GoldSim

GoldSim
Developer(s) GoldSim Technology Group LLC
Stable release GoldSim Version 10.5 SP2 / September 22, 2011
Written in C++
Operating system Windows
Type Simulation software
License Proprietary
Website www.goldsim.com

GoldSim is dynamic, probabilistic simulation software developed by GoldSim Technology Group. This general-purpose simulator is a hybrid of several simulation approaches, combining an extension of system dynamics with some aspects of discrete event simulation, and embedding the dynamic simulation engine within a Monte Carlo simulation framework.

While it is a general-purpose simulator, GoldSim has been most extensively used for high-profile environmental and engineering risk analysis, with applications in the areas of water resource management [1] [2] ,[3] mining [4] [5] ,[6] radioactive waste management [7] [8] [9] ,[10] and most recently, geological carbon sequestration [11] [12] and aerospace mission risk analysis [13] .[14]

Contents

History

In 1990, Golder Associates, an international engineering consulting firm, was asked by the United States Department of Energy (DOE) to develop probabilistic simulation software that could be used to help with decision support and management within the Office of Civilian Radioactive Waste Management. The results of this effort were two DOS-based programs (RIP and STRIP), which were used to support radioactive waste management projects within the DOE.

In 1996, in an effort funded by Golder Associates, the US DOE, the Japan Nuclear Cycle Development Institute (currently the Japan Atomic Energy Agency) and the Spanish National Radioactive Waste Company (ENRESA), the capabilities of RIP and STRIP were incorporated into a general purpose Windows-based simulator called GoldSim. Subsequent funding was also provided by NASA.

Initially only offered to the original funding organizations, GoldSim was released to the public in 2002. In 2004, GoldSim Technology Group LLC was spun off from Golder Associates and is now a wholly independent company.[15]

Recent notable applications include providing the simulation framework for: 1) the Yucca Mountain Repository Performance Assessment model developed by Sandia National Laboratories;[7][8] 2) a long-term water management model of California’s Central Valley, developed by the California Department of Water Resources (DWR) and U.S. Bureau of Reclamation;[1][2] 3) a comprehensive system-level computational model for performance assessment of geological sequestration of CO2 developed by Los Alamos National Laboratory;[11] and 4) models for simulating risks associated with future manned space missions in NASA’s Constellation program developed by NASA Ames Research Center.[13][14]

Modeling Environment

GoldSim provides a visual and hierarchical modeling environment, which allows users to construct models by adding “elements” (model objects) that represent data, equations, processes or events, and linking them together into graphical representations that resemble influence diagrams. Influence arrows are automatically drawn as elements are referenced by other elements. Complex systems can be translated into hierarchical GoldSim models by creating layer of “containers” (or sub-models). Visual representations and hierarchical structures help users to build very large, complex models that can still be explained to interested stakeholders (e.g., government regulators, elected officials, and the public).

Though it is primarily a continuous simulator, GoldSim has a number of features typically associated with discrete simulators. By combining these two simulation methods, systems that are best represented using both continuous and discrete dynamics can often be more accurately simulated. Examples include tracking the quantity of water in a reservoir that is subject to both continuous inflows and outflows, as well as sudden storm events; and tracking the quantity of fuel in a space vehicle as it is subjected to random perturbations (e.g., component failures, extreme environmental conditions).

Because the software was originally developed for complex environmental applications, in which many inputs are uncertain and/or stochastic, in addition to being a dynamic simulator, GoldSim is a Monte Carlo simulator, such that inputs can be defined as distributions and the entire system simulated a large number of times to provide probabilistic outputs [16] . As such, the software incorporates a number of computational features to facilitate probabilistic simulation of complex systems, including tools for generating and correlating stochastic time series, advanced sampling capabilities (including latin hypercube sampling and importance sampling), and support for distributed processing.[17]

