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Department of Mechanical Engineering
Students in summer on north campus, red gears in background. © Roland Baege​/​TU Dortmund
Publications

Conference contributions

2024

  1. Manque, N., Liedmann, J., Barthold, F., Valdebenito, M., Faes, M. (2024)
    Isogeometric Analysis for Coping with Geometric Uncertainty in Mechanical Systems
    Presented at the REC2024, Beijing, China, Oct 26-27, 2024
    Abstract preview

  2. Manque, N., Valdebenito, M., Moens, D., Faes, M. (2024)
    A Reduced-Order Model for Interval Analysis in Linear Dynamical Systems
    Presented at the ISRERM2024, Hefei, China, Oct 18-21, 2024
    Abstract preview

  3. Bonnet-Eymard, D., Persoons, A., Faes, M., Moens, D. (2024)
    Separable Physics-Informed Neural Networks for Robust Inverse Quantification in Solid Mechanics
    Presented at the ISRERM2024, Hefei, China, Oct 18-21, 2024

  4. Li, P., Zhao, Y., Dang, C., Broggi, M., Valdebenito, M., Faes, M. (2024)
    Measures of Conditional Failure Probability Considering Bayesian Updating
    Presented at the ISRERM2024, Hefei, China, Oct 18-21, 2024

  5. Weng, L., Faes, M., Valdebenito, M., Chen, J. (2024)
    Decoupled Reliability-Based Design Opti-mization of Linear Structures Subject to Uncertain Loads
    Presented at the ISRERM2024, Hefei, China, Oct 18-21, 2024

  6. Li, P. ,  Zhao, Y.  , Dang , C. , Broggi, M. , Valdebenito, M. , Faes, M. (2024)
    Bayesian updating of conditional failure probability using method of moments
    Presented at the ISMA-USD 2024, Leuven, Belgium, Sep 9-11, 2024
    Abstract preview

  7. Dodt, M., Bogaerts, L., Persoons, A., Faes, M., Moens, D. (2024).
    A multifidelity framework for grey-box modelling of automated welding processes.
    Presented at the ISMA-USD 2024, Leuven, Belgium, Sep 9-11, 2024
    Abstract preview

  8. Bonnet-Eymard, D., Persoons, A., Gavallas, P., Faes, M., Stefanou, G., Moens, D. (2024).
    Physics-informed neural networks to propagate random field properties of composite materials.
    Presented at the ISMA-USD 2024, Leuven, Belgium, Sep 9-11, 2024
    Abstract preview

  9. Misraji, M., Valdebenito, M., Zhang, X., Faes, M. (2024).
    First excursion probability sensitivity by means of domain decomposition method.
    Presented at the ISMA-USD 2024, Leuven, Belgium, Sep 9-11, 2024
    Abstract preview

  10. Manque, N., Valdebenito, M., Moens, D., Faes, M. (2024).
    A reduced-order model for interval analysis in linear dynamical systems.
    Presented at the ISMA-USD 2024, Leuven, Belgium, Sep 9-11, 2024
    Abstract preview

  11. Li, P., Zhao, Y., Dang, C., Broggi, M., Valdebenito, M., Faes, M. (2024).
    Bayesian updating of conditional failure probability using method of moments.
    Presented at the ISMA-USD 2024, Leuven, Belgium, Sep 9-11, 2024
    Abstract preview

  12. Bogaerts, L., Faes, M., Moens, D. (2024).
    A new approach to combine physics-based and data-driven models using a localised trustworthiness metric. In: Volume Modeling and Analysis of Real World and Industry Applications.
    Presented at the 16th World Congress on Computational Mechanics and 4th Pan American Congress on Computational Mechanics, Vancouver, Canada, Jul 21-26, 2024
    Abstract preview
     
  13. Callens, R., Moens, D., Faes, M. (2024).
    Multilevel Quasi-Monte Carlo for interval analysis of non-linear numerical models.
    Presented at the ECCOMAS 2024, Lisbon, Portugal, Jun 02-07 2024.
     
