Nuclear Fuel Cycle Codes Catalogue - TR_EVOL: Transition Evolution code
Flowchart of TR_EVOL fuel cycle simulator

TR_EVOL (Transition Evolution code) fuel cycle simulator is a tool dedicated to the study of mass balances of advanced transition electronuclear scenarios. This tool is developed and maintained by CIEMAT's Nuclear Innovation Unit.

TR_EVOL is an extension of the burn-up simulation system EVOLCODE which still constitutes the cornerstone of the code for the simulation of the different reactors involved in the studied cycle. The irradiation and decay of the nuclear materials are calculated through ORIGEN2.2 code.

In TR_EVOL nuclear fleets can be modeled either considering each single reactor individually or with macro-reactors averaged by kind of technology. The different material storages are represented in TR_EVOL by buffers that store the isotopic contents averaged at the time intervals defined by the user. Buffers are interconnected by simple rules aimed to describe any fuel cycle model. Some of these rules are: Certain amounts of material are extracted from one buffer, adding nuclear material from one buffer to another, new material appears, buffers are decayed, buffers are irradiated, etc.

In this way a facility can be simulated as a combination of simple instructions. Examples of facilities that can be modelled include: Initial inventories, mining, fabrication and reprocessing plants, reactors, etc.

The scenario description is embedded in two input files, being three in the case that the cost module is enabled. In one of the mandatory files the reactor fleet characteristics are described (reactor properties and energy production), while in the other the particular rules that have to be applied are defined, indicating what results have to be printed in the output file. Once TR_EVOL simulation is completed, different observables can be obtained. These include mass inventories, isotopic contents, radiotoxicity, decay heat, etc.

References

Validation effort/Benchmarking

  • NEA (2012), "Benchmark study on nuclear fuel cycle transition scenarios-analysis codes", OECD Publishing, Paris, www.oecd-nea.org/pl_19182
  • Skarbeli, A. V. et al. (2020), “Quantification of the differences introduced by nuclear fuel cycle simulators in advanced scenario studies”, Annals of Nuclear Energy, Vol: 137, 10.1016/j.anucene.2019.107160
  • Thiollière, Nicolas, et al. (2022), "Impact of fresh fuel loading management in fuel cycle simulators: A functionality isolation test." Nuclear Engineering and Design, Vol: 392, http://dx.doi.org/10.1016/j.nucengdes.2022.111748

 

Reference + description of the use

  • Skarbeli, A. V., Álvarez-Velarde, F., and Bécares, V. (2021), “Optimization under uncertainty for robust fuel cycle analyses”, Int. Journal of Energy Research, Vol: 45/4, p. 6139-6151, 10.1002/er.6236
  • Skarbeli, A. V. and Álvarez-Velarde, F. (2020), “Sparse Polynomial Chaos expansion for advanced nuclear fuel cycle sensitivity analysis” Annals of Nuclear Energy, Vol: 142, 10.1016/j.anucene.2020.107430
  • Skarbeli, A. V. et al. (2020), “Quantification of the differences introduced by nuclear fuel cycle simulators in advanced scenario studies”, Annals of Nuclear Energy, Vol: 137, 10.1016/j.anucene.2019.107160
  • Skarbeli, A. V. and Álvarez-Velarde, F. (2019), “Uncertainty quantification on advanced fuel cycle scenario simulations applying local and global methods”, Annals of Nuclear Energy, Vol: 124, 10.1016/j.anucene.2018.10.018
  • Merino-Rodríguez, I. et al. (2017), “Economics and Resources Analysis of the Potential Use of Reprocessing Options by a Medium Sized Nuclear Reactor Fleet”. Energies, Vol: 10/12, p. 690, 10.3390/en10050690
  • Merino-Rodríguez, I. et al. (2016), “Cross check of the new economic and mass balance features of the fuel cycle scenario code TR_EVOL”, EPJ Nuclear Sciences & Technologies, Vol: 2, p. 33, 10.1051/epjn/2016029