600–700 mm, rock sizes of 12.5–15 cm, and a rock skeleton slope of 1:2. Lastly, a predictive formula for HSCC flow velocity through inclined rock interstices was developed, providing insights for efficient RFC construction and enhanced structural performance.

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引用次数: 0

Sustainable cities and urban dynamics: The role of the café culture in transforming the public realm

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-19 DOI: 10.1016/j.asej.2025.103320

Emad Noaime , Chaham Alalouch , Abdelhakim Mesloub , Haifa Hamdoun , Hela Gnaba , Mohmmed Mashary Alnaim

This paper explores the intricate role of coffee shops in shaping public spaces within the urban fabric an enhanced to the urban social sustainability. The investigation focuses on four distinct models of cafés − from roadside kiosks to garden-embedded establishments − each offering unique contributions to the urban tapestry. These models are evaluated in Hail, Saudi Arabia, against key urban attributes like design, accessibility, and community engagement, highlighting their multifaceted impact on public life. By conducting an extensive examination utilizing ethnographic methodologies, case studies, and comparative assessments, we elucidate the transformation of coffee shops from simple refreshment spots to essential social centers that play a crucial role in enhancing urban liveliness, fostering social unity, and bolstering economic prosperity. The findings suggest that beyond serving as leisure spots, coffee shops are instrumental in fostering inclusive public realms, stimulating cultural exchange, and driving economic growth. The study underscores the need for strategic urban planning that leverages these spaces for broader social and developmental goals, offering insights into the potential for coffee shops to enhance the quality of urban life in Hail and beyond and contributing to the transformative agenda of Vision 2030.

{"title":"Sustainable cities and urban dynamics: The role of the café culture in transforming the public realm","authors":"Emad Noaime , Chaham Alalouch , Abdelhakim Mesloub , Haifa Hamdoun , Hela Gnaba , Mohmmed Mashary Alnaim","doi":"10.1016/j.asej.2025.103320","DOIUrl":"10.1016/j.asej.2025.103320","url":null,"abstract":"<div><div>This paper explores the intricate role of coffee shops in shaping public spaces within the urban fabric an enhanced to the urban social sustainability. The investigation focuses on four distinct models of cafés − from roadside kiosks to garden-embedded establishments − each offering unique contributions to the urban tapestry. These models are evaluated in Hail, Saudi Arabia, against key urban attributes like design, accessibility, and community engagement, highlighting their multifaceted impact on public life. By conducting an extensive examination utilizing ethnographic methodologies, case studies, and comparative assessments, we elucidate the transformation of coffee shops from simple refreshment spots to essential social centers that play a crucial role in enhancing urban liveliness, fostering social unity, and bolstering economic prosperity. The findings suggest that beyond serving as leisure spots, coffee shops are instrumental in fostering inclusive public realms, stimulating cultural exchange, and driving economic growth. The study underscores the need for strategic urban planning that leverages these spaces for broader social and developmental goals, offering insights into the potential for coffee shops to enhance the quality of urban life in Hail and beyond and contributing to the transformative agenda of Vision 2030.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 3","pages":"Article 103320"},"PeriodicalIF":6.0,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437926","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

Tropical Cyclone Intensity Prediction using Bayesian Machine Learning with Marine Predators Algorithm on Satellite Cloud Imagery

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-18 DOI: 10.1016/j.asej.2025.103316

Mahmoud Ragab

Due to its wide range of associated hazards, tropical cyclones (TC) become the costliest natural disaster worldwide. A correct diagnosis model for the TC intensity can save property and lives. Unfortunately, intensity forecasting of TC has been a bottleneck and has made it difficult to forecast weather. Several existing approaches and techniques make a diagnosis of TC wind speed through the satellite data at the specified time with varying success. Deep learning (DL)-based intensity forecasting has recently held great promise in surpassing conventional approaches. DL-based techniques have been developed in geosciences to replace traditional methods. However, weather forecasting is uncertain due to the Earth system’s nonlinearity, complexity, and chaotic effects. Thus, this manuscript develops a new Bayesian Machine Learning with Marine Predators Algorithm for TC Intensity Prediction (BMLMPA-TCIP) approach. The major goal of the BMLMPA-TCIP model is to estimate the level of the TCs on satellite cloud images. To accomplish this, the BMLMPA-TCIP technique utilizes the Gaussian filtering (GF) approach to eradicate the noise in the cloud images. Additionally, the extraction of useful feature vectors is performed by using the capsule network (CapsNet) technique. Moreover, the MPA method accomplishes the hyperparameter tuning of the CapsNet method. Lastly, the BMLMPA-TCIP technique utilizes the Bayesian Belief Network (BBN) method to predict TC intensity. To authorize the performance of the BMLMPA-TCIP approach, a wide variety of experiments are performed under the TC image dataset. The experimental validation of the BMLMPA-TCIP approach illustrates a superior RMSE value of 5.89 over existing techniques.

