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1.
High strain rate hardening of metallic cellular metamaterials
Nejc Novak, Matej Vesenjak, Zoran Ren, 2024, original scientific article

Abstract: Strain rate hardening caused by the changed deformation mode is a fascinating phenomenon in cellular metamaterials where the material’s stiffness and energy absorption capabilities increase as the strain rate increases. This unique behaviour is attributed to a combination of micro-inertia effects, base material’s strain rate hardening and inertia effects. At high strain rates, the metamaterial’s inertia influences its deformation response, which changes to shock mode. This work briefly presents the geometry and fabrication of different metallic metamaterials. Then, it evaluates their mechanical response at different strain rates, ranging from quasi-static to intermediate dynamic and shock, determined by experimental and computational investigation. The three deformation modes can be separated into two critical loading velocities, unique for each metamaterial, which are also presented and compared in this work for various metamaterials. The investigations show that the deformation mode change in metallic metamaterials depends on their porosity. The critical velocities separating the deformation modes decrease with increasing porosity, i.e., decreased density of the metamaterial results in reduced critical loading velocities. The shock deformation mode in cellular metamaterials is thus attainable at much lower loading velocities than in homogeneous (nonporous) materials.
Keywords: metamaterials, cellular structures, high strain rate, experimental testing, computational modelling, compression loading, mechanical properties
Published in DKUM: 22.05.2024; Views: 113; Downloads: 5
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2.
A computational model for analysing the dry rolling/sliding wear behaviour of polymer gears made of POM
Aljaž Ignatijev, Matej Borovinšek, Srečko Glodež, 2024, original scientific article

Abstract: This study presents a computational model to determine the wear behaviour of polymer gears. Using PrePoMax finite element numerical calculation software, a proposed computational model was built to predict dry rolling/sliding wear behaviour based on Archard’s wear model. This allows the calculation of the wear depth in each loading cycle with constant mesh updating using the finite element method. The developed computational model has been evaluated on a spur gear pair, where the pinion made of POM was meshed with a support gear made of steel. The computational results obtained were compared with the analytical results according to the VDI 2736 guidelines. Based on this comparison, it was concluded that the proposed computational model could be used to simulate the wear behaviour of contacting mechanical elements like gears, bearings, etc. The main advantage of the model, if compared to the standardised procedure according to the VDI 2736 guidelines, is the geometry updating after a chosen number of loading cycles, which enables a more accurate prediction of wear behaviour under rolling/sliding loading conditions.
Keywords: polymer gears, rolling/sliding contact, wear, computational modelling
Published in DKUM: 12.04.2024; Views: 128; Downloads: 6
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3.
Exploring factors afecting elementary school teachers' adoption of 3D printers in teaching
Branko Anđić, Andrej Šorgo, Christoph Helm, Robert Weinhandl, Vida Lang, 2023, original scientific article

Abstract: Owing to its advantages such as producing durable models and easy accessibility, 3D modeling and printing (3DMP) has become increasingly popular in educational practice and research. However, the results of many studies have shown that the adoption rate of 3DMP among teachers is still low, especially in elementary schools. Therefore, research is needed to expand current knowledge about what influences teachers' decisions to start and continue using 3DMP in elementary schools. To investigate factors that affect elementary school teachers' decisions to use 3D printing in teaching, this study uses a mixed methods research approach combining binary logistic regression with a qualitative thematic analysis approach. Both approaches assembled predictive constructs from a range of theories on (1) technology acceptance and (2) intentions to continue or abandon 3DMP use. Using a sample of 225 elementary teachers from Montenegro, this study empirically concluded that intentions to discontinue 3DMP was slightly more strongly correlated with the predictors (i.e., performance expectancy, effort expectancy, perceived pedagogical impact, personal innovativeness, management support, user interface quality, technology compatibility, social influence, student expectations) than was intentions to continue using 3DMP. Performance expectancy was a significant determinant of teachers’ continued use of a 3DMP approach. The remaining seven factors (constructs) were found to be insignificant predictors. Perceived pedagogical impact and technology compatibility were significantly associated with teachers' decisions to discontinue using 3DMP. Our results also suggest that the time required to use 3DMP during instruction, the impact of 3DMP on the implementation of curriculum activities, and the availability of 3D printers are all relevant factors that influence teachers’' decision to use or abandon 3DMP.
Keywords: elementary school, binary logistic regression, continuance intentions, thematic analysis approach, 3D modelling and printing
Published in DKUM: 26.03.2024; Views: 211; Downloads: 191
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4.
Reduction of surface defects by optimization of casting speed using genetic programming : an industrial case study
Miha Kovačič, Uroš Župerl, Leo Gusel, Miran Brezočnik, 2023, original scientific article

