检索结果-南通市图书馆

Analysis of particle dispersion and cavity formation during bulk particle water entry using fully coupled CFD-DEM-VOF approach

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Particuology 2024年第7期90卷 558-580页

作者： Utkan Çalışkan Sanja Mišković Norman B.Keevil institute of Mining Engineering University of British Columbia2329 West MallVancouverBC V6T 1Z4Canada

This paper presents the development and validation of a fully coupled computational fluid dynamics—discrete element method—volume of fluid(CFD-DEM-VOF)model to simulate the complex behavior of particle-laden flows with free *** coupling between the fluid and particle phases is established through the implemented continuity,momentum,and alpha transport *** coupled particle forces such as drag,pressure gradient,dense virtual mass,viscous,and interface forces are also integrated,with drag and dense virtual mass forces being dependent on local *** integrated conservative alpha transport equation ensures phase volume conservation during interactions between particles and ***,we have implemented a trilinear interpolation method designed to operate on unstructured hexahedral *** method has been tested for its ability to properly resolve the coupling effects in the numerical simulations,particularly in cases with a relatively low cell-size *** model is validated through three distinct test cases:single particle water entry,dam break with particles,and water entry of a group of particles *** experimental setup is built to study the dynamics of the water entry of a group of particles,where three key flow features are analyzed:the evolution of average particle velocity,cavity shape,and particle dispersion cloud profiles in *** tests involve four different scenarios,including two different water levels(16.1 and 20.1 cm)and two different particle densities(2650 and 4000 kg/m3).High-speed videometry and particle tracking velocimetry(using imageJ/TrackMate)methods are employed for experimental data *** is demonstrated that numerical results are in excellent agreement with theoretical predictions and experimental *** study highlights the significance of vortices in cavity shaping and particle *** validated CFD-DEM-VOF model constitutes a robust tool for simulating particle-laden flows,cont

关键词： CFD-DEM-VOF Trilinear interpolation Particle-laden flow Free-surface Particle water entry Volume conservation

Posture Detection of Heart Disease Using Multi-Head Attention Vision Hybrid(MHAVH)Model

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5期79卷 2673-2696页

作者： Hina Naz Zuping Zhang Mohammed al-Habib Fuad A.Awwad Emad A.A.ismail zaid ali Khan School of Computer Science and Engineering Central South UniversityChangsha410003China Department of Quantitative analysis College of Business AdministrationKing Saud UniversityP.O.Box 71115Riyadh11587Saudi Arabia Electrical and Computer Engineering University of VictoriaVictoriaV9A1B8Canada

Cardiovascular disease is the leading cause of death *** disease causes loss of heart muscles and is also responsible for the death of heart cells,sometimes damaging their functionality.A person’s life may depend on receiving timely assistance as soon as ***,minimizing the death ratio can be achieved by early detection of heart attack(HA)*** the United States alone,an estimated 610,000 people die fromheart attacks each year,accounting for one in every four ***,by identifying and reporting heart attack symptoms early on,it is possible to reduce damage and save many lives *** objective is to devise an algorithm aimed at helping individuals,particularly elderly individuals living independently,to safeguard their *** address these challenges,we employ deep learning *** have utilized a vision transformer(ViT)to address this ***,it has a significant overhead cost due to its memory consumption and computational complexity because of scaling dot-product ***,since transformer performance typically relies on large-scale or adequate data,adapting ViT for smaller datasets is more *** response,we propose a three-in-one steam model,theMulti-Head Attention Vision Hybrid(MHAVH).Thismodel integrates a real-time posture recognition framework to identify chest pain postures indicative of heart attacks using transfer learning techniques,such as ResNet-50 and VGG-16,renowned for their robust feature extraction *** incorporatingmultiple heads into the vision transformer to generate additional metrics and enhance heart-detection capabilities,we leverage a 2019 posture-based dataset comprising RGB images,a novel creation by the author that marks the first dataset tailored for posture-based heart attack *** the limited online data availability,we segmented this dataset into gender categories(male and female)and conducted testing on both segmented and original dat

