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Buniatyan, V. V. ; Huck, Christina ; Poghossian, Arshak ; Schöning, Michael Josef ; Rustamyan, L. G. ; Hovnikyan, H. H.
Fields of asymmetric tensors play an important role in many applications such as medical imaging (diffusion tensor magnetic resonance imaging), physics, and civil engineering (for example Cauchy-Green-deformation tensor, strain tensor with local rotations, etc.). However, such asymmetric tensors are usually symmetrized and then further processed. Using this procedure results in a loss of information. A new method for the processing of asymmetric tensor fields is proposed restricting our attention to tensors of second-order given by a 2x2 array or matrix with real entries. This is achieved by a transformation resulting in Hermitian matrices that have an eigendecomposition similar to symmetric matrices. With this new idea numerical results for real-world data arising from a deformation of an object by external forces are given. It is shown that the asymmetric part indeed contains valuable information.
Industrial facilities must be thoroughly designed to withstand seismic actions as they exhibit an increased loss potential due to the possibly wideranging damage consequences and the valuable process engineering equipment. Past earthquakes showed the social and political consequences of seismic damage to industrial facilities and sensitized the population and politicians worldwide for the possible hazard emanating from industrial facilities. However, a holistic approach for the seismic design of industrial facilities can presently neither be found in national nor in international standards. The introduction of EN 1998-4 of the new generation of Eurocode 8 will improve the normative situation with
specific seismic design rules for silos, tanks and pipelines and secondary process components. The article presents essential aspects of the seismic design of industrial facilities based on the new generation of Eurocode 8 using the example of tank structures and secondary process components. The interaction effects of the process components with the primary structure are illustrated by means of the experimental results of a shaking table test of a three story moment resisting steel frame with different process components. Finally, an integrated approach of
digital plant models based on building information modelling (BIM) and structural health monitoring (SHM) is presented, which provides not only a reliable decision-making basis for operation, maintenance and repair but also an excellent tool for rapid assessment of seismic damage.
Nowadays modern high-performance buildings and facilities are equipped with monitoring systems and sensors to control building characteristics like energy consumption, temperature pattern and structural safety. The visualization and interpretation of sensor data is typically based on simple spreadsheets and non-standardized user-oriented solutions, which makes it difficult for building owners, facility managers and decision-makers to evaluate and understand the data. The solution of this problem in the future are integrated BIM-Sensor approaches which allow the generation of BIM models incorporating all relevant information of monitoring systems. These approaches support both the dynamic visualization of key structural performance parameters, the effective long-term management of sensor data based on BIM and provide a user-friendly interface to communicate with various stakeholders. A major benefit for the end user is the use of the BIM software architecture, which is the future standard anyway. In the following, the application of the integrated BIM-Sensor approach is illustrated for a typical industrial facility as a part of an early warning and rapid response system for earthquake events currently developed in the research project “ROBUST” with financial support by the German Federal Ministry for Economic Affairs and Energy (BMWI).
Butenweg, Christoph ; Bursi, Oreste S. ; Nardin, Chiara ; Lanese, Igor ; Pavese, Alberto ; Marinković, Marko ; Paolacci, Fabrizio ; Quinci, Gianluca
Past earthquakes demonstrated the high vulnerability of industrial facilities equipped with complex process technologies leading to serious damage of the process equipment and multiple and simultaneous release of hazardous substances in industrial facilities. Nevertheless, the design of industrial plants is inadequately described in recent codes and guidelines, as they do not consider the dynamic interaction between the structure and the installations and thus the effect of seismic response of the installations on the response of the structure and vice versa. The current code-based approach for the seismic design of industrial facilities is considered not enough for ensure proper safety conditions against exceptional event entailing loss of content and related consequences. Accordingly, SPIF project (Seismic Performance of Multi-Component Systems in Special Risk Industrial Facilities) was proposed within the framework of the European H2020 - SERA funding scheme (Seismology and Earthquake Engineering Research Infrastructure Alliance for Europe). The objective of the SPIF project is the investigation of the seismic behaviour of a representative industrial structure equipped with complex process technology by means of shaking table tests. The test structure is a three-story moment resisting steel frame with vertical and horizontal vessels and cabinets, arranged on the three levels and connected by pipes. The dynamic behaviour of the test structure and of its relative several installations is investigated. Furthermore, both process components and primary structure interactions are considered and analyzed. Several PGA-scaled artificial ground motions are applied to study the seismic response at different levels. After each test, dynamic identification measurements are carried out to characterize the system condition. The contribution presents the experimental setup of the investigated structure and installations, selected measurement data and describes the obtained damage. Furthermore, important findings for the definition of performance limits, the effectiveness of floor response spectra in industrial facilities will be presented and discussed.
