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Diverting agents in the oil and gas industry:A comprehensive analysis of their origins,types,and applications

Petroleum Research 2024年第1期9卷 72-84页

作者： Namrata Bist Abhishek Nair Kriti Yadav Anirbid Sircar Pandit Deendayal Energy university GandhinagarGujarat382007India Department of Geology Patna UniversityAshok RajpathPatna800005India

During the life of a well,treatments are carried out to boost productivity by stimulating initially unproduced *** treatments include hydraulic fracturing,matrix acidization,and acid fracturing,among *** fracturing treatment is generally applied to deeper reservoirs of oil or natural gas for enhanced *** infusing proppant,water,and chemicals under extreme pressure during the fracturing procedure,fissures in and beneath the reservoir layer can be accessed and *** stimulating procedure,matrix acidization,involves injecting acid down the drilling hole to permeate the rock fissures at stresses lower than the fracture *** addition,carbonate reservoir acid fracturing stimulation is commonly used as an acid treatment technique whereby a pressure greater than the formation disintegration pressure or spontaneous fracture closure pressure is used to compress acid into the *** treatments allow existing wells to sustain hydrocarbon production without new wells being ***,when employed efficiently,can prevent the need to use a rig to provide momentary physical barriers,thus lowering the cost of the *** improvements in diversion technology make use of a variety of degradable particles that act as momentary bridges,either at the perforation entries or inside the existing *** aim of this study is to introduce different types of mechanical and chemical diverters used to enhance the productivity of *** study explains the concepts of different types of diverters and their applications in several formations,it will also help readers to understand the selection procedures based on the suitability and requirements of diverter use by case studies from around the world.

关键词： Refracturing Well treatment Chemical diverter Mechanical diverter Acid fracturing

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Machine learning-enhanced Monte Carlo and subset simulations for advanced risk assessment in transportation infrastructure

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Journal of Mountain Science 2024年第2期21卷 690-717页

作者： Furquan AHMAD Pijush SAMUI S.S.MISHRA Department of Civil Engineering National Institute of TechnologyPatna 800006India

The maintenance of safety and dependability in rail and road embankments is of utmost importance in order to facilitate the smooth operation of transportation *** study introduces a comprehensive methodology for soil slope stability evaluation,employing Monte Carlo Simulation(MCS)and Subset Simulation(SS)with the"UPSS 3.0 Add-in"in *** on an 11.693-meter embankment with a soil slope(inclination ratio of 2H:1V),the investigation considers earthquake coefficients(kh)and pore water pressure ratios(ru)following Indian zoning *** chance of slope failure showed a considerable increase as the Coefficient of Variation(COV),seismic coefficients(kh),and pore water pressure ratios(ru)experienced an *** SS approach showed exceptional efficacy in calculating odds of failure that are notably *** computational modeling,the study optimized the worst-case scenario using ANFIS-GA,ANFIS-GWO,ANFIS-PSO,and ANFIS-BBO *** ANFIS-PSO model exhibits exceptional accuracy(training R2=0.9011,RMSE=0.0549;testing R2=0.8968,RMSE=0.0615),emerging as the most *** study highlights the significance of conducting thorough risk assessments and offers practical insights into evaluating and improving the stability of soil slopes in transportation *** findings contribute to the enhancement of safety and reliability in real-world situations.

关键词： Monte Carlo Simulation Subset Simulation Machine Learning Seismic coefficient

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Proposed numerical and machine learning models for fiber-reinforced polymer concrete-steel hollow and solid elliptical columns

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Frontiers of Structural and Civil Engineering 2024年第8期18卷 1169-1194页

作者： Tang QIONG Ishan JHA Alireza BAHRAMI Haytham F.ISLEEM Rakesh KUMAR Pijush SAMUI School of Applied Technologies Qujing Normal UniversityQujing 655011China Department of Civil Engineering Indian Institute of Technology-BHUVaranasi 221005India Department of Building Engineering Energy Systems and Sustainability ScienceFaculty of Engineering and Sustainable DevelopmentUniversity of GävleGävle 80176Sweden Department of Civil Engineering National Institute of Technology-PatnaPatna 800005India

This study employs a hybrid approach,integrating finite element method(FEM)simulations with machine learning(ML)techniques to investigate the structural performance of double-skin tubular columns(DSTCs)reinforced with glass fiber-reinforced polymer(GFRP).The investigation involves a comprehensive examination of critical parameters,including aspect ratio,concrete strength,number of GFRP confinement layers,and dimensions of steel tubes used in DSTCs,through comparative analyses and parametric *** ensure the credibility of the findings,the results are rigorously validated against experimental data,establishing the precision and trustworthiness of the *** present research work examines the use of the columns with elliptical cross-sections and contributes valuable insights into the application of FEM and ML in the design and evaluation of structural systems within the field of structural engineering.