关键词： image analysis posture of heart attack(PHA)detection hybrid features VGG-16 ResNet-50 vision transformer advance multi-head attention layer

improved Dwarf Mongoose Optimization algorithm for Feature Selection:Application in Software Fault Prediction Datasets

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 Bionic Engineering 2024年第4期21卷 2000-2033页

作者： Abdelaziz i.Hammouri Mohammed A.Awadallah Malik Sh.Braik Mohammed Azmi al-Betar Majdi Beseiso Department of Computer Science Al-Balqa Applied UniversityAl-Salt19117Jordan Department of Scientific Research and Graduate Studies University of Prince Mugrin42241MedinaSaudi Arabia Department of Computer Science Al-Aqsa UniversityGaza4051Palestine Artificial intelligence Research Center(AiRC) Ajman UniversityAjmanUnited Arab Emirates Department of information Technology Al-Huson University CollegeAl-Balqa Applied UniversityAl-HusonIrbid21110Jordan

Feature selection(FS)plays a crucial role in pre-processing machine learning datasets,as it eliminates redundant features to improve classification accuracy and reduce computational *** paper presents an enhanced approach to FS for software fault prediction,specifically by enhancing the binary dwarf mongoose optimization(BDMO)algorithm with a crossover mechanism and a modified positioning updating *** proposed approach,termed iBDMOcr,aims to fortify exploration capability,promote population diversity,and lastly improve the wrapper-based FS process for software fault prediction *** gained superb performance compared to other well-esteemed optimization methods across 17 benchmark *** ranked first in 11 out of 17 datasets in terms of average classification ***,iBDMOcr outperformed other methods in terms of average fitness values and number of selected features across all *** findings demonstrate the effectiveness of iBDMOcr in addressing FS problems in software fault prediction,leading to more accurate and efficient models.

关键词： Dwarf mongoose optimization algorithm Optimization Feature selection Classification

Comparative analysis of jet and underlying event properties across various models as a function of charged particle multiplicity at 7 TeV

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Chinese Physics C 2024年第9期48卷 118-125页

作者： Maryam Waqar Haifa i.alrebdi Muhammad Waqas K.S.al-mugren Muhammad Ajaz Department of Physics Abdul Wali Khan University MardanMardan 23200Pakistan Department of Physics College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia School of Nuclear Science and Technology University of Chinese Academy of SciencesBeijing 100049China

in this study,a comprehensive analysis of jets and underlying events as a function of charged particle multiplicity in proton-proton(pp)collisions at a center-of-mass energy of √s=7 TeV is *** Monte Carlo(MC)event generators,including Pythia8.308,EPOS 1.99,EPOSLHC,EPOS4_(Hydro),and EPOS4_(noHydro),are employed to predict particle *** predictions from these models are compared with experimental data from the CMS *** charged particles are categorized into those associated with underlying events and those linked to jets,and the analysis is restricted to charged particles with|η|0.25 GeV/*** comparing the MC predictions with CMS data,we find that EPOS4_(Hydro),EPOSLHC,and Pythia8 consistently reproduce the experimental results for all charged particles,underlying events,intrajets,and leading charged *** charged jet rates with p_T^(***)>5 GeV/c,EPOS4_(Hydro)and Pythia8 perform exceptionally *** the case of charged jet rates with p_T^(***)→30 GeV/c,EPOSLHC reproduces satisfactorily good results,whereas EPOS4 Hydro exhibits good agreement with the data at higher charged particle multiplicities compared to the other *** can be attributed to the conversion of energy into flow when"Hydro=on"leading to an increase in *** EPOSLHC model describes the data better owing to the new collective flow effects,correlated flow treatment,and parameterization compared to EPOS ***,the examination of the jet p_T spectrum and normalized charged p_T density reveals that EPOS4_(Hydro),EPOS4_(noHydro),and EPOSLHC exhibit good agreement with the experimental results,whereas Pythia8 and EPOS 1.99 do not perform as well owing to the lack of correlated flow treatment.

