Numerical Modeling and Simulation

Master powerful numerical discretization techniques such as FEM, FVM, and FDM to simulate structures, fluids, and heat transfer. Learn to utilize simulation software such as ANSYS and MATLAB.

• This course is aimed at PhD candidates from engineering and technology disciplines, but is also open to postdoc fellows if seats are available.
• PhD candidates from UiT and other universities may be admitted to the course. PhD candidates who are not registered at UiT must upload a document from their university stating that they are registered as PhD candidates.

If there are 5 applicants or fewer, the course responsible will evaluate whether the course will take place.

In addition to the general admission requirements for the PhD program at UiT, the following prior knowledge is recommended:

• Applied mathematics, physics, numerical methods, and partial differential equations.

Upon successful completion of the course, the following learning outcomes are expected to be achieved:

Knowledge:

• Advanced knowledge of the fundamental principles of numerical modeling and simulation, including governing equations for structures, fluid flow, and heat transfer.
• Understanding and comparing the main numerical discretization techniques (FEM, FVM, and FDM) and justify the choice of method for a given engineering problem.
• Specialized understanding of stability, convergence, and error estimation in numerical analysis, enabling critical evaluation of simulation results.
• Knowledge of numerical modeling in relation to experimental and analytical methods for validation purposes.

Skills:

• Can independently discretize and solve partial differential equations (PDEs) for structural, thermal, and fluid systems using FEM, FVM, and FDM.
• can implement and modify simulation workflows in software such as ANSYS® and MATLAB®, including mesh generation, boundary condition setup, and post-processing.
• Can critically assess numerical accuracy, computational efficiency, and resource requirements of different simulation approaches.
• Can communicate and defend the modeling approach, results, and interpretation in an oral examination setting.

Competence:

• Can evaluate and apply numerical modeling as a research tool for solving open-ended, multidisciplinary engineering problems.
• Can identify the limitations and uncertainties of numerical simulations and integrate this understanding into research design and publication.
• Demonstrates the ability to use numerical simulation to generate new knowledge and contribute to the scientific community within engineering science.

Learning types: Acquisition (20%), Practice (20%), Discussion (10%), Investigation (20%), Production (20%), and Collaboration (10%)

Activities: Lectures and workshops

Language of instruction and examination

Schedule

More info about the coursework requirements

More info about the oral exam

Re-sit examination