2023, Articolo in rivista, ENG
Overview of interpretive modelling of fusion performance in JET DTE2 discharges with TRANSP
Stancar Z.; Kirov K.K.; Auriemma F.; Kim H.-T.; Poradzinski M.; Sharma R.; Lorenzini R.; Ghani Z.; Gorelenkova M.; Poli F.; Boboc A.; Brezinsek S.; Carvalho P.; Casson F.J.; Challis C.D.; Delabie E.; Van Eester D.; Fitzgerald M-: Fontdecaba J.M.; Gallart D.; Garcia J.; Garzotti L.; Giroud C.; Kappatou A.; Kazakov Ye.O.; King D.B.; Kiptily V.G.; Kos D.; Lerche E.; Litherland-Smith E.; Maggi C.F.; Mantica P.; Mantsinen M.J.; Maslov M.; Menmuir S.; Nocente M.; Oliver H.J.C.; Sharapov S.E.; Siren P.; Solano E.R.; Sun H.J.; Szepesi G.; JET Contributors
In the paper we present an overview of interpretive modelling of a database of JET-ILW 2021 D-T discharges using the TRANSP code. The main aim is to assess our capability of computationally reproducing the fusion performance of various D-T plasma scenarios using different external heating and D-T mixtures, and to understand the performance driving mechanisms. We find that interpretive simulations confirm a general power-law relationship between increasing external heating power and fusion output, which is supported by absolutely calibrated neutron yield measurements. A comparison of measured and computed D-T neutron rates shows that the calculations' discrepancy depends on the absolute neutron yield. The calculations are found to agree well with measurements for higher performing discharges with external heating power above ~20 MW, while low-neutron shots display an average discrepancy of around +40% compared to measured neutron yields. A similar trend is found for the ratio between thermal and beam-target fusion, where larger discrepancies are seen in shots with dominant beam-driven performance. We compare the observations to studies of JET-ILW D discharges, to find that on average the fusion performance is well modelled over a range of heating power, although an increased unsystematic deviation for lower-performing shots is observed. The ratio between thermal and beam-induced D-T fusion is found to be increasing weakly with growing external heating power, with a maximum value of ?1 achieved in a baseline scenario experiment. An evaluation of the fusion power computational uncertainty shows a strong dependence on the plasma scenario type and fusion drive characteristics, varying between ±25% and 35%. D-T fusion alpha simulations show that the ratio between volume-integrated electron and ion heating from alphas is ?10 for the majority of analysed discharges. Alphas are computed to contribute between ~15% and 40% to the total electron heating in the core of highest performing D-T discharges. An alternative workflow to TRANSP was employed to model JET D-T plasmas with the highest fusion yield and dominant non-thermal fusion component because of the use of fundamental radio-frequency heating of a large minority in the scenario, which is calculated to have provided ~10% to the total fusion power.
2023, Articolo in rivista, ENG
Divertor power spreading in the Divertor Tokamak Test facility for a full power scenario with Ar and Ne seeding
Ivanova-Stanik I.; Chmielewski P.; Day C.; Innocente P.; Zagorski R.
This work describes integrated numerical modelling applied to Divertor Tokamak Test (DTT) scenarios with tungsten wall and divertor in single null configuration using the COREDIV code, which self-consistently solves 1D radial transport equations of plasma and impurities in the core region and 2D multi-fluid transport in the scrape-off layer (SOL). COREDIV code simulations have been performed and compared to the already published solutions from JETTO for DTT full power discharges with Ar seeding. The influence of the particle transport on the fuelling and flux to the plate is analysed. The main conclusion from the performed simulations is that Ne and Ar radiate effectively in the SOL and no difference was found in the fuelling properties between them. The fuelling increases with increase in radial transport in the core region. It has been found that the rise in the diffusion in the core plasma has a small influence on several global plasma parameters, such as plasma radiation, impurity concentration and fluxes to the divertor plate, but has a strong effect on the fuelling. The fuelling and deuterium flux to the plate decrease almost linearly with decreasing plasma density, keeping ? n e ? / n e s e p = constant.
2023, Articolo in rivista, ENG
Core integrated simulations for the Divertor Tokamak Test facility scenarios towards consistent core-pedestal-SOL modelling
Casiraghi I.; Mantica P.; Ambrosino R.; Aucone L.; Baiocchi B.; Balbinot L.; Barberis T.; Castaldo A.; Cavedon M.; Frassinetti L.; Innocente P.; Koechl F.; Nowak S.; Agostinetti P.; Ceccuzzi S.; Figini L.; Granucci G.; Vincenzi P.
Deuterium plasma discharges of the Divertor Tokamak Test facility (DTT) in different operational scenarios have been predicted by a comprehensive first-principle based integrated modelling activity using state-of-art quasi-linear transport models. The results of this work refer to the updated DTT configuration, which includes a device size optimisation (enlargement to R0 = 2.19 m and a = 0.70 m) and upgrades in the heating systems. The focus of this paper is on the core modelling, but special attention was paid to the consistency with the scrape-off layer parameters required to achieve divertor plasma detachment. The compatibility of these physics-based predicted scenarios with the electromagnetic coil system capabilities was then verified. In addition, first estimates of DTT sawteeth and of DTT edge localised modes were achieved.
2022, Articolo in rivista, ENG
Integrated modelling and multiscale gyrokinetic validation study of ETG turbulence in a JET hybrid H-mode scenario
Citrin, J.; Maeyama, S.; Angioni, C.; Bonanomi, N.; Bourdelle, C.; Casson, F. J.; Fable, E.; Goerler, T.; Mantica, P.; Mariani, A.; Sertoli, M.; Staebler, G.; Watanabe, T.
Previous studies with first-principle-based integrated modelling suggested that electron temperature gradient (ETG) turbulence may lead to an anti-gyroBohm isotope scaling in JET high-performance hybrid H-mode scenarios. A dedicated comparison study against higher-fidelity turbulence modelling invalidates this claim. Ion-scale turbulence with magnetic field perturbations included, can match the power balance fluxes within temperature gradient error margins. Multiscale gyrokinetic simulations from two distinct codes produce no significant ETG heat flux, demonstrating that simple rules-of-thumb are insufficient criteria for its onset.
