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Relative Motion Analysis - Velocity01:24

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A stroke engine has a slider-crank mechanism that converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider.
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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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To calculate other physical quantities in kinematics, the time variable must be introduced. The time variable not only allows us to state where an object is (its position) during its motion, but also how fast it’s moving. The speed at which an object is moving is given by the rate at which the position changes with time. For each position, a particular time is assigned. If the details of the motion at each instant are not important, the rate is usually expressed as the average velocity v.
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Instantaneous velocity is the quantity that measures how fast an object is moving along its path. In other words, the instantaneous velocity of an object is the limit of the average velocity as the elapsed time approaches zero, or the derivative of displacement with respect to time. Like average velocity, the instantaneous velocity is a vector with the dimensions of length per unit time. Instantaneous velocity can have both positive and negative values. The instantaneous velocity can be...
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If acceleration as a function of time is known, then velocity and position functions can be derived using integral calculus. For constant acceleration, the integral equations refer to the first and second kinematic equations for velocity and position functions, respectively.
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Data Processing Methods for 3D Seismic Imaging of Subsurface Volcanoes: Applications to the Tarim Flood Basalt
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基于学习的地震速度反转与合成和现场数据.

Stuart Farris1, Robert Clapp1, Mauricio Araya-Polo2

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

Sensors (Basel, Switzerland)
|October 14, 2023
PubMed
概括

在现场地震数据上训练的深度学习模型准确地恢复复杂地质学的地下速度模型. 当现场数据稀缺时,合成数据显示出希望,但需要领域专业知识来弥合数据差距.

科学领域:

  • 地质物理学 地质物理学
  • 机器学习 机器学习
  • 地下表面建模模型

背景情况:

  • 准确的声学地下速度模型对于工业勘探至关重要.
  • 传统的倒置方法在复杂的地质区域面临挑战.
  • 深度学习 (DL) 提供了一个潜在的替代方案,但需要通过现场数据进行强有力的验证.

研究的目的:

  • 用现场和合成地震数据分析深度学习的速度模型恢复能力.
  • 评估训练数据选择和增强对DL模型性能的影响.
  • 评估DL在墨西哥湾等具有挑战性的地质环境中的有效性.

主要方法:

  • 利用标记的现场记录和合成生成的地震图来训练DL模型.
  • 使用定量指标 (MSE,SSIM,R2) 评估模型性能.
  • 评估了地质可信性和对地质物理迁移图像的影响.

主要成果:

  • 在现场数据上训练的模型在所有指标上都胜过在合成数据上训练的模型.
  • 经过实地数据训练的模型产生了更具地质可信性的结果和更清晰的迁移图像.
  • 合成数据模型显示出潜力,但需要先进的技术来弥合领域的差距.
关键词:
深度学习是一种深度学习.现场数据 现场数据 现场数据反向问题是反向的问题.地震传播速度的速度.综合训练数据 综合训练数据

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结论:

  • 深度学习,特别是现场记录的地震图,可以显著提升速度模型构建工作流程.
  • 当现场数据有限时,合成数据可能是一个可行的替代方案,前提是应用领域专业知识.
  • 地球科学家的专业知识对于策划有效的合成数据集至关重要.