PNNL

Abstract

This document provides a user’s guide for Hanford Soil Inventory Model (SIM) Rev. 2. and the software portfolio developed to maintain it. The Hanford SIM application computes waste discharges composed of 75 analytes at 377 waste sites (liquid disposal, unplanned releases, and tank farm leaks) over an operational period of approximately 50 years. A computer model capable of calculating inventories and the associated uncer¬tainties as a function of time was identified to address the needs of the Remediation and Closure Science (RCS) Project. This user’s guide is a companion document to a report on the requirements, conceptual model, simulation, methodology, testing, and quality assurance associated with Hanford SIM Rev. 2. To estimate mass-balanced contaminant inventories and their uncertainties for the Hanford Site post-closure setting, a stochastic simulation method (a Monte Carlo-type calculation) was selected to provide estimates of inventory and uncertainty. The Open Crystal Ball (OCB) statistical package was selected in 2002 for application in this model. The principal outcome of this effort is the upgrade of the software suite to the latest versions of OCB and Crystal Ball (CB), to make the modeling capability available to the broader technical community. This version of Hanford SIM requires the user to have Crystal Ball v7.x and Microsoft Office 2003. This model will be available to U.S. Department of Energy (DOE) offices, DOE contractors, and those wishing to review the technical basis for and simulation of inventories appearing in Hanford assessments. The design of Hanford SIM is highly modular, with separate data input (Microsoft Excel) and calculation engine (OCB.dll) files administered through an interface application that acquires the inputs, manages the data reporting, and creates the output files. Each data input is considered an independent variable; therefore, the waste stream composition/properties and waste stream discharge histories for the waste disposal sites can be examined and developed using a variety of source data (e.g., historical process data, tank waste modeling) and assumptions without affecting other variables.