Nuclear Energy Advanced Modeling and Simulation (NEAMS) Waste Integrated Performance and Safety Codes (IPSC): Gap Analysis for High Fidelity and Performance Assessment Code Development « ECIS « Downloads
This report describes a gap analysis performed in the process of developing the Waste Integrated
Performance and Safety Codes (IPSC) in support of the U.S. Department of Energy (DOE)
Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) Campaign. The goal
of the Waste IPSC is to develop an integrated suite of computational modeling and simulation
capabilities to quantitatively assess the long-term performance of waste forms in the engineered
and geologic environments of a radioactive waste storage or disposal system. The Waste IPSC
will provide this simulation capability (1) for a range of disposal concepts, waste form types,
engineered repository designs, and geologic settings, (2) for a range of time scales and distances,
(3) with appropriate consideration of the inherent uncertainties, and (4) in accordance with
rigorous verification, validation, and software quality requirements.
The gap analyses documented in this report were are performed during an initial gap analysis to
identify candidate codes and tools to support the development and integration of the Waste IPSC,
and during follow-on activities that delved into more detailed assessments of the various codes
that were acquired, studied, and tested. The current Waste IPSC strategy is to acquire and
integrate the necessary Waste IPSC capabilities wherever feasible, and develop only those
capabilities that cannot be acquired or suitably integrated, verified, or validated.
The gap analysis indicates that significant capabilities may already exist in the existing THC
codes although there is no single code able to fully account for all physical and chemicalprocesses involved in a waste disposal system. Large gaps exist in modeling chemical processes
and their couplings with other processes. The coupling of chemical processes with flow transport
and mechanical deformation remains challenging. The data for extreme environments (e.g., for
elevated temperature and high ionic strength media) that are needed for repository modeling are
severely lacking. In addition, most of existing reactive transport codes were developed for nonradioactive
contaminants, and they need to be adapted to account for radionuclide decay and ingrowth.
The accessibility to the source codes is generally limited. Because the problems of
interest for the Waste IPSC are likely to result in relatively large computational models, a
compact memory-usage footprint and a fast/robust solution procedure will be needed. A robust
massively parallel processing (MPP) capability will also be required to provide reasonable
turnaround times on the analyses that will be performed with the code.
A performance assessment (PA) calculation for a waste disposal system generally requires a
large number (hundreds to thousands) of model simulations to quantify the effect of model
parameter uncertainties on the predicted repository performance. A set of codes for a PA
calculation must be sufficiently robust and fast in terms of code execution. A PA system as a
whole must be able to provide multiple alternative models for a specific set of physical/chemical
processes, so that the users can choose various levels of modeling complexity based on their
modeling needs. This requires PA codes, preferably, to be highly modularized. Most of the
existing codes have difficulties meeting these requirements.
Based on the gap analysis results, we have made the following recommendations for the code
selection and code development for the NEAMS waste IPSC: (1) build fully coupled highfidelity
THCMBR codes using the existing SIERRA codes (e.g., ARIA and ADAGIO) and
platform, (2) use DAKOTA to build an enhanced performance assessment system (EPAS), and
build a modular code architecture and key code modules for performance assessments. The key
chemical calculation modules will be built by expanding the existing CANTERA capabilities as
well as by extracting useful components from other existing codes.