Nuclear Energy Advanced Modeling and Simulation (NEAMS) waste Integrated Performance and Safety Codes (IPSC) : gap analysis for high fidelity and performance assessment code development.

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 chemical processes 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 non-radioactive contaminants, and they need to be adapted to account for radionuclide decay and in-growth. 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 high-fidelity 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