A physically based model for thermal plasma arc attachment on a W-ThO2 cathode

Summary form only given. Arc attachment radius imposed a priori when modelling the coupling between cathode, cathode layer and thermal plasma still hinders models from being predictive, as underlined in a recent review1. The aim of this work was to find a physical element, still lacking in the models, which could contribute in governing the arc attachment. In this study the cathode layer is modeled within the frame of the partial local thermal equilibrium approach1 including the space charge layer, the Knudsen layer and the ionization layer, while the plasma column is assumed to be in local thermal equilibrium. Several modeling assumptions were questioned based on e.g. contradictory assumptions in the literature, or oversimplified physics compared to experimental observations. For testing model and assumptions, 5 mm argon arc test cases with a sharp cathode geometry that have been investigated experimentally in the literature were calculated. Within this framework, the following conclusions were drawn. The space charge emitted electrons is negligible. The Richardson-Dushman emission law supplemented with Schottky correction is used within its domain of validity when applied to thorium doped tungsten cathodes, which are mainly characterized by a field enhanced thermionic emission regime. The radiative heat absorption from the plasma at the cathode surface is not negligible compared to the radiative emission. Ignoring the non-homogeneous structure and composition of a doped tungsten cathode operated in these conditions leads to a large over-estimation of the extent of the arc attachment, and results in an under-estimation of the arc temperature. A cathode model based on physical criteria for taking into account a first level of the cathode inhomogeneity has a significant effect on the arc attachment and on arc properties such as temperature and pressure. The cathode physics is thus an important element to include for obtaining a comprehensive and predictive arc model.