2021, Articolo in rivista, ENG
Fast ion transport by sawtooth instability in the presence of ICRF-NBI synergy in JET plasmas
Teplukhina A.A.; Podesta M.; Poli F.M.; Szepesi G.; Kazakov Y.O.; Bonofiglo P.J.; Gorelenkova M.; Nocente M.; Ongena J.; Stancar Z.; Jet Contributors
JET experiments have shown that the three-ion scenarios using waves in the ion cyclotron range of frequencies (ICRF) is an efficient way to build fast ion population through beam ion acceleration by radio frequency (RF) waves. Such a heating scheme is applied to plasmas with at least two thermal ion species. Analysis of mixed discharges with complex heating schemes requires a workflow that allows to model thermal and fast ion transport consistently. This paper is dedicated to modelling of a mixed plasma discharge with significant fraction of fast ions and contributes to development of fast ion transport models. For interpretive analysis with the TRANSP code a JET hydrogen-deuterium plasma discharge with neutral beam injection (NBI) and ICRF heating has been chosen. The task is complicated by NBI-ICRF synergy and plasma magnetohydrodynamic activity, like sawtooth crashes. D beam ions accelerated by RF waves form a high energy tail in fast ion distribution. Significant difference between the neutron rate computed by TRANSP and measured one is observed if the same diffusivity for electrons and ions is assumed. Sensitivity studies show that uncertainties in input plasma parameters and thermal ion transport models are crucial for modelling mixed plasma discharges and increased D transport is required to reach the plasma composition consistent with diagnostic measurements at the plasma edge. Fast ion redistribution by a sawtooth instability is characterised by non-resonant transport due to reconnection of magnetic field lines and resonant transport caused by resonance interaction between the instability and fast ions. With ORBIT simulations it has been shown that resonant interaction strongly affects fast ions of high energies, like beam ions accelerated by RF waves and fusion products. For the considered case, fast ion profiles simulated by ORBIT remain peaked after the sawtooth crashes.
2021, Articolo in rivista, ENG
First principle-based multi-channel integrated modelling in support to the design of the Divertor Tokamak Test facility
Casiraghi I.; Mantica P.; Koechl F.; Ambrosino R.; Baiocchi B.; Castaldo A.; Citrin J.; Dicorato M. ; Frassinetti L.; Mariani A.; Vincenzi P.; Agostinetti P.; Aucone L.; Balbinot L.; Ceccuzzi S.; Figini L.; Granucci G.; Innocente P.; Johnson T.; Nystrom H.; Valisa M.
An intensive integrated modelling work of the main scenarios of the new Divertor Tokamak Test (DTT) facility with a single null divertor configuration has been performed using first principle quasi-linear transport models, in support of the design of the device and of the definition of its scientific work programme. First results of this integrated modelling work on DTT (R0 = 2.14 m, a = 0.65 m) are presented here along with outcome of the gyrokinetic simulations used to validate the reduced models in the DTT range of parameters. As a result of this work, the heating mix has been defined, the size of device has been increased to R0 = 2.19 m and a = 0.70 m, the use of pellets for fuelling has been recommended and reference profiles for diagnostic design, estimates of neutron yields and fast particle losses have been made available.
2020, Articolo in rivista, ENG
Predictive multi-channel flux-driven modelling to optimise ICRH tungsten control and fusion performance in JET
Casson F.J.; Patten H.; Bourdelle C.; Breton S.; Citrin J.; Koechl F.; Sertoli M.; Angioni C.; Baranov Y.; Bilato R.; Belli E.A.; Challis C.D.; Corrigan G.; Czarnecka A.; Ficker O.; Frassinetti L.; Garzotti L.; Goniche M.; Graves J.P.; Johnson T.; Kirov K.; Knight P.; Lerche E.; Mantsinen M.; Mylnar J.; Valisa M.; JET contributors
The evolution of the JET high performance hybrid scenario, including central accumulation of the tungsten (W) impurity, is reproduced with predictive multi-channel integrated modelling over multiple confinement times using first-principle based core transport models. Eight transport channels (Ti, Te, j, nD, nBe, nNi, nW, ) are modelled predictively, with self-consistent sources, radiation and magnetic equilibrium, yielding a system with multiple non-linearities: This system can reproduce the observed radiative temperature collapse after several confinement times. W is transported inward by neoclassical convection driven by the main ion density gradients and enhanced by poloidal asymmetries due to centrifugal acceleration. The slow evolution of the bulk density profile sets the timescale for W accumulation. Modelling this phenomenon requires a turbulent transport model capable of accurately predicting particle and momentum transport (QuaLiKiz) and a neoclassical transport model including the effects of poloidal asymmetries (NEO) coupled to an integrated plasma simulator (JINTRAC). The modelling capability is applied to optimise the available actuators to prevent W accumulation, and to extrapolate in power and pulse length. Central NBI heating is preferred for high performance, but gives central deposition of particles and torque which increase the risk of W accumulation by increasing density peaking and poloidal asymmetry. The primary mechanism for ICRH to control W in JET is via its impact through turbulence in reducing main ion density peaking (which drives inward neoclassical convection), increased temperature screening and turbulent W diffusion. The anisotropy from ICRH also reduces poloidal asymmetry, but this effect is negligible in high rotation JET discharges. High power ICRH near the axis can sensitively mitigate against W accumulation, and dominant ion heating (e.g. He-3 minority) is predicted to provide more resilience to W accumulation than dominant electron heating (e.g. H minority) in the JET hybrid scenario. Extrapolation to DT plasmas finds 17.5 MW of fusion power and improved confinement compared to DD, due to reduced ion-electron energy exchange, and increased Ti/Te stabilisation of ITG instabilities. The turbulence reduction in DT increases density peaking and accelerates the arrival of W on axis; this may be mitigated by reducing the penetration of the beam particle source with an increased pedestal density.
