Advances in the development of DIS_tool and first analysis on TCV disruptions.

Disruptive events still represent a serious concern for the preservation of the structural integrity of large tokamaks . In the last years, thanks to ever increasing computing resources, data - driven approaches to predict disruptions have been continuously developed , dealing with ever larger databases and with data of different machines . The development of disruptions multi - machine database s [ 1 ] is particularly valuable to building a common base for modelling, to further improving the knowledge of the underlying disruption physics , and to extrapolate to larger next - step fusion devices, such as ITER and DEMO . In this perspective, for the first time a tool ( DIS_tool ) [2 ] to support the construction of a reliable and standardized disruption database has been developed and applied to JET and ASDEX Upgrade disruptions data. B y processing multiple diagnostics, DIS_tool is able to detect fast transient events depicting the disruptive process, such as thermal quenches and current spikes, and to comput e automatically characteristic times and parameters of interest . The detection is based on normalized thresholds and the algorithm is parameterized in such a way to run calculations regardless of the characteristic s of the specific machine . This paper will report the adva nces in the development of the tool, describing the extension and the preliminary analysis for TCV, a medium - size machine equipped with a carbon wall and cha racterized by extreme shaping versatility. A common framework to develop a "standardized" multi - mac hine disruption database will be discussed analysing how the variability in terms of machine size, control and experimental programs can affect the disruptive process itself, as well as the subsequent definition of the characteristic parameters.