Ciencias Exactas y Ciencias de la Salud
Permanent URI for this collectionhttps://hdl.handle.net/11285/551014
Pertenecen a esta colección Tesis y Trabajos de grado de los Doctorados correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.
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- A methodology for modeling multiscale multiphysics nature that bridges basic science with sustainable manufacturing technologies using human and Artificial intelligence(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-05-22) Estrada Diaz, Jorge Alfredo; Elías Zúñiga, Alex; emimmayorquin; Martínez Romero, Oscar; Palacios Pineda, Luis Manuel; Ruiz Huerta, Leopoldo; Escuela de Ingeniería y Ciencias; Campus Monterrey; Olvera Trejo, DanielThis dissertation deals with the modeling of multiscale multiphysics phenomena. These complex processes involve the interaction between physical occurrences of different nature, at different time and space scales, turning its description, prediction and control into a daunting task. Being pivotal technologies for the manufacturing of advanced materials, this work revolves around the complex technologies of Selective Laser Melting (SLM), electrospray, Ultrasonic Micro-Injection Molding (UMIM) and smart materials, i.e. Magneto-Rheological Elastomers (MRE). Modeling efforts are taken into action through classical yet powerful methodologies such as dimensional analysis and cutting-edge approaches such as fractal analysis and artificial intelligence, i.e., Artificial Neural Networks (ANNs) and Multiobjective Evolutionary Algorithms (MOEAs), with promising results that reflect on their ability to capture the intricate interplay of process parameters and material properties in these convoluted phenomena. Offering complementary benefits (attaining of meaningful physical insights and efficient handling computational processing operation and pattern identification in data, respectively) both approaches should be jointly exploited for handling multiscale multiphysics phenomena.
- Real-time simulation of mechanical properties on virtual reality: A methodology to improve geometric segmentation, mathematical modeling and characterization of soft tissues(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2022-06-14) Moreno Guerra, Mario Regino; ELIAS ZUÑIGA, ALEX; 19150; Elías Zúñiga, Alex; puemcuervo, emipsanchez; Martínez Romero, Oscar; Díaz Elizondo, José Antonio; Palacios Pineda, Luis Manuel; Escuela de Ingeniería y Ciencias; Campus Monterrey; Rodríguez González, Ciro AngelIn this research project, it is presented a methodology to achieve the development of technological tools and material knowledge that support the real-time simulation of soft tissues for virtual reality. Particularly, this work is focused on two main areas that were identified in previous work as opportunities for improvement: Geometrical and Material Modeling. These areas are key to develop not only medical training processes, but also other research projects that involve soft tissue and composite materials characterization, design and development of biomedical devices, and augmented reality tools, among others. As one of the goals, it is proposed to create virtual tools that allow the interaction, processing, and segmentation of medical images in a semi-automatic way. This was detected by questioning how to increase the applicability of the simulation framework to other anatomical geometries and simplify the creation of new and customized medical cases based on their own set of images. The solution proposed is to provide the user with access to an interactive learning experience based on 3D rendering of medical images. This will not only allow visualization of medical cases but also have a relatively quick and simple process to get anatomically realistic 3D geometries for simulation, design of new products or 3D printing of models. In this path, it was developed the module VISUALIX, which is able to provide said interaction, and the results are presented in chapter 4. Also, a proposal for fractal structure analysis was done using microtomography images, creating FractalCells module with the implemented tools. For material modeling and characterization of soft tissue, a new hybrid formulation is proposed by questioning how a simple technique like Spring-Mass Model (SMM) can describe the soft tissue mechanical properties, if it is based on linear elasticity theory and therefore it can only be used to predict small deformations (<10%). The solution proposed is based on the application of a constitutive model able to describe the mechanical behavior of soft tissue, as well as other composite materials. For this purpose, it is created a hybrid construction of a Strain Energy Density Function (SEDF) used to find an energy equivalence with a variable stiffness SMM. This formulation was named Equivalent Energy Spring Model (EESM) and is Abstract ii presented in chapter 5. It is able to characterize soft tissue properties of non-linearity, anisotropy, and Mullin’s effect, to predict its response at large deformation (>10%). Finally, and in order to validate the proposed model, an experimental phase was defined to perform uniaxial and biaxial cyclical tensile tests with porcine tissue samples in order to have experimental data for material characterization using EESM. This experimental phase is described in chapter 6. The results for the characterization of porcine liver and abdominal wall tissues, as well as the predictions of the EESM formulation are presented in chapter 7, including an evaluation of its accuracy and its capacity to perform in real-time.