2020, Articolo in rivista, ENG
A Self-Contained and Automated Method for Flood Hazard Maps Prediction in Urban Areas
Sinagra, Marco; Nasello, Carmelo; Tucciarelli, Tullio; Barbetta, Silvia; Massari, Christian; Moramarco, Tommaso
Water depths and velocities predicted inside urban areas during severe storms are traditionally the final result of a chain of hydrologic and hydraulic models. The use of a single model embedding all the components of the rainfall-runoff transformation, including the flux concentration in the river network, can reduce the subjectivity and, as a consequence, the final uncertainty of the computed water depths and velocities. In the model construction, a crucial issue is the management of the topographic data. The information given by a Digital Elevation Model (DEM) available on a regular grid, as well as all the other elevation data provided by single points or contour lines, allow the creation of a Triangulated Irregular Network (TIN) based unstructured digital terrain model, which provides the spatial discretization for both the hydraulic and the hydrologic models. The procedure is split into four steps: (1) correction of the elevation z* measured in the nodes of a preliminary network connecting the edges with all the DEM cell centers; (2) the selection of a suitable hydrographic network where at least one edge of each node has a strictly descending elevation, (3) the generation of the computational mesh, whose edges include all the edges of the hydrographic network and also other lines following internal boundaries provided by roads or other infrastructures, and (4) the estimation of the elevation of the nodes of the computational mesh. A suitable rainfall-runoff transformation model is finally applied to each cell of the identified computational mesh. The proposed methodology is applied to the Sovara stream basin, in central Italy, for two flood events-one is used for parameter calibration and the other one for validation purpose. The comparison between the simulated and the observed flooded areas for the validation flood event shows a good reconstruction of the urban flooding.
DOI: 10.3390/w12051266
2020, Articolo in rivista, ENG
Mapping Landslide Prediction through a GIS-Based Model: A Case Study in a Catchment in Southern Italy
Federico Valerio Moresi, Mauro Maesano, Alessio Collalti, Roy C. Sidle, Giorgio Matteucci, Giuseppe Scarascia Mugnozza
Shallow landslides are an increasing concern in Italy and worldwide because of the frequent association with vegetation management. As vegetation cover plays a fundamental role in slope stability, we developed a GIS-based model to evaluate the influence of plant roots on slope safety, and also included a landslide susceptibility map. The GIS-based model, 4SLIDE, is a physically based predictor for shallow landslides that combines geological, topographical, and hydrogeological data. The 4SLIDE combines the infinite slope model, TOPMODEL (for the estimation of the saturated water level), and a vegetation root strength model, which facilitates prediction of locations that are more susceptible for shallow landslides as a function of forest cover. The aim is to define the spatial distribution of Factor of Safety (FS) in steep-forested areas. The GIS-based model 4SLIDE was tested in a forest mountain watershed located in the Sila Greca (Cosenza, Calabria, South Italy) where almost 93% of the area is covered by forest. The sensitive ROC analysis (Receiver Operating Characteristic) indicates that the model has good predictive capability in identifying the areas sensitive to shallow landslides. The localization of areas at risk of landslides plays an important role in land management activities because landslides are among the most costly and dangerous hazards.
2019, Articolo in rivista, ENG
Application of Gaussian process regression to plasma turbulent transport model validation via integrated modelling
