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Unraveling Turbulent Heat Transport: Boundary Layers, Scalar Scaling, and the Ultimate Convection Debate
Abstract: Scalar Turbulence and Heat Transport Scaling in High-Rayleigh Number Convection This structured literature review synthesizes the theoretical and experimental foundations concerning scalar turbulence and heat transport scaling in high-Rayleigh number (Ra) Rayleigh–Bénard convection (RBC), focusing on the critical role of thermal boundary layers (TBLs). The primary objective is to critically assess the evolution, central…
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Rotational Dynamics and Vorticity Across Scales: A Unified Literature Review of Fluid Helicity, Cosmic Structures, and Optical Angular Momentum (OAM)
Abstract This structured literature review synthesizes the concepts of rotational dynamics and vortical structures across three traditionally distinct physical domains: classical fluid mechanics, relativistic cosmology, and quantum optics. The review establishes a unifying Gradient Principle, whereby the core dynamic effects in all systems—from fluid flow to structured light—are governed by the spatial gradients of their…
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Entropic Gravity Explained: How Quantum Thermodynamics Could Replace Gravitons
Impact on Spaceflight Operations For decades, physicists have understood fundamental forces like electromagnetism and gravity as being mediated by quantum fields and virtual particles, such as photons and gravitons. At the same time, some forces in nature—like pressure in a gas—emerge not from fundamental interactions but from thermodynamic principles, driven by entropy and free energy.…
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The AI-Thermodynamics Revolution: Accelerating Scientific Discovery and Engineering a Sustainable Future
The application of Artificial Intelligence (AI), particularly Machine Learning (ML), has demonstrated remarkable success in thermodynamics, enabling the development of highly accurate and efficient models for molecular simulation, materials design, and property prediction. Pioneering work, such as the creation of High-Dimensional Neural Network Potentials (HDNNPs) by Behler and Parrinello [1] and the subsequent rise of…