Optimization of parameters for ab initio molecular dynamics simulation of displacement cascades
Examensarbete för masterexamen
Nuclear engineering, MSc
Radiation can affect a material in many ways. Knowledge of this is vital in choosing the right material for application wherein the material is subjected to radiation. In nuclear fission reactors, materials inside the reactor vessel are exposed to radiations of all kinds. It is important to study their interaction with the materials because they affect the microstructure of the materials which in turn has a devastating effect on the macroscopic properties of the materials. With increase in computational power we have turned to Density Function Theory (DFT), semi-empirical Molecular Dynamics (MD) and other types of simulations to study the effect which can be verified with experimental techniques up to a certain extent. The aim of this thesis is to perform the first-ever simulations of displacement cascades using ab initio molecular dynamics (AIMD). To run these extremely costly simulations, it is paramount to first optimize various input parameters. Iron was chosen as it is widely used for structural components in reactors (as steel alloys). The optimizing simulations were done using MD simulations with semi-empirical Embedded atom method (EAM) potential in BCC iron with different input parameters including energy of the primary knock on atom (PKA), position of the PKA relative to damped boundary conditions, number of atoms, direction of the PKA and damping effects. It is essential to optimize because simulating large number of atoms significantly increases the time required for the simulation which also makes it more expensive to carry out the MD simulations. The other parameters are interrelated. For example, simulating with a high energy PKA in a small set of atoms distorts the results making them unacceptable. Damping coefficients also have to be optimized for the investigation as a strong damping will essentially quench the lattice. From the MD simulations, we could identify the ideal parameters. The influence of the number of atoms was found to be the most significant parameter which in turn decides the maximal PKA energy that can be simulated ab initio. The largest cell size that is possible to use with our current computer allocations is around 4000 atoms, limiting the maximal PKA energy to about 500 eV.
Energi , Grundläggande vetenskaper , Hållbar utveckling , Innovation och entreprenörskap (nyttiggörande) , Annan naturvetenskap , Annan teknik , Annan medicin och hälsovetenskap , Andra lantbruksrelaterade vetenskaper , Annan samhällsvetenskap , Annan humaniora , Energy , Basic Sciences , Sustainable Development , Innovation & Entrepreneurship , Other Natural Sciences , Other Engineering and Technologies , Other Medical Sciences , Other Agricultural Sciences , Other Social Sciences , Other Humanities