  14. Faes, M. (2024)
    Efficient numerical schemes for interval analysis (Keynote lecture).
    Presented at 3rd Sino-German Workshop on Reliability of Complex Systems (SGWRCS 2024), Xi'an, China, April 22-24, 2024
     
  15. Valdebenito, M. (2024)
    On the application of Control Variates for Calculation of Second-Order Statistics, Failure Probability and Sensitivity Analysis in Stochastic Finite Element Analysis (Keynote lecture)
    Presented at 3rd Sino-German Workshop on Reliability of Complex Systems (SGWRCS 2024), Xi'an, China, April 22-24, 2024
     
  16. Faes, M., Valdebenito, M., Novak, L. (2024).
    Fractional moment estimation from Polynomial Chaos Expansions.
    Presented at The 4th International Conference on Vulnerability and Risk Analysis and Management (ICVRAM 2024) and the 8th International Symposium on Uncertainty Modelling and Analysis (ISUMA 2024), Shanghai, China, April 25-27, 2024.
    Abstract preview
     
  17. Colella, G., Bourinet, J., Valdebenito, M., Faes, M., Lange, V., Duddeck,F. (2024)
    Exploration of Transfer Learning, Co-Kriging, and Control Variates for Early-Phase Crashworthiness Analysis
    Presented at The 4th International Conference on Vulnerability and Risk Analysis and Management (ICVRAM 2024) and the 8th International Symposium on Uncertainty Modelling and Analysis (ISUMA 2024), Shanghai, China, April 25-27, 2024
    Abstract preview
     
  18. Misraji, M., Zhang, X., Valdebenito, M., Faes, M. (2024)
    First Excursion Probability Estimation of a Bilinear Conservative Oscillator Subject to Stochastic Gaussian Loading
    Presented at The 4th International Conference on Vulnerability and Risk Analysis and Management (ICVRAM 2024) and the 8th International Symposium on Uncertainty Modelling and Analysis (ISUMA 2024), Shanghai, China, April 25-27, 2024
    Abstract preview
     
  19. Misraji, M., Valdebenito, M., Jerez, D., Jensen, H., Beer, M. and Faes, M. (2024)
    First Excursion Probability Sensitivity by means of Multidomain Line Sampling
    Presented at The 4th International Conference on Vulnerability and Risk Analysis and Management (ICVRAM 2024) and the 8th International Symposium on Uncertainty Modelling and Analysis (ISUMA 2024), Shanghai, China, April 25-27, 2024
    Abstract preview
     
  20. Feng, C., Valdebenito,M., Chwała, M., Liao, K., Broggi, M., Beer, M. (2024)
    Efficient slope reliability analysis under soil spatial variability
    Presented at The 4th International Conference on Vulnerability and Risk Analysis and Management (ICVRAM 2024) and the 8th International Symposium on Uncertainty Modelling and Analysis (ISUMA 2024), Shanghai, China, April 25-27, 2024
    Abstract preview
     
  21. Dang., C. (2024)
    Bayesian Active Learning Methods for Structural Reliability Analysis
    Presented at ICVRAM-ISUMA, China, April 25-28,2024.
    Abstract preview
     
  22. Bogaerts, L., Dodt, M.B., Persoons, A., Faes, M., Van Rymenant, P., Moens, D. (2024).
    Novel Grey-Box Modelling Techniques for Resistance Spot Welding.
    Presented at the Flanders Make Scientific Conference, Kortrijk, Belgium, Mar 26, 2024.
     
