TY - CHAP ED - Steiner, Maria ED - Theiler, Michael ED - Mirboland, Mahsa T1 - 30. Forum Bauinformatik N2 - Die Bauhaus-Universität Weimar ist seit langer Zeit mit dem Forum Bauinformatik eng verbunden. So wurde die Veranstaltung 1989 hier durch den Arbeitskreis Bauinformatik ins Leben gerufen und auch das 10. und 18. Forum Bauinformatik (1998 bzw. 2006) fand in Weimar statt. In diesem Jahr freuen wir uns daher besonders, das 30. Jubiläum an der Bauhaus-Universität Weimar ausrichten zu dürfen und viele interessierte Wissenschaftler und Wissenschaftlerinnen aus dem Bereich der Bauinformatik in Weimar willkommen zu heißen. Das Forum Bauinformatik hat sich längst zu einem festen Bestandteil der Bauinformatik im deutschsprachigen Raum entwickelt. Dabei steht es traditionsgemäß unter dem Motto „von jungen Forschenden für junge Forschende“, wodurch insbesondere Nachwuchswissenschaftlerinnen und ‑wissenschaftlern die Möglichkeit geboten wird, ihre Forschungsarbeiten zu präsentieren, Problemstellungen fachspezifisch zu diskutieren und sich über den neuesten Stand der Forschung zu informieren. Zudem wird eine ausgezeichnete Gelegenheit geboten, in die wissenschaftliche Gemeinschaft im Bereich der Bauinformatik einzusteigen und Kontakte mit anderen Forschenden zu knüpfen. In diesem Jahr erhielten wir 49 interessante und qualitativ hochwertige Beiträge vor allem in den Themenbereichen Simulation, Modellierung, Informationsverwaltung, Geoinformatik, Structural Health Monitoring, Visualisierung, Verkehrssimulation und Optimierung. Dafür möchten wir uns ganz besonders bei allen Autoren, Co-Autoren und Reviewern bedanken, die durch ihr Engagement das diesjährige Forum Bauinformatik erst möglich gemacht haben. Wir danken zudem Professor Große und Professor Díaz für die Unterstützung bei der Auswahl der Beiträge für die Best Paper Awards. Ein herzliches Dankeschön geht an die Kollegen an der Professur Informatik im Bauwesen der Bauhaus-Universität Weimar für die organisatorische, technische und beratende Unterstützung während der Planung der Veranstaltung. KW - Bauinformatik KW - BIM Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20180917-37854 N1 - Printausgabe: ISBN 978-3-00-060726-4 ER - TY - INPR A1 - Mosavi, Amir A1 - Torabi, Mehrnoosh A1 - Hashemi, Sattar A1 - Saybani, Mahmoud Reza A1 - Shamshirband, Shahaboddin T1 - A Hybrid Clustering and Classification Technique for Forecasting Short-Term Energy Consumption N2 - Electrical energy distributor companies in Iran have to announce their energy demand at least three 3-day ahead of the market opening. Therefore, an accurate load estimation is highly crucial. This research invoked methodology based on CRISP data mining and used SVM, ANN, and CBA-ANN-SVM (a novel hybrid model of clustering with both widely used ANN and SVM) to predict short-term electrical energy demand of Bandarabbas. In previous studies, researchers introduced few effective parameters with no reasonable error about Bandarabbas power consumption. In this research we tried to recognize all efficient parameters and with the use of CBA-ANN-SVM model, the rate of error has been minimized. After consulting with experts in the field of power consumption and plotting daily power consumption for each week, this research showed that official holidays and weekends have impact on the power consumption. When the weather gets warmer, the consumption of electrical energy increases due to turning on electrical air conditioner. Also, con-sumption patterns in warm and cold months are different. Analyzing power consumption of the same month for different years had shown high similarity in power consumption patterns. Factors with high impact on power consumption were identified and statistical methods were utilized to prove their impacts. Using SVM, ANN and CBA-ANN-SVM, the model was built. Sine the proposed method (CBA-ANN-SVM) has low MAPE 5 1.474 (4 clusters) and MAPE 5 1.297 (3 clusters) in comparison with SVM (MAPE 5 2.015) and ANN (MAPE 5 1.790), this model was selected as the final model. The final model has the benefits from both models and the benefits of clustering. Clustering algorithm with discovering data structure, divides data into several clusters based on similarities and differences between them. Because data inside each cluster are more similar than entire data, modeling in each cluster will present better results. For future research, we suggest using fuzzy methods and genetic algorithm or a hybrid of both to forecast each cluster. It is also possible to use fuzzy methods or genetic algorithms or a hybrid of both without using clustering. It is issued that such models will produce better and more accurate results. This paper presents a hybrid approach to predict the electric energy usage of weather-sensitive loads. The presented methodutilizes the clustering paradigm along with ANN and SVMapproaches for accurate short-term prediction of electric energyusage, using weather data. Since the methodology beinginvoked in this research is based on CRISP data mining, datapreparation has received a gr eat deal of attention in thisresear ch. Once data pre-processing was done, the underlyingpattern of electric energy consumption was extracted by themeans of machine learning methods to precisely forecast short-term energy consumption. The proposed approach (CBA-ANN-SVM) was applied to real load data and resulting higher accu-racy comparing to the existing models. 