{"title":"Tropical Cyclone Intensity Prediction using Bayesian Machine Learning with Marine Predators Algorithm on Satellite Cloud Imagery","authors":"Mahmoud Ragab","doi":"10.1016/j.asej.2025.103316","DOIUrl":"10.1016/j.asej.2025.103316","url":null,"abstract":"<div><div>Due to its wide range of associated hazards, tropical cyclones (TC) become the costliest natural disaster worldwide. A correct diagnosis model for the TC intensity can save property and lives. Unfortunately, intensity forecasting of TC has been a bottleneck and has made it difficult to forecast weather. Several existing approaches and techniques make a diagnosis of TC wind speed through the satellite data at the specified time with varying success. Deep learning (DL)-based intensity forecasting has recently held great promise in surpassing conventional approaches. DL-based techniques have been developed in geosciences to replace traditional methods. However, weather forecasting is uncertain due to the Earth system’s nonlinearity, complexity, and chaotic effects.Thus, this manuscript develops a new Bayesian Machine Learning with Marine Predators Algorithm for TC Intensity Prediction (BMLMPA-TCIP) approach. The major goal of the BMLMPA-TCIP model is to estimate the level of the TCs on satellite cloud images. To accomplish this, the BMLMPA-TCIP technique utilizes the Gaussian filtering (GF) approach to eradicate the noise in the cloud images. Additionally, the extraction of useful feature vectors is performed by using the capsule network (CapsNet) technique. Moreover, the MPA method accomplishes the hyperparameter tuning of the CapsNet method. Lastly, the BMLMPA-TCIP technique utilizes the Bayesian Belief Network (BBN) method to predict TC intensity. To authorize the performance of the BMLMPA-TCIP approach, a wide variety of experiments are performed under the TC image dataset. The experimental validation of the BMLMPA-TCIP approach illustrates a superior RMSE value of 5.89 over existing techniques.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 3","pages":"Article 103316"},"PeriodicalIF":6.0,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143427821","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

Sustainable construction solutions: The role of sugar factory lime waste-activated slag in high-performance concrete

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-17 DOI: 10.1016/j.asej.2025.103315

Hadi Bahmani, Davood Mostofinejad

This pioneering research aims to develop high-performance concrete (HPC) using waste lime from sugar factories to activate slag. The study explores the transformative effects of high-temperature treatment on sugar factory lime waste and its potential to enhance slag activation, representing a novel approach in sustainable construction materials. The newly formulated HPC was rigorously compared with traditional counterparts made from calcium oxide-activated slag and calcined dolomite. A comprehensive series of tests were conducted at 28 days, assessing critical performance metrics, including compressive strength, four-point bending strength, tensile strength, and water absorption. Microstructural analysis was performed using Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDAX), and Fourier Transform Infrared Spectroscopy (FTIR). The results revealed that samples activated with 10 % sugar factory lime waste achieved a compressive strength of approximately 80 MPa, rivaling samples activated with 10 % calcium oxide. These lime-activated samples also demonstrated outstanding tensile and bending strengths of 5.6 MPa and 6.6 MPa, respectively—the highest recorded in this study. The microstructural analysis indicated a dense microstructure with an elevated Si/Al ratio and significant geopolymerization. The low water absorption rate of 2.1 % highlighted the reduced porosity of this innovative geopolymeric matrix. This research is the first to investigate the high-temperature treatment of sugar factory lime waste for slag activation in HPC. The findings suggest that incorporating 10 % waste lime significantly lowers the climate change impact index to 397.6 kg CO₂ eq—12 % less than samples with 30 % calcium oxide and 7 % lower than those with 30 % dolomite. Using sugar factory waste lime enhances mechanical properties and promotes environmental sustainability, presenting a compelling alternative that excels in both performance and ecological benefits.

