Abstract Prepared by the Computational Fluid Dynamics Task Committee of the Water
Supply, Treatment and Distribution Engineering Committee of the Water, Wastewater, and …

Fluids (gases and liquids) are flowing around us: rains, winds, floods, hurricanes in our
body: blood flow, breathing, drinking in our homes: heating and air conditioning around cars …

The application of deep learning toward discovery of data-driven models requires careful
application of inductive biases to obtain a description of physics which is both accurate and …

Advancements in computing power have recently made it possible to utilize machine
learning and deep learning to push scientific computing forward in a range of disciplines …

This review discusses the recent application of artificial intelligence (AI) algorithms in five
aspects of computational fluid dynamics: aerodynamic models, turbulence models, some …

Machine Learning Guide for Oil and Gas Using Python: A Step-by-Step Breakdown with
Data, Algorithms, Codes, and Applications delivers a critical training and resource tool to …

Chemical engineering is a data-rich subject. Practitioners collect and analyze data for
understanding flow patterns, developing empirical models, designing and optimizing …

This more-of-physics, less-of-math, insightful and comprehensive book simplifies
computational fluid dynamics for readers with little knowledge or experience in heat transfer …

In the current study, Artificial Intelligence (AI) approach was used for the learning of a
physical system. We applied four inputs and one output in the learning process of AI. In the …

Microfluidics allows for the manipulation and analysis of minuscule amounts of liquid within
a system that contains multiple channels, ports, and samples. Advanced microfluidic …