关键词： Monte Carlo models underlying event jets charged particle multiplicity

A Hybrid Classification and identification of Pneumonia Using African Buffalo Optimization and CNN from Chest X-Ray images

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3期138卷 2497-2517页

作者： Nasser alalwan Ahmed i.Taloba Amr Abozeid Ahmed ibrahim alzahrani ali H.al-Bayatti Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia information System Department Faculty of Computers and InformationAssiut UniversityAssiutEgypt Mathematics Department Faculty of ScienceAl-Azhar UniversityCairoEgypt Cyber Technology institute(CTi) De Montfort UniversityLeicesterUK

An illness known as pneumonia causes inflammation in the *** there is so much information available fromvarious X-ray images,diagnosing pneumonia has typically proven *** improve image quality and speed up the diagnosis of pneumonia,numerous approaches have been *** date,several methods have been employed to identify *** Convolutional Neural Network(CNN)has achieved outstanding success in identifying and diagnosing diseases in the fields of medicine and ***,these methods are complex,inefficient,and imprecise to analyze a big number of *** this paper,a new hybrid method for the automatic classification and identification of Pneumonia from chest X-ray images is *** proposed method(ABOCNN)utilized theAfrican BuffaloOptimization(ABO)algorithmto enhanceCNNperformance and *** Weinmed filter is employed for pre-processing to eliminate unwanted noises from chest X-ray images,followed by feature extraction using the Grey Level Co-Occurrence Matrix(GLCM)*** features are then selected from the dataset using the ABO algorithm,and ultimately,high-performance deep learning using the CNN approach is introduced for the classification and identification of *** results on various datasets showed that,when contrasted to other approaches,the ABO-CNN outperforms them all for the classification *** proposed method exhibits superior values like 96.95%,88%,86%,and 86%for accuracy,precision,recall,and F1-score,respectively.

关键词： African buffalo optimization convolutional neural network pneumonia X-ray

Enhancing indoor User Localization:An Adaptive Bayesian Approach for Multi-Floor Environments

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8期80卷 1889-1905页

作者： Abdulraqeb alhammadi zaid Ahmed Shamsan Arijit De Center for Artificial intelligence and Robotics(CAiRO) Malaysia-Japan International Institute of TechnologyUniversiti Teknologi MalaysiaKuala Lumpur54100Malaysia Department of Electrical Engineering College of EngineeringImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia Department of information Engineering Electronics and TelecommunicationsSapienza UniversityRome00185Italy

indoor localization systems are crucial in addressing the limitations of traditional global positioning system(GPS)in indoor environments due to signal attenuation *** complex indoor spaces become more sophisticated,indoor localization systems become essential for improving user experience,safety,and operational *** localization methods based on Wi-Fi fingerprints require a high-density location fingerprint database,but this can increase the computational burden in the online *** networks,which integrate prior knowledge or domain expertise,are an effective solution for accurately determining indoor user *** networks use probabilistic reasoning to model relationships among various localization parameters for indoor environments that are challenging to *** article proposes an adaptive Bayesian model for multi-floor environments based on fingerprinting techniques to minimize errors in estimating user *** proposed system is an off-the-shelf solution that uses existing Wi-Fi infrastructures to estimate user’s *** operates in both online and offline *** the offline phase,a mobile device with Wi-Fi capability collects radio signals,while in the online phase,generating samples using Gibbs sampling based on the proposed Bayesian model and radio map to predict user’s *** results unequivocally showcase the superior performance of the proposed model when compared to other existing models and *** proposed model achieved an impressive lower average localization error,surpassing the accuracy of competing ***,this noteworthy achievement was attained with minimal reliance on reference points,underscoring the efficiency and efficacy of the proposed model in accurately estimating user locations in indoor environments.

