Maria Tauscher, M.Sc.

• Vorhersagefähigkeit von Ingenieurmodellen durch Ersatzmodelle (Surrogate models)
  • Methoden: Polynomial Regression, Support Vector Regression, Artificial Neural Network, Kriging, …
• Fehlerdiagnose in Monitoringsystemen

Forschungsprojekte:

 Researchgate: hier (öffnet externen Link)

Journal-Publikationen

M. Steiner, J.-M. Bourinet, T. Lahmer, 2019: An adaptive sampling method for global sensitivity analysis based on least-squares support vector regression, Reliability Engineering and System Safety, Volume 183, Pages 323 - 340.

Dragos, K., Steiner, M., Zabel, V., Smarsly, K., 2018: Monitoringgestützte Analyse von Schwingungsdämpfern in Turmbauwerken, Bautechnik 95(6), S. 401-409.

M. F. Badawy, M. A. Msekh, K. M. Hamdia, M. Steiner, T. Rabczuk, 2017: Hybrid nonlinear surrogate models for fracture behavior of polymeric nanocomposites using phase field model, Journal of Probabilistic Engineering Mechanics (PREM), Volume 59, Pages 64 - 75.

Buch-Veröffentlichungen

Fritz, H., Peralta, J., Legatiuk, D., Steiner, M., Dragos, K., & Smarsly, K., 2022. Fault diagnosis in structural health monitoring systems using signal processing and machine learning techniques. In: Cury, A., Ribeiro, D., Ubertini, F., Todd, M. D. (eds.). Structural health monitoring based on data science techniques. Pp. 143-164. Cham, Switzerland: Springer, DOI: 10.1007/978-3-030-81716-9_7

Steiner, M., Mirboland, M. & Theiler, M. (Hrsg.), 2018. Forum Bauinformatik 2018 - von jungen Forschenden für junge Forschende. Weimar: Professur Informatik im Bauwesen, Bauhaus-Universität Weimar, 19.09.2018.

Tagungsbeiträge

Tauscher, M., Bendalla, A., & Chayeb, G., 2023. Fault Identification in Wireless Structural Health Monitoring Systems based on Fault Patterns. In: Tagungsband 34. Forum Bauinformatik. Bochum, 06. - 08.09.2023. DOI: 10.13154/294-10112.

Steiner, M., Legatiuk, D. & Smarsly, K., 2019. A support vector regression-based approach towards decentralized fault diagnosis in wireless structural health monitoring systems. In: The 12th International Workshop on Structural Health Monitoring (IWSHM). Stanford, CA, USA, 10.09.2019.

Steiner, M., Fritz, H., Thiebes, L. & Dragos, K., 2018. Fault diagnosis in wireless structural health monitoring systems based on support vector regression. In: 30. Forum Bauinformatik. Weimar, 19.09.2018.

Karimi, S., Mehrkian Jorshari, B., Mousazadeh, E., Steiner, M. & Dragos, K., 2018. Comparative study of experimentally tested tuned liquid column dampers. In: 30. Forum Bauinformatik. Weimar, 19.09.2018

Dragos, K., Steiner, M., Zabel, V. & Smarsly, K., 2018. Data-driven assessment of tuned mass dampers in tower structures. In: The 16th European Conference on Earthquake Engineering (ECEE). Thessaloniki, Griechenland, 18/06/2018.

Steiner, M.; Lahmer, T.; Bourinet, J.-M.: Investigation of a global adaptive sampling method based on least-squares support vector regression, Proceedings of the GRK International Workshop, Weimar, Germany, 2017

Khosravian, R.; Steiner, M.; Könke, C.: Parametric study on the effects of catenary cables and soil-structure interaction on dynamic behavior of pole structures using the finite elements method, Proceedings of the 7th International Conference on Computational Methods, Berkeley, CA, USA, 2016.

Steiner, M.; Khosravian, R.; Lahmer, T.: Quality of estimated sensitivity indices based on metamodels, Proceedings of the 13th international Probabilistic Workshop (IPW 2015), Liverpool, UK, 2015.

Steiner, M.; Khosravian, R.; Lahmer, T.: Best use of metamodels for data derived from civil engineering applications, Proceedings of the Fourth International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering, Prague, Czech Republic, 2015.

Bachelor-Studiengang Bauingenieurwesen, Umweltingenieurwissenschaften und Management [BII]:

• Geometrische Modellierung und technische Darstellung (Wintersemester)
• Informatik für Ingenieure (Sommersemester) 

Bachelor-/Masterarbeiten:

Die Betreuung von Abschlussarbeiten ist unter anderem in den Bereichen Ersatzmodelle, Fehlerdiagnose und Sensorik möglich.