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The Quantum-Mechanical Model of an Atom02:45

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Shortly after de Broglie published his ideas that the electron in a hydrogen atom could be better thought of as being a circular standing wave instead of a particle moving in quantized circular orbits, Erwin Schrödinger extended de Broglie’s work by deriving what is now known as the Schrödinger equation. When Schrödinger applied his equation to hydrogen-like atoms, he was able to reproduce Bohr’s expression for the energy and, thus, the Rydberg formula governing hydrogen spectra.
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基于图像的孔隙/微机械建模的孔隙微结构的随机重建中的计算智能.

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  • 1Department of Engineering Mechanics, School of Mechanics and Aerospace Engineering, Dalian University of Technology, Dalian, 116023 China.

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随机微结构重建生成虚拟多孔材料,用于研究微结构与属性关系 (MPR). 先进的AI方法改善了重建,但对于复杂的系统,数据稀缺性和可解释性等挑战仍然存在.

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科学领域:

  • 材料科学 材料科学 材料科学
  • 计算机建模 计算建模
  • 工程机械 工程机械 工程机械

背景情况:

  • 了解随机多孔介质中的微结构-属性关系 (MPR) 是至关重要的.
  • 基于图像的建模和数值模拟是MPR调查的关键工具.
  • 孔隙介质的静态性质需要大量的3D数字微结构数据集.

研究的目的:

  • 审查随机微观结构重建方法.
  • 强调基于计算智能的方法,如生成对抗网络.
  • 讨论传统方法的局限性和未来的趋势.

主要方法:

  • 审查传统的基于算法的重建方法.
  • 检查基于计算智能 (CI) 的新兴方法.
  • 专注于生成对抗网络 (GAN) 和其他人工智能技术.

主要成果:

  • 随机重建有效地从有限的数据中生成虚拟微观结构.
  • 基于CI的方法提高了重建的可靠性,效率和可扩展性.
  • 通过诸如蒙特卡洛模拟之类的方法,使MPR能够进行可靠的统计分析.

结论:

  • 在人工智能驱动的微观结构重建方面取得了重大进展.
  • 数据稀缺,计算成本和复杂系统的可解释性仍然是挑战.
  • 物理意识的ML和混合AI为MPR研究提供了未来的解决方案.