FDA Express Vol. 37, No. 1, Oct 30, 2020
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Institute of Soft Matter Mechanics, Hohai
University
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fdaexpress@hhu.edu.com
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◆ Latest SCI Journal Papers on FDA
◆ Call for Papers
Collective Behavior in Nonlinear Dynamical Networks
Modeling and Forecasting of Rare and Extreme Events
◆ Books
◆ Journals
Mechanical Systems and Signal Processing
Communications in Nonlinear Science and Numerical Simulation
◆ Paper Highlight
An efficient and accurate method for modeling nonlinear fractional viscoelastic biomaterials
◆ Websites of Interest
Fractal Derivative and Operators and Their Applications
Fractional Calculus & Applied Analysis
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Latest SCI Journal Papers on FDA
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By: Nadarajah, K.; Martin, Gael M.; Poskitt, D. S.
JOURNAL OF STATISTICAL PLANNING AND INFERENCE Volume: 211 Pages: 41-79 Published: MAR 2021
COVID-19 pandemic and chaos theory
Correspondence between some metabelian varieties and left nilpotent varieties
Races with imaginary parts of zeros of the Riemann zeta function and Dirichlet L-functions
Boundary value methods for Caputo fractional differential equations
Mixed finite element methods for fractional Navier-Stokes equations
Liouville property of fractional Lane-Emden equation in general unbounded domain
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Call for Papers
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Collective Behavior in Nonlinear Dynamical Networks
(special issue in Scientia Iranica)
Collective behaviors of dynamical networks are on the focus of intense research in various fields of science. Dynamical networks can be considered as populations of locally interacting nonlinear systems in which complex spatiotemporal patterns can emerge. Forinstance,one of such emerging patterns is the synchronization,which refers to the strongest form of network cooperative dynamics. Each individual in the network tends to share the common rhythms and the same dynamical behavior in the synchronization state. Emerging the traveling and propagating waves, especially spiral waves, is another example of fascinating collective behaviors of dynamical networks.The other important exampleis associated with coexisting of both incoherent and coherent states in networks, simultaneously,which is called chimera state.
Various studies in the literature have investigated the emergence of collective behavior in dynamical networks numerically and analytically. Generally, they have pointed out three main factors on the emergence of collective behaviors: the dynamics of individual system in each node, the coupling strength, and the topology of the network.There are various types of complex nonlinear systems that can be located in each node of networks, such as systems expressed by ordinary differential or difference equations, fractional-order systems, and statistical systems. Finding the proper coupling strength as an important factor which regulates the interactions in dynamical networks is another important point in this field of research.The structure of a network canalso affect the functions of emerging the collective behaviors. The dynamical networks can be identical or non-identical, weighted or unweighted, directed or undirected, time- varying or fixed in various types of topologies such as regular, random, scale-free, small-world, etc.
Potential topics of this special issue include (but not limited to):
• Models of dynamical networksImportant Dates:
Manuscript Due: January 15, 2021
First Round of Reviews: February 15, 2021
Publication Date: June, 2021
Notes:
Please note that SCIENTIA IRANICA does not require publication charges.
Along with the manuscript submission, the corresponding author has to send a cover letter specifying that the submission is for Special Issue on “Collective Behavior in Nonlinear Dynamical Networks.”
The direct link for the submission of papers is http://scientiairanica.sharif.edu/contacts?_action=loginForm.
Modeling and Forecasting of Rare and Extreme Events
( Topical collection in Entropy )
Rare or extreme events designate phenomena that occur with low frequency, but that have huge and dramatic impact. These types of events encompasses natural phenomena, problems produced by the human activities, or even a combination of both. The case of natural events is portraited by catastrophes such as earthquakes, tsunamis, tornadoes, volcanos, floods, asteroid impacts, solar flares. For the events produced by the human species, also called anthropogenic hazards, we have bloody conflicts, such as warfare and terrorism, large industrial accidents, financial and commodity market crashes, economic crisis, Internet security outbreaks, energy or communications blackouts, and others. Regarding calamities involving both natural and anthropogenic factors we can mention global warming, forest fires, migrations, epidemic diseases outbreaks, and many others.
These phenomena often occur in complex systems, characterized by scale-invariance, self-similarity, fractality and non-locality, with power law behavior and alpha–stable distributions characterized by heavy-tails, giving non-negligible probability to extreme events. We find scattered in the literature names such as "dragon kings", "black swans", and others, to mention special cases of apparently unpredictable catastrophic events.
