High-resolution seismic monitoring of instrumented buildings using a model-based state observer Kalil Erazo Eric M. Hernandez Earthquake shaking table Structural engineering Reinforced concrete Bending moment Estimator Engineering Calibration Shear wall Building code Computer science Mathematics Statistics Summary This paper proposes a model‐based state observer to perform high‐definition response estimation in partially instrumented building structures. The proposed estimator is verified in a simulated five‐story shear‐building structure and validated using measurements from a seven‐story reinforced concrete building slice tested at the NEES‐University of California at San Diego shake table. In both cases the proposed estimator yielded satisfactory results by estimating the time history of shear forces, bending moments, displacements, and strains at various points/sections of interest. The proposed algorithm can be used in instrumented buildings for various practical applications such as post‐earthquake damage assessment, structural control, and building code calibration. Copyright © 2016 John Wiley & Sons, Ltd. 2016 en info:eu-repo/semantics/article journal-article https://doi.org/10.1002/eqe.2781 Earthquake Engineering and Structural Dynamics Earthquake Engineering and Structural Dynamics urn:issn:0098-8847 urn:issn:1096-9845 Earthquake Engineering and Structural Dynamics, 2016, vol. 45, n. 15, p. 2513-2531 info:eu-repo/semantics/closedAccess closedAccess Q1 Sustainable cities and communities Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Lower bound of structural damage to achieve practical identifiability of nonlinear models in seismic structural health monitoring Kalil Erazo Eric M. Hernandez Earthquake shaking table Identifiability Nonlinear system Structural engineering Structural health monitoring Engineering Extended Kalman filter Kalman filter Computer science Abstract This paper examines the effect of structural damage on the practical/computational identifiability of the parameters that define nonlinear models of building structures subjected to earthquake‐induced base motions. The objective is to determine the level of physical damage expected to successfully estimate the nonlinear parameters of restoring force models. For this purpose, the analyses aim to determine if the parameters that define a hysteretic (Bouc‐Wen type) model can be identified within a predefined level of accuracy from accelerations measured during seismic events that cause minor damage. The identified model is then interrogated to determine if it can provide accurate predictions of the response and damage level experienced during strong ground motions that cause moderate‐to‐severe damage. The damage model adopted is a Park–Ang type model and the unscented Kalman filter is used for parameter estimation. The results are verified using simulated two‐dimensional building models and validated using experimental data from a large‐scale shake table test. 2024 en info:eu-repo/semantics/article journal-article https://doi.org/10.1002/eqe.4011 Earthquake Engineering and Structural Dynamics Earthquake Engineering and Structural Dynamics urn:issn:0098-8847 urn:issn:1096-9845 Earthquake Engineering and Structural Dynamics, 2024, vol. 53, n. 1, p. 5-22 info:eu-repo/semantics/openAccess openAccess cc-by-nc https://doi.org/10.1002/eqe.4011 Q1 Sustainable cities and communities Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Bayesian estimation of acoustic emissions source in plate structures using particle-based stochastic filtering Kalil Erazo Debarshi Sen Satish Nagarajaiah Particle filter Posterior probability Algorithm Kalman filter Filter (signal processing) Mathematics Bayesian probability Computer science Statistics Computer vision The application of particle-based stochastic filters to acoustic emission source localization in plate structures is presented. The approach employs time-of-flight measurements of guided waves using triangulation to estimate the acoustic emission source coordinates in a probabilistic framework using Bayesian inference, incorporating uncertainties related to material properties, measurement noise, and geometry of the system of interest. The estimate of the source location is given by a probability density function conditional on the guided wave measurements, found using particle-based stochastic simulation algorithms; in this setting, a set of particles is used to explore the space of possible source locations and efficiently estimate the posterior. The use of 2 filters is explored: the ensemble Kalman filter and the particle filter. The former filter assumes that the posterior distribution can be approximated by a Gaussian distribution, although the latter provides a nonparametric estimate of the posterior in the form of a weighted set of samples, overcoming the challenges related to the evaluation of high-dimensional integrals in an efficient way. Results of an experimental validation study conducted in a laboratory environment demonstrate the accuracy and efficiency of the particle filter-based approach. In particular, it is shown that the proposed particle filter-based approach has the capability to locate the emission source under minimal instrumentation, providing confidence intervals as a quantitative measure of the uncertainty in the estimates. 2017 en info:eu-repo/semantics/article journal-article https://doi.org/10.1002/stc.2005 Structural Control and Health Monitoring Structural Control and Health Monitoring urn:issn:1545-2255 urn:issn:1545-2263 Structural Control and Health Monitoring, 2017, vol. 24, n. 11, p. e2005 info:eu-repo/semantics/openAccess openAccess https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/stc.2005 Q1 doaj Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Bayesian structural identification of a hysteretic negative stiffness earthquake protection system using unscented Kalman filtering Kalil Erazo Satish Nagarajaiah Nonlinear system Stiffness Structural engineering Kalman filter Extended Kalman filter Engineering Context (archaeology) System identification Structural health monitoring Structural system Benchmark (surveying) Identification (biology) Control theory (sociology) Computer science Geology Artificial intelligence Physics Data modeling The application of Bayesian system identification in the context of a hysteretic negative stiffness system for seismic protection of structures is presented. The negative stiffness system employs the concept of apparent weakening to decrease the effective lateral stiffness of structures subjected to strong earthquakes, resulting in a significant reduction of the base shear and other seismic demands. In this paper, results from large-scale experimental testing performed by Rice University and the University at Buffalo - SUNY are used to estimate the parameters that define the nonlinear models of structures equipped with negative stiffness systems. For this purpose, an unscented Kalman filter for augmented-state nonlinear estimation is employed for structural identification. It is shown that the identified models have the capability to accurately predict the nonlinear hysteretic behavior of the modified structure. The predicted response quantities include lateral drifts and accelerations, base shear, restoring forces, and internal forces in structural members. The identified models provide benchmark parameters that can be used to predict the performance of negative stiffness systems, which is useful for the future design of structures equipped with this type of earthquake protection devices. 