Abstract: The present disclosure concerns a rotary apparatus (100) configured for inputting thermal energy (heat) into fluids by having fluidic stream repeatedly propagated through rotating and stationary components arranged inside said rotary apparatus in accordance with essentially helical trajectory. The rotary apparatus (100) comprises two or more rotor blade cascades (R1, R2) coaxially arranged on one or more rotor shaft(s), and at least two stationary vane cascades arranged upstream of a first rotor blade cascade (R1) and downstream of a rearmost rotor blade cascade (R2), respectively. In operation, fluid, such as gas, is heated inside the rotary apparatus while repeatedly passing through cascades S1-R1-R2-S2 in accordance with essentially helical trajectory. The rotor blade cascades can be configured to rotate in co- and counter directions and/or with the same or different speed.

Abstract: There is disclosed a method and system for operating a storage area network (SAN) simulator. The method comprises generating training data representative of a SAN system. The method also comprises generating a SAN simulator corresponding to the SAN system, where the SAN simulator outputs a predicted metric of at least one component of the SAN system. The method then comprises using the training data to train a machine learning algorithm (MLA) to determine adjustments for parameters of the SAN simulator.