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Jahresbericht 2019
(2019)
BIM im Membranbau
(2019)
Die fortschreitende Digitalisierung wird zurzeit zu einem der wichtigsten Themen und zugleich zu einer der größten Herausforderungen für die Bauwirtschaft. Building Information Modeling (BIM) kommt eine immer größere Bedeutung zu.
Es ist sicherlich richtig, dass derzeit nur wenige Projekte im Bauwesen den geforderten BIM-Anforderungen der Bauherrschaft genügen. Es ist zu erwarten, dass in den kommenden Jahren auch an Membranbauprojekte immer mehr Anforderungen bezüglich BIM gestellt werden. Aus diesem Grund ist es wichtig, dass sich Planungsbüros für leichte Flächentragwerke mit dem Thema BIM befassen.
Ziel dieser Arbeit ist die Ausarbeitung eines Konzepts für die effiziente durchgehende Umsetzung der Building Information Modeling-Arbeitsmethode bei der Tragwerksplanung im Membranbau.
Es werden vorhandene Funktionalitäten untersucht und alternative Interoperabilitätskomponenten entwickelt. Aufbauend auf den möglichen Werkzeugketten werden verschiedene Einsatzverfahren vorgeschlagen. Darauffolgend wird eines der möglichen Verfahren an einem realen Tragwerk implementiert. Die erhaltenen Ergebnisse werden einer kritischen Analyse unterzogen.
Abschließende Rückschlüsse, Beurteilung der angewandten Planungsmethoden und Ausblick fassen das behandelte Thema zusammen.
Bei der Arbeit verwendete Methoden schließen den parametrischen Entwurf, manuelle Modellierung in zwei verschiedenen Softwareumgebungen und textliche Programmierung mit C#-Sprache ein.
Die Relevanz des untersuchten Themas erstreckt sich überwiegend auf praktisch tätige Ingenieure aus den Bereichen leichte Flächentragwerke, Sondertragwerke, Membranbau, wird aber auch für wissenschaftliche Mitarbeiter der Forschungsinstitutionen, BIM-Spezialisten und Produkthersteller von Interesse sein.
Das Potential der Offshore-Windenergie, welches hauptsächlich auf hohe mittlere Windgeschwindigkeiten zurückzuführen ist, kann nicht ignoriert werden. Trotzdem zeigt die Betrachtung der aktuell installierten Leistung und der Stromgestehungskosten, dass zusätzliche Risiko- und Kostenfaktoren existieren. Diese sind vor allem auf die Installation, die Energiewandlersysteme und die Netzanbindung zurückzuführen. Getriebeschäden sind einer dieser großen Kostenfaktoren. Aus diesem Grund gewinnen getriebelosen Windkraftanlagen mit permanentmagneterregten Synchrongeneratoren immer mehr an Relevanz. In der Netzanbindung von ganzen Offshore-Windparks überwiegt die Hochspannungs-Gleichstrom-Übertragung (HGÜ) ab einer Übertragungsdistanz von 80 km. Diese Tendenz ist sinkend. Steigende windparkinterne Spannungen auf 66 kV fördern zusätzlich den Verzicht auf Umspannplattformen, welche für die HGÜ-Technik aktuell sinnvoll sind. Diese und weitere bereits in Aussicht stehenden Entwicklungen führen zu einer Einschränkung der Risiko- und Kostenfaktoren. Es wird demnach davon ausgegangen, dass die Offshore-Windenergie, als Ergänzung zur Onshore-Windenergie, eine wichtige Rolle im Rahmen der Energiewende einnimmt.
CO2 compensation measures, in particular the compensation of flights, are becoming more and more popular. Carbon offsetting is defined as measures financed by donations that save greenhouse gases previously emitted elsewhere through climate protection projects.
CO2 abatement costs are often low in developing countries. This is why most offset projects are implemented there. Nevertheless, this does not mean that the holiday resort and the project country are in any way related to each other.
By linking carbon offset projects with the destination country, the tourist is able to get an impression of the co-financed project. In case such projects are realized in cooperation with the hotel, the hotel operator obtains a new tourist attraction and can demonstrate its efforts to climate protection in a PR-effective way.
Thermal shape memory alloys show extraordinary material properties and can be used as actuators, dampers and sensors. Since their discovery in the middle of the last century they have been investigated and further developed. The majority of the industrial applications with the highest material sales can still be found in the medical industry, where they are used due to their superelastic and thermal shape memory effect, e.g. as stents or as guidewires and tools in the minimal invasive surgery. Particularly in recent years, more and more applications have been developed for other industrial fields, e.g. for the household goods, civil engineering and automotive sector. In this context it is worth mentioning that for the latter sector, million seller series applications have found their way into some European automobile manufacturers. The German VDI guideline for shape memory alloys introduced in 2017 will give the material a further boost in application. Last but not least the new production technologies of additive manufacturing with metal laser sintering plants open up additional applications for these multifunctional materials. This paper gives an overview of the extraordinary material properties of shape memory components, shows examples of different applications and discusses European trends against the background of the most recent standard and new production technologies.
