Marcos Valdebenito

Marcos Valdebenito

Doctor en Ingeniería Civil
Profesor Hora
FACULTAD DE INGENIERÍA Y CIENCIAS
CHILE
Viña
Email: [email protected]
Linkedin: Saber +

Marcos Valdebenito

Marcos Valdebenito es Doctor en Ingeniería Civil por la Universidad de Innsbruck, Austria (2006-2010); Magíster en Ciencias de la Ingeniería Civil de la Universidad Santa María, Valparaíso, Chile, e ingeniero civil de la misma casa de estudios. Sus áreas de investigación se centran en mecánica estructural estocástica. Específicamente, en fiabilidad estructural, con énfasis en la dinámica estocástica; técnicas avanzadas de simulación tipo Monte Carlo para la evaluación y optimización de la fiabilidad, con énfasis en problemas que implican un gran número de parámetros inciertos; métodos de optimización deterministas y estocásticos; optimización basada en la fiabilidad y su aplicación en la gestión del ciclo de vida; análisis de elementos finitos estocásticos; y análisis estructural difuso. El profesor Valdebenito, quien se ha certificado en innovación educacional y la promoción de metodologías alternativas de enseñanza y aprendizaje, se incorporó a la Facultad de Ingeniería y Ciencias UAI en julio de 2020, donde actualmente es Director de la carrera de Ingeniería Civil. También ha realizado clases en la Universidad Santa María, y se ha desempeñado como profesor visitante en la Universidad Leibniz de Hanover, Alemania. Ha presentado publicaciones en numerosas conferencias en Chile y el extranjero, y ha recibido diversos reconocimientos. Entre ellos, la Beca Humboldt para Investigadores Experimentados, de la Fundación Alexander von Humboldt (Alemania); el K.J. Bathe Award 2016 por la mejor publicación en la revista internacional Computers & Structures en los años 2014 y 2015 de un autor bajo los 40 años. Es miembro del comité editorial de la revista internacional Computers & Structures y revisor de varias revistas con indexación WoS. Actualmente, preside el Comité de Probabilidad y Estadística de las Ciencias Físicas de la Sociedad Bernoulli.

Active Bayesian support vector regression with importance sampling for rare event reliability analysis</>

Zheng, W., Yuan, X., Bao, X., Valdebenito, M. & Faes, M., dic. 2026, In: Reliability Engineering and System Safety, 276.

Active learning Kriging with functional dimension reduction for reliability analysis of stochastic dynamical systems</>

Song, Z., Dang, C., Valdebenito, M. & Faes, M., sep. 2026, In: Reliability Engineering and System Safety, 273.

Modeling Nonstationary Non-Gaussian Random Fields</>

Zhang, X., Valdebenito, M., Faes, M. & Shields, M., ago. 2026, In: Journal of Engineering Mechanics, 152, 8.

Adaptive single-loop reweighted numerical integration for estimating response moment functions under hybrid aleatory and epistemic uncertainties</>

Liu, J., Valdebenito, M., Yang, D. & Faes, M., ago. 2026, In: Computer Methods in Applied Mechanics and Engineering, 457.

First excursion probability sensitivity in stochastic linear dynamics by means of multidomain line sampling</>

Misraji, M., Valdebenito, M., Jerez, D., Jensen, H., Beer, M. & Faes, M., ago. 2026, In: Reliability Engineering and System Safety, 272.

Revisiting the cross entropy method for first-passage probability of Gaussian-process excited uncertain linear structural dynamic systems</>

Kanjilal, O., Tatarevic, A., Valdebenito, M., Papaioannou, I., Faes, M. & Straub, D., ago. 2026, In: Reliability Engineering and System Safety, 272.

Reliability-aware collapse-resisting design of precast concrete beam–column joints using strengthened steel angles and high-strength bolts</>

Zhao, Z., Valdebenito, M., Li, Y., Dang, C., Zhang, W. & Faes, M., jul. 2026, In: Structural Safety, 121.

Sensitivity estimation of stochastic output with respect to distribution parameters of stochastic inputs</>

Zhang, X., Zhao, Y., Valdebenito, M. & Faes, M., jun. 2026, In: Reliability Engineering and System Safety, 270.

Aleatory and epistemic uncertainty in reliability analysis</>

Li, P., Valdebenito, M., Dang, C., Beer, M. & Faes, M., mar. 2026, In: Structural Safety, 119.

