@phdthesis{Brehm2011,
  author    = {Brehm, Maik},
  title     = {Vibration-based model updating: Reduction and quantification of uncertainties},
  doi       = {10.25643/bauhaus-universitaet.1465},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20110926-15553},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  year      = {2011},
  abstract  = {Numerical models and their combination with advanced solution strategies are standard tools for many engineering disciplines to design or redesign structures and to optimize designs with the purpose to improve specific requirements. As the successful application of numerical models depends on their suitability to represent the behavior related to the intended use, they should be validated by experimentally obtained results. If the discrepancy between numerically derived and experimentally obtained results is not acceptable, a model revision or a revision of the experiment need to be considered. Model revision is divided into two classes, the model updating and the basic revision of the numerical model. The presented thesis is related to a special branch of model updating, the vibration-based model updating. Vibration-based model updating is a tool to improve the correlation of the numerical model by adjusting uncertain model input parameters by means of results extracted from vibration tests. Evidently, uncertainties related to the experiment, the numerical model, or the applied numerical solving strategies can influence the correctness of the identified model input parameters. The reduction of uncertainties for two critical problems and the quantification of uncertainties related to the investigation of several nominally identical structures are the main emphases of this thesis. First, the reduction of uncertainties by optimizing reference sensor positions is considered. The presented approach relies on predicted power spectral amplitudes and an initial finite element model as a basis to define the assessment criterion for predefined sensor positions. In combination with geometry-based design variables, which represent the sensor positions, genetic and particle swarm optimization algorithms are applied. The applicability of the proposed approach is demonstrated on a numerical benchmark study of a simply supported beam and a case study of a real test specimen. Furthermore, the theory of determining the predicted power spectral amplitudes is validated with results from vibration tests. Second, the possibility to reduce uncertainties related to an inappropriate assignment for numerically derived and experimentally obtained modes is investigated. In the context of vibration-based model updating, the correct pairing is essential. The most common criterion for indicating corresponding mode shapes is the modal assurance criterion. Unfortunately, this criterion fails in certain cases and is not reliable for automatic approaches. Hence, an alternative criterion, the energy-based modal assurance criterion, is proposed. This criterion combines the mathematical characteristic of orthogonality with the physical properties of the structure by modal strain energies. A numerical example and a case study with experimental data are presented to show the advantages of the proposed energy-based modal assurance criterion in comparison to the traditional modal assurance criterion. Third, the application of optimization strategies combined with information theory based objective functions is analyzed for the purpose of stochastic model updating. This approach serves as an alternative to the common sensitivity-based stochastic model updating strategies. Their success depends strongly on the defined initial model input parameters. In contrast, approaches based on optimization strategies can be more flexible. It can be demonstrated, that the investigated nature inspired optimization strategies in combination with Bhattacharyya distance and Kullback-Leibler divergence are appropriate. The obtained accuracies and the respective computational effort are comparable with sensitivity-based stochastic model updating strategies. The application of model updating procedures to improve the quality and suitability of a numerical model is always related to additional costs. The presented innovative approaches will contribute to reduce and quantify uncertainties within a vibration-based model updating process. Therefore, the increased benefit can compensate the additional effort, which is necessary to apply model updating procedures.},
  subject      = {Dynamik},
  language  = {en}
}
@inproceedings{KoenigVaroudis,
  author    = {K{\"o}nig, Reinhard and Varoudis, Tasos},
  title     = {Spatial Optimizations: Merging depthmapX , spatial graph networks and evolutionary design in Grasshopper},
  series = {Proceedings of ecaade 34: Complexity \& Simplicity},
  booktitle = {Proceedings of ecaade 34: Complexity \& Simplicity},
  address   = {Oulu, Finland},
  doi       = {10.25643/bauhaus-universitaet.2604},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20160622-26040},
  pages     = {1 -- 6},
  abstract  = {In the Space Syntax community, the standard tool for computing all kinds of spatial graph network measures is depthmapX (Turner, 2004; Varoudis, 2012). The process of evaluating many design variants of networks is relatively complicated, since they need to be drawn in a separated CAD system, exported and imported in depthmapX via dxf file format. This procedure disables a continuous integration into a design process. Furthermore, the standalone character of depthmapX makes it impossible to use its network centrality calculation for optimization processes. To overcome this limitations, we present in this paper the first steps of experimenting with a Grasshopper component (reference omitted until final version) that can access the functions of depthmapX and integrate them into Grasshopper/Rhino3D. Here the component is implemented in a way that it can be used directly for an evolutionary algorithm (EA) implemented in a Python scripting component in Grasshopper},
  language  = {en}
}
@unpublished{RezakazemiMosaviShirazian,
  author    = {Rezakazemi, Mashallah and Mosavi, Amir and Shirazian, Saeed},
  title     = {ANFIS pattern for molecular membranes separation optimization},
  volume    = {2018},
  doi       = {10.25643/BAUHAUS-UNIVERSITAET.3821},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20181122-38212},
  pages     = {1 -- 20},
  abstract  = {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},
  subject      = {Fluid},
  language  = {en}
}
@phdthesis{Schilling2003,
  author    = {Schilling, Steffi},
  title     = {Beitrag zur L{\"o}sung ingenieurtechnischer Entwurfsaufgaben unter Verwendung Evolution{\"a}rer Algorithmen},
  doi       = {10.25643/bauhaus-universitaet.87},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20040826-921},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  year      = {2003},
  abstract  = {In der vorliegenden Arbeit erfolgt die Anwendung Evolution{\"a}rer Algorithmen an baupraktischen Problemen. Der Einfluss unterschiedlicher Selektionsmethoden, Rekombinationsmethoden sowie der Einfluss von Mutation und Populationsgr{\"o}ße auf Sucheffizienz und Ergebnis werden er{\"o}rtert. Die erzielten Erkenntnisse fliessen in die Definition Evolution{\"a}rer Strategiewerte ein, die als Grundlage f{\"u}r die Formulierung eines robusten Evolution{\"a}ren Algorithmus dienen. Evolution{\"a}re Algorithmen werden mit einem wachstumsorientierten Algorithmus erweitert (hybride Evolution{\"a}re Algorithmen), um eine Steigerung der Effizienz bei der L{\"o}sungssuche zu erzielen. An ausgew{\"a}hlten Stahlkonstruktionen - Hallen, Wassertank, Dachkonstruktion - wird die Leistungsf{\"a}higkeit von robusten Evoluton{\"a}ren Algorithmen und den entwickelten hybriden Evolution{\"a}ren Algorithmus {\"u}berpr{\"u}ft.},
  subject      = {Optimierung},
  language  = {de}
}