Numerical simulation of the glioblastoma growth in 3D microfluidic devices
The research presented in this study investigates the performance of two different approaches, namely the staggered approach and the coupled approach, in simulating growth glioblastoma cells in microfluidic devices. The main objective is to compare the accuracy and computational efficiency of these...
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| Format: | master thesis |
| Publication Date: | 2023 |
| Country: | España |
| Institution: | Universitat Politècnica de Catalunya (UPC) |
| Repository: | UPCommons. Portal del coneixement obert de la UPC |
| Language: | English |
| OAI Identifier: | oai:upcommons.upc.edu:2117/397888 |
| Online Access: | https://hdl.handle.net/2117/397888 |
| Access Level: | Open access |
| Keyword: | Differential equations, Partial Newton-Raphson method partial differential equations PDEs ordinary differential equation ODE coupled approach Equacions diferencials parcials Newton-Raphson, Mètode de Àrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi numèrica |
| Summary: | The research presented in this study investigates the performance of two different approaches, namely the staggered approach and the coupled approach, in simulating growth glioblastoma cells in microfluidic devices. The main objective is to compare the accuracy and computational efficiency of these approaches in various cases. The objective of this research is to enhance the efficiency and versatility of the coupled approach by introducing modifications that decouple highly coupled nonlinear equations in order to develop a staggered approach. The study focuses on identifying the appropriate scenarios and conditions where each approach can be effectively implemented. To achieve these goals, we begin by analyzing the coupled approach and identifying its limitations in terms of computational efficiency and flexibility. By decoupling the highly coupled equations, we aim to alleviate these limitations and improve the overall performance of analysis, specifically in terms of computational time. Through extensive experimentation and analysis, we establish the suitable situations and conditions where each approach excels. |
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