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Revolutionizing fluid flow with Lyapunov exponents and PDFP optimizer based Physics Informed Neural Networks for microrotation and peristaltic transport

Author

Listed:
  • Asaad, Muhammad
  • Israr, Muhammad
  • Asif, Muhammad
  • Khalifa, Hamiden Abd El-Wahed
  • Alhunayshil, Norah
  • Ayub, Assad

Abstract

The Lyapunov Exponent shows stability and chaos of dynamical systems. In fluid mechanics, it helps to quantify the sensitivity of fluid flows to initial conditions, making it essential for optimizing complex systems such as peristaltic transport and micro rotational flows. So, this study is important because it solves involved Partial Differential Equations (PDEs) with data efficient computational tool of Physics Informed Neural Network (PINNs).

Suggested Citation

  • Asaad, Muhammad & Israr, Muhammad & Asif, Muhammad & Khalifa, Hamiden Abd El-Wahed & Alhunayshil, Norah & Ayub, Assad, 2026. "Revolutionizing fluid flow with Lyapunov exponents and PDFP optimizer based Physics Informed Neural Networks for microrotation and peristaltic transport," Chaos, Solitons & Fractals, Elsevier, vol. 209(P1).
    • Handle: RePEc:eee:chsofr:v:209:y:2026:i:p1:s0960077926005333
    DOI: 10.1016/j.chaos.2026.118392
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