  23. Verkens, B., Faes, M., Van Rymenant, P. , Moens, D. (2024).
    Finite element modelling of resistance spot welding including validation.
    Presented at the Flanders Make Conference on Machine, Vehicle and Production Technologies, Kortrijk, Belgium, Mar 26, 2024
     
  24. Kilicsoy, A., Liedmann, J., Valdebenito, M., Barthold, F., Faes, M. (2024)
    A gradient-enhanced neural network as a surrogate for elastoplastic finite element analysis
    Presented at 24th SIAM Conference on Uncertainty Quantification (UQ24), Trieste, Itaky, February 27 - March 1, 2024
    Abstract preview
     
  25. Manque, N., Liedmann, J., Barthold, F., Valdebenito, M., Faes, M. (2024)
    Application of Isogeometric Analysis for Interval Analysis
    Presented at 94th Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM), Magdeburg, Germany, March 18-22, 2024
    Abstract preview
     
  26. Zhang, X., Misraji, M., Valdebenito, M., Faes, M. (2024)
    Advanced Directional Importance Sampling Method for Dynamic Reliability Analysis of Linear Structural Systems under Stochastic Non-Gaussian Loading
    Presented at 94th Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM), Magdeburg, Germany, March 18-22, 2024
    Abstract preview
     
  27. Böddecker, M., Faes, M., Menzel, A., Valdebenito, M. (2024)
    Quantification of the effect of uncertainty of material parameters on damage initiation in finite strain elastoplasticity
    Presented at 94th Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM), Magdeburg, Germany, March 18-22, 2024
    Abstract preview
     
  28. Callens, R., Moens, D., Faes, M. (2024)
    Certified interval model updating using scenario optimization
    Presented at AIAA SciTech Forum, Orlando, Florida, January 8-12, 2024.
    Abstract preview

 

2023

  1. Li, P., Faes,M. , Valdebenito, M., Broggi M. (2023)
    Bayesian Updating of Overall Failure Probability Based on Gauss-Legendre Numerical Integration and Information Reuse
    Presented at EMI 2023 International Conference, Palermo,Italy,  August  27-30, 2023.
     
  2. Feng, C., Faes, M., Broggi, M., Beer, M. (2023).
    Application of Interval Field Method to the Stability Analysis of Slopes in the Presence of Uncertainties
    Presented at Geo-Risk 2023, Arlington, Virginia, July 23-26, 2023.
     
  3. Valdebenito, M., Faes, M., Misraji, M., Jerez, D., Beer, M. (2023).
    First Excursion Probability Sensitivity Estimation by means of Multidomain Line Sampling
    Presented at the 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14), Dublin, Ireland, July 9-13, 2023
     
  4. Feng, C., Broggi, M., Faes, M., Beer, M. (2023).
    Geotechnical uncertainty analysis with sparse data using interval field method
    Presented at the 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14), Dublin, Ireland, July 9-13, 2023
     
  5. Hong, F., Wei, P., Song, J., Valdebenito, M., Faes, M., Beer, M. (2023).
    A Collaborative Bayesian Optimization Method for estimation of Failure probability bounds under mixed uncertainties
    Presented at the 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14), Dublin, Ireland, July 9-13, 2023
     
  6. Liu, J., Dang, C., Faes, M., Valdebenito, M., Beer, M. (2023).
    Estimation of failure probability function and its bounds under random and interval variables: A fully decoupled approach using Bayesian active learning
    Presented at the 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14), Dublin, Ireland, July 9-13, 2023
     
  7. Faes, M., Klein, N., Pauly, M., Valdebenito, M., Misraji, M. (2023). 
    Approximate Bayesian Computation for Parameter Identification in Computational Mechanics
    Presented at the 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14), Dublin, Ireland, July 9-13, 2023
     
  8. Fina, M., Faes, M., Valdebenito, M., Wagner, W., Broggi, M., Beer, M., Freitag S. (2023).
    Uncertainty Quantification of Buckling Loads of Thin and Slender Structures Applying Linear and Nonlinear Analysis
    Presented at the 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14), Dublin, Ireland, July 9-13, 2023
     
  9. Ni, P., Jerez, D., Fragkoulis, V., Mitseas, I., Faes, M., Valdebenito, M., Beer, M. (2023).
    Probability of failure of nonlinear oscillators with fractional derivative elements subject to imprecise Gaussian loads
    Presented at Eurodyn2023, the XIIth International Conference on Structural Dynamics, Delft, The Netherlands, 02-05 July 2023.
     
