Open Access Published by De Gruyter

Volume 12 Issue 1

January 2023

Issue of Nonlinear Engineering

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Contents
Journal Overview

Mathematical models for infectious diseases can help researchers, public health officials, and policymakers to predict the course of an outbreak. We formulate an epidemic model for the transmission dynamics of Zika infection with carriers to understand the intricate progression route of the infection. In our study, we focused on the visualization of the transmission patterns of the Zika with asymptomatic carriers, using fractional calculus. For the validity of the model, we have shown that the solutions of the system are positive and bounded. Moreover, we conduct a qualitative analysis and examine the dynamical behavior of Zika dynamics. The existence and uniqueness of the solution of the system have been proved through analytic skills. We establish the necessary conditions to ensure the stability of the recommended system based on the Ulam–Hyers stability concept (UHS). Our research emphasizes the most critical factors, specifically the mosquito biting rate and the existence of asymptomatic carriers, in increasing the complexity of virus control efforts. Furthermore, we predict that the asymptomatic fraction has the ability to spread the infection to non-infected regions. Furthermore, treatment due to medication, the fractional parameter or memory index, and vaccination can serve as effective control measures in combating this viral infection.

Rapid Communication

Open Access April 3, 2023

Influence of joint flexibility on buckling analysis of free–free beams

D. V. Ramana Reddy, K. T. Balaram Padal, Jagadish Babu Gunda

Article number: 20220274

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Abstract

In this work, an application of two noded beam finite element methodology, which is demonstrated in the previous research work for vibration analysis of beam with a flexible joint problem, has been further extended here to investigate the buckling behaviour of free–free beam subjected to an in-plane compressive load. Joint is modelled as rotational spring, where the rotational spring stiffness governs the behaviour of the flexible joint. Variation of first five non-dimensional buckling loads of free–free beam with reference to the joint location as well as joint stiffness parameters are briefly presented. It is understood that looseness of the joint can significantly influence the buckling behaviour of free–free beam and plays an important role in accurately determining the buckling behaviour of jointed beams subjected to an in-plane compressive loads.

The typical power transformer diagnosis approach is imprecise and unstable. A support vector machine classification algorithm is proposed, by designing an algorithm program that can improve the accuracy and speed of energy transformer diagnosis, the vibration signals of the surface twisting in different states are extracted by wavelet packet energy spectrum signal processing method, it is verified that the curve similarity between the vibration simulation model and the measured data is greater than 0.98, proving the simulation model’s validity. The calculation technique of online short circuit inductance is developed from the equivalent transformer model, and the variation error of simulation results is less than 0.05% when compared to the real transformer characteristics. The suggested state diagnostic technique successfully compensates for the drawbacks of the reactance method, which is incapable of detecting and judging the slightly loose or faulty winding. The method’s accuracy and superiority, as well as the practicability of the state diagnosis system, are demonstrated.

Background Computer networks are involved in many fields such as business, education, marketing, government, and tourism in several forms. Technologies related to security protection and improvement of information integrity are used and developed for computer networks intruded on by unauthorized people and help save their confidentiality. Methods To improve the risk identification of computer networks, this manuscript combined a fuzzy hierarchical reasoning model with the scientific inversion parallel programming method to study the risk of computer networks. Moreover, this article defined and analyzed a d -order neighborhood message propagation algorithm. A d -order neighborhood parallel message propagation algorithm using the Gaussian graph model was proposed. Results The risk of the computer network was analyzed using the proposed method resulting in better protection effectiveness. Conclusion The simulations showed that the proposed algorithm could effectively detect risks and improve the security of the computer network.

In this study, an adaptive fuzzy extended state observer (AFESO) for single-input–single-output nonlinear affine systems in the presence of external disturbances and output constraints is proposed. In this regard, an extended state observer (ESO) was employed to estimate the unmeasured states and external disturbances simultaneously. To improve the estimation accuracy, the observer gains were adjusted using an adaptation law. To obtain a more comprehensive mathematical analysis and an accurate model for the ESO and to increase the degree of freedom, a Takagi–Sugeno fuzzy system was employed. The proposed AFESO relaxes the limitations of the ESO and improves the system performance as compared with the classical methods in the presence of time-varying disturbances. Next, a command-filtered backstepping controller is designed based on the barrier Lyapunov function method, which guarantees fast convergence of the tracking error as well as satisfying the output constraints of the system. The stability analysis showed that both the estimation error of the AFESO and the tracking error of the controller are bounded, and the tracking error converges to a small neighborhood of the origin. A simulating example of a flexible-joint manipulator shows the effectiveness of the proposed method as compared with the recently proposed method in the literature.

About this journal

The purpose of the Journal of Nonlinear Engineering is to provide a medium for dissemination of original research results in theoretical, experimental, practical, and applied nonlinear phenomena in engineering. The journal serves as a forum to exchange new ideas and applications of nonlinear problems occurring in automation and control, aeronautical, biological, civil, chemical, communication, electrical, industrial, mechanical, mathematical, physical, and structural systems engineering.

The articles will be considered for publication if they examine nonlinearities in any engineering systems to provide a more realistic mathematical modeling, new design using nonlinearities of the system, stabilizing the system by taking advantage of nonlinearity, discovering the real behavior of the system by including nonlinearity, optimizing the system based on nonlinear interactions, development algorithms to tame nonlinearities and taking advantage of them.

The journal considers submissions of different types of articles."Research Articles" are focused on fundamental theoretical aspects, as well as on significant applications in science, engineering etc.
"Rapid Communications" are intended to present information of exceptional novelty and exciting results of significant interest to the readers. "Review articles" and "Commentaries", which present the existing literature on the specific topic from new perspectives, are welcome as well.

Aims and Scope

Nonlinear engineering

Theoretical, experimental, practical, and applied nonlinear phenomena in engineering

Nonlinear problems occurring in aeronautical, biological, civil, chemical, communication, electrical, industrial, mechanical, mathematical, physical, and structural systems

Nonlinear control of systems and circuits

Engineering systems

Designing and stabilizing behavior of the system

Optimizing and developing the algorithms

Nonlinear electrical and electronic devices

Nonlinear problems in artificial intelligence and signal processing

Computational theory and nonlinear mathematics

Computer science applications in nonlinear engineering

Nonlinear neural networks