Multi-objective optimization of a multi-field actuated, multilayered, segmented flexible composite beam

Abstract

Multi-layered, self-actuated devices have been the focus of recent studies due to their ability to exhibit large displacements and achieve complex shapes. Such devices have been constructed using active materials responsive to varying stimuli including electro-active and magneto-active materials to perform useful functions and achieve a wider variety of target shapes compared to single-field actuated unimorph/bimorph structures. However, fabrication of these devices for experimentation is time-consuming and expensive, which warrants the use of simulations as a means of designing high-performing structures. This work seeks to optimize structures employing materials response to magnetic and electric fields for multiple objective functions selected based on the needs of soft robotics applications such as grippers. A multi-objective optimization problem is constructed, utilizing a model developed for any arbitrary number of segments, layers, and material types, accommodating for large displacements and simultaneously applied fields. Three objective functions are chosen: (1) target shape approximation, based on the errors between the coordinates of the computed and desired shapes, (2) cost based on volume of magnetic material, and (3) work performed on a tip-force. The arbitrary optimization problem is reduced to a specific case study containing eight segments to alleviate the computational cost of an unwieldy number of parameters. The parameters are narrowed to: (1) segment lengths, (2) magnetic material in each magneto-active layer. The structure is pre-set to three material types: electro-active polymer, magneto-active elastomer, and a passive substrate. The case study's optimization problem is performed by a genetic algorithm developed by MATLAB for multiple objective functions. The results of the optimization on the case study are analyzed by studying the feasible designs on the Pareto front of the objective functions. Different trade-offs between objective functions are identified, and various feasible designs are found more suitable than others, based on the needs and priorities of an application.

Event identification in acoustic emission from wire breaks in pre-stressing/post-tensioning cables

“…Multi-objective optimization methods can find one or a set of optimal solutions within the feasible space of an optimization problem. NSGA-II, proposed by Deb et al [59], is a well-known low-cost multiobjective evolutionary algorithm that is widely used in engineering problems [60][61][62][63][64][65]. NSGA-II was employed in this study to address the issue of an optimal number of features for wire break detection.…”

Review of composite – laminated material analysis in MATLAB using Piezo – electric sensor and actuator

“…A genetic algorithm developed by MATLAB for various objective functions induces a multi-objective optimizing problem and the execution of an optimization problem in a case study. In the case study Erol et al [51], optimization outcomes are examined by analyzing the alternative designs of the optimization problem on the Pareto interaction. Different trade-offs are calculated between the thematic roles, and, depending on application demands and preferences, different feasible designs are considered to be more desirable than others.…”

Analytical modeling of a multilayer, multimorph lithium-ion battery actuator

“…Previous work with multilayer, multifield actuation is conducted by Erol et al (2020). They investigate the multi-objective optimization of the actuated shape of a segmented, multilayer, and multi-field actuator.…”

“…electroactive, magnetoactive, pneumatic, etc.). Electroactive materials require an externally applied electric field (Pelrine et al, 2000); magnetoactive materials require a magnetic field (Erol et al, 2020); soft pneumatic actuators (SPAs) require pumps and tubes (Huang et al, 2020); and liquid crystalline elastomers require stimulation by temperature, light, or electric fields (Ohm et al, 2010). This ability to not require continuous external input, but to also power an external load, makes energy storage based actuators strong candidates for mobile applications and applications with minimal accessibility.…”