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Moving Least Squares Interpolation Based A-Posteriori Error Technique in Finite Element Elastic Analysis

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Computer Modeling in Engineering & Sciences 2021年第10期129卷 167-189页

作者： Mohd Ahmed Devender Singh Saeed Al Qadhi nguyen viet thanh Civil Engineering Department College of EngineeringKing Khalid UniversityAbha61421Saudi Arabia Ministry of Information Soochna BhavanCGO ComplexDelhi110003India Urban Transport&Coastal Engineering Department University of Transport and CommunicationsHanoi100000Vietnam

The performance of a-posteriori error methodology based on moving least squares(MLS)interpolation is explored in this paper by varying the finite element error recovery parameters,namely recovery points and field variable derivatives *** MLS interpolation based recovery technique uses the weighted least squares method on top of the finite element method’s field variable derivatives solution to build a continuous field variable derivatives *** boundary of the node support(mesh free patch of influenced nodes within a determined distance)is taken as circular,i.e.,circular support domain constructed using radial weights is *** field variable derivatives(stress and strains)are recovered at two kinds of points in the support domain,i.e.,Gauss points(super-convergent stress locations)and nodal *** errors are computed as the difference between the stress from the finite element results and projected stress from the post-processed energy norm at both elemental and global *** benchmark numerical tests using quadrilateral and triangular meshes measure the finite element errors in strain and stress *** numerical examples showed the support domain-based recovery technique’s capabilities for effective and efficient error estimation in the finite element analysis of elastic *** MLS interpolation based recovery technique performs better for stress extraction at Gauss points with the quadrilateral discretization of the problem *** is also shown that the behavior of the MLS interpolation based a-posteriori error technique in stress extraction is comparable to classical Zienkiewicz-Zhu(ZZ)a-posteriori error technique.

关键词： Recovery points field variable derivatives effectivity error recovery support domain error convergence

Spectral wave transformation model for simulating refrac-tion-diffraction with strongly reflecting coastal structures

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Acta Oceanologica Sinica 2011年第2期30卷 25-32页

作者： ZHENG Jinhai nguyen viet thanh ZHANG Chi State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering HohaiUniversity Nanjing 210098 China College of Harbor Coastal and Offshore Engineering Hohai University Nanjing 210098 China

On the basis of the wave action balance equation which incorporates refraction,diffraction,reflection and wave-current interaction,a directional spectral wave transformation model WABED is developed for predicting the irregular wave refraction-diffraction with strongly reflecting structures in coastal *** the model,diffraction is taken into account by introducing a term formulated from a parabolic approximation wave equation,and reflection is calculated through a back-marching numerical approach at the reflecting *** experimental data sets are used to examine the performance of present model with regard to wave characteristics around reflecting coastal *** is from a physical experiment at idealized inlet with parallel jetties,while the other is from a laboratory study on a coastal project of the concave *** good agreements are found for both cases,revealing the applicability of the present model for predicting combined wave refraction-diffraction processes with strongly reflecting coastal structures.

关键词： Wave Height Coastal Structure Spectral Wave Wave Prediction Spectral Wave Model

Anti‐sloshing control:Flatness‐based trajectory planning and tracking control with an integrated extended state observer

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IET Cyber-Systems and Robotics 2024年第3期6卷 31-48页

作者： Khanh nguyen viet Minh Do Duc thanh Cao Duc Tung Lam nguyen School of Electrical and Electronic Engineering Hanoi University of Science and TechnologyHanoiVietnam vietnam Maritime University HaiphongVietnam

The phenomenon of sloshing causes a significantly negative impact on a wide range of industries.A time‐optimal flatness‐based trajectory planning and Lyapunov‐based model predictive control(LMPC)is proposed for trajectory tracking of a transmitting cylindrical container filled with ***,this research presents an equivalent discrete model based on a mass‐spring‐damper ***,after the flatness of the adopted non‐linear model for 2D is established,time‐optimal trajectories are introduced.A control method called LMPC is shown to solve the problem of orbital tracking,which allows setting limits for state *** addition,to ensure system performance,a linear extended state observer(LESO)is integrated to cope with system ***,the efficiency of the proposed approach for liquid sloshing suppression and tracking is illustrated by simulations.

