>> Prof. Dapino wins the 2017 ASME Adaptive Structures and Material Systems Award

Prof. Dapino was named the 2017 recipient of the ASME Adaptive Structures and Material Systems Award. Dapino joins a prestigious list of past winners of this award, which was established by the Aerospace Division as a division-level award in 1993 and elevated to a Society Award in 2014.

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The Adaptive Structures and Material Systems Award recognizes significant contributions to the sciences and technologies associated with adaptive structures and/or materials systems. The award is intended to honor a lifetime of achievement and sustained impact in the field. The ASME Adaptive Structures and Material Systems Award recognizes Dapino’s “outstanding contributions to the sciences and technologies associated with smart materials, including undergraduate and graduate education, fundamental scholarly research, and the successful transition of academic research to industry applications.”

>> Prof. Dapino wins the Distinguished Graduate Faculty Award of the Department of Mechanical and Aerospace Engineering

Dapino was named the recipient of the 2017 Distinguished Graduate Faculty Award from the Department of Mechanical and Aerospace Engineering.


The Distinguished Graduate Faculty Award was created in 2014 by the Mechanical Engineering External Advisory Board to recognize those who consistently work to foster a superior culture for graduate student mentoring.


Marcelo Dapino (left) and Marcello Canova (right) are the recipients of the Department of Mechanical and Aerospace Engineering’s 2017 faculty awards, presented by the Mechanical External Advisory Board.

>> “Globally convergent nonlinear 3D inverse model for smart materials with hessian-based optimization” appeared in Computer Methods in Applied Mechanics and Engineering

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A globally convergent and fully coupled 3D inverse model for smart materials is presented. In practice, stress and field (electric, magnetic, or temperature) are applied to smart materials whereas strain and flux density (electric, magnetic, or temperature) are measured. We refer to constitutive models that follow this scheme as direct models. In certain design and control situations, however, inverse models are necessary in which the field and stress are found from specified flux density and strain. This inversion typically involves an iterative procedure, which may be prone to convergence issues. An inverse model approach is proposed for arbitrary smart materials. The inversion requirement is a continuous and second order differentiable direct model for any chosen smart material. The approach is globally convergent, which makes it ideal for use in finite element frameworks. The premise of the proposed iterative system model is to constitute a recursive correction formula based on second order approximations of a novel scalar error function which offers a faster convergence rate. A continuation approach is then used to achieve global convergence for arbitrary input parameters. Magnetostrictive Galfenol is chosen to illustrate the effectiveness of the inverse model, and compact analytical derivations of the Jacobian and Hessian matrices are presented. The convergence rate of the proposed approach is superior to that of an existing inverse model. Finally, the inverse model’s robustness is demonstrated through integration of the model into a finite-element framework to simulate a magnetostrictive composite plate actuator in full 3D.

 

H. TARI and M.J. Dapino, “Globally convergent nonlinear 3D inverse model for smart materials with hessian-based optimization,” Computer Methods in Applied Mechanics and Engineering, 318 (2017), 864-881, May 2017.