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Monte carlo simulations of the n_TOF lead spallation target with the Geant4 toolkit: A benchmark study

Monte Carlo (MC) simulations are an essential tool to determine fundamental features of a neutron beam, such as the neutron flux or the γ-ray background, that sometimes can not be measured or at least not in every position or energy range. Until recently, the most widely used MC codes in this field...

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Main Authors: Lerendegui-Marco, J., Cortés-Giraldo, M.A., Guerrero, C., Quesada, J.M., Meo, S. Lo, Massimi, C., Barbagallo, M., Colonna, N., Mancussi, D., Mingrone, F., Sabaté-Gilarte, M., Vannini, G., Vlachoudis, V., Aberle, O., Andrzejewski, J., Audouin, L., Bacak, M., Balibrea, J., Bečvář, F., Berthoumieux, E., Billowes, J., Bosnar, D., Brown, A., Caamaño, M., Calviño, F., Calviani, M., Cano-Ott, D., Cardella, R., Casanovas, A., Cerutti, F., Chen, Y.H., Chiaveri, E., Cortés, G., Cosentino, L., Damone, L.A., Diakaki, M., Domingo-Pardo, C., Dressler, R., Dupont, E., Durán, I., Fernández-Domínguez, B., Ferrari, A., Ferreira, P., Finocchiaro, P., Göbel, K., Gómez-Hornillos, M.B., García, A.R., Gawlik, A., Gilardoni, S., Glodariu, T., Gonçalves, I.F., González, E., Griesmayer, E., Gunsing, F., Harada, H., Heinitz, S., Heyse, J., Jenkins, D.G., Jericha, E., Käppeler, F., Kadi, Y., Kalamara, A., Kavrigin, P., Kimura, A., Kivel, N., Kokkoris, M., Krtička, M., Kurtulgil, D., Leal-Cidoncha, E., Lederer, C., Leeb, H., Lonsdale, S.J., Macina, D., Marganiec, J., Martínez, T., Masi, A., Mastinu, P., Mastromarco, M., Maugeri, E.A., Mazzone, A., Mendoza, E., Mengoni, A., Milazzo, P.M., Musumarra, A., Negret, A., Nolte, R., Oprea, A., Patronis, N., Pavlik, A., Perkowski, J., Porras, I., Praena, J., Radeck, D., Rauscher, T., Reifarth, R., Rout, P.C., Rubbia, C., Ryan, J.A., Saxena, A., Schillebeeckx, P.
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creator Lerendegui-Marco, J.
Cortés-Giraldo, M.A.
Guerrero, C.
Quesada, J.M.
Meo, S. Lo
Massimi, C.
Barbagallo, M.
Colonna, N.
Mancussi, D.
Mingrone, F.
Sabaté-Gilarte, M.
Vannini, G.
Vlachoudis, V.
Aberle, O.
Andrzejewski, J.
Audouin, L.
Bacak, M.
Balibrea, J.
Bečvář, F.
Berthoumieux, E.
Billowes, J.
Bosnar, D.
Brown, A.
Caamaño, M.
Calviño, F.
Calviani, M.
Cano-Ott, D.
Cardella, R.
Casanovas, A.
Cerutti, F.
Chen, Y.H.
Chiaveri, E.
Cortés, G.
Cosentino, L.
Damone, L.A.
Diakaki, M.
Domingo-Pardo, C.
Dressler, R.
Dupont, E.
Durán, I.
Fernández-Domínguez, B.
Ferrari, A.
Ferreira, P.
Finocchiaro, P.
Göbel, K.
Gómez-Hornillos, M.B.
García, A.R.
Gawlik, A.
Gilardoni, S.
Glodariu, T.
Gonçalves, I.F.
González, E.
Griesmayer, E.
Gunsing, F.
Harada, H.
Heinitz, S.
Heyse, J.
Jenkins, D.G.
Jericha, E.
Käppeler, F.
Kadi, Y.
Kalamara, A.
Kavrigin, P.
Kimura, A.
Kivel, N.
Kokkoris, M.
Krtička, M.
Kurtulgil, D.
Leal-Cidoncha, E.
Lederer, C.
Leeb, H.
Lonsdale, S.J.
Macina, D.
Marganiec, J.
Martínez, T.
Masi, A.
Mastinu, P.
Mastromarco, M.
Maugeri, E.A.
Mazzone, A.
Mendoza, E.
Mengoni, A.
Milazzo, P.M.
Musumarra, A.
Negret, A.
Nolte, R.
Oprea, A.
Patronis, N.
Pavlik, A.
Perkowski, J.
Porras, I.
Praena, J.
Radeck, D.
Rauscher, T.
Reifarth, R.
Rout, P.C.
Rubbia, C.
Ryan, J.A.
Saxena, A.