  10. Behrendt, M., Dang, C., Faes, M., Valdebenito, M., Beer, M. (2023).
    Structural reliability analysis using imprecise evolutionary power spectral density functions.
    Presented at Eurodyn2023, the XIIth International Conference on Structural Dynamics, Delft, The Netherlands, 02-05 July 2023.
     
  11. Valdebenito. M., Faes, M., Misraji, M., Jerez, D., Beer, M. (2023).
    On The Application Of Multidomain Line Sampling For Reliability And Sensitivity Analysis In Stochastic Linear Dynamics
    Presented at the 5th International Conference on Uncertainty Quantification in Computational Science and Engineering, Athens, Greece, 12-14 June 2023.
     
  12. Misraji, M.,Faes, M.,Valdebenito. M. (2023).
    Application Of Directional Importance Sampling For Estimation Of First Excursion Probabilities Of Nonlinear Conservative Sdof Systems Subject To Gaussian Stochastic Loading.
    Presented at the 5th International Conference on Uncertainty Quantification in Computational Science and Engineering, Athens, Greece, 12-14 June 2023.
     
  13. Manque, N., Valdebenito, M., Faes, M., Beaurepaire, P. (2023).
    A Reduced Order Model Approach for Fuzzy Field Analysis.
    Presented at the 5th International Conference on Uncertainty Quantification in Computational Science and Engineering, Athens, Greece, 12-14 June 2023.
     
  14. Ypsilantis, K., Faes, M., Ivens, J., Moens, D. (2023).
    Robust Topology Optimization For Fiber-Reinforced Composites Under Material Uncertainty.
    Presented at the 5th International Conference on Uncertainty Quantification in Computational Science and Engineering, Athens, Greece, 12-14 June 2023.
     
  15. Ascia, P., Faes, M., Duddeck, F. (2023).
    Quantifying The Epistemic Uncertainty Linked To The Development Process Of An Early- Stage Component For Crashworthiness.
    Presented at the 5th International Conference on Uncertainty Quantification in Computational Science and Engineering, Athens, Greece, 12-14 June 2023.
     
  16. Dodt, M., Persoons, A., Faes, M., Moens, D. (2023).
    A Self-Learning Digital Twin For Process Control Of Fast Processes Under Uncertainty.
    Presented at the 5th International Conference on Uncertainty Quantification in Computational Science and Engineering, Athens, Greece, 12-14 June 2023.
     
  17. Behrendt, M. Faes, M., Valdebenito, M., Beer, M. (2023).
    Bounding Limited Data Sets Of Power Spectral Density Functions For Uncertainty Quantification.
    Presented at the 5th International Conference on Uncertainty Quantification in Computational Science and Engineering, Athens, Greece, 12-14 June 2023.
     
  18. Callens, R., Faes, M., Moens, D. (2023).
    Certified Interval Model Updating Using Scenario Optimisation.
    Presented at the 5th International Conference on Uncertainty Quantification in Computational Science and Engineering, Athens, Greece, 12-14 June 2023.
     

2022

  1. Faes. M., Fina, M., Lauff, C., Valdebenito, M., Wagner, W., Freitag, S. (2022).
    Bounding the first excursion probability of stochastic oscillators under randomness and imprecision. 
    Presented at the International Conference on Noise and Vibration Engineering (ISMA) / International Conference on Uncertainty in Structural Dynamics (USD), Leuven, BELGIUM, 12 Sep 2020-14 Sep 2022.
     
  2. Van Bavel, B., Zhao, Y., Vandepitte, D., Moens, D., Faes, M. (2022).
    Bridging the composite meso-macro gap: A numerically efficient spatial uncertainty quantification approach. 
    Presented at the International Conference on Noise and Vibration Engineering (ISMA) / International Conference on Uncertainty in Structural Dynamics (USD), Leuven, BELGIUM, 12 Sep 2020-14 Sep 2022.
     
