Tesi etd-03072025-114609
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Tipo di tesi
Dottorato
Autore
BRAZIL NARDIN, ANDERSON
URN
etd-03072025-114609
Titolo
Advanced Simulation Approaches for Architected Structures-Based Continuum
Settore scientifico disciplinare
ING-IND/34
Corso di studi
Istituto di Biorobotica - PHD IN BIOROBOTICA
Commissione
Presidente Prof.ssa MAUD MARCHAL
Membro Prof.ssa CECILIA LASCHI
Membro Dott. DURIEZ, CHRISTIAN
relatore BECCAI, LUCIA
Membro FALOTICO, EGIDIO
Membro Prof.ssa CECILIA LASCHI
Membro Dott. DURIEZ, CHRISTIAN
relatore BECCAI, LUCIA
Membro FALOTICO, EGIDIO
Parole chiave
- architected structures
- continuum manipulators
- bioinspired robotics
- nonlinear modeling
- simulation framework
Data inizio appello
25/08/2025;
Disponibilità
parziale
Riassunto analitico
Bioinspired soft robotic systems have gained considerable interest in recent years, driven by the demand for safer interactions and adaptable behavior in unstructured environments. This shift has placed increasing emphasis on materials with nonlinear responses and on robotic structures featuring complex internal architectures, such as continuum and lattice-based morphologies capable of large deformations, tunable stiffness, and mechanical resilience.
This thesis addresses the modeling challenges posed by such systems through a comprehensive simulation framework comprising three core contributions: a strain-dependent, piecewise formulation of Young’s modulus to capture spatial variations in stiffness within architected materials; the application of parallel execution strategies to significantly reduce computation time during large-scale parametric studies; and the development of a scalable modeling workflow capable of handling both localized unit cell analyses and full-system robotic simulations. These contributions are integrated into an open-source simulation environment, enhancing the modeling capabilities currently available to the soft robotics research community.
Technologically, the work introduces a tool that enables material property updates under mechanical load, validated against experimental observations and real-time sensor feedback. Scientifically, the thesis evaluates the trade-offs between multiple modeling strategies—including homogenization, high-resolution solid finite element modeling, and parameter sweeps—to identify appropriate approaches based on structural scale, actuation mode, and design requirements.
Together, the results highlight how advanced simulation tools can support the design and evaluation of soft robots with non-uniform geometry and material distribution. The thesis proposes a robust set of computational strategies to address the geometric, material, and functional variability characteristic of large-scale soft robotic systems, bridging the gap between numerical modeling and practical robotic implementation.
This thesis addresses the modeling challenges posed by such systems through a comprehensive simulation framework comprising three core contributions: a strain-dependent, piecewise formulation of Young’s modulus to capture spatial variations in stiffness within architected materials; the application of parallel execution strategies to significantly reduce computation time during large-scale parametric studies; and the development of a scalable modeling workflow capable of handling both localized unit cell analyses and full-system robotic simulations. These contributions are integrated into an open-source simulation environment, enhancing the modeling capabilities currently available to the soft robotics research community.
Technologically, the work introduces a tool that enables material property updates under mechanical load, validated against experimental observations and real-time sensor feedback. Scientifically, the thesis evaluates the trade-offs between multiple modeling strategies—including homogenization, high-resolution solid finite element modeling, and parameter sweeps—to identify appropriate approaches based on structural scale, actuation mode, and design requirements.
Together, the results highlight how advanced simulation tools can support the design and evaluation of soft robots with non-uniform geometry and material distribution. The thesis proposes a robust set of computational strategies to address the geometric, material, and functional variability characteristic of large-scale soft robotic systems, bridging the gap between numerical modeling and practical robotic implementation.
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