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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 purpose of this paper is to review the evolution of policies and practices of innovation in China for the past 40 years.

This is a review paper. It adopts a different multi-dimensional, qualitative methodology to examine China’s trajectory of innovation from the economic reform since 1978, highlighting “China” experiences in the developing innovation-driven economy, also pointing the challenges that China faces in this transition process and future prospects. The analysis of China’s innovation performance was based mostly on secondary data from sources and institutions that use statistical data to build country rankings, such as the global innovation index and global competitiveness index.

It is found that the institutional foundations of the national innovation system in China are already being laid, and so far, China has made extraordinary progress regarding innovation performance from country to region and from business to individual. However, some critical challenges in its innovation-driven development still need urgent attention and effective efforts to reinforce them.

This paper aims to fill the gap in the literature by providing an overview of the evolution of the policies and practices of innovation development in China since the 1978 economic reforms and explores the Chinese experiences in transforming into an innovation-driven economy.

Scientific advances and the emergence of a wide range of broadband services have resulted in the internet developing as a critical component of most peoples’ daily lives. The rapid development of the global economy and improvements to the information network speed and reliability have driven a radical evolution of the concept of “library.” Modern information technologies have not only drastically altered the functionality and accessibility of libraries, but it is no longer a matter of the library community to use scientific and technological innovation ideas and techniques to promote its business. The sample of this study was distributed to the consumers of the Guangdong Intelligent Library for the questionnaire.

A total of 520 questionnaires were distributed, returning 375 validresponses for an effective recovery rate of 72%.

Perceptual ease of use has a positive and direct impact on perceptual usefulness. Perceptual ease of use has a positive and direct impact on attitude. Perceptual usefulness has a positive and direct impact on attitude. Perceptual usefulness has a positive direct impact on behavioral intentions. Attitude has a positive and direct impact on behavioral intentions. Subjective norms have a positive and direct impact on behavioral intentions. Perceptual behavioral control has a positive and direct impact on behavioral intentions. Perceptual behavioral control has a positive and direct impact on behavior. Behavioral intentions have a positive and direct impact on behavior.

Based on the survey results and analysis, recommendations are made to help smart libraries integrate artificial intelligence methods to provide highly attractive service offerings in an extremely competitive environment.