Waste management facility accident analysis (WASTE ACC) system: software for analysis of waste management alternatives
Conference
·
OSTI ID:206839
This paper describes the Waste Management Facility Accident Analysis (WASTE{underscore}ACC) software, which was developed at Argonne National Laboratory (ANL) to support the US Department of Energy`s (DOE`s) Waste Management (WM) Programmatic Environmental Impact Statement (PEIS). WASTE{underscore}ACC is a decision support and database system that is compatible with Microsoft{reg_sign} Windows{trademark}. It assesses potential atmospheric releases from accidents at waste management facilities. The software provides the user with an easy-to-use tool to determine the risk-dominant accident sequences for the many possible combinations of process technologies, waste and facility types, and alternative cases described in the WM PEIS. In addition, its structure will allow additional alternative cases and assumptions to be tested as part of the future DOE programmatic decision-making process. The WASTE{underscore}ACC system demonstrates one approach to performing a generic, systemwide evaluation of accident risks at waste management facilities. The advantages of WASTE{underscore}ACC are threefold. First, the software gets waste volume and radiological profile data that were used to perform other WM PEIS-related analyses directly from the WASTE{underscore}MGMT system. Second, the system allows for a consistent analysis across all sites and waste streams, which enables decision makers to understand more fully the trade-offs among various policy options and scenarios. Third, the system is easy to operate; even complex scenario runs are completed within minutes.
- Research Organization:
- Argonne National Lab., IL (United States)
- Sponsoring Organization:
- USDOE, Washington, DC (United States)
- DOE Contract Number:
- W-31109-ENG-38
- OSTI ID:
- 206839
- Report Number(s):
- ANL/DIS/CP--89084; CONF-960212--32; ON: DE96006913
- Country of Publication:
- United States
- Language:
- English
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