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In 2015, the United Nations General Assembly proposed seventeen Sustainable Development Goals (SDGs) intended to ensure sustainable development worldwide at the economic, environmental, and social levels. SDGs are now being used by some corporations in formulating and expressing business strategies. However, assessing the effects of corporate activities and products regarding their contribution to SDGs is difficult. In this paper, we have developed a method for linking life cycle sustainability assessment (LCSA) with the SDGs and calculating the contribution to SDG achievement. An essential part of this approach is the weighting of LCSA impact categories, which is typically done using equal weighting. This weighting method enables compensation of negative contributions by positive contributions in different impact categories but results in ambiguity in the results. This article identifies alternative weighting methods, integrates them into a computational approach, and determines their influence on the SDG contribution scores. The analysis shows that the use of alternative weights changes SDG contribution scores. However, the same product always has the highest SDG contribution score, regardless of the weighting method used. Nonetheless, the recommendations for action with regard to the total product alternatives would change depending on the weighting method., Deutsche Forschungsgemeinschaft (DFG)

Viele Klimaabkommen, einschließlich des Pariser Abkommens und der Europäischen Union 2020, betonen die Wichtigkeit der Verbesserung der Energieeffizienz von Gebäuden als kritische Maßnahme zur Begrenzung der globalen Erwärmung; dadurch steigt die Notwendigkeit, energieeffiziente und niedrig-kohlenstoffhaltige Lösungen für Gebäude und Bau [1], [2] zu entwickeln. Biopolymere Aerogel stellen innovative Dämmstoffe aufgrund ihrer besonderen Eigenschaften wie geringer Dichte, hoher Oberflächenfläche und einer sehr geringen Wärmeleitfähigkeit (z.B. 0,017 W.m-1.K-1) [3] dar. Einige Faktoren verzögern jedoch ihre Nutzung in industriellen Anwendungen wie hoher Preis, Empfindlichkeit gegenüber Feuchtigkeit, geringe mechanische Stabilität (in einigen Fällen) und Herausforderungen im Zusammenhang mit der Skalierung [4]. Lignin repräsentiert ein erneuerbares Biopolymer, wenn es bei der Herstellung von Aerogelen verwendet wird, führte dies zu einem mechanisch stabilen Biopolym Aerogel mit höherer Hydrophobizität und somit geringerer Feuchtigkeitsempfindlichkeit [5]. Ziel dieser Studie ist es daher, das Potenzial von Lignin als Zusatzstoff in Alginat-Aerogelen zu evaluieren, um die für die Anwendung relevanten Eigenschaften zu verbessern. In dieser Studie wurden Lignin-Mikropartikel mit wasserhaltigen Alginat-Lösungen gemischt und Hydrogel-Partikel wurden mittels Tropfmethode in Calciumchlorid-Lösung produziert, um die Ionengelierung des Alginats zu fördern. Anschließend wurden die CO2-überkritisch getrockneten Alginat-Lignin-Hybrid-Aerogel-Partikel mit Cellulosefasern gemischt und mittels Blow-in-Technik in hohle Holzrahmen geblasen. Die Aerogel-Partikel wurden hinsichtlich ihrer Teilchenmorphologie und porösen Struktur bewertet, während die Aerogel-Cellulosefaser-Mischungen hinsichtlich Homogenität und Wärmeleitfähigkeit bewertet wurden. Die vorläufigen Ergebnisse zeigten, dass Alginat-Lignin-Hybrid-Aerogel stabil genug sind, um als Rohmaterial für die Blow-in-Dämmung verwendet z, Many climate change agreements including paris agreement and european union 2020 emphasized the importance of improving energy efficiency of buildings as a critical measure to limit global warming; thus increasing the need to develop energy-efficient and low-carbon solutions for buildings and construction [1], [2]. Biopolymer aerogels represent innovative insulation materials due to their distinctive properties such as low density, high surface area and a very low thermal conductivity (e.g. 0.017 W.m-1.K-1) [3]. However, some factors delay their utilization into industrial applications such as high price, sensitivity to moisture, low mechanical stability (in some cases) and challenges associated with scale up [4]. Lignin represents a renewable biopolymer when incorporating with aerogels led to a mechanically stable biopolymer aerogel with higher hydrophobicity consequently less sensitivity to moisture [5]. Aim of this study is therefore to evaluate the potential of lignin as additive in alginate aerogels in order to enhance application relevant properties. In this study, lignin microparticles were mixed with aqueous alginate solutions and hydrogel particles were produced via dripping method in calcium chloride solution to facilitate ion induced gelation of alginate. Thereafter, the CO2 supercritical dried alginate-lignin hybrid aerogel particles were mixed with cellulose fibers and then blown into hollow wood frames using blow in technique. Aerogel particles were evaluated in terms of particle morphology and porous structure, while the aerogel cellulose fiber mixtures were evaluated in terms of homogeneity and thermal conductivity. The preliminary results showed that alginate-lignin hybrid aerogels are sufficiently stable thus suitable to be used as a raw material for blow in insulation. Replacement of cellulose fibers by lignin aerogel particles up to 32 wt% decreased the thermal conductivity by 9% and a lower thermal conductivity of 34.09 W.m-1.K-1 was achieved. T

Biopolymer aerogels are nanoporous lightweight materials with high surface area and very low density (0.15 g/cm3). The properties made them well desired in diverse applications such as insulation, catalysts, and drug delivery systems. However, one main drawback of the biopolymer aerogels is their hydrophilic surface and the open pore structure of aerogels which permits the penetration of moisture or reactive molecules into the inner part of the materials and may cause damage of the pores. The conventional approaches comprise of a subsequent modification step either by: (1) a hydrophobic post-modification of aerogel inner surfaces, or (2) an application of a protective coating to the aerogel outer surfaces. This research work investigates an alternative solution which introduces the possibility of one-step simultaneous gelation and coating of alginate aerogels using lignin as the coating material. In this study, lignin particles are mixed with the alginate solution subsequently the lignin alginate hydrogel particles are produced via dripping method in calcium chloride solution to facilitate ions-induced gelation. Thereafter, aerogel particles are evaluated in terms of particle morphology and porous structure, While the coating layer is evaluated in term of homogeneity and thickness. The preliminary results showed the formation of porous lignin layer as an outer shell of alginate aerogel particles as validated by SEM images, the addition of lignin up to 50% wt dry mass basis did not negatively influence the porous structure (Sv up to 350 m2/g). The targeted application for the developed lignin coated alginate aerogel particles is as thermal insulation material for building elements using blow in technique.

A systematic approach is presented to achieve the stable grasping of objects through a two-finger robotic hand, in which each finger cavity was filled with granular media. The compaction of the latter, controlled by vacuum pressure, was used to adjust the structural and contact stiffness of the finger. The grasping stability was studied under the concurrent effect of an external torque and applied vacuum pressure. Stable grasping was defined as the no slippage condition between the grasped object and the two fingers. Three control schemes were adopted and applied experimentally to ensure the effectiveness of the grasping process. The results showed that stable and unstable grasping regions exist for each combination of applied torque and vacuum pressure. The two-finger robotic hands can be further improved for applications that require high load-carrying capabilities., A systematic approach is presented to achieve the stable grasping of objects through a two-finger robotic hand, in which each finger cavity was filled with granular media. The compaction of the latter, controlled by vacuum pressure, was used to adjust the structural and contact stiffness of the finger. The grasping stability was studied under the concurrent effect of an external torque and applied vacuum pressure. Stable grasping was defined as the no slippage condition between the grasped object and the two fingers. Three control schemes were adopted and applied experimentally to ensure the effectiveness of the grasping process. The results showed that stable and unstable grasping regions exist for each combination of applied torque and vacuum pressure. The two-finger robotic hands can be further improved for applications that require high load-carrying capabilities.

Spectrum scarcity is viewed as one of the key obstacles in the area of wireless communications. The lack of available unlicensed resources is impairing the development of newer and more modern communications systems. This is the case of L-band Digital Aeronautical Communications System (LDACS), an innovative air communication system that aims to use the part of the frequency spectrum licensed by Distance Measuring Equipment (DME), a legacy radio navigation system. DME has a low channel utilization rate, leaving idle numerous resources that could be used by LDACS through the use of Dynamic Spectrum Access (DSA) in Cognitive Radio (CR). In order to avoid interferences and collisions while taking advantage of these idle resources, this thesis proposes a new LDACS Machine Learning (ML)-based Medium Access Control (MAC). It incorporates a Long Short Term Memory (LSTM) Recurrent Neural Network (RNN) in order to observe, learn, predict and avoid the DME licensed users. The results from this new MAC are analyzed and compared to two alternative approaches, showing the advantages of a ML-based approach.

