RWTH Aachen Research Articles

Diary of Bilateral Project with RWTH Aachen University

Diary of Bilateral Project with RWTH Aachen University

Robust Channel Modeling of 2.4 GHz and 5 GHz Indoor Measurements: Empirical, Ray Tracing, and Artificial Neural Network Models

Robust channel models for indoor areas are a crucial part of network planning and are immensely valuable for the small cell and indoor 5G network evolution. As the main input for many resource allocation and network planning problems, the accuracy of the path loss model can improve the overall accuracy of these techniques. Previous measurement campaigns exist for outdoor areas and higher frequencies; however, extensive indoor measurements at these frequencies are missing from the literature. Both WLAN and LTE networks use 2.4- and 5-GHz bands. For this work, indoor measurements were carried out in two distinct indoor environments, at two frequencies, and various models were compared. The measurements were made at the Deutsches Museum Bonn and the ICT cubes, an office space at RWTH Aachen University. Both empirical and deterministic models are tested on the data; the free-space path loss model, the single and dual-slope models with line-of-sight and nonline-of-sight, ray tracing models, and artificial neural network models were all tested and evaluated. Overall, the artificial neural network combined with the free-space path loss model proved to be the most robust model, which accurately predicted the propagation in the indoor environments, at both frequencies.

Experiences with digital teaching formats during the COVID-19 pandemic at the Department of Spatial Design at the Faculty of Architecture, RWTH Aachen University, as illustrated by the course Einführen in das Entwerfen (Introduction to Design)

With the arrival of the COVID-19 pandemic in Central Europe in March 2020, all of the courses offered by the Department of Spatial Design at the Faculty of Architecture, RWTH Aachen University up to that point immediately had to be converted into digital formats. How was this supposed to work in a discipline that is particularly characterized by analog work (drawings and models) and intensive exchange? The following text is a retrospective experience report describing the possibilities and limitations of digital formats in architectural education, using the course Einführen in das Entwerfen (Introduction to Design) as an example. After a brief outline of the module, both the analog teaching concept and its conversion to a digital teaching format during the COVID-19 pandemic are described. This is followed by a personal evaluation by the author about lessons learned and developments for the future of the course.

Investigations on Interface Shear Fatigue of Semi-Precast Slabs with Lattice Girders

Due to their high cost efficiency and flexibility, semi-precast concrete slabs with lattice girders are widely used in constructions all over the world. Prefabricated concrete slabs, combined with in situ concrete topping, exhibit a quasi-monolithic structural behavior in which lattice girders serve as vertical shear reinforcement and ensure the transfer of longitudinal shear within the interface, acting in combination with concrete-to-concrete bonding mechanisms. To be applicable in industrial and bridge construction, semi-precast slabs need to have sufficient resistance against fatigue failure. To improve and expand the limits of application, theoretical and experimental investigations are conducted at the Institute of Structural Concrete (IMB), RWTH Aachen University. To investigate the fatigue behavior of lattice girders, small size tests with lattice girder diagonals were carried out. These test results have been used to derive an S–N curve (S: stress, N: number of load cycles) for lattice girders for a more refined fatigue design. Subsequently, the fatigue behavior of semi-precast slabs with lattice girders was investigated by fatigue tests on single-span slab segments. The fatigue design regulations of lattice girders according to technical approvals can generally be confirmed by this test program; however, they tend to be conservative. The use of the derived S–N curve leads to significantly improved agreement of fatigue behavior observed in tests and design expressions.

Deep learning-based classification of kidney transplant pathology: a retrospective, multicentre, proof-of-concept study

