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Generative machine learning models for creative purposes play an increasingly prominent role in the field of dance and technology. A particularly popular approach is the use of such models for generating synthetic motions. Such motions can either serve as source of ideation for choreographers or control an artificial dancer that acts as improvisation partner for human dancers. Several examples employ autoencoder-based deep-learning architectures that have been trained on motion capture recordings of human dancers. Synthetic motions are then generated by navigating the autoencoder's latent space. This paper proposes an alternative approach of using an autoencoder for creating synthetic motions. This approach controls the generation of synthetic motions on the level of the motion itself rather than its encoding. Two different methods are presented that follow this principle. Both methods are based on the interactive control of a single joint of an artificial dancer while the other joints remain under the control of the autoencoder. The first method combines the control of the orientation of a joint with iterative autoencoding. The second method combines the control of the target position of a joint with forward kinematics and the application of latent difference vectors. As illustrative example of an artistic application, this latter method is used for an artificial dancer that plays a digital instrument. The paper presents the implementation of these two methods and provides some preliminary results.
Editorial
(2022)
Editorial
(2022)
Editorial
(2022)
Editorial
(2022)
Editorial
(2022)
Editorial
(2022)
Entrepreneurship – die systematische Erkennung und Förderung von Unternehmertalenten gehört zu dem Kernaufgabengebiet von Hochschulen. Oftmals wird der Bereich jedoch auf die Förderung von Studierenden im Kontext von Gründungsvorhaben reduziert. In der Abstimmung mit Partnern der Region Südlicher Oberrhein liegt hier jedoch auch ein Aufgabengebiet der wissenschaftlichen Weiterbildungsangebote von Hochschulen, mit der auch Unternehmertalente in und für bestehende Unternehmen gefördert werden.
The sharp rise in electricity and oil prices due to the war in Ukraine has caused fluctuations in the results of the previous study about the economic analysis of electric buses. This paper shows how the increase in fuel prices affects the implementation of electric buses. This publication is constructing the Total Cost of Ownership (TCO) model in the small-mid-size city, Offenburg for the transition to electric buses. The future development of costs is estimated and a projection based on learning curves will be carried out. This study intends to introduce a new future prospect by presenting the latest data based on previous research. Through the new TCO result, the cost differences between the existing diesel bus and the electric bus are updated, and also the future prospects for the economic feasibility of the electric bus in a small and midsize city are presented.
Gas Analysis and Optimization of Debinding and Sintering Processes for Metallic Binder-Based AM*
(2022)
Binder-based additive manufacturing processes for metallic
AM components in a wide range of applications usually use
organic binders and process-related additives that must be
thermally removed before sintering. Debinding processes are
typically parameterized empirically and thus far from the optimum.
Since debinding based on thermal decomposition processes
of organic components and the subsequent thermochemical
reactions between process atmosphere and metal
powder materials make uncomplicated parameterization difficult,
in-situ instrumentation was introduced at Fraunhofer
IFAM. This measurement method relies on infrared spectroscopy
and mass spectrometry in various furnace concepts to
understand the gas processes of decomposition of organic
components and the subsequent thermochemical reactions
between the carrier gas atmosphere and the metal part, as well
as their kinetics. This method enables an efficient optimization
of the temperature-time profiles and the required atmosphere
composition to realize dense AM components with low contamination.
In the paper, the optimization strategy is presented,
and the achievable properties are illustrated using a fused
filament fabrication (FFF) component example made of 316L
stainless steel.
In the literature, many studies have described the 3D printing of ceramic-based scaffolds (e.g., printing with calcium phosphate cement) in the form of linear structures with layer rotations of 90°, although no right angles can be found in the human body. Therefore, this work focuses on the adaptation of biological shapes, including a layer rotation of only 1°. Sample shapes were printed with calcium phosphate cement using a 3D Bioplotter from EnvisionTec. Both straight and wavy spokes were printed in a round structure with 12 layers. Depending on the strand diameter (200 and 250 µm needle inner diameter) and strand arrangement, maximum failure loads of 444.86 ± 169.39 N for samples without subsequent setting in PBS up to 1280.88 ± 538.66 N after setting in PBS could be achieved.
Es wird ein System zur Vorlesungsnachverfolgung (engl. Lecture Tracking) vorgestellt, das eine Kamera automatisch in Richtung des Vortragenden ausrichtet. Die kontinuierliche Positionsbestimmung der Kamera als auch die des Vortragenden erfolgt dabei durch Smartphones. Die Kamera und ein Smartphone sind an einen Roboter montiert, der als Schwenkeinheit dient. Das andere Smartphone trägt der Vortragende. Beide Smartphones können ihre Position im Raum bestimmen, sodass der erforderliche Drehwinkel berechnet und an den Roboter gesendet werden kann. Dieser führt dann die entsprechende Rotation durch, sodass der Vortragende immer in der Bildmitte zu sehen ist.
Im Projekt „BioMeth“ wurden zwei neuartige und bislang noch nicht für die biologische Methanisierung beschriebene Anlagenkonzepte entwickelt. Der neuentwickelte Invers-Membranreaktor (IMR) ermöglicht es, den Eintrag der erforderlichen Eduktgase Wasserstoff H2 und Kohlendioxid CO2 über kommerziell erhältliche Ultrafiltrationsmembranen und den Entgasungsbereich für den Methanaustrag räumlich zu trennen und zusätzlich einen hydraulischen Druck zur Steigerung des Wasserstoffeintrages zu nutzen. Ein Vorteil des Verfahrens ist, dass perspektivisch sowohl das CO2 aus klassischem Biogas als auch CO2-Quellen aus industriellen Abluftströmen, z. B. aus der Zementindustrie als Kohlenstoffquelle genutzt werden können.
Über die biologische Methanisierung hinaus eignet sich der Invers-Membranreaktor der Einschätzung der Autoren nach auch generell zur biotechnologischen Herstellung nicht-flüchtiger Wertstoffe ausgehend von gasförmigen Substraten. Im IMR kann z. B. ein Membranmodul zum Eintrag der Eduktgase verwendet werden, während ein weiteres Hohlmembranmodul zur zyklischen oder kontinuierlichen Abtrennung der wertstoffhaltigen Reaktionslösung unter Rückhaltung der Mikrobiologie im Sinne eines In-situ Product Recovery (ISPR)-Konzeptes genutzt werden kann.
Als herausragendes Ergebnis erwies sich während der Untersuchung des IMR, dass mit dem Konzept der Membranbegasung CH4-Konzentrationen von > 90 Vol.-% über eine einjährige Versuchsreihe kontinuierlich und mit flexiblem Gaseintrag erzielt werden konnten. Nach Inbetriebnahme war dabei außer der Zugabe von H2 und CO2 als Energie- bzw. C-Quelle lediglich eine zweimalige Ergänzung von Supplementen erforderlich. Die maximal erreichte membranflächen-spezifische Methanbildungsrate ohne Gaszirkulation lag bei 83 LN Methan pro m2 Membranfläche und Tag bei einer Produktgaszusammensetzung von 94 Vol.% Methan, 2 Vol.% H2, und 4 Vol.% CO2.
Das zweite noch in der frühen Testphase befindliche Verfahren nutzt Druckunterschiede in einer 10 m hohen gepackten Gegenstromblasensäule, die mit einem ebenfalls 10 m hohen separaten Entgasungs-Reaktor kombiniert wurde. Diese Verfahrenskonzept soll es ermöglichen, eine hohe Wasserstofflöslichkeit aufgrund des am Säulenfuß vorliegenden hydrostatischen Druckes zu erreichen und dabei gleichzeitig den Energiebedarf zu minimieren, die Investitionskosten zu reduzieren und optimale zeitliche und räumlichen Bedingungen für die mikrobiologische Umsetzung von H2 und CO2 zu schaffen. Erste Untersuchungen am Gegenstromblasensäulenreaktor zum Stoffübergang von Luft bestätigten eine gute Anreicherung der im Kreislauf geführten Flüssigkeit bereits bei verhältnismäßig niedrigen Gasleerrohrgeschwindigkeiten. In der zweiten Säule des Reaktoraufbaus sollte am Kopf aufgrund der Druckentspannung ein Ausgasen der im Vergleich zu Atmosphärendruck mit Gas übersättigten Flüssigkeit erfolgen. Das Ausgasen der Flüssigkeit konnte ebenfalls am Beispiel des Lufteintrages bestätigt werden.