2018 en info:eu-repo/semantics/article journal-article https://doi.org/10.1002/stc.2203 Structural Control and Health Monitoring Structural Control and Health Monitoring urn:issn:1545-2255 urn:issn:1545-2263 Structural Control and Health Monitoring, 2018, vol. 25, n. 9, p. e2203 info:eu-repo/semantics/openAccess openAccess https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/stc.2203 Q1 doaj Sustainable cities and communities Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Real-time dynamic stress response estimation at critical locations of instrumented structures embedded in random fields Kalil Erazo Eric M. Hernandez Estimator Spectral density Finite element method Vibration Random vibration Structural engineering Process (computing) Computer science Field (mathematics) Engineering Control theory (sociology) Mathematics Acoustics Statistics Physics Artificial intelligence 2013 en info:eu-repo/semantics/conferenceObject proceedings-article https://doi.org/10.1007/978-1-4614-6546-1_39 Conference Proceedings of the Society for Experimental Mechanics Series Conference Proceedings of the Society for Experimental Mechanics Series urn:issn:2191-5644 urn:issn:2191-5652 Conference Proceedings of the Society for Experimental Mechanics Series, 2013, p. 367-374 info:eu-repo/semantics/closedAccess closedAccess Climate action Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Recursive Nonlinear Identification of a Negative Stiffness Device for Seismic Protection of Structures with Geometric and Material Nonlinearities Kalil Erazo Satish Nagarajaiah Nonlinear system Control theory (sociology) Stiffness Vibration Context (archaeology) Displacement (psychology) Structural system Kalman filter Extended Kalman filter Structural engineering Computer science Mathematics Engineering Physics Acoustics Geology Artificial intelligence 2020 en info:eu-repo/semantics/conferenceObject proceedings-article https://doi.org/10.1007/978-3-030-47638-0_34 Conference Proceedings of the Society for Experimental Mechanics Series Conference Proceedings of the Society for Experimental Mechanics Series urn:issn:2191-5644 urn:issn:2191-5652 Conference Proceedings of the Society for Experimental Mechanics Series, 2020, p. 315-322 info:eu-repo/semantics/closedAccess closedAccess Climate action Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal An Output-Only Bayesian Identification Approach for Nonlinear Structural and Mechanical Systems Kalil Erazo Satish Nagarajaiah Kalman filter Identification (biology) Bayesian probability Nonlinear system Posterior probability Forcing (mathematics) Computer science Control theory (sociology) Inverse Extended Kalman filter State (computer science) Recursive Bayesian estimation System identification Algorithm Applied mathematics Mathematical optimization Mathematics Artificial intelligence Data mining Control (management) 2020 en info:eu-repo/semantics/conferenceObject proceedings-article https://doi.org/10.1007/978-3-030-47638-0_47 Conference Proceedings of the Society for Experimental Mechanics Series Conference Proceedings of the Society for Experimental Mechanics Series urn:issn:2191-5644 urn:issn:2191-5652 Conference Proceedings of the Society for Experimental Mechanics Series, 2020, p. 431-437 info:eu-repo/semantics/closedAccess closedAccess Reduced inequalities Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal State estimation in nonlinear structural systems Kalil Erazo Eric M. Hernandez Kalman filter Estimator Extended Kalman filter Nonlinear system Ensemble Kalman filter Control theory (sociology) Particle filter Invariant extended Kalman filter State (computer science) Computer science Alpha beta filter Noise (video) Algorithm Mathematics Moving horizon estimation Statistics Artificial intelligence Physics 2014 en info:eu-repo/semantics/conferenceObject proceedings-article https://doi.org/10.1007/978-3-319-04522-1_24 Conference Proceedings of the Society for Experimental Mechanics Series Conference Proceedings of the Society for Experimental Mechanics Series urn:issn:2191-5644 urn:issn:2191-5652 Conference Proceedings of the Society for Experimental Mechanics Series, 2014, p. 249-257 info:eu-repo/semantics/closedAccess closedAccess Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Analysis and damage correlation of ground motion intensity measures from records of the 2023 Turkey-Syria earthquake Kalil Erazo Ground motion Seismology Structural geology Hydrogeology Geology Intensity (physics) Correlation Geodesy Geography Geotechnical engineering Mathematics Physics 2024 en info:eu-repo/semantics/article journal-article https://doi.org/10.1007/s10518-024-01989-8 Bulletin of Earthquake Engineering Bulletin of Earthquake Engineering urn:issn:1570-761X urn:issn:1573-1456 Bulletin of Earthquake Engineering, 2024, vol. 23, n. 3, p. 1255-1278 info:eu-repo/semantics/closedAccess closedAccess Q1 Climate action Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Updated seismic hazard curves, maps, and spectra for the northern Dominican Republic using a probabilistic seismic hazard analysis Kalil Erazo Seismic hazard Seismology Peak ground acceleration Geology Induced seismicity Building code Earthquake scenario Incremental Dynamic Analysis Spectral acceleration Structural geology Ground motion Engineering Structural engineering 2023 en info:eu-repo/semantics/article journal-article https://doi.org/10.1007/s10950-023-10150-y Journal of Seismology Journal of Seismology urn:issn:1383-4649 urn:issn:1573-157X Journal of Seismology, 2023, vol. 27, n. 3, p. 409-428 info:eu-repo/semantics/closedAccess closedAccess Q2 Sustainable cities and communities Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Bayesian seismic strong-motion response and damage estimation with application to a full-scale seven story shear wall structure Kalil Erazo Babak Moaveni Satish Nagarajaiah Earthquake shaking table Nonlinear system Structural engineering Robustness (evolution) Cantilever Engineering Kalman filter Context (archaeology) Geology Computer science 2019 en info:eu-repo/semantics/article journal-article