Histopathological assessment of transplant biopsies is currently the standard method to diagnose allograft rejection and can help guide patient management, but it is one of the most challenging areas of pathology, requiring considerable expertise, time, and effort. We aimed to analyse the utility of deep learning to preclassify histology of kidney allograft biopsies into three main broad categories (ie, normal, rejection, and other diseases) as a potential biopsy triage system focusing on transplant rejection. We performed a retrospective, multicentre, proof-of-concept study using 5844 digital whole slide images of kidney allograft biopsies from 1948 patients. Kidney allograft biopsy samples were identified by a database search in the Departments of Pathology of the Amsterdam UMC, Amsterdam, Netherlands (1130 patients) and the University Medical Center Utrecht, Utrecht, Netherlands (717 patients). 101 consecutive kidney transplant biopsies were identified in the archive of the Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany. Convolutional neural networks (CNNs) were trained to classify allograft biopsies as normal, rejection, or other diseases. Three times cross-validation (1847 patients) and deployment on an external real-world cohort (101 patients) were used for validation. Area under the receiver operating characteristic curve (AUROC) was used as the main performance metric (the primary endpoint to assess CNN performance). Serial CNNs, first classifying kidney allograft biopsies as normal (AUROC 0·87 [ten times bootstrapped CI 0·85-0·88]) and disease (0·87 [0·86-0·88]), followed by a second CNN classifying biopsies classified as disease into rejection (0·75 [0·73-0·76]) and other diseases (0·75 [0·72-0·77]), showed similar AUROC in cross-validation and deployment on independent real-world data (first CNN normal AUROC 0·83 [0·80-0·85], disease 0·83 [0·73-0·91]; second CNN rejection 0·61 [0·51-0·70], other diseases 0·61 [0·50-0·74]). A single CNN classifying biopsies as normal, rejection, or other diseases showed similar performance in cross-validation (normal AUROC 0·80 [0·73-0·84], rejection 0·76 [0·66-0·80], other diseases 0·50 [0·36-0·57]) and generalised well for normal and rejection classes in the real-world data. Visualisation techniques highlighted rejection-relevant areas of biopsies in the tubulointerstitium. This study showed that deep learning-based classification of transplant biopsies could support pathological diagnostics of kidney allograft rejection. European Research Council; German Research Foundation; German Federal Ministries of Education and Research, Health, and Economic Affairs and Energy; Dutch Kidney Foundation; Human(e) AI Research Priority Area of the University of Amsterdam; and Max-Eder Programme of German Cancer Aid.

Radiological characterization of a German pressurized water reactor based on a highly resolved method for activity analysis and dose rate calculation

Abstract. The amendment to the atomic act in 2011 results to phase out nuclear energy in Germany until the end of 2022. Subsequently, the licensee of the nuclear power plant is responsible for decommissioning and dismantling. During operation, activation of structures near the core of the reactor occur which govern the amount of radioactive waste, the dose rate distribution and dismantling strategies. Thus, a detailed radiological characterization of in-core and out-core structures is required to optimize decommissioning processes regarding the quantification and minimization of radioactive waste, radiation protection and reducing radiation exposure. These objectives are achieved using an innovative and efficient method developed and applied at the Chair of Repository Safety (Lehrstuhl für Endlagersicherheit, ELS) RWTH Aachen University. Within the framework of the joint project „Development of a methodology for activity analysis and dose rate estimation“, funded by the Federal ministry of Education and Research, approaches the objective to develop a standardized and highly resolved method to calculate time-dependent activity of components and structures near the reactor core based on operating history of the nuclear power plant and neutron fluence distribution. The approach requires the development of a detailed model for Monte-Carlo simulations which provides the basis to neutron fluence, neutron spectra and radiation transport simulations. To calculate the nuclide specific 3-Dimensional (3D) activity distribution of the entire facility, a facility-dependent activation cross section library is produced which focuses on recent nuclear databases (ENDF/B-VIII.0). A highly resolved and space-dependent 3D activity distribution of the entire facility is obtained using a modular program package, developed at ELS, including the activation code ORIGEN2. The results are produced in the form of detailed 3D activity maps. The source terms are generated on the basis of the space-dependent 3D activity distribution using an additional module of the program package. The combination of recent nuclear databases focusing on ENDF/B-VII.1 and complemented by JEFF-3.3 ensures a comprehensive characterisation of source terms. Subsequently, source terms are prepared for 3D radiation transport simulation using the Monte-Carlo method and the computer code MCNP. The simulations are conducted separately for each individual component obtaining the partial contribution of all in-core and out-core structures as well as the dose rate distribution of the entire facility. Similar to the activity calculation, the simulation results are used to generate 3D gamma flux and dose rate maps using the graphic module of the whole program system. On the basis of the radiological characterisation and in view of a high-level radiation protection these maps allow the optimum planning and realisation of the decommissioning and dismantling process of the nuclear power plant.

