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相关概念视频

Deformation in a Circular Shaft01:10

Deformation in a Circular Shaft

1.0K
One of the distinctive characteristics of circular shafts is their ability to maintain their cross-sectional integrity under torsion. In other words, each cross-section continues to exist as a flat, unaltered entity, simply rotating like a solid, rigid slab. To understand the distribution of shearing stress within such a shaft, consider a cylindrical section inside this circular shaft. This section has a length of L and a radius of R, with one end fixed. The radius of the cylindrical section is...
1.0K
Transmission Shafts: Problem Solving01:09

Transmission Shafts: Problem Solving

553
Designing a solid shaft that transmits power from a motor to a machine tool involves a series of calculations to ensure the shaft can withstand the stresses applied by bending moments and torques. First, calculate the torque exerted on the gear, considering the power transmitted by the shaft and its rotational speed. Following this, compute the tangential forces acting on the gears, which directly relate to the torque and the gear radius.
Next, use bending moment diagrams for the shaft to...
553
Plastic Deformation in Circular Shafts01:20

Plastic Deformation in Circular Shafts

519
When materials are subjected to forces that surpass their yield strength, they undergo a process known as plastic deformation. This results in a permanent alteration or strain in their structure. This concept can be specifically applied to circular shafts, where the deformation leads to a change in its shape. The precise evaluation of this plastic deformation requires understanding the stress distribution within the circular shaft, which is achieved by calculating the maximum shearing stress in...
519
Stress Concentrations in Circular Shafts01:18

Stress Concentrations in Circular Shafts

623
Consider the elastic torsion formula, which applies to a circular shaft with a consistent cross-section. This formula assumes that the shaft's ends are loaded with rigid plates firmly attached. However, in many cases, torques are applied to the shaft through mechanisms like flange couplings or gears, which are connected by keys inserted into keyways. This application method modifies the stress distribution near the point of torque application, causing it to deviate from the distributions...
623
Design Example: Deciding Thickness of Lubricating Fluid in a Shaft01:23

Design Example: Deciding Thickness of Lubricating Fluid in a Shaft

372
Effective lubrication between a rotating shaft and its bearing housing is essential in rotating machinery to minimize friction, wear, and energy loss. With carefully controlled thickness and viscosity, the lubricant layer prevents metal-to-metal contact, ensuring smooth operation.
To calculate the required thickness of the lubricant layer, the tangential velocity at the shaft's surface must first be determined. This velocity is calculated by converting the rotational speed to angular velocity...
372
Thin-Walled Hollow Shafts01:15

Thin-Walled Hollow Shafts

644
In analyzing a thin-walled hollow shaft subjected to torsional loading, a segment with width dx is isolated for examination. Despite its equilibrium state, this segment faces torsional shearing forces at its ends. These forces are quantitatively described by the product of the longitudinal shearing stress on the segment's minor surface and the area of this surface, leading to the concept of shear flow. This shear flow is consistent throughout the structure, indicating a uniform distribution of...
644

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相关实验视频

Updated: Mar 15, 2026

Surrogate Model Development for Digital Experiments in Welding
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Surrogate Model Development for Digital Experiments in Welding

Published on: March 28, 2025

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对一个过程参数驱动的深度学习预测模型的研究,用于在轴接中的多物理场.

Chaolong Yang1, Zhiqiang Xu2, Feiting Shi3,4

  • 1College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China.

Materials (Basel, Switzerland)
|March 14, 2026
PubMed
概括
此摘要是机器生成的。

这项研究开发了机器学习模型,用于预测大型轮轴的接质量. 多层感知器 (MLP) 模型在预测温度,变形和残余应力方面取得了很高的准确性,超过了传统方法.

关键词:
在MLP深度学习模型中,变形变形的情况大的法兰轴轴.剩余压力是一种残留压力.温度的温度的温度的温度的温度.接过程参数 接过程参数

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Automatic Laser-based Geometry Capture for Finite Element Analysis of Weld Beads
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Automatic Laser-based Geometry Capture for Finite Element Analysis of Weld Beads

Published on: July 25, 2025

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相关实验视频

Last Updated: Mar 15, 2026

Surrogate Model Development for Digital Experiments in Welding
09:17

Surrogate Model Development for Digital Experiments in Welding

Published on: March 28, 2025

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Automatic Laser-based Geometry Capture for Finite Element Analysis of Weld Beads
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Automatic Laser-based Geometry Capture for Finite Element Analysis of Weld Beads

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科学领域:

  • 材料科学与工程 材料科学与工程
  • 计算力学 计算力学 计算力学
  • 人工智能的人工智能

背景情况:

  • 大面条轴是高端设备的关键部件,接质量直接影响性能和安全.
  • 传统的实验和有限元方法用于预测接的多物理场是耗时和低效的.

研究的目的:

  • 开发快速和准确的预测模型,用于接温度,变形和大轴的残余应力.
  • 将热机械合有限元模拟与机器学习相结合,以提高预测能力.

主要方法:

  • 使用有限元模拟生成了一个由100个过程参数组组成的数据集.
  • 构建和比较了包括MLP,RF,RBF-SVR,TabNet,XGBoost和FT-Transformer在内的机器学习模型.
  • 采用早期停止和退出等策略来缓解过度装配,用于验证的十倍交叉验证.

主要成果:

  • 该MLP模型表现出卓越的性能,准确预测高峰温度 (误差<5%),变形和残余应力 (误差<10%).
  • 最低压力模型与模拟值有很好的一致性,平均峰值余应力误差约为6MPa.
  • 随机森林 (RF) 模型排名第二,提供了良好的解释性和工程应用性.

结论:

  • 开发的MLP模型有效地复制了接的多物理场,允许快速预测和优化大型侧翼轴接.
  • 该研究强调了机器学习在预测接质量方面克服传统方法的局限性的潜力.
  • 未来的工作可以通过扩展数据集和结合实验验证来增强模型概括性.