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This paper numerically investigates the influence of a fixed downstream control cylinder on the flow-induced vibration of an elastically-supported primary cylinder. These two cylinders are situated in a tandem arrangement with small…

Fluid Dynamics · Physics 2024-05-16 Junlei Wang , Shenfang Li , Daniil Yurchenko , Hongjun Zhu , Chandan Bose

A variational technique is used to derive analytical expressions for the sensitivity of recirculation length to steady forcing in separated flows. Linear sensitivity analysis is applied to the two-dimensional steady flow past a circular…

Fluid Dynamics · Physics 2014-10-03 E. Boujo , F. Gallaire

Mainstream flow matching methods typically focus on learning the local velocity field, which inherently requires multiple integration steps during generation. In contrast, Mean Velocity Flow models establish a relationship between the local…

Machine Learning · Computer Science 2026-03-18 Chenrui Ma

We address unsupervised optical flow estimation for ego-centric motion. We argue that optical flow can be cast as a geometrical warping between two successive video frames and devise a deep architecture to estimate such transformation in…

Computer Vision and Pattern Recognition · Computer Science 2017-10-31 Stefano Alletto , Davide Abati , Simone Calderara , Rita Cucchiara , Luca Rigazio

Based on a continuum theory, we investigate the manipulation of the non-equilibrium behavior of a sheared liquid crystal via closed-loop feedback control. Our goal is to stabilize a specific dynamical state, that is, the stationary…

Soft Condensed Matter · Physics 2015-06-17 David A. Strehober , Eckehard Schöll , Sabine H. L. Klapp

Computational Steering, the combination of a simulation back-end with a visualisation front-end, offers great possibilities to exploit and optimise scenarios in engineering applications. Due to its interactivity, it requires fast grid…

Computational Engineering, Finance, and Science · Computer Science 2018-07-03 Atanas Atanasov , Hans-Joachim Bungartz , Jérôme Frisch , Miriam Mehl , Ralf-Peter Mundani , Ernst Rank , Christoph van Treeck

In this paper, we present a novel control scheme for feedback optimization. That is, we propose a discrete-time controller that can steer the steady state of a physical plant to the solution of a constrained optimization problem without…

Systems and Control · Electrical Eng. & Systems 2020-07-09 Verena Häberle , Adrian Hauswirth , Lukas Ortmann , Saverio Bolognani , Florian Dörfler

Three-dimensional control is considered in the flow past a backward-facing step (BFS). The BFS flow at Reynolds number $Re=500$ (defined with the step height and the maximum inlet velocity) is two-dimensional and linearly stable but…

Fluid Dynamics · Physics 2020-08-12 E. Yim , I. Shukla , F. Gallaire , E. Boujo

This contribution presents experimental study of two-dimensional pedestrian flow with the aim to capture the pedestrian behaviour within the cluster formed in front of the bottleneck. Two experiments of passing through a room with one…

Physics and Society · Physics 2018-01-08 Marek Bukáček , Pavel Hrabák , Milan Krbálek

Advanced feedforward control methods enable mechatronic systems to perform varying motion tasks with extreme accuracy and throughput. The aim of this paper is to develop a data-driven feedforward controller that addresses input…

Systems and Control · Electrical Eng. & Systems 2023-11-30 Jilles van Hulst , Maurice Poot , Dragan Kostić , Kai Wa Yan , Jim Portegies , Tom Oomen

The theory of controlled mechanical systems of [6, 3, 4] is extended to the case of ideal incompressible fluids consisting of charged particles in the presence of an external magnetic field. The resulting control is of feedback type and…

Mathematical Physics · Physics 2021-03-10 Simon Hochgerner

Methods for building a consistent interface between hydrodynamic and simulation modules is presented. These methods account for the backflow across the hydrodynamic/simulation hyper-surface. The algorithms are efficient, relatively…

Nuclear Theory · Physics 2015-06-18 Scott Pratt

In this paper we present a new method for deformable NeRF that can directly use optical flow as supervision. We overcome the major challenge with respect to the computationally inefficiency of enforcing the flow constraints to the backward…

Computer Vision and Pattern Recognition · Computer Science 2023-03-30 Chaoyang Wang , Lachlan Ewen MacDonald , Laszlo A. Jeni , Simon Lucey

The paper presents a feedforward plus feedback controller structure with I and PI controllers for control of an integrating process with dead time. Guidelines for controller gain selection based on time domain specifications of damping…

Systems and Control · Electrical Eng. & Systems 2019-08-27 Sujay D. Kadam

This paper investigates the problem of regulating in real time a linear dynamical system to the solution trajectory of a time-varying constrained convex optimization problem. The proposed feedback controller is based on an adaptation of the…

Optimization and Control · Mathematics 2021-09-13 Gianluca Bianchin , Jorge Cortes , Jorge I. Poveda , Emiliano Dall'Anese

The flow of dry granular materials from silos is of great practical interest in industry and of theoretical import for understanding multiphase dynamics. Recent studies have demonstrated that one way to control the rate of flow from a silo…

Soft Condensed Matter · Physics 2025-08-28 Ryan Kozlowski , Luis A. Pugnaloni

Granular flows due to simultaneous vertical and horizontal excitations of a flat-bottomed cylindrical pan are investigated using event-driven molecular dynamics simulations. In agreement with recent experimental results, we observe a…

Materials Science · Physics 2009-11-11 Oleh Baran , John J. Drozd , Robert J. Martinuzzi , Peter H. Poole

Pouring a specific amount of liquid is a challenging task. In this paper we develop methods for robots to use visual feedback to perform closed-loop control for pouring liquids. We propose both a model-based and a model-free method…

Robotics · Computer Science 2017-02-28 Connor Schenck , Dieter Fox

This research gauges the ability of deep reinforcement learning (DRL) techniques to assist the optimization and control of fluid mechanical systems. It combines a novel, "degenerate" version of the proximal policy optimization (PPO)…

Optimization and Control · Mathematics 2021-05-19 H. Ghraieb , J. Viquerat , A. Larcher , P. Meliga , E. Hachem

We present an estimator-based control design procedure for flow control, using reduced-order models of the governing equations, linearized about a possibly unstable steady state. The reduced models are obtained using an approximate balanced…

Optimization and Control · Mathematics 2015-05-13 Sunil Ahuja , Clarence W. Rowley