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On the interaction phenomena to the nonlinear generalized Hietarinta-type equation

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Journal of Ocean Engineering and Science 2024年第1期9卷 89-97页

作者： Usman Younas T.A.Sulaiman jingli ren A.Yusuf State Key Laboratory of Power Grid Environmental Protection/Henan Academy of Big Data Zhengzhou UniversityZhengzhou 450001China Faculty of Science Federal University DutseJigawaNigeria Department of Computer Engineering Biruni University IstanbulTurkey

In this paper,we describe the nonlinear behavior of a generalized fourth-order Hietarinta-type equa-tion for dispersive waves in(2+1)*** various wave formations are retrieved by using Hirota’s bilinear method(HBM)and various test function *** Hirota method is a widely used and robust mathematical tool for finding soliton solutions of nonlinear partial differential equa-tions(NLPDEs)in a variety of disciplines like mathematical physics,nonlinear dynamics,oceanography,engineering sciences,and others requires bilinearization of nonlinear *** different wave structures in the forms of new breather,lump-periodic,rogue waves,and two-wave solutions are *** addi-tion,the physical behavior of the acquired solutions is illustrated in three-dimensional,two-dimensional,density,and contour profiles by the assistance of suitable *** on the obtained results,we can assert that the employed methodology is straightforward,dynamic,highly efficient,and will serve as a valuable tool for discussing complex issues in a diversity of domains specifically ocean and coastal *** have also made an important first step in understanding the structure and physical be-havior of complex structures with our findings *** believe this research is timely and relevant to a wide range of engineering *** results obtained are useful for comprehending the fundamental scenarios of nonlinear sciences.

关键词： Hirota’s bilinear method Lump-periodic solutions Breather waves Rouge waves Multi-waves

Sparse identification-assisted exploration of the atomic-scale deformation mechanism in multiphase CoCrFeNi high-entropy alloys

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Science China(Technological Sciences) 2024年第4期67卷 1124-1132页

作者： XIAO Lu GUO XiaoXiang SUN YuTong WANG Gang LONG WeiMin LIAW Peter K. ren jingli School of Mathematics and Statistics Zhengzhou UniversityZhengzhou 450001China Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing 100190China Institute of Materials Shanghai UniversityShanghai 200444China SKL of Advanced Brazing Metals&Technology Zhengzhou Research Institute of Mechanical EngineeringZhengzhou 450001China Department of Materials Science and Engineering The University of TennesseeKnoxvilleTN 37996USA

This study investigated the atomic-scale deformation mechanism of multiphase CoCrFeNi high-entropy alloys(HEAs)at liquid helium,liquid nitrogen,and room temperatures.A million-atom multiphase HEA was prepared using molecular dynamics simulation involving melt and quench *** HEA exhibited high-density dislocations and some twins,consistent with experimental *** analysis revealed an inconsistent evolution of the microstructure under tensile *** particular,the elastic and initial plastic stages exhibited an increase in the disordered structure at the expense of the face-centered cubic and hexagonal close-packed structures,followed by a subsequent transformation involving multiple structural ***,through sparse identification,a model depicting microstructural evolution during tension was extracted for the CoCrFeNi HEA at three typical temperatures and three tensile *** model highlighted the importance of the body-centered cubic structure in the evolutionary process.

关键词： high-entropy alloy data-driven method microstructure evolution multiphase structure molecular dynamics simulation

Design of a prediction system based on the dynamical feed-forward neural network

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Science China(Information Sciences) 2023年第1期66卷 43-59页

作者： Xiaoxiang GUO Weimin HAN jingli ren Henan Academy of Big Data Zhengzhou University Department of Mathematics University of Iowa

Analysis and prediction of time series play a significant role in scientific fields of meteorology,epidemiology, and economy. Efficient and accurate prediction of signals can give an early detection of abnormal variations, provide guidance on preparing a timely response and avoid presumably adverse *** this paper, a prediction system is designed based on the dynamical feed-forward neural network. The trajectory information in the reconstructed phase space, which is topologically equivalent to the dynamical evolution of the system, is applied to establish the prediction model. Moreover, an integer constrained particle swarm optimization algorithm is employed to select the optimal time delay, which is the parameter of our system. Simulation results for applications on the Lorenz system, stock market index, and influenza data indicate that our proposed method can produce efficient and reliable predictions.