Schillebeeckx, P.
description Monte Carlo (MC) simulations are an essential tool to determine fundamental features of a neutron beam, such as the neutron flux or the γ-ray background, that sometimes can not be measured or at least not in every position or energy range. Until recently, the most widely used MC codes in this field had been MCNPX and FLUKA. However, the Geant4 toolkit has also become a competitive code for the transport of neutrons after the development of the native Geant4 format for neutron data libraries, G4NDL. In this context, we present the Geant4 simulations of the neutron spallation target of the n_TOF facility at CERN, done with version 10.1.1 of the toolkit. The first goal was the validation of the intra-nuclear cascade models implemented in the code using, as benchmark, the characteristics of the neutron beam measured at the first experimental area (EAR1), especially the neutron flux and energy distribution, and the time distribution of neutrons of equal kinetic energy, the so-called Resolution Function. The second goal was the development of a Monte Carlo tool aimed to provide useful calculations for both the analysis and planning of the upcoming measurements at the new experimental area (EAR2) of the facility.
doi_str_mv 10.1051/epjconf/201714603030
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Lo ; Massimi, C. ; Barbagallo, M. ; Colonna, N. ; Mancussi, D. ; Mingrone, F. ; Sabaté-Gilarte, M. ; Vannini, G. ; Vlachoudis, V. ; Aberle, O. ; Andrzejewski, J. ; Audouin, L. ; Bacak, M. ; Balibrea, J. ; Bečvář, F. ; Berthoumieux, E. ; Billowes, J. ; Bosnar, D. ; Brown, A. ; Caamaño, M. ; Calviño, F. ; Calviani, M. ; Cano-Ott, D. ; Cardella, R. ; Casanovas, A. ; Cerutti, F. ; Chen, Y.H. ; Chiaveri, E. ; Cortés, G. ; Cosentino, L. ; Damone, L.A. ; Diakaki, M. ; Domingo-Pardo, C. ; Dressler, R. ; Dupont, E. ; Durán, I. ; Fernández-Domínguez, B. ; Ferrari, A. ; Ferreira, P. ; Finocchiaro, P. ; Göbel, K. ; Gómez-Hornillos, M.B. ; García, A.R. ; Gawlik, A. ; Gilardoni, S. ; Glodariu, T. ; Gonçalves, I.F. ; González, E. ; Griesmayer, E. ; Gunsing, F. ; Harada, H. ; Heinitz, S. ; Heyse, J. ; Jenkins, D.G. ; Jericha, E. ; Käppeler, F. ; Kadi, Y. ; Kalamara, A. ; Kavrigin, P. ; Kimura, A. ; Kivel, N. ; Kokkoris, M. ; Krtička, M. ; Kurtulgil, D. ; Leal-Cidoncha, E. ; Lederer, C. ; Leeb, H. ; Lonsdale, S.J. ; Macina, D. ; Marganiec, J. ; Martínez, T. ; Masi, A. ; Mastinu, P. ; Mastromarco, M. ; Maugeri, E.A. ; Mazzone, A. ; Mendoza, E. ; Mengoni, A. ; Milazzo, P.M. ; Musumarra, A. ; Negret, A. ; Nolte, R. ; Oprea, A. ; Patronis, N. ; Pavlik, A. ; Perkowski, J. ; Porras, I. ; Praena, J. ; Radeck, D. ; Rauscher, T. ; Reifarth, R. ; Rout, P.C. ; Rubbia, C. ; Ryan, J.A. ; Saxena, A. ; Schillebeeckx, P.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c455t-da2f28c829ac7d86a1d84666a420fcdda2d485d266b6669d88e6552147583a0f3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Background radiation</topic><topic>Benchmarks</topic><topic>Computer simulation</topic><topic>Energy distribution</topic><topic>Energy measurement</topic><topic>Kinetic energy</topic><topic>Neutron beams</topic><topic>Neutron flux</topic><topic>Neutrons</topic><topic>Position measurement</topic><topic>Spallation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lerendegui-Marco, J.</creatorcontrib><creatorcontrib>Cortés-Giraldo, M.A.</creatorcontrib><creatorcontrib>Guerrero, C.</creatorcontrib><creatorcontrib>Quesada, J.M.</creatorcontrib><creatorcontrib>Meo, S. 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Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>SciTech Premium Collection</collection><collection>ProQuest advanced technologies &amp; aerospace journals</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Directory of Open Journals (DOAJ)</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lerendegui-Marco, J.</au><au>Cortés-Giraldo, M.A.</au><au>Guerrero, C.</au><au>Quesada, J.M.</au><au>Meo, S. Lo</au><au>Massimi, C.</au><au>Barbagallo, M.</au><au>Colonna, N.</au><au>Mancussi, D.</au><au>Mingrone, F.</au><au>Sabaté-Gilarte, M.</au><au>Vannini, G.</au><au>Vlachoudis, V.