检索结果-南通市图书馆

Experimental investigation of viscous oil-water-sand flow in horizontal pipes:Flow patterns and pressure gradient

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Petroleum 2024年第2期10卷 275-293页

作者： tarek Ganat Petroleum and Chemical Engineering Department Sultan Qaboos UniversityP.O.Box 50Muscat 123Sultanate of Oman

Fluid production from unconsolidated reservoirs often leads in sand production,which poses a number of *** deposition in flowlines can result in significant pressure dips,pipe and facility damage,and obstructions that decrease *** research is needed to understand the movement and deposition of sand in oil-water-sand(O-W-S) *** article focuses on O-W-S flows in a 6-meter-long horizontal pipe with an inner diameter of 0.0381 *** study looks at the flow behavior of high viscosity oil-water(O-W),water-sand(W-S),and oil-water-sand(O-W-S) *** were carried out at 250 psig pressure in a laboratory flow test facility using various heavy synthetic oils(viscosities ranging from 3500 cP to 7500 cP at 25℃) and tap *** sand concentration varied from 1% to 10%,with an average sand particle diameter of 145 μm and material density of 2630 kg/m~*** cuts ranged from 0.0 to *** experimental results revealed a minor change in pressure gradient between(O-W) and(O-W-S) ***,increasing the sand concentration in(O-W-S) flow resulted in higher pressure *** reduction factor of pressure gradient indicated that the highest decrease in pressure drop occurred at higher superficial oil ***,a direct relationship was observed between the reduction factor and the decrease in water *** results also showed that the minimum required transportation velocity for sand slurry decreased with increasing superficial oil velocity,while the minimum transportation condition increased with higher sand *** comparison between the expected pressure gradient from Bannwart and McKibben et *** the actual experimental data demonstrated significant accuracy for the oil viscosities and superficial oil velocities used in the study.

关键词： Slurry velocity Flow pattern Pressure gradient high viscosity Minimum transport condition

An Optimization Approach of IoD Deployment for Optimal Coverage Based on Radio Frequency Model

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Computer Modeling in Engineering & Sciences 2024年第6期139卷 2627-2647页

作者： tarek Sheltami Gamil Ahmed Ansar Yasar Computer Engineering Department Interdisciplinary Research Center of Smart Mobility and LogisticsKing Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Transportation Research Institute(IMOB) Hasselt UniversityHasselt3500Belgium

Recently,Internet of Drones(IoD)has garnered significant attention due to its widespread ***,deploying IoD for area coverage poses numerous limitations and *** include interference between neighboring drones,the need for directional antennas,and altitude restrictions for *** challenges necessitate the development of efficient *** research paper presents a cooperative decision-making approach for an efficient IoDdeployment to address these challenges *** primary objective of this study is to achieve an efficient IoDdeployment strategy thatmaximizes the coverage regionwhile minimizing interference between neighboring *** deployment problem,the interference increases as the number of deployed drones increases,resulting in bad quality of *** the other hand,deploying a few drones cannot satisfy the coverage *** accomplish this,an enhanced version of a concise population-based meta-heuristic algorithm,namely Improved Particle SwarmOptimization(IPSO),is *** objective function of IPSO is defined based on the coverage probability,which is primarily influenced by the characteristics of the antennas and drone altitude.A radio frequency(RF)model is derived to evaluate the coverage quality,considering both Line of Sight(LOS)and Non-Line of Sight(NLOS)down-link coverage probabilities for ground *** is assumed that each drone is equipped with a directional antenna to optimize coverage in a given *** simulations are conducted to assess the effectiveness of the proposed *** demonstrate that the proposed method achieves maximum coverage with minimum transmission ***,a comparison is made against Collaborative Visual Area Coverage Approach(CVACA),and a game-based approach in terms of coverage quality and convergence *** simulation results reveal that our approach outperforms both CVACA and the gamebased schemes in terms of coverage an

关键词： IoD line of sight optimal deployment IPSO RF model

Smart prediction of liquefaction-induced lateral spreading

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Rock Mechanics and Geotechnical Engineering 2024年第6期16卷 2310-2325页

