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Hydrodynamics

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Theoretical investigations on analysis and optimization of freeze drying of pharmaceutical powder using machine learning modeling of temperature distribution.

Scientific reports
This study investigates the application of various neural network-based models for predicting temperature distribution in freeze drying process of biopharmaceuticals. For heat-sensitive biopharmaceutical products, freeze drying is preferred to preven...

Simulating fish autonomous swimming behaviours using deep reinforcement learning based on Kolmogorov-Arnold Networks.

Bioinspiration & biomimetics
The study of fish swimming behaviours and locomotion mechanisms holds significant scientific and engineering value. With the rapid advancements in artificial intelligence, a new method combining deep reinforcement learning (DRL) with computational fl...

A bioinspired fish fin webbing for proprioceptive feedback.

Bioinspiration & biomimetics
The propulsive fins of ray-finned fish are used for large scale locomotion and fine maneuvering, yet also provide sensory feedback regarding hydrodynamic loading and the surrounding environment. This information is gathered via nerve cells in the web...

Intelligent Microfluidics for Plasma Separation: Integrating Computational Fluid Dynamics and Machine Learning for Optimized Microchannel Design.

Biosensors
Efficient separation of blood plasma and Packed Cell Volume (PCV) is vital for rapid blood sensing and early disease detection, especially in point-of-care and resource-limited environments. Conventional centrifugation methods for separation are reso...

3D velocity and pressure field reconstruction in the cardiac left ventricle via physics informed neural network from echocardiography guided by 3D color Doppler.

Computer methods and programs in biomedicine
Fluid dynamics of the heart chamber can provide critical biological cues for understanding cardiac health and disease and have the potential for supporting diagnosis and prognosis. However, directly acquiring fluid dynamics information from clinical ...

Role of physics-informed constraints in real-time estimation of 3D vascular fluid dynamics using multi-case neural network.

Computers in biology and medicine
Numerical simulations of fluid dynamics in tube-like structures are important to biomedical research to model flow in blood vessels and airways. It is further useful to some clinical applications, such as predicting arterial fractional flow reserves,...

An interpretable approach to estimate the self-motion in fish-like robots using mode decomposition analysis.

Nature communications
The artificial lateral line system, composed of velocity and pressure sensors, is the sensing system for fish-like robots by mimicking the lateral line system of aquatic organisms. However, accurately estimating the self-motion of the fish-like robot...

Amphibious robotic dog: design, paddling gait planning, and experimental characterization.

Bioinspiration & biomimetics
Mammal-inspired quadruped robots excel in traversing diverse terrestrial terrains but often lack aquatic mobility, limiting their effectiveness in amphibious environments. To address this challenge, an amphibious robotic dog (ARD) was developed, inte...

Predicting Milk Flow Behavior in Human Lactating Breast: An Integrated Machine Learning and Computational Fluid Dynamics Approach.

Journal of biomechanical engineering
This study develops a comprehensive framework that integrates computational fluid dynamics (CFD) and machine learning (ML) to predict milk flow behavior in lactating breasts. Utilizing CFD and other high-fidelity simulation techniques to tackle fluid...