scholarly journals “Holographic Implementations” in the Complex Fluid Dynamics through a Fractal Paradigm

Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2273
Author(s):  
Alexandra Saviuc ◽  
Manuela Gîrțu ◽  
Liliana Topliceanu ◽  
Tudor-Cristian Petrescu ◽  
Maricel Agop
Keyword(s):  
Fluid Dynamics ◽  
Differential Geometry ◽  
Harmonic Mapping ◽  
Period Doubling ◽  
Velocity Fields ◽  
Hydrodynamic Type ◽  
Airy Functions ◽  
Structural Units ◽  
Type Group ◽  
Complex Fluid

Assimilating a complex fluid with a fractal object, non-differentiable behaviors in its dynamics are analyzed. Complex fluid dynamics in the form of hydrodynamic-type fractal regimes imply “holographic implementations” through velocity fields at non-differentiable scale resolution, via fractal solitons, fractal solitons–fractal kinks, and fractal minimal vortices. Complex fluid dynamics in the form of Schrödinger type fractal regimes imply “holographic implementations”, through the formalism of Airy functions of fractal type. Then, the in-phase coherence of the dynamics of the complex fluid structural units induces various operational procedures in the description of such dynamics: special cubics with SL(2R)-type group invariance, special differential geometry of Riemann type associated to such cubics, special apolar transport of cubics, special harmonic mapping principle, etc. In such a manner, a possible scenario toward chaos (a period-doubling scenario), without concluding in chaos (nonmanifest chaos), can be mimed.

scholarly journals Enhancement of cerebrovascular 4D flow MRI velocity fields using machine learning and computational fluid dynamics simulation data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
David R. Rutkowski ◽  
Alejandro Roldán-Alzate ◽  
Kevin M. Johnson
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Velocity Fields ◽  
Dynamics Simulation ◽  
Patient Specific ◽  
4D Flow Mri ◽  
4D Flow ◽  
Flow Phase ◽  
Flow Mri ◽  
Trained Network

AbstractBlood flow metrics obtained with four-dimensional (4D) flow phase contrast (PC) magnetic resonance imaging (MRI) can be of great value in clinical and experimental cerebrovascular analysis. However, limitations in both quantitative and qualitative analyses can result from errors inherent to PC MRI. One method that excels in creating low-error, physics-based, velocity fields is computational fluid dynamics (CFD). Augmentation of cerebral 4D flow MRI data with CFD-informed neural networks may provide a method to produce highly accurate physiological flow fields. In this preliminary study, the potential utility of such a method was demonstrated by using high resolution patient-specific CFD data to train a convolutional neural network, and then using the trained network to enhance MRI-derived velocity fields in cerebral blood vessel data sets. Through testing on simulated images, phantom data, and cerebrovascular 4D flow data from 20 patients, the trained network successfully de-noised flow images, decreased velocity error, and enhanced near-vessel-wall velocity quantification and visualization. Such image enhancement can improve experimental and clinical qualitative and quantitative cerebrovascular PC MRI analysis.

scholarly journals Application of a bounded upwinding scheme to complex fluid dynamics problems

2013 ◽  
Vol 57 (3-4) ◽  
pp. 435-459 ◽  
Author(s):  
V.G. Ferreira ◽  
M.K. Kaibara ◽  
G.A.B. Lima ◽  
J.M. Silva ◽  
M.H. Sabatini ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Complex Fluid ◽  
Dynamics Problems

On the Discretization of the Power-Law Hemolysis Model

2020 ◽  
Vol 143 (1) ◽  
Author(s):  
Mohammad M. Faghih ◽  
Ahmed Islam ◽  
M. Keith Sharp
Keyword(s):  
Fluid Dynamics ◽  
Power Law ◽  
Velocity Fields ◽  
Radial Expansion ◽  
Complex Flows ◽  
Cfd Simulations ◽  
Large Exponent ◽  
Computer Based ◽  
Computational Fluid Dynamics Cfd ◽  
Simple Flows

