Search results

The purpose of this paper is to identify corrosion types and corrosion transitions by a novel electrochemical noise analysis method based on Adaboost.

The corrosion behavior of Q235 steel was investigated in typical passivation, uniform corrosion and pitting solution by electrochemical noise. Nine feature parameters were extracted from the electrochemical noise data based on statistical analysis and shot noise theory. The feature parameters were analysis by Adaboost to train model and identify corrosion types. The trained Adaboost model was used to identify corrosion type transitions.

Adaboost algorithm can accurately identify the corrosion type, and the accuracy rate is 99.25%. The identification results of Adaboost for the corrosion type are consistent with corroded morphology analysis. Compared with other machine learning, Adaboost can identify corrosion types more accurately. For corrosion type transition, Adaboost can effectively identify the transition from passivation to uniform corrosion and from passivation to pitting corrosion consistent with corroded morphology analysis.

Adaboost is a suitable method for prediction of corrosion type and transitions. Adaboost can establish the classification model of metal corrosion, which can more conveniently and accurately explore the corrosion types. Adaboost provides important reference for corrosion prediction and protection.

For an axial-flow compressor rotor, the upstream inflow conditions will vary as the aircraft faces harsh flight conditions (such as taking off, landing or maneuvering) or the whole compressor operates at off-design conditions. With the increase of upstream boundary layer thickness, the rotor blade tip will be loaded and the increased blade load will deteriorate the shock/boundary layer interaction and tip leakage flows, resulting in high aerodynamic losses in the tip region. The purpose of this paper is to achieve a better flow control for tip secondary flows and provide a probable design strategy for high-load compressors to tolerate complex upstream inflow conditions.

This paper presents an analysis and application of shroud wall optimization to a typical transonic axial-flow compressor rotor by considering the inlet boundary layer (IBL). The design variables are selected to shape the shroud wall profile at the tip region with the purpose of controlling the tip leakage loss and the shock/boundary layer interaction loss. The objectives are to improve the compressor efficiency at the inlet-boundary-layer condition while keeping its aerodynamic performance at the uniform condition.

After the optimization of shroud wall contour, aerodynamic benefits are achieved mainly on two aspects. On the one hand, the shroud wall optimization has reduced the intensity of the tip leakage flow and the interaction between the leakage and main flows, thereby decreasing the leakage loss. On the other hand, the optimized shroud design changes the shock structure and redistributes the shock intensity in the spanwise direction, especially weakening the shock near the tip. In this situation, the shock/boundary layer interaction and the associated flow separations and wakes are also eliminated. On the whole, at the inlet-boundary-layer condition, the compressor with optimized shroud design has achieved a 0.8 per cent improvement of peak efficiency over that with baseline shroud design without sacrificing the total pressure ratio. Moreover, the re-designed compressor also maintains the aerodynamic performance at the uniform condition. The results indicate that the shroud wall profile has significant influences on the rotor tip losses and could be properly designed to enhance the compressor aerodynamic performance against the negative impacts of the IBL.

The originality of this paper lies in developing a shroud wall contour optimization design strategy to control the tip leakage loss and the shock/boundary layer interaction loss in a transonic compressor rotor. The obtained results could be beneficial for transonic compressors to tolerate the complex upstream inflow conditions.

In a boundary layer ingestion (BLI) propulsion system, the fan operates continuously under distorted inflow conditions, leading to an increment of aerodynamic loss and in turn impacting the potential fuel burn reduction of the aircraft. Usually, in the preliminary design stage of a BLI propulsion system, it is essential to assess the impact of fuselage boundary layer fluids on fan aerodynamic performances under various flight conditions. However, the hub region flow loss is one of the major loss sources in a fan and would greatly influence the fan performances. Moreover, the inflow distortion also results in a complex and highly nonlinear mapping relation between loss and local physical parameters. It will diminish the prediction accuracy of the commonly used low-fidelity computational approaches which often incorporate traditional physics-based loss models, reducing the reliability of these approaches in evaluating fan performances. Meanwhile, the high-fidelity full-annulus unsteady Reynolds-averaged Navier–Stokes (URANS) approach, even though it can give rather accurate loss predictions, is extremely time-consuming. This study aims to develop a fast and accurate hub loss prediction method for a BLI fan under distorted inflow conditions.

