Publikationen


Suche nach „[H.] [Song]“ hat 5 Publikationen gefunden
Suchergebnis als PDF
    NachhaltigElektrotechnik und MedientechnikIQMA

    Zeitschriftenartikel

    W. Ni, L. Liu, Y. Zhang, C. Niu, H. Fan, G. Song, D. Liu, Günther Benstetter, G. Lei

    Effect of intermittent He/D ion irradiations on W nano-fuzz growth over W targets

    Vacuum, vol. 173, no. March

    2020

    DOI: 10.1016/j.vacuum.2019.109146

    Abstract anzeigen

    The intermittent He/D ion irradiations of polycrystalline W have been performed at the ion energy of 50 eV by changing the time of the single irradiations and the irradiation temperature. All irradiated W specimens have been observed by scanning electron microscopy, and the effect of intermittent He/D ion irradiations on the W fuzz growth has been analyzed. The W fuzz growth over W targets does not show the clear dependence on the intermittent He/D ion irradiations, where the He/D ion fluence of the single irradiations typically varies from 5.0 × 1024 to 2.5 × 1025/m2. However, a slight change in the W surface temperature during the single He ion irradiations significantly affects the W fuzz growth rate. Analysis indicates that W fuzz growth is significantly affected by the total He ion fluence varying from 5.0 × 1024 to 5.0 × 1025/m2 and the irradiation temperature varying from 1100 to 1450 K. This current study will play a crucial role in understanding the W fuzz growth under the periodic He/D ion irradiations of W divertor in fusion reactors, such as ELMs.

    NachhaltigElektrotechnik und MedientechnikIQMA

    Zeitschriftenartikel

    W. Ni, L. Liu, Y. Zhang, H. Fan, G. Song, D. Liu, Günther Benstetter, G. Lei

    Mass loss of pure W, W-Re alloys, and oxide dispersed W under ITER-relevant He ion irradiations

    Journal of Nuclear Materials, vol. 527

    2019

    DOI: 10.1016/j.jnucmat.2019.151800

    Abstract anzeigen

    In this study, polycrystalline W, W-Re alloys, and La2O3 and Y2O3 dispersion-strengthened W have been irradiated by our large-power materials irradiation experimental system (LP-MIES) at the irradiation temperature of 1360–1460 K. Our measurements show that the W nano-fuzz layer which is < 5.2 μm thick has been formed over all the specimens exposed to the low-energy (50 or 100 eV) and high-flux (1.37 × 1022–1.62 × 1022 ions/m2⋅s) He+ irradiations. The mass loss of the fuzz layer almost linearly increases with the He+ fluence, which does not show any dependence on the thickness of fuzz layer varying from 1.1 to 5.2 μm La2O3 and Y2O3 dispersions into W significantly suppress the growth of W fuzz, indicating that He diffusion and the evolution of He nano-bubbles in the near-surface can be significantly influenced due to the dispersion. After He+ (100 eV) irradiation at He+ fluence of 5.83 × 1026/m2, the mass loss of 0.1 vol% - 1.0 vol% La2O3-dispersed W is about 20% lower than the one of the pure W, and the La2O3 dispersed W exhibits the best erosion resistance among various W material grades. Our analysis indicates that both the surface sputtering of W fuzz by energetic ions and surface bursting of He nano-bubbles can be responsible for the mass loss of W under ITER-relevant He+ irradiations.

    MobilEuropan Campus Rottal-Inn

    Zeitschriftenartikel

    Katerina Volchek, A. Liu, H. Song, D. Buhalis

    Forecasting tourist arrivals at attractions: Search engine empowered methodologies

    Tourism Economics, vol. 25, no. 3, pp. 425-447

    2019

    DOI: 10.1177/1354816618811558

    Abstract anzeigen

    Tourist decision to visit attractions is a complex process influenced by multiple factors of individual context. This study investigates how the accuracy of tourism demand forecasting can be improved at the micro level. The number of visits to five London museums is forecast and the predictive powers of Naïve I, seasonal Naïve, seasonal autoregressive moving average, seasonal autoregressive moving average with explanatory variables, SARMAX-mixed frequency data sampling and artificial neural network models are compared. The empirical findings extend understanding of different types of data and forecasting algorithms to the level of specific attractions. Introducing the Google Trends index on pure time-series models enhances the forecasts of the volume of arrivals to attractions. However, none of the applied models outperforms the others in all situations. Different models’ forecasting accuracy varies for short- and long-term demand predictions. The application of higher frequency search query data allows for the generation of weekly predictions, which are essential for attraction- and destination-level planning.

    MobilEuropan Campus Rottal-Inn

    Zeitschriftenartikel

    Katerina Volchek, Law, R., Buhalis, D., H. Song

    The Good, the bad, and the ugly: Tourist perceptions on interactions with personalised content

    e-Review of Tourism Research, vol. 16, no. 2-3, pp. 62-67

    2019

    Abstract anzeigen

    Personalisation is a critical factor in superior customer experience and retention. It is also observed to be acause ofuserfrustration. This paper challenges the assumption that accurate content personalisation always positively affects tourist perceptions on the usefulness and ease of use of the information systems. The study integrates the logic of technology acceptance and the process of human motivation to explain personalised recommender system acceptance. In-depthsemi-structuredinterviews with tourists, industry practitioners, and academic experts were used in research. The findings illustrate that the characteristics of personalised content have double and, sometimes, ambivalent influence on tourist perceptions on system performance. A comprehensive strategy is required to optimise the potential of personalisation. This study expands the understanding of tourist interactions with personalised content and calls for further exploration of the effects of information system components on user experience.

    MobilEuropan Campus Rottal-Inn

    Beitrag (Sammelband oder Tagungsband)

    Katerina Volchek, H. Song, R. Law, D. Buhalis

    Forecasting London Museum Visitors Using Google Trends Data

    Proceedings of the ENTER2018 eTourism Conference

    2018

    Abstract anzeigen

    Information search is an indicator of tourist interest in a specificservice and potential purchase decision. User online search patterns are a well-known toolfor forecasting pre-trip consumerbehaviour, such as hotel demand and international tourist arrivals. However, the potential of search engine data for estimating thedemand for tourist attractions, which is created both before and during a trip, remains underexplored. This research note investigates the relationships between Google search queries for the most popular London museums and actual visits to theseattractions. Preliminary findings indicatehigh correlation between monthly series data. Search query data isexpected togenerate reliable forecasts ofvisits toLondon museums.