https://doi.org/10.1016/j.engstruct.2019.02.017 Engineering Structures Engineering Structures urn:issn:0141-0296 urn:issn:1873-7323 Engineering Structures, 2019, vol. 186, p. 146-160 info:eu-repo/semantics/closedAccess closedAccess Q1 Sustainable cities and communities Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal An offline approach for output-only Bayesian identification of stochastic nonlinear systems using unscented Kalman filtering Kalil Erazo Satish Nagarajaiah Kalman filter Nonlinear system Unscented transform Computer science Divergence (linguistics) Extended Kalman filter Posterior probability Markov chain Monte Carlo Realization (probability) Control theory (sociology) System identification Stability (learning theory) Monte Carlo method Bayesian probability Algorithm Mathematics Ensemble Kalman filter Artificial intelligence Machine learning Measure (data warehouse) 2017 en info:eu-repo/semantics/article journal-article https://doi.org/10.1016/j.jsv.2017.03.001 Journal of Sound and Vibration Journal of Sound and Vibration urn:issn:0022-460X urn:issn:1095-8568 Journal of Sound and Vibration, 2017, vol. 397, p. 222-240 info:eu-repo/semantics/closedAccess closedAccess Q1 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal On the effectiveness of principal component analysis for decoupling structural damage and environmental effects in bridge structures Kalil Erazo Debarshi Sen Wei Zhang Satish Nagarajaiah Limin Sun Classification of discontinuities Structural health monitoring Principal component analysis Structural engineering Discontinuity (linguistics) Bridge (graph theory) Decoupling (probability) Vibration Sensitivity (control systems) Engineering Computer science Mathematics Physics 2019 en info:eu-repo/semantics/article journal-article https://doi.org/10.1016/j.jsv.2019.06.003 Journal of Sound and Vibration Journal of Sound and Vibration urn:issn:0022-460X urn:issn:1095-8568 Journal of Sound and Vibration, 2019, vol. 457, p. 280-298 info:eu-repo/semantics/closedAccess closedAccess Q1 Industry, innovation and infrastructure Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal A model-based observer for state and stress estimation in structural and mechanical systems: Experimental validation Kalil Erazo Eric M. Hernandez Observer (physics) Kalman filter Control theory (sociology) Cantilever State observer Covariance Random vibration Alpha beta filter Shaker Engineering Mathematics Algorithm Computer science Extended Kalman filter Structural engineering Vibration Acoustics Statistics Artificial intelligence 2014 en info:eu-repo/semantics/article journal-article https://doi.org/10.1016/j.ymssp.2013.10.011 Mechanical Systems and Signal Processing Mechanical Systems and Signal Processing urn:issn:0888-3270 urn:issn:1096-1216 Mechanical Systems and Signal Processing, 2014, vol. 43, n. 1-2, p. 141-152 info:eu-repo/semantics/closedAccess closedAccess Q1 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Vibration-based structural health monitoring under changing environmental conditions using Kalman filtering Kalil Erazo Debarshi Sen Satish Nagarajaiah Limin Sun Residual Structural health monitoring Robustness (evolution) Kalman filter Vibration Probability density function Computer science Control theory (sociology) Biological system Algorithm Structural engineering Engineering Mathematics Statistics Acoustics Artificial intelligence Physics 2019 en info:eu-repo/semantics/article journal-article https://doi.org/10.1016/j.ymssp.2018.07.041 Mechanical Systems and Signal Processing Mechanical Systems and Signal Processing urn:issn:0888-3270 urn:issn:1096-1216 Mechanical Systems and Signal Processing, 2019, vol. 117, p. 1-15 info:eu-repo/semantics/closedAccess closedAccess Q1 Reduced inequalities Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal A novel unscented Kalman filter for recursive state-input-system identification of nonlinear systems Kalil Erazo Ying Lei Dandan Xia Satish Nagarajaiah Kalman filter Control theory (sociology) Nonlinear system Unscented transform Identification (biology) Extended Kalman filter System identification Filter (signal processing) Computer science Displacement (psychology) Sensor fusion Nonlinear system identification Acceleration Measure (data warehouse) Fast Kalman filter Artificial intelligence Physics Computer vision 2019 en info:eu-repo/semantics/article journal-article https://doi.org/10.1016/j.ymssp.2019.03.013 Mechanical Systems and Signal Processing Mechanical Systems and Signal Processing urn:issn:0888-3270 urn:issn:1096-1216 Mechanical Systems and Signal Processing, 2019, vol. 127, p. 120-135 info:eu-repo/semantics/closedAccess closedAccess Q1 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal An extended model-based observer for state estimation in nonlinear hysteretic structural systems Kalil Erazo Milad Roohi David V. Rosowsky Eric M. Hernandez Observer (physics) Nonlinear system Control theory (sociology) Estimator Kalman filter Extended Kalman filter Computer science Benchmark (surveying) State observer Alpha beta filter Mathematics Artificial intelligence 2021 en info:eu-repo/semantics/article journal-article https://doi.org/10.1016/j.ymssp.2020.107015 Mechanical Systems and Signal Processing Mechanical Systems and Signal Processing urn:issn:0888-3270 urn:issn:1096-1216 Mechanical Systems and Signal Processing, 2021, vol. 146, p. 107015 info:eu-repo/semantics/closedAccess closedAccess Q1 Sustainable cities and communities Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Uncertainty Quantification for State Estimation in Nonlinear Structural Systems Kalil Erazo Eric M. Hernandez Kalman filter Ensemble Kalman filter Nonlinear system Robustness (evolution) Extended Kalman filter Invariant extended Kalman filter Control theory (sociology) Covariance Estimator Computer science Covariance matrix Piecewise Covariance intersection Nonlinear filter Filter (signal processing) Algorithm Mathematics Filter design Artificial intelligence Statistics This paper presents the application of state estimators in nonlinear structural systems. The objective is to provide a comparison of the effectiveness to reconstruct the state time history in nonlinear building-type structures of four existing algorithms - namely, extended Kalman filter, unscented Kalman filter, ensemble Kalman filter and the particle filter. We compare their accuracy under ideal conditions and their robustness to different types of modeling errors. The uncertainty in the estimate of the quantities of interest is described by their covariance matrix. The systems of interest are nonlinear frames, where the material nonlinearity is given by piecewise linear hysteretic force deformation functions. 