AIMC Topic: Hydrodynamics

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Sociohydrodynamics: Data-driven modeling of social behavior.

Proceedings of the National Academy of Sciences of the United States of America
Living systems display complex behaviors driven by physical forces as well as decision-making. Hydrodynamic theories hold promise for simplified universal descriptions of socially generated collective behaviors. However, the construction of such theo...

Expanding point cloud statistical shape model applications: Generalized vascular modeling for population-level hemodynamic simulations.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Population-scale hemodynamic research faces limitations due to the trade-off between computationally expensive patient-specific Computational Fluid Dynamics (CFD) and overly idealized cylindrical models. To overcome this, we...

Optimization of hemocompatibility metrics in ventricular assist device design using machine learning and CFD-based response surface analysis.

The International journal of artificial organs
Ventricular assist devices (VADs) are essential for end-stage heart failure patients, but their design must balance hydraulic efficiency and hemocompatibility to minimize blood damage. This study presents a multi-objective optimization framework inte...

Underwater bionic undulating fins incorporating thickness effects: hydrodynamic performance and optimal thickness variation rate analysis.

Bioinspiration & biomimetics
In response to the urgent issues faced by current bionic undulating fin robot propulsion mechanisms, such as low working efficiency, insufficient swimming speed, ignoring thickness parameters, and the need for further improvement in biomimetic degree...

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...

Keystone microbial taxa identified by deep learning reveal mechanisms of phosphorus stoichiometric homeostasis in submerged macrophytes under different hydrodynamic states.

Water research
Phosphorus (P) pollution in aquatic ecosystems triggers eutrophication, disrupting ecological processes. Although phytoremediation using submerged macrophytes is promising, its efficacy depends on plant-microbe interactions and stoichiometric homeost...

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...

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,...

Rapid wall shear stress prediction for aortic aneurysms using deep learning: a fast alternative to CFD.

Medical & biological engineering & computing
Aortic aneurysms pose a significant risk of rupture. Previous research has shown that areas exposed to low wall shear stress (WSS) are more prone to rupture. Therefore, precise WSS determination on the aneurysm is crucial for rupture risk assessment....