bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling and Evaluation of the Thermo-mechanical Behavior of Filter Materials and Filter Structures
Authors: Abendroth Martin , Roth Stephan , Malik Alexander , Seupel Andreas , Kuna Meinhard , Kiefer Bjoern 
Published: May 2024

AbstractTo capture and predict the chemo-thermo-mechanical behavior of ceramic foam filters, material models and simulation tools are required. The description of the thermo-mechanical inelastic behavior as well as the in-situ layer formation on reactive filters have been the aims of this subproject. Challenging aspects in the whole progress are the exact geometrical replication of the underlying foam structure of the filter and the lack of experimental data for many relevant loading cases. The software FoamGUI is developed to generate parametrized, periodic three-dimensional representative volume elements (RVE) of foam structures, which are used in continuum and fluid mechanical simulations as well as for 3D-printing. Calculation concepts are formulated to predict the inelastic deformation and failure behavior of ceramic open-cell foams under thermo-mechanical loading. First-order homogenization approaches are used to conclude from the mesoscopic behavior of the foam RVE to the macroscopic response of filter structures. A hybrid approach is developed in the established framework of rate-independent plasticity in combination with neural networks, which replace the plastic flow potential and the evolution equations of internal state variables. Another modeling aspect is motivated by the experimentally observed growth of an in situ layer during the so-called reactive phase of the filtration process. This phenomenon motivates the development of a model to describe diffusion, chemical reactions and phase transition processes of multi-phase/multi-component systems using the phase-field method. This allows the simulation of spatially and temporally resolved microstructure evolution leading to the layer formation.
Reactive Cleaning and Active Filtration in Continuous Steel Casting
Authors: Spitzenberger Andy , Bauer Katrin , Schwarze Rüdiger 
Published: May 2024

AbstractBasic fluid dynamic processes of melt filtration have been investigated in order to increase the performance and efficiency of filtration systems in steelmaking, especially for continuous steel casting. Numerical simulations have been performed to investigate the interactions between filter structures and the mean melt flow, the development of endogenous non-metallic inclusion (NMI) populations in the flow, and inclusion removal from the melt. For this purpose, Euler–Lagrange models of the particle-laden flow have been developed. As a major finding, the reactive cleaning process of the melt has been proven to be a very efficient cleaning method. Here, inclusion removal is strongly improved by the lifting action of reactively generated gas bubbles at the NMI surfaces. Details of the reactive cleaning process and the combination of reactive cleaning and active filtration have been investigated, too. The prediction quality of the numerical models with regard to fluid flow and the efficiency of the employed filtration systems have been successfully examined by comparing numerical simulations with the results from experimental investigations in different water model experiments and the steel casting simulator.
Interactions Between Molten Iron and Carbon Bonded Filter Materials
Authors: Wei Xingwen , Storti Enrico , Dudczig Steffen , Fabrichnaya Olga , Aneziris Christos G. , Volkova Olena 
Published: May 2024

AbstractThis chapter presents the interaction between carbon free active and carbon bonded reactive ceramic filter materials and molten iron by utilizing the sessile drop method. The most of carbon free ceramic filter materials showed non-reactive system during the interaction. After the interaction, the number, type, and the size of the non-metallic inclusions were registered with the aid of ASPEX analysis. On the other hand, the carbon bonded materials showed a series of phenomenon during the interaction including the formation of oxide layers covered on the iron droplet and whiskers on the surface of the sample droplets and substrates. To explain these phenomena, the stability of the oxides was calculated. The calculated results indicate that the oxides that consisted of substrates could decompose under the present experimental conditions.
Cleanness of Molten Steel—Active and Reactive, Exchangeable Filter Systems for the Continuous Casting of Steel
Authors: Wetzig Tony , Baaske Andreas , Karrasch Sven , Dudczig Steffen , Aneziris Christos G. 
Published: May 2024