2014 en info:eu-repo/semantics/conferenceObject proceedings-article https://doi.org/10.1061/9780784413609.150 Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014 Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014 Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014, 2014, p. 1494-1503 info:eu-repo/semantics/closedAccess closedAccess Sustainable cities and communities Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Bayesian Model–Data Fusion for Mechanistic Postearthquake Damage Assessment of Building Structures Kalil Erazo Eric M. Hernandez Bayesian probability Kalman filter Probabilistic logic Moment (physics) Computer science Frame (networking) Ensemble Kalman filter Acceleration Recursive Bayesian estimation Extended Kalman filter Artificial intelligence Physics This paper presents a probabilistic framework for estimating seismic-induced damage in partially instrumented buildings. The proposed framework uses acceleration measurements at a limited number of stories and Bayesian filtering to estimate the response at all stories. The paper compares four Bayesian filters: the extended, unscented, and ensemble Kalman filters, and the particle filter. The estimated response throughout the building serves as input to a damage model that yields an estimate of structural damage and its uncertainty at all stories. The methodology is numerically verified in an elastoplastic 5-story shear building and in a 10-story inelastic moment-resisting frame under various types of model errors and minimal instrumentation. It was found that under ideal and mild modeling error conditions, the proposed methodology provides consistent estimates of damage and its uncertainty. 2016 en info:eu-repo/semantics/article journal-article https://doi.org/10.1061/(asce)em.1943-7889.0001114 Journal of Engineering Mechanics Journal of Engineering Mechanics urn:issn:0733-9399 urn:issn:1943-7889 Journal of Engineering Mechanics, 2016, vol. 142, n. 9 info:eu-repo/semantics/closedAccess closedAccess Q1 Sustainable cities and communities Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Uncertainty Quantification of State Estimation in Nonlinear Structural Systems with Application to Seismic Response in Buildings Kalil Erazo Eric M. Hernandez Sensitivity (control systems) Parametric statistics Kalman filter Nonlinear system Bayesian probability Computer science Ensemble Kalman filter Ideal (ethics) Uncertainty quantification Particle filter Filter (signal processing) Control theory (sociology) Algorithm Mathematics Extended Kalman filter Engineering Statistics Artificial intelligence Machine learning This paper presents the application of Bayesian filtering for the estimation and uncertainty quantification of interstory drifts and shears in partially instrumented buildings. We investigate the performance of four Bayesian filters: the extended, unscented, and ensemble Kalman filters, and the particle filter. The filters were compared in a simulation environment under ideal modeling and model error conditions. Computational efficiency, estimation accuracy and statistical error behavior of the filters was investigated. It was found that under ideal modeling conditions all the filters perform adequately. However, the filters exhibit significant sensitivity to parametric and nonparametric model errors. In the application studied, the sensitivity to parametric errors was nonsymmetric, with underestimation of model stiffness and yielding strength having a larger detrimental effect on the accuracy than overestimation of these parameters. 2016 en info:eu-repo/semantics/conferenceObject proceedings-article https://doi.org/10.1061/ajrua6.0000837 ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering urn:issn:2376-7642 ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 2016, vol. 2, n. 3 info:eu-repo/semantics/closedAccess closedAccess Sustainable cities and communities Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Parameter Estimation of Stochastic Fractional Dynamic Systems Using Nonlinear Bayesian Filtering System Identification Methods Kalil Erazo Alberto Di Matteo Pol D. Spanos Control theory (sociology) Kalman filter Nonlinear system Noise (video) Context (archaeology) Extended Kalman filter Filter (signal processing) System identification Computer science Estimation theory Mathematics Identification (biology) Nonlinear filter Algorithm Filter design Statistics Artificial intelligence Data modeling This paper presents the application of nonlinear Bayesian filtering–based system identification (SI) methods when employed to estimate the parameters of stochastic fractional dynamic systems. The objective is to demonstrate the capabilities and limitations of time-domain stochastic filtering–based SI for systems endowed with fractional derivative elements when the estimation is performed under different operating conditions. The conditions include measured forcing inputs (input-output identification), stochastic/unmeasured forcing inputs (output-only identification), and different types of measurements and levels of measurement noise, in the context of both linear and hysteretic fractional oscillators. The accuracy and estimation error of three methods was studied, namely, the unscented Kalman filter, the ensemble Kalman filter, and the particle filter. Baseline results that can be applied to the modeling, identification, and control of fractional structural and mechanical systems are provided. It is shown that nonlinear Bayesian filtering methods have the capability to accurately estimate the response and parameters of fractional oscillators, and that the coefficient and order of fractional elements are observable/identifiable from output response measurements. 2024 en info:eu-repo/semantics/article journal-article https://doi.org/10.1061/jenmdt.emeng-7482 Journal of Engineering Mechanics Journal of Engineering Mechanics urn:issn:0733-9399 urn:issn:1943-7889 Journal of Engineering Mechanics, 2024, vol. 150, n. 2 info:eu-repo/semantics/closedAccess closedAccess Q1 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Stochastic Analysis of Fractional Structural Systems Subjected to Fractional Ground Motions Kalil Erazo Pol D. Spanos Fractional Brownian motion Covariance Structural system Dissipation Superposition principle Fractional calculus Stochastic process Discretization Linear system In this paper, the nonstationary stochastic response of fractional structural systems subjected to fractional excitations is examined. Fractional operators provide an effective mathematical construct to model energy dissipation and stiffness–damping coupling mechanisms that cannot be modeled by integer operators. In particular, the memory property of fractional operators makes them suitable for treating the non-Markovian features exhibited by systems with path-dependent responses, such as the damping and stiffness mechanisms in structural systems and soils under dynamic loading. In this paper, particular