2018 American Institute of Chemical Engineers Environ Prog, 2018 https://doi.org/10.1002/ep.12934 KW - Data Mining KW - support vector machine (SVM) KW - Machine Learning KW - forecasting KW - Prediction KW - Electric Energy Consumption KW - clustering KW - artificial neural networks (ANN) Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20180907-37550 N1 - This is the pre-peer reviewed version of the following article: https://onlinelibrary.wiley.com/doi/10.1002/ep.12934, which has been published in final form at https://doi.org/10.1002/ep.12934. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. ER - TY - INPR A1 - Kavrakov, Igor A1 - Morgenthal, Guido T1 - A synergistic study of a CFD and semi-analytical models for aeroelastic analysis of bridges in turbulent wind conditions N2 - Long-span bridges are prone to wind-induced vibrations. Therefore, a reliable representation of the aerodynamic forces acting on a bridge deck is of a major significance for the design of such structures. This paper presents a systematic study of the two-dimensional (2D) fluid-structure interaction of a bridge deck under smooth and turbulent wind conditions. Aerodynamic forces are modeled by two approaches: a computational fluid dynamics (CFD) model and six semi-analytical models. The vortex particle method is utilized for the CFD model and the free-stream turbulence is introduced by seeding vortex particles upstream of the deck with prescribed spectral characteristics. The employed semi-analytical models are based on the quasi-steady and linear unsteady assumptions and aerodynamic coefficients obtained from CFD analyses. The underlying assumptions of the semi-analytical aerodynamic models are used to interpret the results of buffeting forces and aeroelastic response due to a free-stream turbulence in comparison with the CFD model. Extensive discussions are provided to analyze the effect of linear fluid memory and quasi-steady nonlinearity from a CFD perspective. The outcome of the analyses indicates that the fluid memory is a governing effect in the buffeting forces and aeroelastic response, while the effect of the nonlinearity is overestimated by the quasi-steady models. Finally, flutter analyses are performed and the obtained critical velocities are further compared with wind tunnel results, followed by a brief examination of the post-flutter behavior. The results of this study provide a deeper understanding of the extent of which the applied models are able to replicate the physical processes for fluid-structure interaction phenomena in bridge aerodynamics and aeroelasticity. KW - Ingenieurwissenschaften KW - Aerodynamik KW - Bridge KW - Aerodynamic nonlinearity KW - Fluid memory KW - Vortex particle method KW - Buffeting KW - Flutter Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200206-40873 N1 - This is the pre-peer reviewed version of the following article: https://www.sciencedirect.com/science/article/abs/pii/S0889974617308423?via%3Dihub, which has been published in final form at https://doi.org/10.1016/j.jfluidstructs.2018.06.013 ER - TY - INPR A1 - Kavrakov, Igor A1 - Morgenthal, Guido T1 - Aeroelastic analyses of bridges using a Pseudo-3D vortex method and velocity-based synthetic turbulence generation N2 - The accurate representation of aerodynamic forces is essential for a safe, yet reasonable design of long-span bridges subjected to wind effects. In this paper, a novel extension of the Pseudo-three-dimensional Vortex Particle Method (Pseudo-3D VPM) is presented for Computational Fluid Dynamics (CFD) buffeting analysis of line-like structures. This extension entails an introduction of free-stream turbulent fluctuations, based on the velocity-based turbulence generation. The aerodynamic response of a long-span bridge is obtained by subjecting the 3D dynamic representation of the structure to correlated free-stream turbulence in two-dimensional (2D) fluid planes, which are positioned along the bridge deck. The span-wise correlation of the free-stream turbulence between the 2D fluid planes is established based on Taylor's hypothesis of frozen turbulence. Moreover, the application of the laminar Pseudo-3D VPM is extended to a multimode flutter analysis. Finally, the structural response from the Pseudo-3D flutter and buffeting analyses is verified with the response, computed using the semi-analytical linear unsteady model in the time-domain. Meaningful merits of the turbulent Pseudo-3D VPM with respect to the linear unsteady model are the consideration of the 2D aerodynamic nonlinearity, nonlinear fluid memory, vortex shedding and local non-stationary turbulence effects in the aerodynamic forces. The good agreement of the responses for the two models in the 3D analyses demonstrates the applicability of the Pseudo-3D VPM for aeroelastic analyses of line-like structures under turbulent and laminar free-stream conditions. KW - Bridge KW - Aerodynamik KW - Ingenieurwissenschaften KW - Computational Bridge Aerodynamics KW - Buffeting KW - Flutter