作者： Muhammad Nouman Amjad Raja tarek Abdoun Waleed El-Sekelly New York University(NYU)Abu Dhabi Abu Dhabi129188United Arab Emirates University of Management and Technology Lahore54372Pakistan Department of Civil and Environmental Eng. Rensselaer Polytechnic Institute(RPI)1108th StreetJEC 4049TroyNY12180USA Department of Structural Engineering Mansoura UniversityMansoura35516Egypt

The prediction of liquefaction-induced lateral spreading/displacement(Dh)is a challenging task for civil/geotechnical *** this study,a new approach is proposed to predict Dh using gene expression programming(GEP).Based on statistical reasoning,individual models were developed for two topographies:free-face and gently sloping *** with a comparison with conventional approaches for predicting the Dh,four additional regression-based soft computing models,*** process regression(GPR),relevance vector machine(RVM),sequential minimal optimization regression(SMOR),and M5-tree,were developed and compared with the GEP *** results indicate that the GEP models predict Dh with less bias,as evidenced by the root mean square error(RMSE)and mean absolute error(MAE)for training(i.e.1.092 and 0.815;and 0.643 and 0.526)and for testing(i.e.0.89 and 0.705;and 0.773 and 0.573)in free-face and gently sloping ground topographies,*** overall performance for the free-face topology was ranked as follows:GEP>RVM>M5-tree>GPR>SMOR,with a total score of 40,32,24,15,and 10,*** the gently sloping condition,the performance was ranked as follows:GEP>RVM>GPR>M5-tree>SMOR with a total score of 40,32,21,19,and 8,***,the results of the sensitivity analysis showed that for both free-face and gently sloping ground,the liquefiable layer thickness(T_(15))was the major parameter with percentage deterioration(%D)value of 99.15 and 90.72,respectively.

关键词： Lateral spreading Intelligent modeling Gene expression programming(GEP) Closed-form solution Feature importance

Advancing sandstone reservoir compressibility prediction:A correlation-driven methodology

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Petroleum Research 2024年第2期9卷 273-279页

作者： tarek Ganat Meftah hrairi Amr Badawy Vahid Khosravi Mohammed Abdalla Department of Petroleum Chemical Engineering Sultan Qaboos UniversityP.O.Box 50Al-Khod123MuscatOman Department of Mechanical and Aerospace Engineering International Islamic University MalaysiaP.O.Box 1050728Kuala LumpurMalaysia Reservoir Engineering Section Petronas Carigali SDN BHDP.O.Box 10500088Kuala LumpurMalaysia Department of Chemical and Petroleum Engineering Faculty of EngineeringTechnologyand Built EnvironmentUCSI University56000Kuala LumpurMalaysia Chemical&Petroleum Engineering United Arab Emirates UniversityP.O.Box No.15551Al AinUAE

This study presents a correlation-based approach for predicting the compressibility of sandstone reservoir *** study proposes a matrix of new empirical equations that significantly improve the precision of measuring the pore volume compressibility,with the most optimal fit of results based on a cubic polynomial *** accuracy of the calculations was validated through comparison with actual data using root mean square method,and the suggested correlations significantly enhance the precise prediction of rock compressibility in sandstone *** this study,the source of data collection is consolidated and unconsolidated sandstone from East Asia offshore ***,variations in compressibility with net overburden pressure over the course of the field's lifespan have been *** results demonstrate the application of regression analysis in establishing a network of linkages between independent and dependent *** proposed correlations for consolidated and unconsolidated sandstones offer a remarkable improvement in the accurate calculation of rock compressibility compared to traditional laboratory procedures,with an average error of 2.5%compared to 5-10%for laboratory *** approach of this study offers a cost-effective and time-efficient alternative to remarkedly enhance the overall performance of sandstone reservoirs in the oil and gas industry.

关键词： Compressibility Consolidated and unconsolidated sandstone Rock properties Rock mechanics

A Lightweight Intrusion Detection System Using Convolutional Neural Network and Long Short-Term Memory in Fog Computing

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第9期80卷 4703-4728页

作者： hawazen alzahrani tarek Sheltami Abdulaziz Barnawi Muhammad Imam Ansar Yaser Computer Engineering Department Interdisciplinary Research Center of Smart Mobility and LogisticsKing Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Computer Engineering Department Interdisciplinary Research Center for Intelligent Secure SystemsKing Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Transportation Research Institute(IMOB) Hasselt UniversityHasselt3500Belgium