Objective. In radiation oncology, experiments are often carried out using mice as a model for in vivo research studies. Due to recent technological advances in the development of high-precision small-animal irradiation facilities, the importance of quality assurance for both dosimetry and imaging is increasing. Additive manufacturing (AM) offers the possibility to produce complex models from a three-dimensional data set and to build cost-effective phantoms that can easily be adapted to different purposes. The aim of this work was therefore to develop detailed anatomical mouse models for quality assurance and end-to-end testing of small-animal irradiation and imaging by means of AM. Approach. Two mouse phantom concepts were designed, constructed, and examined for this purpose. The first model includes cavities corresponding to the most important organs. The final solid model was constructed using AM in two separate parts that can be attached with a plug connection after filling these cavities with tissue-equivalent mixtures. Moreover, different radiation dosimeters can be placed in the lower part of the model. For the second concept, AM was used for building modules like the phantom outer shell and bones, so that different mixtures can be used as a filling, without modifying the phantom structure. Main results. CT as well as Micro-CT scans of both concepts showed an excellent quality and adequate image contrast, with material attenuation properties close to those of mouse tissues, apart from the current bone surrogates. Radiation dose measurements with radiochromic films were, with some exceptions in areas with larges bone volumes, in agreement with calculations within less than ±4%. Significance. AM shows great potential for the development of mouse models that are inexpensive, easy to adapt, and accurate, thus enabling their use for quality assurance in small-animal radiotherapy and imaging. The introduction of such 3D-printable mouse phantoms in the workflow could, Behörde für Wissenschaft, Forschung und Gleichstellung

In Magnetic Particle Imaging, the spatial distribution of a tracer is measured and depicted with a concentration dependent signal intensity for any location that contains particles, whereas surrounding tissue does not provide any signal. After tracer injection, the signal over time (positive contrast) can be utilized as a transient response to calculate dynamic diagnostic parameters like perfusion parameter maps. In this work, a bolus of physiological saline solution without any particles (negative contrast) is proposed, where the remaining steady state concentration contributes to the image contrast. This opens up the possibility to stretch the total monitoring time of a patient by utilizing a positive-negative contrast sequence, while keeping the total iron dose constant in the subject. Resulting time responses show that normalized signals from positive and negative boli are concurrent in the phantom experiments, indicating identical diagnostic parameters for in-vivo use.

In recent works, arbitrary waveform or pulsed excitation in Magnetic Particle Imaging (MPI) was proposed to offer better resolution and sensitivity. Generating these excitation fields poses a new challenge in MPI hardware design. This work proposes a method which models the excitation chain as a linear system and predicts the required input voltage for the desired output field. The initial prediction is then iteratively improved to compensate for inaccuracies of the model. The method is demonstrated to achieve accurate field waveforms in both linear and slew rate limited regions of the amplifier.

The model-based reconstruction problem is still one of the key challenges in magnetic particle imaging (MPI) when using multi-dimensional Lissajous-type excitations. One aspect, which is often highlighted in the literature, is the magnetization behavior of the magnetic nanoparticles in fluids. Another aspect, which is at least as important as the particle model itself but sometimes treated less prominently, is a very careful calibration of the model input, respectively the scanner parameters such as analog filter and applied magnetic fields. The careful consideration of both aspects is the essential requirement for a proper solution to the model-based problem. In the present work we combine previously calibrated scanner components with mono-and polydisperse particle models for immobilized nanoparticles to derive a model-based system function and an calibration routine exploiting applied magnetic field generalizability. It is experimentally validated on the Bruker preclinical MPI system using 2D Lissajous trajectories., Deutsche Forschungsgemeinschaft (DFG)

Micromagnetic fluids are at the core of magnetic particle imaging as underlying tracer materials. They are formed when magnetic nanoparticles are suspended in a fluid such as blood, cytoplasm or water. One of the fundamental assumptions made in current MPI models is that the micromagnetic response of nanoparticles and the dynamics of the fluid transporting them are decoupled. In this contribution, we use a simplified micromagnetic model that takes this interaction into account to investigate scenarios where this assumption breaks down., Deutsche Forschungsgemeinschaft (DFG)

Diese Dissertation untersucht Techniken für adaptive Multi-Hop Netzwerke im IIoT im Hinblick auf zeitlich variierenden Datenverkehr. Sie zeigt, dass eine effiziente Übertragung von Managementverkehr entscheidend für eine hohe Anpassungsfähigkeit in IEEE 802.15.4 DSME ist, entwickelt Techniken zur Erhöhung der Anpassungsfähigkeit und validiert diese durch Simulationen, Hardwareexperimente und analytische Modelle. Dabei reduziert QMA Kollisionen im Managementverkehr und das Senden mehrerer Pakete pro GTS und Gruppenbestätigungen entlasten diesen zusätzlich. Schließlich ermöglicht eine dynamische CAP-Reduzierung die fein abgestufte Abwägung zwischen Management- und Datenverkehr., This dissertation explores techniques for adaptive multi-hop networks in the IIoT concerning time-varying, dynamically changing traffic. It demonstrates that efficient transmission of management traffic is crucial for high adaptability in IEEE 802.15.4 DSME, develops several techniques to increase adaptability and validates them through simulations, hardware experiments, and analytical models. In particular, QMA reduces collisions in management traffic by learning when it is feasible to transmit a packet. Sending multiple packets per GTS and group acknowledgments further relieve the management traffic load. Finally, dynamic CAP-reduction enables a fine-grained trade-off between management and data traffic.

Das nichtlineare Dämpfungsvehalten von Partikeldämpfern und die Vielzahl an Einflussparametern hindern derzeit deren weit verbreitete industrielle Nutzung. Das Ziel dieser Arbeit ist daher die Entwicklung eines neuen Entwurfskonzeptes in Form einer Toolchain, um eine systematische Auslegung von Partikeldämpfern zu ermöglichen. Dabei werden verschiedene experimentelle als auch numerische Modelle miteinander kombiniert. Die Toolchain beginnt mit der Analyse des makroskopischen Verhaltens einzelner Partikelstöße, führt über die Analyse der Eigenschaften von vibrierenden granularen Medien und endet mit der Auslegung des Partikeldämpfers für die gewünschte Struktur. Die Wirksamkeit der Toolchain wird schlussendlich anhand von verschiedenen Beispielen demonstriert., The nonlinear damping behavior of particle dampers and the multitude of influence parameters hinder their wide industrial usage. Hence, the goal of this work is the development of a new design methodology in form of a toolchain enabling a systematic damper design. On that account, various numerical models and experimental tests are combined. The toolchain commences with investigations of the micro-mechanical behavior of single particle impacts, continues with analyzing the properties of vibrating granular matter inside different containers and ends with designing a particle damper for a desired vibrating structure. The good agreement of the experimental and numerical models and their efficiency for the damper design and dimensioning are demonstrated on multiple examples.

To achieve CO2 neutrality in 2050, internal combustion engine vehicles will be gradually substituted by electric vehicles since they enable an emission-free use phase if powered with renewable energy. However, producing lithium-ion batteries for electric vehicles is associated with high environmental impacts and economic challenge such as supply bottlenecks. Seeking to tackle these challenges by integrating recovery activities, car and battery manufacturers are increasingly transforming their production systems to circular production. Yet, transforming the entire production system poses several risks and uncertainties, e.g., technological developments and regional political instabilities. Therefore, a robust transformation toward a sustainable circular battery production is needed. Using a scenario design approach, we envision sustainable circular battery production in 2050 and the correlating transformation with minimum total CO2 emissions throughout the transformation process. To consider the potential enablers, inhibitors, and feasible (counter)measures, we conducted a workshop with experts from life cycle engineering, mechanical engineering, and business economics. Based on the results, both technological enablers and fundamental challenges of sustainable circular battery production were derived, which have to be addressed in the context of life cycle engineering., Bundesministerium für Bildung und Forschung (BMBF)

Traction batteries are a key component for the performance and cost of electric vehicles. While they enable emission-free driving, their supply chains are associated with environmental and socio-economic impacts. Hence, the advancement of batteries increasingly focuses on sustainability next to technical performance. However, due to different system definitions, comparing the results of sustainability assessments is difficult. Therefore, a sustainability assessment of different batteries on a common basis considering the three sustainability dimensions is needed. This paper investigates the sustainability of current and prospective traction battery technologies for electric vehicles. It provides a common base for the comparison of the predominant lithium-ion batteries with new technologies such as lithium-sulfur and all-solid-state batteries regarding the environmental and socio-economic impacts in their supply chain. A life cycle sustainability assessment of ten battery types is carried out using a cradle-to-gate perspective and consistent system boundaries. Four environmental impact categories (climate change, human toxicity, mineral resource depletion, photochemical oxidant formation), one economic performance indicator (total battery cost), and three social risk categories (child labor, corruption, forced labor) are analyzed. The assessment results indicate that the new battery technologies are not only favorable in terms of technical performance but also have the potential to reduce environmental impacts, costs, and social risks. This holds particularly for the lithium-sulfur battery with solid electrolyte. The environmental benefits are even amplified with a higher share of renewable energy for component and battery production. Nevertheless, hotspots related to the high energy demand of production and the supply chain of the active materials remain. This article emphasizes the need to evaluate different battery technologies on a common basis to ensure comparab, Bundesministerium für Bildung und Forschung (BMBF)