This paper develops a data-driven hub loss prediction method for a BLI fan under distorted inflows. To improve the prediction accuracy and applicability, physical understandings of hub flow features are integrated into the modeling process. Then, the key physical parameters related to flow loss are screened by conducting a sensitivity analysis of influencing parameters. Next, a quasi-steady assumption of flow is made to generate a training sample database, reducing the computational time by acquiring one single sample from the highly time-consuming full-annulus URANS approach to a cost-efficient single-blade-passage approach. Finally, a radial basis function neural network is used to establish a surrogate model that correlates the input parameters and the output loss.

The data-driven hub loss model shows higher prediction accuracy than the traditional physics-based loss models. It can accurately capture the circumferentially and radially nonuniform variation trends of the losses and the associated absolute magnitudes in a BLI fan under different blade load, inlet distortion intensity and rotating speed conditions. Compared with the high-fidelity full-annulus URANS results, the averaged relative prediction errors of the data-driven hub loss model are kept less than 10%.

The originality of this paper lies in developing a new method for predicting flow loss in a BLI fan rotor blade hub region. This method offers higher prediction accuracy than the traditional loss models and lower computational time cost than the full-annulus URANS approach, which could realize fast evaluations of fan aerodynamic performances and provide technical support for designing high-performance BLI fans.

The accelerating process of economic globalization and the increasingly fierce international competition are conducive to the promotion of the construction of the urban regional innovation system. Based on this, the Bayesian discriminant model was established in this paper, and the development stage of the regional innovation system was prejudged. Then according to the discriminant analysis, the results of the pre judgment were tested. In addition, based on the innovation system of urban planning and construction, a framework of urban planning analysis based on regional innovation system was put forward, which was used to guide regional planning and implementation, and was applied to the planning of Shanxi science and technology innovation city. It is proved that the fuzzy evaluation system based on Bayes is beneficial to the innovative planning of the new city.

This paper aims to analyze the rates of returns on education in China and in the process raises issues relevant to the management of China’s system of education. In the ongoing great transformation period of China, the rising rates of returns on education may have been indicators reflecting China’s social progressiveness. However, very little research efforts have been devoted to the study of the impacts of such factors as geographical regions and genders, etc. The authors hope to fill these gaps in the literature.

The China Health and Nutrition Survey (CHNS) database is used for this study (University of North Carolina). The longitudinal nature of the data sets covering 1989, 1991, 1993, 1997, 2000, 2004, 2006, 2009 and 2011 provides a good basis for comparative analyses. The theory is grounded upon the Mincer equations through which econometric estimates are then made.

Disparities in returns on education are found between genders and across geographical regions. The regression results show that the women’s returns on education are consistently higher than those of men. However, the scales of such gender differences differ between the rural and urban areas: smaller for rural area and larger, more significantly so for urban. Additionally, we have found that the rates of returns on education in China have risen significantly over these years, and these increases have been largely due to the effects of institutional reforms. The urban-rural gap in their degrees of market orientation has contributed to the differences in their rates of returns on education. The analyses also suggest that foreign direct investment inflows, international trade and the increasing competitiveness from private enterprises render human capital more valuable to urban businesses. In case of the rural areas, a lack of incentive system tends to have contributed to the lower rates of returns on education.

The authors have presented evidence on the trends in the rates of returns on education during China’s critical transition period. Analyses of the possible reasons behind the differential rates of returns are provided. These findings are helpful for the government to shape their policies towards education. For instance, the government should give more emphasis to vocational schooling due to their significantly higher rates of returns.

The use of modern technologies in restaurants has become a trend. For food and beverage services, embracing new technologies helps solve the dilemmas of increasing labor costs and the high level of staff turnover in the industry. However, knowledge regarding how consumers perceive and evaluate technology-assisted dining experiences (TADEs) is limited. This study aims to conceptualize and operationalize TADEs while considering increasing technological applications in restaurants.

This study conducted in-depth interviews with 71 restaurant consumers in Nanjing and Wuhan, China. Following the interviews, this study carried out a survey and identified the factor structure of TADEs.

The in-depth interviews identified 26 attributes of TADEs. An analysis of the survey data identified four important aspects (with 21 items) of TADEs, namely, novelty and fashion, convenience, high efficiency and restrictions and possible risks.

Hospitality managers can implement the suggested measures for dining service design and technology management to improve the experiences of customers.

These findings have theoretical implications for the new phenomenon of technology-integrated dining, the application of technology and consumer management in the catering industry.

Bumpless Cu/SiO₂ hybrid bonding, which this paper aims to, is a key technology of three-dimensional (3D) high-density integration to promote the integrated circuits industry’s continuous development, which achieves the stacks of chips vertically connected via through-silicon via. Surface-activated bonding (SAB) and thermal-compression bonding (TCB) are used, but both have some shortcomings. The SAB method is overdemanding in the bonding environment, and the TCB method requires a high temperature to remove copper oxide from surfaces, which increases the thermal budget and grossly damages the fine-pitch device.

