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Motivated by the importance of accurate identification for a range of applications, this paper compares and contrasts the effective and efficient classification of network-based applications using behavioral observations of network-traffic and those using Deep-Packet Inspection.Importantly, throughout our work we are able to make comparison with data possessing an accurate, independently-determined ground-truth that describes the actual applications causing the network-traffic observed.In a unique study in both the spatial-domain: comparing across different network-locations and in the temporal-domain: comparing across a number of years of data, we illustrate the decay in classification accuracy across a range of application-classification mechanisms. Further, we document the accuracy of spatial classification without training-data possessing spatial diversity.Finally, we illustrate the classification of UDP traffic. We use the same classification approach for both stateful flows (TCP) and stateless flows based upon UDP. Importantly, we demonstrate high levels of accuracy: greater than 92% for the worst circumstance regardless of the application.

The experimental results of low pressure supersonic molecular beam injection (SMBI) fuelling on the HL-2A closed divertor indicate that during the period of pulsed SMBI the power density convected at the target plate surfaces was 0.4 times of that before or after the beam injection. An empirical scaling law used for the SMBI penetration depth for the HL-2A plasma was obtained. The cluster jet injection (CJI) is a new fuelling method which is based on and developed from the experiments of SMBI in the HL-1M tokamak. The hydrogen clusters are produced at liquid nitrogen temperature in a supersonic adiabatic expansion of moderate backing pressure gases into vacuum through a Laval nozzle and are measured by Rayleigh scattering. The measurement results have shown that the averaged cluster size of as large as hundreds of atoms was found at the backing pressures of more than 0.1 MPa. Multifold diagnostics gave coincidental evidence that when there was hydrogen CJI in the HL-2A plasma, a great deal of particles from the jet were deposited at a terminal area rather than uniformly ablated along the injecting path. SMB with clusters, which are like micro-pellets, will be of benefit for deeper fuelling, and its injection behaviour was somewhat similar to that of pellet injection. Both the particle penetration depth and the fuelling efficiency of the CJI were distinctly better than that of the normal SMBI under similar discharge operation. During hydrogen CJI or high-pressure SMBI, a combination of collision and radiative stopping forced the runaway electrons to cool down to thermal velocity due to such a massive fuelling.

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Summary Lithium‐ion battery packs have been generally used as the power source for electric vehicles. Heat generated during discharge and limited space in the battery pack may bring safety issues and negative effect on the battery pack. Battery thermal management system is indispensable since it can effectively moderate the temperature rise by using a simple system, thereby improving the safety of battery packs. However, the comprehensive investigation on the optimal design of battery thermal management system with liquid cooling is still rare. This article develops a comprehensive methodology to design an efficient mini‐channel cooling system, which comprises thermodynamics, fluid dynamics, and structural analysis. The developed methodology mainly contains four steps: the design of the mini‐channel cooling system and computational fluid dynamics analysis, the design of experiments and selection of surrogate models, formulation of optimization model, and multi‐objective optimization for selection of the optimum scheme for mini‐channel cooling battery thermal management system. The findings in the study display that the temperature difference decreases from 8.0878 to 7.6267 K by 5.70%, the standard temperature deviation decreases from 2.1346 to 2.1172 K by 0.82%, and the pressure drop decreases from 302.14 to 167.60 Pa by 44.53%. The developed methodology could be extended for industrial battery pack design process to enhance cooling effect thermal performance and decrease power consumption.