Tailoring the Properties of Optical Force Probes for Polymer Mechanochemistry.

Invited for the cover of this issue are Robert Göstl and co-workers at DWI-Leibniz Institute for Interactive Materials, RWTH Aachen University and Heidelberg University. The image depicts the tailoring of optical force probes for analyzing polymer materials. Read the full text of the article at 10.1002/chem.202102938.

Investigations on Decreased High Temperature Ductility of Different Continuously Cast Steel Grades

Continuous casting of premium steel grades requires a process with a high degree of precision and the knowledge about the mechanical behavior of the steel at temperatures above 800 °C. Herein, several origins of effects which lead to unwanted impairment of the hot strand shell like segregations, size, amount, kind, and distribution of precipitates as well as porosities from a metallurgical point of view are dealt. The systematic description of potential defect reasons helps to predict harmful operation parameters in context with the chemical composition of steel grades. A compilation of results from experiments at Department of Ferrous Metallurgy of RWTH Aachen University is complemented by a literature review. It is focused on the high temperature ductility and the underlying mechanisms inside the solidifying steel. Finally, potential measures to adjust the continuous casting process to prevent defects are elaborated.

A deep learning model for classifying human facial expressions from infrared thermal images

The analysis of human facial expressions from the thermal images captured by the Infrared Thermal Imaging (IRTI) cameras has recently gained importance compared to images captured by the standard cameras using light having a wavelength in the visible spectrum. It is because infrared cameras work well in low-light conditions and also infrared spectrum captures thermal distribution that is very useful for building systems like Robot interaction systems, quantifying the cognitive responses from facial expressions, disease control, etc. In this paper, a deep learning model called IRFacExNet (InfraRed Facial Expression Network) has been proposed for facial expression recognition (FER) from infrared images. It utilizes two building blocks namely Residual unit and Transformation unit which extract dominant features from the input images specific to the expressions. The extracted features help to detect the emotion of the subjects in consideration accurately. The Snapshot ensemble technique is adopted with a Cosine annealing learning rate scheduler to improve the overall performance. The performance of the proposed model has been evaluated on a publicly available dataset, namely IRDatabase developed by RWTH Aachen University. The facial expressions present in the dataset are Fear, Anger, Contempt, Disgust, Happy, Neutral, Sad, and Surprise. The proposed model produces 88.43% recognition accuracy, better than some state-of-the-art methods considered here for comparison. Our model provides a robust framework for the detection of accurate expression in the absence of visible light.

Ion Selective Membranes

Ion Selective Membranes

Margarethenhöhe goes towards low-carbon area - sustainable concepts for energy-efficient built heritage

Within the framework of a project funded by the Federal Ministry of Economics and Energy (BMWi) in Germany, it is being examined how, with different approaches, even historic buildings can contribute to an energy-efficient heritage district. Five partners are investigating the legal, structural and technical conditions for improving the building envelope in line with the preservation order, modernizing the buildings and providing a future-oriented energy supply. The inclusion of renewable energies and the digital networking of all components is of particular importance. For this all suitable measures will be adapted in five buildings for demonstration. Then, on basis of an extensive monitoring, the theoretically elaborated model approaches and the results obtained by means of numerical simulations can be validated. The joint project started in 2016. The IWB of University of Stuttgart as coordinator, the Margarethe Krupp Foundation as owner, the Gas and Heat Institute Essen e.V. and two institutes of the RWTH Aachen University, the Institute for Integrated Analog Circuits and the Institute for Building and Climate Technology, are partners in the research network.

