This paper studies the relay selection schemes in mobile communication system over Nakagami-m channel. To make efficient use of licensed spectrum, both single relay selection (SRS) scheme and multirelays selection (MRS) scheme over the Nakagami-m channel are proposed. Also, the intercept probability (IP) and outage probability (OP) of the proposed SRS and MRS for the communication links depending on realistic spectrum sensing are derived. Furthermore, this paper assesses the manifestation of conventional direct transmission scheme to compare with the proposed SRS and MRS ones based on the Nakagami-m channel, and the securityreliability trade-off (SRT) performance of the proposed schemes and the conventional schemes is well investigated. Additionally, the SRT of the proposed SRS and MRS schemes is demonstrated better than that of direct transmission scheme over the Nakagami-m channel, which can protect the communication transmissions against eavesdropping attacks. Additionally, simulation results show that our proposed relay selection schemes achieve better SRT performance than that of conventional direct transmission over the Nakagami-m channel.

Cavitating flow prediction is essential for designing cavitation-resistant hydraulic machines. Despite the advances achieved in normal-temperature cavitation prediction, cryogenic cavitation prediction has remained a challenging task in which thermal effects play a significant role. The present study aims to enhance the prediction of cryogenic cavitation, and both the cavitation and turbulence models are improved simultaneously. The original cavitation model embedded in the CFX flow solver is modified by incorporating additional source terms (such as mass and heat transfer rates) for dual evaporation and condensation processes. The RNG k-e turbulence model is modified on the basis of the filter-based turbulence model and density correction method to permit a smooth prediction of turbulence eddy viscosity, which mitigates the overestimation of the turbulence length scale in the cryogenic cavity (which is intrinsic to the original RNG k-e turbulence model). The modified cavitation and turbulence models are implemented through CFX Expression Language (CEL) within the CFX frame. To verify the modified models and the enhancement of cryogenic cavitation prediction, Hord's liquified nitrogen (LN2) and liquefied hydrogen (LH2) experiments over a hydrofoil and ogive are used, and cavitating flow simulation is conducted for each of the test cases. When using the modified models, the predicted temperature and pressure curves agree well with the measured values, and the predicted cavity lengths are much closer to the measured lengths. It is proven that the cryogenic cavitating flow can be well depicted by the modified models.

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Cryogenic liquid turbine expanders have emerged quite recently as a replacement of J-T valve for enhancing energy efficiency of industrial systems, such as Air Separation Units (ASUs), Supercritical Compressed Air Energy Storage (SC-CAES) systems, et al. In the liquid turbine expander, the rotating impeller-induced swirling flow and cavitation are essentially significant and intensive, which requests some in-depth work towards a thorough understanding flow physics and then effective attenuation. The present study aims at effectively mitigating the swirling flow and cavitation. The entropy production analysis method (EPAM) is proposed to characterize the swirling flow and cavitation. It is then incorporated with the improved cavitation and turbulence models and validated through the simulation of the Hord's liquid nitrogen hydrofoil. To mitigate the swirling flow and subsequent cavitation, the design optimization method is developed, in which a novel optimization objective function is constituted by incorporating the local entropy production rate and vapor volume fraction to capture the mechanical energy dissipation and cryogenic cavitating flow physics; the NURBS-FFD (Non-Uniform Relational B-Splines and Free Form Deformation) parametric method is used to facilitate a flexible variation in impeller blade and diffuser vane geometries. It is solved within CFX frame by means of the Particle Swarm Optimization algorithm coupling the Kriging-based adaptive surrogate model. With the design optimization, the impeller and vaned diffuser tube geometries are collaboratively fine-tuned, and the mechanical energy dissipation and cavitating flow across both the impeller and vaned diffuser tube is effectively mitigated.