关键词： elliptical column fiber-reinforced polymer machine learning finite element method ABAQUS

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An Effective Hybrid Model of ELM and Enhanced GWO for Estimating Compressive Strength of Metakaolin-Contained Cemented Materials

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1521-1555页

作者： Abidhan Bardhan Raushan Kumar Singh Mohammed Alatiyyah Sulaiman Abdullah Alateyah Department of Civil Engineering National Institute of Technology PatnaPatnaIndia Department of Computer Engineering and Applications GLA UniversityMathuraIndia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam Bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Computer Science College of Science and ArtsQassim UniversityUnaizahSaudi Arabia

This research proposes a highly effective soft computing paradigm for estimating the compressive strength(CS)of metakaolin-contained cemented *** proposed approach is a combination of an enhanced grey wolf optimizer(EGWO)and an extreme learning machine(ELM).EGWO is an augmented form of the classic grey wolf optimizer(GWO).Compared to standard GWO,EGWO has a better hunting mechanism and produces an optimal *** EGWO was used to optimize the ELM structure and a hybrid model,ELM-EGWO,was *** train and validate the proposed ELM-EGWO model,a sum of 361 experimental results featuring five influencing factors was *** on sensitivity analysis,three distinct cases of influencing parameters were considered to investigate the effect of influencing factors on predictive *** consequences show that the constructed ELM-EGWO achieved the most accurate precision in both training(RMSE=0.0959)and testing(RMSE=0.0912)*** outcomes of the ELM-EGWO are significantly superior to those of deep neural networks(DNN),k-nearest neighbors(KNN),long short-term memory(LSTM),and other hybrid ELMs constructed with GWO,particle swarm optimization(PSO),harris hawks optimization(HHO),salp swarm algorithm(SSA),marine predators algorithm(MPA),and colony predation algorithm(CPA).The overall results demonstrate that the newly suggested ELM-EGWO has the potential to estimate the CS of metakaolin-contained cemented materials with a high degree of precision and robustness.

关键词： Metakaolin-contained cemented materials compressive strength extreme learning machine grey wolf optimizer swarm intelligence uncertainty analysis artificial intelligence

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Impact of infectious density-induced additional screening and treatment saturation on COVID-19:Modeling and cost-effective optimal control

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Infectious Disease Modelling 2024年第2期9卷 569-600页

作者： Sonu Lamba Tanuja Das Prashant K.Srivastava Department of Mathematics Indian Institute of Technology Patna Bihta–801106PatnaBiharIndia Department of Mathematics and Statistics University of New Brunswick FrederictonNBE3B 5A3Canada

This study introduces a novel SI2HR model,where“I2”denotes two infectious classes representing asymptomatic and symptomatic infections,aiming to investigate and analyze the cost-effective optimal control measures for managing *** model incorporates a novel concept of infectious density-induced additional screening(IDIAS)and accounts for treatment ***,the model considers the possibility of reinfection and the loss of immunity in individuals who have previously *** validate and calibrate the proposed model,real data from November–December 2022 in Hong Kong are *** estimated parameters obtained from this calibration process are valuable for prediction purposes and facilitate further numerical *** analysis of the model reveals that delays in screening,treatment,and quarantine contribute to an increase in the basic reproduction number R0,indicating a tendency towards *** particular,from the elasticity of R0,we deduce that normalized sensitivity indices of baseline screening rate(θ),quarantine rates(γ,αs),and treatment rate(α)are negative,which shows that delaying any of these may cause huge surge in R0,ultimately increases the disease ***,by the contour plots,we note the two-parameter behavior of the infectives(both symptomatic and asymptomatic).Expanding upon the model analysis,an optimal control problem(OCP)is formulated,incorporating three control measures:precautionary interventions,boosted IDIAS,and boosted *** Pontryagin's maximum principle and the forward-backward sweep method are employed to solve the *** numerical simulations highlight that enhanced screening and treatment,coupled with preventive interventions,can effectively contribute to sustainable disease ***,the cost-effectiveness analysis(CEA)conducted in this study suggests that boosting IDIAS alone is the most economically efficient and cost-effective approach compared to other *** CEA resul

关键词： COVID-19 IDIAS Estimation Prediction Optimal control Cost-effectiveness analysis

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Energy-Efficient Implementation of BCD to Excess-3 Code Converter for Nano-Communication Using QCA Technology

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China Communications 2024年第6期21卷 103-111页

