An LSTM-driven thermoelectric coupling response prediction method for shape memory alloy actuators

An LSTM-driven thermoelectric coupling response prediction method for shape memory alloy actuators

Abstract Shape memory alloys (SMAs) show exceptional potential in actuator design due to their shape memory effect and superelasticity, yet their thermoelectric hysteresis challenges accurate modeling. This study proposes a hybrid framework integrating long short-term memory (LSTM) networks with phy...

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Bibliographic Details
Main Authors: Shaozhe Ding, Longbin Liu, Shifeng Zhang, Mingkun Li
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-025-02306-2
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