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The purpose of this paper is to analyze the ability of turbulence models to model the flow field in the runner of a Francis turbine. Although the complex flow in the turbine can be simulated by CFD models, the prediction accuracy still needs to be improved. The choice of the turbulence model is one key tool that affects the prediction accuracy of numerical simulations.

This study used the SST k-w and RNG k-e turbulence models, which can both accurately predict complex flow fields in numerical simulations, to simulate the flow in the entire flow passage of a Francis turbine with the results compared against experimental data for the performance and blade pressure distribution in the turbine to evaluate the applicability of the turbulence models.

The results show that the SST k-w turbulence model more accurately predicts the turbine performance than the RNG turbulence model. However, the blade surface pressures predicted by the SST k-w turbulence model were basically identical to those predicted by the RNG k-e turbulence model, with both accurately predicting the experimental data.

Due to the lack of space, the method used to measure the blade surface pressure distributions is not introduced in this paper.

Turbine performance and flow field pressure in the runner, which are the basis of turbine preliminary performance judgment and optimization through CFD, can be used to judge the rationality of the turbine runner design. The paper provides an evidence for the turbulence selection in numerical simulation to predict turbine performance and flow field pressure in the runner and improves the CFD prediction accuracy.

This paper fulfils a test of the flow field pressure in the runner, which provide an evidence for judge the adaptability of turbulence model on the flow field in runner. And this paper also provides important evaluations of two turbulence models for modeling the flow field pressure distribution in the runner of a Francis turbine to improve the accuracy of CFD models for predicting turbine performance.

This paper aims to develop a signal acquisition system of surface electromyography (sEMG) and use the characteristics of (sEMG) signal to interference action pattern.

This paper proposes a fusion method based on combining the coefficient of AR model and wavelet coefficient. It improves the recognition rate of the target action. To overcome the slow convergence speed and local optimum in standard BP network, the study presents a BP algorithm which combine with LM algorithm and PSO algorithm, and it improves the convergence speed and the recognition rate of the target action.

Experiments verify the effectiveness of the system from two aspects the target motion recognition rate and the corresponding reaction speed of the robotic system.

The study developed a signal acquisition system of sEMG and used the characteristics of (sEMG) signal to interference action pattern. The myoelectricity integral values are presented to determine the starting point and end point of target movement, which is more effective than using single sample point amplitude method.

This study aims to examine whether corporate stconcerns on social responsibility issues pressurize corporate managers to act in a socially responsible way and how this affects corporate value.

This study follows previous studies such as Wu et al. (2008) and Jiang and Huang (2011) in using the research model.

The analysis shows that in regions where large attention paid to demolitions, corporate managers are under great pressure from corporate stakeholders and they thus act in more socially responsible ways; this, in turn, results in higher corporate values. Furthermore, in regions in which demolition events attract more attention, the increase in corporate value is relatively small for state-owned enterprises and unprofitable listed enterprises.

The findings demonstrate that internet governance heightens corporate stakeholders’ awareness of social responsibility, and this leads to pressure on corporate relative behaviors to satisfy the requests of corporate stakeholders, leading to an increase in corporate value and improvement in social welfare.

This chapter explores the characteristics of emerging environmental movement organizations in China, and more specifically the role of guanxi – or personal networks – in Chinese environmental activism. While organizational networks of environmental NGOs are still weak in Chinese environmental activism, personal networks of environmental activists are instrumental in building the first sprouts of a green civil society. We explore this via an in-depth case study of relatively successful environmental activism to halt the construction of a number of hydro-electric projects on the Nu River. The case study illustrates that in China, more so than in western countries, informal personal networks, rather than formal organizational networks, play a crucial role in the organization and success of contemporary environmental campaigns. This is partly explained by the immature environmental movement, and partly by the specifics of Chinese social networks.