@article{HarirchianLahmerBuddhirajuetal., author = {Harirchian, Ehsan and Lahmer, Tom and Buddhiraju, Sreekanth and Mohammad, Kifaytullah and Mosavi, Amir}, title = {Earthquake Safety Assessment of Buildings through Rapid Visual Screening}, series = {Buildings}, volume = {2020}, journal = {Buildings}, number = {Volume 10, Issue 3}, publisher = {MDPI}, doi = {10.3390/buildings10030051}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200331-41153}, pages = {15}, abstract = {Earthquake is among the most devastating natural disasters causing severe economical, environmental, and social destruction. Earthquake safety assessment and building hazard monitoring can highly contribute to urban sustainability through identification and insight into optimum materials and structures. While the vulnerability of structures mainly depends on the structural resistance, the safety assessment of buildings can be highly challenging. In this paper, we consider the Rapid Visual Screening (RVS) method, which is a qualitative procedure for estimating structural scores for buildings suitable for medium- to high-seismic cases. This paper presents an overview of the common RVS methods, i.e., FEMA P-154, IITK-GGSDMA, and EMPI. To examine the accuracy and validation, a practical comparison is performed between their assessment and observed damage of reinforced concrete buildings from a street survey in the Bing{\"o}l region, Turkey, after the 1 May 2003 earthquake. The results demonstrate that the application of RVS methods for preliminary damage estimation is a vital tool. Furthermore, the comparative analysis showed that FEMA P-154 creates an assessment that overestimates damage states and is not economically viable, while EMPI and IITK-GGSDMA provide more accurate and practical estimation, respectively.}, subject = {Maschinelles Lernen}, language = {en} } @article{HarirchianLahmerKumarietal., author = {Harirchian, Ehsan and Lahmer, Tom and Kumari, Vandana and Jadhav, Kirti}, title = {Application of Support Vector Machine Modeling for the Rapid Seismic Hazard Safety Evaluation of Existing Buildings}, series = {Energies}, volume = {2020}, journal = {Energies}, number = {volume 13, issue 13, 3340}, publisher = {MDPI}, address = {Basel}, doi = {10.3390/en13133340}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200707-41915}, pages = {15}, abstract = {The economic losses from earthquakes tend to hit the national economy considerably; therefore, models that are capable of estimating the vulnerability and losses of future earthquakes are highly consequential for emergency planners with the purpose of risk mitigation. This demands a mass prioritization filtering of structures to identify vulnerable buildings for retrofitting purposes. The application of advanced structural analysis on each building to study the earthquake response is impractical due to complex calculations, long computational time, and exorbitant cost. This exhibits the need for a fast, reliable, and rapid method, commonly known as Rapid Visual Screening (RVS). The method serves as a preliminary screening platform, using an optimum number of seismic parameters of the structure and predefined output damage states. In this study, the efficacy of the Machine Learning (ML) application in damage prediction through a Support Vector Machine (SVM) model as the damage classification technique has been investigated. The developed model was trained and examined based on damage data from the 1999 D{\"u}zce Earthquake in Turkey, where the building's data consists of 22 performance modifiers that have been implemented with supervised machine learning.}, subject = {Erdbeben}, language = {en} } @article{HarirchianLahmerRasulzade, author = {Harirchian, Ehsan and Lahmer, Tom and Rasulzade, Shahla}, title = {Earthquake Hazard Safety Assessment of Existing Buildings Using Optimized Multi-Layer Perceptron Neural Network}, series = {Energies}, volume = {2020}, journal = {Energies}, number = {Volume 13, Issue 8, 2060}, publisher = {MDPI}, address = {Basel}, doi = {10.3390/en13082060}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200504-41575}, pages = {16}, abstract = {The latest earthquakes have proven that several existing buildings, particularly in developing countries, are not secured from damages of earthquake. A variety of statistical and machine-learning approaches have been proposed to identify vulnerable buildings for the prioritization of retrofitting. The present work aims to investigate earthquake susceptibility through the combination of six building performance variables that can be used to obtain an optimal prediction of the damage state of reinforced concrete buildings using artificial neural network (ANN). In this regard, a multi-layer perceptron network is trained and optimized using a database of 484 damaged buildings from the D{\"u}zce earthquake in Turkey. The results demonstrate the feasibility and effectiveness of the selected ANN approach to classify concrete structural damage that can be used as a preliminary assessment technique to identify vulnerable buildings in disaster risk-management programs.