  3. Bonnet-Eymard, D., Faes, M., Moens, D. (2022). 
    Physics informed neural network as surrogate model to quantify the uncertainty of the elastic response of a material. 
    Presented at the International Conference on Noise and Vibration Engineering (ISMA) / International Conference on Uncertainty in Structural Dynamics (USD), Leuven, BELGIUM, 12 Sep 2020-14 Sep 2022.
     
  4. Dodt, M., Persoons, A., Faes, M., Moens, D. (2022). 
    Active Learning in Grey-Box Models for near-real-time Online Monitoring of Dynamic Processes. 
    Presented at the International Conference on Noise and Vibration Engineering (ISMA) / International Conference on Uncertainty in Structural Dynamics (USD), Leuven, BELGIUM, 12 Sep 2020-14 Sep 2022.
     
  5. Barzanooni, R., van Mierlo, K. Pabst, M., Faes, M., Moens, D., Duddeck, F. (2022). 
    Evaluation of uncertain boundary conditions for analysis of structural components with respect to crashworthiness. 
    Presented at the International Conference on Noise and Vibration Engineering (ISMA) / International Conference on Uncertainty in Structural Dynamics (USD), Leuven, BELGIUM, 12 Sep 2020-14 Sep 2022.
     
  6. Callens, R., Moens, D., Faes, M. (2022). 
    Multilevel Quasi-Monte Carlo for interval analysis in structural dynamics. 
    Presented at the International Conference on Noise and Vibration Engineering (ISMA) / International Conference on Uncertainty in Structural Dynamics (USD), Leuven, BELGIUM, 12 Sep 2020-14 Sep 2022.
     
  7. Fina, M. , Faes, M., Valdebenito, M., Wagner, W., Broggi, M., Beer, M., Freitag, S. (2022).
    Estimation of Second-order Statistics of Buckling Loads Applying Linear and Nonlinear
    Analysis.
    Presented at the 8th International Symposium on Reliability Engineering and Risk Management, Hannover, Germany
     
  8. Faes, M., Fina, M., Valdebenito, M., Lauff, C., Wagner, W., Freitag, S., Beer, M. (2022).
    Bounding Failure Probabities in Imprecise Stochastic FE Models. 
    Presented at the 8th International Symposium on Reliability Engineering and Risk Management, Hannover, Germany
     
  9. Dang, C., Wei, P., Faes, M., Beer, M. (2022). 
    Estimation of response expectation function under hybrid uncertainties by parallel Bayesian quadrature optimization. 
    Presented at the 8th International Symposium on Reliability Engineering and Risk Management, Han­no­ver, Germany
     
  10. Sharifi-Nik, K., Ghohani-Arab1, H., Rashki, M., Faes, M. (2022).
    The proposed rank-based active learning Kriging for efficient structural reliability analysis using weighted average simulation method.
    Presented at the 8th International Symposium on Reliability Engineering and Risk Management, Han­no­ver, Germany
     
  11. Faes, M., Valdebenito, M. (2022).
    A Fully Decoupled Reliability-Based Design Optimization Approach.
    Presented at the 13th International Conference on Structural Safety & Reliability, Shanghai, P.R. China.
     
  12. Faes, M., Valdebenito, M., Moens, D., Beer, M. (2022). 
    On the efficient propagation of imprecise probabilities via operator norm theory.
    Presented at the 13th International Conference on Structural Safety & Reliability, Shanghai, P.R. China.
     
  13. Behrendt, M., Faes, M., Valdebenito, M., Beer, M. (2022). 
    Capturing Epistemic Uncertainties in the Power Spectral Density for Limited Data Sets.
    Presented at the Probabilistic Safety Assessment and Management PSAM 16, Honolulu, Hawaii, June 26-July 1, 2022.
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