作者： Nuriddin Safoev Angshuman Khan Khudoykulov Zarif Turakulovich Rajeev Arya Department of Cybersecurity&Criminology Tashkent University of Information TechnologiesTashkent 100084Uzbekistan Department of Electronics and Communication Engineering University of Engineering and ManagementJaipurRajasthan 303807India Department of Cryptology Tashkent University of Information TechnologiesTashkent 100084Uzbekistan Department of Electronics and Communication Engineering National Institute of Technology PatnaBihar 800005India

Code converters are essential in digital nano communication;therefore,a low-complexity optimal QCA layout for a BCD to Excess-3 code converter has been proposed in this paper.A QCA clockphase-based design technique was adopted to investigate integration with other complicated *** a unique XOR gate,the recommended circuit’s cell complexity has been *** findings produced using the QCADesigner-2.0.3,a reliable simulation tool,prove the effectiveness of the current structure over earlier designs by considering the number of cells deployed,the area occupied,and the latency as design *** addition,the popular tool QCAPro was used to estimate the energy dissipation of the proposed *** proposed technique reduces the occupied space by∼40%,improves cell complexity by∼20%,and reduces energy dissipation by∼1.8 times(atγ=1.5EK)compared to the current scalable *** paper also studied the suggested structure’s energy dissipation and compared it to existing works for a better performance evaluation.

关键词： BCD code converter Excess-3 nano communication QCA circuits

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Prediction of bearing capacity of pile foundation using deep learning approaches

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Frontiers of Structural and Civil Engineering 2024年第6期18卷 870-886页

作者： Manish KUMAR Divesh Ranjan KUMAR Jitendra KHATTI Pijush SAMUI Kamaldeep Singh GROVER Department of Civil Engineering SRM Institute of Science and Technology Tiruchirappalli CampusTrichy 621105India Department of Civil Engineering National Institute of Technology PatnaBihar 800005India Department of Civil Engineering Faculty of EngineeringThammasat School of EngineeringThammasat UniversityBangkok10200Thailand Department of Civil Engineering Rajasthan Technical UniversityKota 324010India

The accurate prediction of bearing capacity is crucial in ensuring the structural integrity and safety of pile *** research compares the Deep Neural Networks(DNN),Convolutional Neural Networks(CNN),Recurrent Neural Networks(RNN),Long Short-Term Memory(LSTM),and Bidirectional LSTM(BiLSTM)algorithms utilizing a data set of 257 dynamic pile load tests for the first ***,this research illustrates the multicollinearity effect on DNN,CNN,RNN,LSTM,and BiLSTM models’performance and accuracy for the first time.A comprehensive comparative analysis is conducted,employing various statistical performance parameters,rank analysis,and error matrix to evaluate the performance of these *** performance is further validated using external validation,and visual interpretation is provided using the regression error characteristics(REC)curve and Taylor *** from the comparative analysis reveal that the DNN(Coefficient of determination(R^(2))_(training(TR))=0.97,root mean squared error(RMSE)_(TR)=0.0413;R^(2)_(testing(TS))=0.9,RMSE_(TS)=0.08)followed by BiLSTM(R^(2)_(TR)=0.91,RMSE_(TR)=0.782;R^(2)_(TS)=0.89,RMSE_(TS)=0.0862)model demonstrates the highest performance *** is noted that the BiLSTM model is better than LSTM because the BiLSTM model,which increases the amount of information for the network,is a sequence processing model made up of two LSTMs,one of which takes the input in a forward manner,and the other in a backward *** prediction of pile-bearing capacity is strongly influenced by ram weight(having a considerable multicollinearity level),and the effect of the considerable multicollinearity level has been determined for the model based on the recurrent neural network *** this study,the recurrent neural network model has the least performance and accuracy in predicting the pile-bearing capacity.

关键词： deep learning algorithms high-strain dynamic pile test bearing capacity of the pile

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Cloud‐based video streaming services:Trends,challenges,and opportunities

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CAAI Transactions on Intelligence Technology 2024年第2期9卷 265-285页

作者： Tajinder Kumar Purushottam Sharma Jaswinder Tanwar Hisham Alsghier Shashi Bhushan Hesham Alhumyani Vivek Sharma Ahmed I.Alutaibi CSE Department JMIETIYamunanagarHaryanaIndia Department of Information Technology ASETAmity University Uttar PradeshNoidaIndia Tata Communications Limited New DelhiIndia Department of Information Technology College of Computer and Information SciencesMajmaah UniversityMajmaahSaudi Arabia Amity School of Engineering and Technology Amity UniversityPatnaBiharIndia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaifSaudi Arabia Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityMajmaahSaudi Arabia

