Drift-Scale THC Seepage Model.

Technical Information Center Oak Ridge Tennessee

关键词: Radioactive waste facilities;    Mathematical models;    Environmental transport;    Yucca Mountain;    Validation;   

RP-ID  :  DE2005840428

学科分类：工程和技术（综合）

美国|英语

来源: National Technical Reports Library

【 摘 要 】

The purpose of this report (REV04) is to document the thermal-hydrologic-chemical (THC) seepage model, which simulates the composition of waters that could potentially seep into emplacement drifts, and the composition of the gas phase. The THC seepage model is processed and abstracted for use in the total system performance assessment (TSPA) for the license application (LA). This report documents the THC seepage model and a derivative used for validation, the Drift Scale Test (DST) THC submodel. The THC seepage model is a drift-scale process model for predicting the composition of gas and water that could enter waste emplacement drifts and the effects of mineral alteration on flow in rocks surrounding drifts. The DST THC submodel uses a drift-scale process model relying on the same conceptual model and many of the same input data (i.e., physical, hydrologic, thermodynamic, and kinetic) as the THC seepage model. The DST THC submodel is the primary means for validating the THC seepage model. The DST THC submodel compares predicted water and gas compositions, and mineral alteration patterns, with observed data from the DST. These models provide the framework to evaluate THC coupled processes at the drift scale, predict flow and transport behavior for specified thermal-loading conditions, and predict the evolution of mineral alteration and fluid chemistry around potential waste emplacement drifts. The DST THC submodel is used solely for the validation of the THC seepage model and is not used for calibration to measured data. The work scope for this report is summarized as follows: further develop the THC seepage model; use sensitivity analyses and model-data comparisons to evaluate model, data, and parameter uncertainties; validate the model by comparison of derivative cases with field and experimental data; perform simulations to predict the composition of fracture water that could potentially seep into repository emplacement drifts; submit modeling results to the Technical Data Management System (TDMS) and document the models; and evaluate model uncertainty and the propagation of uncertainty to other models.