WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7150

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Access Right: Closed AccessSubject: search.filters.subject.Finite Element Model

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  • Article
    A Fiber-Driven Finite Element Model for Predicting Residual Limb Soft Tissue Deformation: Applications in Prosthetic Socket Design
    (Springer, 2025) Mihçin, Şenay; Qiu, Ziyan; Tang, Lei; Huang, Fuhao; Wei, Pingping; Mihcin, Senay; Li, Dichen; 01. Izmir Institute of Technology; 03. Faculty of Engineering; 03.10. Department of Mechanical Engineering
    PurposeChanges in residual limb volume and shape pose significant challenges in achieving and maintaining an accurate and comfortable fit for prosthetic socket. While numerous techniques for measuring residual limb volume have been proposed, their clinical application remains limited by insufficient resolution and the inability to perform in-socket measurements. To address this issue, this study develops a novel method for predicting residual limb soft tissue deformation to guide prosthetic socket design.MethodsA three-dimensional (3D) finite element (FE) model of the human thigh was developed to simulate the soft tissue deformation during daily activities, driven by muscle contraction to replicate natural biomechanics. The model included hard tissue and muscle components, with the muscle modeled as a structure of evenly distributed, contractile fibers that generate movement. Parameters controlling fiber contraction were iteratively adjusted to best match the calculated tissue deformation and that observed in physical muscle models.ResultsThe optimized FE model significantly improved the accuracy of predicting dynamic soft tissue deformation, with average errors of 0.83% and 1.86% for tissue expansion and contraction regions, respectively. For various gait patterns, the average differences in equivalent volume and cross-sectional area changes were also less than 0.83% and 1.86%, respectively.ConclusionThe model demonstrated consistent prediction accuracy across different gait data. The fiber-driven soft tissue model developed offers a valuable tool for pre-design simulations of prosthetic sockets and orthoses. It is equally applicable to other wearable devices that interface with the skin, providing a robust framework for improving device design and functionality.
  • Article
    Citation - WoS: 1
    Citation - Scopus: 1
    Reliability Assessment of Structures With Bayesian Model Updating Accelerated Via Polynomial-Chaos Metamodeling
    (Taylor & Francis Ltd, 2025) Hızal, Çağlayan; Aktaş, Engin; Aktas, Engin; 03.03. Department of Civil Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    Finite element models are often preferred in numerical modeling of structures, but model assumptions lead to inaccuracies and uncertainties. Measuring these is necessary to determine the reliability and accuracy of the numerical model. This has led to the development of FE model update methods that aim to calibrate the numerical model based on data obtained by structural health monitoring (SHM). However, a general framework that provides a realistic life cycle performance assessment of structures by efficiently incorporating monitored data into structural identification has not yet been impeccably presented. Bayesian modeling can characterize uncertain structural parameters as random variables and provide a systematic methodology for integrating a probabilistic SHM framework into model updating. Unfortunately, these lead to complex and time-consuming, causing limitations in their application. Metamodeling techniques which are effective stochastic predictors can be used to decrease the computational burden in the model updating. This study aims at adapting Polynomial-Chaos-Kriging metamodeling technique integrate to Bayesian model updating process to overcome the computational difficulties and reduce different source of uncertainty with using SHM, then, make more accurate reliability assessment. Therefore, an experimental study is used to assess reliability of structure that is exposed to different types of corrosion effects.