}, subject = {Erdbeben}, language = {en} } @inproceedings{HartmannSmarslyLahmer, author = {Hartmann, Veronika and Smarsly, Kay and Lahmer, Tom}, title = {ROBUST SCHEDULING IN CONSTRUCTION ENGINEERING}, series = {Digital Proceedings, International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering : July 20 - 22 2015, Bauhaus-University Weimar}, booktitle = {Digital Proceedings, International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering : July 20 - 22 2015, Bauhaus-University Weimar}, editor = {G{\"u}rlebeck, Klaus and Lahmer, Tom}, organization = {Bauhaus-Universit{\"a}t Weimar}, issn = {1611-4086}, doi = {10.25643/bauhaus-universitaet.2799}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170314-27994}, pages = {5}, abstract = {In construction engineering, a schedule's input data, which is usually not exactly known in the planning phase, is considered deterministic when generating the schedule. As a result, construction schedules become unreliable and deadlines are often not met. While the optimization of construction schedules with respect to costs and makespan has been a matter of research in the past decades, the optimization of the robustness of construction schedules has received little attention. In this paper, the effects of uncertainties inherent to the input data of construction schedules are discussed. Possibilities are investigated to improve the reliability of construction schedules by considering alternative processes for certain tasks and by identifying the combination of processes generating the most robust schedule with respect to the makespan of a construction project.}, subject = {Angewandte Informatik}, language = {en} } @article{HauckLahmerKaltenbacher, author = {Hauck, A. and Lahmer, Tom and Kaltenbacher, Manfred}, title = {Enhanced homogenization technique for magnetomechanical systems using the generalized finite element method}, series = {COMPEL: The international journal for computation and mathematics in electrical and electronic engineering}, journal = {COMPEL: The international journal for computation and mathematics in electrical and electronic engineering}, pages = {935 -- 947}, abstract = {Enhanced homogenization technique for magnetomechanical systems using the generalized finite element method}, subject = {Angewandte Mathematik}, language = {en} } @article{IlyaniAkmarLahmerBordasetal., author = {Ilyani Akmar, A.B. and Lahmer, Tom and Bordas, St{\´e}phane Pierre Alain and Beex, L.A.A. and Rabczuk, Timon}, title = {Uncertainty quantification of dry woven fabrics: A sensitivity analysis on material properties}, series = {Composite Structures}, journal = {Composite Structures}, doi = {10.1016/j.compstruct.2014.04.014}, pages = {1 -- 17}, abstract = {Uncertainty quantification of dry woven fabrics: A sensitivity analysis on material properties}, subject = {Angewandte Mathematik}, language = {en} } @inproceedings{JaouadiLahmer, author = {Jaouadi, Zouhour and Lahmer, Tom}, title = {Topology optimization of structures subjected to multiple load cases by introducing the Epsilon constraint method}, series = {Digital Proceedings, International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering : July 20 - 22 2015, Bauhaus-University Weimar}, booktitle = {Digital Proceedings, International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering : July 20 - 22 2015, Bauhaus-University Weimar}, editor = {G{\"u}rlebeck, Klaus and Lahmer, Tom}, organization = {Bauhaus-Universit{\"a}t Weimar}, issn = {1611-4086}, doi = {10.25643/bauhaus-universitaet.2804}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170314-28042}, pages = {7}, abstract = {A topology optimization method has been developed for structures subjected to multiple load cases (Example of a bridge pier subjected to wind loads, traffic, superstructure...). We formulate the problem as a multi-criterial optimization problem, where the compliance is computed for each load case. Then, the Epsilon constraint method (method proposed by Chankong and Haimes, 1971) is adapted. The strategy of this method is based on the concept of minimizing the maximum compliance resulting from the critical load case while the other remaining compliances are considered in the constraints. In each iteration, the compliances of all load cases are computed and only the maximum one is minimized. The topology optimization process is switching from one load to another according to the variation of the resulting compliance. In this work we will motivate and explain the proposed methodology and provide some numerical examples.}, subject = {Angewandte Informatik}, language = {en} } @article{KaltenbacherLahmerMohretal., author = {Kaltenbacher, Barbara and Lahmer, Tom and Mohr, Marcus and Kaltenbacher, Manfred}, title = {PDE based determination of piezoelectric material tensors}, series = {European Journal of Applied Mathematics}, journal = {European Journal of Applied Mathematics}, doi = {10.25643/bauhaus-universitaet.3595}, pages = {383 -- 416}, abstract = {PDE based determination of piezoelectric material tensors.}, subject = {Angewandte Mathematik}, language = {en} } @article{KeitelKarakiLahmeretal., author = {Keitel, Holger and Karaki, Ghada and Lahmer, Tom and Nikulla, Susanne and Zabel, Volkmar}, title = {Evaluation of coupled partial models in structural engineering using graph theory and sensitivity analysis}, series = {Engineering structures}, journal = {Engineering structures}, pages = {3726 -- 3736}, abstract = {Evaluation of coupled partial models in structural engineering using graph theory and sensitivity analysis}, subject = {Angewandte Mathematik}, language = {en} } @article{KnabeDatchevaLahmeretal., author = {Knabe, Tina and Datcheva, Maria and Lahmer, Tom and Cotecchia, F. and Schanz, Tom}, title = {Identification of constitutive parameters of soil using an optimization strategy and statistical analysis}, series = {Computers and Geotechnics}, journal = {Computers and Geotechnics}, pages = {143 -- 157}, abstract = {Identification of constitutive parameters of soil using an optimization strategy and statistical analysis}, subject = {Angewandte Mathematik}, language = {en} }