GDSA framework: Among those participating in the workshop is Sandia National Laboratories, which, along with its partner national laboratories, will use the workshop to compare its Geologic Disposal Safety Assessment (GDSA) software framework to the software codes developed by their international peers.
The Sandia-led GDSA framework is a computer modeling system designed to simulate the coupled processes affecting radionuclide mobilization and transport in deep geologic repositories and to perform forward propagation of uncertainty calculations. The framework has been applied to generic repository concepts in salt, argillite, and crystalline rock, as well as deep borehole disposal concepts.
The GDSA framework is built on two Sandia software packages: PFLOTRAN, an open-source software that models how chemicals react and how liquids and gases flow underground, and Dakota, which specializes in uncertainty sampling and sensitivity analysis.
Other Department of Energy national laboratories involved in developing the GDSA framework and the DECOVALEX initiative include Argonne, Idaho, Lawrence Berkeley, Lawrence Livermore, Los Alamos, Oak Ridge, and Pacific Northwest national laboratories.
The workshop: The international workshop teams will compare the safety-assessment models they developed for two reference repository cases, one in a salt formation and the other in crystalline rock. Each case comes with a set of key questions, which took about two years of discussion to fully define, along with the details of the hypothetical repository, according to Sandia National Laboratories.
Emily Stein, a Sandia manager overseeing the development of the framework, said that comparing the results of the GDSA framework against the results from other teams’ software will build confidence in the software and models. Specifically, the teams will compare the results of their models to see if there is a consensus reached by multiple teams. Then the models that produced different results will be studied to try to determine why their results were different.
“This type of comparison, where we’re all starting with the same two problem descriptions and are developing numerical models around them, is one important way to create confidence in safety assessment models and the tools we’re using to do the simulations,” Stein said. “We can’t actually take this big, full million-year simulation and compare it to a real-world experiment of the same scale. It’s a very important exercise.”