Variance-reduced estimation of Third-order statistics using control variates with splitting</>

Acevedo, C., Valdebenito, M., González, I., Jensen, H. & Faes, M., mar. 2026, In: Reliability Engineering and System Safety, 267.

Third moment method for reliability analysis involving independent parametric probability-boxes</>

Wang, B., Zhang, X., Zhao, Y., Valdebenito, M. & Faes, M., mar. 2026, In: Applied Mathematical Modelling, 151.

On the impact of geometric variance on the performance of formed parts</>

Schnelle, L., Fehlemann, N., Kilicsoy, A., Bechler, N., Valdebenito, M., Korkolis, Y., Faes, M., Münstermann, S. & Schröder, K., 2026, In: Procedia CIRP, 142, p. 175-179.

Multidomain Line Sampling for Reliability and Sensitivity Analysis in Stochastic Linear Dynamics</>

Valdebenito, M., Misraji, M. & Faes, M., 2026.

Bivariate Dimension-Reduction Methods with Different Integration Schemes for Estimating High-Order Statistical Moments in Stochastic Mechanics</>

Dang, C., Xu, J., Wei, P., Valdebenito, M., Faes, M. & Beer, M., 2026.

Time-dependent structural reliability analysis</>

Dang, C., Li, P., Valdebenito, M. & Faes, M., dic. 2025, In: Mechanical Systems and Signal Processing, 241.

Probability Sensitivity Estimation with Respect to Distribution Parameters via the Method of Moments</>

Zhang, X., Valdebenito, M., Zhao, Y. & Faes, M., dic. 2025, In: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 11, 4.

A Bayesian piecewise fitting method for estimating probability distributions of performance functions</>

Zhao, Y., Liu, Y., Li, P., Weng, Y., Valdebenito, M. & Faes, M., nov. 2025, In: Reliability Engineering and System Safety, 263.

Time-dependent reliability analysis by a single-loop Bayesian active learning method using Gaussian process regression</>

Dang, C., Valdebenito, M. & Faes, M., sep. 2025, In: Computer Methods in Applied Mechanics and Engineering, 444.

Control Variates Method to Estimate Stochastic Buckling Loads</>

Fina, M., Valdebenito, M., Wagner, W., Broggi, M., Freitag, S., Faes, M. & Beer, M., jul. 2025, In: International Journal for Numerical Methods in Engineering, 126, 13.

First excursion probability sensitivity in stochastic linear dynamics by means of Domain Decomposition Method</>

Misraji, M., Valdebenito, M. & Faes, M., jul. 2025, In: Mechanical Systems and Signal Processing, 235.

Reliability analysis combining method of moments with control variates</>

Acevedo, C., Zhang, X., Valdebenito, M. & Faes, M., jul. 2025, In: Probabilistic Engineering Mechanics, 81.

Efficient forward and inverse uncertainty quantification for dynamical systems based on dimension reduction and Kriging surrogate modeling in functional space</>

Song, Z., Xu, W., Valdebenito, M. & Faes, M., jul. 2025, In: Mechanical Systems and Signal Processing, 235.

Response probability distribution estimation of expensive computer simulators</>

Dang, C., Valdebenito, M., Manque, N., Xu, J. & Faes, M., may. 2025, In: Structural Safety, 114.

Confined seepage analysis of saturated soils using fuzzy fields</>

Manque, N., Phoon, K., Liu, Y., Valdebenito, M. & Faes, M., mar. 2025, In: Journal of Rock Mechanics and Geotechnical Engineering, 17, 3, p. 1302-1320.

Interval Isogeometric Analysis for coping with geometric uncertainty</>

Manque, N., Liedmann, J., Barthold, F., Valdebenito, M. & Faes, M., mar. 2025, In: Computer Methods in Applied Mechanics and Engineering, 437.

Towards a single-loop Gaussian process regression based-active learning method for time-dependent reliability analysis</>

Dang, C., Valdebenito, M. & Faes, M., mar. 2025, In: Mechanical Systems and Signal Processing, 226.

Directional importance sampling for dynamic reliability of linear structures under non-Gaussian white noise excitation</>

Zhang, X., Misraji, M., Valdebenito, M. & Faes, M., feb. 2025, In: Mechanical Systems and Signal Processing, 224.

On fractional moment estimation from polynomial chaos expansion</>

Novák, L., Valdebenito, M. & Faes, M., feb. 2025, In: Reliability Engineering and System Safety, 254.

Yet another Bayesian active learning reliability analysis method</>

Dang, C., Zhou, T., Valdebenito, M. & Faes, M., ene. 2025, In: Structural Safety, 112.