Maschinelles Lernen verändert zusehends die Arbeitswelt. Auch in der Produktionsplanung und -steuerung finden sich vielversprechende Anwendungsfälle. In diesem Beitrag sollen ausgewählte Anwendungsbereiche und Ansätze vorgestellt werden, die anhand einer umfangreichen Untersuchung wissenschaftlicher Veröffentlichungen identifiziert wurden. Als Strukturierungshilfe dient das Aachener PPS-Modell.
Beuys-Gespräch
(2022)
Titanium and stainless steel are commonly known as osteosynthesis materials with high strength and good biocompatibility. However, they have the big disadvantage that a second operation for hardware removal is necessary. Although resorbable systems made of polymers or magnesium are increasingly used, they show some severe adverse foreign body reactions or unsatisfying degradation behavior. Therefore, we started to investigate molybdenum as a potential new biodegradable material for osteosynthesis in craniomaxillofacial surgery. To characterize molybdenum as a biocompatible material, we performed in vitro assays in accordance with ISO Norm 10993-5. In four different experimental setups, we showed that pure molybdenum and molybdenum rhenium alloys do not lead to cytotoxicity in human and mouse fibroblasts. We also examined the degradation behavior of molybdenum by carrying out long-term immersion tests (up to 6 months) with molybdenum sheet metal. We showed that molybdenum has sufficient mechanical stability over at least 6 months for implants on the one hand and is subject to very uniform degradation on the other. The results of our experiments are very promising for the development of new resorbable osteosynthesis materials for craniomaxillofacial surgery based on molybdenum.
Grundlagen der Logistik
(2022)
Logistikprozesse unterliegen einem ständigen Verbesserungs- und Optimierungsgebot. Lediglich den Status quo zu erhalten, ist keine Strategie und führt nicht zum Erfolg. Im Gegenteil: Gerade in der Logistik ist Stillstand ein sicheres Indiz dafür, dass man überholt wird. Zukunftsthemen wie die Digitalisierung und Automatisierung sind jedoch auch kein Allheilmittel. Sie bilden den Grundstein für die Transparenz von Logistikprozessen und -systemen, indem sie auf verbesserte Überwachung von Objekten und Prozessen setzen, die Vernetzung von Akteuren fördern, auch in Form von digitalen Zwillingen. Die Ansätze zur Verbesserung, Umgestaltung und Anpassung von Logistiksystemen und -operatoren kann auch in Zukunft nur durch eine(n) gut ausgebildete(n) Logistiker*in erfolgen.
Das vorliegende Buch soll deshalb als beispielhafte Anleitung und in diesem Sinne als Handwerkszeug für Logistiker*innen und -interessierte dienen. Die konkrete Umsetzung und Verbesserung, sei es in Richtung einer Effizienzsteigerung oder einer Neugestaltung, muss immer durch den Menschen selbst vorgenommen werden.
An import ban of Russian energy sources to Germany is currently being increasingly discussed. We want to support the discussion by showing a way how the electricity system in Germany can manage low energy imports in the short term and which measures are necessary to still meet the climate protection targets. In this paper, we examine the impact of a complete stop of Russian fossil fuel imports on the electricity sector in Germany, and how this will affect the climate coals of an earlier coal phase-out and climate neutrality by 2045.
Following a scenario-based analysis, the results gave a point of view on how much would be needed to completely rely on the scarce non-renewable energy resources in Germany. Huge amounts of investments would be needed in order to ensure a secure supply of electricity, in both generation energy sources (RES) and energy storage systems (ESS). The key findings are that a rapid expansion of renewables and storage technologies will significantly reduce the dependence of the German electricity system on energy imports. The huge integration of renewable energy does not entail any significant imports of the energy sources natural gas, hard coal, and mineral oil, even in the long term. The results showed that a ban on fossil fuel imports from Russia outlines huge opportunities to go beyond the German government's climate targets, where the 1.5-degree-target is achieved in the electricity system.
During the coronavirus crisis, labs had to be offered in digital form in mechanical engineering at short notice. For this purpose, digital twins of more complex test benches in the field of fluid energy machines were used in the mechanical engineering course, with which the students were able to interact remotely to obtain measurement data. The concept of the respective lab was revised with regard to its implementation as a remote laboratory. Fortunately, real-world labs were able to be fully replaced by remote labs. Student perceptions of remote labs were mostly positive. This paper explains the concept and design of the digital twins and the lab as well as the layout, procedure, and finally the results of the accompanying evaluation. However, the implementation of the digital twins to date does not yet include features that address the tactile experience of working in real-world labs.
The energy system is changing since some years in order to achieve the climate goals from the Paris Agreement which wants to prevent an increase of the global temperature above 2 °C [1]. Decarbonisation of the energy system has become for governments a big challenge and different strategies are being stablished. Germany has set greenhouse gas reduction limits for different years and keeps track of the improvement made yearly. The expansion of renewable energy systems (RES) together with decarbonisation technologies are a key factor to accomplish this objective.
This research is done to analyse the effect of introducing biochar, a decarbonisation technology, and study how it will affect the energy system. Pyrolysis is the process from which biochar is obtained and it is modelled in an open-source energy system model. A sensibility analysis is done in order to assess the effect of changing the biomass potential and the costs for pyrolysis.
The role of pyrolysis is analysed in the form of different future scenarios for the year 2045 to evaluate the impact when the CO2 emission limit is zero. All scenarios are compared to the reference scenario, where pyrolysis is not considered.
Results show that biochar can be used to compensate the emissions from other conventional power plant and achieve an energy transition with lower costs. Furthermore, it was also found that pyrolysis can also reduce the need of flexibility. This study also shows that the biomass potential and the pyrolysis costs can strongly affect the behaviour of pyrolysis in the energy system.
Zunehmender städtischer und regionaler Güterverkehr belastet die Anwohner, Verkehrsteilnehmer und die Umwelt. Das Projekt LogIKTram verfolgt das Ziel, regionalen Güterverkehr von der Straße auf die Schiene zu verlagern und somit eine Entlastung zu erzielen. Diese Idee soll am Beispiel einer Gütertram in der Region Karlsruhe erprobt werden. Dafür entwickelt die Hochschule Offenburg unter anderem ein Logistikkonzept und ein Planungsmodell. Beides wird in einer IKT-Plattform umgesetzt.
The impact of the circular economy on sustainable development: A European panel data approach
(2022)
The circular economy (CE) has attracted considerable attention because of its potential to help achieve sustainable development (SD). This paper presents a comprehensive analysis of the effect of the CE on the three dimensions of SD at the country level. We analysed the impact of each CE source of value (renewable energy, reuse, repair, recycling) and the influence of an overall factor-analysis-derived measure of the CE on the economic, environmental and social dimensions of SD. The aim was to compare the individual impacts and outcomes of the CE and its sources of value in a single study. Panel data analysis was performed using a sample of 25 European countries for the period 2010 to 2019. The findings show a major impact of the CE on achieving SD, which has positive
effects on the economy, environment and society. However, the results show that the impact of each CE value source on the three SD dimensions varies. While renewable energies and reuse reduce the impact on the environment, recycling has no effect, and repair increases GHG emissions. However, repair is the only CE source with a positive economic impact at the country level. Finally, renewable energy, repair and recycling reduce unemployment. Decision makers should conduct impact analysis to design suitable, efficient and targeted measures depending on each country's specific objectives.
In this paper, we study the runtime performance of symmetric cryptographic algorithms on an embedded ARM Cortex-M4 platform. Symmetric cryptographic algorithms can serve to protect the integrity and optionally, if supported by the algorithm, the confidentiality of data. A broad range of well-established algorithms exists, where the different algorithms typically have different properties and come with different computational complexity. On deeply embedded systems, the overhead imposed by cryptographic operations may be significant. We execute the algorithms AES-GCM, ChaCha20-Poly1305, HMAC-SHA256, KMAC, and SipHash on an STM32 embedded microcontroller and benchmark the execution times of the algorithms as a function of the input lengths.
In recent years, the topic of embedded machine learning has become very popular in AI research. With the help of various compression techniques such as pruning, quantization and others compression techniques, it became possible to run neural networks on embedded devices. These techniques have opened up a whole new application area for machine learning. They range from smart products such as voice assistants to smart sensors that are needed in robotics. Despite the achievements in embedded machine learning, efficient algorithms for training neural networks in constrained domains are still lacking. Training on embedded devices will open up further fields of applications. Efficient training algorithms would enable federated learning on embedded devices, in which the data remains where it was collected, or retraining of neural networks in different domains. In this paper, we summarize techniques that make training on embedded devices possible. We first describe the need and requirements for such algorithms. Then we examine existing techniques that address training in resource-constrained environments as well as techniques that are also suitable for training on embedded devices, such as incremental learning. At the end, we also discuss which problems and open questions still need to be solved in these areas.