Ho, A.; Citrin, J.; Auriemma, F.; Bourdelle, C.; Casson, F. J.; Kim, Hyun-Tae; Manas, P.; Szepesi, G.; Weisen, H.; Abduallev, S.; Abhangi, M.; Abreu, P.; Afzal, M.; Aggarwal, K. M.; Ahlgren, T.; Ahn, J. H.; Aho-Mantila, L.; Aiba, N.; Airila, M.; Albanese, R.; Aldred, V.; Alegre, D.; Alessi, E.; Aleynikov, P.; Alfier, A.; Alkseev, A.; Allinson, M.; Alper, B.; Alves, E.; Ambrosino, G.; Ambrosino, R.; Amicucci, L.; Amosov, V.; Sunden, E. Andersson; Angelone, M.; Anghel, M.; Angioni, C.; Appel, L.; Appelbee, C.; Arena, P.; Ariola, M.; Arnichand, H.; Arshad, S.; Ash, A.; Ashikawa, N.; Aslanyan, V.; Asunta, O.; Auriemma, F.; Austin, Y.; Avotina, L.; Axton, M. D.; Ayres, C.; Bacharis, M.; Baciero, A.; Baiao, D.; Bailey, S.; Baker, A.; Balboa, I.; Balden, M.; Balshaw, N.; Bament, R.; Banks, J. W.; Baranov, Y. F.; Barnard, M. A.; Barnes, D.; Barnes, M.; Barnsley, R.; Wiechec, A. Baron; Orte, L. Barrera; Baruzzo, M.; Basiuk, V.; Bassan, M.; Bastow, R.; Batista, A.; Batistoni, P.; Baughan, R.; Bauvir, B.; Baylor, L.; Bazylev, B.; Beal, J.; Beaumont, P. S.; Beckers, M.; Beckett, B.; Becoulet, A.; Bekris, N.; Beldishevski, M.; Bell, K.; Belli, F.; Bellinger, M.; Belonohy, E.; Ben Ayed, N.; Benterman, N. A.; Bergsaker, H.; Bernardo, J.; Bernert, M.; Berry, M.; Bertalot, L.; Besliu, C.; Beurskens, M.; Bieg, B.; Bielecki, J.; Biewer, T.; Bigi, M.; Bilkova, P.; Binda, F.; Bisoffi, A.; Bizarro, J. P. S.; Bjorkas, C.; Blackburn, J.; Blackman, K.; Blackman, T. R.; Blanchard, P.; Blatchford, P.; Bobkov, V.; Boboc, A.; Bodnar, G.; Bogar, O.; Bolshakova, I.; Bolzonella, T.; Bonanomi, N.; Bonelli, F.; Boom, J.; Booth, J.; Borba, D.; Borodin, D.; Borodkina, I.; Botrugno, A.; Bottereau, C.; Boulting, P.; Bourdelle, C.; Bowden, M.; Bower, C.; Bowman, C.; Boyce, T.; Boyd, C.; Boyer, H. J.; Bradshaw, J. M. A.; Braic, V.; Bravanec, R.; Breizman, B.; Bremond, S.; Brennan, P. D.; Breton, S.; Brett, A.; Brezinsek, S.; Bright, M. D. J.; Brix, M.; Broeckx, W.; Brombin, M.; Broslawski, A.; Brown, D. P. D.; Brown, M.; Bruno, E.; Bucalossi, J.; Buch, J.; Buchanan, J.; Buckley, M. A.; Budny, R.; Bufferand, H.; Bulman, M.; Bulmer, N.; Bunting, P.; Buratti, P.; Burckhart, A.; Buscarino, A.; Busse, A.; Butler, N. K.; Bykov, I.; Byrne, J.; Cahyna, P.; Calabro, G.; Calvo, I.; Camenen, Y.; Camp, P.; Campling, D. C.; Cane, J.; Cannas, B.; Capel, A. J.; Card, P. J.; Cardinali, A.; Carman, P.; Carr, M.; Carralero, D.; Carraro, L.; Carvalho, B. B.; Carvalho, I.; Carvalho, P.; Casson, F. J.; Castaldo, C.; Catarino, N.; Caumont, J.; Causa, F.; Cavazzana, R.; Cave-Ayland, K.; Cavinato, M.; Cecconello, M.; Ceccuzzi, S.; Cecil, E.; Cenedese, A.; Cesario, R.; Challis, C. D.; Chandler, M.; Chandra, D.; Chang, C. S.; Chankin, A.; Chapman, I. T.; Chapman, S. C.; Chernyshova, M.; Chitarin, G.; Ciraolo, G.; Ciric, D.; Citrin, J.; Clairet, F.; Clark, E.; Clark, M.; Clarkson, R.; Clatworthy, D.; Clements, C.; Cleverly, M.; Coad, J. P.; Coates, P. A.; Cobalt, A.; Coccorese, V.; Cocilovo, V.; Coda, S.; Coelho, R.; Coenen, J. W.; Coffey, I.; Colas, L.; Collins, S.; Conka, D.; Conroy, S.; Conway, N.; Coombs, D.; Cooper, D.; Cooper, S. R.; Corradino, C.; Corre, Y.; Corrigan, G.; Cortes, S.; Coster, D.; Couchman, A. S.; Cox, M. P.; Craciunescu, T.; Cramp, S.; Craven, R.; Crisanti, F.; Croci, G.; Croft, D.; Crombe, K.; Crowe, R.; Cruz, N.; Cseh, G.; Cufar, A.; Cullen, A.; Curuia, M.; Czarnecka, A.; Dabirikhah, H.; Dalgliesh, P.; Dalley, S.; Dankowski, J.; Darrow, D.; Davies, O.; Davis, W.; Day, C.; Day, I. E.; De Bock, M.; de Castro, A.; de la Cal, E.; de la Luna, E.; De Masi, G.; de Pablos, J. L.; De Temmerman, G.; De Tommasi, G.; de Vries, P.; Deakin, K.; Deane, J.; Agostini, F. Degli; Dejarnac, R.; Delabie, E.; den Harder, N.; Dendy, R. O.; Denis, J.; Denner, P.; Devaux, S.; Devynck, P.; Di Maio, F.; Di Siena, A.; Di Troia, C.; Dinca, P.; D'Inca, R.; Ding, B.; Dittmar, T.; Doerk, H.; Doerner, R. P.; Donne, T.; Dorling, S. E.; Dormido-Canto, S.; Doswon, S.; Douai, D.; Doyle, P. T.; Drenik, A.; Drewelow, P.; Drews, P.; Duckworth, Ph.; Dumont, R.; Dumortier, P.; Dunai, D.; Dunne, M.; Duran, I.; Durodie, F.; Dutta, P.; Duval, B. P.; Dux, R.; Dylst, K.; Dzysiuk, N.; Edappala, P. V.; Edmond, J.; Edwards, A. M.; Edwards, J.; Eich, Th.; Ekedahl, A.; El-Jorf, R.; Elsmore, C. G.; Enachescu, M.; Ericsson, G.; Eriksson, F.; Eriksson, J.; Eriksson, L. G.; Esposito, B.; Esquembri, S.; Esser, H. G.; Esteve, D.; Evans, B.; Evans, G. E.; Evison, G.; Ewart, G. D.; Fagan, D.; Faitsch, M.; Falie, D.; Fanni, A.; Fasoli, A.; Faustin, J. M.; Fawlk, N.; Fazendeiro, L.; Fedorczak, N.