An efficient Bayesian updating framework for characterizing the posterior failure probability</>

Li, P., Zhao, Y., Dang, C., Broggi, M., Valdebenito, M. & Faes, M., ene. 2025, In: Mechanical Systems and Signal Processing, 222.

INTEGRATED APPROACH FOR ESTIMATING FAILURE PROBABILITIES USING METHOD OF MOMENTS AND CONTROL VARIATES WITH SPLITTING</>

Acevedo, C., Zhang, X., Valdebenito, M. & Faes, M., 2025.

Confined seepage analysis of saturated soils using fuzzy fields</>

Manque, N., Phoon, K., Liu, Y., Valdebenito, M. & Faes, M., 2025, In: Journal of Rock Mechanics and Geotechnical Engineering.

Exploiting the precision of FORM and the accuracy of importance sampling for estimating failure probability and its sensitivity</>

Valdebenito, M. & Faes, M., 2025, In: Civil Engineering and Environmental Systems, 42, 2, p. 76-94.

Crashworthiness Analysis</>

Colella, G., Valdebenito, M., Duddeck, F., Lange, V. & Faes, M., dic. 2024, In: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 10, 4.

Limit-State Function Sensitivity under Epistemic Uncertainty</>

Zhao, H., Zhou, C., Chang, Q., Shi, H., Valdebenito, M. & Faes, M., dic. 2024, In: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 10, 4.

An approximate decoupled reliability-based design optimization method for efficient design exploration of linear structures under random loads</>

Weng, L., Acevedo, C., Yang, J., Valdebenito, M., Faes, M. & Chen, J., dic. 2024, In: Computer Methods in Applied Mechanics and Engineering, 432.

A reduced-order model approach for fuzzy fields analysis</>

Manque, N., Valdebenito, M., Beaurepaire, P., Moens, D. & Faes, M., nov. 2024, In: Structural Safety, 111.

Design Optimization with Variable Screening by Interval-Based Sensitivity Analysis</>

Chang, Q., Zhou, C., Faes, M. & Valdebenito, M., sep. 2024, In: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 10, 3.

Bayesian active learning line sampling with log-normal process for rare-event probability estimation</>

Dang, C., Valdebenito, M., Wei, P., Song, J. & Beer, M., jun. 2024, In: Reliability Engineering and System Safety, 246.

Control variates with splitting for aggregating results of Monte Carlo simulation and perturbation analysis</>

Acevedo, C., Valdebenito, M., González, I., Jensen, H., Faes, M. & Liu, Y., may. 2024, In: Structural Safety, 108.

Structural reliability analysis with extremely small failure probabilities</>

Dang, C., Cicirello, A., Valdebenito, M., Faes, M., Wei, P. & Beer, M., abr. 2024, In: Probabilistic Engineering Mechanics, 76.

Partially Bayesian active learning cubature for structural reliability analysis with extremely small failure probabilities</>

Dang, C., Faes, M., Valdebenito, M., Wei, P. & Beer, M., mar. 2024, In: Computer Methods in Applied Mechanics and Engineering, 422.

Line sampling for time-variant failure probability estimation using an adaptive combination approach</>

Yuan, X., Zheng, W., Zhao, C., Valdebenito, M., Faes, M. & Dong, Y., mar. 2024, In: Reliability Engineering and System Safety, 243.

Operator norm-based determination of failure probability of nonlinear oscillators with fractional derivative elements subject to imprecise stationary Gaussian loads</>

Jerez, D., Fragkoulis, V., Ni, P., Mitseas, I., Valdebenito, M., Faes, M. & Beer, M., feb. 2024, In: Mechanical Systems and Signal Processing, 208.

Constrained Bayesian optimization algorithms for estimating design points in structural reliability analysis</>

Song, J., Cui, Y., Wei, P., Valdebenito, M. & Zhang, W., ene. 2024, In: Reliability Engineering and System Safety, 241.

Efficient slope reliability analysis under soil spatial variability using maximum entropy distribution with fractional moments</>

Feng, C., Valdebenito, M., Chwała, M., Liao, K., Broggi, M. & Beer, M., 2024, In: Journal of Rock Mechanics and Geotechnical Engineering, 16, 4, p. 1140-1152.

A reduced-order model for interval analysis in linear dynamical systems</>

Manque, N., Valdebenito, M., Moens, D. & Faes, M., 2024.

First excursion probability sensitivity by means of domain decomposition method</>

Misraji, M., Valdebenito, M., Zhang, X. & Faes, M., 2024.

