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Related Concept Videos

Plastic Deformations01:19

Plastic Deformations

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Plastic deformation represents a fundamental concept in materials science, which explains the irreversible change in the shape of a material when it experiences stress beyond its elastic capability. This phenomenon is important in structural engineering, especially in designing and analyzing cantilever beams—structures that are securely fixed at one end and bear loads at the opposite end. When these beams are subjected to loads within their elastic range, they will return to their...
474
Plastic Deformations01:14

Plastic Deformations

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It is essential to understand how structural members behave under plastic deformation when the bending stress exceeds the material's yield strength. This state of deformation permanently alters the shape of the member, in contrast to the linear elastic behavior observed before yielding. The strain at any point in the member is expressed in terms of maximum strain. Notably, the neutral axis, which coincides with the centroid during elastic bending, shifts away from the centroid under plastic...
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Temperature Dependent Deformation01:12

Temperature Dependent Deformation

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In a nonhomogeneous rod made up of steel and brass, restrained at both ends and subjected to a temperature change, several steps are involved in calculating the stress and compressive load. Due to the problem's static indeterminacy, one end support is disconnected, allowing the rod to experience the temperature change freely. Next, an unknown force is applied at the free end, triggering deformations in the rod's steel and brass portions. These deformations are then calculated and added...
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Deformations in a Symmetric Member in Bending01:18

Deformations in a Symmetric Member in Bending

526
When analyzing the deformation of a symmetric prismatic member subjected to bending by equal and opposite couples, it becomes clear that as the member bends, the originally straight lines on its wider faces curve into circular arcs, with a constant radius centered at a point known as Point C. This phenomenon helps to understand the stress and strain distribution within the member more clearly.
When the member is segmented into tiny cubic elements, it is observed that the primary stress...
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Deformation of Member under Multiple Loadings01:11

Deformation of Member under Multiple Loadings

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When a rod is made of different materials or has various cross-sections, it must be divided into parts that meet the necessary conditions for determining the deformation. These parts are each characterized by their internal force, cross-sectional area, length, and modulus of elasticity. These parameters are then used to compute the deformation of the entire rod.
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Flapping Soft Fin Deformation Modeling using Planar Laser-Induced Fluorescence Imaging
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[Study on Prediction Model of Soft Tissue Deformation during Needle Insertion].

Dedong Gao, Guangwei Zhao, Shan Wang

    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi = Journal of Biomedical Engineering = Shengwu Yixue Gongchengxue Zazhi
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    Summary

    Researchers developed a polyvinyl alcohol (PVA) hydrogel model to simulate soft tissue deformation during flexible needle insertion. A back propagation neural network accurately predicted tissue displacement, improving insertion accuracy.

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    Area of Science:

    • Biomedical Engineering
    • Materials Science
    • Computational Modeling

    Background:

    • Simulating soft tissue is crucial for understanding medical device interactions.
    • Flexible needle insertion requires precise control to avoid tissue damage.
    • Existing methods for predicting tissue deformation have limitations.

    Purpose of the Study:

    • To develop a quantitative model for soft tissue deformation during flexible needle insertion.
    • To evaluate the accuracy of a back propagation neural network in predicting tissue displacement.
    • To assess the impact of the predictive model on improving needle insertion accuracy.

    Main Methods:

    • Polyvinyl alcohol (PVA) hydrogel was fabricated to mimic human soft tissue properties.
    • Markers were embedded in the hydrogel, and their displacements were tracked using an image acquisition system.
    • A back propagation (BP) neural network was trained to model the Y-direction displacement based on marker data.

    Main Results:

    • The BP neural network model achieved a fitting degree above 95% compared to experimental data.
    • The maximum relative error for valid data was limited to 30%, with a maximum absolute error of 0.8mm.
    • The model demonstrated quantitative prediction capabilities for soft tissue deformation.

    Conclusions:

    • The developed PVA hydrogel effectively simulates soft tissue for experimental analysis.
    • The BP neural network provides a reliable method for quantitatively predicting soft tissue deformation.
    • This predictive modeling approach can enhance the accuracy of flexible needle insertion procedures.