attention is devoted to fractional structural systems excited by a proposed stochastic ground motion model consisting of a nonstationary filtered fractional Kanai–Tajimi process, thus accounting for path-dependent energy dissipation in both the structure and the seismic waves’ propagating medium. The work attempts to elucidate the sensitivity and effects on probabilistic structural response predictions due to non-Markovian features in the excitation when both the system and the excitation are modeled using fractional operators. To analyze the fractional operators describing the structure and soil, the operators are discretized and approximated as the superposition of the solutions of a system of linear first-order ordinary differential equations, which, together with the system dynamics equations, are transformed into an equivalent first-order linear state-space model. The stochastic response evaluation for the system is conducted in closed form by solving the associated Lyapunov covariance equation. The analytical results from stochastic analyses are juxtaposed with pertinent Monte Carlo simulations to demonstrate the accuracy of the proposed method. Validation results using measured data from the 2023 Turkey–Syria earthquake demonstrated that the recorded ground motions exhibit fractional features with an energy rate of decay in the spectral density that is captured more accurately by the proposed fractional model than the traditional integer Kanai–Tajimi model. 2026 en info:eu-repo/semantics/article journal-article https://doi.org/10.1061/jenmdt.emeng-8901 Journal of Engineering Mechanics Journal of Engineering Mechanics urn:issn:0733-9399 urn:issn:1943-7889 Journal of Engineering Mechanics, 2026, vol. 152, n. 8 info:eu-repo/semantics/closedAccess closedAccess Q1 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Seismic Response Estimation and Performance Assessment of Large-Scale Structures Using Deep-Learning Methods Kalil Erazo Jacob A. Morgan Oral Büyüköztürk Robustness (evolution) Artificial neural network Nonlinear system Earthquake shaking table Convolutional neural network Context (archaeology) Earthquake engineering Experimental data Applications of machine learning (ML) in structural engineering and mechanics have increased substantially in recent years. Interest in ML stems from its potential to handle complex problems with increased accuracy and/or computational efficiency compared with traditional methods when a sufficient amount of data is available. This study explored the application of deep neural networks to seismic response and damage estimation for large-scale civil structures in the context of performance-based earthquake engineering. The objective was to experimentally validate the accuracy and efficiency of modified versions of the long short-term memory (LSTM) neural network and the physics-guided convolutional neural network (PhyCNN) in structures subjected to base excitations in linear and nonlinear response regimes. In particular, the robustness of the methods to predict the response and state of integrity of structures undergoing severe damage due to strong base motions when the methods are trained using limited low-amplitude linear input–output data was assessed. The performance and predicting capabilities of the methods were evaluated using experimental data from two full-scale case studies: a six-story building structure in San Bernardino, California, instrumented as part of the California Strong Motion Instrumentation Program (CSMIP), and a seven-story full-scale shear wall structure tested on the high-performance outdoor shake table at the University of California at San Diego. The results show that deep neural networks have limited robustness when applied to estimate response features outside the training domain, with a significant reduction in the prediction accuracy if the level of nonlinearity for prediction is higher than in the training data set. 2026 en info:eu-repo/semantics/article journal-article https://doi.org/10.1061/jsendh.steng-14737 Journal of Structural Engineering Journal of Structural Engineering urn:issn:0733-9445 urn:issn:1943-541X Journal of Structural Engineering, 2026, vol. 152, n. 2 info:eu-repo/semantics/closedAccess closedAccess Q1 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal On-line response and damage estimation of a shear wall structure tested on a shake table using Bayesian filtering Kalil Erazo Satish Nagarajaiah Earthquake shaking table Shear wall Acceleration Bayesian probability Response analysis Structural engineering Computer science Engineering Artificial intelligence Physics This paper presents the application of a probabilistic method to estimate the complete dynamic response and state of damage of a large-scale structural system subjected to strong base excitations. The structure considered consists of a sevenstory slice of a shear wall building tested at the George E. Brown Jr. Network for Earthquake Engineering Simulation site at the University of California at San Diego. The acceleration response measured at limited locations is combined with a nonlinear model to estimate the complete dynamic response at unmeasured degrees of freedom. To improve the predicting capability of the mathematical model a subset of the parameters is jointly estimated with the response, a strategy known as joint state-parameter estimation or augmented state estimation. The estimated response is used to compute a damage index as a quantitative measure of damage. 2019 en info:eu-repo/semantics/conferenceObject proceedings-article https://doi.org/10.1117/12.2527936 Proceedings of SPIE - The International Society for Optical Engineering Proceedings of SPIE - The International Society for Optical Engineering Proceedings of SPIE - The International Society for Optical Engineering, 2019, vol. 2, p. 114 info:eu-repo/semantics/closedAccess closedAccess Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Structural health monitoring of civil infrastructure using applied recursive bayesian estimation methods Kalil Erazo Satish Nagarajaiah Estimation Bayesian probability Computer science Econometrics Engineering Artificial intelligence Mathematics Systems engineering 2022 en info:eu-repo/semantics/bookPart book-chapter https://doi.org/10.1142/9789811243011_0006 Recent Developments In Structural Health Monitoring And Assessment - Opportunities And Challenges: Bridges, Buildings And Other Infrastructures Recent Developments In Structural Health Monitoring And Assessment - Opportunities And Challenges: Bridges, Buildings And Other Infrastructures Recent Developments In Structural Health Monitoring And Assessment - Opportunities And Challenges: Bridges, Buildings And Other Infrastructures, 2022, p. 171-195 info:eu-repo/semantics/closedAccess closedAccess Industry, innovation and