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Availability,sustainability and accessibility of agro crop residue production and solar radiation in Egypt for producing highly chemical products through pyrolysis processes

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Clean Energy 2023年第3期7卷 654-670页

作者： saad a.el-sayed Mohamed A.Ismail Mohamed E.Mostafa Emad H.Noseir Tarek M.Khass Mechanical Power Engineering Department Faculty of EngineeringZagazig UniversityAl-SharkiaEgypt Mechanical Engineering Department College of EngineeringKing Faisal UniversityAl-AhsaSaudi Arabia Environmental Engineering Department Faculty of EngineeringZagazig UniversityAl-SharkiaEgypt

This study examines the large amount of agricultural waste produced in Egypt between 2010 and 2019 by analysing data from various departments within the Agriculture *** also provides a comprehensive database on the biomass available from agricultural waste in Egypt and its potential applications for producing power,heat and chemical *** biomass-pyrolysis systems powered by solar energy are used,research demonstrates the potential to convert agricultural waste into a variety of chemical *** approach utilizes solar energy,a clean and renewable source,and has wide-ranging industrial and power generation *** Egypt’s reliance on agriculture,the country currently utilizes little biomass for energy production and has not previously used it as a source for creating chemical products,which could potentially save on the imported oil used in these *** findings of the study are graphically presented using histograms,pie charts,*** overall production of residues reached the 30-Mt level in *** it contains the most rice-cultivated land,Dakahlia(Lower Egypt region)produces the highest percentage of the total residue(37.17%).Qena governorate(Upper Egypt region)produces 1.14 metric tons of residues,with sugarcane accounting for 20.3%of the total.

关键词： biomass agro-residue solar radiation pyrolysis chemical products sustainability

Thermal explosion of a reactive gas mixture at constant pressure for non-uniform and uniform temperature systems

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Performance Evaluation of an Evaporative Cooling Pad for Humidification-Dehumidification Desalination

Defence technology 2022年第10期

作者： saad a.el-sayed

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Fluid Dynamics & Materials Processing 2024年第10期20卷 2323-2335页

作者： Ibtissam el Aouni Hicham Labrim elhoussaine Ouabida Ahmed Ait Errouhi Rachid el Bouayadi Driss Zejli Aouatif saad Advanced Systems Engineering Laboratory National School of Applied SciencesIbn Tofail UniversityKenitra14000Morocco

The perfect combination of renewable energy and desalination technologies is the key to meeting water demands in a cost-effective,efficient and environmentally friendly *** desalination technique by humidificationdehumidification is non-conventional approach suitable for areas with low infrastructure(such as rural and decentralized regions)since it does not require permanent *** this study,this technology is implemented by using solar energy as a source of thermal power.A seawater desalination unit is considered,which consists of a chamber with two evaporators(humidifiers),a wetted porous material made of a corrugated cellulose cardboard and a condenser(dehumidifier).The evaporation system is tested with dry bulb temperature and relative air humidity *** results of numerical simulations indicate that higher inlet air velocities(from 0.75 to 3 m/s)lead to a decrease in theΔT,ΔRH,and *** the air remaining within the evaporator for 30 cm,the temperature differential increases to 5.7°C,accompanied by a 39%rise in relative humidity *** changes result in a significant enhancement in humidification efficiency,achieving a remarkable efficiency level of 78%.However,a wettability value of 630 m^(2)/m^(3)leads to a smaller reduction of these *** the pad thickness,particularly to 0.3 m,improves performance by boostingΔT,ΔRH,and effectiveness,especially for pads with a wettability of 630 m^(2)/m^(3),for which superior performances are predicted by the numerical tests.

关键词： Desalination humidification dehumidification porous material solar energy evaporator

Energy Design and Optimization of Greenhouse by Natural Convection

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Fluid Dynamics & Materials Processing 2024年第8期20卷 1903-1913页

作者： H.Benzzine H.Labrim Aouatif saad Y.Achour D.Zejli R.el Bouayadi Advanced Systems Engineering Laboratory(a.elab) National School of Applied SciencesIbn Tofail UniversityKenitraMorocco

This study addresses the pressing need for energy-efficient greenhouse management by focusing on the innovative application of natural *** primary objective of this study is to evaluate various ventilation strategies to enhance energy efficiency and optimize crop production in agricultural *** advanced numerical simulation tools,the study conducts a comprehensive assessment of natural ventilation’s effectiveness under real-world *** results underscore the crucial role of the stack effect and strategic window positioning in greenhouse cooling,providing valuable insights for greenhouse *** findings shed light on the significant benefits of optimized ventilation and also offer practical implications for improving greenhouse design,ensuring sustainable and efficient agricultural *** study demonstrated energy savings in cooling from November to April,with a maximum saving of 680 kWh in March,indicating the effectiveness of strategically positioning windows to leverage the stack *** approach enhances plant growth and reduces the need for costly cooling systems,thereby improving overall energy efficiency and lowering operational expenses.