Bayesian updating of conditional failure probability using method of moments</>

Li, P., Zhao, Y., Dang, C., Broggi, M., Valdebenito, M. & Faes, M., 2024.

Sobolev Neural Network with Residual Weighting as a Surrogate in Linear and Non-Linear Mechanics</>

Kilicsoy, A., Liedmann, J., Valdebenito, M., Barthold, F. & Faes, M., 2024, In: IEEE Access, 12, p. 137144-137161.

Estimation of First Excursion Probability in Stochastic Linear Dynamics by means of Multidomain Line Sampling</>

Valdebenito, M., Wei, P., Song, J., Beer, M. & Broggi, M., 2024.

Estimation of Second-order Statistics of Buckling Loads Applying Linear and Nonlinear Analysis</>

Fina, M., Faes, M., Valdebenito, M., Wagner, W., Broggi, M., Beer, M. & Freitag, S., 2024.

Bounding Failure Probabilities in Imprecise Stochastic FE models</>

Faes, M., Fina, M., Valdebenito, M., Lauff, C., Wagner, W., Freitag, S. & Beer, M., 2024.

Physic-informed probabilistic analysis with Bayesian machine learning in augmented space</>

Hong, F., Wei, P., Song, J., Faes, M., Valdebenito, M. & Beer, M., 2024.

Structural reliability analysis using imprecise evolutionary power spectral density functions</>

Behrendt, M., Dang, C., Faes, M., Valdebenito, M. & Beer, M., 2024, In: Journal of Physics: Conference Series, 2647, 6.

Probability of failure of nonlinear oscillators with fractional derivative elements subject to imprecise Gaussian loads</>

Ni, P., Jerez, D., Fragkoulis, V., Mitseas, I., Faes, M., Valdebenito, M. & Beer, M., 2024, In: Journal of Physics: Conference Series, 2647, 6.

Collaborative and Adaptive Bayesian Optimization for bounding variances and probabilities under hybrid uncertainties</>

Hong, F., Wei, P., Song, J., Valdebenito, M., Faes, M. & Beer, M., dic. 2023, In: Computer Methods in Applied Mechanics and Engineering, 417.

Augmented first-order reliability method for estimating fuzzy failure probabilities</>

Valdebenito, M., Yuan, X. & Faes, M., nov. 2023, In: Structural Safety, 105.

Effect of uncertainty of material parameters on stress triaxiality and Lode angle in finite elasto-plasticity—A variance-based global sensitivity analysis</>

Böddecker, M., Faes, M., Menzel, A. & Valdebenito, M., nov. 2023, In: Advances in Industrial and Manufacturing Engineering, 7.

Structural reliability analysis by line sampling</>

Dang, C., Valdebenito, M., Faes, M., Song, J., Wei, P. & Beer, M., sep. 2023, In: Structural Safety, 104.

Combining data and physical models for probabilistic analysis</>

Hong, F., Wei, P., Song, J., Faes, M., Valdebenito, M. & Beer, M., jul. 2023, In: Probabilistic Engineering Mechanics, 73.

Estimation of small failure probabilities by partially Bayesian active learning line sampling</>

Dang, C., Valdebenito, M., Song, J., Wei, P. & Beer, M., jul. 2023, In: Computer Methods in Applied Mechanics and Engineering, 412.

Simulation of random fields on random domains</>

Zheng, Z., Valdebenito, M., Beer, M. & Nackenhorst, U., jul. 2023, In: Probabilistic Engineering Mechanics, 73.

Efficient decoupling approach for reliability-based optimization based on augmented Line Sampling and combination algorithm</>

Yuan, X., Valdebenito, M., Zhang, B., Faes, M. & Beer, M., may. 2023, In: Computers and Structures, 280.

Estimation of an imprecise power spectral density function with optimised bounds from scarce data for epistemic uncertainty quantification</>

Behrendt, M., Faes, M., Valdebenito, M. & Beer, M., abr. 2023, In: Mechanical Systems and Signal Processing, 189.

Bayesian maximum entropy method for stochastic model updating using measurement data and statistical information</>

Wang, C., Yang, L., Xie, M., Valdebenito, M. & Beer, M., abr. 2023, In: Mechanical Systems and Signal Processing, 188.

Global failure probability function estimation based on an adaptive strategy and combination algorithm</>

Yuan, X., Qian, Y., Chen, J., Faes, M., Valdebenito, M. & Beer, M., mar. 2023, In: Reliability Engineering and System Safety, 231.