References

  1. ^ a b CalLite: Central Vally Water Management Screening Model (2009), State of California, Department of Water Resources Web site.
  2. ^ a b Elaine Rundle (2009), California Water Resources Uses CalLite Risk Simulation, Government Technology.
  3. ^ Joe Volpe and Charlie Voss (2005), Using Dynamic System Models for Water Use Accountability and Planning In Georgia, Proceedings of the 2005 Georgia Water Resources Conference, held April 25–27, 2005, at the University of Georgia.
  4. ^ Tobias Puhlmann, Charles Voss, Juliana Esper, and Rodrigo Dutra Amaral (2006), Development And Operation Of A Water Balance At Rio Paracatu Mineração, Brazil, Proceedings of the 7th International Conference on Acid Rock Drainage (ICARD), March 26–30, 2006, St. Louis MO. R.I. Barnhisel (ed.) Published by the American Society of Mining and Reclamation (ASMR).
  5. ^ Ted Eary, Jody Eshleman, Ryan Jakubowski and Andrew Watson (2008), Applying Numerical Hydrochemical Models as Decision Support Tools for Mine Closure Planning, presented at Tailings and Mine Waste ’08, October 19–22, 2008, Vail, Colorado.
  6. ^ Jan Vermaak and Paul Lindsay (2006), A Numerical Model to Simulate the Effectiveness of Remedial Measures Aimed at Reducing Acidity and Metal Concentrations in the Ngakawau River and its Tributaries Near Stockton Coal Mine, West Coast, New Zealand, Proceedings of Water in Mining 2006, November 14–16, 2006, Brisbane, Australia.
  7. ^ a b David Ewing Duncan (2003), Do or Die at Yucca Mountain, Wired Magazine, Issue 11.04, April 2003.
  8. ^ a b US Department of Energy, Office of Civilian Radioactive Waste Management. (2008). Final Supplemental Environmental Impact Statement for a Geologic Repository for the Disposal of Spent Nuclear Fuel and High-Level Radioactive Waste at Yucca Mountain, Nye County, Nevada. Reports can be downloaded from DOE Web site (hyperlink above). Details on the usage of GoldSim in YMP are given in FY01 Supplemental Science and Performance Analyses.
  9. ^ Patrick D. Mattie, Robert G. Knowlton & Bill W. Arnold. (2007). A User’s Guide to the GoldSim/BLT-MS Integrated Software Package: A Low-Level Radioactive Waste Disposal Performance Assessment Model. Sandia Report (SAND2007-1354)
  10. ^ D. Vopálka, D. Lukin and A. Vokál (2006), Modelling of processes occurring in deep geological repository — development of new modules in the GoldSim environment, Czechoslovak Journal of Physics, Volume 56, Supplement 4 / December, 2006.
  11. ^ a b Philip H. Stauffer, Hari S. Viswanathan, Rajesh J. Pawar and George D. Guthrie (2009), A System Model for Geologic Sequestration of Carbon Dioxide, Environ. Sci. Technol., 2009, 43 (3), pp 565–570.
  12. ^ Yingqi Zhang, Curtis M. Oldenburg, Stefan Finsterle and Gudmundur S. Bodvarsson (2006), System-Level Modeling For Geological Storage Of CO2, PROCEEDINGS, TOUGH Symposium 2006, Lawrence Berkeley National Laboratory, Berkeley, California, May 15–17, 2006.
  13. ^ a b Difficult Decisions Made Easier. (2006) Spinoff, NASA Center for AeroSpace Information (CASI)
  14. ^ a b Donovan L. Mathias, Susie Go, Ken Gee, and Scott Lawrence (2008), Simulation Assisted Risk Assessment Applied to Launch Vehicle Conceptual Design, NASA Center for AeroSpace Information (CASI).
  15. ^ Golder Associates Launches Independent Software Company Based on GoldSim Software. (2004), Water & Wastes DIGEST
  16. ^ Probabilistic Simulation. GoldSim website.
  17. ^ Supercomputing Center Sees 46 Percent Performance Gain with HPC System Microsoft Case Studies

See also

External links