TY - JOUR
T1 - Controlled swelling-induced shape change of soft gel filled structures
AU - Monchetti, Silvia
AU - Brighenti, Roberto
AU - Hanuhov, Tamara
AU - Cohen, Noy
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2024/11
Y1 - 2024/11
N2 - Gels are polymers that can imbibe large amounts of solvent and generate large volumetric deformations in a process commonly termed swelling. The swelling-induced deformations can be harnessed to produce pressure against surrounding elastic elements, and therefore lead to spatial shape changes without the need for an external energy source. In the present paper, we consider a thin cylindrical elastic tube that encapsulates a gel and deforms in response to the swelling-induced forces. It is expected that by controlling the spatial stiffness distribution of the tube, the deformed swelling-induced shape can be programmed. We exploit this simple idea to obtain controlled shape change driven by the large volumetric expansion of gels. To this end, we train a machine learning algorithm through many FE simulations that enable solving the inverse problem: for any prescribed swelling-induced target shape, the algorithm provides the spatial stiffness distribution of the thin tube. The results confirm that precise controlled shape change is achievable by exploiting the large swelling-induced volumetric deformations in an autonomous manner (i.e. without the need for any external energy source). This work paves the way for new perspectives in the design of shape-change systems based on the simple yet proper elastic distribution of confining structures.
AB - Gels are polymers that can imbibe large amounts of solvent and generate large volumetric deformations in a process commonly termed swelling. The swelling-induced deformations can be harnessed to produce pressure against surrounding elastic elements, and therefore lead to spatial shape changes without the need for an external energy source. In the present paper, we consider a thin cylindrical elastic tube that encapsulates a gel and deforms in response to the swelling-induced forces. It is expected that by controlling the spatial stiffness distribution of the tube, the deformed swelling-induced shape can be programmed. We exploit this simple idea to obtain controlled shape change driven by the large volumetric expansion of gels. To this end, we train a machine learning algorithm through many FE simulations that enable solving the inverse problem: for any prescribed swelling-induced target shape, the algorithm provides the spatial stiffness distribution of the thin tube. The results confirm that precise controlled shape change is achievable by exploiting the large swelling-induced volumetric deformations in an autonomous manner (i.e. without the need for any external energy source). This work paves the way for new perspectives in the design of shape-change systems based on the simple yet proper elastic distribution of confining structures.
KW - Confined swelling
KW - Controlled shape change
KW - Gels
KW - Inverse problem
KW - Machine learning
KW - Volume expansion
UR - http://www.scopus.com/inward/record.url?scp=85200642207&partnerID=8YFLogxK
U2 - 10.1016/j.tws.2024.112280
DO - 10.1016/j.tws.2024.112280
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AN - SCOPUS:85200642207
SN - 0263-8231
VL - 204
JO - Thin-Walled Structures
JF - Thin-Walled Structures
M1 - 112280
ER -