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The purpose of this paper is to provide a mixture model with modified mass transfer expression for calculating cavitating (two‐phase) flow.

The mass transfer relations are derived based on the mechanics of evaporation and condensation, in which the mass and momentum transfer count for factors such as non‐dissolved gas, turbulence, surface tension, phase‐change rate, etc.

As shown by two calculation examples, the modified model can predict the cavitating flow with high accuracy, agreeing well with experimental results.

The methods described are of value in improving stability in numerical calculations.

The purpose of this paper is to predict pressure pulsation in Kaplan hydraulic turbines.

State of the art numerical simulation techniques are employed to simulate three‐dimensional flows in the whole flow passage of a Kaplan turbine so that pressure pulsations can be computed in both time domain and frequency domain. Numerical results are verified by experiments carried out on the most advanced experimental platform in China.

It is found that the proposed numerical model is a viable tool for prediction of pressure pulsations. The simulation shows that the model turbine and prototype turbine have the same pressure pulsation frequencies and rotating frequencies and the same transmission patterns under similar operation conditions. However, there is no similarity for the amplitude of the pressure pulsation between the model turbine and the prototype turbine. Therefore pressure pulsations in a prototype turbine cannot be obtained by scaling the experimental results of the model turbine using a similarity relationship.

The findings will be very valuable for the design of hydraulic turbines and large‐scale hydraulic power stations.

The proposed numerical method provides a viable tool for hydraulic turbine and power station designers to predict the pressure pulsations in prototype turbines. It is a useful tool to help improve the performance of hydraulic turbines. The findings made in the numerical simulation have been verified by experiments, which is also a valuable reference for hydraulic turbine designers.

This paper aims to propose a novel multiple transient modeling scheme for the 12-pulse phase-shifting reactor (PSR) rectifier to enhance the efficiency of full-cycle design evaluation.

The detailed time-domain method is adopted to model the rectifier at the behavioral layer. The diode bridges/transformer model at the architecture layer is established by using the switch function and Park transformation. The frequency domain model at the functional layer is derived with the time-varying Fourier decomposition and frequency-shifting. At the component layer, the magneto-thermal characteristics of the rectifier are analyzed with field-circuit and magnetic-thermal coupling methods. A computer-aided design program integrating multiple modeling is also developed for industrial product design.

The function layer modeling is preferred in the initial design stage, making up for the lack of modeling accuracy at the architectural layer and the lack of modeling rapidity at the behavioral layer. The component modeling is irreplaceable for the detailed evaluation in the latter design stage. The multiple modeling scheme based on the four-layer modeling helps the designers achieve high-quality products with a short development cycle.

The singular transient modeling cannot cover the needs of different stages in the full-cycle design evaluation. This paper fills this gap with a novel multiple modeling scheme. Meanwhile, the proposed multiple modeling scheme and developed computer-aided design program provide a great convenience for full cycle design evaluation of the 12-pulse PSR rectifier.

Technical progress is an important technique within improving China’s comparative advantages, as new and renewable technologies will be beneficial for energy security. Productive technical progress and green technical innovation are necessary to improve working conditions and productivity of industries. Therefore, the purpose of this paper is to study technical progress in China under such harsh competitive circumstances, as well as types of technical progress that can be promoted, productive technical progress or green technology progress, and how technical progress will affect China’s competitive advantages.

The authors perform a multi-index multi-factor constitutive model based on a sample of 468 Chinese industries, and divide the industries into four categories.

The results indicate that there is a “U”-shape relationship between green technology progress and comparative advantages and an inverted “U”-shape relationship between the intensity of market competition and comparative advantages.

China has crossed the inflection point of the “U”-shaped curve. This, coupled with the slowing of economic growth, demonstrates the need for advocating green technology in China to decrease the pollutant discharge. Establishing Chinese national brands within overseas markets and earning a profit through the downstream of production chain enhance China’s international competitiveness.

One of the most original findings of this paper points out that China is faced with a situation in which exports are severely decreased and domestic environment pollution is increased. Vigorous promotion of green technology progress, improvement of the quality and the technical content of exported products, the establishment of national brand within the overseas market, as well as enhancement of China’s international competitiveness, is needed.

Recently, China has been paying increasing attention to how to improve the efficiency of the marine environment and realize a green and sustainable development of the marine economy. Consequently, the industrial structure is crucial to improving efficiency. The purpose of this paper is to introduce environmental factors into the efficiency analysis framework and explore the relationship between marine industrial structure and marine environmental efficiency.

This paper uses marine economic data under the DEA-BBC model to measure the marine environmental efficiency of provinces and cities and classifies them by cluster analysis. Then, the marine industrial structure and marine environmental efficiency are studied by an econometric model with human capital, ownership structure, land economic development level, scientific research input and government intervention degree as control variables.

The overall level of marine environmental efficiency is relatively low in China, increasing and then decreasing over the research period. The rationalization of industrial structure and scientific research input have significant promoting effects on marine environmental efficiency, while the degree of government intervention has a significant inhibiting effect. The positive effect of human capital on efficiency depends on whether it can be successfully converted into productivity. The effects of industrial structure advancement, ownership structure and land economic development level of on the marine environmental efficiency are mixed.

The results provide a theoretical and decision-making basis for China to transform and upgrade its marine industrial structure and sustainably develop the marine economy.