AbstractThe filtration of steel melts in the continuous casting of steel is of special interest in order to meet the ever-increasing purity requirements regarding the metal’s purity. Due to the high mass flow and the high casting duration, the application of in-built filters in the tundish system is rather challenging, especially regarding the filter capacity. In the framework of this contribution, a new concept involving the immersion of filters into the steel melt from above the tundish was investigated. This approach allows for the flexible exchange of used filters without interruption of the underlying process. At the Institute of Ceramics, Refractories and Composite Materials, carbon-bonded alumina filters on the basis of established slurry compositions and modified replication techniques were scaled up for the industrial application in continuous casting of steel. The best property profile was observed for a triple coating approach based on centrifugation, dip coating and spray coating. In the tundish of a steel casting simulator, a lab-scale casting test was conducted in order to check the thermos-mechanical behavior of the filter in contact with molten steel. After the successful evaluation in lab scale, the filters were tested in industrial trials in cooperation with the company thyssenkrupp Steel Europe AG. A ladle casting with immersed filter lasted approximately 45 min with a static casting speed of 8 to 10 t/min and a melt temperature of above 1550 °C. The filters were analyzed for inclusions and potential damage at the Institute of Ceramics, Refractories and Composite Materials. Dense clogging layers on the filter surface were identified as in-situ layers as usually observed in lab-scale steel casting simulator tests in consequence of reactive filtration effects. Furthermore, inclusion clusters which were removed at the filter bottom due to the direct inflow in consequence of the buoyancy were observed as signs of active filtration. A further alternative to foam filters is presented by gel-cast spaghetti filter structures with mechanically robust full-strut structure. In the subproject T01K, the gel casting process was optimized in order to realize the necessary upscaling of the components. With the aid of alginate-based gel casting, spaghetti filter with organized lattice structures were manufactured and tested. Steel casting simulator trials showed favorable behavior in contact with the melt.
Precipitation of Iron-Containing Intermetallic Phases from Aluminum Alloys by Metal Melt Filtration
Authors: Schoß Johannes Paul , Keßler Andreas , Dommaschk Claudia , Szucki Michal , Wolf Gotthard 
Published: May 2024

AbstractIron (Fe) provides a non-reactive dissolved impurity in aluminum (Al) alloys, which forms a coarse, plate-shaped intermetallic β-phase during solidification. This β-phase is detrimental to the mechanical and casting properties. Therefore, the reduction of Fe by binding in Fe-containing intermetal-lics (sludge phase) was realized via a two-stage procedure, which consisted of conditioning of the melt by manganese (Mn) and chromium (Cr) with subsequent-ly applied metal melt filtration. For this purpose, the formation characteristics of the Fe-rich intermetallic phases were investigated regarding the temperature, time, and initial chemical composition to separate these intermetallics from the residual melt. To evaluate the different process parameters of Fe removal for a potential implementation in lightweight metal foundries, a process technology on an indus-trial scale was developed in cooperation with an industrial partner. The examina-tion of samples in optical microscopy (OM) using image analysis were conducted to determine the area fractions of Fe-rich intermetallics. In addition, optical emis-sion spectrometer (OES) measurements were performed. Complementary investi-gations were achieved by scanning electron microscopy (SEM), with energy dis-persive spectroscopy (EDS), and electron backscatter diffraction (EBSD) to measure the partial chemical composition and for phase identification. The for-mation characteristics of the Fe-containing phases were investigated using DSC cooling curves and selective sampling in quenching experiments. In the experi-mental trials, a maximum reduction of iron of ≈50% was revealed compared to the unfiltered sample, whereby greater influence on the formation of α-intermetallics was inferred by temperature than by time. Moreover, the elements Mn and Cr were reduced by about 66% and 86% at 620 °C, respectively, thus, the element contents in the filtered samples approached the chemical composition of the standard alloy (EN-AC-AlSi9Cu3(Fe)).
Functionalized Feeders, Hollowware, Spider Bricks and Starter Casting Tubes for Increasing the Purity in Steel Casting Processes
Authors: Wetzig Tony , Schwarz Matthias , Schöttler Leandro , Gehre Patrick , Aneziris Christos G. 
Published: May 2024