{"title":"Sustainable construction solutions: The role of sugar factory lime waste-activated slag in high-performance concrete","authors":"Hadi Bahmani, Davood Mostofinejad","doi":"10.1016/j.asej.2025.103315","DOIUrl":"10.1016/j.asej.2025.103315","url":null,"abstract":"<div><div>This pioneering research aims to develop high-performance concrete (HPC) using waste lime from sugar factories to activate slag. The study explores the transformative effects of high-temperature treatment on sugar factory lime waste and its potential to enhance slag activation, representing a novel approach in sustainable construction materials. The newly formulated HPC was rigorously compared with traditional counterparts made from calcium oxide-activated slag and calcined dolomite. A comprehensive series of tests were conducted at 28 days, assessing critical performance metrics, including compressive strength, four-point bending strength, tensile strength, and water absorption. Microstructural analysis was performed using Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDAX), and Fourier Transform Infrared Spectroscopy (FTIR). The results revealed that samples activated with 10 % sugar factory lime waste achieved a compressive strength of approximately 80 MPa, rivaling samples activated with 10 % calcium oxide. These lime-activated samples also demonstrated outstanding tensile and bending strengths of 5.6 MPa and 6.6 MPa, respectively—the highest recorded in this study. The microstructural analysis indicated a dense microstructure with an elevated Si/Al ratio and significant geopolymerization. The low water absorption rate of 2.1 % highlighted the reduced porosity of this innovative geopolymeric matrix. This research is the first to investigate the high-temperature treatment of sugar factory lime waste for slag activation in HPC. The findings suggest that incorporating 10 % waste lime significantly lowers the climate change impact index to 397.6 kg CO<sub>2</sub> eq—12 % less than samples with 30 % calcium oxide and 7 % lower than those with 30 % dolomite. Using sugar factory waste lime enhances mechanical properties and promotes environmental sustainability, presenting a compelling alternative that excels in both performance and ecological benefits.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 3","pages":"Article 103315"},"PeriodicalIF":6.0,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419868","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

Data-driven optimal adaptive MPPT techniques for grid-connected photovoltaic systems

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-17 DOI: 10.1016/j.asej.2025.103318

Ahmed H. EL-Ebiary, Mostafa I. Marei, Mohamed Mokhtar

The constant fluctuations in the maximum power obtained from Photovoltaic (PV) systems are due to variations of temperature and irradiance. Maximum Power Point Tracking (MPPT) techniques are used to guarantee the best possible efficiency and performance for the PV systems. In this paper, an Incremental Conductance (IC) MPPT technique based on adaptive controllers is proposed. This paper presents two different types of adaptive PI controllers, including optimized Fractional Order Adaptive PI (FOAPI), and Single Perceptron Adaptive PI (SP-API). The IC technique along with the adaptive controllers ensure accurate extraction of maximum power under sudden changes and different weather conditions. Moreover, machine learning is utilized to initialize the duty cycle of PV system converter, where different regression models are compared and the model with the least Root Mean square error (RMSE) is exploited. Three case studies are carried out to compare and validate the performance of the suggested adaptive MPPT controllers.

引用次数: 0

Incorporating stochasticity in demands for optimizing resource allocation in versatile edge systems devoid of layer constraints

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2025-02-14 DOI: 10.1016/j.asej.2025.103300

Jimei Gao , Chunhua Cai

While stochastic demand models have been introduced to better capture resource fluctuations, each instance of problem under different architectures needs to be analyzed and solved separately with duplicated work, this limitation motivates research to develop a scalable and adaptive resource scheduling solution capable of handling edge systems with any number of layers. Fortunately, we found that this kind of stochastic scheduling problem combined with sharing has an invariant optimal substructure that is independent of the number of layers, and propose the Placement of Resource in Any layer Edge architecture (PRAE) algorithm. We find an efficient way to solve it by splitting it into multiple subproblem groups and characterizing the relationship between these subproblems as an isomorphic network. We then identify optimal conditions for subproblem groups at different layers, and quickly achieve a solution using dynamic programming. Extensive evaluations show that PRAE improves resource utilization by over 28% compared to average demand models and achieves over 98% of optimal performance across diverse scenarios, with significantly lower computational complexity.

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