3 research outputs found
Petri Nets Modeling of Dead-End Refinement Problems in a 3D Anisotropic hp-Adaptive Finite Element Method
We consider two graph grammar based Petri nets models for anisotropic refinements of three dimensional hexahedral grids. The first one detects possible dead-end problems during the graph grammar based anisotropic refinements of the mesh. The second one employs an enhanced graph grammar model that is actually dead-end free. We apply the resulting algorithm to the simulation of resistivity logging measurements for estimating the location of underground oil and/or gas formations. The graph grammar based Petri net models allow to fix the self-adaptive mesh refinement algorithm and finish the adaptive computations with the required accuracy needed by the numerical solution
Petri Nets Modeling of Dead-End Refinement Problems in a 3D Anisotropic hp-Adaptive Finite Element Method
We consider two graph grammar based Petri nets models for anisotropic refinements of three dimensional hexahedral grids. The first one detects possible dead-end problems during the graph grammar based anisotropic refinements of the mesh. The second one employs an enhanced graph grammar model that is actually dead-end free. We apply the resulting algorithm to the simulation of resistivity logging measurements for estimating the location of underground oil and/or gas formations. The graph grammar based Petri net models allow to fix the self-adaptive mesh refinement algorithm and finish the adaptive computations with the required accuracy needed by the numerical solution
A summary of my twenty years of research according to Google Scholars
I am David Pardo, a researcher from Spain working mainly on numerical analysis
applied to geophysics. I am 40 years old, and over a decade ago, I realized that my performance as
a researcher was mainly evaluated based on a number called \h-index". This single number contains
simultaneously information about the number of publications and received citations. However, dif-
ferent h-indices associated to my name appeared in di erent webpages. A quick search allowed me
to nd the most convenient (largest) h-index in my case. It corresponded to Google Scholars.
In this work, I naively analyze a few curious facts I found about my Google Scholars and, at
the same time, this manuscript serves as an experiment to see if it may serve to increase my Google
Scholars h-index