Cloud computing has drastically changed the delivery and consumption of live streaming *** designs,challenges,and possible uses of cloud computing for live streaming are studied.A comprehensive overview of the technical and business issues surrounding cloudbased live streaming is provided,including the benefits of cloud computing,the various live streaming architectures,and the challenges that live streaming service providers face in delivering high‐quality,real‐time *** different techniques used to improve the performance of video streaming,such as adaptive bit‐rate streaming,multicast distribution,and edge computing are discussed and the necessity of low‐latency and high‐quality video transmission in cloud‐based live streaming is *** such as improving user experience and live streaming service performance using cutting‐edge technology,like artificial intelligence and machine learning are *** addition,the legal and regulatory implications of cloud‐based live streaming,including issues with network neutrality,data privacy,and content moderation are *** future of cloud computing for live streaming is examined in the section that follows,and it looks at the most likely new developments in terms of trends and *** technology vendors,live streaming service providers,and regulators,the findings have major policy‐relevant *** on how stakeholders should address these concerns and take advantage of the potential presented by this rapidly evolving sector,as well as insights into the key challenges and opportunities associated with cloud‐based live streaming are provided.

关键词： cloud computing video analysis video coding

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Predicting Rock Burst in Underground Engineering Leveraging a Novel Metaheuristic-Based LightGBM Model

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 229-253页

作者： Kai Wang Biao He Pijush Samui Jian Zhou No.Three Engineering Co. Ltd.CCCC First Highway Engineering CompanyBeijing101102China Department of Civil Engineering Faculty of EngineeringUniversiti MalayaKuala Lumpur50603Malaysia Department of Civil Engineering National Institute of Technology PatnaBihar800005India School of Resources and Safety Engineering Central South UniversityChangsha410083China

Rock bursts represent a formidable challenge in underground engineering,posing substantial risks to both infrastructure and human *** sudden and violent failures of rock masses are characterized by the rapid release of accumulated stress within the rock,leading to severe seismic events and structural ***,the development of reliable prediction models for rock bursts is paramount to mitigating these *** study aims to propose a tree-based model—a Light Gradient Boosting Machine(LightGBM)—to predict the intensity of rock bursts in underground engineering.322 actual rock burst cases are collected to constitute an exhaustive rock burst dataset,which serves to train the *** population-basedmetaheuristic algorithms are used to optimize the hyperparameters of the LightGBM ***,the sensitivity analysis is used to identify the predominant factors that may incur the occurrence of rock *** results show that the population-based metaheuristic algorithms have a good ability to search out the optimal hyperparameters of the LightGBM *** developed LightGBM model yields promising performance in predicting the intensity of rock bursts,with which accuracy on training and testing sets are 0.972 and 0.944,*** sensitivity analysis discloses that the risk of occurring rock burst is significantly sensitive to three factors:uniaxial compressive strength(σc),stress concentration factor(SCF),and elastic strain energy index(Wet).Moreover,this study clarifies the particular impact of these three factors on the intensity of rock bursts through the partial dependence plot.

关键词： Rock burst prediction LightGBM coati optimization algorithm pelican optimization algorithm partial dependence plot

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Optics-based metaheuristic approach to assess critical failure surfaces in both circular and non-circular failure modes for slope stability analysis

Rock Mechanics Bulletin

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Rock Mechanics Bulletin 2024年第1期3卷 37-54页

作者： Jayraj Singh Amit Kumar Verma Haider Banka Ravishankar kumar Amit Jaiswal Department of Computer Science&Engineering NIIT UniversityRajasthanIndia Department of Civil&Environment Engineering Indian Institute of TechnologyPatnaBihar801106India Department of Computer Science&Engineering Indian Institute of Technology(ISM)DhanbadJharkhand826004India Department of Mining Bharat Coking Coal LimitedDhanbadJharkhand826005India

In many construction projects,a proactive slope stability evaluation is a *** many deterministic or non-deterministic approaches have been commonly used,metaheuristic approaches have resulted in high precision and significant outcomes for slope stability analysis *** current work focuses on the reliable assessment of critical failure surfaces associated with the least factor of safety value in both homogeneous and non-homogeneous slopes using a new simplified meta-heuristic approach called optics-inspired optimization(OIO).The algorithm utilizes six different LEM methods as a fitness function for deriving the factor of *** analysis over three benchmark studies has been performed to demonstrate the algorithm's robustness and *** implementation found more robust results as compared to previous ***,the algorithm's statistical implication is conducted using the ANOVA test,which inferred better *** this interpretation,the approach claims to be suitable and efficient for slope stability analysis.

关键词： OIO-Algorithm Metaheuristic algorithms Slope stability analysis Critical failure surface LEM'S procedure

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