</au><au>Aberle, O.</au><au>Andrzejewski, J.</au><au>Audouin, L.</au><au>Bacak, M.</au><au>Balibrea, J.</au><au>Bečvář, F.</au><au>Berthoumieux, E.</au><au>Billowes, J.</au><au>Bosnar, D.</au><au>Brown, A.</au><au>Caamaño, M.</au><au>Calviño, F.</au><au>Calviani, M.</au><au>Cano-Ott, D.</au><au>Cardella, R.</au><au>Casanovas, A.</au><au>Cerutti, F.</au><au>Chen, Y.H.</au><au>Chiaveri, E.</au><au>Cortés, G.</au><au>Cosentino, L.</au><au>Damone, L.A.</au><au>Diakaki, M.</au><au>Domingo-Pardo, C.</au><au>Dressler, R.</au><au>Dupont, E.</au><au>Durán, I.</au><au>Fernández-Domínguez, B.</au><au>Ferrari, A.</au><au>Ferreira, P.</au><au>Finocchiaro, P.</au><au>Göbel, K.</au><au>Gómez-Hornillos, M.B.</au><au>García, A.R.</au><au>Gawlik, A.</au><au>Gilardoni, S.</au><au>Glodariu, T.</au><au>Gonçalves, I.F.</au><au>González, E.</au><au>Griesmayer, E.</au><au>Gunsing, F.</au><au>Harada, H.</au><au>Heinitz, S.</au><au>Heyse, J.</au><au>Jenkins, D.G.</au><au>Jericha, E.</au><au>Käppeler, F.</au><au>Kadi, Y.</au><au>Kalamara, A.</au><au>Kavrigin, P.</au><au>Kimura, A.</au><au>Kivel, N.</au><au>Kokkoris, M.</au><au>Krtička, M.</au><au>Kurtulgil, D.</au><au>Leal-Cidoncha, E.</au><au>Lederer, C.</au><au>Leeb, H.</au><au>Lonsdale, S.J.</au><au>Macina, D.</au><au>Marganiec, J.</au><au>Martínez, T.</au><au>Masi, A.</au><au>Mastinu, P.</au><au>Mastromarco, M.</au><au>Maugeri, E.A.</au><au>Mazzone, A.</au><au>Mendoza, E.</au><au>Mengoni, A.</au><au>Milazzo, P.M.</au><au>Musumarra, A.</au><au>Negret, A.</au><au>Nolte, R.</au><au>Oprea, A.</au><au>Patronis, N.</au><au>Pavlik, A.</au><au>Perkowski, J.</au><au>Porras, I.</au><au>Praena, J.</au><au>Radeck, D.</au><au>Rauscher, T.</au><au>Reifarth, R.</au><au>Rout, P.C.</au><au>Rubbia, C.</au><au>Ryan, J.A.</au><au>Saxena, A.</au><au>Schillebeeckx, P.</au><au>Schillebeeckx, P.</au><au>Hambsch, F.-J.</au><au>Heyse, J.</au><au>Oberstedt, S.</au><au>Mondelaers, W.</au><au>Plompen, A.</au><au>Kopecky, S.</au><au>Siegler, P.</au><aucorp>the n_TOF Collaboration</aucorp><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Monte carlo simulations of the n_TOF lead spallation target with the Geant4 toolkit: A benchmark study</atitle><btitle>EPJ Web of conferences</btitle><date>2017-01-01</date><risdate>2017</risdate><volume>146</volume><spage>3030</spage><pages>3030-</pages><issn>2100-014X</issn><issn>2101-6275</issn><eissn>2100-014X</eissn><abstract>Monte Carlo (MC) simulations are an essential tool to determine fundamental features of a neutron beam, such as the neutron flux or the γ-ray background, that sometimes can not be measured or at least not in every position or energy range. Until recently, the most widely used MC codes in this field had been MCNPX and FLUKA. However, the Geant4 toolkit has also become a competitive code for the transport of neutrons after the development of the native Geant4 format for neutron data libraries, G4NDL. In this context, we present the Geant4 simulations of the neutron spallation target of the n_TOF facility at CERN, done with version 10.1.1 of the toolkit. The first goal was the validation of the intra-nuclear cascade models implemented in the code using, as benchmark, the characteristics of the neutron beam measured at the first experimental area (EAR1), especially the neutron flux and energy distribution, and the time distribution of neutrons of equal kinetic energy, the so-called Resolution Function. The second goal was the development of a Monte Carlo tool aimed to provide useful calculations for both the analysis and planning of the upcoming measurements at the new experimental area (EAR2) of the facility.</abstract><cop>Les Ulis</cop><pub>EDP Sciences</pub><doi>10.1051/epjconf/201714603030</doi><oa>free_for_read</oa></addata></record>
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subjects Background radiation
Benchmarks
Computer simulation
Energy distribution
Energy measurement
Kinetic energy
Neutron beams
Neutron flux
Neutrons
Position measurement
Spallation
title Monte carlo simulations of the n_TOF lead spallation target with the Geant4 toolkit: A benchmark study
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