Für die Kurzstudie zur Lokalisierung von mobilen Robotersystemen wurden Prozesse und Technologien untersucht, die in Zukunft vermehrt im Hochbau zum Einsatz kommen. Die praxisnahen Analysen zeigten nicht nur unterschiedliche Erkenntnisse zu verschiedenen Lasermessgeräten, auch konnten Einsichten zur Präzision Verortung von mobilen Robotern gewonnen werden. Durch die Untersuchung der Sensortechnologien war es zudem möglich, Unterschiede zu Lokalisierungsgenauigkeiten festzuhalten. Da Laserscanner zukünftig häufiger in Planung, Ausführung und Betrieb von Gebäuden eingesetzt werden, liefert die Kurzstudie richtungsweisende Erkenntnisse zur Positionierung beweglicher Elemente., For the case study on the localization of mobile robot systems, processes and technologies, which will increasingly be used in the construction engineering, have been examined. The practice-oriented analysis has revealed findings on different laser measuring devices and insights about aspects of precision and localization of mobile robots. By testing the sensor technologies, differences in localization accuracy have been determined. Since laser scanners will increasingly be used in the planning, execution, and operation phases of buildings, the case study provides essential insights into positioning of mobile elements., Behörde für Stadtentwicklung und Wohnen, Hamburg

While different vehicle configurations enter the AAM market, airlines declare different ticket fares for their operations. This research investigates the operating cost of an airline and the economic viability with the announced fare per km rates. For this purpose, three use cases in the metropolitan area of Hamburg showcase representative applications of an AAM system, whereby a flight trajectory model calculates a flight time in each case. The direct operating cost are investigated for each use case individually and are sub-classified in five categories: fee, crew, maintenance, fuel and capital costs. Here, each use case has its own cost characteristics, in which different cost elements dominate. Additionally, a sensitivity analysis shows the effect of a variation of the flight cycles and load factor, that influences the costs as well as the airline business itself. Based on the occurring cost, a profit margin per available seat kilometer lead to a necessary fare per km, that an airline has to charge., While different vehicle configurations enter the AAM market, airlines declare different ticket fares for their operations. This research investigates the operating cost of an airline and the economic viability with the announced fare per km rates. For this purpose, three use cases in the metropolitan area of Hamburg showcase representative applications of an AAM system, whereby a flight trajectory model calculates a flight time in each case. The direct operating cost are investigated for each use case individually and are sub-classified in five categories: fee, crew, maintenance, fuel and capital costs. Here, each use case has its own cost characteristics, in which different cost elements dominate. Additionally, a sensitivity analysis shows the effect of a variation of the flight cycles and load factor, that influences the costs as well as the airline business itself. Based on the occurring cost, a profit margin per available seat kilometer lead to a necessary fare per km, that an airline has to charge.

Aviation is characterized by many stakeholders, long lifespans of its assets, and high requirements regarding safety, security, and documentation. To meet these requirements as well as customer needs, aircraft are regularly retrofitted with new cabins. During the planning and execution of this cabin retrofit, handling the needed and available data poses a challenge to the engineers. While much of the required data is available in some form, generally there is a lack of a digitally usable dataset of the specific aircraft—a virtual representation of the physical asset is missing. To support the implementation of such a digital twin and, thus, the overall process of retrofitting aircraft, an approach to model-driven data handling tailored to the unique circumstances and requirements of aviation is introduced. The methodology consists of a combination of systems engineering and data science techniques framed by an overarching procedure that iteratively creates and enhances a digitally accessible dataset of the relevant data, hence supporting the retrofit engineers by easing access to needed information. Besides the presentation of the research background and the methodology, a simplified example is shown, demonstrating the approach using abstracted but realistic information provided by partners from the industry., Aviation is characterized by many stakeholders, long lifespans of its assets, and high requirements regarding safety, security, and documentation. To meet these requirements as well as customer needs, aircraft are regularly retrofitted with new cabins. During the planning and execution of this cabin retrofit, handling the needed and available data poses a challenge to the engineers. While much of the required data is available in some form, generally there is a lack of a digitally usable dataset of the specific aircraft - a virtual representation of the physical asset is missing. To support the implementation of such a digital twin and, thus, the overall process of retrofitting aircraft, an approach to model-driven data handling tailored to the unique circumstances and requirements of aviation is introduced. The methodology consists of a combination of systems engineering and data science techniques framed by an overarching procedure that iteratively creates and enhances a digitally accessible dataset of the relevant data, hence supporting the retrofit engineers by easing access to needed information. Besides the presentation of the research background and the methodology, a simplified example is shown, demonstrating the approach using abstracted but realistic information provided by partners from the industry.

Es wird über Versuche zur Querkrafttragfähigkeit von gevouteten Stahlbetonbalken ohne Querkraftbewehrung berichtet. Mit Hilfe von experimentellen und numerischen Untersuchungen sollte geklärt werden, ob eine Voutung die Tragfähigkeit von Balken ohne Schubbewehrung (Vccd) signifikant beeinflusst. Die Versuchsergebnisse zeigen, dass der Ansatz von V_ccd beim Querkraftnachweis fragwürdig ist., This research report summarizes the experimental and numerical investigations which were conducted to clarify whether haunching of reinforced concrete beams without shear reinforcement significantly affects the ultimate shear capacity (V_ccd). The experimental results show that the approach of V_ccd in shear design is questionable.

Additive Manufacturing (AM) is rapidly gaining acceptance in healthcare. Due to 3D printing of polyetheretherketone (PEEK) constructions almost any complex geometry, e. g. bio-mimicking implants or light-weight hollow implant bodies, can be produced. In this paper a direct comparison between PEEK and titanium osteosynthesis plates is achieved with a finite element analysis. By that, pros and cons of PEEK as implant material are discussed and different use cases are identified. For the comparison a generic osteosynthesis plate for diaphysis is designed. The exceeding of the yield strength even at low bending and torsional loads highlights the problems that occur when applying PEEK implants at locations which are affected by moderate mechanical loads. Since fracture stabilisation is the main function of osteosynthesis plates, stiffness is a highly relevant property of these. Therefore, a direct exchange of titanium to PEEK would increase the risk of non-union. Thus, a different structure or an improved material, e. g. carbon fibre PEEK composite, is required for loaded locations to replace metallic implants., Bundesministerium für Bildung und Forschung (BMBF)

Porcelain tile manufacturing is an energy-intensive industry that is in dire need of increasing productivity, minimizing costs, and reducing CO2 emissions, while keeping the product quality intact to remain competitive in today’s environment. In this contribution, alternative processing parameters for the porcelain tile production sequence were proposed based on simulation-based process optimization. Flowsheet simulations in the Dyssol framework were used to study the impact of the milling and firing process parameters on the electrical and thermal energy consumption, final product quality, and productivity of the entire processing sequence. For this purpose, a new model of gas flow consumption in the sintering stage was proposed and implemented. During optimization, the primary condition was to maintain the product quality by keeping the final open porosity of the tile within the specified industrial range. The proposed simulation methodology proved to be effective in predicting the influence of the processing parameters on the intermediate and final products of the manufacturing sequence, as well as in estimating the production costs for the Brazilian and Spanish economic conditions. This approach has shown great potential to promote digitalization and establish digital twins in ceramic tile manufacturing for further in-line process control., Porcelain tile manufacturing is an energy-intensive industry that is in dire need of increasing productivity, minimizing costs, and reducing CO2 emissions, while keeping the product quality intact to remain competitive in today’s environment. In this contribution, alternative processing parameters for the porcelain tile production sequence were proposed based on simulation-based process optimization. Flowsheet simulations in the Dyssol framework were used to study the impact of the milling and firing process parameters on the electrical and thermal energy consumption, final product quality, and productivity of the entire processing sequence. For this purpose, a new model of gas flow consumption in the sintering stage was proposed and implemented. During optimization, the primary condition was to maintain the product quality by keeping the final open porosity of the tile within the specified industrial range. The proposed simulation methodology proved to be effective in predicting the influence of the processing parameters on the intermediate and final products of the manufacturing sequence, as well as in estimating the production costs for the Brazilian and Spanish economic conditions. This approach has shown great potential to promote digitalization and establish digital twins in ceramic tile manufacturing for further in-line process control., Deutscher Akademischer Austauschdienst (DAAD)