Abstract: Štore Steel Ltd. produces more than 200 different types of steel with a continuous caster installed in 2016. Several defects, mostly related to thermomechanical behaviour in the mould, originate from the continuous casting process. The same casting speed of 1.6 m/min was used for all steel grades. In May 2023, a project was launched to adjust the casting speed according to the casting temperature. This adjustment included the steel grades with the highest number of surface defects and different carbon content: 16MnCrS5, C22, 30MnVS5, and 46MnVS5. For every 10 °C deviation from the prescribed casting temperature, the speed was changed by 0.02 m/min. During the 2-month period, the ratio of rolled bars with detected surface defects (inspected by an automatic control line) decreased for the mentioned steel grades. The decreases were from 11.27 % to 7.93 %, from 12.73 % to 4.11 %, from 16.28 % to 13.40 %, and from 25.52 % to 16.99 % for 16MnCrS5, C22, 30MnVS5, and 46MnVS5, respectively. Based on the collected chemical composition and casting parameters from these two months, models were obtained using linear regression and genetic programming. These models predict the ratio of rolled bars with detected surface defects and the length of detected surface defects. According to the modelling results, the ratio of rolled bars with detected surface defects and the length of detected surface defects could be minimally reduced by 14 % and 189 %, respectively, using casting speed adjustments. A similar result was achieved from July to November 2023 by adjusting the casting speed for the other 27 types of steel. The same was predicted with the already obtained models. Genetic programming outperformed linear regression.
Keywords: continuous casting of steel, surface defects, automatic control, machine learning, modelling, optimisation, prediction, linear regression, genetic programming
Published in DKUM: 25.03.2024; Views: 201; Downloads: 10
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5.
Optimizing smart manufacturing systems using digital twin
Robert Ojsteršek, Aljaž Javernik, Borut Buchmeister, 2023, original scientific article

Abstract: Presented paper investigates the application of digital twins for the optimisation of intelligent manufacturing systems and focuses on the comparison between simulation modelling results and real-world production conditions. A digital twin was created in the Simio software environment using a data-driven simulation model derived from a real-world production system. Running the digital twin in real time, which was displayed graphically, facilitated the analysis of key parameters, including the number of finished products, average flow time, workstation utilization and product quality. The discrepancies were attributed to the use of random distributions of input data in the dynamic digital twin, as opposed to the long-term measurements and averages in the real-world system. Despite the limitations in the case study, the results underline the financial justification and predictive capabilities of digital twins for optimising production systems. Real-time operation enables continuous evaluation and tracking of parameters and offers high benefits for intelligent production systems. The study emphasises the importance of accurate selection of input data and warns that even small deviations can lead to inaccurate results. Finally, the paper high-lights the role of digital twins in optimising production systems and argues for careful consideration of input data. It highlights the importance of analysing real-world production systems and creating efficient simulation models as a basis for digital twin solutions. The results encourage extending the research to different types of production, from job shop to mass production, in order to obtain a comprehensive optimisation perspective.
Keywords: smart manufacturing, digital twin, optimisation, simulation modelling, Simio, case study
Published in DKUM: 25.03.2024; Views: 166; Downloads: 9
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6.
Computational model for analysing the tooth deflection of polymer gears
Aljaž Ignatijev, Srečko Glodež, Janez Kramberger, 2024, original scientific article

Abstract: A computational model for analysing the tooth deflection of polymer gears is presented in this paper. Because polymer gears have less stiffness compared to metal gears, the proposed approach considers a comprehensive analysis to determine the most suitable numerical model, i.e., the number of teeth that should be modelled for a given gear’s geometry and material. The developed computational model has been evaluated using a spur gear pair, where the pinion made of POM was meshed with a support gear made of steel. Material properties were assigned with linear elastic characteristics for the gear, while the pinion was characterised by hyperelastic properties using POM material. Furthermore, a nonlubricated frictional contact between the gear and pinion was considered in the numerical computations. The computational results that were obtained were compared to the empirical results according to VDI 2736 guidelines. Here, the computational approach showed more accurate results due to the hyperelastic material characteristics of POM and the simulation of multiple teeth meshing. However, VDI 2736 calculation showed comparability with the computational results, with a slightly larger deviation at higher loads. In this respect, the proposed computational approach is more suitable for analysing the tooth deflection of polymer gears under higher loads.
Keywords: polymer gears, tooth deflection, computational modelling
Published in DKUM: 19.03.2024; Views: 196; Downloads: 9
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7.
Modelling of unit differential reversal curves in the G2E hysteresis model
Ermin Rahmanović, Martin Petrun, 2024, original scientific article