KW - Long-span Bridges KW - Vortex Particle Method Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200206-40864 N1 - This is the pre-peer reviewed version of the following article: https://www.sciencedirect.com/science/article/pii/S0141029617322976?via%3Dihub, which has been published in final form at https://doi.org/10.1016/j.engstruct.2018.08.093 ER - TY - THES A1 - Kaltenbrunner, Martin T1 - An Abstraction Framework for Tangible Interactive Surfaces N2 - This cumulative dissertation discusses - by the example of four subsequent publications - the various layers of a tangible interaction framework, which has been developed in conjunction with an electronic musical instrument with a tabletop tangible user interface. Based on the experiences that have been collected during the design and implementation of that particular musical application, this research mainly concentrates on the definition of a general-purpose abstraction model for the encapsulation of physical interface components that are commonly employed in the context of an interactive surface environment. Along with a detailed description of the underlying abstraction model, this dissertation also describes an actual implementation in the form of a detailed protocol syntax, which constitutes the common element of a distributed architecture for the construction of surface-based tangible user interfaces. The initial implementation of the presented abstraction model within an actual application toolkit is comprised of the TUIO protocol and the related computer-vision based object and multi-touch tracking software reacTIVision, along with its principal application within the Reactable synthesizer. The dissertation concludes with an evaluation and extension of the initial TUIO model, by presenting TUIO2 - a next generation abstraction model designed for a more comprehensive range of tangible interaction platforms and related application scenarios. KW - Informatik KW - Human Computer Interaction KW - Benutzeroberfläche KW - Open Source KW - Mensch-Maschine-Kommunikation KW - Tangible User Interfaces KW - Protocols Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20180205-37178 ER - TY - INPR A1 - Steiner, Maria A1 - Bourinet, Jean-Marc A1 - Lahmer, Tom T1 - An adaptive sampling method for global sensitivity analysis based on least-squares support vector regression N2 - In the field of engineering, surrogate models are commonly used for approximating the behavior of a physical phenomenon in order to reduce the computational costs. Generally, a surrogate model is created based on a set of training data, where a typical method for the statistical design is the Latin hypercube sampling (LHS). Even though a space filling distribution of the training data is reached, the sampling process takes no information on the underlying behavior of the physical phenomenon into account and new data cannot be sampled in the same distribution if the approximation quality is not sufficient. Therefore, in this study we present a novel adaptive sampling method based on a specific surrogate model, the least-squares support vector regresson. The adaptive sampling method generates training data based on the uncertainty in local prognosis capabilities of the surrogate model - areas of higher uncertainty require more sample data. The approach offers a cost efficient calculation due to the properties of the least-squares support vector regression. The opportunities of the adaptive sampling method are proven in comparison with the LHS on different analytical examples. Furthermore, the adaptive sampling method is applied to the calculation of global sensitivity values according to Sobol, where it shows faster convergence than the LHS method. With the applications in this paper it is shown that the presented adaptive sampling method improves the estimation of global sensitivity values, hence reducing the overall computational costs visibly. KW - Approximation KW - Sensitivitätsanalyse KW - Abtastung KW - Surrogate models KW - Least-squares support vector regression KW - Adaptive sampling method KW - Global sensitivity analysis KW - Sampling Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20181218-38320 N1 - This is the pre-peer reviewed version of the following article: https://www.sciencedirect.com/science/article/pii/S0951832017311808, which has been published in final form at https://doi.org/10.1016/j.ress.2018.11.015. SP - 1 EP - 33 ER - TY - JOUR A1 - Mosavi, Amir A1 - Najafi, Bahman A1 - Faizollahzadeh Ardabili, Sina A1 - Shamshirband, Shahaboddin A1 - Rabczuk, Timon T1 - An Intelligent Artificial Neural Network-Response Surface Methodology Method for Accessing the Optimum Biodiesel and Diesel Fuel Blending Conditions in a Diesel Engine from the Viewpoint of Exergy and Energy Analysis JF - Energies N2 - Biodiesel, as the main alternative fuel to diesel fuel which is produced from renewable and available resources, improves the engine emissions during combustion in diesel engines. In this study, the biodiesel is produced initially from waste cooking oil (WCO). The fuel samples are applied in a diesel engine and the engine performance has been considered from the viewpoint of exergy and energy approaches. Engine