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The teaching of civil engineering consists of different didactic approaches, such as lectures, group work or research-based teaching, depending on the respective courses. Currently, the metaverse is gaining importance in teaching and offers the possibility of a new teaching approach for civil engineering and especially for the teaching of courses from the areas of “Digital Design and Construction”. Although the advantages of teaching in the metaverse, such as location and time independence or a higher learning outcome, are mentioned in the literature, there are also challenges that must be considered when teaching in the metaverse. Against this background, this paper examines the implications of using the metaverse as a teaching tool in teaching “Digital Design and Construction”. The impact of teaching BIM in the metaverse is evaluated by (1) a literature review and workshops to evaluate use cases and demands for extended reality (XR) and the metaverse, (2) integrating XR and the metaverse in the courses and valuation by quantitative evaluations and (3) analyzing student papers of the courses and outcomes of a World Café. Due to these steps, this paper presents a novel approach by reflecting the students’ perspective. Furthermore, this paper presents a validated approach for integrating BIM and the metaverse in teaching.
This study explores the potential of robust, strongly basic type I ion exchange resins—specifically, Amberlyst® A26 OH and Lewatit® K 6465—as catalysts for the aldol condensation of citral and acetone, yielding pseudoionone. Emphasis is placed on their long-term stability and commendable performance in continuous operational settings. The aldol reaction, which traditionally is carried out using aqueous sodium hydroxide as the catalyst, holds the potential for enhanced sustainability and reduced waste production through the use of basic ion exchange resins in heterogeneous catalysis. Density Functional Theory (DFT) calculations are employed to investigate catalyst deactivation mechanisms. The result of these calculations indicates that the active sites of Amberlyst® A26 OH are cleaved more easily than the active sites of Lewatit® K 6465. However, the experimental data show a gradual decline in catalytic activity for both resins. Batch experiments reveal Amberlyst® A26 OH’s active sites diminishing, while Lewatit® K 6465 maintains relative consistency. This points to distinct deactivation processes for each catalyst. The constant count of basic sites in Lewatit® K 6465 during the reaction suggests additional factors due to its unique polymer structure. This intriguing observation also highlights an exceptional temperature stability for Lewatit® K 6465 compared to Amberlyst® A26 OH, effectively surmounting one of the prominent challenges associated with the utilization of ion exchange resins in catalytic applications.
A novel approach to manufacture components with integrated conductor paths involves embedding and sintering an isotropic conductive adhesive (ICA) during fused filament fabrication (FFF). However, the molten plastic is deposited directly onto the adhesive path which causes an inhomogeneous displacement of the uncured ICA. This paper presents a 3D printing strategy to achieve a homogeneous cross-section of the conductor path. The approach involves embedding the ICA into a printed groove and sealing it with a wide extruded plastic strand. Three parameter studies are conducted to obtain a consistent cavity for uniform formation of the ICA path. Specimens made of polylactic acid (PLA) with embedded ICA paths are printed and evaluated. The optimal parameters include a groove printed with a layer height of 0.1 mm, depth of 0.4 mm, and sealed with a PLA strand of 700 µm diameter. This resulted in a conductor path with a homogeneous cross-section, measuring 660 µm ± 22 µm in width (relative standard deviation: 3.3%) and a cross-sectional area of 0.108 mm2 ± 0.008 mm2 (relative standard deviation 7.2%). This is the first study to demonstrate the successful implementation of a printing strategy for embedding conductive traces with a homogeneous cross-sectional area in FFF 3D printing.
Multifocal intraocular lenses incorporate a variety of design considerations, including dimensioning of the base monofocal shape and the diffraction grating. While studying three different lens models, we present a practical approach for mathematical modelling and evaluation of these geometries. Contrary to typical lens measurement methods, non-contact measurements were performed on the Alcon SN6AD1, HumanOptics MS 612 DAY and the AMO ZMA00 lenses using a confocal microscope. Subsequent data processing includes centering, tilting correction, filtering and an algorithmic decomposition into a conic and polynomial part and the diffraction grating. Lastly, evaluation of fitting parameters and grating shape is done to allow for inferences about further optical properties. Results and analysis show the confocal microscope to be a suitable imaging method for lens measurements. The processing of this data enables the reconstruction of the annular diffraction grating over the complete lens diameter. Apodization, near addition and diffraction efficiency characteristics are found utilizing the grating shape. Additionally, near-optical axis curvature, asphericity and higher order polynomials are identified qualitatively from the reconstruction of the monofocal base form. Derived properties also include the lens optical base and addition power. By making use of the surface geometries, as well as the lens’ material and thickness, a full lens model can be created for further studies. In summary, our analytical approach enables the insight to various intraocular lens design decisions. Furthermore, this procedure is suitable for lens model creation for research and simulation.
