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Author:

Ye, C. (Ye, C..) | Liu, R. (Liu, R..) | Wu, X. (Wu, X..) | Liang, F. (Liang, F..) | Ying, M.T.C. (Ying, M.T.C..) | Lv, J. (Lv, J..)

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Scopus

Abstract:

Elastic compression stockings (ECSs) are essential for the prevention and treatment of venous disorders of the lower limbs. Finite element modeling (FEM) is an effective method for numerically analyzing ECS pressure performance for guiding ECS material design and pressure dose selection in treatment. However, existing FEM studies have primarily used the two-dimensional (2D) mechanical properties (i.e., properties along the wale and course directions) of ECS fabrics and ignored their three-dimensional (3D) mechanical properties (i.e., those along the thickness direction), causing deviations in pressure predictions. To address this limitation, the present study developed a new approach for determining the 3D mechanical properties of ECS fabrics through orthotropic theoretical analysis, analytical model development, FEM, and experimental testing and validation. The results revealed that the deviation ratios between the experimental and simulated pressure values of ECS fabrics was 19.3% obtained using the 2D material mechanical properties that was reduced to 10.3% obtained using the 3D material mechanical properties. Equivalently, the FEM simulation precision increased by 46.6%. These results indicate that the proposed approach can improve finite element analysis efficiency for ECS pressure prediction, thus facilitating the functional design of elastic compression materials for improving compression therapeutic efficacy. © 2022 The Authors

Keyword:

Mechanical properties Compression stockings Elastic compression materials Finite element modeling Pressure prediction

Author Community:

  • [ 1 ] [Ye C.]Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
  • [ 2 ] [Liu R.]Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
  • [ 3 ] [Liu R.]Laboratory for Artificial Intelligence in Design, Hong Kong Science Park, New Territories, Hong Kong
  • [ 4 ] [Wu X.]Laboratory for Artificial Intelligence in Design, Hong Kong Science Park, New Territories, Hong Kong
  • [ 5 ] [Liang F.]Department of Engineering Mechanics, Shanghai Jiao Tong University, Shanghai, China
  • [ 6 ] [Ying M.T.C.]Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
  • [ 7 ] [Lv J.]School of Fundamental Education, Beijing Polytechnic College, Beijing, China

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Source :

Materials and Design

ISSN: 0264-1275

Year: 2022

Volume: 217

8 . 4

JCR@2022

8 . 4 0 0

JCR@2022

JCR Journal Grade:1

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 6

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 13

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