Abstract: Iron losses represent a crucial factor in the design process of electrical machines. For this reason, it is important to consider adequate hysteresis behavior within models which predict iron losses. A promising hysteresis description is the static hysteresis model developed by the G2Elab research group. It proposes a unique approach of modelling magnetization curves inside the major loop based on the so-called unit differential reversal curves (uDRCs). This work focuses on modelling of the uDRCs. We analyzed the accuracy and identification approaches of several uDRC models, where we compared the established model with simplified solutions with less parameters. Further, we analyzed the impact of individual models regarding identification convergence. Finally, we highlighted which simplified models give the best trade-off between the ease and stability of identification process of parameters, and the accuracy of the hysteresis model.
Keywords: static hysteresis model, iron loss, loss surface model, magnetic material, mathematical modelling
Published in DKUM: 26.01.2024; Views: 164; Downloads: 17
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8.
Most prominent topics in wellness tourism research : topic modelling analysis
Mila Zečević, Milica Rančić Demir, 2022, independent scientific component part or a chapter in a monograph

Abstract: This paper presents a brief overview of the development of the wellness tourism literature. In addition, an analysis and presentation of the topics that appear within this literature field are given. The purpose of this research was to point out the relevant topics that have attracted research efforts over time. In order to detect these topics, we have selected wellness tourism literature articles from Web of Science. Our analysis used topic modelling tools using a machine learning algorithm in Python. The results imply the distinction between two main research topics within wellness tourism literature – wellness and health and medical research. Such differentiation also matches the development of the wellness tourism research field itself.
Keywords: wellness tourism, literature, topic modelling, health, medical
Published in DKUM: 17.01.2024; Views: 182; Downloads: 5
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9.
Barriers to applying last-mile logistics in the Egyptian market : an extension of the technology acceptance model
Mohamed Amr Sultan, Tomaž Kramberger, Mahmoud Barakat, Ahmed Hussein Ali, 2023, original scientific article

Abstract: Drawing on the Technology Acceptance Model (TAM), this research aims to investigate the impact of social, environmental, and technological barriers on adopting the last-mile logistics application. This research used a self-administrative questionnaire to collect 1060 respondents from the Egyptian market and analysed it using partial least square structural equation modeling. The findings revealed that some elements could obstruct the implementation of last-mile delivery technologies, namely complexity, collaboration efforts between users and application developers and the impact of technical knowledge and expertise on the potentially involved users. The sharing economy helps organisations reduce contaminants, emissions and carbon footprints, and last-mile logistics is one of the tools of the sharing economy that can enhance the productivity and competitiveness of logistics and boost consumer fulfillment. This research will help enhance organisations’ performance in Egypt as a developing country and push towards applying environmental sustainability practices, as it introduces a tool to enhance customer satisfaction and reduce emissions by illustrating how last-mile logistics can be implemented. This is particularly important as last-mile logistics face some implementation barriers, especially in developing countries. In addition, it will help in extending the theory through conceptualising its abstract ideas with the research variables and applying it in a different context.
Keywords: technology acceptance model, technology implementation barrier, last-mile delivery, sustainability, sharing economy, structural equation modelling
Published in DKUM: 15.12.2023; Views: 472; Downloads: 8
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10.
Managing the complexity of empty container movements through repositioning strategies and routing practices under certain demand and supply : doctoral dissertation
Alaa Abdelshafie, 2023, doctoral dissertation

Abstract: Over the past decades, container transportation management has become an important part of the global maritime industry. Due to an ever-increasing movement of containers across the globe in line with the economic boom, the trade imbalance and issues related to empty containers have become inevitable. The accumulation of empty containers in specific ports not only causes a waste of money but also increases the environmental footprint. Accordingly, the urgent need for empty container management has been gaining more attention than ever before, as the shipping companies recognized that more revenues are always derived from a good repositioning strategy. In this respect, this thesis described state-of-the-art of empty container management, focusing on the practices concerning the movement of empty containers that are varied between organizational policies, technical solutions, and optimization applications. With the development of computer-aided systems, the combination of optimization and simulation models has been proposed to tackle the maritime empty container problem. The thesis shows how the strengths of optimization-based simulation can be integrated to provide high-quality solutions with low computational costs. Agent-based modelling was developed to model the global movements of empty containers, providing realistic details of interactions among entities and characteristics of components within the system. The model was applied between ports in the Middle East and Asia for one of the biggest shipping lines worldwide. By using simulated annealing (SA), the best sequence for moving containers can be determined. The results comparison demonstrate that the proposed optimised repositioning strategy can significantly reduce the shipping line’s costs and make full use of empty containers in the planning horizon.
Keywords: shipping industry, container transportation management, empty container repositioning, simulation, optimization, agent-based modelling
Published in DKUM: 08.12.2023; Views: 471; Downloads: 18
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