Das Transforming Energy Supply System (Modelling) Framework oder auch kurz Tessif ist ein am Energietechnik Institut der Technischen Universität Hamburg in Python entwickeltes Framework, das den Vergleich verschiedener Softwaretools zum Modellieren und Optimieren von Energiesystemen ermöglicht. Für den Vergleich transformiert Tessif ein zuvor erstelltes Energiesystemmodell in die verschiedenen Modelle der in Tessif integrierten Softwaretools, die das Energiesystem anschließend optimieren. Die Ergebnisse der Optimierungen werden abschließend von Tessif vereinheitlicht und somit vergleichbar. Zum jetzigen Zeitpunkt sind die Programme Oemof, PyPSA, FINE und Calliope in Tessif integriert und können in Tessif für die Modellierung und Optimierung von Energiesystemen verwendet werden. Im Rahmen dieser Arbeit wird mit Urbs ein weiteres Programm zur Modellierung und Optimierung in Tessif integriert. Die Integration besteht zu einem großen Teil aus der Transformation des Energiesystemmodells von Tessifs in Urbs Modellformulierung (es2es) sowie der Umwandlung der Optimierungsergebnisse in Tessifs einheitliche Darstellungsweise (es2mapping). In dieser Arbeit wird dabei ausführlich auf die verschiedenen Modellierungsansätze und deren Unterschiede sowie die Umsetzung der Transformation eingegangen. Die korrekte Integration von Urbs wird anhand eines exemplarischen Vergleichs diverser Beispielenergiesystemmodelle gewährleistet. Zusätzlich werden die Unterschiede zwischen den verschiedenen Softwaretools ausgearbeitet. Abschließend werden die Ergebnisse des exemplarischen Vergleichs genutzt, um Urbs im Rahmen von Tessif einzuordnen und die Stärken sowie Schwächen von Urbs zu identifizieren., The Transforming Energy Supply System (Modelling) Framework, or Tessif for short, is a framework developed with Python at the Institute of Energy Technology of the Technical University of Hamburg that enables the comparison of different software tools for modeling and optimizing energy systems. For the comparison, Tessif transforms a previously created energy system model into the model of the software tools integrated in Tessif, which then optimizes the energy system. The results of the optimizations are finally unified by Tessif and thus become comparable. Currently, the programs Oemof, PyPSA, FINE and Calliope are integrated in Tessif and can be used within the framework of Tessif for the modeling and optimization of energy systems. In the context of this work, Urbs, another program for modeling and optimization, is integrated into Tessif. The integration consists to a large extent of the transformation of the energy system model from Tessif into Urbs model formulation (es2es) as well as the conversion of the optimization results into Tessifs uniform representation mode (es2mapping). Herein, the various modeling approaches and their differences as well as the implementation of the transformation are discussed in detail. The correct integration of Urbs is ensured by comparing various example energy system models. In addition, the differences between the various software tools are elaborated. Finally, the results of the comparison are used to classify Urbs in the context of Tessif and to identify the advantages and disadvantages of using Urbs.

When designing crash absorber particles for application as a filling material in the double-hull of ships, the main goal is to achieve an optimal mechanical performance, in combination with a low-density particle structure, while fulfilling several additional requirements regarding, for example, non-toxic and hydrophobic behavior. In this study, a fluidized bed was used to coat Poraver® glass particles with Candelilla wax and silicone to attain these specifications. A uniform coating was achieved with wax, but the process turned out to be far more challenging when using silicone. To evaluate the suitability of coated particles as a granular filling material, and to compare their performances with that of untreated Poraver® particles, several mechanical tests, as well as structural investigations, were conducted. While no notable improvement in mechanical behavior was observed on the single-particle level, bulk tests showed promising results regarding compressibility and abrasion resistance of coated particles compared to untreated ones., When designing crash absorber particles for application as a filling material in the double-hull of ships, the main goal is to achieve an optimal mechanical performance, in combination with a low-density particle structure, while fulfilling several additional requirements regarding, for example, non-toxic and hydrophobic behavior. In this study, a fluidized bed was used to coat Poraver® glass particles with Candelilla wax and silicone to attain these specifications. A uniform coating was achieved with wax, but the process turned out to be far more challenging when using silicone. To evaluate the suitability of coated particles as a granular filling material, and to compare their performances with that of untreated Poraver® particles, several mechanical tests, as well as structural investigations, were conducted. While no notable improvement in mechanical behavior was observed on the single-particle level, bulk tests showed promising results regarding compressibility and abrasion resistance of coated particles compared to untreated ones.

Spinal cord injury (SCI) can lead to the dysfunction of nerve fibers by hemi- or complete transection, resulting in permanent paraplegia. In recent years, a number of therapies have been developed to treat spinal cord injury. A mechanical microconnector system (mMS) that supports the regeneration of nerve fibers after SCI through a combination of different therapies was designed in previous works. For this implantable mMS with minimum feature size of a few hundreds of micrometers, it is essential to provide fast, flexible, three-dimensional fabrication. This paper describes a new fabrication method of the mMS made of silicone using additive manufacturing based on a commercially available material jetting printer. The application of this technology advances the fabrication and adaptability of mMS in terms of higher elasticity of the implant using silicone and additionally with respect to high customizability and rapid prototyping using additive manufacturing. We show the successful adaption and realization of a silicone-based mMS dimensioned for a human model with structure sizes down to 300 um. We elaborate the advantages and disadvantages of additive, silicone-based 3D printing for this application in comparison to molding-based and subtractive 3D printing methods, thus demonstrating the relevance of this technology for medical application.

Der Beitrag des Luftverkehrs zum anthropogenen Klimawandel wird auf etwa 4 % geschätzt. In diesem Zusammenhang werden alternative Kraftstoffe als eine wichtige Maßnahme zur Verringerung der Treibhausgasemissionen im Luftverkehrssystem und damit zur Verringerung des Beitrags des gewerblichen Luftverkehrs zum anthropogenen Klimawandel angesehen. Dennoch liegt der Nutzungsanteil alternativer Kraftstoffe bisher unter 1 %. Ziel dieses Papiers ist es daher, eine breite Auswahl von Flugkraftstoffoptionen auf ihr Treibhausgasminderungspotenzial hin zu analysieren und Szenarien für ihre mögliche zukünftige Entwicklung abzuleiten. Bei den untersuchten Kraftstoffoptionen handelt es sich um gemischtes synthetisches Kerosin und reines synthetisches Kerosin, drei Alkohole (Methanol, Ethanol und Butanol) und drei Gase (Methan, Ammoniak und Wasserstoff). Es wurden allgemeine sozioökonomische Voraussetzungen und Anforderungen innerhalb des Luftverkehrssystems ermittelt. Die Entwicklung des Energiebedarfs im Luftverkehr, der Ausbau der Produktionskapazitäten und die Bereitschaft, die Kosten der Energiewende zu tragen, scheinen die wichtigsten Hebel für einen erfolgreichen Übergang zu erneuerbaren Energien zu sein., The air transport sector’s contribution to anthropogenic climate forcing is estimated at around 4 %. In this respect, alternative fuels are considered as a key measure to reduce greenhouse gas emissions within the air transport system and thus to reduce the contribution of commercial aviation to anthropogenic climate change. Nevertheless, so far the usage-shares of alternative fuels are below 1 %. Thus, the goal of this paper is to analyse a broad selection of aviation fuel options for their greenhouse gas reduction potential based and to derive scenarios for their potential future development. The fuel options studied are blended synthetic kerosene and neat synthetic kerosene fuels, three alcohols (methanol, ethanol and butanol) and three gases (methane, ammonia and hydrogen). General socio-economic preconditions and requirements within the air transport system were identified. Key Levers for a successful transition towards renewably sourced energies appear to be the development of aviation's energy demand, the ramp-up of production capacities and the willingness to cover the cost of the energy transition.

Buildings are responsible for 40% of energy consumption annually in Europe, along with the respective greenhouse gas emissions. To mitigate these impacts, intensive research is ongoing in the sector of the Nearly Zero-Energy Buildings (NZEBs). However, as it is expected that the operational energy of future buildings becomes greener and more efficient, impacts related to the embodied energy of building materials becomes of more significance. Thus, choices on building materials are of crucial importance as they affect the energy performance of the building envelope and its environmental impacts. The objective of this study was to implement preliminary Life Cycle Assessment (LCA) on new advanced building materials, with the final scope to achieve lower embodied carbon in NZEBs. The materials examined are concretes and aerogels for wall façades. Design of sustainable advanced materials and building envelope components is expected to improve the overall energy performance of buildings, including NZEBs. The study findings provide clear evidence on the necessity for further research on the topic, as lack of embodied impacts’ data of novel materials is presented in literature and adds to the discussion around NZEBs.

The currently still high fossil energy demand is forcing the glass industry to search for innovative approaches for the reduction in CO₂ emissions and the integration of renewable energy sources. In this paper, a novel power-to-methane concept is presented and discussed for this purpose. A special focus is on methods for the required CO₂ capture from typical flue gases in the glass industry, which have hardly been explored to date. To close this research gap, process simulation models are developed to investigate post-combustion CO₂ capture by absorption processes, followed by a techno-economic evaluation. Due to reduced flue gas volume, the designed CO₂ capture plant is found to be much smaller (40 m³ absorber column volume) than absorption-based CO₂ separation processes for power plants (12,560 m³ absorber column volume). As there are many options for waste heat utilization in the glass industry, the waste heat required for CO₂ desorption can be generated in a particularly efficient and cost-effective way. The resulting CO² separation costs range between 41 and 42 EUR/t CO₂, depending on waste heat utilization for desorption. These costs are below the values of 50–65 EUR/t CO₂ for comparable industrial applications. Despite these promising economic results, there are still some technical restrictions in terms of solvent degradation due to the high oxygen content in flue gas compositions. The results of this study point towards parametric studies for approaching these issues, such as the use of secondary and tertiary amines as solvents, or the optimization of operating conditions such as stripper pressure for further cost reductions potential.

