Package: sandy
SANDYSampling tool for nuclear dataSANDY is a python package that can read, write and perform a set of operations on nuclear data files inENDF-6 format.Stochastic sampling of nuclear dataThe primary objective of the code, as it was originally conceived, is to produceperturbed filescontaining sampled parameters
that represent the information stored in the evaluated nuclear data covariances.
Such files can be ultimately used to propagate uncertainties through any given compatible system using a brute force technique.Currently, SANDY can draw samples for:cross sections;angular distrbutions of outgoing particles;energy distrbutions of outgoing particles;fission neutron multiplicities;fission yields.API for ENDF-6 filesThe recent development on SANDY extended the original goal and focused on providing a simple interface for nuclear data files in ENDF-6 format.
Nuclear data such as cross sections, fission yields, radioactive decay constants and so on can be imported into tabulated dataframes (making extensive use ofpandas) for further post-processing, analysis, plotting, ...Examples are availablehere.:wrench: InstallationSANDY can be installed both on Linux (recommended) or Windows (using Anaconda).
The installation instructions are availablehere.:notebook_with_decorative_cover: DocumentationThe official SANDY documentation can be foundhere.:video_game: Jupyter notebooksHereyou can find some coolJupyter notebooksthat kind of give an idea of what one can do with SANDY.:telephone_receiver: ContactsLuca Fiorito-lucafiorito.11@gmail.com:bookmark: AcknowledgmentsSANDY was conceived and developed as a part of the PhD thesis onNuclear data uncertainty propagation and uncertainty quantification in nuclear codesin the framework of a collaboration betweenSCK CENandULB.:clipboard: ReferenceAmong the publications about SANDY, please use the following as a reference for citation.L. Fiorito, G. Žerovnik, A. Stankovskiy, G. Van den Eynde, P.E. Labeau,Nuclear data uncertainty propagation to integral responses using SANDY, Annals of Nuclear Energy, Volume 101, 2017, Pages 359-366, ISSN 0306-4549.:earth_africa: PublicationsBelow is a (incomplete) list of scientific studies about SANDY.If some info are not correct or missing, please let us know!Neudecker, D., Cabellos, O., Clark, A.R., Haeck, W., Capote, R., Trkov, A., White, M.C., Rising, M.E.
Which nuclear data can be validated with LLNL pulsed-sphere experiments?
(2021) Annals of Nuclear Energy, 159, art. no. 108345, .https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105590545&doi=10.1016%2fj.anucene.2021.108345&partnerID=40&md5=61a9a6561a26957cb9d0508d87834959DOI: 10.1016/j.anucene.2021.108345Kos, B., Grove, R.E., Kodeli, I.A.
From CAD to nuclear data S/U for shielding applications
(2020) Transactions of the American Nuclear Society, 122, pp. 625-628.https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092203776&doi=10.13182%2fT122-32416&partnerID=40&md5=2add99e4007bb1aa2c52e84b0d75f4bcDOI: 10.13182/T122-32416Sui, Z., Cao, L., Wan, C., Zou, X.
Covariance-oriented sample transformation: A new sampling method for reactor-physics uncertainty analysis
(2019) Annals of Nuclear Energy, 134, pp. 452-463.https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072272843&doi=10.1016%2fj.anucene.2019.07.001&partnerID=40&md5=e08c5089695828c7879c534c81a43f67DOI: 10.1016/j.anucene.2019.07.001Romojaro, P., Álvarez-Velarde, F., García-Herranz, N.
Sensitivity methods for effective delayed neutron fraction and neutron generation time with summon
(2019) Annals of Nuclear Energy, 126, pp. 410-418.https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057459216&doi=10.1016%2fj.anucene.2018.11.042&partnerID=40&md5=c9dfe228d3bb7ca3fd7b91a641c4a12dDOI: 10.1016/j.anucene.2018.11.042Goričanec, T., Kos, B., Žerovnik, G., Marshall, M.A., Kodeli, I.A., Lengar, I., Štancar, Ž., Bess, J.D., Heinrichs, D.P., Kim, S.S., Zerkle, M.L., Snoj, L.
Evaluation of the criticality and reaction rate benchmark experiments utilizing UO2F2 aqueous solution of intermediate enrichment in spherical geometry at ORNL
(2019) Progress in Nuclear Energy, 111, pp. 97-108.https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056226450&doi=10.1016%2fj.pnucene.2018.10.024&partnerID=40&md5=62d173a2f53ccadf0c510c1ba2093467DOI: 10.1016/j.pnucene.2018.10.024Abrate, N., Aufiero, M., Dulla, S., Fiorito, L.