The Internet of Things(IoT)links various devices to digital services and significantly improves the quality of our ***,as IoT connectivity is growing rapidly,so do the risks of network vulnerabilities and *** interesting Intrusion Detection Systems(IDSs)are presented based on machine learning(ML)techniques to overcome this *** the resource limitations of fog computing environments,a lightweight IDS is *** paper introduces a hybrid deep learning(DL)method that combines convolutional neural networks(CNN)and long short-term memory(LSTM)to build an energy-aware,anomaly-based *** test this system on a recent dataset,focusing on reducing overhead while maintaining high accuracy and a low false alarm *** compare CICIoT2023,KDD-99 and NSL-KDD datasets to evaluate the performance of the proposed IDS model based on key metrics,including latency,energy consumption,false alarm rate and detection rate *** findings show an accuracy rate over 92%and a false alarm rate below 0.38%.These results demonstrate that our system provides strong security without excessive resource *** practicality of deploying IDS with limited resources is demonstrated by the successful implementation of IDS functionality on a Raspberry Pi acting as a Fog *** proposed lightweight model,with a maximum power consumption of 6.12 W,demonstrates its potential to operate effectively on energy-limited devices such as low-power fog nodes or edge *** prioritize energy efficiency whilemaintaining high accuracy,distinguishing our scheme fromexisting *** experiments demonstrate a significant reduction in false positives,ensuring accurate identification of genuine security threats while minimizing unnecessary alerts.

关键词： Intrusion detection fog computing CNN LSTM energy consumption

Mitigating Blackhole and Greyhole Routing Attacks in Vehicular Ad hoc Networks Using Blockchain Based Smart Contracts

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Modeling in Engineering & Sciences 2024年第2期138卷 2005-2021页

作者： Abdulatif alabdulatif Mada alharbi Abir Mchergui tarek Moulahi Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science Higher Institute of Management of GabesGabes UniversityGabes6029Tunisia Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia Faculty of Science and Technology of Sidi Bouzid Kairouan UniversityKairouan3131Tunisia

The rapid increase in vehicle traffic volume in modern societies has raised the need to develop innovative solutions to reduce traffic congestion and enhance traffic management *** advanced technology,such as Intelligent Transportation Systems(ITS),enables improved traffic management,helps eliminate congestion,and supports a safer *** provides real-time information on vehicle traffic and transportation systems that can improve decision-making for road ***,ITS suffers from routing issues at the network layer when utilising Vehicular Ad hoc Networks(VANETs).This is because each vehicle plays the role of a router in this network,which leads to a complex vehicle communication network,causing issues such as repeated link breakages between vehicles resulting from the mobility of the network and rapid topological *** may lead to loss or delay in packet transmissions;this weakness can be exploited in routing attacks,such as black-hole and gray-hole attacks,that threaten the availability of ITS *** this paper,a Blockchain-based smart contracts model is proposed to offer convenient and comprehensive security mechanisms,enhancing the trustworthiness between ***-Classification Blockchain-Based Contracts(SCBC)and Voting-Classification Blockchain-Based Contracts(VCBC)are utilised in the proposed *** results show that VCBC succeeds in attaining better results in PDR and TP performance even in the presence of Blackhole and Grayhole attacks.

关键词： Blockchain data privacy machine learning routing attacks smart contract VANET

A hybrid machine-learning model for solar irradiance forecasting

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Clean Energy 2024年第1期8卷 100-110页

作者： Ameera M.almarzooqi Maher Maalouf tarek h.M.El-Fouly Vasileios E.Katzourakis Mohamed S.El Moursi Constantinos V.Chrysikopoulos Department of Industrial and Systems Engineering Khalifa UniversityAbu DhabiPO Box 127788UAE Electrical Engineering and Computer Science Department Khalifa University Abu DhabiUAE Department of Civil Infrastructure and Environmental Engineering Khalifa UniversityAbu DhabiPO Box 127788UAE School of Chemical and Environmental Engineering Technical University of CreteChaniaGreece