The integration of Internet of Things devices onto the Blockchain implies an increase in the transactions that occur on the Blockchain, thus increasing the storage requirements.
A solution approach is to leverage cloud resources for storing blocks within the chain. The paper, therefore, proposes two solutions to this problem. The first being an improved hybrid architecture design which uses containerization to create a side chain on a fog node for the devices connected to it and an Advanced Time‑variant Multi‑objective Particle Swarm Optimization Algorithm (AT‑MOPSO) for determining the optimal number of blocks that should be transferred to the cloud for storage. This algorithm uses time‑variant weights for the velocity of the particle swarm optimization and the non‑dominated sorting and mutation schemes from NSGA‑III. The proposed algorithm was compared with results from the original MOPSO algorithm, the Strength Pareto Evolutionary Algorithm (SPEA‑II), and the Pareto Envelope‑based Selection Algorithm with region‑based selection (PESA‑II), and NSGA‑III. The proposed AT‑MOPSO showed better results than the aforementioned MOPSO algorithms in cloud storage cost and query probability optimization. Importantly, AT‑MOPSO achieved 52% energy efficiency compared to NSGA‑III.
To show how this algorithm can be applied to a real‑world Blockchain system, the BISS industrial Blockchain architecture was adapted and modified to show how the AT‑MOPSO can be used with existing Blockchain systems and the benefits it provides.
Background: Running overuse injuries (ROIs) occur within a complex, partly injury-specific interplay between training loads and extrinsic and intrinsic risk factors. Biomechanical risk factors (BRFs) are related to the individual running style. While BRFs have been reviewed regarding general ROI risk, no systematic review has addressed BRFs for specific ROIs using a standardized methodology.
Objective: To identify and evaluate the evidence for the most relevant BRFs for ROIs determined during running and to
suggest future research directions.
Design: Systematic review considering prospective and retrospective studies. (PROSPERO_ID: 236,832).
Data Sources: PubMed. Connected Papers. The search was performed in February 2021.
Eligibility Criteria: English language. Studies on participants whose primary sport is running addressing the risk for the seven most common ROIs and at least one kinematic, kinetic (including pressure measurements), or electromyographic BRF. A BRF needed to be identified in at least one prospective or two independent retrospective studies. BRFs needed to be determined during running.
Results: Sixty-six articles fulfilled our eligibility criteria. Levels of evidence for specific ROIs ranged from conflicting to moderate evidence. Running populations and methods applied varied considerably between studies. While some BRFs appeared for several ROIs, most BRFs were specific for a particular ROI. Most BRFs derived from lower-extremity joint kinematics and kinetics were located in the frontal and transverse planes of motion. Further, plantar pressure, vertical ground reaction force loading rate and free moment-related parameters were identified as kinetic BRFs.
Conclusion: This study offers a comprehensive overview of BRFs for the most common ROIs, which might serve as a starting point to develop ROI-specific risk profiles of individual runners. We identified limited evidence for most ROI-specific risk factors, highlighting the need for performing further high-quality studies in the future. However, consensus on data collection standards (including the quantification of workload and stress tolerance variables and the reporting of injuries) is warranted.
Background: Many countries have restricted public life in order to contain the spread of the novel coronavirus (SARS-CoV2). As a side effect of related measures, physical activity (PA) levels may have decreased.
Objective: We aimed (1) to quantify changes in PA and (2) to identify variables potentially predicting PA reductions.
Methods: A systematic review with random-effects multilevel meta-analysis was performed, pooling the standardized mean differences in PA measures before and during public life restrictions.
Results: A total of 173 trials with moderate methodological quality (modified Downs and Black checklist) were identified. Compared to pre-pandemic, total PA (SMD − 0.65, 95% CI − 1.10 to − 0.21) and walking (SMD − 0.52, 95% CI − 0.29 to − 0.76) decreased while sedentary behavior increased (SMD 0.91, 95% CI: 0.17 to 1.65). Reductions in PA affected all intensities (light: SMD − 0.35, 95% CI − 0.09 to − 0.61, p = .013; moderate: SMD − 0.33, 95% CI − 0.02 to − 0.6; vigorous: SMD − 0.33, − 0.08 to − 0.58, 95% CI − 0.08 to − 0.58) to a similar degree. Moderator analyses revealed no influence of variables such as sex, age, body mass index, or health status. However, the only continent without a PA reduction was Australia and cross-sectional trials yielded higher effect sizes (p < .05).
Conclusion: Public life restrictions associated with the COVID-19 pandemic resulted in moderate reductions in PA levels and large increases in sedentary behavior. Health professionals and policy makers should therefore join forces to develop strategies counteracting the adverse effects of inactivity.
During the coronavirus crisis, labs had to be offered in digital form in mechanical engineering at short notice. For this purpose, digital twins of more complex test benches in the field of fluid energy machines were used in the mechanical engineering course, with which the students were able to interact remotely to obtain measurement data. The concept of the respective lab was revised with regard to its implementation as a remote laboratory. Fortunately, real-world labs were able to be fully replaced by remote labs. Student perceptions of remote labs were mostly positive. This paper explains the concept and design of the digital twins and the lab as well as the layout, procedure, and finally the results of the accompanying evaluation. However, the implementation of the digital twins to date does not yet include features which address the tactile experience of working in real-world labs.
Konzeption und Evaluierung eines Trainings-Windkanals für den spezifischen Einsatz im Skisprung
(2022)
Teaching and learning concepts that are adapted to the constantly evolving requirements due to rapid technological progress are essential for teaching in media photonics technology. After the development of a concept for research-oriented education in optics and photonics, the next step will be a conceptual restructuring and redesign of the entire curriculum for education in media photonics technology. By including typical research activities as essential components of the learning process, a broad platform for practical projects and applied research can be created, offering a variety of new development opportunities.
This paper has the objective of creating a framework for a different cultural dimension of corporate entrepreneurship leading to corporate entrepreneurial culture (CEC). The analysis of CEC is based on a review of existing concepts of organisational culture and entrepreneurship. They are combined to create a framework of CEC, including macro- and microlevels and examples of subcultures. Core ideas of the framework are validated by qualitative interviews with ten experts. The identified organisational category of the CEC framework is defined by the levels of micro-cultures or subcultures and includes the upper levels of the hierarchy, including the industry level. Geographic categories such as regional or national culture are also part of the system. The individual category of the CEC framework is characterised by competencies (including aspects such as motivation, creativity, mobilising others, coping with uncertainty, teamwork and social competencies) and entrepreneurial personalities. The results of the interviews show the importance of these individual competencies for a lively CEC. The different levels, such as national and professional cultures, as a dimension of the organisational category of the framework are also confirmed by the interviews. The findings indicate that the individual category of CEC could be used for job satisfaction or engagement and the degree of CEC of an organisation could be defined and developed by the organisational category. The identified framework contributes to an understanding of this complex topic and supports companies in the implementation of entrepreneurial ideas in different organisational contexts.
To achieve Germany's climate targets, the industrial sector, among others, must be transformed. The decarbonization of industry through the electrification of heating processes is a promising option. In order to investigate this transformation in energy system models, high-resolution temporal demand profiles of the heat and electricity applications for different industries are required. This paper presents a method for generating synthetic electricity and heat load profiles for 14 industry types. Using this methodology, annual profiles with a 15-minute resolution can be generated for both energy demands. First, daily profiles for the electricity demand were generated for 4 different production days. These daily profiles are additionally subdivided into eight end-use application categories. Finally, white noise is applied to the profile of the mechanical drives. The heat profile is similar to the electrical but is subdivided into four temperature ranges and the two applications hot water and space heating. The space heating application is additionally adjusted to the average monthly outdoor temperature. Both time series were generated for the analysis of an electrification of industrial heat application in energy system modelling.
The contribution of the RoofKIT student team to the SDE 21/22 competition is the extension of an existing café in Wuppertal, Germany, to create new functions and living space for the building with simultaneous energetic upgrading. A demonstration unit is built representing a small cut-out of this extension. The developed energy concept was thoroughly simulated by the student team in seminars using Modelica. The system uses mainly solar energy via PVT collectors as the heat source for a brine-water heat pump (space heating and hot water). Energy storage (thermal and electrical) is installed to decouple generation and consumption. Simulation results confirm that carbon neutrality is achieved for the building operation, consuming and generating around 60 kWh/m2a.