infrastructure Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Seismic fragility curves for a concrete bridge using structural health monitoring and digital twins 2022 info:eu-repo/semantics/article journal-article https://doi.org/10.12989/eas.2022.22.5.503 Earthquake and Structures Earthquake and Structures Earthquake and Structures, 2022 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Structural monitoring and identification of civil infrastructure in the United States Kalil Erazo Satish Nagarajaiah Structural health monitoring Civil infrastructure Identification (biology) Structural system Engineering Structural integrity Forensic engineering Construction engineering Scale (ratio) Risk analysis (engineering) Process (computing) Civil engineering Computer science Structural engineering Business Monitoring the performance and estimating the remaining useful life of aging civil infrastructure in the United States has been identified as a major objective in the civil engineering community. Structural health monitoring has emerged as a central tool to fulfill this objective. This paper presents a review of the major structural monitoring programs that have been recently implemented in the United States, focusing on the integrity and performance assessment of large-scale structural systems. Applications where response data from a monitoring program have been used to detect and correct structural deficiencies are highlighted. These applications include (but are not limited to): i) Post-earthquake damage assessment of buildings and bridges; ii) Monitoring of cables vibration in cable-stayed bridges; iii) Evaluation of the effectiveness of technologies for retrofit and seismic protection, such as base isolation systems; and iv) Structural damage assessment of bridges after impact loads resulting from ship collisions. These and many other applications show that a structural health monitoring program is a powerful tool for structural damage and condition assessment, that can be used as part of a comprehensive decision-making process about possible actions that can be undertaken in a large-scale civil infrastructure system after potentially damaging events. 2016 en info:eu-repo/semantics/article journal-article https://doi.org/10.12989/smm.2016.3.1.051 Structural Monitoring and Maintenance Structural Monitoring and Maintenance urn:issn:2288-6605 urn:issn:2288-6613 Structural Monitoring and Maintenance, 2016, vol. 3, n. 1, p. 51-69 info:eu-repo/semantics/openAccess openAccess cc-by https://doi.org/10.12989/smm.2016.3.1.051 Q3 Industry, innovation and infrastructure Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Updated Seismic Hazard Curves, Maps, and Spectra for the Northern Dominican Republic using a Probabilistic Seismic Hazard Analysis Kalil Erazo Seismology Seismic hazard Hazard Probabilistic logic Geology Hazard map Geography Statistics Mathematics Landslide 2022 en info:eu-repo/semantics/preprint preprint https://doi.org/10.21203/rs.3.rs-2082413/v1 Research Square Research Square Research Square, 2022 info:eu-repo/semantics/openAccess openAccess cc-by https://www.researchsquare.com/article/rs-2082413/latest.pdf Sustainable cities and communities Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Updated Seismic Hazard Curves, Maps, and Spectra for the Northern Dominican Republic using a Probabilistic Seismic Hazard Analysis Kalil Erazo Seismic hazard Seismology Peak ground acceleration Incremental Dynamic Analysis Geology Induced seismicity Earthquake scenario Earthquake simulation Building code Spectral acceleration Seismic risk Poisson distribution Ground motion Statistics Mathematics Engineering Structural engineering 2022 en info:eu-repo/semantics/other other https://doi.org/10.21203/rs.3.rs-2082413/v2 Research Square Research Square Research Square, 2022 info:eu-repo/semantics/openAccess openAccess cc-by https://doi.org/10.21203/rs.3.rs-2082413/v2 Sustainable cities and communities Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Analysis of ground motion intensity measures for records of the 2023 Turkey-Syria earthquake Kalil Erazo Peak ground acceleration Spectral acceleration Intensity (physics) Seismology Context (archaeology) Seismic hazard Ground motion Strong ground motion Geology Acceleration Event (particle physics) Earthquake scenario Geodesy Environmental science Physics Abstract Ground motion intensity measures (GMIM) provide a quantitative metric of the strength of a ground motion with the goal of providing a mapping to the potential damaging effects induced by earthquakes. The potential correlation between GMIM and earthquake damage allows their use in earthquake engineering applications such as (pre-event) seismic hazard/risk assessment and mitigation, and (post-event) damage assessment and resources allocation for disasters response. GMIM are also used for damage prediction in the context of performance-based earthquake engineering and earthquake-resistant design. This paper presents the evaluation of GMIM using strong motion records obtained during the 2023 Turkey-Syria earthquake. The GMIM studied include peak ground acceleration, peak ground velocity, spectral accelerations, root-mean-square acceleration, Arias intensity, cumulative absolute velocity, Housner spectral intensity, and Araya-Saragoni intensity. The GMIM are evaluated at several spatial locations where ground motion records were measured during the events. Examination of the results show that some of the GMIM showed particularly high values at locations where severe damage was observed after the earthquake. It is also shown that the maximum considered earthquake (MCE) spectra was exceeded at several locations where extensive damage was observed. 2023 en info:eu-repo/semantics/other other https://doi.org/10.21203/rs.3.rs-3761020/v1 Research Square Research Square Research Square, 2023 info:eu-repo/semantics/openAccess openAccess cc-by https://www.researchsquare.com/article/rs-3761020/latest.pdf Climate action Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Identification of Nonlinear Structural and Mechanical Systems Using Bayesian Filtering Methods Kalil Erazo Identification (biology) Bayesian probability Nonlinear system Computer science System identification Mathematics Algorithm Econometrics Artificial intelligence Data mining Physics 2023 en info:eu-repo/semantics/other other https://doi.org/10.2139/ssrn.4552248 SSRN SSRN urn:issn:1556-5068 SSRN, 2023 info:eu-repo/semantics/openAccess openAccess https://doi.org/10.2139/ssrn.4552248 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Seismic Response Estimation and Performance Assessment in Large-Scale Structures Using Deep Learning Methods Kalil Erazo Jacob A. Morgan Oral Büyüköztürk Scale (ratio) Estimation Computer science Artificial intelligence Deep learning Machine learning Seismology Geology Engineering