A Neural Network Time Dependent Hydrodynamic Force Model for Forced Two-Degree-Of-Freedom Sinusoidal Motion of a Circular Cylinder in a Free Stream

2021 ◽  
Author(s):  
Erdem Aktosun ◽  
Nikolaos I. Xiros ◽  
Jason M. Dahl
Keyword(s):  
Neural Network ◽  
Energy Harvesting ◽  
Circular Cylinder ◽  
Free Stream ◽  
Hydrodynamic Force ◽  
Cross Flow ◽  
Time Dependent ◽  
Force Model ◽  
Large Set ◽  
Flow Motion

Abstract A data-driven hydrodynamic force model is developed to model the dynamic forces on an oscillating circular cylinder for flow conditions where Vortex-Induced-Vibrations (VIV) are known to occur. The model is developed for use in future control systems to improve VIV-based energy harvesting. The dynamic model is empirical, utilizing force measurements obtained for a large set of forced motion experiments, spanning a range of parametric values that prescribe the kinematics of the cylinder motion. The model includes the dynamics of a circular cylinder undergoing forced combined in-line and cross-flow motion in a free stream. The experiments were conducted in a fully automated towing tank where parameters of in-line amplitude of motion, cross-flow amplitude of motion, reduced velocity, and phase difference between in-line and cross-flow motion were varied over nearly 10,000 experiments. All experiments were carried out at a constant Reynolds number of 7620. A feed forward neural network is trained using the force database to develop a time dependent model of forces on the cylinder for given kinematic conditions. Selected outputs of the force model are presented, providing a basis for future synthesis in energy harvesting control applications.

Sting-free measurements on a magnetically supported right circular cylinder aligned with the free stream

2008 ◽  
Vol 596 ◽  
pp. 49-72 ◽  
Author(s):  
HIROSHI HIGUCHI ◽  
HIDEO SAWADA ◽  
HIROYUKI KATO
Keyword(s):  
Circular Cylinder ◽  
Shear Layer ◽  
Free Stream ◽  
Aerodynamic Force ◽  
Cross Flow ◽  
Leading Edge ◽  
Magnetic Suspension ◽  
Recirculation Region ◽  
Mean Velocity ◽  
Wide Range

The flow over cylinders of varying fineness ratio (length to diameter) aligned with the free stream was examined using a magnetic suspension and balance system in order to avoid model support interference. The drag coefficient variation of a right circular cylinder was obtained for a wide range of fineness ratios. Particle image velocimetry (PIV) was used to examine the flow field, particularly the behaviour of the leading-edge separation shear layer and its effect on the wake. Reynolds numbers based on the cylinder diameter ranged from 5×104 to 1.1×105, while the major portion of the experiment was conducted at ReD=1.0×105. For moderately large fineness ratio, the shear layer reattaches with subsequent growth of the boundary layer, whereas over shorter cylinders, the shear layer remains detached. Differences in the wake recirculation region and the immediate wake patterns are clarified in terms of both the mean velocity and turbulent flow fields, including longitudinal vortical structures in the cross-flow plane of the wake. The minimum drag corresponded to the fineness ratio for which the separated shear layer reattached at the trailing edge of the cylinder. The base pressure was obtained with a telemetry technique. Pressure fields and aerodynamic force fluctuations are also discussed.

Two-Dimensional Unsteady Viscous Flows

2017 ◽  
Author(s):  
Jian-Jun Shu
Keyword(s):  
Circular Cylinder ◽  
Flow Field ◽  
Hydrodynamic Force ◽  
Viscous Flows ◽  
Reynolds Numbers ◽  
Fundamental Solutions ◽  
Time Dependent ◽  
Two Dimensional ◽  
Low Reynolds Numbers ◽  
Rotational Motions

A number of new closed-form fundamental solutions for the two-dimensional generalized unsteady Oseen and Stokes flows associated with arbitrary time-dependent translational and rotational motions have been developed. As an example of application, the hydrodynamic force acting on a circular cylinder translating in an unsteady flow field at low Reynolds numbers is calculated using the new generalized fundamental solutions.

Flow-Induced Vibration of a Cylinder in the Wake of Another of Smaller Diameter

2014 ◽  
Author(s):  
Md. Mahbub Alam ◽  
An Ran ◽  
Yu Zhou
Keyword(s):  
Circular Cylinder ◽  
Free Stream ◽  
Cross Flow ◽  
Induced Response ◽  
Stream Velocity ◽  
Flow Induced Vibration ◽  
Cylinder Diameter ◽  
Spacing Ratio ◽  
Vortex Shedding Frequency ◽  
Shedding Frequency

This paper presents cross-flow induced response of a both-end-spring-mounted circular cylinder (diameter D) placed in the wake of a rigid circular cylinder of smaller diameter d. The cylinder vibration is constrained to the transverse direction. The cylinder diameter ratio d/D and spacing ratio L/d are varied from 0.2 to 1.0 and 1.0 to 5.5, respectively, where L is the distance between the center of the upstream cylinder to the forward stagnation point of the downstream cylinder. A violent vibration of the cylinder is observed for d/D = 0.2 ∼ 0.8 at L/d = 1.0, for d/D = 0.24 ∼ 0.6 at 1.0 < L/d ≤ 2.5, for d/D = 0.2 ∼ 0.4 at 2.5 < L/d ≤ 3.5, and for d/D = 0.2 at 3.5 < L/d ≤ 5.5, but not for d/D = 1.0. A smaller d/D generates vibration for a longer range of L/d. The violent vibration occurs at a reduced velocity Ur (=U∞/fnD, where U∞ is the free-stream velocity and fn the natural frequency of the cylinder system) beyond the vortex excitation regime (Ur ≥ 8) depending on d/D and L/d. Once the vibration starts to occur, the vibration amplitude increases rapidly with increasing Ur. It is further noted that the flow behind the downstream cylinder is characterized by two predominant frequencies, corresponding to the cylinder vibration frequency and the natural vortex shedding frequency of the cylinder, respectively. While the former persists downstream, the latter vanishes rapidly.