Bounding imprecise failure probabilities in structural mechanics based on maximum standard deviation</>

Fina, M., Lauff, C., Faes, M., Valdebenito, M., Wagner, W. & Freitag, S., mar. 2023, In: Structural Safety, 101.

A stochastic finite element scheme for solving partial differential equations defined on random domains</>

Zheng, Z., Valdebenito, M., Beer, M. & Nackenhorst, U., feb. 2023, In: Computer Methods in Applied Mechanics and Engineering, 405.

First-passage probability estimation of high-dimensional nonlinear stochastic dynamic systems by a fractional moments-based mixture distribution approach</>

Ding, C., Dang, C., Valdebenito, M., Faes, M., Broggi, M. & Beer, M., feb. 2023, In: Mechanical Systems and Signal Processing, 185.

Sample regeneration algorithm for structural failure probability function estimation</>

Yuan, X., Wang, S., Valdebenito, M., Faes, M. & Beer, M., ene. 2023, In: Probabilistic Engineering Mechanics, 71.

A REDUCED ORDER MODEL APPROACH FOR FUZZY FIELDS ANALYSIS</>

Manque, N., Valdebenito, M., Faes, M. & Beaurepaire, P., 2023, In: UNCECOMP Proceedings.

Structural reliability analysis</>

Dang, C., Valdebenito, M., Faes, M., Wei, P. & Beer, M., nov. 2022, In: Structural Safety, 99.

A novel sensitivity index for analyzing the response of numerical models with interval inputs</>

Chang, Q., Zhou, C., Valdebenito, M., Liu, H. & Yue, Z., oct. 2022, In: Computer Methods in Applied Mechanics and Engineering, 400.

Parallel adaptive Bayesian quadrature for rare event estimation</>

Dang, C., Wei, P., Faes, M., Valdebenito, M. & Beer, M., sep. 2022, In: Reliability Engineering and System Safety, 225.

A general hierarchical ensemble-learning framework for structural reliability analysis</>

Zhou, C., Zhang, H., Valdebenito, M. & Zhao, H., sep. 2022, In: Reliability Engineering and System Safety, 225.

Interval uncertainty propagation by a parallel Bayesian global optimization method</>

Dang, C., Wei, P., Faes, M., Valdebenito, M. & Beer, M., ago. 2022, In: Applied Mathematical Modelling, 108, p. 220-235.

Enriching stochastic model updating metrics</>

Zhao, W., Yang, L., Dang, C., Rocchetta, R., Valdebenito, M. & Moens, D., may. 2022, In: Mechanical Systems and Signal Processing, 171.

Operator Norm-Based Statistical Linearization to Bound the First Excursion Probability of Nonlinear Structures Subjected to Imprecise Stochastic Loading</>

Ni, P., Jerez, D., Fragkoulis, V., Faes, M., Valdebenito, M. & Beer, M., mar. 2022, In: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 8, 1.

Data-driven and active learning of variance-based sensitivity indices with Bayesian probabilistic integration</>

Song, J., Wei, P., Valdebenito, M., Faes, M. & Beer, M., ene. 2022, In: Mechanical Systems and Signal Processing, 163.

Capturing Epistemic Uncertainties in the Power Spectral Density for Limited Data Sets</>

Behrendt, M., Faes, M., Valdebenito, M. & Beer, M., 2022.

On the use of Directional Importance Sampling for reliability-based design and optimum design sensitivity of linear stochastic structures</>

Jerez, D., Jensen, H., Valdebenito, M., Misraji, M., Mayorga, F. & Beer, M., 2022, In: Probabilistic Engineering Mechanics, 70.

Cost-Benefit Analysis of Design for Progressive Collapse Under Accidental or Malevolent Extreme Events</>

Beck, A., da Rosa Ribeiro, L. & Valdebenito, M., 2022.

Bounding the first excursion probability of stochastic oscillators under randomness and imprecision</>

Faes, M., Fina, M., Lauff, C., Valdebenito, M., Wagner, W. & Freitag, S., 2022.

An efficient importance sampling approach for reliability analysis of time-variant structures subject to time-dependent stochastic load</>

Yuan, X., Liu, S., Faes, M., Valdebenito, M. & Beer, M., oct. 2021, In: Mechanical Systems and Signal Processing, 159.

Failure probability estimation of a class of series systems by multidomain Line Sampling</>

Valdebenito, M., Wei, P., Song, J., Beer, M. & Broggi, M., sep. 2021, In: Reliability Engineering and System Safety, 213.