Geography Cartography Systems engineering 2024 en info:eu-repo/semantics/other other https://doi.org/10.2139/ssrn.4978015 SSRN SSRN urn:issn:1556-5068 SSRN, 2024 info:eu-repo/semantics/openAccess openAccess https://doi.org/10.2139/ssrn.4978015 Climate action Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Probabilistic seismic hazard analysis and design earthquake for Santiago, Dominican Republic Erazo, Kalil Riesgos sísmicos Análisis de riesgo de terremotos This article presents the results of a probabilistic seismic hazard analysis (PSHA) conducted for a site in the city of Santiago, located in the Dominican Republic. To perform the PSHA recent seismological data of the Septentrional fault (seismic source) is used to calibrate an earthquake recurrence model, and to compute the seismic hazard curves of several earthquake, ground motion, and structural response parameters of interest in earthquake engineering applications. The parameters studied include horizontal peak ground acceleration and 5 % damping pseudo-acceleration response spectrum ordinates. The effect of uncertainty in the seismic fault rupture zone location is studied using a Monte Carlo analysis; for this purpose, the rupture location is treated as a random variable along the fault. The PSHA results are compared to the site design response spectrum with 2 % exceedance probability in 50 years specified in the Dominican Republic building code. It is concluded that there is a 17 % probability that the actual 2 % exceedance spectrum ordinates are greater than those specified in the design spectrum due to uncertainties related to the attenuation law employed to relate earthquake source and ground motion characteristics at the site. Based on the attenuation model, the design spectrum at the site is consistent with the spectrums generated by a 7.9 (moment) magnitude earthquake, which is close to the 7.8 magnitude characteristic earthquake estimated in previous studies for the Septentrional fault. 2019 spa info:eu-repo/semantics/bookPart book-chapter https://doi.org/10.22206/cyap.2019.v2i1.pp67-84 Ciencia, ingenierías & aplicaciones Ciencia, ingenierías & aplicaciones urn:issn:2636-218X (impreso) urn:issn:2636-2171 (en linea) Ciencia, ingenierías & aplicaciones, 2019 info:eu-repo/semantics/closedAccess closedAccess Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Analysis of Fractional Dynamical Systems Using Recursive Bayesian Estimation Methods and Response Data Kalil Erazo Alberto Di Matteo Pol D. Spanos Bayesian probability Recursive Bayesian estimation Estimation Computer science Bayes estimator Mathematics Applied mathematics Statistics Engineering The research titled Analysis of fractional dynamical systems using recursive Bayesian estimation methods and response data was presented at the Engineering Mechanics Institute Conference and Probabilistic Mechanics & Reliability Conference (EMI/PMC 2024), University of Illinois Urbana-Champaign, Chicago, IL, May 28-31 2024, as part of the Minisymposium Computational methods for stochastic engineering dynamics. 2024 en info:eu-repo/semantics/article journal-article https://doi.org/10.22206/cyap.2024.v7i2.3338 Ciencia, Ingenierías y Aplicaciones Ciencia, Ingenierías y Aplicaciones urn:issn:2636-2171 urn:issn:2636-218X Ciencia, Ingenierías y Aplicaciones, 2024, vol. 7, n. 2, p. 139-141 info:eu-repo/semantics/openAccess openAccess cc-by-nc-sa https://revistas.intec.edu.do/index.php/cite/article/download/3338/3827 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Experimental verification of a finite element model based functional observer for structural systems Kalil Erazo Eric M. Hernandez Finite element method Computer science Observer (physics) Element (criminal law) Structural engineering Engineering Physics The objective of this paper is to present the results of an experimental study aimed at verifying the performance of an algorithm developed by one of the authors for state estimation in structural and mechanical systems subject to unmeasured excitations realizations of random processes with known spectral density matrix. The proposed algorithm operates as a modified finite element model of the original system, driven by corrective forces which are linear combinations of the noise contaminated measurements. The proposed method is capable of handling large-scale finite element models, and any quantity in the modified model constitutes an estimate of the corresponding quantity in the system. A laboratory model consisting of an aluminium cantilever beam was used to perform the test, where two types of loading conditions were tested: an impact hammer test and a banded white noise excitation through a shaker. The experimental results of the proposed estimator are compared to other techniques, such as a Luenberger observer and the Kalman filter. The quality displayed by the proposed observer exceeded or was comparable to the compared methods with the advantage of reduced computational cost. 2013 en info:eu-repo/semantics/conferenceObject proceedings-article https://doi.org/10.2514/6.2013-1897 54th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference 54th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference 54th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 2013 info:eu-repo/semantics/closedAccess closedAccess Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Disaggregated Empirical Fragility Modeling and Bayesian Parameter Updating for Buildings in Haiti Kalil Erazo Marc-Ansy Laguerre Fragility Bayesian probability Baseline (sea) Markov chain Range (aeronautics) Bayesian inference Vulnerability (computing) Incremental Dynamic Analysis Quantifying the vulnerability of buildings is fundamental to seismic risk mitigation, and fragility curves are among the most widely used tools for this purpose. With the growing availability and access to post-earthquake damage data from reconnaissance campaigns and measured ground motion parameters, new opportunities have emerged to derive and refine fragility models, improving the seismic damage prediction models and the quantification of seismic risk. Following the 2010 Haiti earthquake, extensive datasets were compiled that include both structural and geotechnical characteristics, as well as observed damage states for a wide range of building classes. In this study, two such datasets are employed in a complementary manner to develop disaggregated fragility models to probabilistically quantify structural damage conditioned on specific building and site attributes, rather than parameters averaged over an entire building stock. The first dataset comprises approximately 335,000 building assessment tags collected, and it is used to develop a set of baseline fragility curves conditioned on parameters such as number of stories, soil type, wall system, topography, roof type, and building age. The second dataset comprises 170 reinforced concrete buildings with more detailed and reliable information, and it is used to update the baseline fragility models using Bayesian estimation. The Bayesian updating introduces fragilities specific to the presence of captive columns and priority index, a metric representing the ratio of wall and column area to floor area. Bayesian updating is performed within a Markov Chain Monte Carlo (MCMC) framework using the Metropolis–Hastings algorithm. The resulting fragility functions reveal the high vulnerability of the Haitian building stock and demonstrate how multiple site and structural attributes influence seismic fragility. 