Laser powder bed fusion of metals (PBF-LB/M) is a process widely used in additive manufacturing (AM). It is highly sensitive to its process parameters directly determining the quality of the components. Hence, optimal parameters are needed to ensure the highest part quality. However, current approaches such as experimental investigation and the numerical simulation of the process are time-consuming and costly, requiring more efficient ways for parameter optimization. In this work, the use of machine learning (ML) for parameter search is investigated based on the influence of laser power and speed on simulated melt pool dimensions and experimentally determined part density. In total, four machine learning algorithms are considered. The models are trained to predict the melt pool size and part density based on the process parameters. The accuracy is evaluated based on the deviation of the prediction from the actual value. The models are implemented in python using the scikit-learn library. The results show that ML models provide generalized predictions with small errors for both the melt pool dimensions and the part density, demonstrating the potential of ML in AM. The main limitation is data collection, which is still done experimentally or simulatively. However, the results show that ML provides an opportunity for more efficient parameter optimization in PBF-LB/M.

Adsorption is the most widely used technique for advanced wastewater treatment. The preparation and application of natural renewable and environmentally friendly materials makes this process easier and more profitable. Chitosan is often used as an effective biomaterial in the adsorption world because of its numerous functional applications. Chitosan is one of the most suitable and functionally flexible adsorbents because it contains hydroxyl (-OH) and amine (-NH2) groups. The adsorption capacity and selectivity of chitosan can be further improved by introducing additional functions into its basic structure. Owing to its unique surface properties and adsorption ability of chitosan, the development and application of chitosan nanomaterials has gained significant attention. Here, recent research on chitosan nanoparticles is critically reviewed by comparing various methods for their synthesis with particular emphasis on the role of experimental conditions, limitations, and applications in water and wastewater treatment. The recovery of pollutants using magnetic nanoparticles is an important treatment process that has contributed to additional development and sustainable growth. The application of such nanoparticles in the recovery metals, which demonstrates a “close loop technology” in the current scenarios, is also presented in this review., Adsorption is the most widely used technique for advanced wastewater treatment. The preparation and application of natural renewable and environmentally friendly materials makes this process easier and more profitable. Chitosan is often used as an effective biomaterial in the adsorption world because of its numerous functional applications. Chitosan is one of the most suitable and functionally flexible adsorbents because it contains hydroxyl (-OH) and amine (-NH2) groups. The adsorption capacity and selectivity of chitosan can be further improved by introducing additional functions into its basic structure. Owing to its unique surface properties and adsorption ability of chitosan, the development and application of chitosan nanomaterials has gained significant attention. Here, recent research on chitosan nanoparticles is critically reviewed by comparing various methods for their synthesis with particular emphasis on the role of experimental conditions, limitations, and applications in water and wastewater treatment. The recovery of pollutants using magnetic nanoparticles is an important treatment process that has contributed to additional development and sustainable growth. The application of such nanoparticles in the recovery metals, which demonstrates a “close loop technology” in the current scenarios, is also presented in this review.

Im Vergleich zu klassischen Konstruktionsmaterialien zeigen faserverstärkte Verbundwerkstoffe hohe spezifische Festigkeiten und Steifigkeiten auf. Als Nachteilig müssen hingegen die komplexen Versagensmechanismen und eine hohe Anfälligkeit für unentdeckte Schäden betrachtet werden die bei diesen Werkstoffen beobachtet werden. Während des gesamten Lebenszyklus von Verbundwerkstoffen ist es daher entscheidend, den Materialzustand einzuschätzen und verfolgen zu können, um ein frühzeitiges Versagen zu verhindern. Aufgrund der hohen Kostensensitivität von Verbundwerkstoffanwendungen ist die Implementierung eines kontinuierlichen Systems zur Bauteilüberwachung in der Regel nicht praktikabel. Vielmehr ist es üblich zerstörungsfreie Prüfungen in regelmäßigen Intervallen auszuführen, um die strukturelle Integrität sicherzustellen. Die derzeit verfügbaren zerstörungsfreie Prüfmethoden reichen jedoch nicht aus, um alle möglichen Schadensszenarien vollständig abzudecken. In dieser Arbeit wird ein neuer Ansatz zur Bestimmung der Materialeigenschaften der Epoxidharzkomponente mittels Fourier-Transformations-Infrarotspektroskopie (FTIR) -Spektroskopie vorgestellt. Durch die Nachbearbeitung der erfassten molekularen Informationen wird der Materialzustand auf Basis abstrakter Parameter modelliert und die inhärente Materialeigenschaften wie Festigkeit berechnet und vorhergesagt. Zunächst wird anhand von Herstellungsparameter gezeigt, dass mithilfe klassischer chemometrischer Methoden und FTIR-Messungen das Mischungsverhältnis eines Epoxidharzes schnell und zuverlässig bestimmt werden kann. In einem zweiten Schritt werden Materialänderungen aufgrund mechanischer Belastung beim Kriechen beobachtet und mit Hilfe des abgeleiteten Zustandvectors beschrieben, wobei fortschrittliche Verfahren zur Merkmalsextraktion angewendet werden. Schließlich werden Proben analysiert, die thermischen Belastungen ausgesetzt wurden, wobei gezeigt werden konnte, dass die Restfestigkeit ausschließlich durch, By design fiber-reinforced plastics (FRP) show extraordinary specific strength and stiffness performance when compared to classic structural materials. Unfortunately, the extraordinary properties come at the price of complexity in design, manufacturing and operation. Most notably, manifold failure modes and complicated detectability of inherent damages represent a challenge for composite engineers until now. Throughout the life-cycle of composites, it is crucial to understand and track the material state in order to prevent premature failure. Due to the high-cost sensitivity of the composites sector implementing material health monitoring systems is usually not practical in application. Instead, non-destructive testing (NDT) methods are usually applied to assure structural integrity and damages within allowed limitations at planned maintenance events. Nonetheless, currently available NDT methods are insufficient to fully cover all possible damage scenarios. In this work a new approach to determine material properties of the epoxy resin component using Fourier-transform infrared spectroscopy (FTIR)-spectroscopy is presented. It is shown that by post-processing the acquired molecular information the material state can be determined and based on this material state inherent material properties such as strength can be predicted. First, starting with the evaluation of manufacturing parameters it is shown that by using classic chemometrics techniques FTIR measurements can be used to quantify the mixing ratio of an epoxy resin fast and reliable. Thereafter, material changes due to mechanical loading in creep are observed and described by applying advanced feature extraction methods. Finally, specimens exposed to thermal loads are analyzed and it is confirmed, that the residual strength can be determined solely by applying FTIR measurements and machine learning algorithms. Furthermore, it is demonstrated, that the method is suitable to reveal the material exposure history., Deutsche Forschungsgemeinschaft (DFG)

In the pharmaceutical industry, the coating of particles is a widely used technique to obtain desired surface modifications of the final product, e.g., controlled release of the active agents. The production of round, coated particles is particularly important, which is why fluidized bed rotor granulators (FBRG) are often used for this process. In this work, Computational Fluid Dynamics (CFD) coupled with the Discrete Element Method (DEM) is used to investigate the wet particle dynamics, depending on the properties of the coating liquid in a FBRG. The DEM contact model was extended by liquid bridge model to account for capillary and viscous forces during wet contact of particles. The influence of the relative contact velocity on the maximum length of the liquid bridge is also considered in the model. Five different cases were compared, in which the particles were initially wetted, and the liquid loading as well as the surface tension and viscosity of the liquid were changed. The results show that increasing viscosity leads to a denser particle bed and a significant decrease in particle rotational velocities and particle motion in the poloidal plane of the FBRG. Reducing the liquid loading and surface tension results in increased particle movement., In the pharmaceutical industry, the coating of particles is a widely used technique to obtain desired surface modifications of the final product, e.g., controlled release of the active agents. The production of round, coated particles is particularly important, which is why fluidized bed rotor granulators (FBRG) are often used for this process. In this work, Computational Fluid Dynamics (CFD) coupled with the Discrete Element Method (DEM) is used to investigate the wet particle dynamics, depending on the properties of the coating liquid in a FBRG. The DEM contact model was extended by liquid bridge model to account for capillary and viscous forces during wet contact of particles. The influence of the relative contact velocity on the maximum length of the liquid bridge is also considered in the model. Five different cases were compared, in which the particles were initially wetted, and the liquid loading as well as the surface tension and viscosity of the liquid were changed. The results show that increasing viscosity leads to a denser particle bed and a significant decrease in particle rotational velocities and particle motion in the poloidal plane of the FBRG. Reducing the liquid loading and surface tension results in increased particle movement., Deutsche Forschungsgemeinschaft (DFG)

Presentation about cost minimized hydrogen prodcution in the "CODAHEA - Hydrogen Talk" webinar