Application of Advanced RANS Turbulence Models for the Prediction of Turbomachinery Flows

AbstractThe current trend in turbomachinery toward broader operating characteristics requires that operating points in the off-design region can be captured accordingly from the simulation models. Complex processes like separation and vortex formation/dissipation occur under these conditions. Linear two equation models are often not able to represent these effects correctly since their derivation is based on oversimplifications, such as the Boussinesq hypothesis, which makes it impossible to capture anisotropic turbulence. Advanced RANS models are usually not considered in the design process of turbomachines because (1) they are usually more delicate with regards to stability and convergence behavior and (2) require additional computational effort. To make the usage of advanced RANS models more applicable for complex turbomachinery simulations, a selected group of models were implemented into a robust framework of a pressure-based fully coupled solver. To further enhance stability, coupling terms between the turbulent transport equations were derived for several models. Anisotropic turbulence is introduced by computing an algebraic expression or by solving the transport equations for the Reynolds stress components. The evaluation of the models is performed on the RWTH Aachen “Radiver” centrifugal compressor case with vaned diffuser. For design conditions and operation points near the stability limit, all investigated turbulence models predict the compressor characteristic. Operation points in the choking region, on the other hand, are only predicted well by anisotropic models. The good results and improved convergence behavior of the advanced RANS models clearly indicates their applicability in the design process of turbomachines.

SINDRUM II

In 1987 a collaboration including ETHZ - UZH - PSI - RWTH Aachen - Univ.,Tbilisi proposed a new search for \mu eμe conversion in muonic atoms. The SINDRUM II spectrometer came into operation in the \muμE1 area in 1989, but a dedicated beam line was delayed until 1998 by technical setbacks.

Development of a new design approach for composite dowels positioned close to the concrete surface

AbstractComposite dowels as shear connectors between steel profiles and concrete sections have been investigated for decades. The long‐term aim is to implement a consistent design concept within Eurocode 4 ‐ covering both, the fields of bridge and building construction. Especially in building construction, where the concrete slabs are dimensioned increasingly slimmer in contrast to bridge construction, the composite dowels are positioned unavoidably close to free concrete surfaces. This causes additional failure modes, leading to the overall failure of the structure, which have not been entirely investigated yet. At University of Kaiserslautern more than 30 push‐out tests were performed within a joint research project in cooperation with RWTH Aachen University. These tests were focused on the resistance of composite dowels close to the concrete surface in dependence of varying influence parameters. Some results showed a significant reduction in shear strength and deformation capacity, mostly accompanied by the spalling of the concrete cover. Simultaneously, numerical simulations were calibrated and utilized to get a deeper understanding of the load transfer mechanisms and to interpolate between existing experimental results. On the basis of experimental measurements and numerical simulations a load transfer model was developed with a corresponding design approach to calculate the theoretical resistance.

Sorption and Reaction of Biomass Derived HC Blends and Their Constituents on a Commercial Pt–Pd/Al2O3 Oxidation Catalyst

Within the Research Cluster of Excellence “The Fuel Science Center” at RWTH Aachen University, the production and application of new fuels from bio-based carbon feedstocks and CO2 with hydrogen from renewable electricity generation is being investigated. In this study, the storage and oxidation of ethanol, 1-butanol, 2-butanone, cyclopentanone, and cyclopentane as well as two blends thereof on a series production Pt–Pd/Al2O3 oxidation catalyst were investigated. Hydrocarbon (HC) storage and temperature-programmed surface reaction (TPSR) experiments were carried out to analyze their adsorption and desorption behavior. In addition, the individual HCs and both blends were investigated using Diffuse Reflectance Infrared Fourier Transform Spectroscopy (TP-DRIFTS). In general, all oxygenated HCs are adsorbed more strongly than cyclopentane due to their higher polarity. Interestingly, it could be observed that the two different blends [blend 1: ethanol (50 mol %), 2-butanone (21 mol %), cyclopentanone (14 mol %) and cyclopentane (15 mol %); blend 2: 1-butanol (45 mol %), ethanol (29 mol %) and cyclopentane (27 mol %)] exhibit a different storage behavior compared to the single hydrocarbons. It was shown that the presence of 1-butanol and cyclopentane in blend 2 strongly inhibits the oxidation of ethanol. As a result, the ethanol light-off temperature was increased by at least 100 K. A difference was also found in the storage behavior of cyclopentane. While no significant storage could be detected in the pure compound experiment, the experiments with both mixtures showed a larger amount stored. The presence of adsorbed species of the hydrocarbons and their corresponding reaction products has been demonstrated and gives an insight into the storage mechanism of blends.Graphic

