J. Qiu

h-index5
2papers

2 Papers

NAJan 17, 2017
Implicit-Explicit Integral Deferred Correction Methods for Stiff Problems

S. Boscarino, J. Qiu, G. Russo

The main goal of this paper is to investigate the order reduction phenomenon that appears in the integral deferred correction (InDC) methods based on implicit-explicit (IMEX) Runge-Kutta (R-K) schemes when applied to a class of stiff problems characterized by a small positive parameter $\varepsilon$, called singular perturbation problems (SPPs). In particular, an error analysis is presented for these implicit-explicit InDC (InDC-IMEX) methods when applied to SPPs. In our error estimate, we expand the global error in powers of $\varepsilon$ and show that its coefficients are global errors of the corresponding method applied to a sequence of differential algebraic systems. A study of these errors in the expansion yields error bounds and it reveals the phenomenon of order reduction. In our analysis we assume uniform quadrature nodes excluding the left-most point in the InDC method and the globally stiffly accurate property for the IMEX R-K scheme. Numerical results for the Van der Pol equation and PDE applications are presented to illustrate our theoretical findings.

FLU-DYNOct 10, 2025
Smart navigation of a gravity-driven glider with adjustable centre-of-mass

X. Jiang, J. Qiu, K. Gustavsson et al.

Artificial gliders are designed to disperse as they settle through a fluid, requiring precise navigation to reach target locations. We show that a compact glider settling in a viscous fluid can navigate by dynamically adjusting its centre-of-mass. Using fully resolved direct numerical simulations (DNS) and reinforcement learning, we find two optimal navigation strategies that allow the glider to reach its target location accurately. These strategies depend sensitively on how the glider interacts with the surrounding fluid. The nature of this interaction changes as the particle Reynolds number Re$_p$ changes. Our results explain how the optimal strategy depends on Re$_p$. At large Re$_p$, the glider learns to tumble rapidly by moving its centre-of-mass as its orientation changes. This generates a large horizontal inertial lift force, which allows the glider to travel far. At small Re$_p$, by contrast, high viscosity hinders tumbling. In this case, the glider learns to adjust its centre-of-mass so that it settles with a steady, inclined orientation that results in a horizontal viscous force. The horizontal range is much smaller than for large Re$_p$, because this viscous force is much smaller than the inertial lift force at large Re$_p$. *These authors contributed equally.