Structural health monitoring (SHM) is a non-destructive testing method that supports the condition assessment and lifetime estimation of civil infrastructure. Sensor faults may result in the loss of valuable data and erroneous structural condition assessments and lifetime estimations, in the worst case with structural damage remaining undetected. As a result, the concepts of fault diagnosis (FD) have been increasingly adopted by the SHM community. However, most FD concepts for SHM consider only single-fault occurrence, which may oversimplify actual fault occurrences in real-world SHM systems. This paper presents an adaptive FD approach for SHM systems that addresses simultaneous faults occurring in multiple sensors. The adaptive FD approach encompasses fault detection, isolation, and accommodation, and it builds upon analytical redundancy, which uses correlated data from multiple sensors of an SHM system. Specifically, faults are detected using the predictive capabilities of artificial neural network (ANN) models that leverage correlations within sensor data. Upon defining time instances of fault occurrences in the sensor data, faults are isolated by analyzing the moving average of individual sensor data around the time instances. For fault accommodation, the ANN models are adapted by removing faulty sensors and by using sensor data prior to the occurrence of faults to produce virtual outputs that substitute the faulty sensor data. The proposed adaptive FD approach is validated via two tests using sensor data recorded by an SHM system installed on a railway bridge. The results demonstrate that the proposed approach is capable of ensuring the accuracy, reliability, and performance of real-world SHM systems, in which faults in multiple sensors occur simultaneously., Structural health monitoring (SHM) is a non-destructive testing method that supports the condition assessment and lifetime estimation of civil infrastructure. Sensor faults may result in the loss of valuable data and erroneous structural condition assessments and lifetime estimations, in the worst case with structural damage remaining undetected. As a result, the concepts of fault diagnosis (FD) have been increasingly adopted by the SHM community. However, most FD concepts for SHM consider only single-fault occurrence, which may oversimplify actual fault occurrences in real-world SHM systems. This paper presents an adaptive FD approach for SHM systems that addresses simultaneous faults occurring in multiple sensors. The adaptive FD approach encompasses fault detection, isolation, and accommodation, and it builds upon analytical redundancy, which uses correlated data from multiple sensors of an SHM system. Specifically, faults are detected using the predictive capabilities of artificial neural network (ANN) models that leverage correlations within sensor data. Upon defining time instances of fault occurrences in the sensor data, faults are isolated by analyzing the moving average of individual sensor data around the time instances. For fault accommodation, the ANN models are adapted by removing faulty sensors and by using sensor data prior to the occurrence of faults to produce virtual outputs that substitute the faulty sensor data. The proposed adaptive FD approach is validated via two tests using sensor data recorded by an SHM system installed on a railway bridge. The results demonstrate that the proposed approach is capable of ensuring the accuracy, reliability, and performance of real-world SHM systems, in which faults in multiple sensors occur simultaneously., Deutsche Forschungsgemeinschaft (DFG), Bundesministerium für Digitales und Verkehr, Bundesministerium für Bildung und Forschung (BMBF)

In this article, the model of a 5 kW small wind turbine blade is developed and improved. Emphasis has been placed on improving the blade’s efficiency and aerodynamics and selecting the most optimal material for the wind blade. The QBlade software was used to enhance the chord and twist. Also, a new finite element model was developed using the ANSYS software to analyze the structure and modal problems of the wind blade. The results presented the wind blade’s von Mises stresses and deformations using three different materials (Carbon/epoxy, E-Glass/epoxy, and braided composite). The modal analysis results presented the natural frequencies and mode shapes for each material. It was found, based on the results, that the maximum deflections of E-glass, braided composite and carbon fiber were 46.46 mm, 33.54 mm, and 18.29 mm, respectively., In this article, the model of a 5 kW small wind turbine blade is developed and improved. Emphasis has been placed on improving the blade’s efficiency and aerodynamics and selecting the most optimal material for the wind blade. The QBlade software was used to enhance the chord and twist. Also, a new finite element model was developed using the ANSYS software to analyze the structure and modal problems of the wind blade. The results presented the wind blade’s von Mises stresses and deformations using three different materials (Carbon/epoxy, E-Glass/epoxy, and braided composite). The modal analysis results presented the natural frequencies and mode shapes for each material. It was found, based on the results, that the maximum deflections of E-glass, braided composite and carbon fiber were 46.46 mm, 33.54 mm, and 18.29 mm, respectively.

Cruise ships or yachts that operate in areas with seasonal freezing temperatures have large openings in the outer shell. Those are thermal cut edges, and they are exposed to very low temperatures. From fatigue crack growth testing of base materials, it is known that low temperatures can accelerate the crack growth, which may reduce the fatigue life of a structure. However, the current guidelines and rules of classification societies do not provide design curves for the fatigue assessment of thermal cut steel edges at sub-zero temperatures. Therefore, fatigue tests of thermal cut edges are conducted at −20 C and −50 C as well as at room temperatures for reference. The specimens are plasma-cut and tested in a temperature chamber under uniaxial loading with a resonant testing machine. The test results are statistically evaluated using linear regression and the maximum likelihood method. The results show that the fatigue strength at sub-zero temperatures is significantly higher compared to room temperature. The test results of this study indicate that sub-zero temperatures down to −50 C do not seem to cause a reduced fatigue life of thermal cut steel edges., Cruise ships or yachts that operate in areas with seasonal freezing temperatures have large openings in the outer shell. Those are thermal cut edges, and they are exposed to very low temperatures. From fatigue crack growth testing of base materials, it is known that low temperatures can accelerate the crack growth, which may reduce the fatigue life of a structure. However, the current guidelines and rules of classification societies do not provide design curves for the fatigue assessment of thermal cut steel edges at sub-zero temperatures. Therefore, fatigue tests of thermal cut edges are conducted at −20° C and -50° C as well as at room temperatures for reference. The specimens are plasma-cut and tested in a temperature chamber under uniaxial loading with a resonant testing machine. The test results are statistically evaluated using linear regression and the maximum likelihood method. The results show that the fatigue strength at sub-zero temperatures is significantly higher compared to room temperature. The test results of this study indicate that sub-zero temperatures down to −50° C do not seem to cause a reduced fatigue life of thermal cut steel edges.

Journal bearings in typical applications are subjected to misalignment due to several causes, such as shaft deformation under load and errors related to the installation and manufacturing processes. Misalignment has well-known severe negative consequences on the performance of the bearings. This paper deals with the bearing chamfer to reduce these consequences of misalignment, and two forms of bearing edge modification are considered in the analysis. These forms are linear and curved chamfering of the bearing edges, where the height of the chamfer in the circumferential direction and the length of the modification in the longitudinal direction are considered as geometrical design parameters. The investigation includes a numerical solution of the hydrodynamic lubrication problem of finite length journal bearing, considering 3D misalignment cases using the finite difference method. This includes the assessment of the chamfer forms and their effects on the bearing performance in terms of the main bearing design parameters. Furthermore, the stability of the chamfered bearings is also investigated under impact load. Results showed that both chamfer forms are beneficial for a certain limit of the design parameters in reducing the maximum pressure and coefficient of friction and in elevating the film thickness levels, extending the range of misalignment in which the journal bearing can operate safely. In addition, the chamfered bearings in both forms showed more stability range in terms of the critical speed and shaft center trajectories under impact load. The bearings with the curved chamfer, where the slope is continuous at the start of modification, showed more uniform film thickness levels, and their shaft center trajectories were closer to the perfectly aligned bearing in the stable operating range of the system., Journal bearings in typical applications are subjected to misalignment due to several causes, such as shaft deformation under load and errors related to the installation and manufacturing processes. Misalignment has well-known severe negative consequences on the performance of the bearings. This paper deals with the bearing chamfer to reduce these consequences of misalignment, and two forms of bearing edge modification are considered in the analysis. These forms are linear and curved chamfering of the bearing edges, where the height of the chamfer in the circumferential direction and the length of the modification in the longitudinal direction are considered as geometrical design parameters. The investigation includes a numerical solution of the hydrodynamic lubrication problem of finite length journal bearing, considering 3D misalignment cases using the finite difference method. This includes the assessment of the chamfer forms and their effects on the bearing performance in terms of the main bearing design parameters. Furthermore, the stability of the chamfered bearings is also investigated under impact load. Results showed that both chamfer forms are beneficial for a certain limit of the design parameters in reducing the maximum pressure and coefficient of friction and in elevating the film thickness levels, extending the range of misalignment in which the journal bearing can operate safely. In addition, the chamfered bearings in both forms showed more stability range in terms of the critical speed and shaft center trajectories under impact load. The bearings with the curved chamfer, where the slope is continuous at the start of modification, showed more uniform film thickness levels, and their shaft center trajectories were closer to the perfectly aligned bearing in the stable operating range of the system.