Abstract Flow-induced hemolysis remains a concern for blood-contacting devices, and computer-based prediction of hemolysis could facilitate faster and more economical refinement of such devices. While evaluation of convergence of velocity fields obtained by computational fluid dynamics (CFD) simulations has become conventional, convergence of hemolysis calculations is also essential. In this paper, convergence of the power-law hemolysis model is compared for simple flows, including pathlines with exponentially increasing and decreasing stress, in gradually expanding and contracting Couette flows, in a sudden radial expansion and in the Food and Drug Administration (FDA) channel. In the exponential cases, convergence along a pathline required from one to tens of thousands of timesteps, depending on the exponent. Greater timesteps were required for rapidly increasing (large exponent) stress and for rapidly decreasing (small exponent) stress. Example pathlines in the Couette flows could be fit with exponential curves, and convergence behavior followed the trends identified from the exponential cases. More complex flows, such as in the radial expansion and the FDA channel, increase the likelihood of encountering problematic pathlines. For the exponential cases, comparison of converged hemolysis values with analytical solutions demonstrated that the error of the converged solution may exceed 10% for both rapidly decreasing and rapidly increasing stress.

scholarly journals Thermal Comfort Analysis in Naturally-Ventilated Handball Arena Utilizing CFD Techniques

2019 ◽  
Vol 111 ◽  
pp. 01040
Author(s):  
Ahmed A. Masoud ◽  
Essam E. Khalil ◽  
Abdelmaged H. Ibrahim ◽  
Esmail M. ElBialy
Keyword(s):  
Fluid Dynamics ◽  
Thermal Comfort ◽  
Natural Ventilation ◽  
Velocity Fields ◽  
Prevailing Wind ◽  
Training Time ◽  
Wind Speeds ◽  
Upper Limit ◽  
Full Capacity ◽  
Temperature And Velocity Fields

This work investigates the feasibility and thermal comfort of using natural ventilation in order to achieve thermal comfort in a handball arena with realistic dimensions and a full occupation of 4300 persons in the Gulf area. The work numerically simulates the temperature and velocity fields inside the full arena using computational fluid dynamics techniques at different internal loads, prevailing wind speeds, prevailing wind temperatures and prevailing wind angles. The work generates certain air opening configuration to be used for natural ventilation and the results show that natural ventilation is feasible if the following conditions are met simultaneously: the occupation density is 25% or less, sitting in the prevailing wind side, the lighting load does not exceed 50% of its full capacity, the prevailing wind temperature does not exceed 30 °C and the prevailing wind velocity is in range 3-4 m/s, where the upper limit arises from the requirement to avoid high velocities in the playing area. These conditions can be met during the training time and during parts of the day and over parts of the year hours making this method conditionally feasible.

scholarly journals Go Fast With the Flow

2015 ◽  
Vol 137 (05) ◽  
pp. 40-45
Author(s):  
John Martin
Keyword(s):  
Fluid Dynamics ◽  
Cfd Modeling ◽  
Surrounding Water ◽  
Support Teams ◽  
Computer Environment ◽  
World Class ◽  
Computational Fluid Dynamics Cfd ◽  
Complex Fluid ◽  
Fluid Flow Regimes ◽  
Force Data

This article discusses various applications of computational fluid dynamics (CFD) in the field of swimming. Using known physics and fluid dynamics relationships, CFD allows complex fluid flow regimes and geometry to be simulated within a computer environment. The ability to obtain segment-specific fluid force data within a full body stroking model provides enormous amounts of information that would be unobtainable via current empirical testing techniques. CFD software imports a realistic geometry of the athlete, generates the geometry of the surrounding water and air, and meshes these geometries to represent the athlete’s body in its surroundings. For world-class swimmers, the pursuit of a record-breaking performance at the 2016 Rio Olympics may well depend on CFD modeling and other simulations just as much as the athlete's physical ability. Experts see several applications for CFD, as engineers and academics continue their research into swimming, and coaches, athletes, and support teams prep for new competitions and championships, including the 2016 Rio Games. The growth of CFD methodology in swimming will rely on the ability to obtain easy and accurate 3-D kinematics.