关键词： Energy greenhouse cooling natural ventilation simulation temperature

Reinforcement Learning-Empowered Graph Convolutional Network Framework for Data Integrity Attack Detection in Cyber-Physical Systems

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 797-806页

作者： Edeh Vincent Mehdi Korki Mehdi Seyedmahmoudian Alex Stojcevski saad Mekhilef School of Science Computingand Engineering TechnologiesSwinburne University of TechnologyMelbourneAustralia

The massive integration of communication and information technology with the large-scale power grid has enhanced the efficiency, safety, and economical operation of cyber-physical systems. However, the open and diversified communication environment of the smart grid is exposed to cyber-attacks. Data integrity attacks that can bypass conventional security techniques have been considered critical threats to the operation of the grid. Current detection techniques cannot learn the dynamic and heterogeneous characteristics of the smart grid and are unable to deal with non-euclidean data types. To address the issue, we propose a novel Deep-Q-Network scheme empowered with a graph convolutional network (GCN) framework to detect data integrity attacks in cyber-physical systems. The simulation results show that the proposed framework is scalable and achieves higher detection accuracy, unlike other benchmark techniques.

关键词： Deep reinforcement learning graph convolutional network heterogeneous smart grid network

Classified VPN Network Traffic Flow Using Time Related to Artificial Neural Network

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Computers, Materials & Continua 2024年第7期80卷 819-841页

作者： saad Abdalla Agaili Mohamed Sefer Kurnaz Department of electrical and Computer Engineering Altinbas UniversityIstanbul34000Turkey

VPNs are vital for safeguarding communication routes in the continually changing cybersecurity ***,increasing network attack complexity and variety require increasingly advanced algorithms to recognize and categorizeVPNnetwork *** present a novelVPNnetwork traffic flowclassificationmethod utilizing Artificial Neural Networks(ANN).This paper aims to provide a reliable system that can identify a virtual private network(VPN)traffic fromintrusion attempts,data exfiltration,and denial-of-service *** compile a broad dataset of la.eled VPN traffic flows from various apps and usage ***,we create an ANN architecture that can handle encrypted communication and distinguish benign from dangerous *** effectively process and categorize encrypted packets,the neural network model has input,hidden,and output *** use advanced feature extraction approaches to improve the ANN’s classification accuracy by leveraging network traffic’s statistical and behavioral *** also use cutting-edge optimizationmethods to optimize network characteristics and *** suggested ANN-based categorization method is extensively tested and *** show the model effectively classifies VPN traffic *** also show that our ANN-based technique outperforms other approaches in precision,recall,and F1-score with 98.79%*** study improves VPN security and protects against new *** VPNtraffic flows effectively helps enterprises protect sensitive data,maintain network integrity,and respond quickly to security *** study advances network security and lays the groundwork for ANN-based cybersecurity solutions.

关键词： VPN network traffic flow ANN classification intrusion detection data exfiltration encrypted traffic feature extraction network security

RoGRUT: A Hybrid Deep Learning Model for Detecting Power Trapping in Smart Grids

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Computers, Materials & Continua 2024年第5期79卷 3175-3192页

