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Rapidly convergent infinite state representation for fractional calculus and applications to fractional rheology

Author

Listed:
  • Liu, T.M.
  • Chen, Y.M.
  • Liu, J.K.
  • Liu, Q.X.

Abstract

Fractional calculus, as a core tool for modeling complex systems, plays a critical role in numerous fields. However, its prominent nonlocal characteristics introduce a series of challenging problems for numerical analysis. The infinite-state approach has demonstrated great potential in the fast computation of fractional calculus. Nevertheless, the weak singularity and weak algebraic decay properties of infinite-state representations lead to generally low convergence orders of the infinite-state approach, which even fail completely in some cases. To address these issues, this paper proposes two strategies: I) Innovatively developing a local hybrid interpolation quadrature method to achieve high-precision computation of weakly singular integrals; II) Adopting an interval segmentation strategy to overcome the weak algebraic decay of infinite-state representations and realize their exponential decay rate. By combining these strategies, a high-precision infinite-state approach with linearly increasing computational complexity O(n)) is intended to be constructed. Moreover, the proposed algorithm fundamentally eliminates the need for solving high-dimensional ordinary differential equation systems and circumvents stiff problem challenges that plague conventional infinite-state approach. The convergence order of the method is rigorously established through theoretical analysis and subsequently validated via numerical experiments on benchmark problems. In addition, the method is applied to the fast solution of fractional viscoelastic constitutive equations, achieving high-precision fitting to experimental data.

Suggested Citation

  • Liu, T.M. & Chen, Y.M. & Liu, J.K. & Liu, Q.X., 2025. "Rapidly convergent infinite state representation for fractional calculus and applications to fractional rheology," Chaos, Solitons & Fractals, Elsevier, vol. 200(P3).
  • Handle: RePEc:eee:chsofr:v:200:y:2025:i:p3:s0960077925011233
    DOI: 10.1016/j.chaos.2025.117110
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    References listed on IDEAS

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    1. Wang, Lei & Chen, Yiming & Cheng, Gang & Barrière, Thierry, 2020. "Numerical analysis of fractional partial differential equations applied to polymeric visco-elastic Euler-Bernoulli beam under quasi-static loads," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    2. Kar, Silajit & Maiti, Dilip K. & Maiti, Atasi Patra, 2024. "Impacts of non-locality and memory kernel of fractional derivative, awareness and treatment strategies on HIV/AIDS prevalence," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    3. Hou, Jie & Ma, Zhiying & Ying, Shihui & Li, Ying, 2024. "HNS: An efficient hermite neural solver for solving time-fractional partial differential equations," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    4. Mahmoudi, Z. & Khalsaraei, M. Mehdizadeh & Sahlan, M. Nosrati & Shokri, A., 2025. "Laguerre wavelets spectral method for solving a class of fractional order PDEs arising in viscoelastic column modeling," Chaos, Solitons & Fractals, Elsevier, vol. 192(C).
    5. Yuan, Xiaolin & Yu, Yongguang & Ren, Guojian, 2025. "Random attractors for fractional stochastic reaction–diffusion systems with fractional Brownian motion," Chaos, Solitons & Fractals, Elsevier, vol. 190(C).
    6. Kumar, Devendra & Dubey, Ved Prakash & Dubey, Sarvesh & Singh, Jagdev & Alshehri, Ahmed Mohammed, 2023. "Computational analysis of local fractional partial differential equations in realm of fractal calculus," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
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