The Coronavirus disease 2019 (COVID-19) outbreak, spreading across the world with dramatic consequences for social, healthcare and economic systems, is an example of an extreme event.
This Collection on Modeling and Forecasting of Rare and Extreme Events focuses on original and new research results in mathematical, computational, algorithmic, or data-driven studies.
Manuscripts on new methodologies, advanced forms of system modeling and event forecasting, nonlinearity and novel perspectives for information processing are solicited. We welcome submissions addressing such issues, as well as those on more specific topics, illustrating the broad impact of entropy- and information-based techniques on the understanding of these type of phenomena.
Given the present state of COVID19 emergency in the world, submissions on the topic are welcome.
Keywords:
• entropyManuscript Submission Information:
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the collection website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
All details on this online conference are now available at: https://www.mdpi.com/journal/entropy/special_issues/Forecast.
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Books
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(Authors:Elina Shishkina Sergei Sitnik)
Details:https://doi.org/10.1016/C2019-0-00708-X
Book Description：
Transmutations, Singular and Fractional Differential Equations with Applications to Mathematical Physics connects difficult problems with similar more simple ones. The book's strategy works for differential and integral equations and systems and for many theoretical and applied problems in mathematics, mathematical physics, probability and statistics, applied computer science and numerical methods. In addition to being exposed to recent advances, readers learn to use transmutation methods not only as practical tools, but also as vehicles that deliver theoretical insights.
Readership:
Researchers, students working in the area of partial differential equations. Advanced undergraduate students, postgraduate students, researchers interested in new methods in differential equations and mathematical physics.
Contents:
- Introduction
- Acknowledgement and thanks
- Basic definitions and propositions
- Basics of fractional calculus and fractional order differential equations
- Essential of the transmutations
- Weighted generalized functions generated by quadratic form
- Buschman-Erdelyi integral and transmutation operators
- Integral transforms compositions method for transmutations
- Differential equations with Bessel operator
- Applications of transmutations to the different problems
- Fractional powers of Bessel operators
- B-potentials theory
- Fractional differential equations with singular coefficients
- Conclusion
- References
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Journals
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Mechanical Systems and Signal Processing
(Selected)
Xuan Bao Nguyen, Toshihiko Komatsuzaki, Nong Zhang
Eigenvalue and eigenvector derivatives of fractional vibration systems
R. M. Lin, T. Y. Ng
R. M. Lin, T. Y. Ng
Weidi Yin, Yiheng Wei, Tianyu Liu, Yong Wang
Stabilization in finite time for fractional-order hyperchaotic electromechanical gyrostat systems
Zhibo Wang, Huaiqin Wu
Xuefang Xu, Zijian Qiao, Yaguo Lei
Zhiwei Zhu, Suet To, Yangmin Li, Wu-LeZhu, Leixiang Bian
A fractional-order accumulative regularization filter for force reconstruction
Jiang Wensong, Wang Zhongyu, Lv Jing
Yousef Farid, Vahid Johari Majd, Abbas Ehsani-Seresht
Predicting remaining useful life based on a generalized degradation with fractional Brownian motion
Hanwen Zhang, Donghua Zhou, Maoyin Chen, Xiaopeng Xi
An efficient approach for high-dimensional structural reliability analysis
Jun Xu, Shengyang Zhu
Jun Xu, Fan Kong
Wanxin He, Peng Hao, Gang Li
Communications in Nonlinear Science and Numerical Simulation
(Selected)
Xiao Zhang, Bo Yang, Chaozhen Wei, Maokang Luo
Uncertain inverse problem for fractional dynamical systems using perturbed collage theorem
Soheil Salahshour, Ali Ahmadian, Bruno A. Pansera, Massimiliano Ferrara
Asymmetric feedback enhances rhythmicity in damaged systems of coupled fractional oscillators
Yuanyuan Liu, Zhongkui Sun, Xiaoli Yang, Wei Xu
Libo Feng, Ian Turner, Patrick Perré, Kevin Burrage
Ben-Hai B. P. Moghaddam, Z. S. Mostaghim, A.A. Pantelous, J. A. Tenreiro Machado
B. Ducharne, P. Tsafack, Y.A. Tene Deffo, B. Zhang, G. Sebald
Müntz pseudo–spectral method: Theory and numerical experiments
Hassan Khosravian-Arab, M. R. Eslahchi
Monitoring Lévy-process crossovers
Maike A. F. dos Santos, Fernando D. Nobre, Evaldo M. F. Curado
Complex-order particle swarm optimization
J. A. Tenreiro Machado, Seyed Mehdi Abedi Pahnehkolaei, Alireza Alfi
