000062032 001__ 62032
000062032 005__ 20170908131837.0
000062032 0247_ $$2doi$$a10.5424/sjar/2014123-5507
000062032 0248_ $$2sideral$$a87790
000062032 037__ $$aART-2014-87790
000062032 041__ $$aeng
000062032 100__ $$aOuazaa, S.
000062032 245__ $$aSimulating water distribution patterns for fixed spray plate sprinkler using the ballistic theory
000062032 260__ $$c2014
000062032 5060_ $$aAccess copy available to the general public$$fUnrestricted
000062032 5203_ $$aBallistic simulation of the spray sprinkler for self-propelled irrigation machines requires the incorporation of the effect of the jet impact with the deflecting plate. The kinetic energy losses produced by the jet impact with the spray plate were experimentally characterized for different nozzle sizes and two working pressures for fixed spray plate sprinklers (FSPS). A technique of low speed photography was used to determine drop velocity at the point where the jet is broken into droplets. The water distribution pattern of FSPS for different nozzle sizes, working at two pressures and under different wind conditions were characterized in field experiments. The ballistic model was calibrated to simulate water distribution in different technical and meteorological conditions. Field experiments and the ballistic model were used to obtain the model parameters (D50, n, K1 and K2). The results show that kinetic energy losses decrease with nozzle diameter increments; from 80% for the smallest nozzle diameter (2 mm) to 45% for nozzle diameters larger than 5.1 mm, and from 80% for the smallest nozzle diameter (2 mm) to 34.7% for nozzle diameters larger than 6.8 mm, at 138 kPa and 69 kPa working pressures, respectively. The results from the model compared well with field observations. The calibrated model has reproduced accurately the water distribution pattern in calm (r = 0.98) and high windy conditions (r = 0.76). A new relationship was found between the corrector parameters (K1’ and K2’) and the wind speed. As a consequence, model simulation will be possible for untested meteorological conditions.
000062032 536__ $$9info:eu-repo/grantAgreement/ES/MICINN/AGL2010-21681-C03-01
000062032 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000062032 590__ $$a0.703$$b2014
000062032 591__ $$aAGRICULTURE, MULTIDISCIPLINARY$$b25 / 56 = 0.446$$c2014$$dQ2$$eT2
000062032 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000062032 700__ $$0(orcid)0000-0003-4367-2598$$aBurguete, J.
000062032 700__ $$aPaniagua, M.P.
000062032 700__ $$aSalvador, R.
000062032 700__ $$aZapata, N.
000062032 773__ $$g12, 3 (2014), 850-864$$pSpan. j. agric. res.$$tSPANISH JOURNAL OF AGRICULTURAL RESEARCH$$x1695-971X
000062032 8564_ $$s707856$$uhttps://zaguan.unizar.es/record/62032/files/texto_completo.pdf$$yVersión publicada
000062032 8564_ $$s106989$$uhttps://zaguan.unizar.es/record/62032/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000062032 909CO $$ooai:zaguan.unizar.es:62032$$particulos$$pdriver
000062032 951__ $$a2017-09-08-08:31:20
000062032 980__ $$aARTICLE