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Hydrodynamics

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Super-resolution 4D flow MRI to quantify aortic regurgitation using computational fluid dynamics and deep learning.

The international journal of cardiovascular imaging
Changes in cardiovascular hemodynamics are closely related to the development of aortic regurgitation (AR), a type of valvular heart disease. Metrics derived from blood flows are used to indicate AR onset and evaluate its severity. These metrics can ...

The roles of artificial intelligence techniques for increasing the prediction performance of important parameters and their optimization in membrane processes: A systematic review.

Ecotoxicology and environmental safety
Membrane-based separation processes has been recently of significant global interest compared to other conventional separation approaches due to possessing undeniable advantages like superior performance, environmentally-benign nature and simplicity ...

Deep learning enables super-resolution hydrodynamic flooding process modeling under spatiotemporally varying rainstorms.

Water research
Real-time information on flooding extent, severity, and duration is necessary for effective metropolitan flood emergency management. Existing pluvial flood analysis methods are unable to simulate real-time regional flooding processes under spatiotemp...

Optimal design of triangular side orifice using multi-objective optimization NSGA-II.

Water science and technology : a journal of the International Association on Water Pollution Research
Triangular orifices are widely used in industrial and engineering applications, including fluid metering, flow control, and measurement. Predicting discharge through triangle orifices is critical for correct operation and design optimization in vario...

The role of hydrodynamics in collective motions of fish schools and bioinspired underwater robots.

Journal of the Royal Society, Interface
Collective behaviour defines the lives of many animal species on the Earth. Underwater swarms span several orders of magnitude in size, from coral larvae and krill to tunas and dolphins. Agent-based algorithms have modelled collective movements of an...

A two-dimensional hydrodynamics prediction framework for mantle-undulated propulsion robot using multiple proper orthogonal decomposition and long short term memory neural network.

Bioinspiration & biomimetics
In this paper, a deep learning based framework has been developed to predict hydrodynamic forces on a mantle-undulated propulsion robot (MUPRo). A multiple proper orthogonal decomposition (MPOD) algorithm has been proposed to efficiently identify flu...

Enhancing interpretability and generalizability of deep learning-based emulator in three-dimensional lake hydrodynamics using Koopman operator and transfer learning: Demonstrated on the example of lake Zurich.

Water research
Three-dimensional lake hydrodynamic model is a powerful tool widely used to assess hydrological condition changes of lake. However, its computational cost becomes problematic when forecasting the state of large lakes or using high-resolution simulati...

Deep learning, geometric characterization and hydrodynamic modeling for assessing sewer defect impacts on urban flooding: A case study in Guangzhou, China.

Journal of environmental management
Deep learning techniques have offered innovative and efficient tools for accurate and automated detection of sewer defects by leveraging large-scale sewer data and advanced feature learning algorithms. However, there has been a lack of thorough chara...

Hemodynamic factors of spontaneous vertebral artery dissecting aneurysms assessed with numerical and deep learning algorithms: Role of blood pressure and asymmetry.

Neuro-Chirurgie
BACKGROUND AND OBJECTIVES: The pathophysiology of spontaneous vertebral artery dissecting aneurysms (SVADA) is poorly understood. Our goal is to investigate the hemodynamic factors contributing to their formation using computational fluid dynamics (C...

Unsupervised Denoising and Super-Resolution of Vascular Flow Data by Physics-Informed Machine Learning.

Journal of biomechanical engineering
We present an unsupervised deep learning method to perform flow denoising and super-resolution without high-resolution labels. We demonstrate the ability of a single model to reconstruct three-dimensional stenosis and aneurysm flows, with varying geo...