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Tip leakage vortex flow (TLV) is a common flow phenomenon in the axial-flow hydraulic machinery. High-efficiency simulation of TLV is still not an easy task because of the complex turbulent vortex-cavitation interactions. As an important basis of CFD, turbulence model directly affects the efficient computation of TLV. The purpose of this paper is to evaluate the newly developed MST turbulence model in predicting the TLV flows.

By using the MST turbulence model and the ZGB cavitation model, numerical simulations of the TLV generated by a NACA0009 hydrofoil were performed under the cavitation-free and cavitation conditions, and the results were compared with the available experimental data.

The important features of TLV are well captured by the MST-based simulation scheme, and the problem of under-predicting the cavitating TLV tube is well solved. Turbulent viscosity is reasonably adjusted in the TLV core regions, and the LES-like mode is activated, which is beneficial to obtain more turbulent information on the same URANS grids. The requirements of grid size and time step of the MST model are much lower than that of the LES method, thereby weighing a good balance between the simulation accuracy and computation cost.

The MST turbulence model is suitable for the high-efficiency simulation of the TLV flows, which can lay a good foundation for efficient engineering computations of the cavitating TLV in the axial-flow hydraulic machinery.

This study aims to explore the antecedents of perceived value and the moderating effect of trust and the relationship between these antecedents and perceived value in the context of the service sector.

The multivariate statistical analysis technique of structural equation modeling was used to test the proposed theoretical model.

The results indicate that self-efficacy, motivation, social influence, facilitating conditions and emotions have a significant and direct relationship with customers’ perceived value and that trust can enhance the effect of these antecedents on perceived value. These findings have several significant implications for service robot implementation within the service sector.

With the advancement in artificial intelligence and sensor technology, various industries have launched the practice of deploying intelligent robots to build competitive advantages. The use of intelligent robots to assist with the customer service process and improve consumers’ experience within the service sector is becoming more commonplace.

本论文旨在研究服务业中决定感知价值以及哪些中介变量调节感知价值决定因子和感知价值之间的关系。

本论文采用多变量SEM法分析提出的理论模型。

研究结果表明, 自我效能、动机、社会影响、辅助条件、以及情感对消费者感知价值有直接且显著的影响, 此外, 信任对于其影响因子对感知价值的关系有增强作用。本论文研究结果对服务型机器人在服务业中的应用有着很大的启示。

随着人工智能和感应科技的发展, 很多产业都开始应用智能机器人来增强竞争力。使用智能机器人来辅助消费者服务过程以及提高服务体验感受越来越成为普遍。