Zejia Lin, You Wu, Huixin Qiu, Xingming Fu, Kaihui Chen, Dongmei Deng
Lattice Boltzmann method for fractional Cahn-Hilliard equation
Hong Liang, Chunhua Zhang, Rui Du, Yikun Wei
S. S. Ezz-Eldien, E. H. Doha, Y. Wang, W. Cai
On initial conditions for fractional delay differential equations
Roberto Garrappa, Eva Kaslik
A physical interpretation of fractional-order-derivatives in a jerk system: Electronic approach
J. L. Echenausía-Monroy, H. E. Gilardi-Velázquez, R. Jaimes-Reátegui, V. Aboites, G. Huerta-Cuellar
Optimal control of a fractional order model for granular SEIR epidemic with uncertainty
Nguyen Phuong Dong, Hoang Viet Long, Alireza Khastan
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Paper
Highlight
An efficient and accurate method for modeling nonlinear fractional viscoelastic biomaterials
Will Zhang, Adela Capilnasiu, Gerhard Sommer, Gerhard A. Holzapfel, David A. Nordsletten
Publication information: Computer Methods in Applied Mechanics and Engineering, Volume 362, 15 April 2020, 112834
https://doi.org/10.1016/j.cma.2020.112834
Abstract
Computational biomechanics plays an important role in biomedical engineering: using modeling to understand pathophysiology, treatment and device design. While experimental evidence indicates that the mechanical response of most tissues is viscoelastic, current biomechanical models in the computational community often assume hyperelastic material models. Fractional viscoelastic constitutive models have been successfully used in literature to capture viscoelastic material response; however, the translation of these models into computational platforms remains limited. Many experimentally derived viscoelastic constitutive models are not suitable for three-dimensional simulations. Furthermore, the use of fractional derivatives can be computationally prohibitive, with a number of current numerical approximations having a computational cost that is O(NT2)
and a storage cost that is O(NT)（NTdenotes the number of time steps). In this paper, we present a novel numerical approximation to the Caputo derivative which exploits a recurrence relation similar to those used to discretize classic temporal derivatives, giving a computational cost that is O(NT)
and a storage cost that is fixed over time. The approximation is optimized for numerical applications, and an error estimate is presented to demonstrate the efficacy of the method. The method, integrated into a finite element solid mechanics framework, is shown to be unconditionally stable in the linear viscoelastic case. It was then integrated into a computational biomechanical framework, with several numerical examples verifying the accuracy and computational efficiency of the method, including in an analytic test, in an analytic fractional differential equation, as well as in a computational biomechanical model problem.
Highlights
•A new Prony-series based approximation to the Caputo derivative is introduced.
•Error estimates are derived and compared with other methods in literature.
•Integrated into a nonlinear FE approach for fractional viscoelastic mechanics.
•Stability estimates are derived in the linear elastic limit.
•Accuracy, convergence and performance are evaluated in practical examples.
•Evaluated using analytic tests, fractional ODE, and 3-D mechanics of liver tissues.
Keywords
Caputo derivative; Viscoelasticity; Solid mechanics; Computational biomechanics; Large deformation
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Lin Qiu, Chao Hu, Qing-Hua Qin
Publication information: Applied Mathematics Letters,June 2020, 109:106554
https://doi.org/10.1016/j.aml.2020.106554
Abstract
A novel numerical technique is developed in this paper to accurately and efficiently resolve the inverse source problem of the nonlinear time-fractional wave equation. Based on all given conditions, the homogenization function of nonlinear time-fractional wave equation can be derived, and then a family of homogenization functions is obtained. Furthermore, a numerical model is established by the superposition of homogenization functions and used for tackling inverse source problem. The proposed method is free of mesh generation, numerical integration, iteration, regularization and fundamental solutions, and it is easy to program and implement on the existing software. Three numerical experiments demonstrate the accuracy and convergence of the proposed strategy for the inverse source problem even with high noise imposed on the boundary conditions.
Keywords:
Time-fractional wave equation; Inverse source problem; Homogenization function; Superposition method
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The End of This Issue
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