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相关概念视频

Couette Flow01:22

Couette Flow

939
Couette flow represents the flow of fluid between two parallel plates, with one plate fixed and the other moving with a constant velocity. This configuration allows for a simplified analysis using the Navier-Stokes equations, which govern fluid motion under conditions of viscosity and incompressibility. For Couette flow, the assumptions include a steady, laminar, incompressible flow with a zero-pressure gradient in the flow direction. This flow type is beneficial for understanding shear-driven...
939
Accelerating Fluids01:17

Accelerating Fluids

2.1K
When a fluid is in constant acceleration, the pressure and buoyant force equations are modified. Suppose a beaker is placed in an elevator accelerating upward with a constant acceleration, a. In the beaker, assume there is a thin cylinder of height h with an infinitesimal cross-sectional area, ΔS.
The motion of the liquid within this infinitesimal cylinder is considered to obtain the pressure difference. Three vertical forces act on this liquid:
2.1K
Rapidly Varying Flow01:24

Rapidly Varying Flow

441
Rapidly varying flow (RVF) in open channels is characterized by abrupt changes in flow depth over a short distance, with the rate of depth change relative to distance often approaching unity. These flows are inherently complex due to their transient and multi-dimensional nature, making exact analysis difficult. However, approximate solutions using simplified models provide valuable insights into their behavior.Key Features of Rapidly Varying FlowRVF is commonly observed in scenarios involving...
441
Turbulent Flow01:24

Turbulent Flow

671
Turbulent flow is characterized by unpredictable fluctuations in velocity and pressure, which result in a chaotic fluid movement distinct from the orderly patterns of laminar flow. While laminar flow is governed by smooth, parallel layers with minimal mixing, turbulent flow exhibits highly irregular, three-dimensional patterns. This behavior arises due to instabilities in the fluid's velocity profile, and amplifies as the flow velocity increases. Minor disturbances, known as turbulent...
671
Steady Flow of a Fluid Stream01:27

Steady Flow of a Fluid Stream

664
Consider a control volume, such as a pipe with solid boundaries, through which fluid flows and changes direction due to the impulse exerted by the resulting force from the pipe walls. In steady flow, the mass of fluid entering the control volume at a given time, t, with velocity v1, is equal to the mass leaving after infinitesimal time dt, with velocity v2.
During this process, the momentum of the fluid within the control volume remains constant over the time interval dt. By applying the...
664
Gradually Varying Flow01:29

Gradually Varying Flow

406
Gradually varying flow (GVF) in open channels describes situations where water depth changes slowly along the channel due to factors like non-uniform bed slope, channel shape variations, or obstructions. This flow type occurs when the depth adjusts gradually to balance gravitational forces, shear forces, and energy requirements, resulting in a low rate of depth change.Characteristics of Gradually Varying FlowGVF is commonly observed in natural streams, rivers, and canals, where flow depth...
406

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相关实验视频

Updated: Jan 14, 2026

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

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在分子动力学中以能量为基础的粗粒化:一个基于流量的框架,没有数据.

Maximilian Stupp1, P S Koutsourelakis1,2

  • 1Professorship of Data-Driven Materials Modeling, School of Engineering and Design, Technical University of Munich, Garching bei München 85748, Germany.

Journal of chemical theory and computation
|October 24, 2025
PubMed
概括

这项研究引入了一种新的无数据生成框架,用于粗粒度分子模拟. 该方法准确地重建原子配置,并学习有意义的表示,而不依赖于广泛的模拟数据.

科学领域:

  • 计算化学和分子建模计算化学和分子建模
  • 统计力学 统计力学
  • 机器学习在科学中的应用

背景情况:

  • 传统的粗粒度 (CG) 模型需要广泛的全原子模拟数据,限制了准确性和通用性.
  • 数据依赖性排除了未访问的配置,这给抽样配置空间带来了挑战.
  • "和蛋"问题和逆向映射的不准确性阻碍了传统的CG方法.

研究的目的:

  • 开发一个完全没有数据的粗粒度生成框架.
  • 在没有先前的模拟轨迹的情况下直接针对全原子博尔兹曼分布.
  • 为了能够准确地重建分子结构,并解决后置映射问题.

主要方法:

  • 一个生成框架,定义一个结构化的潜空间,具有缓慢和快速的集体变量.
  • 从潜空间到原子坐标的可学习的对称地图,用于结构重建.
  • 通过基于能源的目标进行训练,最大限度地减少反向Kullback-Leibler分歧,使用自适应化方案.

主要成果:

  • 该框架成功地在合成和基准系统上捕捉了博尔茨曼分布的所有相关模式.
  • 从已知的潜空间中对原子配置进行高准确度重建.
  • 在没有外部数据的情况下,自动学习物理上有意义的粗粒度表示.

更多相关视频

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
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Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

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Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
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Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

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相关实验视频

Last Updated: Jan 14, 2026

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

9.0K
Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

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Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
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Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

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结论:

  • 拟议的无数据框架为传统粗粒技术提供了一个有希望的替代方案.
  • 它有效地解决了数据依赖和后置映射问题的局限性.
  • 该方法提供了准确的分子结构生成和模拟的原则方法.