Peer-to-peer energy trading and local electricity markets have been widely discussed as new options for the transformation of the energy system from the traditional centralized scheme to the novel decentralized one. Moreover, it has also been proposed as a more favourable alternative for already expiring feed in tariff policies that promote investment in renewable energy sources. Peer-to-peer energy trading is usually defined as the integration of several innovative technologies, that enable both prosumers and consumers to trade electricity, without intermediaries, at a consented price. Furthermore, the techno-economic aspects go hand in hand with the socio-economic aspects, which represent at the end significant barriers that need to be tackled to reach a higher impact on current power systems. Applying a qualitative analysis, two scalable peer-to-peer concepts are presented in this study and the possible participant´s entry probability into such concepts. Results show that consumers with a preference for environmental aspects have in general a higher willingness to participate in peer-to-peer energy trading. Moreover, battery storage systems are a key technology that could elevate the entry probability of prosumers into a peer-to-peer market.
Robust scheduling problem is a major decision problem that is addressed in the literature, especially for remanufacturing systems; this problem is complex because of the high uncertainty and complex constraints involved. Generally, the existing approaches are dedicated to specific processes and do not enable the quick and efficient generation and evaluation of schedules. With the emergence of the Industry 4.0 paradigm, data availability is now considered an opportunity to facilitate the decision-making process. In this study, a data-driven decisionmaking process is proposed to treat the robust scheduling problem of remanufacturing systems in uncertain environments. In particular, this process generates simulation models based on a data-driven modeling approach. A robustness evaluation approach is proposed to answer several decision questions. An application of the decision process in an industrial case of a remanufacturing system is presented herein, illustrating the impact of robustness evaluation results on real-life decisions.
Auswirkung eines Importstopps russischer Energieträger auf die Klimaschutzziele in Deutschland
(2022)
Ein Importstopp russischer Energieträger nach Deutschland wird derzeit vermehrt diskutiert. Wir wollen die Diskussion unterstützen, indem wir einen Weg zeigen, wie das Elektrizitätssystem in Deutschland kurzfristig mit geringen Energieimporten auskommt und welche Maßnahmen notwendig sind, um die Klimaschutzziele trotzdem einzuhalten. Die Ergebnisse eines solchen Energiewendeszenarios mit reduzierter Importabhängigkeit werden mit dem Energiesystemmodell MyPyPSA-Ger berechnet. Die wichtigsten Erkenntnisse sind, dass ein zügiger Ausbau Erneuerbarer Energien und von Speichertechnologien • die Abhängigkeit des deutschen Elektrizitätssystems von Energieimporten deutlich reduziert. • auch langfristig keine wesentlichen Importe der Energieträger Erdgas, Steinkohle und Mineralöl nach sich zieht. • über die Klimaziele der Bundesregierung hinaus das 1,5-Grad-Ziel im Elektrizitätssystem erreicht wird.
This paper will introduce the open-source model MyPyPSA-Ger, a myopic optimization model developed to represent the German energy system with a detailed mapping of the electricity sector, on a highly disaggregated level, spatially and temporally, with regional differences and investment limitations. Furthermore, this paper will give new outlooks on the German federal government 2050 emissions goals of the electricity sector to become greenhouse gas neutral by proposing new CO2 allowance strategies. Moreover, the regional differences in Germany will be discussed, their role and impact on the energy transition, and which regions and states will drive the renewable energy utilization forward.
Following a scenario-based analysis, the results point out the major keystones of the energy transition path from 2020 to 2050. Solar, onshore wind, and gas-fired power plants will play a fundamental role in the future electricity systems. Biomass, run of river, and offshore wind technologies will be utilized in the system as base-load generation technologies. Solar and onshore wind will be installed almost everywhere in Germany. However, due to the nature of Germany’s weather and geographical features, the southern and northern regions will play a more important role in the energy transition.
Higher CO2 allowance costs will help achieve the 1.5-degree-target of the electricity system and will allow for a rapid transition. Moreover, the more expensive, and the earlier the CO2 tax is applied to the system, the less it will cost for the energy transition, and the more emissions will be saved throughout the transition period. An earlier phase-out of coal power plants is not necessary with high CO2 taxes, due to the change in power plant’s unit commitment, as they prioritize gas before coal power plants. Having moderate to low CO2 allowance cost or no clear transition policy will be more expensive and the CO2 budget will be exceeded. Nonetheless, even with no policy, renewables still dominate the energy mix of the future.
However, maintaining the maximum historical installation rates of both national and regional levels, with the current emissions reduction strategy, will not be enough to reach the level of climate-neutral electricity system. Therefore, national and regional installation requirements to achieve the federal government emission reduction goals are determined. Energy strategies and decision makers will have to resolve great challenges in order to stay in line with the 1.5-degree-target.
Anterior cruciate ligament (ACL) ruptures are frequent in the age group of 15–19 years, particularly for female athletes. Although injury-prevention programs effectively reduce severe knee injuries, little is known about the underlying mechanisms and changes of biomechanical risk factors. Thus, this study analyzes the effects of a neuromuscular injury-prevention program on biomechanical parameters associated with ACL injuries in elite youth female handball players. In a nonrandomized, controlled intervention study, 19 players allocated to control (n = 12) and intervention (n = 7) group were investigated for single- and double-leg landings as well as unanticipated side-cutting maneuvers before and after a 12-week study period. The lower-extremity motion of the athletes was captured using a three-dimensional motion capture system consisting of 12 infrared cameras. A lower-body marker set of 40 markers together with a rigid body model, including a forefoot, rearfoot, shank, thigh, and pelvis segment in combination with two force plates was used to determine knee joint angles, resultant external joint moments, and vertical ground reaction forces. The two groups did not differ significantly during pretesting. Only the intervention group showed significant improvements in the initial knee abduction angle during single leg landing (p = 0.038: d = 0.518), knee flexion moment during double-leg landings (p = 0.011; d = −1.086), knee abduction moment during single (p = 0.036; d = 0.585) and double-leg landing (p = 0.006; d = 0.944) and side-cutting (p = 0.015;d = 0.561) as well as vertical ground reaction force during double-leg landing (p = 0.004; d = 1.482). Control group demonstrated no significant changes in kinematics and kinetics. However, at postintervention both groups were not significantly different in any of the biomechanical outcomes except for the normalized knee flexion moment of the dominant leg during single-leg landing. This study provides first indications that the implementation of a training intervention with specific neuromuscular exercises has positive impacts on biomechanical risk factors associated with ACL injury risk and, therefore, may help prevent severe knee injuries in elite youth female handball players.
In this project, different calcification methods for collagen and collagen coatings were compared in terms of their applicability for 3D printing and production of collagen-coated scaffolds. For this purpose, scaffolds were printed from polycaprolactone PCL using the EnvisionTec 3D Bioplotter and then coated with collagen. Four different coating methods were then applied: hydroxyapatite (HA) powder directly in the collagen coating, incubation in 10× SBF, coating with alkaline phosphatase (ALP), and coating with poly-L-aspartic acid. The results were compared by ESEM, µCT, TEM, and EDX. HA directly in the collagen solution resulted in a pH change and thus an increase in viscosity, leading to clumping on the scaffolds. As a function of incubation time in 10× SBF as well as in ALP, HA layer thickness increased, while no coating on the collagen layer was apparently observed with poly-L-aspartic acid. Only ultrathin sections and TEM with SuperEDX detected nano crystalline HA in the collagen layer. Exclusively the incubation in poly-L-aspartic acid led to HA crystals within the collagen coating compared to all other methods where the HA layers formed in different forms only at the collagen layer.