scholarly journals Mapping flow distortion on oceanographic platforms using computational fluid dynamics

Ocean Science ◽  
2013 ◽  
Vol 9 (5) ◽  
pp. 855-866 ◽  
Author(s):  
N. O'Sullivan ◽  
S. Landwehr ◽  
B. Ward
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Wind Speed ◽  
Close Agreement ◽  
Velocity Fields ◽  
Experimental Measurements ◽  
Flow Distortion ◽  
Direct Measurements ◽  
Computational Fluid Dynamics Cfd ◽  
Set Up

Abstract. Wind speed measurements over the ocean on ships or buoys are affected by flow distortion from the platform and by the anemometer itself. This can lead to errors in direct measurements and the derived parametrisations. Here we computational fluid dynamics (CFD) to simulate the errors in wind speed measurements caused by flow distortion on the RV Celtic Explorer. Numerical measurements were obtained from the finite-volume CFD code OpenFOAM, which was used to simulate the velocity fields. This was done over a range of orientations in the test domain from −60 to +60° in increments of 10°. The simulation was also set up for a range of velocities, ranging from 5 to 25 m s−1 in increments of 0.5 m s−1. The numerical analysis showed close agreement to experimental measurements.

The Practical Application of CFD in the Design of Industrial Centrifugal Compressors

2000 ◽  
Author(s):  
James M. Sorokes ◽  
Bradley R. Hutchinson
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Fluid Flow ◽  
Gas Turbine ◽  
Flow Fields ◽  
Practical Application ◽  
Jet Engine ◽  
Flow Problems ◽  
Computational Fluid Dynamics Cfd ◽  
Complex Fluid

Abstract In the development of industrial turbomachinery, the aerodynamic designer is faced with many complex fluid flow problems. In the mid to late 1980’s, Computational Fluid Dynamics (CFD) software was developed to assist in the solution of these flow fields. Initially applied only by high end gas turbine or jet engine designers, these sophisticated tools eventually found their way to engineers at industrial turbomachinery manufacturers. However, it has only been in the last five to ten years that industrial users have begun to make more widespread use of CFD. There are a variety of reasons for this slow adoption.

scholarly journals Reproducibility of Experiments With Swirling Flow: Numerical Prediction With Polynomial Chaos

2018 ◽  
Vol 3 (1) ◽  
Author(s):  
Alouette van Hove ◽  
Lasse N. Skov ◽  
Denis F. Hinz
Keyword(s):  
Fluid Dynamics ◽  
Polynomial Chaos ◽  
Swirling Flow ◽  
Flow Patterns ◽  
Velocity Fields ◽  
Good Reproducibility ◽  
Computational Fluid Dynamics Cfd ◽  
Computational Uncertainty ◽  
Flow Experiments ◽  
Inflow Conditions

Achieving good reproducibility in fluid flow experiments can be challenging, in particular in scenarios where the experimental boundary conditions are obscure. We use computational uncertainty quantification (UQ) to evaluate the influence of uncertain inflow conditions on the reproducibility of experiments with swirling flow. Using a nonintrusive polynomial chaos method in combination with a computational fluid dynamics (CFD) code, we obtain the expectation and variance of the velocity fields downstream from symmetric and asymmetric swirl disturbance generators. Our results suggest that the flow patterns downstream from the asymmetric swirl disturbance generator are more reproducible than the flow patterns downstream from the symmetric swirl disturbance generator. This confirms that the inherent breaking of symmetry eliminates instability mechanisms in the wake of the disturber, thereby creating more stable swirling patterns that make the experiments more reproducible.

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