24:
271:. 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).
264:. 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).
286:
simulator, such that inputs can be defined as distributions and the entire system simulated a large number of times to provide probabilistic outputs. As such, the software incorporates a number of computational features to facilitate probabilistic simulation of complex systems, including tools for
259:
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
247:; 3) a flood operations model to help better understand and fine tune operations of a large dam used for water supply and flood control in Queensland, Australia; and 4) models for simulating risks associated with future crewed space missions by
224:
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.
198:(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
538:
Jongtae Jeong, Youn-Myoung Lee, Jung-Woo Kim, Dong-Keun Cho, Nak Yul Ko, and Min Hoon Baik (2016), Progress of the Long-Term Safety
Assessment of a Reference Disposal System for High Level Wastes in Korea,
358:
617:
Susie Go, Donovan L. Mathias, Scott
Lawrence, Ken Gee and Christopher J. Mattenberger (2014), An Integrated Reliability and Physics-based Risk Modeling Approach for Assessing Human Spaceflight Systems,
424:
Erfan
Goharian, Steven J. Burian, Jason Lillywhite, and Ryan Hile (2016), Vulnerability Assessment to Support Integrated Water Resources Management of Metropolitan Water Supply Systems,
341:
Lloyd
Townley, Huanhuan Jiang and Jinquan Tang (2019), WRRM1 and WRRM2: Implementations in GoldSim of Unit Process Models and IWA Benchmark Models (BSM1 and BSM2) for Nutrient Removal,
522:
K.P. Lee, R. Andrews, N. Hasan, R. Senger, M. Kozak, A. K. Wahi, and W. Zhou (2018), Integration of Models for the
Hanford Integrated Disposal Facility Performance Assessment,
411:
James C. Schlaman and Danny
Johnson (20147, Eliminating the Silo Effect Integrated Water, Wastewater, Watershed Model Helps the Atlanta Region Plan a More Holistic Future,
378:
James Andrew
Griffiths, Fangfang Zhu, Faith Ka Shun Chan and David Laurence Higgitt (2019), Modelling the impact of sea-level rise on urban flood probability in SE China,
585:
Sean
Sanguinitoa, Angela L. Goodman, and James I. Sams III (2018), CO2-SCREEN tool: Application to the oriskany sandstone to estimate prospective CO2 storage resource,
355:
635:
489:
William
Schafer, John Barber, Manuel Contreras and Jesus Tellez (2016), Integrating Surface Water Load Modelling into Mine Closure Performance Evaluation,
651:
476:
Valérie Plagnes, Brad Schmid, Brett Mitchell and Ian Judd-Henrey (2017), Water Balance Modelling of a Uranium Mill Effluent Management System,
143:
developed by GoldSim Technology Group. This general-purpose simulator is a hybrid of several simulation approaches, combining an extension of
601:
Donovan L. Mathias, Susie Go, and Christopher J. Mattenberger (2014), Engineering Risk Assessment of Space Thruster Challenge Problem,
395:
735:
437:
Brent C. Johnson, Pamela Rohal, and Ted Eary (2018), Coupling PHREEQC with GoldSim for a More Dynamic Water Modeling Experience,
725:
715:
229:
552:
B. Haverkamp, J. Krone, and I. Shybetskyi (2013), Safety Assessment for a Surface Repository in the Chernobyl Exclusion Zone,
450:
Nick Martin and Michael Gabora (2018), Modelling Complex Mine Water Closure Challenges using a Coupled FEFLOW-GoldSim Model,
745:
205:
In 1996, in an effort funded by Golder Associates, the US DOE, the Japan Nuclear Cycle Development Institute (currently the
322:
195:
710:
633:
The Comparison of Three Photovoltaic System Designs Using the Photovoltaic Reliability and Performance Model (PV-RPM)
467:, Dissertation for Montana Tech of The University of Montana, Copyright ProQuest, UMI Dissertations Publishing 2014.
92:
632:
202:-based programs (RIP and STRIP), which were used to support radioactive waste management projects within the DOE.
158:
While it is a general-purpose simulator, GoldSim has been most extensively used for environmental and engineering
740:
356:
Integrated Urban Water Resources Modeling In A Semi-Arid Mountainous Region Using A Cyberinfrastructure Framework
720:
274:
Because the software was originally developed for complex environmental applications, in which many inputs are
244:
705:
233:
267:
Though it is primarily a continuous simulator, GoldSim has a number of features typically associated with
730:
159:
48:
237:
206:
175:
268:
248:
148:
292:
317:
300:
152:
109:
400:
Proceedings of Australian National Committee on Large Dams (ANCOLD) Annual Conference 2014
8:
666:
312:
296:
140:
97:
396:
Wivenhoe Somerset Dam Optimisation Study – Simulating Dam Operations for Numerous Floods
568:
Philip H. Stauffer, Hari S. Viswanathan, Rajesh J. Pawar and George D. Guthrie (2009),
506:
283:
261:
642:, Sandia Report SAND2012-10342, Sandia National Laboratories, Albuquerque, New Mexico.