In the last years, social robots have become a trending topic. Indeed, robots which communicate with us and mimic human behavior patterns are fascinating. However, while there is a massive body of research on their design and acceptance in different fields of application, their market potential has been rarely investigated. As their future integration in society may have a vast disruptive potential, this work aims at shedding light on the market potential, focusing on the assistive health domain. A study with 197 persons from Italy (age: M = 67.87; SD = 8.87) and Germany (age: M = 62.15; SD = 6.14) investigates cultural acceptance, desired functionalities, and purchase preferences. The participants filled in a questionnaire after watching a video illustrating some examples of social robots. Surprisingly, the individual perception of health status, social status as well as nationality did hardly influence the attitude towards social robots, although the German group was somewhat more reluctant to the idea of using them. Instead, there were significant correlations with most dimensions of the Almere model (like perceived enjoyment, sociability, usefulness and trustworthiness). Also, technology acceptance resulted strongly correlated with the individual readiness to invest money. However, as most persons consider social robots as “Assistive Technological Devices” (ATDs), they expected that their provision should mirror the usual practices followed in the two Countries for such devices. Thus, to facilitate social robots’ future visibility and adoption by both individuals and health care organisations, policy makers would need to start integrating them into official ATDs databases.
When people with hearing loss are provided with different devices in each ear, these devices usually have different processing latencies. This leads to static temporal offsets between both ears in the order of several milliseconds. This thesis measured effects of such offsets in stimulation timing on mechanisms of binaural hearing, such as sound localization and speech understanding in noise in hearing-impaired and normal-hearing listeners.
Nowadays decarbonisation of the energy system is one of the main concerns for most governments. Renewable energy technologies, such as rooftop photovoltaic systems and home battery storage systems, are changing the energy system to be more decentralised. As a consequence, new ways of energy business models are emerging, e.g., peer-to-peer energy trading. This new concept provides an online marketplace where direct energy exchange can occur between its participants. The purpose of this study is to conduct a content analysis of the existing literature, ongoing research projects, and companies related to peer-to-peer energy trading. From this review, a summary of the most important aspects and journal papers is assessed, discussed, and classified. It was found that the different energy market types were named in various ways and a proposal for standard language for the several peer-to-peer market types and the different actors involved is suggested. Additionally, by grouping the most important attributes from peer-to-peer energy trading projects, an assessment of the entry barrier and scalability potential is performed by using a characterisation matrix.
In the railway technical centers, scheduling the maintenance activities is a very complex task, it consists in ordering, in the time, all the maintenance operations on the workstations, while respecting the number of resources, precedence constraints, and the workstations' availabilities. Currently, this process is not completely automatic. For improving this situation, this paper presents a mathematical model for the maintenance activities scheduling in the case of railway remanufacturing systems. The studied problem is modeled as a flexible job-shop, with the possibility for a job to be executed several times on a stage. MILP formulation is implemented with the Makespan as an objective, representing the time for remanufacturing the train. The aim is to create a generic model for optimizing the planning of the maintenance activities and improving the performance of the railway technical centers. At last, numerical results are presented, discussing the impact of the instances size on the computing time to solve the described problem.
In this paper, a concept for an anthropomorphic replacement hand cast with silicone with an integrated sensory feedback system is presented. In order to construct the personalized replacement hand, a 3D scan of a healthy hand was used to create a 3D-printed mold using computer-aided design (CAD). To allow for movement of the index and middle fingers, a motorized orthosis was used. Information about the applied force for grasping and the degree of flexion of the fingers is registered using two pressure sensors and one bending sensor in each movable finger. To integrate the sensors and additional cavities for increased flexibility, the fingers were cast in three parts, separately from the rest of the hand. A silicone adhesive (Silpuran 4200) was examined to combine the individual parts afterwards. For this, tests with different geometries were carried out. Furthermore, different test series for the secure integration of the sensors were performed, including measurements of the registered information of the sensors. Based on these findings, skin-toned individual fingers and a replacement hand with integrated sensors were created. Using Silpuran 4200, it was possible to integrate the needed cavities and to place the sensors securely into the hand while retaining full flexion using a motorized orthosis. The measurements during different loadings and while grasping various objects proved that it is possible to realize such a sensory feedback system in a replacement hand. As a result, it can be stated that the cost-effective realization of a personalized, anthropomorphic replacement hand with an integrated sensory feedback system is possible using 3D scanning and 3D printing. By integrating smaller sensors, the risk of damaging the sensors through movement could be decreased.
Non-contact anterior cruciate ligament injuries typically occur during cutting maneuvers and are associated with high peak knee abduction moments (KAM) within early stance. To screen athletes for injury risk or quantify the efficacy of prevention programs, it may be necessary to design tasks that mimic game situations. Thus, this study compared KAMs and ranking consistency of female handball players in three sport-specific fake-and-cut tasks of increasing complexity. The biomechanics of female handball players (n = 51, mean ± SD: 66.9 ± 7.8 kg, 1.74 ± 0.06 m, 19.2 ± 3.4 years) were recorded with a 3D motion capture system and force plates during three standardized fake-and-cut tasks. Task 1 was designed as a simple pre-planned cut, task 2 included catching a ball before a pre-planned cut in front of a static defender, and task 3 was designed as an unanticipated cut with three dynamic defenders involved. Inverse dynamics were used to calculate peak KAM within the first 100 ms of stance. KAM was decomposed into the frontal plane knee joint moment arm and resultant ground reaction force. RANOVAs (α ≤ 0.05) were used to reveal differences in the KAM magnitudes, moment arm, and resultant ground reaction force for the three tasks. Spearman's rank correlations were calculated to test the ranking consistency of the athletes' KAMs. There was a significant task main effect on KAM (p = 0.02; ηp2 = 0.13). The KAM in the two complex tasks was significantly higher (task 2: 1.73 Nm/kg; task 3: 1.64 Nm/kg) than the KAM in the simplest task (task 1: 1.52 Nm/kg). The ranking of the peak KAM was consistent regardless of the task complexity. Comparing tasks 1 and 2, an increase in KAM resulted from an increased frontal plane moment arm. Comparing tasks 1 and 3, higher KAM in task 3 resulted from an interplay between both moment arm and the resultant ground reaction force. In contrast to previous studies, unanticipated cutting maneuvers did not produce the highest KAMs. These findings indicate that the players have developed an automated sport-specific cutting technique that is utilized in both pre-planned and unanticipated fake-and-cut tasks.
Lithium-ion batteries show strongly nonlinear behaviour regarding the battery current and state of charge. Therefore, the modelling of lithium-ion batteries is complex. Combining physical and data-driven models in a grey-box model can simplify the modelling. Our focus is on using neural networks, especially neural ordinary differential equations, for grey-box modelling of lithium-ion batteries. A simple equivalent circuit model serves as a basis for the grey-box model. Unknown parameters and dependencies are then replaced by learnable parameters and neural networks. We use experimental full-cycle data and data from pulse tests of a lithium iron phosphate cell to train the model. Finally, we test the model against two dynamic load profiles: one consisting of half cycles and one dynamic load profile representing a home-storage system. The dynamic response of the battery is well captured by the model.
As emissions reach record levels, governments must implement and strengthen climate policies for the global pathway to net‐zero emissions by 2050. Climate finance plays a crucial role in the net‐zero transition. It refers to local, national, or transnational financing seeking to support mitigation and adaptation actions that address climate change. Public export–import banks (EXIMs) and government export credit agencies (ECAs) are highly influential actors for climate action. Although there is no consensus among EXIMs and ECAs on how to define climate finance, 20 institutions assessed in this research give evidence that they strongly support climate‐action‐related transactions: EXIM and ECA financing, guarantees, and insurance amounted to EUR 6.7–8.4 billion in 2020, much more than estimated by the Climate Policy Initiative (CPI). However, the results also reveal that EXIM and ECA lending, guarantee, and insurance activities must rise substantially in order to contribute to climate finance volumes required by 2030 as estimated by CPI. To retain their current proportion relative to other climate finance flows, assessed institutions would need to increase their climate financing 6.8 times to up to EUR 57.4 billion by 2030.
Making innovation, trade, investment and environment policy goals mutually supportive creates challenges for internationally‐oriented firms, financial institutions, governments and other stakeholders. Will the Ukraine war derail the green energy transition? How can governments and the financial system work together to broaden, deepen, and accelerate the global transition to net‐zero? What are innovation, trade and investment opportunities for green growth? How to refocus government financing instruments to support countries and trade partners meet their climate targets in times of crisis? The IfTI Global Symposium 2022 hosted by the Institute of Trade and Innovation (IfTI) at Offenburg University discussed challenges to trade in a new global order, as well as opportunities and threats of the green transition. This Special Section brings together practitioner commentaries of key symposium speakers.