As the functions of environmental regulations cannot be quantified while assessing their environmental efficiency, there has been no comprehensive evaluation of environmental efficiency. The purpose of this paper is to evaluate environmental regulations based on triangular and trapezoidal fuzzy numbers.

This paper uses L-R fuzzy numbers to transform the evaluation language into triangular fuzzy numbers, and adopts an α-level flexible slacks-based measurement model to evaluate the performance of these regulations. Trapezoidal fuzzy numbers are combined with a data envelopment analysis model, and an α-slack-based measurement (SBM) model is used to evaluate the environmental efficiency. The α-SBM model is confirmed to be stable and sustainable.

Relevant index data from 16,375 enterprises were collected to test the proposed model, and models corresponding to triangular fuzzy numbers and trapezoidal fuzzy numbers were used to evaluate their environmental efficiency. Comparative results showed that the proposed model is feasible and stable.

The main contributions of this study are twofold. First, this paper provides a valuable evaluation method for environmental regulation. Second, our research improves the practical performance of trapezoidal fuzzy data envelopment analysis and enhances its feasibility and stability.

The purpose of this paper is to study the saturation and nonlinear performance of magnetic field in the air gap of switched reluctance motor (SRM).

The analytical method of sub-domain combined with the saturation compensation method is used to determine the nonlinear distribution of air gap magnetic field in SRM. Also, the resolutions of the two-dimensional (2D) Laplace’s equation and Poisson’s equation in polar coordinates are used to obtain the simplified expression of magnetic flux density.

For verifying the effectiveness of analytical model, the results are compared with those obtained from the 2D finite element method (FEM). The influence of magnetic saturation is taken into account by associating the sub-domain analysis result with the nonlinear B-H properties of stator and rotor iron. The magnetic flux density in radial and tangential direction considering the saturation effect may be calculated accurately. It can be seen that one can easily determine the linear analytical results accurately, whereas it is difficult to determine the magnetic flux density with saturation influence; especially at some local positions, there is a larger difference between analytical and FE model due to the complex boundary conditions.

This paper presents the development and optimization design of high-performance SRM.

The magnetic saturation may be taken into account for the SRM and analytical models support to simulated system performance.

The establishment of free trade zones (FTZs) is an important experiment as part of the reform and opening up policy. This paper aims to focus on the issue of production efficiency of environmental protection enterprises in FTZs. Changes in the external and internal environments of enterprises can easily lead to changes in the production efficiencies of enterprises. The establishment of FTZs can change the external environment of enterprises. Knowledge accumulation changes the internal environment of enterprises. However, traditional efficiency analysis has usually ignored the internal and external heterogeneity of decision-making units, resulting in the distortion of the evaluation results.

This paper examines the relationship between knowledge accumulation and development potential based on financial data of environmental protection enterprises that were listed in Shanghai and Shenzhen A stocks, from 2009 to 2016. Then, through data envelopment analysis cross-efficiency analysis of the listed environmental protection enterprises from external heterogeneity, BP neural network model is set up.

The results show that the model set up in this paper is stable and reliable. The paper makes policy suggestions such as stimulating trade inside industry, quickening technological progress and enhancing environmental protection.

This paper analyzes the economy, environmental protection, science and technology and education to simulate the external environment of enterprises. Based on the experience data from the completion of Shanghai FTZ, this paper predicts the future development potential of Hainan FTZ enterprises.

The purpose of this paper is to assess the water quality parameters resulting on: First, the flow direction in biofilters (ascending or descending), second, constructed wetland (CW) with local plant species and third, the combined system for the removal of organic matter and nutrients pollutants from water in arid regions.

An integrated system is presented and tested in situ with a vertical up-flow and down-flow biofilters. Two configurations schemes are followed by a three separated horizontal subsurface CWs: two planted with Phragmites australis, Typha latifolia and the third unplanted. The methodology is based on a statistical analysis of the collected data.

The present experiment demonstrated that the wetlands planted with P. australis and T. latifolia showed the highest removal. Moreover, T. latifolia performed better than P. australis for most of the parameters, notably in the first system, whereas the wetland efficiency indicated that P. australis contributed greatly to the removal of TP in the first system and NO₃-N in the second system. In general, for the highest removal efficiencies of the combined biofilters and wetlands system, the present study demonstrated that the first system performed better than the second for all the parameters.

The originality of the research is that it compares in situ two biofilter systems: vertical up-flow and down-flow biofilters. To avoid the effects of domestic wastewater that is discharged directly without treatment in the Oued Righ channel or in the lake, this integrated system can be one of the alternatives for wastewater treatment, as it reveals the need to protect aquatic ecosystems in arid regions, and can decrease the risks to human health and the environment.

Without damaging and consuming natural resources, green computing technology can meet the needs of society for a long time. This paper discusses how to realize the sustainable development of social economy through the innovation of green computing technology.

For the green computing technology and sustainable social and economic development problems, it builds back propagation (BP) neural network model and analyzes the topological structure of the network model as well as the impact of the training errors allowed by the network on its performance.

By optimizing the number of input nodes, the number of hidden nodes and the target value, the genetic algorithm (GA) can get the optimal neural network model. The simulation experiment proves that the proposed model is effective.

It can not only reduce the possibility of falling into local optimum, but also optimize the initial weights and thresholds of BP neural network and further improve the stability and test effect of BP neural network model.