Numerical simulation of nonlinear material behaviour: Application to sports bra design

Liang, Ruixin; Yip, Joanne; Yu, Winnie; Chen, Lihua; Lau, Newman

doi:10.1016/j.matdes.2019.108177

Cited by 14 publications

(25 citation statements)

References 21 publications

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“…Based on preliminary calculations with different element lengths, the geometric model of the body contained a total of 119,510 elements, in which the model of the breasts had 22,931 elements. The methods for building and validating the FE contact models for the interaction between the body and sports bra made reference to our previous study (Liang et al , 2019), which provided the basis of this paper.…”

Section: Finite Element Model and Verificationmentioning

confidence: 99%

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Computational modelling methods for sports bra–body interactions

Liang¹,

Yu²,

Chen

et al. 2020

IJCST

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PurposeThe breasts are mainly fatty and connective tissues with no muscles that directly support them, so wearing sports bras is one of the most effective means of alleviating the discomfort of breast movement and potential injury during vigorous physical exercise. However, the design and development processes of traditional sports bras are time-consuming and costly. Hence, a novel method of simulating the static contact pressure between a sports bra and women’s body based on the finite element (FE) and artificial neural network (ANN) models is developed in this study to contribute to the design considerations of sports bras.Design/methodology/approachThree-dimensional FE models of a female subject and sports bras with different fabric properties are developed to determine the amount of contact pressure exerted onto the body. The FE results are then verified by measuring the amount of pressure exerted by the sports bra on the skin with pressure sensors. The Taguchi technique is used to effectively reduce the number of trials from 625 to only 25 cases. These 25 results obtained through FE modelling are then used to provide the training set for the ANNs. Finally, a comparison between the FE and ANN results is carried out.FindingsA novel model of the static contact pressure between a sports bra and human subject based on the FE and ANN methods is presented in this paper. The root mean square error values show that there is only a small difference between the FE and ANN results.Originality/valueThe ANN function established in this study can be used to predict the mechanical behaviours of breasts and has a fundamental impact on the computer-aided design of functional garments in general.

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Section: Finite Element Model and Verificationmentioning

confidence: 99%

“…To simulate the contact pressure between the sports bra and body, the first problem that had to be solved is penetration. To do so, the model of the body was first geometrically reduced and then expanded, and the process is shown in Figure 4 (Liang et al , 2019).…”

Section: Finite Element Model and Verificationmentioning

confidence: 99%

Computational modelling methods for sports bra–body interactions

Liang¹,

Yu²,

Chen

et al. 2020

IJCST

Self Cite

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“…Recently, considerable progress has been made on the finite element models (FEMs) of breast deformation in recent years. 10,11 Li et al built a threedimensional (3D) biomechanical FEM consisting of elastic breast, rigid body, and bra to simulate the bra-breast interaction. 12 Liang et al simulated the static and dynamic contact FEM that consists of a body and sports bra.…”

mentioning

confidence: 99%

“…12 Liang et al simulated the static and dynamic contact FEM that consists of a body and sports bra. 10 Sun et al constructed FEM including a rigid torso, deformable breast, and bra without underwire. 11 However, these simplified geometric components involved in the FEM cannot be accurate enough to observe global breast mechanics.…”

mentioning

confidence: 99%

Non-linear finite element model established on pectoralis major muscle to investigate large breast motions of senior women for bra design

Zhang

Lau

Sun

et al. 2022

Textile Research Journal

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This paper presents a three-dimensional nonlinear biomechanical finite element model to simulate elderly breast deformation under arm abduction. The finite element model was constructed based on complex anatomical structures that consist of the soft tissues including torso, breast, pectoralis major muscle, and rigid bones including humerus, sternum, clavicle and ribs. The elderly breast was defined as material nonlinearity and geometric nonlinearity. The computational model can simulate and illustrate the deformation of soft tissues during arm abduction from 30° to 90°. The finite element model was validated by motion data. The Young’s modulus for the clavicular portion and the sternocostal portion of the pectoralis major muscle was characterized as 0.1 MPa and 0.08 MPa, respectively. Besides this, the finite element model presented here features the musculoskeletal system for breast deformation and reveals the synergistic relationship between the breast and the pectoralis major muscle. A questionnaire was conducted to analyze the importance of purchasing factors and the discomfort positions in a sports bra from the perspective of senior women. Combined with the finite element model results, this study provides a promising basis for the design of sports bras in an ergonomic way.

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“…The criterion of the differences is the root mean square error (RMSE) given in Eq. 1 19,21,22. ) 𝑒𝑒𝑒𝑒 Eq.…”

mentioning

confidence: 99%

Finite Element-Based Machine Learning Method to Predict Breast Displacement during Running

Liang

Yip

et al. 2021

AATCC Journal of Research

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This paper presents an effective method to simulate the dynamic deformation of the breasts when a sports bra is worn during physical activity. A subject-specific finite element (FE) model of a female subject is established, and the accuracy of the material coefficients of the model is analyzed. An FE model of the sports bra is also built based on a commercially-available compression sports bra with a vest style. Then, an FE contact model between the body and bra is developed and validated, and the results applied to train a neural network model for predicting breast displacement based on bra straps with different tensile moduli. In this study, a four-layer neural network with a backpropagation algorithm (a Levenberg-Marquardt learning algorithm) is used. A comparison of the FE and machine learning results shows that machine learning can well predict the dynamic displacement of the breasts in a more time-efficient and convenient manner.

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Numerical simulation of nonlinear material behaviour: Application to sports bra design

Cited by 14 publications

References 21 publications

Computational modelling methods for sports bra–body interactions

Computational modelling methods for sports bra–body interactions

Non-linear finite element model established on pectoralis major muscle to investigate large breast motions of senior women for bra design

Finite Element-Based Machine Learning Method to Predict Breast Displacement during Running

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