The laser ultrasound (LU) technique has been used to determine dispersion curves for surface acoustic waves (SAW) propagating in AlScN/Al2O3 systems. Polar and non-polar Al0.77Sc0.23N thin films were prepared by magnetron sputter epitaxy on Al2O3 substrates and coated with a metal layer. SAW dispersion curves have been measured for various propagation directions on the surface. This is easily achieved in LU measurements since no additional surface structures need to be fabricated, which would be required if elastic properties are determined with the help of SAW resonators. Variation of the propagation direction allows for efficient use of the system’s anisotropy when extracting information on elastic properties. This helps to overcome the complexity caused by a large number of elastic constants in the film material. An analysis of the sensitivity of the SAW phase velocities (with respect to the elastic moduli and their dependence on SAW propagation direction) reveals that the non-polar AlScN films are particularly well suited for the extraction of elastic film properties. Good agreement is found between experiment and theoretical predictions, validating LU as a non-destructive and fast technique for the determination of elastic constants of piezoelectric thin films.
Ziel des Beitrages ist es, die geschäftspolitischen Entscheidungen der Reedereien in dem extrem volatilen Umfeld einer Pandemie, geprägt von regulatorischen und operativen Schwierigkeiten, zu analysieren, um anschließend nachzuvollziehen, wie die gesamte Branche der Containerlinienreedereien einen derartigen Aufschwung erreichen konnte. Dabei wird eruiert, ob die Sonderprivilegien der Reedereien, wie der jüngst verlängerten Gruppenfreistellung für Konsortien und die hohen Subventionen, unter den aktuellen Bedingungen noch Rechtfertigung finden können.
Hiervon losgelöst wird zudem analysiert, wie die einst florierende Branche der Kreuzfahrtreedereien mit den pandemiebedingten Herausforderungen, wie den ausbleibenden Buchungen, notwendigen Routenänderungen und Rücktrittswellen, umgegangen ist.
Positioning mobile systems with high accuracy is a prerequisite for intelligent autonomous behavior, both in industrial environments and in field robotics. This paper describes the setup of a robotic platform and its use for the evaluation of simultaneous localization and mapping (SLAM) algorithms. A configuration using a mobile robot Husky A200, and a LiDAR (light detection and ranging) sensor was used to implement the setup. For verification of the proposed setup, different scan matching methods for odometry determination in indoor and outdoor environments are tested. An assessment of the accuracy of the baseline 3D-SLAM system and the selected evaluation system is presented by comparing different scenarios and test situations. It was shown that the hdl_graph_slam in combination with the LiDAR OS1 and the scan matching algorithms FAST_GICP and FAST_VGICP achieves good mapping results with accuracies up to 2 cm.
Young female handball players represent a high-risk population for anterior cruciate ligament (ACL) injuries. While the external knee abduction moment (KAM) is known to be a risk factor, it is unclear how cutting technique affects KAMs in sport-specific cutting maneuvers. Further, the effect of added game specificity (e.g., catching a ball or faking defenders) on KAMs and cutting technique remains unknown. Therefore, this study aimed: (i) to test if athletes grouped into different clusters of peak KAMs produced during three sport-specific fake-and-cut tasks of different complexities differ in cutting technique, and (ii) to test whether technique variables change with task complexity. Fifty-one female handball players (67.0 ± 7.7 kg, 1.70 ± 0.06 m, 19.2 ± 3.4 years) were recruited. Athletes performed at least five successful handball-specific sidestep cuts of three different complexities ranging from simple pre-planned fake-and-cut maneuvers to catching a ball and performing an unanticipated fake-and-cut maneuver with dynamic defenders. A k-means cluster algorithm with squared Euclidean distance metric was applied to the KAMs of all three tasks. The optimal cluster number of koptimal = 2 was calculated using the average silhouette width. Statistical differences in technique variables between the two clusters and the tasks were analyzed using repeated-measures ANOVAs (task complexity) with nested groupings (clusters). KAMs differed by 64.5%, on average, between clusters. When pooling all tasks, athletes with high KAMs showed 3.4° more knee valgus, 16.9% higher downward and 8.4% higher resultant velocity at initial ground contact, and 20.5% higher vertical ground reaction forces at peak KAM. Unlike most other variables, knee valgus angle was not affected by task complexity, likely due to it being part of inherent movement strategies and partly determined by anatomy. Since the high KAM cluster showed higher vertical center of mass excursions and knee valgus angles in all tasks, it is likely that this is part of an automated motor program developed over the players' careers. Based on these results, reducing knee valgus and downward velocity bears the potential to mitigate knee joint loading and therefore ACL injury risk.
In dem ersten Teil dieses Beitrags, welcher in der Industrie 4.0 Management Ausgabe 5/2021 erschienen ist, wurde das Referenzmodell bereits in seinen wesentlichen Grundzügen erläutert [1]. Im zweiten Teil soll die Weiterentwicklung zu einem flexiblen Referenzmodell aufgezeigt werden. Der Fokus liegt auf die Implementierung von weiteren Planungstools, und die Implementierung von KI-Tools zur Erreichung eines dynamischen Produktionsengineerings in Form einer ganzheitlichen und integrierten Fabrikplanung.
An Overview of Technologies for Improving Storage Efficiency in Blockchain-Based IIoT Applications
(2022)
Since the inception of blockchain-based cryptocurrencies, researchers have been fascinated with the idea of integrating blockchain technology into other fields, such as health and manufacturing. Despite the benefits of blockchain, which include immutability, transparency, and traceability, certain issues that limit its integration with IIoT still linger. One of these prominent problems is the storage inefficiency of the blockchain. Due to the append-only nature of the blockchain, the growth of the blockchain ledger inevitably leads to high storage requirements for blockchain peers. This poses a challenge for its integration with the IIoT, where high volumes of data are generated at a relatively faster rate than in applications such as financial systems. Therefore, there is a need for blockchain architectures that deal effectively with the rapid growth of the blockchain ledger. This paper discusses the problem of storage inefficiency in existing blockchain systems, how this affects their scalability, and the challenges that this poses to their integration with IIoT. This paper explores existing solutions for improving the storage efficiency of blockchain–IIoT systems, classifying these proposed solutions according to their approaches and providing insight into their effectiveness through a detailed comparative analysis and examination of their long-term sustainability. Potential directions for future research on the enhancement of storage efficiency in blockchain–IIoT systems are also discussed.
Biomechanical Risk Factors of Injury-Related Single-Leg Movements in Male Elite Youth Soccer Players
(2022)
Altered movement patterns during single-leg movements in soccer increase the risk of lower-extremity non-contact injuries. The identification of biomechanical parameters associated with lower-extremity injuries can enrich knowledge of injury risks and facilitate injury prevention. Fifty-six elite youth soccer players performed a single-leg drop landing task and an unanticipated side-step cutting task. Three-dimensional ankle, knee and hip kinematic and kinetic data were obtained, and non-contact lower-extremity injuries were documented throughout the season. Risk profiling was assessed using a multivariate approach utilising a decision tree model (classification and regression tree method). The decision tree model indicated peak knee frontal plane angle, peak vertical ground reaction force, ankle frontal plane moment and knee transverse plane angle at initial contact (in this hierarchical order) for the single-leg landing task as important biomechanical parameters to discriminate between injured and non-injured players. Hip sagittal plane angle at initial contact, peak ankle transverse plane angle and hip sagittal plane moment (in this hierarchical order) were indicated as risk factors for the unanticipated cutting task. Ankle, knee and hip kinematics, as well as ankle and hip kinetics, during single-leg high-risk movements can provide a good indication of injury risk in elite youth soccer players.
Note: In lieu of an abstract, this is an excerpt from the first page.
Recently, we reported the three-dimensional computer-aided design (3D-CAD) reconstruction of the first “Iron Hand” of the famous Franconian knight, Götz von Berlichingen (1480–1562), who lost his right hand by a cannon ball splinter injury in 1504 in the War of the Succession of Landshut [...]
Simulation based studies for operational energy system analysis play a significant role in evaluation of various new age technologies and concepts in the energy grid. Various modelling approaches already exist and in this original paper, four models representing these approaches are compared in two real-world hybrid energy system scenarios. The models, namely TransiEnt, µGRiDS, and OpSim (including pandaprosumer and mosaic) are classified into component-oriented or system-oriented approaches as deduced from the literature research. The methodology section describes their differences under standard conditions and the necessary parameterization for the purpose of creating a framework facilitating a closest possible comparison. A novel methodology for scenario generation is also explained. The results help to quantify primary differences in these approaches that are also identified in literature and qualify the influence of the accuracy of the models for application in a system-wide analysis. It is shown that a simplified model may be sufficient for the system-oriented approach especially when the objective is an optimization-based control or planning. However, from a field level operational point of view, the differences in the time series signify the importance of the component-oriented approaches.