AbstractAlthough continuous casting became the state of the art for the casting of ordinary steel grades, ingot casting by bottom teeming still has relevance in the steelmaking industry, especially for the manufacturing of specialty and alloy steels. As for every casting process, the ever-increasing quality requirements by customers lead to increased demand for new technologies to increase the purity of the cast steel melt regarding its inclusion content. Due to the special design of the bottom-teeming ingot casting facility and the discontinuous operation as batch process, the application of filters is a promising approach. Tailored foam geometries were prepared based on additive manufacturing via selective laser sintering (SLS) and transformed into filters via modified replication techniques and flame spraying. Additionally to filter application, the functionalization and quality improvement of applied hollowware refractories has high potential to remove existing inclusions from the steel melt and avoid the formation of new inclusions during casting. The investigated hollowware components were manufactured by pressure slip casting on the basis of coarse-grained alumina compositions and subsequent functionalization by spray coating based on carbon-bonded alumina slurries. Simultaneous application of functionalized, “reactive” refractory components and flame-sprayed, “active” filters enables a combined filtration system which unites the advantages of the distinct filtration mechanisms. In the continuous casting of specialty steels, the conditions are more severe resulting in additional challenges regarding the application of filters. An approach investigated in this subproject is the use of extruded filter starter casting tubes above the tundish outlet. To achieve this, extrusion mixes based on cellulose derivatives and materials of the system Al2O3-ZrO2-C (AZC) were investigated for their suitability. The new concepts were tested in industrial casting trials in cooperation with the company Deutsche Edelstahlwerke Specialty Steels Europe GmbH (DEW). Post-mortem, the former melt-refractory interface of the applied components was investigated and steel samples from the ladle, the gating system and the ingot were analyzed in comparison to untreated samples.
Preference Management in a Single User Group Recommender System
Authors: Emamgholizadeh Hanif , Delić Amra , Ricci Francesco 
Published: May 2024

AbstractGroup recommender systems (GRSs) support groups of users to find items, e.g., restaurants, that suit, as much as possible, all the group members’ preferences. We consider a GRS scenario where a single member of the group, the organizer, uses the system to find and choose a suitable restaurant for the entire group. We present a novel GRS that helps the organizer to: enter the preferences of all the group members, recall them, and manage incompatible preferences. In the system’s experimental evaluation, we have found that the designed functionality for recalling group members’ preferences and managing incompatible preferences improve the quality of the organizer’s choice.
Beyond Sensors: A Rule-Based Approach for Cost-Effective Visitor Guidance
Authors: Neubig Stefan , Bečevová Markéta , Brosda Fabian , Loges Ronja , Hein Andreas , Keller Robert , Krcmar Helmut 
Published: May 2024

AbstractTourism is an important economic driver for numerous regions, attracting more than one billion visitors annually. While economically significant, excessive numbers of visitors lead to local overcrowding, which negatively impacts visitors’ experience and safety, and causes environmental harm. This paper proposes a practical approach to empowering destination management organizations (DMOs) to manage tourist flows. We advocate for a rule-based approach that models visitor occupancy based on easily understandable influence factors like weather and date. As a central component, an ontology-guided knowledge graph ensures compatibility with diverse touristic data models and allows seamless integration into existing infrastructures. By digitizing DMOs’ experiential knowledge, we facilitate the implementation of lean and cost-effective visitor guidance. We demonstrate our approach by implementing two applications for two different use cases. The results of our qualitative evaluation reveal the compelling potential for rule-based occupancy modeling approaches serving as a baseline for future visitor management systems.
Customer-to-Customer Real-Time Value Co-creation in Tourism Live Streaming: A Live Streamer Perspective
Authors: Shang Kaiti , Buhalis Dimitrios , Fan Daisy X. F. , Augustyn Marcjanna 
Published: May 2024

