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Multidisciplinary Design Optimization of a Nanorobot for Drug Delivery to Cancer Cells Based on Metaheuristic Algorithms

Kazembeigi, Saeideh | 2021

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 54653 (45)
  4. University: Sharif University of Technology
  5. Department: Aerospace Engineering
  6. Advisor(s): Abedian, Ali; Ghorbanian, Kaveh
  7. Abstract:
  8. This thesis is about multidisciplinary design optimization of MRI ¬controlled robots with a nonlinear model approach in the cardiovascular system and simulates its behavior to reach cancer cells. Such robots, designed to perform medical procedures with minimal side effects to the patient, include a set of ferromagnetic nanoparticles attached to the polymer and disposable drugs such as cancer drugs.The disciplines considered in this issue include structure, hydrodynamics, propulsion, controllability, and trajectory. The proposed model in this study, in addition to the main forces acting on the robot such as magnetic force, hydrodynamics, and apparent weight, also examines other forces due to the vessel wall such as contact, electrostatic, and stric forces. Also, in modeling the non-Newtonian behavior of blood, the effects of pulsed due to heart pumping and the effects of vessel wall on the parabolic profile of blood flow will be considered.The proposed model will analyze the types of robots and, finally, multidisciplinary design optimization of the robot based on a metaheuristic genetic algorithm to obtain the response space in the form of Pareto fronts. The objective functions for this design are: 1. Design the best geometry to achieve maximum propulsion force, minimum drag force, and maximum volume ¬to ¬surface ratio for the least required magnetic field, more controllability of the robot, and the ability to carry the maximum amount of drug to cancer cells, respectively. 2. Design the best path in different types of horizontal arteries to reach the object
  9. Keywords:
  10. Biomechanics ; Nonlinear Modeling ; Multi-Disciplinary Design Optimization ; Meta Heuristic Algorithm ; Targeted Druy Delivery ; Cancer Cells ; Magnetic Nanorobots

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