A novel method for quasi-continuous tar monitoring in hot syngas from biomass gasification is reported. A very small syngas stream is extracted from the gasifier output, and the oxygen demand for tar combustion is determined by a well-defined dosage of synthetic air. Assuming the total oxidation of all of the combustible components at the Pt-electrode of a lambda-probe, the difference of the residual oxygen concentrations from successive operations with and without tar condensation represents the oxygen demand. From experiments in the laboratory with H2/N2/naphthalene model syngas, the linear sensitivity and a lower detection limit of about 70 ± 5 mg/m3 was estimated, and a very good long-term stability can be expected. This extremely sensitive and robust monitoring concept was evaluated further by the extraction of a small, constant flow of hot syngas as a sample (9 L/h) using a Laval nozzle combined with a metallic filter (a sintered metal plate (pore diameter 10 µm)) and a gas pump (in the cold zone). The first tests in the laboratory of this setup—which is appropriate for field applications—confirmed the excellent analysis results. However, the field tests concerning the monitoring of the tar in syngas from a woodchip-fueled gasifier demonstrated that the determination of the oxygen demand by the successive estimation of the oxygen concentration with/without tar trapping is not possible with enough accuracy due to continuous variation of the syngas composition. A method is proposed for how this constraint can be overcome.
Forschung im Fokus 2022
(2022)
In asymmetric treatment of hearing loss, processing latencies of the modalities typically differ. This often alters the reference interaural time difference (ITD) (i.e., the ITD at 0° azimuth) by several milliseconds. Such changes in reference ITD have shown to influence sound source localization in bimodal listeners provided with a hearing aid (HA) in one and a cochlear implant (CI) in the contralateral ear. In this study, the effect of changes in reference ITD on speech understanding, especially spatial release from masking (SRM) in normal-hearing subjects was explored. Speech reception thresholds (SRT) were measured in ten normal-hearing subjects for reference ITDs of 0, 1.75, 3.5, 5.25 and 7 ms with spatially collocated (S0N0) and spatially separated (S0N90) sound sources. Further, the cues for separation of target and masker were manipulated to measure the effect of a reference ITD on unmasking by A) ITDs and interaural level differences (ILDs), B) ITDs only and C) ILDs only. A blind equalization-cancellation (EC) model was applied to simulate all measured conditions. SRM decreased significantly in conditions A) and B) when the reference ITD was increased: In condition A) from 8.8 dB SNR on average at 0 ms reference ITD to 4.6 dB at 7 ms, in condition B) from 5.5 dB to 1.1 dB. In condition C) no significant effect was found. These results were accurately predicted by the applied EC-model. The outcomes show that interaural processing latency differences should be considered in asymmetric treatment of hearing loss.
The increase of the Internet of Things (IoT) calls for secure solutions for industrial applications. The security of IoT can be potentially improved by blockchain. However, blockchain technology suffers scalability issues which hinders integration with IoT. Solutions to blockchain’s scalability issues, such as minimizing the computational complexity of consensus algorithms or blockchain storage requirements, have received attention. However, to realize the full potential of blockchain in IoT, the inefficiencies of its inter-peer communication must also be addressed. For example, blockchain uses a flooding technique to share blocks, resulting in duplicates and inefficient bandwidth usage. Moreover, blockchain peers use a random neighbor selection (RNS) technique to decide on other peers with whom to exchange blockchain data. As a result, the peer-to-peer (P2P) topology formation limits the effective achievable throughput. This paper provides a survey on the state-of-the-art network structures and communication mechanisms used in blockchain and establishes the need for network-based optimization. Additionally, it discusses the blockchain architecture and its layers categorizes existing literature into the layers and provides a survey on the state-of-the-art optimization frameworks, analyzing their effectiveness and ability to scale. Finally, this paper presents recommendations for future work.
The present essay discusses several channels of social policy on climate mitigation and utilizes the Universal Basic Income (UBI) scheme as an example for endowment increasing and inclusive social policy instruments. UBI comprises the payment of a fixed amount of money to every member of a society from birth to death and is not bounded to any precondition. It is expected to increase resilience of individuals against disruptive and unexpected processes, such as climate change, digitization, aging population and the changing world of work, rather than particular life-trajectories. UBI is found to be a social policy instrument whose effects can contribute to climate mitigation. This essay is far from being conclusive and rather aims to raise questions which require further analysis.
The significant market growth of stationary electrical energy storage systems both for private and commercial applications has raised the question of battery lifetime under practical operation conditions. Here, we present a study of two 8 kWh lithium-ion battery (LIB) systems, each equipped with 14 lithium iron phosphate/graphite (LFP) single cells in different cell configurations. One system was based on a standard configuration with cells connected in series, including a cell-balancing system and a 48 V inverter. The other system featured a novel configuration of two stacks with a parallel connection of seven cells each, no cell-balancing system, and a 4 V inverter. The two systems were operated as part of a microgrid both in continuous cycling mode between 30% and 100% state of charge, and in solar-storage mode with day–night cycling. The aging characteristics in terms of capacity loss and internal resistance change in the cells were determined by disassembling the systems for regular checkups and characterizing the individual cells under well-defined laboratory conditions. As a main result, the two systems showed cell-averaged capacity losses of 18.6% and 21.4% for the serial and parallel configurations, respectively, after 2.5 years of operation with 810 (serial operation) and 881 (parallel operation) cumulated equivalent full cycles. This is significantly higher than the aging of a reference single cell cycled under laboratory conditions at 20 °C, which showed a capacity loss of only 10% after 1000 continuous full cycles.
To achieve its climate goals, the German industry has to undergo a transformation toward renewable energies. To analyze this transformation in energy system models, the industry’s electricity demands have to be provided in a high temporal and sectoral resolution, which, to date, is not the case due to a lack of open-source data. In this paper, a methodology for the generation of synthetic electricity load profiles is described; it was applied to 11 industry types. The modeling was based on the normalized daily load profiles for eight electrical end-use applications. The profiles were then further refined by using the mechanical processes of different branches. Finally, a fluctuation was applied to the profiles as a stochastic attribute. A quantitative RMSE comparison between real and synthetic load profiles showed that the developed method is especially accurate for the representation of loads from three-shift industrial plants. A procedure of how to apply the synthetic load profiles to a regional distribution of the industry sector completes the methodology.
The lifetime of a battery is affected by various aging processes happening at the electrode scale and causing capacity and power fade over time. Two of the most critical mechanisms are the deposition of metallic lithium (plating) and the loss of lithium inventory to the solid electrolyte interphase (SEI). These side reactions compete with reversible lithium intercalation at the graphite anode. Here we present a comprehensive physicochemical pseudo-3D aging model for a lithium-ion battery cell, which includes electrochemical reactions for SEI formation on graphite anode, lithium plating, and SEI formation on plated lithium. The thermodynamics of the aging reactions are modeled depending on temperature and ion concentration, and the reactions kinetics are described with an Arrhenius-type rate law. The model includes also the positive feedback of plating on SEI growth, with the presence of plated lithium leading to a higher SEI formation rate compared to the values obtained in its absence at the same operating conditions. The model is thus able to describe cell aging over a wide range of temperatures and C-rates. In particular, it allows to quantify capacity loss due to cycling (here in % per year) as function of operating conditions. This allows the visualization of aging colormaps as function of both temperature and C-rate and the identification of critical operation conditions, a fundamental step for a comprehensive understanding of batteries performance and behavior. For example, the model predicts that at the harshest conditions (< –5 °C, > 3 C), aging is reduced compared to most critical conditions (around 0–5 °C) because the cell cannot be fully charged.
Industrial companies can use blockchain to assist them in resolving their trust and security issues. In this research, we provide a fully distributed blockchain-based architecture for industrial IoT, relying on trust management and reputation to enhance nodes’ trustworthiness. The purpose of this contribution is to introduce our system architecture to show how to secure network access for users with dynamic authorization management. All decisions in the system are made by trustful nodes’ consensus and are fully distributed. The remarkable feature of this system architecture is that the influence of the nodes’ power is lowered depending on their Proof of Work (PoW) and Proof of Stake (PoS), and the nodes’ significance and authority is determined by their behavior in the network.
