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相关概念视频

Accelerating Fluids01:17

Accelerating Fluids

1.0K
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:
1.0K
Turbulent Flow: Problem Solving01:09

Turbulent Flow: Problem Solving

89
Carbonation is a process used to dissolve carbon dioxide gas in a liquid, commonly used in the production of carbonated beverages. Achieving efficient carbonation requires careful control of temperature, pressure, and flow conditions. By adjusting these parameters, carbonation efficiency can be maximized, producing a higher concentration of CO2 in the liquid.
Temperature is a key factor in CO2 solubility. In this case, the CO2 gas and the liquid are cooled to 20°C. Lower temperatures...
89
Mesh Analysis01:20

Mesh Analysis

548
Mesh analysis is a valuable method for simplifying circuit analysis using mesh currents as key circuit variables. Unlike nodal analysis, which focuses on determining unknown voltages, mesh analysis applies Kirchhoff's voltage law (KVL) to find unknown currents within a circuit. This method is particularly convenient in reducing the number of simultaneous equations that need to be solved.
A fundamental concept in mesh analysis is the definition of meshes and mesh currents. A mesh is a closed...
548
Turbulent Flow01:24

Turbulent Flow

132
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...
132
Laminar Flow: Problem Solving01:24

Laminar Flow: Problem Solving

108
Laminar flow occurs when a fluid moves smoothly in parallel layers with minimal mixing and turbulence. In fluid mechanics, ensuring laminar flow within a pipe is essential for precise control of flow characteristics, especially in engineering applications. The key factor in determining whether flow remains laminar is the Reynolds number, a dimensionless quantity that depends on the fluid's velocity, density, viscosity, and the pipe's diameter. A Reynolds number of 2100 or lower...
108
Couette Flow01:22

Couette Flow

196
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...
196

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相关实验视频

Updated: May 31, 2025

Design and Optimization Strategies of a High-Performance Vented Box
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使用MeshGraphNets加速计算流体动力学模拟燃烧后的碳捕获建模.

Bo Lei1, Yucheng Fu2, Jose Cadena1

  • 1Lawrence Livermore National Laboratory, Livermore, CA, United States.

Frontiers in artificial intelligence
|January 23, 2025
PubMed
概括

基于数据的方法MeshGraphNets (MGN) 加快了碳捕获系统的建模. 这种人工智能模型准确地预测二氧化碳捕获效率比传统方法快1700倍,有助于系统优化.

关键词:
碳捕获 碳捕获 碳捕获计算流体动力学的流体动力学.设计优化设计优化图形神经网络的神经网络机器学习是机器学习.代孕模拟的代孕模拟

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科学领域:

  • 化学工程是化学工程的重要组成部分.
  • 环境科学 环境科学
  • 计算科学 计算科学

背景情况:

  • 包装列对于燃烧后的二氧化碳 (CO2) 捕获至关重要,增强了溶剂与气体的接触.
  • 计算流体动力学 (CFD) 模拟液体气体水力学,以提高二氧化碳捕获效率,但在计算上是昂贵的.
  • 优化碳捕获系统 (CCS) 受到CFD广泛的设计空间和高成本的阻碍.

研究的目的:

  • 开发一个数据驱动的替代模型,以高效地模拟二氧化碳捕获中的封装列.
  • 使用MeshGraphNets (MGN),一个图形神经网络,用于准确的流体动力学建模.
  • 为了实现基于溶剂的燃烧后碳捕获系统的快速设计优化.

主要方法:

  • 使用MeshGraphNets (MGN),一个图形神经网络框架,用于数据驱动的建模.
  • 模拟了一个随机包装的列,有超过16万个图节点.
  • 多种关键输入参数:溶剂表面张力,进气速度和接触角度.

主要成果:

  • MGN模型准确地预测了广泛的参数范围内的复杂流体动力学.
  • 实现的模拟速度是传统CFD的1700倍以上.
  • 证明了对 CO2 捕获分析的不同系统参数的适应性.

结论:

  • MGN提供了一个计算效率高,准确的替代方案,用于CFD的包装列建模.
  • 数据驱动的方法对于碳捕获系统的大规模设计优化是实用的.
  • 在CCS应用中,MGN在复杂的流体动力学方面表现出强度和多功能性.