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相关概念视频

Neuroplasticity01:01

Neuroplasticity

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Neuroplasticity reflects the brain's remarkable capacity to adapt and evolve, responding dynamically to learning, experiences, or injury by reorganizing its neural circuitry. This reorganization involves creating new neural connections and refining old ones through a series of biological processes that contribute to the brain's lifelong development and adaptability.
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Three-Dimensional Force System:Problem Solving01:30

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

Two-Dimensional Force System: Problem Solving

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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...
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相关实验视频

Updated: Jan 15, 2026

Soft Pneumatic Robot Modulates Graph Theory Metrics of Brain Network for Hand Rehabilitation After Stroke
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使用物理增强神经网络的适应性灵活结构的反向设计.

Moslem Mohammadi1, Abbas Z Kouzani1, Mahdi Bodaghi2

  • 1School of Engineering, Deakin University, Geelong, VIC, Australia.

Virtual and physical prototyping
|October 9, 2025
PubMed
概括

本研究介绍了机械元材料的高效反向设计框架,显著减少了计算时间. 新方法准确预测非线性反应,并使定制材料设计成为可能.

科学领域:

  • 机械工程 机械工程
  • 材料科学 材料科学 材料科学
  • 计算力学 计算力学 计算力学

背景情况:

  • 机械超材料表现出复杂的非线性行为,使传统的设计和分析过程漫长且计算密集.
  • 在拉力负荷下曲是这些材料非线性应变应力反应的关键因素.
  • 需要有效的设计方法来克服当前方法的局限性.

研究的目的:

  • 为机械超材料开发一个计算效率高的反向设计框架.
  • 准确预测非线性应变应激反应,包括曲行为.
  • 为了使金属材料结构的反向设计能够达到所需的刚性特征.

主要方法:

  • 在MATLAB/Simscape中使用灵活结构的减少顺序模型 (ROM) 进行设计和模拟.
  • 实施了在ROM结果上训练的物理增强神经网络 (PENN),以快速预测刚度曲线.
  • 采用进化优化来代地改进结构参数,以实现目标应变应激反应.

主要成果:

  • ROM模型在12核CPU上实现了平均4.5分钟的计算时间.
  • 经过训练的PENN模型在单核CPU上在不到一秒的时间内预测了刚度曲线,证明了显著的加速度.
  • 反向设计成功地产生了具有所需应变应激反应的超材料结构.
关键词:
通过3D打印打印3D打印.超材料是指一种超材料.一个曲的,曲的.灵活的结构灵活的结构.软机器人软机器人 软机器人

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  • 通过3D打印进行实验验证,证实了拟议方法的效率和有效性.

    • 结论:

    • 拟议的框架为设计具有非线性特征的机械元材料提供了一个计算效率高的替代方案.
    • ROM和PENN的集成加速了预测和反向设计过程.
    • 该方法经过实验验证,突出了其在创建定制元材料结构中的实际应用性.