Fatigue and drowsiness are responsible for a significant percentage of road traffic accidents. There are several approaches to monitor the driver’s drowsiness, ranging from the driver’s steering behavior to analysis of the driver, e.g. eye tracking, blinking, yawning or electrocardiogram (ECG). This paper describes the development of a low-cost ECG sensor to derive heart rate variability (HRV) data for the drowsiness detection. The work includes the hardware and the software design. The hardware has been implemented on a printed circuit board (PCB) designed so that the board can be used as an extension shield for an Arduino. The PCB contains a double, inverted ECG channel including low-pass filtering and provides two analog outputs to the Arduino, that combined them and performs the analog-to-digital conversion. The digital ECG signal is transferred to an NVidia embedded PC where the processing takes place, including QRS-complex, heart rate and HRV detection as well as visualization features. The compact resulting sensor provides good results in the extraction of the main ECG parameters. The sensor is being used in a larger frame, where facial-recognition-based drowsiness detection is combined with ECG-based detection to improve the recognition rate under unfavorable light or occlusion conditions.
In the field of autonomously driving vehicles the environment perception containing dynamic objects like other road users is essential. Especially, detecting other vehicles in the road traffic using sensor data is of utmost importance. As the sensor data and the applied system model for the objects of interest are noise corrupted, a filter algorithm must be used to track moving objects. Using LIDAR sensors one object gives rise to more than one measurement per time step and is therefore called extended object. This allows to jointly estimate the objects, position, as well as its orientation, extension and shape. Estimating an arbitrary shaped object comes with a higher computational effort than estimating the shape of an object that can be approximated using a basic geometrical shape like an ellipse or a rectangle. In the case of a vehicle, assuming a rectangular shape is an accurate assumption.
A recently developed approach models the contour of a vehicle as periodic B-spline function. This representation is an easy to use tool, as the contour can be specified by some basis points in Cartesian coordinates. Also rotating, scaling and moving the contour is easy to handle using a spline contour. This contour model can be used to develop a measurement model for extended objects, that can be integrated into a tracking filter. Another approach modeling the shape of a vehicle is the so-called bounding box that represents the shape as rectangle.
In this thesis the basics of single, multi and extended object tracking, as well as the basics of B-spline functions are addressed. Afterwards, the spline measurement model is established in detail and integrated into an extended Kalman filter to track a single extended object. An implementation of the resulting algorithm is compared with the rectangular shape estimator. The implementation of the rectangular shape estimator is provided. The comparison is done using long-term considerations with Monte Carlo simulations and by analyzing the results of a single run. Therefore, both algorithms are applied to the same measurements. The measurements are generated using an artificial LIDAR sensor in a simulation environment.
In a real-world tracking scenario detecting several extended objects and measurements that do not originate from a real object, named clutter measurements, is possible. Also, the sudden appearance and disappearance of an object is possible. A filter framework investigated in recent years that can handle tracking multiple objects in a cluttered environment is a random finite set based approach. The idea of random finite sets and its use in a tracking filter is recapped in this thesis. Afterwards, the spline measurement model is included in a multi extended object tracking framework. An implementation of the resulting filter is investigated in a long-term consideration using Monte Carlo simulations and by analyzing the results of a single run. The multi extended object filter is also applied to artificial LIDAR measurements generated in a simulation environment.
The results of comparing the spline based and rectangular based extended object trackers show a more stable performance of the spline extended object tracker. Also, some problems that have to be addressed in future works are discussed. The investigation of the resulting multi extended object tracker shows a successful integration of the spline measurement model in a multi extended object tracker. Also, with these results some problems remain, that have to be solved in future works.
This thesis deals with the object tracking problem of multiple extended objects. For instance, this tracking problem occurs when a car with sensors drives on the road and detects multiple other cars in front of it. When the setup between the senor and the other cars is in a such way that multiple measurements are created by each single car, the cars are called extended objects. This can occur in real world scenarios, mainly with the use of high resolution sensors in near field applications. Such a near field scenario leads a single object to occupy several resolution cells of the sensor so that multiple measurements are generated per scan. The measurements are additionally superimposed by the sensor’s noise. Beside the object generated measurements, there occur false alarms, which are not caused by any object and sometimes in a sensor scan, single objects could be missed so that they not generate any measurements.
To handle these scenarios, object tracking filters are needed to process the sensor measurements in order to obtain a stable and accurate estimate of the objects in each sensor scan. In this thesis, the scope is to implement such a tracking filter that handles the extended objects, i.e. the filter estimates their positions and extents. In context of this, the topic of measurement partitioning occurs, which is a pre-processing of the measurement data. With the use of partitioning, the measurements that are likely generated by one object are put into one cluster, also called cell. Then, the obtained cells are processed by the tracking filter for the estimation process. The partitioning of measurement data is a crucial part for the performance of tracking filter because insufficient partitioning leads to bad tracking performance, i.e. inaccurate object estimates.