关键词： control dynamic model motion planning

Prediction of the Local Scour at the Bridge Square Pier Using a 3D Numerical Model

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Open Journal of Applied Sciences 2014年第2期4卷 34-42页

作者： nguyen viet thanh Dang Huu Chung Tran Dinh Nghien University of Transport and Communication Hanoi Viet Nam vietnam Academy of Science and Technology Hanoi Viet Nam

In this paper, the problem on local scour around a single square pier was studied by using both the numerical and physical models. The numerical model for the study is FSUM based on a finite-difference method to solve the Reynolds averaged Navier-Stokes equations (RANS) and the equations for suspended sediment concentration and bed morphology. The computed result was verified through data measured in the experimental flume with a sand bed. In general, the typical features of local scour around the pier were successfully simulated by FSUM, such as stream flow, bow flow, down flow, horseshoe vortex. The comparison between the computation and experiment data shows a quite good fitness. Both numerical model and experiment results show that the maximum scour depth occurs at two front edges of the pier. Although the computed result shows a little bigger scour depth in comparison with the measurement in the physical model, it still confirms the reliability of numerical model in some measure.

关键词： Numerical Modeling Experiment Bridge Square Pier Local Scour FSUM Model

Truly optimal semi-active damping to control free vibration of a single degree of freedom system

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Theoretical & Applied Mechanics Letters 2024年第2期14卷 142-145页

作者： viet Duc La Ngoc Tuan nguyen Institute of Mechanics Vietnam Academy of Science and TechnologyHanoi 10000Vietnam Graduate University of Science and Technology Vietnam Academy of Science and TechnologyHanoi 10000Vietnam

This paper studies a single degree of freedom system under free vibration and controlled by a general semiactive damping.A general integral of squared error is considered as the performance index.A one-time switching damping controller is proposed and *** pontryagin maximum principle is used to prove that no other form of semi-active damping can provide the better performance than the proposed one-time switching damping.

关键词： Analytical optimization Quadratic integral Lyapunov equation Pontryagin maximum principle

Forecasting measured responses of structures using temporal deep learning and dual attention

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Frontiers of Structural and Civil Engineering 2024年第6期18卷 832-850页

作者： viet-Hung DANG Trong-Phu nguyen Thi-Lien PHAM Huan X.nguyen Department of Structural Mechanics Hanoi University of Civil EngineeringHanoi 11600Vietnam Faculty of Applied Science University of Economics-Technology for IndustriesHanoi 11600Vietnam London Digital Twin Research Centre Faculty of Science and TechnologyMiddlesex UniversityLondon NW44BTUK International School Vietnam National UniversityHanoi 11600Vietnam

The objective of this study is to develop a novel and efficient model for forecasting the nonlinear behavior of structures in response to time-varying random *** key idea is to design a deep learning architecture to leverage the relationships,between external excitations and structure's vibration signals,and between historical values and future values,within multiple time-series *** proposed method consists of two main steps:the first step applies a global attention mechanism to combine multiple-measured time series and time-varying excitation into a weighted time series before feeding it to a temporal architecture;the second step utilizes a self-attention mechanism followed by a fully connected layer to predict multi-step future *** viability of the proposed method is demonstrated via two case studies involving synthetic data from a three-dimensional(3D)reinforced concrete structure and experimental data from an 18-story steel ***,comparison and robustness studies are carried out,showing that the proposed method outperforms conventional methods and maintains high performance in the presence of noise with an amplitude of less than 10%.

关键词： structural dynamic time-varying excitation deep learning signal processing response forecasting

Unknown DDoS Attack Detection with Fuzzy C-Means Clustering and Spatial Location Constraint Prototype Loss

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Computers, Materials & Continua 2024年第2期78卷 2181-2205页

作者： thanh-Lam nguyen HaoKao thanh-Tuan nguyen Mong-Fong Horng Chin-Shiuh Shieh Department of Electronic Engineering National Kaohsiung University of Science and TechnologyKaohsiung807618Taiwan Department of Electronic and Automation Engineering Nha Trang UniversityNha Trang650000Vietnam