Reinforced concrete (RC) frames with masonry infills are frequently used in seismic regions all over the world. Generally masonry infills are considered as nonstructural elements and thus are typically neglected in the design process. However, the observations made after strong earthquakes have shown that masonry infills can modify the dynamic behavior of the structure significantly. The consequences were total collapses of buildings and loss of human lives. This paper presents the new system INODIS (Innovative Decoupled Infill System) developed within the European research project INSYSME (Innovative Systems for Earthquake Resistant Masonry Enclosures in RC Buildings). INODIS decouples the frame and the masonry infill by means of special U-shaped rubbers placed in between frame and infill. The effectiveness of the system was investigated by means of full scale tests on RC frames with masonry infills subjected to in-plane and out-of-plane loading. Furthermore small specimen tests were conducted to determine material characteristics of the components and the resistances of the connections. Finally, a micromodel was developed to simulate the in-plane behavior of RC frames infilled with AAC blocks with and without installation of the INODIS system.
Butenweg, Christoph ; Marinković, Marko ; Kubalski, Thomas ; Fehling, Ekkehard ; Pfetzing, Thomas ; Meyer, Udo
Butenweg, Christoph ; Marinković, Marko ; Pavese, Alberto ; Lanese, Igor ; Hoffmeister, Benno ; Pinkawa, Marius ; Vulcu, Mihai-Cristian ; Bursi, Oreste ; Nardin, Chiara ; Paolacci, Fabrizio ; Quinci, Gianluca ; Fragiadakis, Michalis ; Weber, Felix ; Huber, Peter ; Renault, Philippe ; Gündel, Max ; Dyke, Shirley ; Ciucci, M. ; Marino, A.
Past earthquakes demonstrated the high vulnerability of industrial facilities equipped with complex process technologies leading to serious damage of the process equipment and multiple and simultaneous release of hazardous substances in industrial facilities. Nevertheless, the design of industrial plants is inadequately described in recent codes and guidelines, as they do not consider the dynamic interaction between the structure and the installations and thus the effect of seismic response of the installations on the response of the structure and vice versa. The current code-based approach for the seismic design of industrial facilities is considered not enough for ensure proper safety conditions against exceptional event entailing loss of content and related consequences. Accordingly, SPIF project (Seismic Performance of Multi- Component Systems in Special Risk Industrial Facilities) was proposed within the framework of the European H2020 - SERA funding scheme (Seismology and Earthquake Engineering Research Infrastructure Alliance for Europe). The objective of the SPIF project is the investigation of the seismic behavior of a representative industrial structure equipped with complex process technology by means of shaking table tests. The test structure is a three-story moment resisting steel frame with vertical and horizontal vessels and cabinets, arranged on the three levels and connected by pipes. The dynamic behavior of the test structure and installations is investigated with and without base isolation. Furthermore, both firmly anchored and isolated components are taken into account to compare their dynamic behavior and interactions with each other. Artificial and synthetic ground motions are applied to study the seismic response at different PGA levels. After each test, dynamic identification measurements are carried out to characterize the system condition. The contribution presents the numerical simulations to calibrate the tests on the prototype, the experimental setup of the investigated structure and installations, selected measurement data and finally describes preliminary experimental results.
Butenweg, Christoph ; Meskouris, Konstantin ; Meister, Sylvia ; Dreyer, Stephan ; Schulte-Althoff, Christoph
Buxbaum, Bernd ; Schwarte, Rudolf ; Ringbeck, Thorsten ; Grothof, Markus ; Sluiter, A. ; Frey, Jochen ; Hildebrand, M. ; David, Klaus
Buxbaum, Bernd ; Schwarte, Rudolf ; Ringbeck, Thorsten ; Heinol, Horst-Guenther ; Xu, Z. ; Olk, J. ; Tai, W. ; Zhang, Z. ; Luan, X.
Buxbaum, Bernd ; Schwarte, Rudolf ; Xu, Zhanping ; Ringbeck, Thorsten ; Heinol, Horst-Guenther ; Schulte, J. ; Tai, W. ; Zhang, Z. ; Luan, X. ; Fricke, J.