214:
213:(ENRESA), the capabilities of RIP and STRIP were incorporated into a general purpose
191:
171:
236:; 2) a comprehensive system-level computational model for performance assessment of
104:
82:
620:
Proceedings, Probabilistic Safety Assessment and Management PSAM 12, Honolulu, HI,
603:
Proceedings, Probabilistic Safety Assessment and Management PSAM 12, Honolulu, HI,
652:
Golder Associates Launches Independent Software Company Based on GoldSim Software
639:
569:
362:
144:
464:
343:
Innovation Conference on Sustainable Wastewater Treatment and Resource Recovery
163:
367:
Proceedings of the 11th International Conference on Hydroinformatics, HIC 2014
699:
137:
23:
228:
Notable applications include providing the simulation framework for: 1) the
288:
275:
217:-based simulator called GoldSim. Subsequent funding was also provided by
279:
34:
210:
179:
631:
Steven P. Miller, Jennifer E. Granata and Joshua S. Stein (2012),
452:
11th ICARD | IMWA | WISA MWD 2018 Conference – Risk to Opportunity
439:
11th ICARD | IMWA | WISA MWD 2018 Conference – Risk to Opportunity
194:, an international engineering consulting firm, was asked by the
199:
167:
570:
A System Model for Geologic Sequestration of Carbon Dioxide
491:
International Mine Water Association Conference Proceedings
218:
688:
282:, in addition to being a dynamic simulator, GoldSim is a
120:
151:, and embedding the dynamic simulation engine within a
232:
Repository Performance Assessment model developed by
554:
Proceedings of the 2013 Waste Management Symposium,
524:
Proceedings of the 2018 Waste Management Symposium,
426:
Journal of Water Resources Planning and Management,
697:
587:International Journal of Greenhouse Gas Control,
413:Proceedings of the Water Environment Federation
501:
499:
354:Erfan Goharian and Steven J. Burian (2014),
291:, advanced sampling capabilities (including
546:
532:
516:
496:
211:Spanish National Radioactive Waste Company
22:
597:
595:
564:
562:
390:
388:
625:
254:
698:
457:
454:, January 2018 Pretoria, South Africa.
444:
441:, January 2018 Pretoria, South Africa.
431:
287:generating and correlating stochastic
613:
611:
592:
559:
405:
385:
372:
348:
335:
323:List of computer simulation software
162:, with applications in the areas of
295:, nested Monte Carlo analysis, and
182:mission risk analysis and energy.
13:
608:
196:United States Department of Energy
14:
757:
680:
54:14.0 R3 / January 4, 2024
736:Simulation programming languages
660:
645:
579:
483:
470:
726:Environmental science software
716:Scientific simulation software
418:
245:Los Alamos National Laboratory
238:geological sequestration of CO
1:
465:A Probabilistic Water Balance
328:
746:Science software for Windows
234:Sandia National Laboratories
39:GoldSim Technology Group LLC
7:
576:, 2009, 43 (3), pp 565–570.
507:Do or Die at Yucca Mountain
505:David Ewing Duncan (2003),
306:
10:
762:
541:Progress in Nuclear Energy
513:, Issue 11.04, April 2003.
207:Japan Atomic Energy Agency
185:
656:Water & Wastes DIGEST
249:NASA Ames Research Center
149:discrete event simulation
115:
103:
91:
81:
73:
69:
47:
43:
33:
21:
711:Risk management software
667:Probabilistic Simulation
293:latin hypercube sampling
174:management , geological
394:Michel Raymond (2014),
741:Probabilistic software
574:Environ. Sci. Technol.
402:, Canberra, Australia.
318:Monte Carlo Simulation
301:distributed processing
153:Monte Carlo simulation
56:; 8 months ago
721:Mathematical software
478:Journal of Hydrology,
369:, New York, New York.
147:with some aspects of
380:Geoscience Frontiers
255:Modeling Environment
176:carbon sequestration
706:Simulation software
313:Computer Simulation
299:), and support for
297:importance sampling
269:discrete simulators
141:simulation software
98:Simulation software
18:
731:Numerical software
638:2013-03-02 at the
463:Lisa Wade (2014),
361:2014-11-29 at the
345:, Shanghai, China.
