Evaluating computational performances of hyperelastic models on supraspinatus tendon uniaxial tensile test data
محل انتشار: مجله مکانیک کاربردی محاسباتی، دوره: 52، شماره: 1
سال انتشار: 1400
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 238
فایل این مقاله در 17 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_JCAM-52-1_003
تاریخ نمایه سازی: 21 اردیبهشت 1400
چکیده مقاله:
Accurate modelling of the mechanical behaviour of tendon tissues is vital due to their essential role in the facilitation of joint mobility in humans and animals. This study focuses on the modelling of the supraspinatus tendon which helps to maintain dynamic stability at the glenohumeral joint in humans. It is observed that in sporting activities or careers that involve frequent arm abduction, injuries to this tendon are a common cause of discomfort. Therefore, this paper evaluates the relative modelling capabilities of three hyperelastic models, namely the Yeoh, Ogden and Martins material models on the tensile behaviour of three tendon specimens. We compare their fitting accuracies, convergence rates during optimisation, and the different forms of sensitivities to data-related features and initial parameter estimates. We find that the Martins model outperforms the other models in fitting accuracies; the Yeoh model has the most stable performance across all initial parameter estimates (with correlations above ۹۹ %) and has the fastest convergence rates (above ۲۰ and ۸ times as fast as the Ogden and Martins models’ rates, respectively); and that the Ogden model does not depend on differences in the topological features of the test data. The material parameters of relevant constitutive model may be used for further development of computational models.
کلیدواژه ها:
hyperelastic model ، tendon tensile behavior ، Sensitivity analysis ، strain energy density function
نویسندگان
Harry Ngwangwa
Biomechanics Research Group, Department of Mechanical and Industrial Engineering, School of Engineering, College of Science, Engineering and Technology, University of South Africa, Private Bag X۶, Florida, ۱۷۱۰, Johannesburg, South Africa.
F. Nemavhola
Biomechanics Research Group, Department of Mechanical and Industrial Engineering, School of Engineering, College of Science, Engineering and Technology, University of South Africa, Private Bag X۶, Florida, ۱۷۱۰, Johannesburg, South Africa.
مراجع و منابع این مقاله:
لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :