Publikationen und Vorträge von Dr.-Ing. Marco Behrendt

Behrendt, M.; Dang, C.; Beer, M. (2024): Data-driven and physics-based interval modelling of power spectral density functions from limited data,  Mechanical Systems and Signal Processing, 208, Article 111078
DOI: 10.1016/j.ymssp.2023.111078

Behrendt, M.; Dang, C.; Faes, M.G.R.; Valdebenito, M.A.; Beer, M. (2024): Structural reliability analysis using imprecise evolutionary power spectral density functions,  XII. International Conference on Structural Dynamics, Journal of Physics: Conference Series, 2647, 062003
DOI: 10.1088/1742-6596/2647/6/062003

Behrendt, M.; Lyu, M.Z.; Luo, Y.; Chen, J.B.; Beer, M. (2024): Failure probability estimation of dynamic systems employing relaxed power spectral density functions with dependent frequency modeling and sampling,  Probabilistic Engineering Mechanics, 75, Article 103592
DOI: 10.1016/j.probengmech.2024.103592

Bittner, M.; Behrendt, M.; Beer, M. (2024): Relaxed evolutionary power spectral density functions: A probabilistic approach to model uncertainties of non-stationary stochastic signals,  Mechanical Systems and Signal Processing, 211, Article 111210
DOI: 10.1016/j.ymssp.2024.111210

Behrendt, M.; de Angelis, M.; Beer, M. (2023): Uncertainty propagation of missing data signals with the interval discrete Fourier transform,  ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 9(3), Article 04023022
DOI: 10.1061/AJRUA6.RUENG-1048

Behrendt, M.; Faes, M.G.R.; Valdebenito, M.A.; Beer, M. (2023): Estimation of an imprecise power spectral density function with optimised bounds from scarce data for epistemic uncertainty quantification,  Mechanical Systems and Signal Processing, 189, Article 110072.
DOI: 10.1016/j.ymssp.2022.110072

Behrendt, M.; Bittner, M.; Comerford, L.; Beer, M.; Chen, J.B. (2022): Relaxed Power Spectrum Estimation from Multiple Data Records utilising Subjective Probabilities,  Mechanical Systems and Signal Processing, 165, Article 108346.
DOI: 10.1016/j.ymssp.2021.108346

Behrendt, M.; de Angelis, M.; Comerford, L.A.; Zhang, Y.J.; Beer, M. (2022): Projecting interval uncertainty through the discrete Fourier transform: an application to time signals with poor precision,  Mechanical Systems and Signal Processing, Volume 172, 1 June 2022, 108920.
DOI: 10.1016/j.ymssp.2022.108920

Behrendt, M.; Kitahara, M.; Kitahara, T.; Comerford, L.; Beer, M. (2022): Data-driven reliability assessment of dynamic structures based on power spectrum classification,  Engineering Structures, 268, 114648.
DOI: 10.1016/j.engstruct.2022.114648

Behrendt, M.; Bittner, M.; Beer, M. (2022): Stochastic process generation from relaxed power spectra utilising stochastic harmonic functions,  Proceedings of the 8th International Symposium on Reliability Engineering and Risk Management (ISRERM 2022), Hannover, Germany.
DOI: 10.3850/978-981-18-5184-1_MS-01-220-cd

Behrendt, M.; de Angelis, M.; Comerford, L.; Beer, M. (2022): Assessing the severity of the missing data problem with the interval DFT algorithm,  Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022), Dublin, Ireland.
DOI: 10.3850/978-981-18-5183-4_S14-05-243-cd

Behrendt, M.; Faes, M.G.R.; Valdebenito, M.A.; Beer, M. (2022): Capturing Epistemic Uncertainties in the Power Spectral Density for Limited Data Sets,  Probabilistic Safety Assessment and Management PSAM 16, Honolulu, USA. Weitere Informationen

Behrendt, M.; Kitahara, M.; Kitahara, T.; Comerford, L.; Beer, M. (2022): Classification of power spectra from data sets with high spectral variance for reliability analysis of dynamic structures,  Proceedings of the 8th International Symposium on Reliability Engineering and Risk Management (ISRERM 2022)
DOI: 10.3850/978-981-18-5184-1_MS-11-160-cd

Bittner, M.; Behrendt, M.; Behrensdorf, J.; Beer, M. (2022): Epistemic Uncertainty Quantification of Localised Seismic Power Spectral Densities,  Probabilistic Safety Assessment and Management PSAM 16, Honolulu, USA. Weitere Informationen

De Angelis, M.; Behrendt, M.; Comerford, L.; Zhang, Y.; Beer, M. (2021): Forward interval propagation through the discrete Fourier transform,  The 9th international workshop on Reliable Engineering Computing
arXiv: arXiv:2012.09778

Behrendt, M.; Bittner, M.; Comerford, L.; Broggi, M.; Beer, M. (2020): Parameter Investigation of Relaxed Uncertain Power Spectra for Stochastic Dynamic Systems,  Proceedings of the XI International Conference on Structural Dynamics (EURODYN 2020), Athens, Greece.
DOI: 10.47964/1120.9311.18861

Behrendt, M., Comerford, L., Beer, M. (2019): Development of a Relaxed Stationary Power Spectrum using Imprecise Probabilities with Application to High-rise Buildings.,  IEEE Symposium Series on Computational Intelligence (SSCI).
DOI: 10.1109/SSCI44817.2019.9002899

Behrendt, M., Comerford, L., Beer, M., (2019): Relaxed Stationary Power Spectrum Model Using Imprecise Probabilities,  COMPDYN Proceedings, 1, pp. 592-599.
DOI: 10.7712/120119.6941.19045

Behrendt, M.; Comerford, L.; Beer, M. (2019): Stochastic Processes Identification from Data Ensembles via Power Spectrum Classification.,  13th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP13).
DOI: 10.22725/ICASP13.407

Behrendt, M.; Punurai, W.; Beer, M. (2018): Synchronized Load Quantification from Multiple Data Records for Analysing High-rise Buildings,  7th Asia Conference on Earthquake Engineering, 22-25 November 2018, Bangkok, Thailand.
DOI: 10.15488/4957

Behrendt, M.; Brandt, S.; Eckert, C. (2016): Optimierung von Gebietszerlegungen mit Hilfe der Partikelschwarmoptimierung,  28. Forum Bauinformatik, Hannover, Deutschland.