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Precipitation Gravimetry01:03

Precipitation Gravimetry

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Precipitation gravimetry is based on converting an analyte into a sparingly soluble precipitate, which is separated by filtration and weighed. An ideal precipitate should be pure, insoluble, of known composition, and easily filtered from the reaction mixture.
In determining nickel by gravimetric analysis, a precipitant of ethanolic dimethylglyoxime is added to a hot nickel salt solution. This is quickly followed by the dropwise addition of dilute ammonia solution until precipitation occurs. A...
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Influence of Earth's Curvature and Atmospheric Refraction on Leveling01:26

Influence of Earth's Curvature and Atmospheric Refraction on Leveling

237
During leveling, the Earth's curvature and atmospheric refraction introduce deviations in the line of sight from a true horizontal reference. When the line of sight is leveled, it remains perpendicular to the plumb line only at a single point. Beyond this, it deviates due to the Earth’s curvature, represented by the correction C. For a sight distance D, the deviation can be derived using the relationship:This relationship shows that the deviation increases quadratically with distance.
237
Differential Leveling01:12

Differential Leveling

293
Differential leveling is a precise method in surveying used to determine the elevation difference between two points. Its primary goal is to establish accurate vertical measurements to create level surfaces or grade lines critical for designing and constructing infrastructures such as roads, bridges, and buildings.The procedure for differential leveling begins with setting up and leveling the instrument at a point where the benchmark can be seen. The level rod is held on the benchmark (BM), and...
293

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相关实验视频

Updated: Sep 1, 2025

Data Processing Methods for 3D Seismic Imaging of Subsurface Volcanoes: Applications to the Tarim Flood Basalt
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深度学习地震学

S Mostafa Mousavi1,2, Gregory C Beroza1

  • 1Department of Geophysics, Stanford University, Stanford, CA 94305, USA.

Science (New York, N.Y.)
|August 11, 2022
PubMed
概括
此摘要是机器生成的。

通过分析地震波来了解地球内部, 深度学习方法正在彻底改变地震学. 这篇综述探讨了应用这些强大的人工智能技术在地震数据分析中的趋势,挑战和机遇.

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科学领域:

  • 地质学
  • 地震学
  • 人工智能

背景情况:

  • 地震波对于探测地球内部结构至关重要.
  • 大规模的地震数据集越来越多.
  • 深度学习 (DL) 对地震数据处理具有很大的前景.

研究的目的:

  • 在地震学中提供DL应用的系统概述.
  • 确定主要趋势,挑战和机遇.
  • 突出地质科学和其他研究领域的更广泛影响.

主要方法:

  • 对地震学应用的当前深度学习方法的审查.
  • 使用DL进行地震数据处理工作流程的分析.
  • 确定共同的挑战和成功的战略.

主要成果:

  • 深度学习正在推动基础地震研究.
  • 特定的DL技术已被证明是地震数据分析的有效方法.
  • 需要仔细考虑DL应用的细微差别,以获得最佳结果.

结论:

  • 深度学习为地震学的进步提供了巨大潜力.
  • 了解DL应用的细节是地球科学的关键.
  • 这种方法可以为其他科学领域提供更广泛的见解.