AbstractLive streaming has emerged as a new medium for the creation and dissemination of travel experiences, product marketing and destination promotion. Empirical studies on live streamers’ motivations and travel behavior in tourism live streaming are currently under-explored. This study adopted a live streamer perspective and followed a qualitative approach to 1) explore the motivations and travel behaviour of live streamers in tourism, and 2) investigate the process of customer-to-customer real-time value co-creation of the live streamer with other stakeholders by drawing on the Porter-Lawler model. Findings provide in-depth understanding of live streamers’ motivations for engaging in tourism live streaming and the influence of viewers on live streamers. Recommendations are also offered to tourism live streaming platforms regarding how to develop a better incentive strategy for live streamers.
Transformative Communication on Webpages from the Eudaimonic Perspective
Authors: Heinonen Johanna , Myburgh Jade , Murto Maria 
Published: May 2024

AbstractThe key to creating genuinely transformative travel experiences lies in effective communication strategies. By engaging with an audience through meaningful and thought-provoking content, tourism organisations can inspire them to fulfil their life's purpose and embark on a journey of personal growth and discovery. Whether through inspiring stories, beautiful imagery, or practical tips and advice, the right content can help connect with an audience on a deeper level and create unforgettable travel experiences. This study reviewed the literature on eudaimonic communication and analysed the textual content on selected companies’ web pages. By identifying specific elements and their absence, the study aimed to enhance the effectiveness of webpage communication, ultimately leading to a transformative response in the end-user. As a result, it was clear that elements of transformative and eudaimonic communication appeared on web pages, but the way they were used did not support transformation.
Workplace Transformation: Exploring the Impact of Digital Nomad-Inspired Travel Experiences
Authors: Chevtaeva Ekaterina 
Published: May 2024

AbstractThis short research paper explores the experiences and transformations of employed remote workers who engage in remote work trips, a type of digital nomad-inspired travel where individuals combine work and leisure while traveling. The study aims to understand the meaning of these experiences and their impact on participants’ work practices. The methodology employed in this study is Heidegger's hermeneutical phenomenology, which focuses on subjective interpretations of experiences. Data was collected between 2022 and 2023 through prolonged engagement with seven participants who have work flexibility but do not identify as digital nomads. Semi-structured interviews were conducted to empathize with the participants’ experiences. The study highlights that remote work travel is not perceived as a typical vacation experience and differs from digital nomadism. The dimension of self-awareness at work emerged, revealing a range of feelings toward work arrangements in new environments. Some participants felt balanced and healthier, while others felt a lack of motivation. Overall, the experiences made participants more aware of their work style preferences that potentially benefits enterprises as well.
Unlocking the Potential of Content-Based Restaurant Recommender Systems
Authors: Godolja Dante , Kolb Thomas Elmar , Neidhardt Julia 
Published: May 2024

AbstractContent-based restaurant recommender systems use features such as cuisine type, price range, and location to suggest dining options to users. Current research explores ways to improve their effectiveness. In this work, we explore different ideas on how to build a recommender system. We explore TF-IDF as a baseline and the state-of-the-art model SBERT. These ideas are tested on a real-world data-set of a digital restaurant guide. Evaluation involves both qualitative assessment by a domain expert and quantitative analysis. The results show that, with proper preprocessing, TF-IDF can achieve similar scores to SBERT and, depending on the scenario, even better results. However, SBERT still provides more novel recommendations than TF-IDF. Depending on the scenario, both models can be used to generate meaningful restaurant recommendations. However, more implicit aspects like a restaurant’s atmosphere can hardly be captured by these models.
Personalized Smart Travel with Identification and Payment
Authors: Özçelik Şuayb Talha , Yöndem Meltem Turhan , Sayıcı Tunga , Balcı Emre , Al Begüm , Akkurt Oğuzhan 
Published: May 2024