tests are performed at a constant 1500 rpm speed with various loads and fuel samples. The obtained experimental data are also applied to develop an artificial neural network (ANN) model. Response surface methodology (RSM) is employed to optimize the exergy and energy efficiencies. Based on the results of the energy analysis, optimal engine performance is obtained at 80% of full load in presence of B10 and B20 fuels. However, based on the exergy analysis results, optimal engine performance is obtained at 80% of full load in presence of B90 and B100 fuels. The optimum values of exergy and energy efficiencies are in the range of 25–30% of full load, which is the same as the calculated range obtained from mathematical modeling. KW - Biodiesel KW - ANN modeling KW - biodiesel KW - Artificial Intelligence KW - diesel engines KW - energy, exergy KW - mathematical modeling KW - OA-Publikationsfonds2018 Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20180507-37467 UR - http://www.mdpi.com/1996-1073/11/4/860 VL - 2018 IS - 11, 4 PB - MDPI CY - Basel ER - TY - INPR A1 - Rezakazemi, Mashallah A1 - Mosavi, Amir A1 - Shirazian, Saeed T1 - ANFIS pattern for molecular membranes separation optimization N2 - In this work, molecular separation of aqueous-organic was simulated by using combined soft computing-mechanistic approaches. The considered separation system was a microporous membrane contactor for separation of benzoic acid from water by contacting with an organic phase containing extractor molecules. Indeed, extractive separation is carried out using membrane technology where complex of solute-organic is formed at the interface. The main focus was to develop a simulation methodology for prediction of concentration distribution of solute (benzoic acid) in the feed side of the membrane system, as the removal efficiency of the system is determined by concentration distribution of the solute in the feed channel. The pattern of Adaptive Neuro-Fuzzy Inference System (ANFIS) was optimized by finding the optimum membership function, learning percentage, and a number of rules. The ANFIS was trained using the extracted data from the CFD simulation of the membrane system. The comparisons between the predicted concentration distribution by ANFIS and CFD data revealed that the optimized ANFIS pattern can be used as a predictive tool for simulation of the process. The R2 of higher than 0.99 was obtained for the optimized ANFIS model. The main privilege of the developed methodology is its very low computational time for simulation of the system and can be used as a rigorous simulation tool for understanding and design of membrane-based systems. Highlights are, Molecular separation using microporous membranes. Developing hybrid model based on ANFIS-CFD for the separation process, Optimization of ANFIS structure for prediction of separation process KW - Fluid KW - Simulation KW - Molecular Liquids KW - optimization KW - machine learning KW - Membrane contactors KW - CFD Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20181122-38212 N1 - This is the pre-peer reviewed version of the following article: https://www.sciencedirect.com/science/article/pii/S0167732218345008, which has been published in final form at https://doi.org/10.1016/j.molliq.2018.11.017. VL - 2018 SP - 1 EP - 20 ER - TY - THES A1 - Lang, Kevin T1 - Argument Search with Voice Assistants N2 - The need for finding persuasive arguments can arise in a variety of domains such as politics, finance, marketing or personal entertainment. In these domains, there is a demand to make decisions by oneself or to convince somebody about a specific topic. To obtain a conclusion, one has to search thoroughly different sources in literature and on the web to compare various arguments. Voice interfaces, in form of smartphone applications or smart speakers, present the user with natural conversations in a comfortable way to make search requests in contrast to a traditional search interface with keyboard and display. Benefits and obstacles of such a new interface are analyzed by conducting two studies. The first one consists of a survey for analyzing the target group with questions about situations, motivations, and possible demanding features. The latter one is a wizard-of-oz experiment to investigate possible queries on how a user formulates requests to such a novel system. The results indicate that a search interface with conversational abilities can build a helpful assistant, but to satisfy the demands of a broader audience some additional information retrieval and visualization features need to be implemented. KW - Amazon Alexa KW - Argument KW - Suche KW - Stimme KW - Assistent KW - alexa KW - voice KW - assistant KW - arguments KW - search Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20190617-39353 ER - TY - JOUR A1 - Bredekamp, Horst T1 - Auguste Rodins Weimarer Eva N2 - Festvortrag zur feierlichen Wiederaufstellung der von Auguste Rodin gestalteten Plastik "Eva" auf ihren angestammten Platz im Foyer des Hauptgebäudes der Bauhaus-Universität Weimar am 12. Dezember 2018 T3 - Neue Bauhausvorträge - 5 KW - Plastik KW - Kunstgeschichte Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200727-42042 ER -