The process of the additive manufacturing (AM) of carbon-fiber-reinforced polymer (CFRP) parts based on the process of fused deposition modeling (FDM) has seen considerable research in recent years, which amplifies the importance of adapted slicing and pathplanning methods. In particular, load-oriented techniques are of high interest when employing carbon fiber materials, as classical methods, such as tape-laying and laminating, struggle with highly curved and complex geometries and require the costly production of molds. While there have been some promising propositions in this field, most have restricted themselves to a planar slicing approach, which severely limits the ability to place the fibers along stress paths. In this paper, a nonplanar slicing approach is presented that utilizes principal stress directions to construct optimized nonplanar constituting layers on which pathplanning can be carried out. These layers are oriented such that the effect of the weak interlayer adhesion is minimized. Support material is adaptively generated to enable the use of arbitrary part geometry. Furthermore, a continuous pathplanning method and post-processor are applied to yield manufacturing instructions. The approach is verified for its viability of application through experimental investigation on a multi-axis robotic 3D printer. This constitutes an important step in allowing the fabrication of CFRP parts to further utilize the possibilities of additive manufacturing., The process of the additive manufacturing (AM) of carbon-fiber-reinforced polymer (CFRP) parts based on the process of fused deposition modeling (FDM) has seen considerable research in recent years, which amplifies the importance of adapted slicing and pathplanning methods. In particular, load-oriented techniques are of high interest when employing carbon fiber materials, as classical methods, such as tape-laying and laminating, struggle with highly curved and complex geometries and require the costly production of molds. While there have been some promising propositions in this field, most have restricted themselves to a planar slicing approach, which severely limits the ability to place the fibers along stress paths. In this paper, a nonplanar slicing approach is presented that utilizes principal stress directions to construct optimized nonplanar constituting layers on which pathplanning can be carried out. These layers are oriented such that the effect of the weak interlayer adhesion is minimized. Support material is adaptively generated to enable the use of arbitrary part geometry. Furthermore, a continuous pathplanning method and post-processor are applied to yield manufacturing instructions. The approach is verified for its viability of application through experimental investigation on a multi-axis robotic 3D printer. This constitutes an important step in allowing the fabrication of CFRP parts to further utilize the possibilities of additive manufacturing.

The influence of the particle size distribution of maltodextrin powders with a dextrose equivalent level of 29 as well as two tableting process variables, namely the compression pressure and the dwell time, on the tensile strength, porosity, and pore size distribution of the final tablet was studied. The mechanical strength and porosity of the tablets are assessed in relation to the powder and process parameters. Regarding the process parameter, it was show that the compaction pressure clearly has a more pronounced influence on the tablet porosity and mechanical strength compared to the influence of the dwell time in the range of the study. As a result, the study offers a better understanding of how the properties of a tablet are influenced by the inter-correlation of powder characteristics and tableting parameters. Therefore, the shelf-life studies and tablet downstream processing as well as drug product development will benefit greatly from this work.

When facing today’s scarcity of mineral phosphorus (P) resources and the environmental issues following enhanced P losses especially from agriculture, new solutions need to be implemented. In this framework, the potential for a mechanical separation of a P rich grain fraction from wheat, rye, barley and oats is investigated in order to provide animal feed with reduced organic P content. Thus, P accumulation in manure and soils should be prevented. Also, the subsequent utilization of the separated organic P, which occurs in the form of inositol P, for a sustainable P management via activation of intrinsic enzymes is evaluated. It was shown that in grain layers at 7.0, 5.5, 6.4 and 2.5% cross section of wheat, rye, barley and oats, respectively, maximum inositol P occurs with 1.6, 0.8, 1.4 and 1.2 g/100 g. Phytase activity is also highest in the outer layers of the grains with maxima of 9300, 12,000, 8400 and 2400 U/kg, respectively. A removal of the specific layers where inositol P is accumulated could possibly achieve a 24, 31, 60 and 27% organic P reduction for wheat, rye, barley and oats with 7, 14, 25 or 7% grain elimination. A debranning, eliminating all the outer grain layers to a certain extent, in contrast, leads to significantly higher mass losses. Within the P enriched layer determined from inositol P distribution, phytase activity is calculated to be around 285, 831, 777 and 42 U/kg for wheat, rye, barley and oats, respectively.

To date high printing resolution and scalability, i.e., macroscale component dimensions and fast printing, are incompatible characteristics for additive manufacturing (AM) processes. It is hereby demonstrated that the combination of direct writing as an AM process with colloidal assembly enables the breaching of this processing barrier. By tailoring printing parameters for polystyrene (PS) microparticle-templates, how to avoid coffee ring formation is demonstrated, thus printing uniform single lines and macroscale areas. Moreover, a novel “comb”-strategy is introduced to print macroscale, crack-free colloidal coatings with low viscous colloidal suspensions. The printed templates are transformed into ceramic microporous channels as well as photonic coatings via atomic layer deposition (ALD) and calcination. The obtained structures reveal promising wicking capabilities and broadband reflection in the near-infrared, respectively. This work provides guidelines for printing low viscous colloidal suspensions and highlights the advancements that this printing process offers toward novel applications of colloidal-based printed structures.

Diese Dissertation präsentiert neue Ergebnisse zur kooperativen Regelung von Fahrzeugen. Modulare Architekturen werden untersucht, die aus Netzwerken vereinfachter Modelle und komplexer Fahrzeuge bestehen, die die von diesen vereinfachten Modellen erzeugten Trajektorien verfolgen. Dissipativitätstheorie und \textit{integral quadratic constraints} werden verwendet, um hinreichende Bedingungen für Stabilität und Regelgüte zu finden, die höchstens linear mit der Netzwerkgröße skalieren. Konvexe und nicht-konvexe Interaktionen zwischen Fahrzeugen werden im Zusammenhang mit einem \textit{source-seeking} Problem betrachtet, bei dem Fahrzeuge das Minimum eines externen Skalarfelds lokalisieren müssen. Experimente mit Quadrotoren und Simulationsstudien veranschaulichen die Ergebnisse., This thesis presents results on cooperative control of vehicles by studying modular architectures consisting of networks of simplified models and complex vehicles tracking the trajectories generated by these simplified models. Convex intervehicle interactions from formation control and non-convex inter-vehicle interactions emerging from flocking dynamics are studied within the context of a source-seeking problem, where vehicles are required to locate the minimum of an external scalar field. The main analysis tools are dissipativity theory and integral quadratic constraints while the experimental results are with quadrotors.

Jüngste Phänomene wie Urbanisierung, Klimawandel und Digitalisierung beeinflussen die Art und Weise, wie wir heute und in Zukunft wohnen. Gebäude unter sozialen, ökologischen und digitalen Gesichtspunkten zu konzipieren, ist daher Teil der stetigen gesellschaftlichen Herausforderung, angemessenen Wohnraum bereitzustellen. Diese Forschungsarbeit zielt darauf ab, eine Verbindung zwischen diesen Anforderungen zu schlagen und herauszufinden, wie in der Praxis zukunftsfähiges Wohnen aussehen kann. Eine Methode zur Gebäudebeurteilung wird vorgestellt, anhand der zunächst soziale und ökologische Gebäudeanforderungen evaluiert werden. Darüber hinaus wird untersucht, wie ein Smart Building umzusetzen ist, um eine menschorientierte, umweltfreundliche und zukunftsorientierte Gestaltung zu verwirklichen. Zunächst werden die Verankerung von angemessenem Wohnen als Menschenrecht sowie verschiedene Probleme und zeitgenössische Entwicklungen in Bezug auf Wohnraum beleuchtet. Gemeinsam mit einer Analyse der enormen Umweltauswirkungen der Bauindustrie werden wesentliche Anforderungen an die Gestaltung von Wohngebäuden aus sozialer und ökologischer Perspektive ermittelt und mit gängigen Gebäudebewertungssystemen verglichen. Auf der Grundlage dieser Erkenntnisse wird ein praxisorientiertes Gebäudebeispiel unter Verwendung von Building Information Modeling modelliert und mithilfe des EU-Berichtsrahmens Level(s) sowie ausgewählten Life Cycle Assessment-Tools optimiert. Das Planungsergebnis ist ein Mehrfamilienhaus aus überwiegend biobasierten Materialien mit zwölf Wohneinheiten und großzügig gestalteten Gemeinschaftsflächen. Zusätzlich ist ein intelligentes Gebäudesystem mit Berücksichtigung von Datensicherheit und -schutz unter Verwendung einer Internet of Things-Fog-Cloud-Architektur integriert. Die Nutzung von smarten Geräten verbessert die vorher festgelegten Gebäudeanforderungen und erlaubt eine dynamische Reaktion auf verschiedene Zukunftsszenarien, wie extreme Wetterereignisse und, Recent phenomena like urbanization, climate change and digitalization are influencing the way we dwell today and in the future. Designing buildings from a social, environmental and digital perspective is therefore part of the societal challenge of providing adequate housing. This research aims to bridge the gap between these design objectives and to find out what a future-proof residential building can look like in practice. A building assessment methodology is presented that first evaluates social and environmental building requirements. Additionally, it is investigated how a smart building can be implemented to realize a human-centered, ecological and future-oriented design. First, the enshrinement of adequate housing as a human right, possible problems and contemporary developments related to housing are elaborated. Together with an analysis of the enormous environmental impact of the construction industry, essential requirements for the design of residential buildings from a social and environmental perspective are identified and compared with common building sustainability assessment methods. Based on these findings, a practical building example is modeled using Building Information Modeling and optimized by means of the EU Level(s) framework and selected life cycle assessment tools. The design result is an apartment building made of predominantly biobased materials with twelve residential units and spacious common areas. In addition, a smart building system is integrated with consideration of data security and protection using an Internet of Things-fog-cloud architecture. The use of smart devices enhances the predetermined objectives for building design and allows for a dynamic reaction to various future scenarios, such as extreme weather events and pandemics, for the benefit of the residents. The findings of this research provide a guideline for addressing social and environmental requirements for building design and highlights the benefits of implementing a