关键词： prediction system phase space reconstruction topological equivalence dynamical feed-forward neural network integer constrained particle swarm optimization algorithm

FURTHER RESULTS ON LIMITATIONS OF SAMPLED-DATA FEEDBACK

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Journal of Systems Science & Complexity 2014年第5期27卷 817-835页

作者： ren jingli CHENG Zhibo GUO Lei School of Mathematics and Statistics Zhengzhou University School of Mathematics and Information Science Henan Polytechnic University Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of Sciences

To control continuous-time uncertain dynamical systems with sampled data-feedback is prevalent today,but the sampling rate is usually not allowed to be arbitrarily fast due to various physical and/or computational *** this paper,the authors examine the limitations of sampled-data feedback control for a class of uncertain systems in continuous-time,with sampling rate not necessary fast enough and with the unknown system structure confined to a set of functions with both linear and nonlinear *** limitations of the sampled-data feedback control for the uncertain systems are established quantitatively,which extends the existing related results in the literature.

关键词： Sampled-data feedback stabilization uncertain nonlinear systems

Dynamics of exact soliton solutions to the coupled nonlinear system using reliable analytical mathematical approaches

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Communications in Theoretical Physics 2021年第8期73卷 50-66页

作者： Muhammad Bilal Usman Younas jingli ren Henan Academy of Big Data/School of Mathematics and Statistics Zhengzhou UniversityZhengzhou 450001China

Nonlinear Schrödinger-type equations are important models that have emerged from a wide variety of fields,such as fluids,nonlinear optics,the theory of deep-water waves,plasma physics,and so *** this work,we obtain different soliton solutions to coupled nonlinear Schrödinger-type(CNLST)equations by applying three integration tools known as the(G’/G^(2))-expansion function method,the modified direct algebraic method(MDAM),and the generalized Kudryashov *** soliton and other solutions obtained by these methods can be categorized as single(dark,singular),complex,and combined soliton solutions,as well as hyperbolic,plane wave,and trigonometric solutions with arbitrary *** spectrum of the solitons is enumerated along with their existence ***,2D,3D,and contour profiles of the reported results are also plotted by choosing suitable values of the parameters involved,which makes it easier for researchers to comprehend the physical phenomena of the governing *** solutions acquired demonstrate that the proposed techniques are efficient,valuable,and straightforward when constructing new solutions for various types of nonlinear partial differential equation that have important applications in applied sciences and *** the reported solutions are verified by substitution back into the original equation through the software package Mathematica.

关键词： soliton solutions exact solutions CNLST equations (G’/G^(2))-expansion function method MDAM generalized Kudryashov method

Phase prediction for high-entropy alloys using generative adversarial network and active learning based on small datasets

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Science China(Technological Sciences) 2023年第12期66卷 3615-3627页

作者： CHEN Cun ZHOU HengRu LONG WeiMin WANG Gang ren jingli Henan Academy of Big Data School of Mathematics and StatisticsZhengzhou UniversityZhengzhou 450001China State Key Laboratory of Advanced Brazing Filler Metals and Technology Zhengzhou Research Institute of Mechanical EngineeringZhengzhou 450001China Institute of Materials Shanghai UniversityShanghai 200444China

In this paper,a new machine learning(ML)model combining conditional generative adversarial networks(CGANs)and active learning(AL)is proposed to predict the body-centered cubic(BCC)phase,face-centered cubic(FCC)phase,and BCC+FCC phase of high-entropy alloys(HEAs).Considering the lack of data,CGANs are introduced for data augmentation,and AL can achieve high prediction accuracy under a small sample size owing to its special sample selection ***,we propose an ML framework combining CGAN and AL to predict the phase of *** arithmetic optimization algorithm(AOA)is introduced to improve the artificial neural network(ANN).AOA can overcome the problem of falling into the locally optimal solution for the ANN and reduce the number of training *** AOA-optimized ANN model trained by the AL sample selection strategy achieved high prediction accuracy on the test *** improve the performance and interpretability of the model,domain knowledge is incorporated into the feature ***,considering that the proposed method can alleviate the problem caused by the shortage of experimental data,it can be applied to predictions based on small datasets in other fields.