Evaluation of new endodontic tooth models in clinical education from the perspective of students and demonstrators

BackgroundThe quality of root canal treatments performed by undergraduate students is often unsatisfactory questioning the current methods of teaching. Based on treatment errors made by students participating the endodontic courses at RWTH Aachen University (Germany), new radiopaque artificial root canal treatment models (DRSK RCT; incisor, premolar, molar) were designed and developed. The aim of the study was to evaluate these models by groups of students and demonstrators.MethodsA total number of 60 students and seven demonstrators from a single institution (RWTH Aachen) participated in this study. They performed endodontic treatments on either initial versions of the DRSK RCT or modified versions. The initial versions were evaluated by students (n = 25) and demonstrators (n = 7). The obtained questionnaire was conducted as 7-point Likert-Scale covering the topics material properties, feeling while performing exercises and perception of its closeness to reality via 19 items (students) and 21 items (demonstrators). According to the evaluations several alterations were applied to the DRSK RCT, the whole study was repeated and evaluated by different students (n = 35) and the same demonstrators (n = 7). Additionally, the demonstrators blindly evaluated the quality of root canal treatments performed by the students (n = 35) on the modified DRSK RCT. Comparisons between the initial versions and the modified versions were calculated using Chi-squared tests.ResultsStudents as well as demonstrators positively evaluated both variants of the DRSK RCT with especially high ratings in the overall evaluation. Students’ rating of the pulp anatomy significantly increased from 5.4 ± 1.1 (mean ± SD) to 5.9 ± 0.9 (mean ± SD; p < 0.05) for the modified model. Likewise, students felt that the ability to flare root canals improved after alterations have been applied. Ratings significantly increased from 4.8 ± 1.6 (mean ± SD) to 5.6 ± 1.0 (mean ± SD; p < 0.05).ConclusionThe results indicate that the DRSK RCT is a promising candidate to be used as an alternative to extracted teeth or as an additional tool for improving dental education. However, some limitations of our analysis have to be considered.

A comparison of various universally applicable power distribution strategies for fuel cell hybrid trains utilizing component modeling at different levels of detail: From simulation to test bench measurement

A comparative study of energy management strategies for fuel cell hybrid trains, which focuses merely on universally applicable power distribution strategies, is presented in this contribution. These scalable strategies include a load follower strategy, an adaptive rule-based strategy, and adaptive Pontryagin's minimum principle (APMP)-based strategies with or without considering the relaxation process in batteries. For the load follower strategy, information about the characteristic consumption curves of the fuel cell system and the equivalent circuit of the batteries is not required. The adaptive rule-based strategy exploits the fuel cell system's characteristic consumption curves to maintain the fuel cell power close to its mean value. For the APMP-based strategies, in addition to the fuel cell modeling, the battery modeling with and without relaxation process in batteries is considered separately. In order to fairly compare the different scalable energy management strategies regarding hydrogen efficiency, Pontryagin's minimum principle-based strategy is used as the reference strategy, which considers the relaxation process in batteries. The comparison of the four strategies in terms of fuel economy is firstly based on the simulative analysis. For the different strategies, the additional hydrogen consumption amounts to 1.6%, 0.7%, 0.6%, and 0.6% respectively, compared to the reference strategy under a typical all-day regional train driving cycle. Then, in the RWTH Aachen University's Center for Mobile Propulsion, the hydrogen consumption is measured experimentally using the different strategies for a short driving cycle. The APMP strategy considering the relaxation process in batteries, consumes the least hydrogen per kilometer travel of 161.9 g/km, with charge sustaining maintained, which is the most energy-efficient energy management strategy. The simulation and experimental results show that the strategy should be selected based on the level of detail to utilize the modeling accuracy of components. Furthermore, due to the scalability of the strategies, they can be further transferred to other applications without enormous tuning effort.

Controlling 100 lasers automatically via the cloud

AbstractIn the Cluster of Excellence “Internet of Production” (IoP), two hundred scientists at RWTH Aachen University in cooperation with Fraunhofer ILT have set up a data center for controlling and monitoring industrial processes. The concept for this is based on a project for controlling laser systems developed at the Fraunhofer Institute for Laser Technology ILT and uses the open source software Kubernetes. A corresponding system has been running successfully at the institute for two years, and with it the institute can automatically and remotely install the software for new lasers in just a few minutes.