; Felton, R. C.; Fenton, K.; Fernades, A.; Fernandes, H.; Ferreira, J.; Fessey, J. A.; Fevrier, O.; Ficker, O.; Field, A.; Fietz, S.; Figueiredo, A.; Figueiredo, J.; Fil, A.; Finburg, P.; Firdaouss, M.; Fischer, U.; Fittill, L.; Fitzgerald, M.; Flammini, D.; Flanagan, J.; Fleming, C.; Flinders, K.; Fonnesu, N.; Fontdecaba, J. M.; Formisano, A.; Forsythe, L.; Fortuna, L.; Fortuna-Zalesna, E.; Fortune, M.; Foster, S.; Franke, T.; Franklin, T.; Frasca, M.; Frassinetti, L.; Freisinger, M.; Fresa, R.; Frigione, D.; Fuchs, V.; Fuller, D.; Futatani, S.; Fyvie, J.; Gal, K.; Galassi, D.; Galazka, K.; Galdon-Quiroga, J.; Gallagher, J.; Gallart, D.; Galvao, R.; Gao, X.; Gao, Y.; Garcia, J.; Garcia-Carrasco, A.; Garcia-Munoz, M.; Gardarein, J. -L.; Garzotti, L.; Gaudio, P.; Gauthier, E.; Gear, D. F.; Gee, S. J.; Geiger, B.; Gelfusa, M.; Gerasimov, S.; Gervasini, G.; Gethins, M.; Ghani, Z.; Ghate, M.; Gherendi, M.; Giacalone, J. C.; Giacomelli, L.; Gibson, C. S.; Giegerich, T.; Gil, C.; Gil, L.; Gilligan, S.; Gin, D.; Giovannozzi, E.; Girardo, J. B.; Giroud, C.; Giruzzi, G.; Gloeggler, S.; Godwin, J.; Goff, J.; Gohil, P.; Goloborod'ko, V.; Gomes, R.; Goncalves, B.; Goniche, M.; Goodliffe, M.; Goodyear, A.; Gorini, G.; Gosk, M.; Goulding, R.; Goussarov, A.; Gowland, R.; Graham, B.; Graham, M. E.; Graves, J. P.; Grazier, N.; Grazier, P.; Green, N. R.; Greuner, H.; Grierson, B.; Griph, F. S.; Grisolia, C.; Grist, D.; Groth, M.; Grove, R.; Grundy, C. N.; Grzonka, J.; Guard, D.; Guerard, C.; Guillemaut, C.; Guirlet, R.; Gurl, C.; Utoh, H. H.; Hackett, L. J.; Hacquin, S.; Hagar, A.; Hager, R.; Hakola, A.; Halitovs, M.; Hall, S. J.; Cook, S. P. Hallworth; Hamlyn-Harris, C.; Hammond, K.; Harrington, C.; Harrison, J.; Harting, D.; Hasenbeck, F.; Hatano, Y.; Hatch, D. R.; Haupt, T. D. V.; Hawes, J.; Hawkes, N. C.; Hawkins, J.; Hawkins, P.; Haydon, P. W.; Hayter, N.; Hazel, S.; Heesterman, P. J. L.; Heinola, K.; Hellesen, C.; Hellsten, T.; Helou, W.; Hemming, O. N.; Hender, T. C.; Henderson, M.; Henderson, S. S.; Henriques, R.; Hepple, D.; Hermon, G.; Hertout, P.; Hidalgo, C.; Highcock, E. G.; Hill, M.; Hillairet, J.; Hillesheim, J.; Hillis, D.; Hizanidis, K.; Hjalmarsson, A.; Hobirk, J.; Hodille, E.; Hogben, C. H. A.; Hogeweij, G. M. D.; Hollingsworth, A.; Hollis, S.; Homfray, D. A.; Horacek, J.; Hornung, G.; Horton, A. R.; Horton, L. D.; Horvath, L.; Hotchin, S. P.; Hough, M. R.; Howarth, P. J.; Hubbard, A.; Huber, A.; Huber, V.; Huddleston, T. M.; Hughes, M.; Huijsmans, G. T. A.; Hunter, C. L.; Huynh, P.; Hynes, A. M.; Iglesias, D.; Imazawa, N.; Imbeaux, F.; Imrisek, M.; Incelli, M.; Innocente, P.; Irishkin, M.; Ivanova-Stanik, I.; Jachmich, S.; Jacobsen, A. S.; Jacquet, P.; Jansons, J.; Jardin, A.; Jarvinen, A.; Jaulmes, F.; Jednorog, S.; Jenkins, I.; Jeong, C.; Jepu, I.; Joffrin, E.; Johnson, R.; Johnson, T.; Johnston, Jane; Joita, L.; Jones, G.; Jones, T. T. C.; Hoshino, K. K.; Kallenbach, A.; Kamiya, K.; Kaniewski, J.; Kantor, A.; Kappatou, A.; Karhunen, J.; Karkinsky, D.; Karnowska, I.; Kaufman, M.; Kaveney, G.; Kazakov, Y.; Kazantzidis, V.; Keeling, D. L.; Keenan, T.; Keep, J.; Kempenaars, M.; Kennedy, C.; Kenny, D.; Kent, J.; Kent, O. N.; Khilkevich, E.; Kim, H. T.; Kim, H. S.; Kinch, A.; King, C.; King, D.; King, R. F.; Kinna, D. J.; Kiptily, V.; Kirk, A.; Kirov, K.; Kirschner, A.; Kizane, G.; Klepper, C.; Klix, A.; Knight, P.; Knipe, S. J.; Knott, S.; Kobuchi, T.; Koechl, F.; Kocsis, G.; Kodeli, I.; Kogan, L.; Kogut, D.; Koivuranta, S.; Kominis, Y.; Koeppen, M.; Kos, B.; Koskela, T.; Koslowski, H. R.; Koubiti, M.; Kovari, M.; Kowalska-Strzeciwilk, E.; Krasilnikov, A.; Krasilnikov, V.; Krawczyk, N.; Kresina, M.; Krieger, K.; Krivska, A.; Kruezi, U.; Ksiazek, I.; Kukushkin, A.; Kundu, A.; Kurki-Suonio, T.; Kwak, S.; Kwiatkowski, R.; Kwon, O. J.; Laguardia, L.; Lahtinen, A.; Laing, A.; Lam, N.; Lambertz, H. T.; Lane, C.; Lang, P. T.; Lanthaler, S.; Lapins, J.; Lasa, A.; Last, J. R.; Laszynska, E.; Lawless, R.; Lawson, A.; Lawson, K. D.; Lazaros, A.; Lazzaro, E.; Leddy, J.; Lee, S.; Lefebvre, X.; Leggate, H. J.; Lehmann, J.; Lehnen, M.; Leichtle, D.; Leichuer, P.; Leipold, F.; Lengar, I.; Lennholm, M.; Lerche, E.; Lescinskis, A.; Lesnoj, S.; Letellier, E.; Leyland, M.; Leysen, W.; Li, L.; Liang, Y.; Likonen, J.; Linke, J.; Linsmeier, Ch.; Lipschultz, B.; Liu, G.; Liu, Y.; Lo