Experts play an important role in the evaluation of ideas. Owing to their experience and knowledge, they are believed to be best suited to objectively evaluate ideas. At the same time, expert evaluations sometimes fail to accurately reflect stakeholder preferences. For this reason, more and more organizations have begun to solicit ‘non-expert’ evaluations from the ‘crowd’ (e.g., via community voting). We illustrate how organizations can involve stakeholders in idea evaluation in the context of the Fab City project. Integrating citizens into the innovation process is particularly interesting in a Fab City–a city that produces many of the products it needs locally–since it enables one to develop regional preferences into tailored solutions. Here, citizens evaluate a solution, implement it as a local product, and ultimately share the design (mostly open-source) within the community. In the course of a Fab City initiative in Hamburg–the Maker Challenge–citizens were invited to evaluate almost 100 innovative ideas in pairwise comparisons. We draw on over 20,000 votes from around 400 citizen judges to assess the crowd opinion formation process. Unlike in other studies, our data allow us to measure the time every citizen judge needed to make their decision. Thus, we can conclude how diligent citizen judges are and, conversely, how much attention an idea can attract. Looking at the citizen judges’ evaluation times, it appears that, in most cases, the opinion-formation process is spontaneous. In a few cases, however, a substantial amount of time is spent. All the evaluation times followed a Poisson distribution. Further, we compare expert evaluations with crowd evaluations and relate the results to the literature. We conclude that the crowd evaluation process resembles the expert evaluation process. Also, we show that citizens optimize their cognitive effort over time. For real-world cases, such as the Fab City project, this implies that not only the ideation process and the, Digitalization and Technology Research Center of the Bundeswehr (dtec.bw)

Going wireless is one of the key industrial trends, which assists the emergence of new manufacturing and maintenance processes by reducing the complexity and cost of physical equipment. However, the adoption of Wireless Sensor Networks (WSNs) in production environments is limited due to the strict Quality of Service (QoS) requirements of industrial applications. In particular, Wireless Avionics Intra-Communication (WAIC) systems operating in 4.3 GHz band are designed for intra-aircraft use cases with considerable restrictions on the transmission power of sensors, which results in multi-hop topologies, complicating a guaranteed QoS. The Internet Engineering Task Force (IETF) has developed the protocol stack IPv6 over the Time Slotted Channel Hopping (TSCH) mode of IEEE 802.15.4 (6TiSCH) based on the IEEE 802.15.4 Standard for Low-Rate Wireless Networks, which combines the TSCH reliability with ubiquitous IPv6 connectivity and with the robust Routing Protocol for Low-Power and Lossy Networks (RPL). The Scheduling Function (SF) is a core IPv6 over the TSCH mode of IEEE 802.15.4 (6TiSCH) component, but the specification of the SF is an open research topic: numerous scientific articles investigated how QoS for a wide range of applications can be met by developing specialized SFs. However, no full-scale information exchange between the layers of the 6TiSCH stack was considered to optimize the SFs and to improve the network performance. In this work, we propose a novel solution named 6TiSCH-CLX to satisfy demanding QoS requirements using cross-layer communication. It is an extension of the 6TiSCH framework at the network and Medium Access Control (MAC) layers, addressing latency and reliability challenges agnostic of the physical layer. 6TiSCH-CLX is evaluated both analytically and in simulations for several safety-critical avionic intra-communication use cases in WAIC. Preliminary results indicate considerable improvements to latency, while maintaining almost 100% Packet

In this work, nanostructured pectin aerogels were prepared via a sol-gel process and subsequent drying under supercritical conditions. To this end, three commercially available citrus pectins and an in-house produced and enzymatically modified watermelon rind pectin (WRP) were compared. Then, the effect of pectin's structure and composition on the aerogel properties were analysed and its potential application as a delivery system was explored by impregnating them with vanillin. Results showed that the molecular weight, degree of esterification and branching degree of the pectin samples played a main role in the production of hydrogels and subsequent aerogels. The developed aerogel particles showed high specific surface areas (468–584 m2/g) and low bulk density (0.025–0.10 g/cm3). The shrinkage effect during aerogel formation was significantly affected by the pectin concentration and structure, while vanillin loading in aerogels and its release profile was also seen to be influenced by the affinity between pectin and vanillin. Furthermore, the results highlight the interest of WRP as a carrier of active compounds which might have potential application in food and biomedical areas, among others.

The growing market for fiber-reinforced thermoplastics (FRTP) requires new flexible production processes for prototype and small series production, as conventional forming techniques involving molds are not cost efficient in these cases. Inspired by incremental sheet metal forming (ISF), an alternative manufacturing processes for the forming of FRTP with just two robot guided standard tools is outlined. To maintain a locally formed shape in the heated, flexible fabric, auxiliary wire mesh metal is used as it has similar deformation mechanisms, especially shearability, while being sufficiently self-supporting. Feasibility of the approach is discussed and investigated in basic experiments., Bundesministerium für Wirtschaft und Klimaschutz (BMWK)

The demand for lightweight materials, such as fiber-reinforced plastics (FRP), is constantly growing. However, current FRP production mostly relies on expensive molds representing the final part geometry, which is not economical for prototyping or highly individualized products, such as in the medical or sporting goods sector. Therefore, inspired by incremental sheet metal forming, we conduct a systematic functional analysis on new processing methods for shaping woven FRP without the use of molds. Considering different material combinations, such as dry fabric with thermoset resin, thermoset prepreg, thermoplastic commingled yarn weave and organo sheets, we propose potential technical implementations of novel dieless forming techniques, making use of simple robot-guided standard tools, such as hemispherical tool tips or rollers. Feasibility of selected approaches is investigated in basic practical experiments with handheld tools. Results show that the main challenge of dieless local forming, the conservation of already formed shapes while allowing drapability of remaining areas, is best fulfilled by local impregnation, consolidation and solidification of commingled yarn fabric, as well as concurrent forming of prepreg and metal wire mesh support material. Further research is proposed to improve part quality., Bundesministerium für Wirtschaft und Klimaschutz (BMWK)

Abstrakt Das Verstehen und Beschreiben der Wechselwirkungen zwischen gelösten Stoffen in einer fluiden Phase und Feststoffen spielt eine gewichtige Rolle bei der Auslegung grüner Prozesse, in denen überkritisches CO2 (sc-CO2) als Lösungsmittel genutzt wird. In dieser Arbeit wird mit Hilfe der überkritischen-Fluid-Chromatographie (SFC) die Thermodynamik ebensolcher Systeme untersucht. Dabei wird eine große Bandbreite an polaren und nicht-polaren Stoffen mit Methanol als Begleitstoff versetzt. Die Retentionsergebnisse für mehrere Systeme auf vier unterschiedlichen Silika-Matrizen sind für unterschiedlichen Konzentrationen von beigefügten Stoffen, Drücken und Temperaturen bestimmt worden. Zusätzlich sind zwei unterschiedliche Typen von Retentionsmodellen entwickelt worden mit dem Ziel, eine möglichst hohe Genauigkeit der Wechselwirkungen zwischen den gelösten Stoffen und dem Feststoff in sc-CO2. Das erste Modell legt den Fokus auf die Eigenschaften des gelösten Stoffes und das zweite auf den Einfluss des Begleitstoffs Methanol., Knowing the interactions between a solute and an adsorbent is of great importance for the design of various green processes which utilize supercritical carbon dioxide (sc-CO2) as a solvent. In this work, by means of supercritical fluid chromatography (SFC) the thermodynamics of such systems have been studied. A wide range of polar and nonpolar solutes was used whereas methanol acted as the modifier. The retention data for various systems on four silica matrices was collected at various pressures, temperatures and modifier concentrations by SFC. Subsequently, two different types of retention models, one focusing on solute properties and the other modifier effects, were developed with the goal to generate a more accurate description of the solute-solid-interactions in sc-CO2.

Presentation about the cost and potential of green hydrogen production in the European catchment area

Technology development opens up for new possibilities to facilitate the production processes through digital information systems. To optimize the systems’ value, the form, content, and medium must fit the needs of the workers. This article aims to contribute to the discussion on value, use and design of digital assistance systems for production. It presents empirical data from a case study at a Norwegian shipyard, on production workers’ perception of coordinative challenges, and the value (including content) of digital assistance systems in complex shipbuilding projects. A quantitative survey among supervisors and operators at the shop floor was conducted twice due to different circumstances at the yard. These variations in circumstances are valuable to enable an evaluation of the workers’ perception of coordinative challenges and digital solutions in different situations. The findings indicate a pronounced positive attitude towards the potential of digital systems. Moreover, the role of supervisors and operators in coordinative challenges leads to different requirements to the solutions. The results from this study will have both industrial and scientific implications, as they provide valuable insights to help develop user-friendly systems that aid both workers and the company in terms of efficiency and accurate communication.

Disruptions inevitably occur in the project execution of complex one-off projects (Fischäder 2007). They cause effort and costs and, in many cases, delay the progress of the project. Nevertheless, in practice, disruption management is often inadequate ..., Bundesministerium für Wirtschaft und Klimaschutz (BMWK), Deutsches Zentrum für Luft- und Raumfahrt (DLR)