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New 0-D methodology for predicting NO formation under continuously varying temperature and mixture composition conditions

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dc.contributor.author Benajes Calvo, Jesus Vicente es_ES
dc.contributor.author López Sánchez, José Javier es_ES
dc.contributor.author Molina Alcaide, Santiago Alberto es_ES
dc.contributor.author Redón Lurbe, Pau es_ES
dc.date.accessioned 2016-06-06T11:49:22Z
dc.date.available 2016-06-06T11:49:22Z
dc.date.issued 2015-02
dc.identifier.issn 0196-8904
dc.identifier.uri http://hdl.handle.net/10251/65310
dc.description.abstract The development of new diesel combustion modes characterized by low combustion temperatures, to minimize the NOx emissions, has caused a noticeable change in the diesel spray s structure and in the NOx chemistry, gaining relevance the N2O and the prompt routes in detriment of the thermal mechanism.Therefore, to accurately predict the NOx emissions, the detailed chemistry and physics must be taken into account, with the consequence of increasing the computational cost. The authors propose in the current study a new predictive methodology associated to low computational cost, where detailed chemistry and simplified physics are considered. To diminish even more the computational cost, the chemistry was tabulated as a function of temperature and oxygen excess mass fraction (parameter which effectively couples the equivalence ratio and the EGR rate). This tool has been developed with the objective of being applicable in continuously varying temperature and mixture fraction conditions (the diffusion diesel spray context) and was validated with the Two-Stage Lagrangian model (TSL-model) and with real engine measurements. The results in both validation scenarios reflect a high degree of accuracy making it applicable, at least, to perform qualitative predictions. By extension, it is expected to perform similarly in continuously varying temperature conditions (i.e.: homogenous charge compression ignition diesel combustion modes) which are less demanding computationally speaking. es_ES
dc.description.sponsorship The authors would like to acknowledge the contribution of the Spanish Ministry of Economic and Competitively for the financial support of the present research study associate to the projects TRA 2008-06448 (VELOSOOT) and to Dr. V. Golovitchev for his valuable comments and suggestions. en_EN
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Energy Conversion and Management es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject NO formation es_ES
dc.subject Diffusion combustion es_ES
dc.subject Diesel engines es_ES
dc.subject Chemical kinetics es_ES
dc.subject 0-D modeling es_ES
dc.subject.classification MAQUINAS Y MOTORES TERMICOS es_ES
dc.title New 0-D methodology for predicting NO formation under continuously varying temperature and mixture composition conditions es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.enconman.2014.12.010
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//TRA2008-06448/ES/ESTUDIO DE COMPRENSION DE PROCESOS DE COMBUSTION DIESEL CON BAJA FORMACION DE HOLLIN/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario CMT-Motores Térmicos - Institut Universitari CMT-Motors Tèrmics es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Máquinas y Motores Térmicos - Departament de Màquines i Motors Tèrmics es_ES
dc.description.bibliographicCitation Benajes Calvo, JV.; López Sánchez, JJ.; Molina Alcaide, SA.; Redón Lurbe, P. (2015). New 0-D methodology for predicting NO formation under continuously varying temperature and mixture composition conditions. Energy Conversion and Management. 91:367-376. https://doi.org/10.1016/j.enconman.2014.12.010 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1016/j.enconman.2014.12.010 es_ES
dc.description.upvformatpinicio 367 es_ES
dc.description.upvformatpfin 376 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 91 es_ES
dc.relation.senia 298542 es_ES
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES


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