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The semi-analytical wall boundary conditions present a mathematically rigorous framework to prescribe the influence of solid walls in SPH for fluid flows. In this paper they are investigated with respect to the skew-adjoint property which…

Fluid Dynamics · Physics 2015-06-15 Arno Mayrhofer , Benedict D. Rogers , Damien Violeau , Martin Ferrand

Smart devices, storage and other distributed technologies have the potential to greatly improve the utilisation of network infrastructure and renewable generation. Decentralised control of these technologies overcomes many scalability and…

Optimization and Control · Mathematics 2024-10-30 Paul Scott , Sylvie Thiébaux

Differentiable programming, enabled by automatic differentiation (AD), provides a robust framework for gradient-based optimization in computational plasma physics. While optimization is often only used towards design, we demonstrate that it…

Plasma Physics · Physics 2026-03-13 A. S. Joglekar , A. G. R. Thomas , A. L. Milder , K. G. Miller , J. P. Palastro , D. H. Froula

We investigate the reconstruction of a turbulent flow field in the atmospheric boundary layer from a time series of lidar measurements, using Large-Eddy Simulations (LES) and a 4D-Var data assimilation algorithm. This leads to an…

Fluid Dynamics · Physics 2020-11-17 Pieter Bauweraerts , Johan Meyers

Two-dimensional (2D) flows are efficiently controlled with spanwise waviness, i.e. spanwise-periodic (SP) wall blowing/suction/deformation. We tackle the global linear stability of 2D flows subject to small-amplitude 3D SP control. Building…

Fluid Dynamics · Physics 2019-10-04 E. Boujo , A. Fani , F. Gallaire

The high dimensionality and complex dynamics of turbulent flows remain an obstacle to the discovery and implementation of control strategies. Deep reinforcement learning (RL) is a promising avenue for overcoming these obstacles, but…

Fluid Dynamics · Physics 2023-01-31 Alec J. Linot , Kevin Zeng , Michael D. Graham

Two models based on convolutional neural networks are trained to predict the two-dimensional velocity-fluctuation fields at different wall-normal locations in a turbulent open channel flow, using the wall-shear-stress components and the…

Fluid Dynamics · Physics 2020-06-23 L. Guastoni , A. Güemes , A. Ianiro , S. Discetti , P. Schlatter , H. Azizpour , R. Vinuesa

A Pontryagin maximum principle for an optimal control problem in three dimensional linearized compressible viscous flows is established using the Ekeland variational principle. The controls are distributed over a bounded domain, while the…

Optimization and Control · Mathematics 2019-10-25 Stefan Doboszczak , Manil T. Mohan , Sivaguru S. Sritharan

High penetration of renewable energy sources and the increasing share of stochastic loads require the explicit representation of uncertainty in tools such as the optimal power flow (OPF). Current approaches follow either a linearized…

Systems and Control · Computer Science 2020-07-24 Andreas Venzke , Lejla Halilbasic , Uros Markovic , Gabriela Hug , Spyros Chatzivasileiadis

Turbulent flow control has numerous applications and building reduced-order models (ROMs) of the flow and the associated feedback control laws is extremely challenging. Despite the complexity of building data-driven ROMs for turbulence, the…

Fluid Dynamics · Physics 2021-07-19 Arvind T. Mohan , Kaushik Nagarajan , Daniel Livescu

Computational fluid dynamics (CFD) is a useful tool for prediction of turbulence in aerodynamic and biomedical applications. The choice of appropriate turbulence models is key to reaching accurate predictions. The present investigation…

Fluid Dynamics · Physics 2018-03-13 Fardin Khalili , Peshala P. T. Gamage , Hansen A. Mansy

In this study, we utilize the emerging Physics Informed Neural Networks (PINNs) approach for the first time to predict the flow field of a compressor cascade. Different from conventional training methods, a new adaptive learning strategy…

Machine Learning · Computer Science 2024-05-08 Zhihui Li , Francesco Montomoli , Sanjiv Sharma

Direct numerical simulations (DNSs) of turbulent pipe flow subjected to streamwise-varying wall rotation are performed. This control method is able to achieve drag reduction and even relaminarize the flow under certain control parameters at…

Fluid Dynamics · Physics 2022-11-30 Xu Liu , Hongbo Zhu , Yan Bao , Dai Zhou , Zhaolong Han

We integrate a discrete vortex method with complex network analysis to strategize dynamic stall mitigation over a pitching airfoil with active flow control. The objective is to inform actuator placement and timing to introduce control…

Fluid Dynamics · Physics 2026-01-14 Het D. Patel , Yi Tsung Lee , Ashok Gopalarathnam , Chi-An Yeh

Transition to turbulence dramatically alters the properties of fluid flows. In most canonical shear flows, the laminar flow is linearly stable and a finite-amplitude perturbation is necessary to trigger transition. Controlling transition to…

Fluid Dynamics · Physics 2020-05-20 Anton Pershin , Cedric Beaume , Steven M. Tobias

High-pressure transcritical fluid flows are central to modern energy and propulsion systems. A key challenge arises in confined configurations, where optimizing performance requires a detailed understanding of the coupled hydrodynamic and…

Fluid Dynamics · Physics 2026-01-21 M. Bernades , J. M. O. Massey , B. J. McKeon , L. Jofre

The interaction of a suspension of rotating colloids with a periodically patterned structure is here investigated by means of continuum theoretical predictions and hydrodynamic simulations. Close to the obstacle surface, rotors circulate…

Statistical Mechanics · Physics 2025-08-22 Joscha Mecke , Yongxiang Gao , Marisol Ripoll

This work presents a mathematical model for the optimal control of thin-film flows over a flexible topography influenced by an external force. Our thin-film model allows for the rupture of films as well as the coalescence of bubbles. The…

Optimization and Control · Mathematics 2025-06-19 S. Alrashidy , A. Kalogirou , D. Kalise , K. G. van der Zee

Flow matching (FM) has shown promising results in data-driven planning. However, it inherently lacks formal guarantees for ensuring state and action constraints, whose satisfaction is a fundamental and crucial requirement for the safety and…

Machine Learning · Computer Science 2025-12-02 Tzu-Yuan Huang , Armin Lederer , Dai-Jie Wu , Xiaobing Dai , Sihua Zhang , Stefan Sosnowski , Shao-Hua Sun , Sandra Hirche

Dynamic induction control is a wind farm flow control strategy that utilises wind turbine thrust variations to accelerate breakdown of the aerodynamic wake and improve downstream turbine performance. However, when floating wind turbines are…

Optimization and Control · Mathematics 2023-03-28 Maarten J. van den Broek , Daniel van den Berg , Benjamin Sanderse , Jan-Willem van Wingerden
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