关键词： high-entropy alloys phase prediction machine learning conditional generative adversarial networks active learning

Correlation between jerky flow and jerky dynamics in a nanoscratch on a metallic glass film

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Science China(Physics,Mechanics & Astronomy) 2020年第7期63卷 89-92页

作者： LiPing Yu DongXue Han jingli ren XiaoXiang Guo ShaoKang Guan Gang Wang Henan Academy of Big Data Zhengzhou University.Zhengzhou 450052China College of Science Henan University of TechnologyZhengzhou 450001China Laboratory for Microstructures Institute of MaterialsShanghai UniversityShanghai 200444China School of Materials Science and Engineering Zhengzhou UniversityZhengzhou 450001China

Chaos has been well understood in dynamic system, however, how the chaotic behavior occur in jerky flow in material, is still not clear, and is lack of specific chaotic attractor. Here the jerky evolution of lateral force and the stair-like fluctuation of lateral displacement are observed for Ni62 Nb38(at.%) metallic glass film during nanoscratch process. This jerky flow is investigated by using the largest Lyapunov exponent, Kolmogorov entropy and fractal dimension, and chaotic behavior of lateral force-time and normal displacement-lateral displacement sequences is verified. In addition to time series analysis, it is found that jerk equation can be used to describe the jerky flow of the metallic-glass film during nanoscratch. More importantly, unambiguous chaotic attractor is presented by jerky dynamics using "jerk"-singularities, namely the total change rate of lateral force relative to scratch time. These reveal an inner connection between jerky flow and jerky dynamics in nanoscratch of a metallic-glass film.

关键词： metallic-glass film jerky flow jerky dynamics chaos

Extracting governing system for the plastic deformation of metallic glasses using machine learning

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Science China(Physics,Mechanics & Astronomy) 2022年第6期65卷 76-87页

作者： Liping Yu Xiaoxiang Guo Gang Wang Baoan Sun Dongxue Han Cun Chen jingli ren Weihua Wang College of Science Henan University of TechnologyZhengzhou 450001China Henan Academy of Big Data Zhengzhou UniversityZhengzhou 450052China Institute of Materials Shanghai UniversityShanghai 200444China Institute of Physics Chinese Academy of SciencesBeijing 100190China

This paper shows hidden information from the plastic deformation of metallic glasses using machine ***_(62)Nb_(38)(at.%)metallic glass(MG)film and Zr_(64.13)Cu_(15.75)Al_(10)Ni_(10.12)(at.%)BMG,as two model materials,are considered for nano-scratching and compression experiment,*** interconnectedness among variables is probed using correlation *** evolvement mechanism and governing system of plastic deformation are explored by combining dynamical neural networks and sparse *** governing system has the same basis function for different experiments,and the coefficient error is≤0.14%under repeated experiments,revealing the intrinsic quality in metallic ***,the governing system is conducted based on the preceding result to predict the deformation *** shows that the prediction agrees well with the real value for the deformation process.

关键词： metallic glasses sparse identification dynamical neural networks correlation analysis

Serration and shear avalanches in a ZrCu based bulk metallic glass composite in different loading methods

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Journal of Materials Science & Technology 2019年第9期35卷 2079-2085页

作者： Haichao Sun Zhiliang Ning jingli ren Weizhong Liang Yongjiang Huang Jianfei Sun Xiang Xue Gang Wang School of Materials Science and Engineering Harbin Institute of TechnologyHarbin 150001China School of Mathematics and Statistics Zhengzhou UniversityZhengzhou 450001China School of Materials Science and Engineering Heilongjiang University of Science and TechnologyHarbin 150027China Laboratory for Microstructures Institute of MaterialsShanghai UniversityShanghai 200444China

In the current research, serrated flow is investigated under tensile and compressive loading in a ZrCubased bulk metallic glass composite (BMGC) that is well known for its plastic deformability, which is higher than that of metallic glasses. Statistical analysis on serrations shows a complex, scale free process, in which shear bands are highly correlated. The distribution of the elastic-energy density stored in each serration event follows a power-law relationship, showing a randomly generated serrated event under both tension and compression tests. The plastic deformation in the temporal space is explored by a timeseries analysis, which is consistent with the trajectory convergent evolution in critical dynamic behavior even in the low strain rate regime in both tests. The results demonstrate that the secondary phase in the BMGC can stabilize the shear band extension and facilitate the critical behavior in the low strain rate regime. This study provides a strong evidence of serrated flow phenomenon in BMGC under tension test, and offers a deep understanding of the correlation between serrations and shear banding in temporal space.

关键词： Metallic glass Bulk metallic glass composites Serrated flow Shear avalanches Statistical analysis Critical behavior