Since its inception,the Internet has been rapidly *** the advancement of science and technology and the explosive growth of the population,the demand for the Internet has been on the *** applications in education,healthcare,entertainment,science,and more are being increasingly deployed based on the ***,malicious threats on the internet are on the rise as *** Denial of Service(DDoS)attacks are among the most common and dangerous threats on the internet *** scale and complexity of DDoS attacks are constantly *** Detection Systems(IDS)have been deployed and have demonstrated their effectiveness in defense against those *** addition,the research of Machine Learning(ML)and Deep Learning(DL)in IDS has gained effective results and significant ***,one of the challenges when applying ML and DL techniques in intrusion detection is the identification of unknown *** attacks,which are not encountered during the system’s training,can lead to misclassification with significant *** this research,we focused on addressing the issue of Unknown Attack Detection,combining two methods:Spatial Location Constraint Prototype Loss(SLCPL)and Fuzzy C-Means(FCM).With the proposed method,we achieved promising results compared to traditional *** proposed method demonstrates a very high accuracy of up to 99.8%with a low false positive rate for known attacks on the Intrusion Detection Evaluation Dataset(CICIDS2017)***,the accuracy is also very high,reaching 99.7%,and the precision goes up to 99.9%for unknown DDoS attacks on the DDoS Evaluation Dataset(CICDDoS2019)*** success of the proposed method is due to the combination of SLCPL,an advanced Open-Set Recognition(OSR)technique,and FCM,a traditional yet highly applicable clustering *** has yielded a novel method in the field of unknown attack *** further expands the trend of applying DL and M

关键词： Cybersecurity DDoS unknown attack detection machine learning deep learning incremental learning convolutional neural networks(CNN) open-set recognition(OSR) spatial location constraint prototype loss fuzzy c-means CICIDS2017 CICDDoS2019

GLOBAL BOUND ON THE GRADIENT OF SOLUTIONS TO p-LAPLACE TYPE EQUATIONS WITH MIXED DATA

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Acta Mathematica Scientia 2024年第4期44卷 1394-1414页

作者： Minh-Phuong TRAN The-Quang TRAN thanh-Nhan nguyen Applied Analysis Research Group Faculty of Mathematics and StatisticsTon Duc Thang UniversityHo Chi Minh CityVietnam nguyen Huu Huan High School Thu Duc CityVietnam Group of Analysis and Applied Mathematics Department of MathematicsHo Chi Minh City University of EducationVietnam

In this paper,the study of gradient regularity for solutions of a class of elliptic problems of p-Laplace type is *** particular,we prove a global result concerning Lorentz-Morrey regularity of the non-homogeneous boundary data problem:-div((s^(2)+|▽u|^(2)p-2/2)▽u)=-div(|f|^(p-2)f)+g inΩ,u=h in■Ω,with the(sub-elliptic)degeneracy condition s∈[0,1]and with mixed data f∈L^(p)(Q;R^(n)),g∈Lp/(p-1)(Ω;R^(n))for p∈(1,n).This problem naturally arises in various applications such as dynamics of non-Newtonian fluid theory,electro-rheology,radiation of heat,plastic moulding and many *** on the idea of level-set inequality on fractional maximal distribution functions,it enables us to carry out a global regularity result of the solution via fractional maximal *** to the significance of M_(α)and its relation with Riesz potential,estimates via fractional maximal functions allow us to bound oscillations not only for solution but also its fractional derivatives of orderα.Our approach therefore has its own interest.

关键词： gradient estimates p-Laplace quasilinear elliptic equation fractional maximal operators Lorentz-Morrey spaces

Heterogeneous decentralised machine unlearning with seed model distillation

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CAAI Transactions on Intelligence Technology 2024年第3期9卷 608-619页

作者： Guanhua Ye Tong Chen Quoc viet Hung nguyen Hongzhi Yin School of Information Technology and Electrical Engineering The University of QueenslandSt LuciaQueenslandAustralia School of Information and Communication Technology Griffith UniversityBrisbaneQueenslandAustralia

As some recent information security legislation endowed users with unconditional rights to be forgotten by any trained machine learning model,personalised IoT service pro-viders have to put unlearning functionality into their *** most straight-forward method to unlearn users'contribution is to retrain the model from the initial state,which is not realistic in high throughput applications with frequent unlearning *** some machine unlearning frameworks have been proposed to speed up the retraining process,they fail to match decentralised learning scenarios.A decentralised unlearning framework called heterogeneous decentralised unlearning framework with seed(HDUS)is designed,which uses distilled seed models to construct erasable en-sembles for all ***,the framework is compatible with heterogeneous on-device models,representing stronger scalability in real-world *** experiments on three real-world datasets show that our HDUS achieves state-of-the-art performance.

关键词： data mining data privacy machine learning