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Modeling, Control and Application of Smart Materials

Submission Deadline: 31 March 2026 (closed) View: 566 Submit to Special Issue

Guest Editors

Prof. Zhaobo Chen

Email: hitchenzb@163.com

Affiliation: School of Mechanical and Electrical Engineering, Harbin Institute of Technology, Harbin 150001, China

Homepage:

Research Interests: vibration control based on smart materials

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Prof. Jiaxi Jin

Email: jinjiaxixz@163.com

Affiliation: School of Mechanical and Electrical Engineering, Harbin Institute of Technology, Harbin 150001, China

Homepage:

Research Interests: modeling of piezoelectric actuators and active vibration control

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Summary

Smart materials, characterized by their ability to respond dynamically to external stimuli (e.g., temperature, stress, electric/magnetic fields), have revolutionized fields such as robotics, aerospace, biomedical engineering, and energy harvesting. Their unique properties—including shape memory, self-healing, and piezoelectricity—enable groundbreaking applications, from adaptive structures to precision sensors. However, challenges persist in modeling their nonlinear behaviors, optimizing control strategies, and bridging theoretical advances with real-world implementations. This Special Issue seeks to address these gaps by compiling cutting-edge research on smart materials, fostering interdisciplinary collaboration to unlock their full potential.

This Special Issue, "Modeling, Control and Application of Smart Materials," aims to showcase high-quality theoretical and experimental studies that advance the understanding and utilization of smart materials. We invite contributions that explore novel modeling techniques, innovative control methodologies, and transformative applications across scales. Topics of interest include but are not limited to:
Modeling: Multiscale simulations, constitutive models, and machine learning approaches for smart material behavior.
Control: Adaptive control, real-time feedback systems, and optimization algorithms for material performance.
Applications: Case studies in healthcare (e.g., artificial muscles), energy (e.g., piezoelectric harvesters), and smart infrastructure (e.g., vibration damping).
The scope aligns with CMES's focus on computational methods, engineering systems, and cross-disciplinary solutions.

Suggested Themes
Contributions may cover, but are not restricted to, the following themes:
Advanced Modeling Techniques:
· Multiphysics coupling (electro-thermo-mechanical, etc.).
· Data-driven and AI-aided modeling of smart material dynamics.
Control Strategies:
· Robust and adaptive control for hysteresis compensation.
· Autonomous systems leveraging smart material actuators.
Emerging Applications:
· Biomedical devices (e.g., drug delivery systems, prosthetics).
· Sustainable energy solutions (e.g., energy-harvesting pavements).
Fabrication and Characterization:
· Novel manufacturing methods (4D printing, nanocomposites).
· Experimental validation of smart material performance.


Keywords

smart materials, shape memory alloys, piezoelectric materials, adaptive control, multiphysics modeling, energy harvesting, hysteresis compensation, biomedical applications

Published Papers


  • Open Access

    ARTICLE

    A Numerical Framework for Flexible–Electrical Coupled Analysis of Piezoelectric Structures with Large Deformations

    Xuan Sun, Yueying Zhu, Jiaxi Jin, Zhitong Li, Leizhi Wang, Zhaobo Chen
    CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2026.078891
    (This article belongs to the Special Issue: Modeling, Control and Application of Smart Materials)
    Abstract Piezoelectric smart materials have been widely used in applications such as soft robotic actuation, vibration control and sensing of aerospace structures. In such contexts, the smart structures are typically subjected to significant large deformations and strong electromechanical coupling effects, which pose considerable challenges for conventional analytical approaches and classical finite element models in accurately predicting their nonlinear dynamic responses and capturing multiphysics coupling behaviors. To address these challenges in modeling and analysis, this work develops a flexible–electrical coupled computational framework with a unified mesh description based on the absolute nodal coordinate formulation (ANCF). This coupling… More >

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