AbstractTourism is a sector that has a substantial economic impact on countries. With the advancement of technology, personalized solutions have become essential in the tourism sector. Building a user profile is the most common method to personalize a system. Personalization in the travel industry aims to provide travelers with the same level of support that they would receive from an assistant who knows them best. This can be achieved by analyzing the traveler’s previous activities, demographic information, and characteristics as a traveler. Various new technologies have started to be used in tourism, and one of them is blockchain, which can be a critical element in the tourism industry in the following years. Travelers must present their identification at various points throughout their trip. Blockchain-based identification technology allows users to go paperless throughout their journey. Digital transactions can enhance the payment experience for visitors at tourism destinations. Destinations that offer digital payment services are viewed as smart tourist hotspots and tend to be more successful in attracting visitors. In this perspective, we added a digital payment system to our system. In this project, as a sub-part of the Celtics-Next project, SmarTravel, we planned to develop the personalized tourism system of the future, in which the customer is the focus, with three institutions: Setur Tourism Agency, Turkcell Technology, and Paycell. We hope that our project will set an example of how payment processes and blockchain-based identification can be integrated into customer-oriented smart systems.
UGC-Based Factors Influencing Customer Satisfaction Pre and Post COVID-19: The Case of Lake Constance
Authors: Regitz Dominic , Höpken Wolfram , Fuchs Matthias 
Published: May 2024

AbstractUser-generated content (UGC) created and distributed through social media and tourism-related websites provides potential travelers the opportunity to gain first-hand experiences about destination products and services. UGC is also of great value to tourism service providers. Since UGC represents customers’ opinions and experience outcomes, potential problems, but also drivers behind customer delight can be identified. In this regard, also temporal changes regarding customer requirements can be determined. The aim of this paper is to identify how certain topic areas mentioned in UGC affect customer satisfaction, exemplarily analyzed for the Lake of Constance Region. Furthermore, potential temporal changes regarding customer satisfaction since the outbreak of the COVID-19 pandemic will be examined. A sentiment analysis, topic detection and regression analysis are carried out on two datasets containing UGC before and after the outbreak of the pandemic. Findings show that the pandemic has changed customers’ attitudes towards certain topic areas.
I Know What You Think About Your Last Vacation: A Topic Modelling Approach for Destination Online Reviews
Authors: Quarshie Benjamin , Santoso Halim Budi , Rachmat Chrismanto Antonius , Ngubeni Paulina , Ukpabi Dandison 
Published: May 2024

AbstractOnline reviews (ORs) have garnered interdisciplinary attention, notably in hospitality and tourism. Despite their significance, concerns about OR credibility persist. Destination Management Organizations increasingly recognize ORs as valuable sources of firsthand, authentic feedback from consumers. However, there remains a dearth of cross-continental investigations into ORs, particularly concerning themes discussed by local and international travelers across various destinations. To address this gap, we employ Latent Dirichlet Analysis—a probabilistic technique to extract topics from a given corpus—to examine 10350 TripAdvisor reviews from 12 destinations in Ghana and Indonesia. Our analysis reveals shared concerns among domestic and international travelers regarding activities, destination attractions, local staff attitudes, and positive visitor experiences. This study advances insights, highlights limitations, and lays the groundwork for future research.
Unveiling Destination Perceptions: A Machine Learning Study on Instagram Influencers’ Cognitive Images
Authors: Egger Roman , Surkic Veronika 
Published: May 2024

AbstractThis study examines the cognitive image of Austria as a travel destination through Instagram content posted by travel influencers. The study also investigates how the account type, influencer type, and posting frequency affect user engagement. Machine learning techniques and statistical analysis are used to analyze the data. The study found that influencers contribute to Austria's destination image mainly through content about the Alps, Vienna, and cycling. The study provides insights into successful destination promotion on Instagram through influencer marketing. Micro-influencers who post regularly with relevant content are ideal for DMOs. Meso-influencers and verified accounts receive more likes for less popular themes, while micro-influencers are sufficient for more popular themes. It is also disadvantageous for meso-influencers to be perceived as commercial accounts and not to post as often as emerging influencers.