262:influence diagrams
16:
192:Golder Associates
172:radioactive waste
131:
130:
753:
692:
691:
689:Official website
674:
664:
658:
649:
643:
629:
623:
615:
606:
599:
590:
583:
577:
566:
557:
550:
544:
536:
530:
520:
514:
503:
494:
487:
481:
474:
468:
461:
455:
448:
442:
435:
429:
422:
416:
409:
403:
392:
383:
376:
370:
352:
346:
339:
127:
124:
122:
83:Operating system
64:
62:
57:
26:
19:
15:
761:
760:
756:
755:
754:
752:
751:
750:
696:
695:
687:
686:
683:
678:
677:
671:GoldSim website
665:
661:
650:
646:
640:Wayback Machine
630:
626:
616:
609:
600:
593:
584:
580:
567:
560:
551:
547:
537:
533:
521:
517:
504:
497:
488:
484:
475:
471:
462:
458:
449:
445:
436:
432:
423:
419:
415:, January 2017.
410:
406:
393:
386:
377:
373:
363:Wayback Machine
353:
349:
340:
336:
331:
309:
257:
241:
188:
145:system dynamics
119:
65:
60:
58:
55:
29:
12:
11:
5:
759:
749:
748:
743:
738:
733:
728:
723:
718:
713:
708:
694:
693:
682:
681:External links
679:
676:
675:
659:
644:
624:
607:
591:
578:
558:
556:February 2013.
545:
531:
515:
511:Wired Magazine
495:
482:
469:
456:
443:
430:
428:November 2016.
417:
404:
384:
371:
347:
333:
332:
330:
327:
326:
325:
320:
315:
308:
305:
256:
253:
239:
230:Yucca Mountain
187:
184:
166:management ,
164:water resource
129:
128:
117:
113:
112:
107:
101:
100:
95:
89:
88:
85:
79:
78:
75:
71:
70:
67:
66:
53:
51:
49:Stable release
45:
44:
41:
40:
37:
31:
30:
27:
9:
6:
4:
3:
2:
758:
747:
744:
742:
739:
737:
734:
732:
729:
727:
724:
722:
719:
717:
714:
712:
709:
707:
704:
703:
701:
690:
685:
684:
672:
668:
663:
657:
653:
648:
641:
637:
634:
628:
621:
614:
612:
604:
598:
596:
588:
582:
575:
571:
565:
563:
555:
549:
543:, July 2016.
542:
535:
529:
525:
519:
512:
508:
502:
500:
492:
486:
479:
473:
466:
460:
453:
447:
440:
434:
427:
421:
414:
408:
401:
397:
391:
389:
382:, March 2019.
381:
375:
368:
364:
360:
357:
351:
344:
338:
334:
324:
321:
319:
316:
314:
311:
310:
304:
302:
298:
294:
290:
285:
281:
277:
272:
270:
265:
263:
252:
250:
246:
243:developed by
242:
235:
231:
226:
222:
220:
216:
212:
208:
203:
201:
197:
193:
183:
181:
177:
173:
169:
165:
161:
160:risk analysis
156:
154:
150:
146:
142:
139:
138:probabilistic
135:
126:
118:
114:
111:
108:
106:
102:
99:
96:
94:
90:
86:
84:
80:
76:
72:
68:
52:
50:
46:
42:
38:
36:
32:
25:
20:
670:
662:
655:
647:
627:
619:
602:
589:August 2018.
586:
581:
573:
553:
548:
540:
534:
527:
523:
518:
510:
493:, July 2016.
490:
485:
477:
472:
459:
451:
446:
438:
433:
425:
420:
412:
407:
399:
379:
374:
366:
350:
342:
337:
273:
266:
258:
227:
223:
204:
189:
157:
136:is dynamic,
133:
132:
35:Developer(s)
28:GoldSim Logo
289:time series
284:Monte Carlo
155:framework.
110:Proprietary
700:Categories
622:June 2014.
605:June 2014.
526:March 2018
480:June 2017.
329:References
280:stochastic
209:) and the
74:Written in
61:2024-01-04
276:uncertain
190:In 1990,
180:aerospace
654:(2004),
636:Archived
359:Archived
307:See also
123:.goldsim
278:and/or
215:Windows
186:History
134:GoldSim
116:Website
105:License
87:Windows
59: (
17:GoldSim
168:mining
219:NASA
125:.com
93:Type
669:.
200:DOS
121:www
77:C++
702::
610:^
594:^
572:,
561:^
509:,
498:^
398:,
387:^
365:,
303:.
251:.
221:.
178:,
170:,
673:.
528:.
240:2
63:)
Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.