Time Domain Simulation of Vortex-Induced Vibrations Based on Phase-Coupled Oscillator Synchronization

2015 ◽  
Author(s):  
Mats J. Thorsen ◽  
Svein Sævik ◽  
Carl M. Larsen
Keyword(s):  
Vortex Shedding ◽  
Time Domain ◽  
Hydrodynamic Force ◽  
Circular Cross Section ◽  
Cross Flow ◽  
Force Model ◽  
Time Domain Simulation ◽  
Local Flow ◽  
Hydrodynamic Damping ◽  
Vortex Induced Vibrations

Since 2012, there has been ongoing development of a simplified hydrodynamic force model at the Norwegian University of Science and Technology which enables time domain simulation of vortex-induced vibrations (VIV). Time domain simulation has a number of advantages compared to frequency domain. More specifically, having a time domain formulation of the hydrodynamic force which is efficient and reliable, will allow designers to include any relevant non-linear effects in their simulations, thereby increasing the level of realism and confidence in the results. The present model computes the dynamic cross-flow and in-line fluid force on a circular cross-section based on the incoming local flow velocity and the motion of the cylinder section. The most important difference between this and other existing models is the way synchronization between the vortex shedding and cylinder motion is taken into account. In contrast to the traditional VIV prediction tools, the vortex shedding frequency is in this model free to vary within a specified range, and changes according to the instantaneous phase difference between the cylinder velocity and the vortex shedding process itself. Hence, the oscillating lift and drag forces continuously update their frequencies, trying to lock on to the frequency of vibration. Combined with a simple hydrodynamic damping model and a constant added mass, it has previously been shown that highly realistic results can be obtained. In this paper, the theoretical background is reviewed, and the capabilities of the model are tested against new cases. These are: i) High mode VIV of tension-dominated riser in sheared flow, and ii) Low mode VIV of a pipeline with high bending stiffness. Both cross-flow and in-line vibrations are considered, and comparison with experimental observations is given. Based on the results, strengths and weaknesses of the model is discussed, and an outline of future developments is given.

TRANSONIC CROSS FLOW (M∞ = 0.8) OVER A CIRCULAR CYLINDER AT HIGH REYNOLDS NUMBERS

2012 ◽  
Vol 43 (5) ◽  
pp. 589-613
Author(s):  
Vyacheslav Antonovich Bashkin ◽  
Ivan Vladimirovich Egorov ◽  
Ivan Valeryevich Ezhov ◽  
Sergey Vladimirovich Utyuzhnikov
Keyword(s):  
Circular Cylinder ◽  
Cross Flow ◽  
Reynolds Numbers ◽  
High Reynolds Numbers ◽  
High Reynolds

Adsorption Isotherm Predictions for Multiple Molecules in MOFs Using the Same Deep Learning Model

2019 ◽  
Author(s):  
Ryther Anderson ◽  
Achay Biong ◽  
Diego Gómez-Gualdrón
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Molecular Simulation ◽  
Large Scale ◽  
Learning Model ◽  
Operating Conditions ◽  
Small Subset ◽  
Screening Methods ◽  
Large Set ◽  
Metal Organic

<div>Tailoring the structure and chemistry of metal-organic frameworks (MOFs) enables the manipulation of their adsorption properties to suit specific energy and environmental applications. As there are millions of possible MOFs (with tens of thousands already synthesized), molecular simulation, such as grand canonical Monte Carlo (GCMC), has frequently been used to rapidly evaluate the adsorption performance of a large set of MOFs. This allows subsequent experiments to focus only on a small subset of the most promising MOFs. In many instances, however, even molecular simulation becomes prohibitively time consuming, underscoring the need for alternative screening methods, such as machine learning, to precede molecular simulation efforts. In this study, as a proof of concept, we trained a neural network as the first example of a machine learning model capable of predicting full adsorption isotherms of different molecules not included in the training of the model. To achieve this, we trained our neural network only on alchemical species, represented only by their geometry and force field parameters, and used this neural network to predict the loadings of real adsorbates. We focused on predicting room temperature adsorption of small (one- and two-atom) molecules relevant to chemical separations. Namely, argon, krypton, xenon, methane, ethane, and nitrogen. However, we also observed surprisingly promising predictions for more complex molecules, whose properties are outside the range spanned by the alchemical adsorbates. Prediction accuracies suitable for large-scale screening were achieved using simple MOF (e.g. geometric properties and chemical moieties), and adsorbate (e.g. forcefield parameters and geometry) descriptors. Our results illustrate a new philosophy of training that opens the path towards development of machine learning models that can predict the adsorption loading of any new adsorbate at any new operating conditions in any new MOF.</div>

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