Nuclear data uncertainty quantification in molten salt reactors with XGPT
(2019) International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, M and C 2019, pp. 2348-2357.https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075336363&partnerID=40&md5=23053c54dbd27849a555f0a6d427f748Stankovskiy, A., Iwamoto, H., Çelik, Y., Van den Eynde, G.
High-energy nuclear data uncertainties propagated to MYRRHA safety parameters
(2018) Annals of Nuclear Energy, 120, pp. 207-218.https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048381075&doi=10.1016%2fj.anucene.2018.05.041&partnerID=40&md5=4806dda020edda14693ca71d63b20454DOI: 10.1016/j.anucene.2018.05.041Trottier, A., Adams, F.P., Levinsky, A., Roubtsov, D.
Nuclear data sensitivity for reactor physics parameters in a lead-cooled reactor
(2018) Annals of Nuclear Energy, 120, pp. 333-347.https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048130954&doi=10.1016%2fj.anucene.2018.05.047&partnerID=40&md5=592a1fded9a1bac786dcda721355503eDOI: 10.1016/j.anucene.2018.05.047Iwamoto, H., Stankovskiy, A., Fiorito, L., Eynde, G.V.D.
Monte Carlo uncertainty quantification of the effective delayed neutron fraction
(2018) Journal of Nuclear Science and Technology, 55 (5), pp. 539-547.https://www.scopus.com/inward/record.uri?eid=2-s2.0-85040986058&doi=10.1080%2f00223131.2017.1416691&partnerID=40&md5=6e723fa992bb23a5bdfb1f558f7ee90dDOI: 10.1080/00223131.2017.1416691Castro, E., Sánchez-Cervera, S., García-Herranz, N., Cuervo, D.
Impact of the homogenization level, nodal or pin-by-pin, on the uncertainty quantification with core simulators
(2018) Progress in Nuclear Energy, 104, pp. 218-228.https://www.scopus.com/inward/record.uri?eid=2-s2.0-85031316608&doi=10.1016%2fj.pnucene.2017.10.001&partnerID=40&md5=934c255c172e881d9fbb4f8b022ea7e8DOI: 10.1016/j.pnucene.2017.10.001Kos, B., Kodeli, I., Fiorito, L., Zerovnik, G.
Nuclear data uncertainty analysis of the tiara iron benchmark using the random sampling code sandy accelerated by the advantg hybrid transport code
(2018) International Conference on Physics of Reactors, PHYSOR 2018: Reactor Physics Paving the Way Towards More Efficient Systems, Part F168384-5, pp. 3066-3077.https://www.scopus.com/inward/record.uri?eid=2-s2.0-85106058892&partnerID=40&md5=55fef5d061a1e751ce8b6fc7cf139f0dHursin, M., Siefman, D., Perret, G., Rochman, D., Vasiliev, A., Ferroukhi, H.
Determination of Sobol sensitivity indices for correlated inputs with SHARK-X
(2018) International Conference on Physics of Reactors, PHYSOR 2018: Reactor Physics Paving the Way Towards More Efficient Systems, Part F168384-5, pp. 3078-3089.https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079141095&partnerID=40&md5=de08bf715e1976c43d715fd274a99cf6Ambrožič, K., Žerovnik, G., Snoj, L.
Computational analysis of the dose rates at JSI TRIGA reactor irradiation facilities
(2017) Applied Radiation and Isotopes, 130, pp. 140-152.https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030097997&doi=10.1016%2fj.apradiso.2017.09.022&partnerID=40&md5=ce936e4571d9385642c07c4104275eb1DOI: 10.1016/j.apradiso.2017.09.022Griseri, M., Fiorito, L., Stankovskiy, A., Van den Eynde, G.
Nuclear data uncertainty propagation on a sodium fast reactor
(2017) Nuclear Engineering and Design, 324, pp. 122-130.https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028988145&doi=10.1016%2fj.nucengdes.2017.08.018&partnerID=40&md5=244f028df2b88f35f8b1460a0da49a5dDOI: 10.1016/j.nucengdes.2017.08.018Stankovskiy, A., Çelik, Y., Eynde, G.V.D.
Impact of intermediate and high energy nuclear data on the neutronic safety parameters of MYRRHA accelerator driven system
(2017) EPJ Web of Conferences, 146, art. no. 09001, .https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030483656&doi=10.1051%2fepjconf%2f201714609001&partnerID=40&md5=16458780820528ea5606fb87501cd54fDOI: 10.1051/epjconf/201714609001