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The purpose of this study is to enhance the thermal performance in the labyrinth channel by different ribs shape. The labyrinth channel is a relatively new cooling structure to decrease the temperature near the trailing region of gas turbine.

Based on the geometric similarity, a simplified geometric model is used. The k − ω turbulence model is used to close the Navier–Stokes equations. Five rib shapes (one rectangular rib, two arched ribs and two trapezoid ribs) and five Reynolds numbers (10,000 to 50,000) are considered. The Nusselt number, flow structure and friction factor are analyzed.

Nusselt number is tightly related to the rib shape in the labyrinth channel. The different shapes of the ribs result in different horseshoe vortex and wake region. In general, the arched rib brings the highest Nusselt number and friction factor. The Nusselt number is increased by 15.8 per cent compared to that of trapezoidal ribs. High Nusselt number is accompanied by the high friction factor in a labyrinth channels. The friction factor is increased by 64.6 per cent compared to rectangular ribs. However, the rib shape has a minor effect on the overall thermal performance.

This study is useful to protect the trailing region of advanced gas turbine.

This paper presents the flow structure and heat transfer characteristics in a labyrinth channel with different rib shapes.

This study aims to develop a novel theoretical model for predicting the users’ intention to use virtual tools designed for construction risk evaluation. Risk evaluation is a vital objective for construction managers. This paper intends to examine critical factors such as potential benefits, motivation, performance expectancy and rich sources of information that may affect users’ intention to use virtual technology.

A pile training module (PTM) was developed in a virtual environment to analyze the proposed virtual reality-technology acceptance model (VR-TAM) factors. Further, a questionnaire survey was conducted with the participation of 102 construction professionals in China to validate the proposed VR-TAM model and PTM tool. The retrieved data was computed to test the proposed model by using partial least squares structural equation modeling and the significance of the PTM tool in a virtual environment.

The results of this study reveal that high-significance paths represent five relationships between crucial factors affecting users’ intention to use a selected virtual reality (VR) module. Five of seven hypothesis paths were significant with acceptable t-values. By quantitative measurement of high-significance paths, this research has found that each factor under VR-TAM has received significant loadings, with many above the 0.7 threshold mark and others around 0.6. The top factors include “motivation” and “benefits” and have multiplier effects on “intention to use” as the source factors.

The finding of this study presents crucial factors for VR adoption, and the proposed VR-TAM model contributes to the body of knowledge toward managing construction risk using pre-optimization and understanding in a virtual environment. This study supports Chinese construction company managers in effectively using VR technology in their construction projects for risk assessment and management.

This study offered the development of a novel VR-TAM integrated with risk assessment techniques for piling processes. Further, the developed model was analyzed by using a survey of Chinese construction professionals to collect perceptions about the modified theoretical model of VR-TAM.

This paper aims to investigate the influences of dimple location on the heat transfer performance of a pin fin-dimpled channel with upright/curved/inclined pin fins under stationary and rotating conditions.

Numerical methods based on a realizable k-ε turbulent model are used to conduct this study. Three kinds of pin fins (upright, curved, inclined) and three dimple locations (front, middle, behind) are studied for Ro varying from 0 to 0.5.

On the whole, pin fin plays a dominated role in heat transfer performance compared to dimple. The heading path and interaction of the longitudinal secondary flow and jet-like flow critically affect heat transfer performance. The formation, development and impingement of jet-like flow and longitudinal secondary flow are significantly affected by dimple locations. Dimple at behind position shows the poorest heat transfer enhancement.

This study is an extend of another previous study in which an innovative curved pin fin is proposed. The originality of this paper is to evaluate the heat transfer performance for the combined cooling structure of dimple and pin fin, which will provide original and useful application and experience for turbine blade design.

The widespread application of smart technologies in services not only brings efficiency and convenience to consumers but also inevitably comes with negative effects. Therefore, this article aims to illustrate the impact of privacy invasion on consumers' intention to use smart services. Using distrust as a mediating variable, compare two different modes of interaction between voice and text, and study the positive impact of privacy commitment. This study aims to provide recommendations for smart service providers to make the consumer experience better.

This paper adopts an experimental approach, with data collection and hypothesis analysis by designing four different experiments.

The results show that the negative impact of privacy invasion on consumers' intention to use smart services is moderated by privacy commitments and interaction modes. This article verifies the mediating effect of distrust on consumers' intention to use when privacy invasion occurs and verifies the moderating effect of the interaction modes by comparing voice interaction with text interaction and demonstrates that text interaction mode will attenuate the mediating role of distrust in the path in privacy invasion. Besides, it also indicates that privacy commitments can moderate the relationship between privacy invasion’s effect on distrust and intention to use.

Focusing on privacy invasion, this study explores consumers' intention to use smart services, compares the two interaction modes of voice and text to explore their moderating effects, deeply explores consumer psychology and studies the mediating role of distrust and the moderating role of privacy commitment.

The purpose of this paper is to investigate the optimal geometry parameters in a dimple/protrusion-pin finned channel with high thermal performance.