A New Class of Biosensors Based on Tobacco Mosaic Virus and Coat Proteins as Enzyme Nanocarrier
(2016)
Bäcker, Matthias ; Koch, C. ; Geiger, F. ; Eber, F. ; Gliemann, H. ; Poghossian, Arshak ; Schöning, Michael Josef
Bäcker, Matthias ; Schusser, Sebastian ; Leinhos, Marcel ; Poghossian, Arshak ; Schöning, Michael Josef
Sensor positioning and thermal model for condition monitoring of pressure gas reservoirs in vehicles
(2018)
Messenger apps like WhatsApp or Telegram are an integral part of daily communication. Besides the various positive effects, those services extend the operating range of criminals. Open trading groups with many thousand participants emerged on Telegram. Law enforcement agencies monitor suspicious users in such chat rooms. This research shows that text analysis, based on natural language processing, facilitates this through a meaningful domain overview and detailed investigations. We crawled a corpus from such self-proclaimed black markets and annotated five attribute types products, money, payment methods, user names, and locations. Based on each message a user sends, we extract and group these attributes to build profiles. Then, we build features to cluster the profiles. Pretrained word vectors yield better unsupervised clustering results than current
state-of-the-art transformer models. The result is a semantically meaningful high-level overview of the user landscape of black market chatrooms. Additionally, the extracted structured information serves as a foundation for further data exploration, for example, the most active users or preferred payment methods.
Messenger apps like WhatsApp and Telegram are frequently used for everyday communication, but they can also be utilized as a platform for illegal activity. Telegram allows public groups with up to 200.000 participants. Criminals use these public groups for trading illegal commodities and services, which becomes a concern for law enforcement agencies, who manually monitor suspicious activity in these chat rooms. This research demonstrates how natural language processing (NLP) can assist in analyzing these chat rooms, providing an explorative overview of the domain and facilitating purposeful analyses of user behavior. We provide a publicly available corpus of annotated text messages with entities and relations from four self-proclaimed black market chat rooms. Our pipeline approach aggregates the extracted product attributes from user messages to profiles and uses these with their sold products as features for clustering. The extracted structured information is the foundation for further data exploration, such as identifying the top vendors or fine-granular price analyses. Our evaluation shows that pretrained word vectors perform better for unsupervised clustering than state-of-the-art transformer models, while the latter is still superior for sequence labeling.
A laser-enhanced solar sail is a solar sail that is not solely propelled by solar radiation but additionally by a laser beam that illuminates the sail. This way, the propulsive acceleration of the sail results from the combined action of the solar and the laser radiation pressure onto the sail. The potential source of the laser beam is a laser satellite that coverts solar power (in the inner solar system) or nuclear power (in the outer solar system) into laser power. Such a laser satellite (or many of them) can orbit anywhere in the solar system and its optimal orbit (or their optimal orbits) for a given mission is a subject for future research. This contribution provides the model for an ideal laser-enhanced solar sail and investigates how a laser can enhance the thrusting capability of such a sail. The term ”ideal” means that the solar sail is assumed to be perfectly reflecting and that the laser beam is assumed to have a constant areal power density over the whole sail area. Since a laser beam has a limited divergence, it can provide radiation pressure at much larger solar distances and increase the radiation pressure force into the desired direction. Therefore, laser-enhanced solar sails may make missions feasible, that would otherwise have prohibitively long flight times, e.g. rendezvous missions in the outer solar system. This contribution will also analyze exemplary mission scenarios and present optimial trajectories without laying too much emphasis on the design and operations of the laser satellites. If the mission studies conclude that laser-enhanced solar sails would have advantages with respect to ”traditional” solar sails, a detailed study of the laser satellites and the whole system architecture would be the second next step
Chajan, Eduard ; Schulte-Tigges, Joschua ; Reke, Michael ; Ferrein, Alexander ; Matheis, Dominik ; Walter, Thomas
One central challenge for self-driving cars is a proper path-planning. Once a trajectory has been found, the next challenge is to accurately and safely follow the precalculated path. The model-predictive controller (MPC) is a common approach for the lateral control of autonomous vehicles. The MPC uses a vehicle dynamics model to predict the future states of the vehicle for a given prediction horizon. However, in order to achieve real-time path control, the computational load is usually large, which leads to short prediction horizons. To deal with the computational load, the control algorithm can be parallelized on the graphics processing unit (GPU). In contrast to the widely used stochastic methods, in this paper we propose a deterministic approach based on grid search. Our approach focuses on systematically discovering the search area with different levels of granularity. To achieve this, we split the optimization algorithm into multiple iterations. The best sequence of each iteration is then used as an initial solution to the next iteration. The granularity increases, resulting in smooth and predictable steering angle sequences. We present a novel GPU-based algorithm and show its accuracy and realtime abilities with a number of real-world experiments.