The challenges of hydrodynamic forces on cells used in Cell Manufacturing and Therapy

2021 ◽  
pp. 100357
Author(s):  
Jeffrey J. Chalmers
Keyword(s):  
Hydrodynamic Forces ◽  
Cell Manufacturing

Application of remote sensing technology to the relation of submarine pipelines and coastal morphology

1995 ◽  
Vol 32 (2) ◽  
pp. 77-83
Author(s):  
Y. Yüksel ◽  
D. Maktav ◽  
S. Kapdasli
Keyword(s):  
Remote Sensing ◽  
Sediment Transport ◽  
Surf Zone ◽  
Hydrodynamic Forces ◽  
Construction Site ◽  
Coastal Morphology ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Sea Bed

Submarine pipelines must be designed to resist wave and current induced hydrodynamic forces especially in and near the surf zone. They are buried as protection against forces in the surf zone, however this procedure is not always feasible particularly on a movable sea bed. For this reason the characteristics of the sediment transport on the construction site of beaches should be investigated. In this investigation, the application of the remote sensing method is introduced in order to determine and observe the coastal morphology, so that submarine pipelines may be protected against undesirable seabed movement.

Patents on Red Blood Cell Manufacturing In Vitro

2011 ◽  
Vol 1 (2) ◽  
pp. 173-181
Author(s):  
Laurence Guyonneau-Harmand ◽  
Luc Douay
Keyword(s):  
Blood Cell ◽  
Red Blood Cell ◽  
Cell Manufacturing

scholarly journals Capsule Migration and Deformation in a Converging Micro-Capillary

Processes ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 452
Author(s):  
Yiyang Wang ◽  
Panagiotis Dimitrakopoulos
Keyword(s):  
Viscosity Ratio ◽  
Hydrodynamic Forces ◽  
Straight Channel ◽  
Lateral Migration ◽  
Computational Investigation ◽  
Physiological Processes ◽  
Lower Viscosity ◽  
Elastic Capsules ◽  
Interfacial Deformation ◽  
Capsule Size

The lateral migration of elastic capsules towards a microchannel centerline plays a major role in industrial and physiological processes. Via our computational investigation, we show that a constriction connecting two straight microchannels facilitates the lateral capsule migration considerably, which is relatively slow in straight channels. Our work reveals that the significant cross-streamline migration inside the constriction is dominated by the strong hydrodynamic forces due to the capsule size. However, in the downstream straight channel, the increased interfacial deformation at higher capillary numbers or a lower viscosity ratio and lower membrane hardness results in increased lateral cross-streamline migration. Thus, our work highlights the different migration mechanisms occurring over curved and straight streamlines.

Machine learning–based reduced-order modeling of hydrodynamic forces using pressure mode decomposition

2021 ◽  
pp. 095441002199986
Author(s):  
Hassan F Ahmed ◽  
Hamayun Farooq ◽  
Imran Akhtar ◽  
Zafar Bangash
Keyword(s):  
Machine Learning ◽  
Short Term Memory ◽  
Stokes Equations ◽  
Decomposition Analysis ◽  
Hydrodynamic Forces ◽  
Reduced Order Modeling ◽  
Navier Stokes ◽  
Reduced Order ◽  
Mode Decomposition ◽  
Lift And Drag

In this article, we introduce a machine learning–based reduced-order modeling (ML-ROM) framework through the integration of proper orthogonal decomposition (POD) and deep neural networks (DNNs), in addition to long short-term memory (LSTM) networks. The DNN is utilized to upscale POD temporal coefficients and their respective spatial modes to account for the dynamics represented by the truncated modes. In the second part of the algorithm, temporal evolution of the POD coefficients is obtained by recursively predicting their future states using an LSTM network. The proposed model (ML-ROM) is tested for flow past a circular cylinder characterized by the Navier–Stokes equations. We perform pressure mode decomposition analysis on the flow data using both POD and ML-ROM to predict hydrodynamic forces and demonstrate the accuracy of the proposed strategy for modeling lift and drag coefficients.

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