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| 1 | Implementing the Node Based Smoothed Finite Element Method as User Element in Abaqus for Linear and Nonlinear Elasticity显示文摘In this paper,the node based smoothed-strain Abaqus user element(UEL)in the framework of finite element method is introduced.The basic idea behind of the node based smoothed finite element(NSFEM)is that finite element cells are divided into subcells and subcells construct the smoothing domain associated with each node of a finite element cell[Liu,Dai and Nguyen-Thoi(2007)].Therefore,the numerical integration is globally performed over smoothing domains.It is demonstrated that the proposed UEL retains all the advantages of the NSFEM,i.e.,upper bound solution,overly soft stiffness and free from locking in compressible and nearly-incompressible media.In this work,the constant strain triangular(CST)elements are used to construct node based smoothing domains,since any complex two dimensional domains can be discretized using CST elements.This additional challenge is successfully addressed in this paper.The efficacy and robustness of the proposed work is obtained by several benchmark problems in both linear and nonlinear elasticity.The developed UEL and the associated files can be downloaded from https://github.com/nsundar/NSFEM. | S.Kshrisagar A.Francis J.J.Yee S.Natarajan C.K.Lee | 2019 | Computers, Materials & Continua2019，，8： | 2 |
| 2 | Disinfection byproduct regulatory compliance surrogates and bromide-associated risk显示文摘Natural and anthropogenic factors can alter bromide concentrations in drinking water sources. Increasing source water bromide concentrations increases the formation and alters the speciation of disinfection byproducts(DBPs) formed during drinking water treatment.Brominated DBPs are more toxic than their chlorinated analogs, and thus have a greater impact on human health. However, DBPs are regulated based on the mass sum of DBPs within a given class(e.g., trihalomethanes and haloacetic acids), not based on species-specific risk or extent of bromine incorporation. The regulated surrogate measures are intended to protect against not only the species they directly represent, but also against unregulated DBPs that are not routinely measured. Surrogates that do not incorporate effects of increasing bromide may not adequately capture human health risk associated with drinking water when source water bromide is elevated. The present study analyzes trihalomethanes(THMs), measured as TTHM,with varying source water bromide concentrations, and assesses its correlation with brominated THM, TTHM risk and species-specific THM concentrations and associated risk.Alternative potential surrogates are evaluated to assess their ability to capture THM risk under different source water bromide concentration conditions. The results of the present study indicate that TTHM does not adequately capture risk of the regulated species when source water bromide concentrations are elevated, and thus would also likely be an inadequate surrogate for many unregulated brominated species. Alternative surrogate measures,including THM3 and the bromodichloromethane concentration, are more robust surrogates for species-specific THM risk at varying source water bromide concentrations. | Chelsea Kolb Royce A.Francis Jeanne M.VanBriesen | 2017 | Journal of Environmental Sciences2017，29，8： | 1 |
| 3 | Analysis of nitrite reductase (nirK and nirS) genes and cultivation reveal depauperate community of denitrifying bacteria in the Black Sea suboxic zone显示文摘 | Brian B.Oakley Christopher A.Francis Kathryn J.Roberts Clara A.Fuchsman S.Srinivasan James T.Staley | 2006 | Environmental Microbiology2006，，1： | 1 |
| 4 | Techniques: Recombinogenic engineering–new options for cloning and manipulating DNA显示文摘 | Joep P.P Muyrers Youming Zhang A.Francis Stewart | 2001 | Trends in Biochemical Sciences2001，，5： | 1 |
| 5 | Enhanced Metaheuristics with Trust Aware Route Selection for Wireless Sensor Networks显示文摘Recently,a trust system was introduced to enhance security and cooperation between nodes in wireless sensor networks(WSN).In routing,the trust system includes or avoids nodes related to the estimated trust values in the routing function.This article introduces Enhanced Metaheuristics with Trust Aware Secure Route Selection Protocol(EMTA-SRSP)for WSN.The presented EMTA-SRSP technique majorly involves the optimal selection of routes in WSN.To accomplish this,the EMTA-SRSP technique involves the design of an oppositional Aquila optimization algorithm to choose safe routes for data communication.For the clustering process,the nodes with maximum residual energy will be considered cluster heads(CHs).In addition,the OAOA technique gets executed to choose optimal routes based on objective functions with multiple parameters such as energy,distance,and trust degree.The experimental validation of the EMTA-SRSP technique is tested,and the results exhibited a better performance of the EMTA-SRSP technique over other approaches. | A.Francis Saviour Devaraj T.Satyanarayana Murthy Fayadh Alenezi E.Laxmi Lydia Mohamad Adzhar Md Zawawi Mohamad Khairi Ishak | 2023 | Computer Systems Science & Engineering2023，46，8： | 0 |
| 6 | An Optimal Deep Learning for Cooperative Intelligent Transportation System显示文摘Cooperative Intelligent Transport System(C-ITS)plays a vital role in the future road traffic management system.A vital element of C-ITS comprises vehicles,road side units,and traffic command centers,which produce a massive quantity of data comprising both mobility and service-related data.For the extraction of meaningful and related details out of the generated data,data science acts as an essential part of the upcoming C-ITS applications.At the same time,prediction of short-term traffic flow is highly essential to manage the traffic accurately.Due to the rapid increase in the amount of traffic data,deep learning(DL)models are widely employed,which uses a non-parametric approach for dealing with traffic flow forecasting.This paper focuses on the design of intelligent deep learning based short-termtraffic flow prediction(IDL-STFLP)model for C-ITS that assists the people in various ways,namely optimization of signal timing by traffic signal controllers,travelers being able to adapt and alter their routes,and so on.The presented IDLSTFLP model operates on two main stages namely vehicle counting and traffic flow prediction.The IDL-STFLP model employs the Fully Convolutional Redundant Counting(FCRC)based vehicle count process.In addition,deep belief network(DBN)model is applied for the prediction of short-term traffic flow.To further improve the performance of the DBN in traffic flow prediction,it will be optimized by Quantum-behaved bat algorithm(QBA)which optimizes the tunable parameters of DBN.Experimental results based on benchmark dataset show that the presented method can count vehicles and predict traffic flowin real-time with amaximumperformance under dissimilar environmental situations. | K.Lakshmi Srinivas Nagineni E.Laxmi Lydia A.Francis Saviour Devaraj Sachi Nandan Mohanty Irina V.Pustokhina Denis A.Pustokhin | 2022 | Computers, Materials & Continua2022，，7： | 0 |
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