Schiavo, V. P.; Loarer, T.; Loarte, A.; Lobel, R. C.; Lomanowski, B.; Lomas, P. J.; Lonnroth, J.; Lopez, J. M.; Lopez-Razola, J.; Lorenzini, R.; Losada, U.; Lovell, J. J.; Loving, A. B.; Lowry, C.; Luce, T.; Lucock, R. M. A.; Lukin, A.; Luna, C.; Lungaroni, M.; Lungu, C. P.; Lungu, M.; Lunniss, A.; Lupelli, I.; Lyssoivan, A.; Macdonald, N.; Macheta, P.; Maczewa, K.; Magesh, B.; Maget, P.; Maggi, C.; Maier, H.; Mailloux, J.; Makkonen, T.; Makwana, R.; Malaquias, A.; Malizia, A.; Manas, P.; Manning, A.; Manso, M. E.; Mantica, P.; Mantsinen, M.; Manzanares, A.; Maquet, Ph.; Marandet, Y.; Marcenko, N.; Marchetto, C.; Marchuk, O.; Marinelli, M.; Marinucci, M.; Markovic, T.; Marocco, D.; Marot, L.; Marren, C. A.; Marshal, R.; Martin, A.; Martin, Y.; Martin de Aguilera, A.; Martinez, F. J.; Martin-Solis, J. R.; Martynova, Y.; Maruyama, S.; Masiello, A.; Maslov, M.; Matejcik, S.; Mattei, M.; Matthews, G. F.; Maviglia, F.; Mayer, M.; Mayoral, M. L.; May-Smith, T.; Mazon, D.; Mazzotta, C.; McAdams, R.; McCarthy, P. J.; McClements, K. G.; McCormack, O.; McCullen, P. A.; McDonald, D.; McIntosh, S.; McKean, R.; McKehon, J.; Meadows, R. C.; Meakins, A.; Medina, F.; Medland, M.; Medley, S.; Meigh, S.; Meigs, A. G.; Meisl, G.; Meitner, S.; Meneses, L.; Menmuir, S.; Mergia, K.; Merrigan, I. R.; Mertens, Ph.; Meshchaninov, S.; Messiaen, A.; Meyer, H.; Mianowski, S.; Michling, R.; Middleton-Gear, D.; Miettunen, J.; Militello, F.; Militello-Asp, E.; Miloshevsky, G.; Mink, F.; Minucci, S.; Miyoshi, Y.; Mlynar, J.; Molina, D.; Monakhov, I.; Moneti, M.; Mooney, R.; Moradi, S.; Mordijck, S.; Moreira, L.; Moreno, R.; Moro, F.; Morris, A. W.; Morris, J.; Moser, L.; Mosher, S.; Moulton, D.; Murari, A.; Muraro, A.; Murphy, S.; Asakura, N. N.; Na, Y. S.; Nabais, F.; Naish, R.; Nakano, T.; Nardon, E.; Naulin, V.; Nave, M. F. F.; Nedzelski, I.; Nemtsev, G.; Nespoli, F.; Neto, A.; Neu, R.; Neverov, V. S.; Newman, M.; Nicholls, K. J.; Nicolas, T.; Nielsen, A. H.; Nielsen, P.; Nilsson, E.; Nishijima, D.; Noble, C.; Nocente, M.; Nodwell, D.; Nordlund, K.; Nordman, H.; Nouailletas, R.; Nunes, I.; Oberkofler, M.; Odupitan, T.; Ogawa, M. T.; O'Gorman, T.; Okabayashi, M.; Olney, R.; Omolayo, O.; O'Mullane, M.; Ongena, J.; Orsitto, F.; Orszagh, J.; Oswuigwe, B. I.; Otin, R.; Owen, A.; Paccagnella, R.; Pace, N.; Pacella, D.; Packer, L. W.; Page, A.; Pajuste, E.; Palazzo, S.; Pamela, S.; Panja, S.; Papp, P.; Paprok, R.; Parail, V.; Park, M.; Diaz, F. Parra; Parsons, M.; Pasqualotto, R.; Patel, A.; Pathak, S.; Paton, D.; Patten, H.; Pau, A.; Pawelec, E.; Soldan, C. Paz; Peackoc, A.; Pearson, I. J.; Pehkonen, S. -P.; Peluso, E.; Penot, C.; Pereira, A.; Pereira, R.; Puglia, P. P. Pereira; von Thun, C. Perez; Peruzzo, S.; Peschanyi, S.; Peterka, M.; Petersson, P.; Petravich, G.; Petre, A.; Petrella, N.; Petrzilka, V.; Peysson, Y.; Pfefferle, D.; Philipps, V.; Pillon, M.; Pintsuk, G.; Piovesan, P.; Pires dos Reis, A.; Piron, L.; Pironti, A.; Pisano, F.; Pitts, R.; Pizzo, F.; Plyusnin, V.; Pomaro, N.; Pompilian, O. G.; Pool, P. J.; Popovichev, S.; Porfiri, M. T.; Porosnicu, C.; Porton, M.; Possnert, G.; Potzel, S.; Powell, T.; Pozzi, J.; Prajapati, V.; Prakash, R.; Prestopino, G.; Price, D.; Price, M.; Price, R.; Prior, P.; Proudfoot, R.; Pucella, G.; Puglia, P.; Puiatti, M. E.; Pulley, D.; Purahoo, K.; Puetterich, Th.; Rachlew, E.; Rack, M.; Ragona, R.; Rainford, M. S. J.; Rakha, A.; Ramogida, G.; Ranjan, S.; Rapson, C. J.; Rasmussen, J. J.; Rathod, K.; Ratta, G.; Ratynskaia, S.; Ravera, G.; Rayner, C.; Rebai, M.; Reece, D.; Reed, A.; Refy, D.; Regan, B.; Regana, J.; Reich, M.; Reid, N.; Reimold, F.; Reinhart, M.; Reinke, M.; Reiser, D.; Rendell, D.; Reux, C.; Reyes