Efficient procedure for failure probability function estimation in augmented space</>

Yuan, X., Liu, S., Valdebenito, M., Gu, J. & Beer, M., sep. 2021, In: Structural Safety, 92.

Decoupled reliability-based optimization using Markov chain Monte Carlo in augmented space</>

Yuan, X., Liu, S., Valdebenito, M., Faes, M., Jerez, D., Jensen, H. & Beer, M., jul. 2021, In: Advances in Engineering Software, 157-158.

Application of a Reduced Order Model for Fuzzy Analysis of Linear Static Systems</>

Valdebenito, M., Jensen, H., Wei, P., Beer, M. & Beck, A., jun. 2021, In: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 7, 2.

Efficient imprecise reliability analysis using the Augmented Space Integral</>

Yuan, X., Faes, M., Liu, S., Valdebenito, M. & Beer, M., jun. 2021, In: Reliability Engineering and System Safety, 210.

Operator norm theory as an efficient tool to propagate hybrid uncertainties and calculate imprecise probabilities</>

Faes, M., Valdebenito, M., Moens, D. & Beer, M., may. 2021, In: Mechanical Systems and Signal Processing, 152.

Bayesian probabilistic propagation of imprecise probabilities with large epistemic uncertainty</>

Wei, P., Liu, F., Valdebenito, M. & Beer, M., feb. 2021, In: Mechanical Systems and Signal Processing, 149.

Active learning line sampling for rare event analysis</>

Song, J., Wei, P., Valdebenito, M. & Beer, M., ene. 2021, In: Mechanical Systems and Signal Processing, 147.

OPTIMAL GAIN CALIBRATION OF ADAPTIVE MODEL-BASED COMPENSATION FOR REAL-TIME HYBRID SIMULATION TESTING</>

Fermandois, G., Galmez, C. & Valdebenito, M., 2021.

Risk-based cost-benefit analysis of frame structures considering progressive collapse under column removal scenarios</>

Beck, A., Ribeiro, L. & Valdebenito, M., dic. 2020, In: Engineering Structures, 225.

Adaptive reliability analysis for rare events evaluation with global imprecise line sampling</>

Song, J., Wei, P., Valdebenito, M. & Beer, M., dic. 2020, In: Computer Methods in Applied Mechanics and Engineering, 372.

Fully decoupled reliability-based design optimization of structural systems subject to uncertain loads</>

Faes, M. & Valdebenito, M., nov. 2020, In: Computer Methods in Applied Mechanics and Engineering, 371.

Bounding the first excursion probability of linear structures subjected to imprecise stochastic loading</>

Faes, M., Valdebenito, M., Moens, D. & Beer, M., oct. 2020, In: Computers and Structures, 239.

An adaptive scheme for reliability-based global design optimization</>

Jensen, H., Jerez, D. & Valdebenito, M., sep. 2020, In: Mechanical Systems and Signal Processing, 143.

On the reliability of structures equipped with a class of friction-based devices under stochastic excitation</>

Jensen, H., Mayorga, F. & Valdebenito, M., jun. 2020, In: Computer Methods in Applied Mechanics and Engineering, 364.

Application of directional importance sampling for estimation of first excursion probabilities of linear structural systems subject to stochastic Gaussian loading</>

Misraji, M., Valdebenito, M., Jensen, H. & Mayorga, C., may. 2020, In: Mechanical Systems and Signal Processing, 139.

Non-intrusive imprecise stochastic simulation by line sampling</>

Song, J., Valdebenito, M., Wei, P., Beer, M. & Lu, Z., may. 2020, In: Structural Safety, 84.

Fuzzy failure probability estimation applying intervening variables</>

Valdebenito, M., Beer, M., Jensen, H., Chen, J. & Wei, P., mar. 2020, In: Structural Safety, 83.

An effective parametric model reduction technique for uncertainty propagation analysis in structural dynamics</>

Jensen, H., Mayorga, F., Valdebenito, M. & Chen, J., mar. 2020, In: Reliability Engineering and System Safety, 195.

Imprecise stochastic dynamics via operator norm theory</>

Faes, M., Valdebenito, M., Beer, M. & Moens, D., 2020.

The use of parametric reduced-order models in stochastic structural dynamics</>

Jensen, H., Mayorga, F., Jerez, D. & Valdebenito, M., 2020.

Efficient propagation of imprecise probability models by imprecise line sampling</>

Wei, P., Song, J., Valdebenito, M. & Beer, M., 2020.

Reliability estimation in stochastic linear dynamics applying directional importance Sampling</>

Valdebenito, M., Misraji, M., Mayorga, C. & Jensen, H., 2020.

Reliability sensitivity analysis for linear structures subject to dynamic Gaussian Excitation</>

Misraji, M., Valdebenito, M., Mayorga, C. & Jensen, H., 2020.

Breaking the double loop</>

Faes, M., Valdebenito, M., Moens, D. & Beer, M., 2020.

Estimation of second order statistics of uncertain linear systems applying linear expansion and monte carlo simulation</>

Acevedo, C., González, I., Valdebenito, M. & Jensen, H., 2020.

Generalization of non-intrusive imprecise stochastic simulation for mixed uncertain variables</>

Song, J., Wei, P., Valdebenito, M., Bi, S., Broggi, M., Beer, M. & Lei, Z., dic. 2019, In: Mechanical Systems and Signal Processing, 134.

Probability sensitivity estimation of linear stochastic finite element models applying Line Sampling</>

Valdebenito, M., Hernández, H. & Jensen, H., nov. 2019, In: Structural Safety, 81.

Calculation of second order statistics of uncertain linear systems applying reduced order models</>

González, I., Valdebenito, M., Correa, J. & Jensen, H., oct. 2019, In: Reliability Engineering and System Safety, 190.

Reliability sensitivity analysis in stochastic finite element models</>

Valdebenito, M., Hernández, H. & Jensen, H., 2019.

Sensitivity estimation of failure probability applying line sampling</>

Valdebenito, M., Jensen, H., Hernández, H. & Mehrez, L., mar. 2018, In: Reliability Engineering and System Safety, 171, p. 99-111.

A physical domain-based substructuring as a framework for dynamic modeling and reanalysis of systems</>

Jensen, H., Araya, V., Muñoz, A. & Valdebenito, M., nov. 2017, In: Computer Methods in Applied Mechanics and Engineering, 326, p. 656-678.

Approximate fuzzy analysis of linear structural systems applying intervening variables</>

Valdebenito, M., Pérez, C., Jensen, H. & Beer, M., ene. 2016, In: Computers and Structures, 162, p. 116-129.

Reliability sensitivity estimation of nonlinear structural systems under stochastic excitation</>

Jensen, H., Mayorga, F. & Valdebenito, M., jun. 2015, In: Computer Methods in Applied Mechanics and Engineering, 289, p. 1-23.

Application of interventing variables in a bilinear approach for fuzzy structural analysis</>

Pérez, C. & Valdebenito, M., abr. 2015.

Sensitivity of First-Excursion Probabilities for Nonlinear Stochastic Dynamical Systems</>

Valdebenito, M. & Jensen, H., ene. 2015.

Estimation of first excursion probabilities for uncertain stochastic linear systems subject to Gaussian load</>

Valdebenito, M., Jensen, H. & Labarca, A., jul. 2014, In: Computers and Structures, 138, p. 36-48.

Approximation Concepts for Fuzzy Structural Analysis</>

Valdebenito, M., Jensen, H., Beer, M. & Pérez, C., 2014.

First excursion probability estimation for uncertain linear systems subject to discrete white noise excitation</>

Valdebenito, M., Jensen, H., Oyarzún, J. & Correa, J., 2014.

Design of isolation systems for large scale building models under stochastic excitation</>

Jensen, H., Kusanovic, D., Valdebenito, M. & Papadrakakis, M., 2013.

On robust maintenance scheduling of fatigue-prone structural systems considering imprecise probability</>

Patelli, E., Valdebenito, M. & De Angelis, M., 2013, In: Chemical Engineering Transactions, 33, p. 1081-1086.

On the application of intervening variables for stochastic finite element analysis</>

Valdebenito, M., Labarca, A. & Jensen, H., 2013, In: Computers and Structures, 126, 1, p. 164-176.

Reliability-based optimization using bridge importance sampling</>

Beaurepaire, P., Jensen, H., Schuëller, G. & Valdebenito, M., 2013, In: Probabilistic Engineering Mechanics, 34, p. 48-57.

On the use of a class of interior point algorithms in stochastic structural optimization</>

Jensen, H., Becerra, L. & Valdebenito, M., 2013, In: Computers and Structures, 126, 1, p. 69-85.

Efficient assessment of first excursion probabilities for uncertain linear dynamical structures subject to gaussian excitation</>

Valdebenito, M., Jensen, H., Oyarzún, J., Correa, J. & Kusanovic, D., 2013.

Optimal Design of Base-Isolated Systems under Stochastic Earthquake Excitation</>

Jensen, H., Valdebenito, M. & Sepulveda, J., 2013.

Compromise design of stochastic dynamical systems</>

Jensen, H., Kusanovic, D. & Valdebenito, M., jul. 2012, In: Probabilistic Engineering Mechanics, 29, p. 40-52.

Reliability-based optimization of maintenance scheduling of mechanical components under fatigue</>

Beaurepaire, P., Valdebenito, M., Schuëller, G. & Jensen, H., may. 2012, In: Computer Methods in Applied Mechanics and Engineering, 221-222, p. 24-40.

Reliability sensitivity estimation of linear systems under stochastic excitation</>

Valdebenito, M., Jensen, H., Schuëller, G. & Caro, F., feb. 2012, In: Computers and Structures, 92-93, p. 257-268.

Reliability analysis of linear dynamical systems with uncertain structural parameters subject to discrete white noise excitation</>

Valdebenito, M., Jensen, H., Schüeller, G. & Labarca, A., 2012.

Discrete variable structural optimization of systems under stochastic earthquake excitation</>

Jensen, H., Valdebenito, M., Sepúlveda, J. & Becerra, L., 2012.

Efficient strategies for reliability-based optimization involving non-linear, dynamical structures</>

Valdebenito, M. & Schuëller, G., oct. 2011, In: Computers and Structures, 89, 19-20, p. 1797-1811.

Reliability-based design optimization of uncertain stochastic systems</>

Jensen, H., Kusanovic, D., Valdebenito, M. & Schuëller, G., jul. 2011, In: Journal of Engineering Mechanics, 138, 1, p. 60-70.

General purpose stochastic analysis software for optimal maintenance scheduling</>

Patelli, E., Valdebenito, M. & Schuëller, G., jul. 2011, In: International Journal of Reliability and Safety, 5, 3-4, p. 211-228.

Reliability sensitivity of linear dynamical systems subject to gaussian excitation</>

Valdebenito, M., Jensen, H., Schuëller, G. & Caro, F., 2011.

An efficient first-order scheme for reliability based optimization of stochastic systems</>

Jensen, H., Schuëller, G., Valdebenito, M. & Kusanovic, D., 2011, In: Computational Methods in Applied Sciences, 22, p. 129-153.

Optimal design of base-isolated systems under stochastic earthquake excitation</>

Jensen, H., Valdebenito, M. & Sepulveda, J., 2011.

Reliability sensitivity and optimization of linear dynamical systems subject to Gaussian excitation</>

Valdebenito, M., Jensen, H. & Schuëller, G., 2011.

A survey on approaches for reliability-based optimization</>

Valdebenito, M. & Schuëller, G., nov. 2010, In: Structural and Multidisciplinary Optimization, 42, 5, p. 645-663.

Reliability-based optimization considering design variables of discrete size</>

Valdebenito, M. & Schuëller, G., sep. 2010, In: Engineering Structures, 32, 9, p. 2919-2930.

Design of maintenance schedules for fatigue-prone metallic components using reliability-based optimization</>

Valdebenito, M. & Schuëller, G., jul. 2010, In: Computer Methods in Applied Mechanics and Engineering, 199, 33-36, p. 2305-2318.

The role of the design point for calculating failure probabilities in view of dimensionality and structural nonlinearities</>

Valdebenito, M., Pradlwarter, H. & Schuëller, G., mar. 2010, In: Structural Safety, 32, 2, p. 101-111.

Reliability-based optimization of stochastic systems using line search</>

Jensen, H., Valdebenito, M., Schuëller, G. & Kusanovic, D., nov. 2009, In: Computer Methods in Applied Mechanics and Engineering, 198, 49-52, p. 3915-3924.

Maintenance strategies for uncertain mechanical systems considering the effects of fatigue</>

Valdebenito, M. & Schuëller, G., 2009.

An efficient reliability-based optimization scheme for uncertain linear systems subject to general Gaussian excitation</>

Jensen, H., Valdebenito, M. & Schuëller, G., nov. 2008, In: Computer Methods in Applied Mechanics and Engineering, 198, 1, p. 72-87.

Efficient strategies for solving reliability-based optimization problems</>

Valdebenito, M. & Schuëller, G., 2008.

Reliability analysis of linear dynamical systems using approximate representations of performance functions</>

Jensen, H. & Valdebenito, M., jul. 2007, In: Structural Safety, 29, 3, p. 222-237.