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相关概念视频

Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

674
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...
674
Two-Dimensional Force System: Problem Solving01:29

Two-Dimensional Force System: Problem Solving

588
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...
588
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
Two-Dimensional Force System01:20

Two-Dimensional Force System

920
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:
920
Unsymmetric Loading of Thin-Walled Members: Problem Solving01:07

Unsymmetric Loading of Thin-Walled Members: Problem Solving

112
The shear center of a channel section with uniform thickness, height, and width, is determined by computing the shear force in the member and calculating the moments of inertia of the sections.
To compute the shear forces, find the shear flow at a specific distance from the endpoint using the vertical shear and the moment of inertia values. The total shear force on the flange is calculated by integrating the shear flow from one end of the flange to the other.
Next, calculate the moments of...
112
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

494
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...
494

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相关实验视频

Updated: Jul 12, 2025

Design and Optimization Strategies of a High-Performance Vented Box
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单层圆顶的结构优化使用代用基于物理的神经网络.

Hongyu Wu1, Yu-Ching Wu1, Peng Zhi1

  • 1Department of Structural Engineering, College of Civil Engineering, Tongji University, Shanghai, China.

Heliyon
|October 27, 2023
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的人工蜂群算法,该算法使用神经网络代用有限元素方法. 这种方法显著加快了单层圆顶结构最佳设计的计算效率.

关键词:
单层圆顶是一层层的.结构优化 结构优化人工蜂群算法的人工蜂群算法这是一种元启发式 (metaheuristic) 听证.神经网络代理基于模型的模型.

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科学领域:

  • 结构工程 结构工程
  • 计算力学 计算力学 计算力学
  • 在工程领域的人工智能.

背景情况:

  • 结构设计中的几何非线性优化问题是计算密集的.
  • 传统的有限元分析 (FEA) 可以成为复杂的优化任务的瓶.
  • 开发高效的替代模型对于加速结构设计过程至关重要.

研究的目的:

  • 开发一种新的人工蜂群算法,与使用神经网络的替代有限元素方法 (FEM) 集成.
  • 应用这种增强的算法来解决单层圆顶的几何非线性优化问题,包括大小,形状和拓优化.
  • 为了提高结构最佳设计的计算效率.

主要方法:

  • 创建和应用一个代用有限元素方法,结合物理信息的神经网络 (PINNs).
  • 在人工蜂群算法中使用前神经网络替代有限元分析.
  • 通过数值示例进行验证: 10 条杆架,拉梅拉圆顶和基维特圆顶.

主要成果:

  • 提出的方法证明了可行性和准确性,结果与现有文献非常一致.
  • 通过修改的人工蜂群算法,优化过程得到了相当大的加速.
  • 基于神经网络代理模型的模型显著提高了单层圆顶结构最佳设计的计算效率.

结论:

  • 神经网络代理模型与人工蜂群算法的集成为高效的结构优化提供了强大的方法.
  • 该方法有效地解决了单层圆顶设计中的几何非线性优化挑战.
  • 这项研究突出了人工智能驱动的代理建模的潜力,可以彻底改变计算结构工程.