Für den erfolgreichen Ausbau der Elektromobilität nimmt die Nutzerakzeptanz eine entscheidende Rolle ein. Neben den Anschaffungskosten, Wirkungsgraden und Reichweiten fällt vor allem der Komfort des Ladevorgangs als entscheidende Einflussgröße ins Gewicht. Zum aktuellen Zeitpunkt beeinflussen eine Reihe an negativen Faktoren (z.B. Ladeinfrastruktur, Preisintransparenz und vielfältige Bezahlsysteme) den Ladekomfort und halten potenzielle Käufer eines Elektroautos letztlich vom Erwerb ab. Im Rahmen dieser Arbeit soll aus unmittelbarer Sicht der Nutzer:innen der derzeitige Stand der Ladeinfrastruktur und das aktuelle Nutzerverhalten sowie potenzielle Erfolgsfaktoren herausgearbeitet werden. Weiterhin werden verschiedene Lösungsvorschläge erprobt, die den Ladekomfort an öffentlichen Ladesäulen erhöhen soll. Dazu wird eine zweitstufige Online-Studie im Zuge des vom Bundesministerium für Wirtschaft und Klimaschutz geförderten Transformationsnetzwerk „TrendAuto2030plus“ koordiniert und von Studierenden des Master-Kurses „Technologie und Innovationsmanagement“ an der TH Köln durchgeführt. Gemessen an der bisherigen Nachfrage ist die Ladeinfrastruktur in Deutschland besser als ihr Ruf. Ein deutliches Bild der Unzufriedenheit zeigt sich derweil in Bezug auf die aktuell vorherrschende Preisintransparenz an öffentlichen Ladestationen. Die Vielfalt der Tarifmodelle und Bezahlsysteme erfordern eine großen Strukturierungs- und Informationsbedarf. Es werden Systeme der Preisanzeige gefragt sein, die der Vielfalt und Dynamik der unterschiedlichen Bezahl- und Tarifmodelle Rechnung tragen und diese transparent und nutzerfreundlich ausweisen.
Feasibility Study of Wheel Torque Prediction with a Recurrent Neural Network Using Vehicle Data
(2023)
In this paper, we present a feasibility study on predicting the torque signal of a passenger car with the help of a neural network. In addition, we analyze the possibility of using the proposed model structure for temperature prediction. This was carried out with a neural network, specifically a three-layer long short-term memory (LSTM) network. The data used were real road load data from a Jaguar Land Rover Evoque with a Twinster gearbox from GKN. The torque prediction generated good results with an accuracy of 55% and a root mean squared error (RMSE) of 49 Nm, considering that the data were not generated under laboratory conditions. However, the performance of predicting the temperature signal was not satisfying with a coefficient of determination (R2) score of −1.396 and an RMSE score of 69.4 °C. The prediction of the torque signal with the three-layer LSTM network was successful but the transferability of the network to another signal (temperature) was not proven. The knowledge gained from this investigation can be of importance for the development of virtual sensor technology.
The demand for explainable and transparent models increases with the continued success of reinforcement learning. In this article, we explore the potential of generating shallow decision trees (DTs) as simple and transparent surrogate models for opaque deep reinforcement learning (DRL) agents. We investigate three algorithms for generating training data for axis-parallel and oblique DTs with the help of DRL agents (“oracles”) and evaluate these methods on classic control problems from OpenAI Gym. The results show that one of our newly developed algorithms, the iterative training, outperforms traditional sampling algorithms, resulting in well-performing DTs that often even surpass the oracle from which they were trained. Even higher dimensional problems can be solved with surprisingly shallow DTs. We discuss the advantages and disadvantages of different sampling methods and insights into the decision-making process made possible by the transparent nature of DTs. Our work contributes to the development of not only powerful but also explainable RL agents and highlights the potential of DTs as a simple and effective alternative to complex DRL models.
Ten years after the journal’s first publication, we are taking a closer look at the knowledge flows of the output of the journal Publications. We analyzed the papers, topics, their authors and countries to assess the development of scholarly communication within Publications. Our bibliometric analyses show the research journal’s community, where the knowledge of this community is coming from, where it is going, and how diverse the community is based on its internationality and multidisciplinarity. We compare these findings with the scopes and topical goals the journal specifies. We aim at informing the editors and editorial board about the journal’s development to advance the journal’s role in scholarly communication. The results show that regarding topical diversity and internationality, the journal has remarkably developed. Moreover, the journal tends towards the field of library and information science, but strengthens its multidisciplinary status via its topics and author backgrounds.
To date, the establishment of high-titer stable viral packaging cells (VPCs) at large scale for gene therapeutic applications is very time- and cost-intensive. Here we report the establishment of three human suspension 293-F-derived ecotropic MLV-based VPCs. The classic stable transfection of an EGFP-expressing transfer vector resulted in a polyclonal VPC pool that facilitated cultivation in shake flasks of 100 mL volumes and yielded high functional titers of more than 1 × 106 transducing units/mL (TU/mL). When the transfer vector was flanked by transposon terminal inverted repeats (TIRs) and upon co-transfection of a plasmid encoding for the transposase, productivities could be slightly elevated to more than 3 × 106 TU/mL. In contrast and using mRNA encoding for the transposase, as a proof of concept, productivities were drastically improved by more than ten-fold exceeding 5 × 107 TU/mL. In addition, these VPC pools were generated within only 3 weeks. The production volume was successfully scaled up to 500 mL employing a stirred-tank bioreactor (STR). We anticipate that the stable transposition of transfer vectors employing transposase transcripts will be of utility for the future establishment of high-yield VPCs producing pseudotype vector particles with a broader host tropism on a large scale.
Ground tire rubber (GTR) is a product obtained by grinding worn tire treads before retreading them or via the cryogenic or ambient temperature milling of end-of-life tires (ELTs). The aim of this study is to evaluate if calcium carbonate can be substituted by GTR and, if so, to what extent. Different types of ground tire rubber are incorporated in an EPDM (ethylene–propylene–diene–rubber) model compound as partial or complete substitutes of calcium carbonate. The raw compounds and the vulcanizates are characterized to identify the limits. In general, it is apparent that increasing amounts of GTR and larger particles degrade the mechanical properties. The GTR also influences the vulcanization kinetics by reducing the scorch time up to 50% and vulcanization time up to nearly 80%. This is significant for production processes. The compounds with one-third substitution with the smaller-particle-size GTR show mostly similar or even better properties than the reference.