Cortes, S. D. A.; Reynolds, S.; Riccardo, V.; Richardson, N.; Riddle, K.; Rigamonti, D.; Rimini, F. G.; Risner, J.; Riva, M.; Roach, C.; Robins, R. J.; Robinson, S. A.; Robinson, T.; Robson, D. W.; Roccella, R.; Rodionov, R.; Rodrigues, P.; Rodriguez, J.; Rohde, V.; Romanelli, F.; Romanelli, M.; Romanelli, S.; Romazanov, J.; Rowe, S.; Rubel, M.; Rubinacci, G.; Rubino, G.; Ruchko, L.; Ruiz, M.; Ruset, C.; Rzadkiewicz, J.; Saarelma, S.; Sabot, R.; Safi, E.; Sagar, P.; Saibene, G.; Saint-Laurent, F.; Salewski, M.; Salmi, A.; Salmon, R.; Salzedas, F.; Samaddar, D.; Samm, U.; Sandiford, D.; Santa, P.; Santala, M. I. K.; Santos, B.; Santucci, A.; Sartori, F.; Sartori, R.; Sauter, O.; Scannell, R.; Schlummer, T.; Schmid, K.; Schmidt, V.; Schmuck, S.; Schneider, M.; Schoepf, K.; Schworer, D.; Scott, S. D.; Sergienko, G.; Sertoli, M.; Shabbir, A.; Sharapov, S. E.; Shaw, A.; Shaw, R.; Sheikh, H.; Shepherd, A.; Shevelev, A.; Shumack, A.; Sias, G.; Sibbald, M.; Sieglin, B.; Silburn, S.; Silva, A.; Silva, C.; Simmons, P. A.; Simpson, J.; Simpson-Hutchinson, J.; Sinha, A.; Sipila, S. K.; Sips, A. C. C.; Siren, P.; Sirinelli, A.; Sjostrand, H.; Skiba, M.; Skilton, R.; Slabkowska, K.; Slade, B.; Smith, N.; Smith, P. G.; Smith, R.; Smith, T. J.; Smithies, M.; Snoj, L.; Soare, S.; Solano, E. R.; Somers, A.; Sommariva, C.; Sonato, P.; Sopplesa, A.; Sousa, J.; Sozzi, C.; Spagnolo, S.; Spelzini, T.; Spineanu, F.; Stables, G.; Stamatelatos, I.; Stamp, M. F.; Staniec, P.; Stankunas, G.; Stan-Sion, C.; Stead, M. J.; Stefanikova, E.; Stepanov, I.; Stephen, A. V.; Stephen, M.; Stevens, A.; Stevens, B. D.; Strachan, J.; Strand, P.; Strauss, H. R.; Strom, P.; Stubbs, G.; Studholme, W.; Subba, F.; Summers, H. P.; Svensson, J.; Swiderski, L.; Szabolics, T.; Szawlowski, M.; Szepesi, G.; Suzuki, T. T.; Tal, B.; Tala, T.; Talbot, A. R.; Talebzadeh, S.; Taliercio, C.; Tamain, P.; Tame, C.; Tang, W.; Tardocchi, M.; Taroni, L.; Taylor, D.; Taylor, K. A.; Tegnered, D.; Telesca, G.; Teplova, N.; Terranova, D.; Testa, D.; Tholerus, E.; Thomas, J.; Thomas, J. D.; Thomas, P.; Thompson, A.; Thompson, C. -A.; Thompson, V. K.; Thorne, L.; Thornton, A.; Thrysoe, A. S.; Tigwell, P. A.; Tipton, N.; Tiseanu, I.; Tojo, H.; Tokitani, M.; Tolias, P.; Tomes, M.; Tonner, P.; Towndrow, M.; Trimble, P.; Tripsky, M.; Tsalas, M.; Tsavalas, P.; Jun, D. Tskhakaya; Turner, I.; Turner, M. M.; Turnyanskiy, M.; Tvalashvili, G.; Tyrrell, S. G. J.; Uccello, A.; Ul-Abidin, Z.; Uljanovs, J.; Ulyatt, D.; Urano, H.; Uytdenhouwen, I.; Vadgama, A. P.; Valcarcel, D.; Valentinuzzi, M.; Valisa, M.; Olivares, P. Vallejos; Valovic, M.; Van De Mortel, M.; Van Eester, D.; Van Renterghem, W.; van Rooij, G. J.; Varje, J.; Varoutis, S.; Vartanian, S.; Vasava, K.; Vasilopoulou, T.; Vega, J.; Verdoolaege, G.; Verhoeven, R.; Verona, C.; Rinati, G. Verona; Veshchev, E.; Vianello, N.; Vicente, J.; Viezzer, E.; Villari, S.; Villone, F.; Vincenzi, P.; Vinyar, I.; Viola, B.; Vitins, A.; Vizvary, Z.; Vlad, M.; Voitsekhovitch, I.; Vondracek, P.; Vora, N.; Vu, T.; Pires de Sa, W. 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This paper outlines an approach towards improved rigour in tokamak turbulence transport model validation within integrated modelling. Gaussian process regression (GPR) techniques were applied for profile fitting during the preparation of integrated modelling simulations allowing for rigourous sensitivity tests of prescribed initial and boundary conditions as both fit and derivative uncertainties are provided. This was demonstrated by a JETTO integrated modelling simulation of the JET ITER-like-wall H-mode baseline discharge #92436 with the QuaLiKiz quasilinear turbulent transport model, which is the subject of extrapolation towards a deuterium-tritium plasma. The simulation simultaneously evaluates the time evolution of heat, particle, and momentum fluxes over similar to 10 confinement times, with a simulation boundary condition at rho(tor) = 0.85. Routine inclusion of momentum transport prediction in multi-channel flux-driven transport modelling is not standard and is facilitated here by recent developments within the QuaLiKiz model. Excellent agreement was achieved between the fitted and simulated profiles for n(e), T-e, T-i, and Omega(tor) within 2 sigma, but the simulation underpredicts the mid-radius Ti and overpredicts the core n(e) and T-e profiles for this discharge. Despite this, it was shown that this approach is capable of deriving reasonable inputs, including derivative quantities, to tokamak models from experimental data. Furthermore, multiple figures-of-merit were defined to quantitatively assess the agreement of integrated modelling predictions to experimental data within the GPR profile fitting framework.
