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Updated: Jan 11, 2026

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The Diffusion of Passive Tracers in Laminar Shear Flow
Published on: May 1, 2018
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通过空间统计信息的多孔介质的潜质扩散建模
1Colorado School of Mines, Golden, Colorado 80401, USA.
Physical review. E
|November 18, 2025
概括
本研究引入了一个新的生成框架,使用隐性扩散模型 (LDM) 来创建现实的多孔介质结构. 该方法使复杂材料的快速,可扩展和可控制的生成成为可能,这对科学研究至关重要.
科学领域:
- 材料科学 材料科学 材料科学
- 计算建模 计算建模
- 地质物理学 地质物理学
背景情况:
- 对多孔介质的准确建模对于理解各种材料中的流体运输,机械性能和多物理现象至关重要.
- 现有的产生多孔介质的方法可能是计算密集的,或者缺乏对结构性质的控制.
研究的目的:
- 开发一种新的生成框架,用于准确有效地建模多孔介质结构.
- 利用在随机模拟和实验数据上训练的潜在扩散模型 (LDM) 提高生成能力.
主要方法:
- 一种混合方法,将随机模拟结合起来,以产生高分辨率的多孔样本,并使用隐性扩散模型 (LDM).
- 使用一个变异自动编码器来减少维度,以及一个UNet的denoiser用于潜伏空间生成在LDM管道内.
- 在从随机模拟中获得的统计控制数据集上训练LDM,保留空间相关统计数据.
主要成果:
- 开发的LDM成功地学习了数据驱动的先前多孔结构,并保留了关键的统计属性.
- 证明无条件生成现实的多孔媒体模型,具有高视觉多样性和生成忠实性.
- 生成的模型准确地反映了输入空间统计数据.
结论:
- 混合生成框架为快速,可扩展和可控制的多孔媒体生成提供了一个有希望的途径.
- 这种方法在数据稀缺或模拟繁重的研究环境中尤为有益.
- 该方法提高了研究复杂的多孔系统中的流体运输和材料特性的能力.
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