Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

628
A three-dimensional force system refers to a scenario in which three forces act simultaneously in three different directions. This type of problem is commonly encountered in physics and engineering, where it is necessary to calculate the resultant force on the system, which can then be used to predict or analyze the behavior of the object or structure under consideration.
To solve a three-dimensional force system, first resolve each force into its respective scalar components. Do this using...
628
Three-Dimensional Force System01:30

Three-Dimensional Force System

2.0K
In mechanical engineering, a three-dimensional force system is a system of forces acting in three dimensions, with forces applied along the x, y, and z coordinate axes. The three-dimensional force system is an important concept in mechanical engineering, as it allows engineers to understand and analyze the behavior of objects and structures in three dimensions. By understanding the forces acting on a system, engineers can design more efficient and effective mechanical systems that can withstand...
2.0K
Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

215
Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the...
215
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

465
In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...
465
Two-Dimensional Force System: Problem Solving01:29

Two-Dimensional Force System: Problem Solving

542
Solving problems related to two-dimensional force systems is an essential aspect of mechanics and engineering. By applying the principles of vector analysis and force equilibrium, one can determine the effect of multiple forces acting on an object in a two-dimensional space.
The first step to solving a two-dimensional force system problem is to draw a free-body diagram of the object under consideration. This diagram helps identify all the external forces acting on the object, including their...
542
Two-Dimensional Force System01:20

Two-Dimensional Force System

873
A two-dimensional system in mechanical engineering involves the analysis of motion and forces in a plane. A two-dimensional force vector can be resolved into its components as:
873

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Predict neuromuscular performance in human epidural electrical stimulation: phase 1 trial interim results.

Communications medicine·2026
Same author

Deep brain-machine interfaces: sensing and modulating the human deep brain.

National science review·2023
查看所有相关文章

相关实验视频

Updated: Jun 6, 2025

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump
09:04

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump

Published on: June 1, 2022

3.0K

生物启发的多维深度融合学习用于预测动态航空航天推进系统.

Michael Qian Vergnolle1, Eastman Z Y Wu2, Yanan Sui1

  • 1School of Aerospace Engineering, Tsinghua University, Beijing, China.

Communications engineering
|November 29, 2024
PubMed
概括

一个新的深度学习模型TimeWaves通过分析全球趋势和本地周期性来准确预测动态系统. 这种先进的预测方法提高了航空航天安全,特别是在预测火箭燃烧不稳定的情况下.

更多相关视频

Author Spotlight: Development of an Automated Camera-Based System for Real-Time Blast Overpressure Monitoring and TBI Risk Assessment in Military Training
06:20

Author Spotlight: Development of an Automated Camera-Based System for Real-Time Blast Overpressure Monitoring and TBI Risk Assessment in Military Training

Published on: December 6, 2024

2.6K
A Rapid Method for Modeling a Variable Cycle Engine
04:58

A Rapid Method for Modeling a Variable Cycle Engine

Published on: August 13, 2019

7.5K

相关实验视频

Last Updated: Jun 6, 2025

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump
09:04

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump

Published on: June 1, 2022

3.0K
Author Spotlight: Development of an Automated Camera-Based System for Real-Time Blast Overpressure Monitoring and TBI Risk Assessment in Military Training
06:20

Author Spotlight: Development of an Automated Camera-Based System for Real-Time Blast Overpressure Monitoring and TBI Risk Assessment in Military Training

Published on: December 6, 2024

2.6K
A Rapid Method for Modeling a Variable Cycle Engine
04:58

A Rapid Method for Modeling a Variable Cycle Engine

Published on: August 13, 2019

7.5K

科学领域:

  • 航空航天工程 航空航天工程
  • 人工智能的人工智能
  • 动态系统分析 动态系统分析

背景情况:

  • 预测动态系统对于航空航天安全至关重要.
  • 现有的方法往往侧重于全球趋势,忽视时间序列数据中的本地周期性.
  • 航空航天推进数据在有限的时间范围内表现出明显的动态周期性.

研究的目的:

  • 开发一种深度学习模型,TimeWaves,能够捕捉动态系统中的全球趋势和本地变化.
  • 为了提高具有固有的周期性的时间序列数据的预测准确性.
  • 为了应对预测火箭燃烧不稳定的挑战.

主要方法:

  • 开发了TimeWaves,这是一个使用3D光谱导向区间提取的深度学习模型.
  • 通过共享的参数融合算法进行集成的里埃和波形分析.
  • 使用TwinBlock实现双向学习工作流程,以实现高效的多尺度特征感知.

主要成果:

  • 时间波有效地捕获时间序列数据中的全球趋势和本地变化.
  • 该模型在预测火箭燃烧不稳定性方面表现强.
  • 通过降低计算成本实现了动态多尺度特征的增强感知.

结论:

  • 时间波为预测具有周期性的动态系统提供了一种新且有效的方法.
  • 该模型显著改善了对关键航空航天现象的预测,例如火箭燃烧不稳定性.
  • 这种深度学习框架为提高航空航天任务安全性和效率提供了可靠的工具.