2016, Articolo in rivista, ENG
Modelling third harmonic ion cyclotron acceleration of deuterium beams for JET fusion product studies experiments
Schneider, M.; Johnson, T.; Dumont, R.; Eriksson, J.; Eriksson, L. -G.; Giacomelli, L.; Girardo, J. -B.; Hellsten, T.; Khilkevitch, E.; Kiptily, V. G.; Koskela, T.; Mantsinen, M.; Nocente, M.; Salewski, M.; Sharapov, S. E.; Shevelev, A. E.
Recent JET experiments have been dedicated to the studies of fusion reactions between deuterium (D) and Helium-3 (He-3) ions using neutral beam injection (NBI) in synergy with third harmonic ion cyclotron radio-frequency heating (ICRH) of the beam. This scenario generates a fast ion deuterium tail enhancing DD and (DHe)-He-3 fusion reactions. Modelling and measuring the fast deuterium tail accurately is essential for quantifying the fusion products. This paper presents the modelling of the D distribution function resulting from the NBI+ICRF heating scheme, reinforced by a comparison with dedicated JET fast ion diagnostics, showing an overall good agreement. Finally, a sawtooth activity for these experiments has been observed and interpreted using SPOT/RFOF simulations in the framework of Porcelli's theoretical model, where NBI+ICRH accelerated ions are found to have a strong stabilizing effect, leading to monster sawteeth.
2014, Articolo in rivista, ENG
The European Integrated Tokamak Modelling (ITM) effort: achievements and first physics results
Falchetto, G. L.; Coster, D.; Coelho, R.; Scott, B. D.; Figini, L.; Kalupin, D.; Nardon, E.; Nowak, S.; Alves, L. L.; Artaud, J. F.; Basiuk, V.; Bizarro, Jao P. S.; Boulbe, C.; Dinklage, A.; Farina, D.; Faugeras, B.; Ferreira, J.; Figueiredo, A.; Huynh, Ph; Imbeaux, F.; Ivanova-Stanik, I.; Jonsson, T.; Klingshirn, H-J; Konz, C.; Kus, A.; Marushchenko, N. B.; Pereverzev, G.; Owsiak, M.; Poli, E.; Peysson, Y.; Reimer, R.; Signoret, J.; Sauter, O.; Stankiewicz, R.; Strand, P.; Voitsekhovitch, I.; Westerhof, E.; Zok, T.; Zwingmann, W.
A selection of achievements and first physics results are presented of the European Integrated Tokamak Modelling Task Force (EFDA ITM-TF) simulation framework, which aims to provide a standardized platform and an integrated modelling suite of validated numerical codes for the simulation and prediction of a complete plasma discharge of an arbitrary tokamak. The framework developed by the ITM-TF, based on a generic data structure including both simulated and experimental data, allows for the development of sophisticated integrated simulations (workflows) for physics application.The equilibrium reconstruction and linear magnetohydrodynamic (MHD) stability simulation chain was applied, in particular, to the analysis of the edgeMHDstability of ASDEX Upgrade type-I ELMy H-mode discharges and ITER hybrid scenario, demonstrating the stabilizing effect of an increased Shafranov shift on edge modes. Interpretive simulations of a JET hybrid discharge were performed with two electromagnetic turbulence codes within ITM infrastructure showing the signature of trapped-electron assisted ITG turbulence. A successful benchmark among five EC beam/ray-tracing codes was performed in the ITM framework for an ITER inductive scenario for different launching conditions from the equatorial and upper launcher, showing good agreement of the computed absorbed power and driven current. Selected achievements and scientific workflow applications targeting key modelling topics and physics problems are also presented, showing the current status of the ITM-TF modelling suite.
2014, Articolo in rivista, ENG
Corrigendum: The European Integrated Tokamak Modelling (ITM) effort: achievements and first physics results (vol 54, 043018, 2014)
Falchetto, G. L.; Coster, D.; Coelho, R.; Scott, B. D.; Figini, L.; Kalupin, D.; Nardon, E.; Nowak, S.; Alves, L. L.; Artaud, J. F.; Basiuk, V.; Bizarro, Joao P. S.; Boulbe, C.; Dinklage, A.; Farina, D.; Faugeras, B.; Ferreira, J.; Figueiredo, A.; Huynh, Ph.; Imbeaux, F.; Ivanova-Stanik, I.; Jonsson, T.; Klingshirn, H. -J.; Konz, C.; Kus, A.; Marushchenko, N. B.; Pereverzev, G.; Owsiak, M.; Poli, E.; Peysson, Y.; Reimer, R.; Signoret, J.; Sauter, O.; Stankiewicz, R.; Strand, P.; Voitsekhovitch, I.; Westerhof, E.; Zok, T.; Zwingmann, W.
References [59-61] were incorrectly cited in Falchetto G.L. et al 2014 (Nucl. Fusion 54 043018), the corresponding paragraphs on page 14-15 should be replaced ...
2003, Articolo in rivista, ENG
Modelling the responses of the Lagoon of Venice ecosystem to variations in physical forcings
Melaku Canu D. (a), Solidoro C. (b), Umgiesser G. (a)
A Finite Element Ecological Model for the Lagoon of Venice (VELFEEM) has been used to test the responses of the Lagoon of Venice ecosystem to variations in physical conditions. The model is obtained by coupling a finite element hydrodynamic model, that computes the velocity fields of water, an energetic model to compute the water temperature fields, and an ecological model that simulates the dynamic of phytoplankton, zooplankton, nutrients (ammonia, nitrate and phosphate) organic detritus (organic nitrogen, organic phosphorous and CBOD) and dissolved oxygen. The transport model is a two-dimensional barotropic finite element model which allows for a better resolution of the lagoon morphology. The ecological model has been developed by starting from the ecological module EUTRO of WASP (Water Analysis Simulation System released by US EPA), and by adapting it to the peculiarity of the Lagoon of Venice. A reference condition has been identified by running a 1-year simulation under climatologic condition. Then, the sensitivity to physical forcing (tide and wind) and to the input of macronutrients has been investigated, by comparing model predictions of spatial and temporal evolution of major state variables and of an aggregate index of Water Quality Trophic Index (TRIX).