Irving Reyna Nolasco
Postdoctoral Researcher at Johns Hopkins University
King Abdullah University of Science and Technology (KAUST)
United States
Hi, I'm Irving Reyna Nolasco!
Postdoctoral Researcher at Johns Hopkins University
Expert in Scientific Computing: Highly skilled in Computational Fluid Dynamics (CFD) and high-order numerical methods for solving partial differential equations, with a robust background in scientific computing. Extensive Experience: Over ten years of experience in computational physics, specializing in the development of computational tools for the simulation and visualization of physical phenomena. Proficient in multiple programming languages, including C, Fortran, Python, CUDA, and MPI. Mathematical Application and Numerical Simulation: Passionate about applying mathematical concepts and developing numerical simulations to address significant problems in both basic science and industrial applications. Focus on Fluid Mechanics and Aerospace Engineering: Attracted to challenging problems in aerospace engineering, fluid mechanics, and nonlinear dynamics. Demonstrates a keen interest in leveraging machine learning, GPU computing, and high-performance computing to push the boundaries of current technologies.
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Experience
Johns Hopkins University
Postdoctoral Researcher
December 2023 - Present
Developed of scientific tools for the simulation, analysis, and visualization of high-speed compressible flows using high-order finite difference methods on structured curvilinear grids. Simulated particle interaction with high-speed compressible flows and comparison with experimental data.
King Abdullah University of Science and Technology
McLaren F1 Racing Team–KAUST partnership
October 2018 - December 2022
Developed computational tools to visualize and analyze data from turbulent flow simulations with a high-order DG solver. Generated high-order mesh of geometries from a F1 car model with the mesh generation software Pointwise. Implemented proper boundary conditions simulating a full F1 car to run with an entropy stable high-order DG solver.
King Abdullah University of Science and Technology
Research Scholar at the Extreme Computing Research Center
August 2018 - November 2023
Analyzed the computational performance and numerical solution capabilities of high-order schemes for compressible turbulent flows with basic tests cases and tests of industrial interest. Generated high-order unstructured grids of complex geometries for flow simulations. Developed scientific tools for visualization and statistical analysis of numerical solutions of compressible flows.
King Abdullah University of Science and Technology
Visiting Student
August 2016 - November 2016
Developed a 3D finite volume solver for the Euler equations on CPU with Fortran and GPU with CUDA C and PyCUDA. Simulated astrophysical gas dynamics with this solver. Implemented MPI techniques on the finite volume solvers (CPU and GPU versions) for gas dynamics simulations on the supercomputer Shaheen II.
Institute of Nuclear Sciences, UNAM
Research student
January 2016 - July 2017
Developed a 2D and 3D structured finite volume solver for the Euler equations on CPU with the Fortran language on Cartesian and cylindrical coordinates for the simulation of astrophysical jets. Extended a finite volume code to run on a multi-core environment with MPI libraries.
Institute of Physical Sciences, UNAM–Cuernavaca
Research student
January 2013 - December 2015
Implemented Fortran libraries in an N-body simulation code for the proper initial conditions of planetary formation simulations. Implemented statistical tools for data analysis and visualization with Python and Julia for N-body simulation data.
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English
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