Postdoctoral Researcher, Computational Research Division
Current Affiliation and Research Interests
I am a postdoctoral researcher at the Center for Computational Sciences and Engineering (CCSE) in the Applied Mathematics Department of the Computational Research Division, a part of the Computing Sciences Directorate at the Lawrence Berkeley National Laboratory.
As part of my work in the Multiscale Modeling and Stochastic Systems (MuMSS) group, I am currently studying the use of compressible fluctuating hydrodynamic schemes for the modeling of gas flows through effusive membranes. We are also developing codes for the simulation of particle laden, fluctuating, incompressible flows. This will provide a platform for the study of fluids with novel rheological properties.
In late 2016 I completed my PhD in applied mathematics at the University of Melbourne. I then spent the following year as a Postdoctoral Research Fellow in the ARC Centre for Excellence in Exciton Science, also based at the University of Melbourne. In these roles I developed methods for solving the Boltzmann equation in the context of nanoscale transport problems.
Daniel. R. Ladiges, Andrew. J. Nonaka, John. B. Bell, and Alejandro. L. Garcia, On the Suppression and Distortion of Non-Equilibrium Fluctuations by Transpiration, Phys. Fluids, 149, 052002, 2019.
Daniel R. Ladiges and John E. Sader. Variational method enabling simplified solutions to the linearized Boltzmann equation for oscillatory gas flows. Physical Review Fluids, 3, 053401, 2018.
Daniel R. Ladiges and John E. Sader. Frequency-domain deviational Monte Carlo method for linear oscillatory gas flows. Physics of Fluids, 27, 102002, 2015.
Daniel R. Ladiges and John E. Sader. Frequency-domain Monte Carlo method for linear oscillatory gas flows. Journal of Computational Physics, 284, 351-366, 2015.