In this review, methods to prevent and remove copper oxidation in the whole bonding process for a lower bonding temperature, such as wet treatment, plasma surface activation, nanotwinned copper and the metal passivation layer, are investigated.

The cooperative bonding method combining wet treatment and plasma activation shows outstanding technological superiority without the high cost and additional necessity of copper passivation in manufacture. Cu/SiO₂ hybrid bonding has great potential to effectively enhance the integration density in future 3D packaging for artificial intelligence, the internet of things and other high-density chips.

To achieve heterogeneous bonding at a lower temperature, the SAB method, chemical treatment and the plasma-assisted bonding method (based on TCB) are used, and surface-enhanced measurements such as nanotwinned copper and the metal passivation layer are also applied to prevent surface copper oxide.

This study aims to explore the spatial distribution characteristics and spactial reciprocity between industrial parks (IPs) and vocational education parks (VEPs): agglomeration density, functional matching, spatial organization efficiency, as well as space intensive utility. To achieve this objective, IPs and VEPs in urban centers of Jiangsu Province are selected as the objects of the study. First, spatial analysis of thermodynamic diagrams is employed in this study to qualitatively analyze the evolutionary characteristics of the spatial distribution of IPs and VEPs to explore the spatial aggregation characteristics of their clustering, integration, and comprehensive crossover. Second, a horizontal comparison of the data and indexes concerned reveals that areas with high agglomeration and functional matching exhibit a sound spatial reciprocity. Third, this study crystallizes the four structural prototpye paradigms formed during the reciprocity evolution between IPs and VEPs; it compares spatial organization efficiency, with the agglomeration–core structure ranking first, followed by the circle–core structure. Finally, SPSS is used to analyze the space intensive utility in order to verify the conclusions of qualitative analysis. The findings can comprehensively explain the regularities of the spatial distribution and reciprocity between IPs and VEPs. The findngs can also elucidate the design of regional industrial development and educational programs.

Most firms in the fashion industry frequently design and promote new products, which leads to a two-period phenomenon in product sales. This study aims to examine the optimal advertising efforts of each channel member and the subsidy strategies of the manufacturer with retail competition in a two-period supply chain.

By utilizing the game theory, this study developed a cooperative advertising model that considers the element of retailer competition in a two-period supply chain.

The main results of this study are as follows. An increase in the subsidy rate of one retailer’s advertising cost will lead to a decrease in the share of the other. When a manufacturer’s marginal profit from one retailer is considerably larger than that from the other, the manufacturer will share more advertising cost with the former. This study demonstrates that a bilateral participation contract can achieve supply chain coordination and increases the likelihood of retailers to participate in this contract when competition effect is small.

First, product price is not a decision variable in this model. This concern can be studied in future work. Second, the one-manufacturer and two-retailer supply chain can be expanded to competitive manufacturers.

This study provides some decision references for the manufacturer and retailer on advertising strategies. The manufacturer can also gain insights into cooperative advertising strategy when facing a competitive retail environment.

Most previous studies related to cooperative advertising focused on a single-period supply chain. This study investigates cooperative advertising strategy with retail competition in two-period sales and explores the potential coordinating power of a bilateral participation contract.

Exploring the determinants of a winery brand reputation (BR) and how those determinants interact is vital for the sustainable development of wineries as well as the growth of the wine industry as a whole. This study aims to test an integrated model to better understand the observed measurement constructs of winery brand reputation, including collective reputation (CR), wine label (WL), expert opinion (EO), social media advertising (SMA) and consumer wine knowledge (CWK).

In-depth interviews, an expert panel review and a pilot study were conducted to examine and improve the observed variables. A questionnaire survey was conducted as the main data source for the study. A total of 616 valid questionnaire responses were collected from 102 cities in mainland China and Hong Kong, Macao and Taiwan from December 2021 to April 2022. Structural equation modeling was conducted for the data analysis.

This study supported 9 of the 18 proposed theoretical hypotheses. WL, EO and SMA had positive effects on BR. CWK was found to have a moderating effect on the relationship between expert opinions/social media advertising and brand reputation.

The results of this study can guide wine practitioners, researchers and administrators in brand development, label regulation and consumer education.

To the best of the authors’ knowledge, this is the first attempt to examine the determinants of winery brand reputation among Chinese wine consumers. This study explains the mechanism of winery brand reputation, demonstrating the dynamics and effects of the observed measurement constructs on brand reputation.