Dr.-Ing. habil. Thomas Most

Dr.-Ing. habil. Thomas Most


Marienstr. 15, Raum 006
Tel: +49 (0) 36 43 / 58 45 21
E-Mail: thomas.most[at]uni-weimar.de

Academic CV

2022 -presentSenior lecturer at the Institute of Structural Mechanics,
Bauhaus-Universität Weimar
2019 -presentSenior principal R&D engineer at Ansys Dynardo GmbH
2010 - 2019Employee at the Dynardo GmbH in Weimar
2013Habilitation thesis "Effiziente Methoden zur Analyse des Einflusses von Unsicherheiten in komplexen Ingenieurmodellen"
2008 - 2010PostDoc researcher in the DFG research training group "Qualitative Assessment of Coupled Numerical and Experimental Models in Civil Engineering"
2005Doctoral thesis "Stochastic crack growth simulation in reinforced concrete structures by means of coupled finite element and meshless methods"
2000 - 2008Scientific coworker at Institute of Structural Mechanics,
Bauhaus-Universität Weimar
1995 - 2000Civil engineering studies at Bauhaus-University Weimar

Research Interests

  • Uncertainty quantification and reliability analysis

  • Simulation based multidisciplinary optimization

  • Model calibration and assessment

  • Computational and fracture mechanics


  • Statik I



  • T. Most, P. Krenz, R. Lampert: “A global optimization approach for antenna design using analytical derivatives from high-frequency simulations”, NAFEMS DACH Conference, Bamberg, 2022

  • T. Most, L. Gräning, J. Will, A. Abdulhkim: “Automatized machine learning approach for industrial application”, NAFEMS DACH Conference, Bamberg, 2022


  • Rasch, M., P.T. Ubben, T. Most, V. Bayer, R. Niemeier: “Safety Assessment and Uncertainty Quantification of Automated Driver Assistance Systems using Stochastic Analysis Methods”, NAFEMS World Congress, Quebec, Canada, 2019

  • Most, T., R. Kallmeyer and R. Niemeier: “Estimate of material parameter uncertainties in calibrated simulation models”, NAFEMS World Congress, Quebec, Canada, 2019

  • Most, T.: “Artificial Intelligence and Machine Learning - Application in Computer Aided Engineering”, 30. Forum „Simulation in der Automobilindustrie“, Weimar, 2019

  • T. Most, J. Will, J. Rotermund, L. Gräning: “Artificial Intelligence and Machine Learning applied in Computer Aided Engineering”, Dynardo RDO-Journal, Issue 2/2019


  • Most, T. and R. Kallmeyer: „Identifikation unscharfer Modellparameter unter Berücksichtigung von Messfehlern“, DVM Workshop Zuverlässigkeit und Probabilistik, Ingolstadt, 2018


  • Most, T. and J. Will: “Robust Design Optimization Methods for Industrial Applications”, NAFEMS World Congress, Stockholm, 2017

  • Niemeier, R. and T. Most: “Robust Design Optimization and Catastrophe Theory”, NAFEMS World Congress, Stockholm, 2017

  • Most, T., S. Marth, M. Thiele: “Reliability based robust design optimization of an electromagnetic actuator system”, 15th International Probabilistic Workshop, Dresden, 2017


  • Most, T., J. Burkhardt, C. Birenbaum: „Optimierung einer Positionier- und Haltevorrichtung nach Steifigkeits- und Gewichtsgesichtspunkten“, NAFEMS Online-Magazin, 2016

  • Most, T. and J. Will: “Sensitivity analysis and parametric optimization as powerful tools for industrial product development”, NAFEMS European Conference on Simulation-Based Optimization, Manchester, 2016


  • Most, T., J. Will, T. Dannenberg: „Anwendung effizienter Methoden zur Sensitivitätsanalyse zur Untersuchung komplexer Ingenieuraufgaben“, Bautechnik, 2013

  • Most, T. and H. Neubert: “Robust Design and Reliability Analysis of an Electromagnetic Actuator System”, 16th ITI Symposium, Dresden, 2013


  • Most, T. and J. Will: “Robust Design Optimization in industrial virtual product development”, 5th International Conference on Reliable Engineering Computing (REC), Brno, 2012

  • Most, T.: “Variance-based sensitivity analysis in the presence of correlated input variables”, 5th International Conference on Reliable Engineering Computing (REC), Brno, 2012


  • Most, T., K.-J. Witt and M. Huber: "Identifikation räumlich korrelierter Bodenkenngrößen.", Bautechnik, 2011

  • Most, T.: "Assessment of structural simulation models by estimating uncertainties due to model selection and model simplification.", Computer and Structures, 2011

  • Most, T.: "Efficient structural reliability methods considering incomplete knowledge of random variable distributions.", Probabilistic Engineering Mechanics, 2011

  • Most, T.: “Efficient sensitivity analysis of complex engineering problems”, 11th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP), Zurich, 2011

  • Most, T. and J. Will: “Sensitivity analysis using the Metamodel of Optimal Prognosis”, Weimarer Optimierungs- und Stochastiktage, 2011


  • Most, T. and T. Knabe: “Reliability analysis of the bearing failure problem considering uncertain stochastic parameters.", Computers and Geotechnics, 2010

  • Most, T.: “Identification of the parameters of complex constitutive models: Least squares minimization vs. Bayesian updating.” 15th International Conference of the IFIP Working Group 7.5 on Reliability and Optimization of Structural Systems, Munich, 2010


  • C. Bucher and Most, T.: “A comparison of approximate response functions in structural reliability analysis.”, Probabilistic Engineering Mechanics, 2008

  • Most, T. and C. Bucher: “New concepts for Moving Least Squares: an interpolating non singular weighting function and Weighted Nodal Least Squares.”, Engineering Analysis with Boundary Elements, 2008 


  • Most, T.: “A natural neighbor based moving least squares approach for the element-free Galerkin method.”, International Journal for Numerical Methods in Engineering, 2007

  • Most, T. and C. Bucher: “Energy-based simulation of concrete cracking using an improved mixed-mode cohesive crack model within a meshless discretization.”, International Journal for Numerical and Analytical Methods in Geomechanics,  2007

  • Most, T. and C. Bucher: “Probabilistic analysis of concrete cracking using neural networks and random fields.”, Probabilistic Engineering Mechanics, 2007

  • Most, T.: “An adaptive response surface approach for structural reliability analyses based on support vector machines”, 11th International Conference on Civil, Structural and Environmental Engineering Computing, Malta, 2007

  • Most, T., G. Hofstetter, M. Hofmann, D. Novak, D. Lehký: “Approximation of constitutive parameters of material models by artificial neural networks”, 9th International Conference on the Application of Artificial Intelligence, Malta, 2007

  • Most, T. and Bucher, C.: “Adaptive response surface approach for reliability analysis using advanced meta-models.” 10th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP), Tokyo, 2007

2004 ~ 2006

  • Most, T. and C. Bucher: “Stochastic simulation of cracking in concrete structures using multi parameter random fields.”, International Journal of Reliability and Safety, 2006
  • Most, T. and C. Bucher: “A Moving Least Squares weighting function for the Element-free Galerkin Method which almost fulfills essential boundary conditions.”, Structural Engineering and Mechanics, 2005

  • Most, T., C. Bucher and Y. Schorling: “Dynamic stability analysis of nonlinear structures with geometrical imperfections under random loading.”, Journal of Sound and Vibration, 2004