Top Research Papers on Fluid Mechanics

This book was developed using material from teaching courses on fluid mechanics, high-speed flows, aerodynamics, high-enthalpy flows, experimental methods, aircraft design, heat transfer, introduction to engineering, and wind engineering. It precisely presents the theoretical and application aspects of the terms associated with these courses. It explains concepts such as cyclone, typhoon, hurricane, and tornado, by highlighting the subtle difference between them. The text comprehensively introduces the subject vocabulary of fluid mechanics for use in courses in engineering and the physical sci...

The reprint collects research papers on mathematical and numerical modelling in fluid dynamics, discusses latest research developments in areas of fluid flows heat and mass transfer, and focuses on special topics and applications of tech-related real-world applications.

Any physical problem can be modeled by algebraic equations, differential equations, and partial differential equations. This formulation of the physical problem into mathematical equation is called mathematical modeling. The Navier–Stokes equations are the basic governing equations for the fluid mechanics problems. To apply the compressible flow equations to practical problems, one needs to have good exposure in fluid mechanics and heat transfer. The nondimensional equations help to keep the change in variables close to 1, and hence there is more stability during computing. Knowing the propert...

This textbook provides a coherent and structured overview of fluid mechanics, a discipline at the heart of most applications and human activities.

This Research Note presents several contributions and mathematical studies in fluid mechanics, namely in non-Newtonian and viscoelastic fluids and on the Navier-Stokes equations in unbounded domains. It includes review of the mathematical analysis of incompressible and compressible flows and results in magnetohydrodynamic and electrohydrodynamic stability and thermoconvective flow of Boussinesq-Stefan type. These studies, along with brief communications on a variety of related topics comprise the proceedings of a summer course held in Lisbon, Portugal in 1991. Together they provide a set of co...

This video gives an overview of how Machine Learning is being used in Fluid Mechanics. In fact, fluid mechanics is one of the original 'big data' sciences, and many advances in ML came out of fluids.

Computational Fluid Mechanics and Heat Transfer, Fourth Edition is a fully updated version of the classic text on finite-difference and finite-volume computational methods. Divided into two parts, the text covers essential concepts in the first part, and then moves on to fluids equations in the second. Designed as a valuable resource for practitioners and students, new examples and homework problems have been added to further enhance the student's understanding of the fundamentals and applications. Provides a thoroughly updated presentation of CFD and computational heat transfer Covers more ma...

Deep reinforcement learning (DRL) has recently been adopted in a wide range\nof physics and engineering domains for its ability to solve decision-making\nproblems that were previously out of reach due to a combination of\nnon-linearity and high dimensionality. In the last few years, it has spread in\nthe field of computational mechanics, and particularly in fluid dynamics, with\nrecent applications in flow control and shape optimization. In this work, we\nconduct a detailed review of existing DRL applications to fluid mechanics\nproblems. In addition, we present recent results that further ill...

In the past few decades various particle image–based volumetric flow measurement techniques have been developed that have demonstrated their potential in accessing unsteady flow properties quantitatively in various experimental applications in fluid mechanics. In this review, we focus on physical properties and circumstances of 3D particle–based measurements and what knowledge can be used for advancing reconstruction accuracy and spatial and temporal resolution, as well as completeness. The natural candidate for our focus is 3D Lagrangian particle tracking (LPT), which allows for position, vel...

An introduction and historical perspective of ML methods, in particular neural networks (NN), are provided and existing PIML applications to fluid mechanics problems are examined, especially in complex high Reynolds number flows.

The effectiveness of physics-informed neural networks (PINNs) for inverse problems related to three-dimensional wake flows, supersonic flows, and biomedical flows is demonstrated.

Spontaneous imbibition behavior gained popularity several decades ago which led to widely exploited application in fractured reservoirs. Recently the imbibition behavior of unconventional reservoirs has attracted a good number of researchers and field engineers to pay attention and research more on how to enhance recovery through imbibition behavior. Despite the numerous studies that have been conducted in this area, it is still controversial whether spontaneous imbibition behavior is applicable on reservoir stimulation especially for shale reservoir. In this paper, the recent works on the spo...

Abstract Fluid inclusion compositions obtained from laser ablation–inductively coupled plasma–mass spectrometry at the Haobugao Zn-Pb skarn in northeastern China provide constraints on fluid origin, evolution, and metal deposition mechanisms and an example of evaluating mineralization potential. Metal concentrations in the prograde fluids were high (up to 1.4 wt% Zn and 1.8 wt% Pb) but remained in solution, likely due to the high temperatures (440–575 °C) and salinities (35.4–45.3 wt% NaCl equivalent). Absolute concentrations of elements (e.g., Rb and Na) and mass ratios (e.g., Zn/Na and K/Na)...

Global demands for sustainable energy are rising rapidly due to the ever-increasing energy crisis. Efficient energy management is one of the feasible methods to solve the existing energy crisis, and has attracted extensive attention. Pulsating heat pipe (PHP), as a potential thermal management system, has broad application prospects due to its simple structure, low cost and excellent heat transfer performance. Numerous researchers are not only committed to enhance heat transfer performances of PHPs from the aspects of working fluids, but also to further understand the operation mechanisms. The...

Results indicated that the corrosion product film showed a laminated structure with complex layers, which were ZnO/Zn(OH)2, a Ca/P phase, zinc compounds, and a Ca-P phase from the inside out, respectively.

It is shown that immotile cilia at the node undergo asymmetric deformation along the dorsoventral axis in response to the flow, uncovering the biophysical mechanism by which ciliary force sensing is necessary, sufficient, and instructive for embryonic laterality.

Hidden fluid mechanics (HFM), a physics-informed deep-learning framework capable of encoding the Navier-Stokes equations into the neural networks while being agnostic to the geometry or the initial and boundary conditions, is developed.

Analysis of cerebrospinal fluid of patients with SARS-CoV-2 infection and neurological manifestations indicates a possible contribution of viral replication on triggering CNS infiltration by immune cells and the inflammation promoting neuronal injury.

An insight into the current state of the art of the use of DRL within fluid mechanics, focusing on control and optimal design problems.

The state-of-the-art architectures and their applications are reviewed, limitations are discussed, and future research opportunities are presented in terms of improving algorithms, considering causalities, expanding applications, and coupling scientific and deep learning solvers.