Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Alageshan, Jaya Kumar"'
We show that flocking of microswimmers in a turbulent flow can enhance the efficacy of reinforcement-learning-based path-planning of microswimmers in turbulent flows. In particular, we develop a machine-learning strategy that incorporates Vicsek-mode
Externí odkaz:
http://arxiv.org/abs/2411.15902
Neural network assisted electrostatic global gyrokinetic toroidal code using cylindrical coordinates
Gyrokinetic simulation codes are used to understand the microturbulence in the linear and nonlinear regimes of the tokamak and stellarator core. The codes that use flux coordinates to reduce computational complexities introduced by the anisotropy due
Externí odkaz:
http://arxiv.org/abs/2408.12851
We introduce a novel model, comprising self-avoiding surfaces and incorporating edges and tubules, that is designed to characterize the structural morphologies and transitions observed within the endoplasmic reticulum (ER). By employing discretized m
Externí odkaz:
http://arxiv.org/abs/2404.04611
Spiral waves are ubiquitous spatiotemporal patterns that occur in various excitable systems. In cardiac tissue, the formation of these spiral waves is associated with life-threatening arrhythmias, and, therefore, it is important to study the dynamics
Externí odkaz:
http://arxiv.org/abs/2201.09181
Inertial particles advected by a background flow can show complex structures. We consider inertial particles in a 2D Taylor-Green (TG) flow and characterize particle dynamics as a function of the particle's Stokes number using dynamic mode decomposit
Externí odkaz:
http://arxiv.org/abs/2102.05120
Publikováno v:
Phys. Rev. Research 2, 023215 (2020)
Topological point defects on orientationally ordered spheres, and on deformable fluid vesicles have been partly motivated by their potential applications in creating super-atoms with directional bonds through functionalization of the "bald-spots" cre
Externí odkaz:
http://arxiv.org/abs/2003.09222
Publikováno v:
In Communications in Nonlinear Science and Numerical Simulation November 2023 126
Publikováno v:
Phys. Rev. E 101, 043110 (2020)
We develop an adversarial-reinforcement learning scheme for microswimmers in statistically homogeneous and isotropic turbulent fluid flows, in both two (2D) and three dimensions (3D). We show that this scheme allows microswimmers to find non-trivial
Externí odkaz:
http://arxiv.org/abs/1910.01728
Publikováno v:
Phys. Rev. Research 2, 023155 (2020)
Unbroken and broken spiral waves, in partial-differential-equation (PDE) models for cardiac tissue, are the mathematical analogs of life-threatening cardiac arrhythmias, namely, ventricular tachycardia (VT) and ventricular-fibrillation (VF). We devel
Externí odkaz:
http://arxiv.org/abs/1905.06547
Akademický článek
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