The BSL turbulence model is used to calculate the flow structure and heat transfer in a dimple/protrusion-pin finned channel. The optimization algorithm is set as Non-dominated Sorting Genetic Algorithm II (NSGA-II). The high Nusselt number and low friction factor are chosen as the optimization objectives. The pin fin diameter, dimple/protrusion diameter, dimple/protrusion location and dimple/protrusion depth are applied as the optimization variables. An in-house code is used to generate the geometry model and mesh. The commercial software Isight is used to perform the optimization process.

The results show that the Nusselt number and friction factor are sensitive to the geometry parameters. In a pin finned channel with a dimple, the Nusselt number is high at the rear part of the dimple, while it is low at the upstream of the dimple. A high dissipative function is found near the pin fin. In the protrusion channel, the Nusselt number is high at the leading edge of the protrusion. In addition, the protrusion induces a high pressure drop compared to the dimpled channel.

The originality of this paper is to optimize the geometry parameters in a pin finned channel with dimple/protrusion. This is good application for the heat transfer enhancement at the trailing side for the gas turbine.

Patent trade recommendations necessitate recommendation interpretability in addition to recommendation accuracy because of patent transaction risks and the technological complexity of patents. This study designs an interpretable knowledge-aware patent recommendation model (IKPRM) for patent trading. IKPRM first creates a patent knowledge graph (PKG) for patent trade recommendations and then leverages paths in the PKG to achieve recommendation interpretability.

First, we construct a PKG to integrate online company behaviors and patent information using natural language processing techniques. Second, a bidirectional long short-term memory network (BiLSTM) is utilized with an attention mechanism to establish the connecting paths of a company — patent pair in PKG. Finally, the prediction score of a company — patent pair is calculated by assigning different weights to their connecting paths. The semantic relationships in connecting paths help explain why a candidate patent is recommended.

Experiments on a real dataset from a patent trading platform verify that IKPRM significantly outperforms baseline methods in terms of hit ratio and normalized discounted cumulative gain (nDCG). The analysis of an online user study verified the interpretability of our recommendations.

A meta-path-based recommendation can achieve certain explainability but suffers from low flexibility when reasoning on heterogeneous information. To bridge this gap, we propose the IKPRM to explain the full paths in the knowledge graph. IKPRM demonstrates good performance and transparency and is a solid foundation for integrating interpretable artificial intelligence into complex tasks such as intelligent recommendations.

The purpose of this study is to unpack the antecedents and consequences of clickbait prevalence in online media at two different levels, namely, (1) Headline-level: what characteristics of clickbait headlines attract user clicks and (2) Publisher-level: what happens to publishers who create clickbait on a prolonged basis.

To test the proposed conjectures, the authors collected longitudinal data in collaboration with a leading company that operates more than 500 WeChat official accounts in China. This study proposed a text mining framework to extract and quantify clickbait rhetorical features (i.e. hyperbole, insinuation, puzzle, and visual rhetoric). Econometric analysis was employed for empirical validation.

The findings revealed that (1) hyperbole, insinuation, and visual rhetoric entice users to click the baited headlines, (2) there is an inverted U-shaped relationship between the number of clickbait headlines posted by a publisher and its visit traffic, and (3) this non-linear relationship is moderated by the publisher's age.

This research contributes to current literature on clickbait detection and clickbait consequences. Future studies can design more sophisticated methods for extracting rhetorical characteristics and implement in different languages.

The findings could aid online media publishers to design attractive headlines and develop clickbait strategies to avoid user churn, and help managers enact appropriate regulations and policies to control clickbait prevalence.

The authors propose a novel text mining framework to quantify rhetoric embedded in clickbait. This study empirically investigates antecedents and consequences of clickbait prevalence through an exploratory study of WeChat in China.

To fabricate a selective laser melting (SLM)-processed AlSi10Mg part with almost full density and free of any apparent pores, this study aims to investigate the effect of ambient argon pressure and laser scanning speed on the particles splash during the AlSi10Mg powder bed laser melting.

Based on the discrete element method (DEM), a 3D model of random distribution of powder particles was established, and the 3D free surface of SLM forming process was dynamically tracked by the volume of fluid, where a Gaussian laser beam acts as the energy source melting the powder bed. Through the numerical simulation and process experimental research, the effect of the applied laser power and scanning speed on the operating laser melting temperature was studied.

The process stability has a fundamental role in the porosity formation, which is process-dependent. The effect of the processing conditions on the process stability and the resultant forming defects were clarified.

The results shows that the pores were the main defects present in the SLM-processed AlSi10Mg sample, which decreases the densification level of the sample.

The optimal processing parameters (argon pressure of 1,000 Pa, laser power of 180 W, scan speed of 1,000 mm/s, powder layer thickness of 35 µm and hatch spacing of 50 µm ) applied during laser melting can improve the quality of selective laser melting of AlSi10Mg,

It can provide a technological support for 3D printing.

Based on the analysis of the pore and balling formation mechanisms, the optimal processing parameters have been obtained, which were argon pressure of 1,000 Pa, laser power of 180 W, scan speed of 1,000 mm/s, powder layer thickness of 35 µm and hatch spacing of 50 µm. Then, a near-fully dense sample free of any apparent pores on the cross-sectional microstructure was produced by SLM, wherein the relative density of the as-built samples is larger than 97.5%.