This impact is based on game theory and an incentive mechanism for reputation between nodes. This system design can be used on legacy machines, which means that security and distributed systems
can be put in place at a low cost on industrial systems. While there are no numerical results yet, this work, based on the open questions regarding the majority problem and the proposed solutions based on a game-theoretic mechanism and a trust management system, points to what and how industrial IoT and existing blockchain frameworks that are focusing only on the power of PoW and PoS can be secured more effectively.
The use of biochar is an important tool to improve soil fertility, reduce the negative environmental impacts of agriculture, and build up terrestrial carbon sinks. However, crop yield increases by biochar amendment were not shown consistently for fertile soils under temperate climate. Recent studies show that biochar is more likely to increase crop yields when applied in combination with nutrients to prepare biochar-based fertilizers. Here, we focused on the root-zone amendment of biochar combined with mineral fertilizers in a greenhouse trial with white cabbage (Brassica oleracea convar. Capitata var. Alba) cultivated in a nutrient-rich silt loam soil originating from the temperate climate zone (Bavaria, Germany). Biochar was applied at a low dosage (1.3 t ha−1). The biochar was placed either as a concentrated hotspot below the seedling or it was mixed into the soil in the root zone representing a mixture of biochar and soil in the planting basin. The nitrogen fertilizer (ammonium nitrate or urea) was either applied on the soil surface or loaded onto the biochar representing a nitrogen-enhanced biochar. On average, a 12% yield increase in dry cabbage heads was achieved with biochar plus fertilizer compared to the fertilized control without biochar. Most consistent positive yield responses were observed with a hotspot root-zone application of nitrogen-enhanced biochar, showing a maximum 21% dry cabbage-head yield increase. Belowground biomass and root-architecture suggested a decrease in the fine root content in these treatments compared to treatments without biochar and with soil-mixed biochar. We conclude that the hotspot amendment of a nitrogen-enhanced biochar in the root zone can optimize the growth of white cabbage by providing a nutrient depot in close proximity to the plant, enabling efficient nutrient supply. The amendment of low doses in the root zone of annual crops could become an economically interesting application option for biochar in the temperate climate zone.
Introduction The use of scaffolds in tissue engineering is becoming increasingly important as solutions need to be found for the problem of preserving human tissue, such as bone or cartilage. In this work, scaffolds were printed from the biomaterial known as polycaprolactone (PCL) on a 3D Bioplotter. Both the external and internal geometry were varied to investigate their influence on mechanical stability and biocompatibility. Materials and Methods: An Envisiontec 3D Bioplotter was used to fabricate the scaffolds. First, square scaffolds were printed with variations in the strand width and strand spacing. Then, the filling structure was varied: either lines, waves, and honeycombs were used. This was followed by variation in the outer shape, produced as either a square, hexagon, octagon, or circle. Finally, the internal and external geometry was varied. To improve interaction with the cells, the printed PCL scaffolds were coated with type-I collagen. MG-63 cells were then cultured on the scaffolds and various tests were performed to investigate the biocompatibility of the scaffolds. Results: With increasing strand thickness and strand spacing, the compressive strengths decreased from 86.18 + 2.34 MPa (200 µm) to 46.38 + 0.52 MPa (600 µm). The circle was the outer shape with the highest compressive strength of 76.07 + 1.49 MPa, compared to the octagon, which had the lowest value of 52.96 ± 0.98 MPa. Varying the external shape (toward roundness) geometry, as well as the filling configuration, resulted in the highest values of compressive strength for the round specimens with honeycomb filling, which had a value of 91.4 + 1.4 MPa. In the biocompatibility tests, the round specimens with honeycomb filling also showed the highest cell count per mm2, with 1591 ± 239 live cells/mm2 after 10 days and the highest value in cell proliferation, but with minimal cytotoxic effects (9.19 ± 2.47% after 3 days).
Lithium-ion batteries exhibit a dynamic voltage behaviour depending nonlinearly on current and state of charge. The modelling of lithium-ion batteries is therefore complicated and model parametrisation is often time demanding. Grey-box models combine physical and data-driven modelling to benefit from their respective advantages. Neural ordinary differential equations (NODEs) offer new possibilities for grey-box modelling. Differential equations given by physical laws and NODEs can be combined in a single modelling framework. Here we demonstrate the use of NODEs for grey-box modelling of lithium-ion batteries. A simple equivalent circuit model serves as a basis and represents the physical part of the model. The voltage drop over the resistor–capacitor circuit, including its dependency on current and state of charge, is implemented as a NODE. After training, the grey-box model shows good agreement with experimental full-cycle data and pulse tests on a lithium iron phosphate cell. We test the model against two dynamic load profiles: one consisting of half cycles and one dynamic load profile representing a home-storage system. The dynamic response of the battery is well captured by the model.
Electrochemical pressure impedance spectroscopy (EPIS) has recently been developed as a potential diagnosis tool for polymer electrolyte membrane fuel cells (PEMFC). It is based on analyzing the frequency response of the cell voltage with respect to an excitation of the gas-phase pressure. We present here a combined modeling and experimental study of EPIS. A pseudo-twodimensional PEMFC model was parameterized to a 100 cm2 laboratory cell installed in its test bench, and used to reproduce steady-state cell polarization and electrochemical impedance spectra (EIS). Pressure impedance spectra were obtained both in experiment and simulation by applying a harmonic pressure excitation at the cathode outlet. The model shows good agreement with experimental data for current densities ⩽ 0.4 A cm−2. Here it allows a further simulative analysis of observed EPIS features, including the magnitude and shape of spectra. Key findings include a strong influence of the humidifier gas volume on EPIS and a substantial increase in oxygen partial pressure oscillations towards the channel outlet at the resonance frequency. At current densities ⩾ 0.8 A cm−2 the experimental EIS and EPIS data cannot be fully reproduced. This deviation might be associated with the formation and transport of liquid water, which is not included in the model.
In pandemic times, the possibilities for conventional sports activities are severely limited; many sports facilities are closed or can only be used with restrictions. To counteract this lack of health activities and social exchange, people are increasingly adopting new digital sports solutions—a behavior change that had already started with the trend towards fitness apps and activity trackers. Existing research suggests that digital solutions increase the motivation to move and stay active. This work further investigates the potentials of digital sports incorporating the dimensions gender and preference for team sports versus individual sports. The study focuses on potential users, who were mostly younger professionals and academics. The results show that the SARS-CoV-19 pandemic had a significant negative impact on sports activity, particularly on persons preferring team sports. To compensate, most participants use more digital sports than before, and there is a positive correlation between the time spent physically active during the pandemic and the increase in motivation through digital sports. Nevertheless, there is still considerable skepticism regarding the potential of digital sports solutions to increase the motivation to do sports, increase performance, or raise a sense of team spirit when done in groups.
Dieses Arbeitspapier behandelt den aktuellen Markt von Legal-Tech-Diensten in Deutschland und die rechtlichen Entwicklungen bezüglich der dort bestehenden Law-Tech-Branche. Ziel ist es dabei, anhand einer systematischen Analyse der beteiligten Marktkräfte, die Attraktivität der Legal-Tech-Branche einzuschätzen, um dem Leser dadurch eine Hilfestellung für die Strategiebildung innerhalb Law-Tech bezogener Unternehmen sowie Kanzleien zu bieten, denn die strategische Planung eines Unternehmens ist als Basis für den nachhaltigen Erfolg desselben unabdinglich.
Darüber hinaus zielt die Arbeit darauf ab, dem Leser einen Überblick über die rechtlichen Entwicklungen im Bereich von Legal-Tech sowie damit einhergehend ein Basiswissen über die Hintergründe der Gesetzgebung in Bezug auf die Law-Tech-Branche zu verschaffen.
Gegenstand dieser Arbeit wird die Frage sein, inwiefern es sich bei User-generated Content um eine sinnvolle Ergänzung für die Kommunikationspolitik von Marken handelt. Zudem soll umrissen werden, auf welche Art und Weise er sich bestmöglich in der Marketingkommunikation einsetzen lässt. Ein besonderes Augenmerk wird dabei der UGC-Kommunikation gewidmet werden, die Unternehmen auf ihren markeneigenen Kanälen betreiben. Da es sich hierbei um ein noch relativ junges, spezifisches und im wissenschaftlichen Diskurs nur wenig untersuchtes Themengebiet handelt, sollen strategische Hintergründe und Zielsetzungen beleuchtet werden, die Unternehmen und Marken dazu bewegen, User-generated Content zu fördern und auf eigenen Kanälen auszuspielen.