X-ray micro tomography and computer-code coupling for modeling physical systems

X-ray micro tomography and computer-code coupling for modeling physical systems

Announcement Date : Feb 3 , 2016


Innovation:X-ray micro tomography and computer-code coupling for modeling physical systems

Author: Rodrigo Guadarrama Lara

Description: To better understand the phenomenology involved in physical systems present in nature, an important tool is the numerical representation of such systems to simulate, study and predict their behavior. Computational simulations have been used for several years to represent mutual interactions between fluids and solid objects with regular geometries (cylinders and spheres). Continuous scientific and technological advances have allowed the
implementation and combination of various methodologies for the development of multi- phase systems.

Since 2013 I have been working on my doctoral studies focused on the continuous development, coupling algorithm implementation and validation of an existent computational programme based on two methodologies known as Discrete Element Method (DEM) and Lattice Boltzmann Method (LBM). This coupling is an alternative to traditional methodologies since it considers a mesoscopic approach (i.e. between macroscopic and microscopic). Furthermore, X-ray micro tomography (XMT) has been used to obtain digital images of objects with irregular geometries (e.g. small solid particles and sand grains) for use in DEM- LBM simulations with the intention of producing more accurate data and results, and understand the effects that such geometries have on the systems under study.

Profit, Social Impact: The benefit provided by these simulations is reflected in different areas such as academic, research and development, and in the cement, petrochemical, pharmaceutical, food and mining industries, to name a few. When on-site tests are not possible or when numerous experiments are necessary but costly, simulations provide an effective tool for data generation and visualization in a relatively short period of time and at low cost. Likewise, analysis of systems using the methodology previously described results in the potential quality improvement of a product, the optimal use of materials and process optimization.