Overview of the III International Workshop on Modeling, Information Processing and Computing (MIP: Computing-2021)

The article provides an overview of the main directions of the scientific program of the III International Workshop on Modeling, Information Processing and Computing - MIP: Computing-2021, which took place on May 28, 2021 in Krasnoyarsk on the basis of the 2Krasnoyarsk Science and Technology City Hall of the Russian Union of Scientific and Engineering Associations. Provides overview information about the reports that were included in the program of the scientific session of the seminar and presented in the form of online / video reports and presentations of the participants with placement on the website of the conference materials. Information is given about the seminar partner - the service of scientific publications with open access CEUR-WS.org on Sun SITE Central Europe, operating under the auspices of the Technical University in Aachen, Germany (RWTH Aachen University). Proceedings of the MIP: Computing 2021 Seminar are published as articles in English in CEUR Workshop Proceedings, Volume 2899.

P 21. A 1H/31P MR spectroscopy study of GABA and high energy phosphates modulation induced by anodal tDCS in the primary motor cortex of healthy subjects

Introduction. Transcranial direct current stimulation (tDCS) is a non-invasive technique that modulates excitability of neurons in humans. Anodal tDCS has been used to investigate GABA concentration (Stagg et al 2009) and cerebral energy consumption in motor cortex (Binkofski et al 2011). To date very little is known about the effect of the duration of tDCS on cortical inhibition and related energy consumption or vice versa. We aim to explore long-term GABA and energy modulation following anodal tDCS on the primary motor cortex (M1) by repeated (1H) proton and (31P) phosphorus magnetic resonance spectroscopy (MRS) up to 60 minutes. Materials and Methods. Four righthanded healthy volunteers were recruited in RWTH Aachen University, Hospital Germany. All experiments were performed on a 3T Siemens PRISMA wholebody scanner using a 1H/31P head coil. One set of 1H GABA and 31P MRS scan and two sets of the same scans were carried out before and after the stimulation, respectively. 1 mA anodal and sham tDCS were applied for 20 minutes with the anodal electrode placed over the left M1 and cathodal electrode placed on the right supraorbital area. GABAedited 1H and 31P spectra were independently acquired from a volumeofinterest of 3x3x3cm (27mL) carefully localised on the left M1. MEGAPRESS Jediting was used for GABA detection (TR/TE = 5350/68 ms and 96 averages), and 3D CSI (TR/TE = 3730/2.3 ms and 6 averages) with NOE enhancement (Waltz4) was utilised for 31P acquisition. Data processing and quantification of GABA and 31P spectra were performed with LCModel and jMRUI software, respectively Results. Normalized GABA, ATP/Pi and PCr/Pi concentration from motor cortex following anodal tDCS are shown Figs. 1 and 2. The GABA signal shown in Fig. 1 increases immediately after anodal stimulation and remained increase until the end of the measurement. ATP/Pi and PCr/Pi ratios shown in Fig. 2 reduced following anodal tDCS and remained decrease until the end of measurement. Discussion and Conclusion. Our results revealed an increase of GABA concentration and decrease of 31P metabolites with increasing brain energy consumption following anodal tDCS as measured with 1H/31P MR Spectroscopy. Our preliminary results are relevant to understand the neurochemical mechanism underlying motor cortical plasticity and energy metabolism in humans. We intend to employ a large number of subjects in future for further analysis. References Stagg C. J., Best J. G., Stephenson M. C., O“Shea J., Wylezinska M., Kincses Z. T. Polarity-sensitive modulation of cortical neurotransmitters by transcranial stimulation. J. Neurosci. 2009;29(16) 5202–5206. Binkofski F, Loebig M, Jauch-Chara K, Bergmann S, Melchert UH, Scholand-Engler HG, Schweiger U, Pellerin L, Oltmanns KM. Brain energy consumption induced by electrical stimulation promotes systemic glucose uptake. Biol Psychiatry. 2011;70(7):690–5. Fig. 1. Fig. 2.