Nowcasting and forecasting solar irradiance are vital for the optimal prediction of grid-connected solar photovoltaic(PV)power *** plants face operational challenges and scheduling dispatch difficulties due to the fluctuating nature of their power *** the generation capacity within the electric grid increases,accurately predicting this output becomes increasingly essential,especially given the random and non-linear characteristics of solar irradiance under variable weather *** study presents a novel prediction method for solar irradiance,which is directly in correlation with PV power output,targeting both short-term and medium-term forecast *** proposed hybrid framework employs a fast trainable statistical learning technique based on the truncated-regularized kernel ridge regression *** proposed method excels in forecasting solar irradiance,especially during highly intermittent weather periods.A key strength of our model is the incorporation of multiple historical weather parameters as inputs to generate accurate predictions of future solar irradiance values in its scalable *** evaluated the performance of our model using data sets from both cloudy and sunny days in Seattle and Medford,USA and compared it against three forecasting models:persistence,modified 24-hour persistence and least *** on three widely accepted statistical performance metrics(root mean squared error,mean absolute error and coefficient of determination),our hybrid model demonstrated superior predictive accuracy in varying weather conditions and forecast horizons.

关键词： solar power generation kernel ridge regression hybrid model forecasting

A critical review towards the causes of the iron-based catalysts deactivation mechanisms in the selective oxidation of hydrogen sulfide to elemental sulfur from biogas

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Energy Chemistry 2024年第3期90卷 388-411,I0010页

作者： Mostafa tarek Janaina S.Santos Victor Márquez Mohammad Fereidooni Mohammad Yazdanpanah Supareak Praserthdam Piyasan Praserthdam Center of Excellence on Catalysis and Catalytic Reaction Engineering(CECC) Department of Chemical EngineeringFaculty of EngineeringChulalongkorn UniversityBangkok 10330Thailan high-Performance Computing Unit(CECC-hCU) Center of Excellence on Catalysis and Catalytic Reaction Engineering(CECC)Chulalongkorn UniversityBangkok 10330Thailand

hydrogen sulfide(h_(2)S) not only presents significant environmental concerns but also induces severe corrosion in industrial equipment,even at low *** various technologies,the selective oxidation of hydrogen sulfide(SOh_(2)S) to elemental sulfur(S) has emerged as a sustainable and environmentally friendly *** to its unique properties,iron oxide has been extensively investigated as a catalyst for SOh_(2)S;however,rapid deactivation has remained a significant *** causes of iron oxide-based catalysts deactivation mechanisms in SOh_(2)S,including sulfur or sulfate deposition,the transformation of iron species,sintering and excessive oxygen vacancy formation,and active site loss,are thoroughly examined in this *** focusing on the deactivation mechanisms,this review aims to provide valuable insights into enhancing the stability and efficiency of iron-based catalysts for SOh_(2)S.

关键词： Selective oxidation of h_(2)S Iron-based Catalysts Mechanism of deactivation Sulfur or sulfate deposition Transformation of iron species Sintering SDG 7

An Improved Enterprise Resource Planning System Using Machine Learning Techniques

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Journal of Software Engineering and Applications 2024年第5期17卷 203-213页

作者： Ahmed Youssri Zakaria Elsayed Abdelbadea Atef Raslan tarek ali Mervat Gheith.al-Sayed Khater Essam A. Amin Department of Software Engineering Faculty of Graduate Studies for Statistical Research (FGSSR) Cairo University Giza Egypt

Traditional Enterprise Resource Planning (ERP) systems with relational databases take weeks to deliver predictable insights instantly. The most accurate information is provided to companies to make the best decisions through advanced analytics that examine the past and the future and capture information about the present. Integrating machine learning (ML) into financial ERP systems offers several benefits, including increased accuracy, efficiency, and cost savings. also, ERP systems are crucial in overseeing different aspects of human Capital Management (hCM) in organizations. The performance of the staff draws the interest of the management. In particular, to guarantee that the proper employees are assigned to the convenient task at the suitable moment, train and qualify them, and build evaluation systems to follow up their performance and an attempt to maintain the potential talents of workers. also, predicting employee salaries correctly is necessary for the efficient distribution of resources, retaining talent, and ensuring the success of the organization as a whole. Conventional ERP system salary forecasting methods typically use static reports that only show the system’s current state, without analyzing employee data or providing recommendations. We designed and enforced a prototype to define to apply ML algorithms on Oracle EBS data to enhance employee evaluation using real-time data directly from the ERP system. Based on measurements of accuracy, the Random Forest algorithm enhanced the performance of this system. This model offers an accuracy of 90% on the balanced dataset.

关键词： ERP hCM Machine Learning Employee Performance Pythonista Pythoneer