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

Transmission-Line Differential Equations01:26

Transmission-Line Differential Equations

1.0K
Transmission lines are essential components of electrical power systems. They are characterized by the distributed nature of resistance (R), inductance (L), and capacitance (C) per unit length. To analyze these lines, differential equations are employed to model the variations in voltage and current along the line.
Line Section Model
A circuit representing a line section of length Δx helps in understanding the transmission line parameters. The voltage V(x) and current i(x) are measured from...
1.0K
Separable Differential Equations01:20

Separable Differential Equations

93
A separable differential equation is a type of first-order differential equation where the derivative dy/dx can be expressed as a product of two functions: one that depends only on x and another that depends only on y. This allows for the rearrangement of the equation so that all terms involving y are on one side, and all terms involving x are on the other. This process, known as the separation of variables, simplifies the process of solving the equation by enabling the integration of both...
93
Introduction to Differential Equations01:20

Introduction to Differential Equations

134
A differential equation is a mathematical expression that establishes a relationship between a function and its derivatives. These equations are fundamental in modeling dynamic systems across various fields of science and engineering. The order of a differential equation is defined by the highest order derivative present in the equation. A first-order differential equation includes only the first derivative, while a second-order differential equation includes up to the second derivative of the...
134
Modeling with Differential Equations01:25

Modeling with Differential Equations

84
Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
84
Linear Differential Equations01:27

Linear Differential Equations

83
The integrating factor method provides a systematic way to solve first-order linear differential equations, especially those that cannot be handled by separation of variables. This method is particularly useful in modeling time-dependent physical systems influenced by both constant inputs and resistive forces. A common example is the motion of a car subjected to a constant engine force while experiencing air resistance proportional to its velocity.In such scenarios, Newton’s second law...
83
Differential Equations: Problem Solving01:21

Differential Equations: Problem Solving

77
When analyzing the motion of falling objects, it is essential to consider not only the force of gravity but also the opposing force of air resistance. A practical example involves releasing a heavy test weight during a safety check on a ship. As the weight falls from rest, gravity accelerates it downward while air resistance exerts an upward force that increases with velocity. This dynamic interplay of forces is well described by differential equations, which provide a mathematical framework...
77

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 journal

Computational modeling of immersed non-spherical bodies in viscous flows to study embolus-hemodynamics interactions in large-vessel occlusion stroke.

Engineering with computers·2026
Same journal

IGANets: Isogeometric analysis networks and their applications to linear structural analysis problems.

Engineering with computers·2026
Same journal

Parameterized shape optimization of a bi-leaflet heart valved conduit for pediatric applications.

Engineering with computers·2026
Same journal

A computational framework to predict the spreading of Alzheimer's disease.

Engineering with computers·2026
Same journal

Implicit sub-stepping scheme for critical state soil models.

Engineering with computers·2026
Same journal

Isogeometric suitable coupling methods for partitioned multiphysics simulation with application to fluid-structure interaction.

Engineering with computers·2026
查看所有相关文章

相关实验视频

Updated: Feb 5, 2026

The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time
06:05

The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time

Published on: February 19, 2021

1.8K

基于密度的拓优化的微分方程驱动的更新策略:使用 MATLAB 代码实现.

Yang Liu1, Wei Tan1

  • 1School of Engineering and Materials Science, Queen Mary University of London, London, E1 4NS UK.

Engineering with computers
|February 4, 2026
PubMed
概括
此摘要是机器生成的。

这项研究介绍了一种基于微分方程的新方法,用于拓优化. 它增强了基于密度的方法,提供了更具响应性的设计过程,以提高工程应用中的性能.

关键词:
密度方法密度方法.微分方程的不同方程.在 MATLAB 代码中,使用的是 MATLAB 代码.拓优化拓的优化更新计划 更新计划

更多相关视频

Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging
11:38

Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging

Published on: October 4, 2024

1.1K
Isolation of High-density Lipoproteins for Non-coding Small RNA Quantification
10:39

Isolation of High-density Lipoproteins for Non-coding Small RNA Quantification

Published on: November 28, 2016

11.8K

相关实验视频

Last Updated: Feb 5, 2026

The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time
06:05

The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time

Published on: February 19, 2021

1.8K
Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging
11:38

Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging

Published on: October 4, 2024

1.1K
Isolation of High-density Lipoproteins for Non-coding Small RNA Quantification
10:39

Isolation of High-density Lipoproteins for Non-coding Small RNA Quantification

Published on: November 28, 2016

11.8K

科学领域:

  • 工程 工程师 工程师 工程师
  • 计算力学 计算力学 计算力学
  • 材料科学 材料科学 材料科学

背景情况:

  • 拓优化通常使用边界驱动的方法,如水平集方法.
  • 微分方程也可以应用于基于密度的拓优化.

研究的目的:

  • 呈现一个新的设计更新方案,使用微分方程进行拓优化.
  • 探索绝对增量格式相对于传统相对增量格式的好处.

主要方法:

  • 制定一个设计更新方案,使用微分方程来演变元素密度.
  • 将微分方程转换为绝对增量格式,类似于最佳性标准 (OC) 方法.
  • 实施和解释MATLAB代码,以尽量减少复合材料和单一材料的合规性.

主要成果:

  • 绝对增量格式提供了一个更积极和响应的优化过程.
  • 拟议的方案有效地解决了密度分布优化问题的问题.
  • 数字示例验证了该计划在合规最小化方面的表现.

结论:

  • 微分方程驱动的进化策略可以有效地用于基于密度的拓优化.
  • 绝对增量格式为经典密度方法提供了一个有前途的替代方案,可能导致更优质的设计.
  • 提出的方法为拓优化任务提供了一个可行的替代方案.