关键词： Localization positioning Bayesian fingerprinting received signal strength(RSS)

Thermal heat flux distribution prediction in an electrical vehicle battery cell using finite element analysis and neural network

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Green Energy and intelligent Transportation 2024年第3期3卷 54-62页

作者： Luttfi A.al-Haddad Latif ibraheem Ahmed i.EL-Seesy alaa Abdulhady Jaber Sinan A.al-Haddad Reza Khosrozadeh Training and Workshops Center University of TechnologyBaghdadIraq Mechanical Engineering Department Memorial University of NewfoundlandNewfoundland and LabradorCanada Mechanical Engineering Department Benha Faculty of EngineeringBenha UniversityBenhaEgypt Mechanical Engineering Department University of TechnologyBaghdadIraq Civil Engineering Department University of TechnologyBaghdadIraq

in terms of battery design and evaluation,Electric Vehicles(EVs)are receiving a great deal of attention as a modern,eco-friendly,sustainable transportation *** this paper,a novel battery pack is designed to maintain a uniform temperature distribution,allowing the battery to operate within its optimal temperature *** proposed battery design is part of a main channel where a portion of cool air will pass from an inlet then exit from an outlet where a uniform temperature distribution is ***,a 3-D model of a battery cell was created,followed by thermal simulation for 15C,25C,and 35C ambient *** simulation results reveal that the temperature distribution is nearly uniform,with slightly higher values in the middle portion of the cell ***,using finite element analysis(FEA),it was determined that the heat flux per unit area is nearly uniform with a slight increase at the ***,a machine learning model is proposed by utilizing a neural network(NN).Lastly,the heat flux values were predicted using the NN model that was *** model was assessed based on statistical measures where a root mean square error(RMSE)value of 0.87%was *** NN outperformed FEA in terms of time consumption with a high prediction accuracy,leveraging the potential of adopting machine learning over FEA in related operational assessments.

关键词： EV battery Thermal distribution Finite element analysis Neural network Heat flux

The current status and future development of high-temperature conventional superconductivity

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

National Science Review 2024年第7期11卷 18-20页

作者： Mikhail i.Eremets High Pressure Chemistry and Physics Group Max-Planck-Institut für Chemie

This survey highlights key advancements in high-temperature superconductivity in hydrogen-rich materials, emphasizing the robust evidence and reproducibility of superconductivity under challenging experimental conditions of megabar pressures. in the near future, achieving room-temperature superconductivity is highly probable, and the field is expected to transition towards near-ambient-pressure superconductivity.

关键词：

Using fracture-based continuum modeling of coupled geomechanical-hydrological processes for numerical simulation of hydraulic fracturing

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Rock Mechanics and Geotechnical Engineering 2024年第5期16卷 1582-1599页

作者： Goodluck i.Ofoegbu GNO Modeling Research LLC. San AntonioTX78253USA

This paper describes numerical simulation of hydraulic fracturing using fracture-based continuum modeling(FBCM)of coupled geomechanical-hydrological processes to evaluate a technique for high-density fracturing and fracture *** simulations are innovative because of modeling discrete fractures explicitly in continuum analysis.A key advantage of FBCM is that fracture initiation and propagation are modeled explicitly without changing the domain grid(*** re-meshing).Further,multiple realizations of a preexisting fracture distribution can be analyzed using the same domain *** simulated hydraulic fracturing technique consists of pressurizing multiple wells simultaneously:initially without permeating fluids into the rock,to seed fractures uniformly and at high density in the wall rock of the wells;followed by fluid injection to propagate the seeded fracture density *** combines the ease of continuum modeling with the potential accuracy of modeling discrete fractures and fracturing *** are modeled as piecewise planar based on intersections with domain elements;fracture geometry stored as continuum properties is used to calculate parameters needed to model individual fractures;and rock behavior is modeled through tensorial aggregation of the behavior of discrete fractures and unfractured *** are presented for previously unfractured rock and for rock with preexisting fractures of horizontal,shallow-dipping,steeply dipping,or vertical *** of a single-well model are used to determine the pattern and spacing for a multiple-well *** results illustrate high-density fracturing and fracture caging through simultaneous fluid injection in multiple wells:for previously unfractured rock or rock with preexisting shallow-dipping or horizontal fractures,and in situ vertical compressive stress greater than *** preexisting fractures are steeply dipping or vertical,and considering the same in situ

关键词： Discrete fracture Fracture-based continuum modeling Fracture caging High-density fracturing Hydraulic fracturing Preexisting fracture