作者： Farah Mohammad saad Al-Ahmadi Jalal Al-Muhtadi Center of Excellence in Information Assurance(CoEIA) King Saud UniversityRiyadh11543Saudi Arabia College of Computer&Information Sciences King Saud UniversityRiyadh11543Saudi Arabia

electricity theft is a widespread non-technical issue that has a negative impact on both power grids and electricity *** hinders the economic growth of utility companies,poses electrical risks,and impacts the high energy costs borne by *** development of smart grids is crucial for the identification of power theft since these systems create enormous amounts of data,including information on client consumption,which may be used to identify electricity theft using machine learning and deep learning ***,there also exist different solutions such as hardware-based solutions to detect electricity theft that may require human resources and expensive ***-based solutions are presented in the literature to identify electricity theft but due to the dimensionality curse,class imbalance issue and improper hyper-parameter tuning of such models lead to poor *** this research,a hybrid deep learning model abbreviated as RoGRUT is proposed to detect electricity theft as amalicious and non-malicious *** key steps of the RoGRUT are data preprocessing that covers the problem of class imbalance,feature extraction and final theft *** advanced-level models like RoBERTa is used to address the curse of dimensionality issue,the near miss for class imbalance,and transfer learning for *** effectiveness of the RoGRUTis evaluated using the dataset fromactual smartmeters.A significant number of simulations demonstrate that,when compared to its competitors,the RoGRUT achieves the best classification *** performance evaluation of the proposed model revealed exemplary results across *** accuracy achieved was 88%,with precision at an impressive 86%and recall reaching 84%.The F1-Score,a measure of overall performance,stood at 85%.Furthermore,themodel exhibited a noteworthyMatthew correlation coefficient of 78%and excelled with an area under the curve of 91%.

关键词： electricity theft smart grid RoBERTa GRU transfer learning

Effect of Co on Solidification Characteristics and Microstructural Transformation of Non-equilibrium Solidified Cu-Ni Alloys

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Journal of Wuhan University of Technology(Materials Science) 2024年第2期39卷 444-453页

作者：安红恩 Bih-Lii Chua Ismail saad Willey Yun Hsien Liew Materials Engineering Research Group Faculty of EngineeringUniversity Malaysia Sabah88400 Kota KinabaluSabahMalaysia College of Mechanical and electronic Engineering Huanghe Jiaotong UniversityJiaozuo 454950China Henan Engineering Technology Research Center on Intelligent Manufacturing Technology and Equipment Jiaozuo 454950China Centre of Research in Energy and Advanced Materials Faculty of EngineeringUniversiti Malaysia SabahJalan UMS88400 Kota KinabaluSabahMalaysia Nano Engineering and Materials Research group Faculty of EngineeringUniversity Malaysia Sabah88400 Kota KinabaluSabahMalaysia

Non-equilibrium solidification structures of Cu55Ni45 and Cu55Ni43Co2 alloys were prepared by the molten glass purification cycle superheating *** variation of the recalescence phenomenon with the degree of undercooling in the rapid solidification process was investigated using an infrared *** addition of the Co element affected the evolution of the recalescence phenomenon in Cu-Ni *** images of the solid-liquid interface migration during the rapid solidification of supercooled melts were captured by using a high-speed *** solidification rate of Cu-Ni alloys,with the addition of Co elements,was ***,the grain refinement structure with low supercooling was characterised using electron backscatter diffraction(EBSD).The effect of Co on the microstructural evolution during nonequilibrium solidification of Cu-Ni alloys under conditions of small supercooling is investigated by comparing the microstructures of Cu55Ni45 and Cu55Ni43Co2 *** experimental results show that the addition of a small amount of Co weakens the recalescence behaviour of the Cu55Ni45 alloy and significantly reduces the thermal strain in the rapid solidification *** the rapid solidification phase,the thermal strain is greatly reduced,and there is a significant increase in the characteristic undercooling ***,the addition of Co and the reduction of Cu not only result in a lower solidification rate of the alloy,but also contribute to the homogenisation of the grain size.

关键词： non-equilibrium solidification recalescence effect solidification character microstructure

Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in electrical Networks

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1339-1370页

作者： Ali S.Alghamdi Mohamed A.Zohdy saad Aldoihi Department of electrical Engineering College of EngineeringMajmaah UniversityAl-Majmaah11952Saudi Arabia electrical and Computer Engineering Department Oakland UniversityRochesterMI48309USA Institute of Earth and Space Science King Abdulaziz City for Science and Technology(KACST)Riyadh11442Saudi Arabia Computer Science and Systems Engineering Institute Polytechnique de ParisPalaiseau CedexFrance

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network *** study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic *** primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss ***,a carbon tax is included in the objective function to reduce carbon *** scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal *** results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution ***,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)*** research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local *** emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

关键词： Renewable energy integration optimal power flow stochastic renewable energy sources gaussian-bare-bones levy cheetah optimizer electrical network optimization carbon tax optimization