In this thesis, a Gaussian inverse Wishart Probability Hypothesis Density (GIW-PHD) filter was implemented to handle the multiple extended object tracking problem. Within this filter framework, the number of objects are modelled as Random Finite Sets (RFSs) and the objects’ extent as random matrices (RM). The partitioning methods that are used to cluster the measurement data are existing ones as well as a new approach that is based on likelihood sampling methods. The applied classical heuristic methods are Distance Partitioning (DP) and Sub-Partitioning (SP), whereas the proposed likelihood-based approach is called Stochastic Partitioning (StP). The latter was developed in this thesis based on the Stochastic Optimisation approach by Granström et al. An implementation, including the StP method and its integration into the filter framework, is provided within this thesis.
The implementations, using the different partitioning methods, were tested on simulated random multi-object scenarios and in a fixed parallel tracking scenario using Monte Carlo methods. Further, a runtime analysis was done to provide an insight into the computational effort using the different partitioning methods. It emphasized, that the StP method outperforms the classical partitioning methods in scenarios, where the objects move spatially close. The filter using StP performs more stable and with more accurate estimates. However, this advantage is associated with a higher computational effort compared to the classical heuristic partitioning methods.
Nachhaltigkeit stellt seit 2018 einen der bedeutsamsten Trends in der Modeindustrie da. Die Missstände innerhalb der Textil- und Bekleidungsindustrie wurden seit dem Einsturz einer Textilfabrik in Bangladesch im Jahre 2013 zu einer öffentlichen Diskussion. Die global ausgerichtete Industrie produziert vermehrt Textilien in kürzester Zeit, um beständig das Angebot an aktuellen Modetrends anbieten zu können. Die sogenannte Fast-Fashion wird von großen Markenkonzernen wie ZARA und Hennes & Mauritz (H&M) zu niedrigen Preisen der breiten Masse zugänglich gemacht. Sie wird als einer der größten Gründe für Überkonsum von Bekleidung und sinkender Wertschätzung dieser Waren bezeichnet. Die Gegenbewegung Slow-Fashion möchte hingegen die Konsumenten davon überzeugen, ihre Bekleidung wieder wertzuschätzen. Slow-Fashion steht für Bekleidung, die unter umweltverträglichen und menschenwürdigen Bedingungen produziert wird. Durch die Gewährleistung von Transparenz hinsichtlich der Produktionsbedingungen und Lieferketten ermöglicht Slow-Fashion einen bewussteren Konsum von Mode.
Durch Slow-Fashion kann die Integration von Nachhaltigkeit in die Bekleidungsindustrie als einen Modetrend des vergangenen Jahres angesehen werden. Allerdings verstehen nachhaltige Bekleidungsmarken Slow-Fashion nicht als zeitgemäßen Trend, sondern vielmehr als Grundbedingung ihrer angebotenen Waren. Dieses Prinzip lässt sich auf Marken sämtlicher Branchen übertragen, sodass sie als ‚nachhaltige Marken‘ tituliert werden könnten. Bislang mangelt es allerdings an einer einheitlichen Definition für nachhaltige Marken. Das Ziel dieser Arbeit ist daher die Erarbeitung eines Definitionsvorschlags. Dabei muss die Bedeutung von Marken und das Prinzip der Nachhaltigkeit voneinander isoliert erörtert werden. Anschließend soll die Schuhmarke ZWEIGUT, die als ein Beispiel aus der Bekleidungsindustrie dient, daraufhin überprüft werden, ob sie dem Anspruch der ausgearbeiteten Definition einer nachhaltigen Marke gerecht wird. Im Laufe dieser Markenanalyse sollen zugleich die Erfolgsbausteine der Marke ZWEIGUT bestimmt werden.
If the process contains a delay (dead time), the Nyquist criterion is well suited to derive a PI or PID tuning rule because the delay is taken into account without approximation. The tuning of the speed of the closed loop enters naturally by the crossover frequency. The goal of robustness and performance is translated into the phase margin.
This paper analyses international cooperation in alternative energy production research and development. Therefore, patents of the technological domain, registered at the European Patent Office from 1997 until 2016, are analysed. International cooperation is considered when patents involve co-assignment or co-inventorship comprising two or more different countries. Generally, international R&D cooperation tends to be increasing over time in alternative energy production. In total, 2234 co-patents from 87 countries are identified. Through social network analysis the cooperative relationships between countries are examined. The most significant states of the network are the United States of America and Germany. Innovative clusters and strong partnerships are identified. Alternative energy technologies that involve international cooperation most extensively are harnessing energy from manmade waste, solar energy and bio-fuels. The paper clarifies which countries are cooperating with each other for what purpose. The findings can be used for establishing R&D strategies in the domain of alternative energy production.