2026 en info:eu-repo/semantics/article journal-article https://doi.org/10.3390/buildings16061137 Buildings Buildings urn:issn:2075-5309 Buildings, 2026, vol. 16, n. 6, p. 1137 info:eu-repo/semantics/openAccess openAccess cc-by https://www.mdpi.com/2075-5309/16/6/1137/pdf?version=1773371176 Q1 doaj Sustainable cities and communities Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Parameter Estimation of Nonlinear Structural Systems Using Bayesian Filtering Methods Kalil Erazo Nonlinear system Estimation Bayesian probability Recursive Bayesian estimation Computer science Bayes estimator Mathematics Algorithm Applied mathematics Artificial intelligence Engineering Physics This paper examines the performance of Bayesian filtering system identification in the context of nonlinear structural and mechanical systems. The objective is to assess the accuracy and limitations of the four most well-established filtering-based parameter estimation methods: the extended Kalman filter, the unscented Kalman filter, the ensemble Kalman filter, and the particle filter. The four methods are applied to estimate the parameters and the response of benchmark dynamical systems used in structural mechanics, including a Duffing oscillator, a hysteretic Bouc–Wen oscillator, and a hysteretic Bouc–Wen chain system. Based on the performance, accuracy, and computational efficiency of the methods under different operating conditions, it is concluded that the unscented Kalman filter is the most effective filtering system identification method for the systems considered, with the other filters showing large estimation errors or divergence, high computational cost, and/or curse of dimensionality as the dimension of the system and the number of uncertain parameters increased. 2024 en info:eu-repo/semantics/article journal-article https://doi.org/10.3390/vibration8010001 Vibration Vibration urn:issn:2571-631X Vibration, 2024, vol. 8, n. 1, p. 1 info:eu-repo/semantics/openAccess openAccess cc-by https://www.mdpi.com/2571-631X/8/1/1/pdf?version=1735631869 Q2 doaj Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Real-time efficient state estimation in nonlinear structural systems 2014 info:eu-repo/semantics/conferenceObject proceedings-article cris:cris-3b26db5c Proceedings of the International Conference on Structural Dynamic , EURODYN Proceedings of the International Conference on Structural Dynamic , EURODYN Proceedings of the International Conference on Structural Dynamic , EURODYN, 2014 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Análisis probabilístico de peligro sísmico y terremoto de diseño para Santiago-República Dominicana Erazo, Kalil Probabilidades Análisis de riesgo sísmico Análisis de riesgo de terremotos Este artículo presenta los resultados de un Análisis Probabilístico de Peligro Sísmico (APPS) realizado para un sitio ubicado en el centro de la ciudad de Santiago, localizada en la República Dominicana. Para realizar el APPS se utilizaron datos sismológicos recientes de la falla Septentrional (fuente sísmica) con el fin de calibrar un modelo de recurrencia de terremotos, y para calcular las curvas de peligro sísmico de varios parámetros de terremotos, movimiento del suelo y respuesta estructural de interés en aplicaciones de ingeniería sísmica. Los parámetros estudiados incluyen aceleración horizontal pico del suelo y ordenadas del espectro de respuesta de pseudo-aceleración con 5 % de amortiguamiento. El efecto de la incertidumbre de la ubicación de la zona de ruptura en la falla es estudiado usando un análisis de Monte Carlo; con este propósito la ubicación de la ruptura se trata como una variable aleatoria uniforme en la longitud de la falla. Los resultados del APPS son comparados con el espectro de diseño del sitio con 2 % de probabilidad de excedencia en 50 años, especificado en la normativa de diseño de la República Dominicana. Se concluye que hay un 17 % de probabilidad de que el valor actual de las ordenadas espectrales con 2 % de excedencia sea mayor que el valor especificado en el espectro de diseño, debido a incertidumbres relacionadas a la ley de atenuación usada para relacionar la fuente de terremotos y las características del movimiento del suelo en el sitio. Basado en el modelo de atenuación, el espectro de diseño en el sitio es consistente con los espectros generados por terremotos de magnitud (momento) de 7.9, lo cual es cercano al terremoto característico de magnitud de 7.8 estimado en estudios recientes de la falla Septentrional. 2020 spa info:eu-repo/semantics/bookPart book-chapter cris:cris-3d37bd94 Ciencia, ingenierías & aplicaciones Ciencia, ingenierías & aplicaciones urn:issn:2636-2171 (en linea) Ciencia, ingenierías & aplicaciones, 2020 info:eu-repo/semantics/openAccess openAccess https://revistas.intec.edu.do/index.php/cite/article/view/1741 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Nonlinear model-data fusion for post-earthquake assessment of structures 2013 info:eu-repo/semantics/conferenceObject proceedings-article cris:cris-3f105141 Structural Health Monitoring 2013: A Roadmap to Intelligent Structures - Proceedings of the 9th International Workshop on Structural Health Monitoring, IWSHM 2013 Structural Health Monitoring 2013: A Roadmap to Intelligent Structures - Proceedings of the 9th International Workshop on Structural Health Monitoring, IWSHM 2013 Structural Health Monitoring 2013: A Roadmap to Intelligent Structures - Proceedings of the 9th International Workshop on Structural Health Monitoring, IWSHM 2013, 2013 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Demandas estructurales inducidas por vientos huracanados y terremotos en un edificio flexible en la República Dominicana Erazo, Kalil Taveras, Adela Estructuras sismoresistentes Edificios Este artículo presenta los resultados de un análisis comparativo de las demandas estructurales inducidas por vientos huracanados y terremotos en un edificio flexible diseñado para la ciudad de Santo Domingo en la República Dominicana. La estructura consiste en un edificio de 33 niveles con periodos fundamentales de vibración mayores de 3 segundos en las dos principales direcciones ortogonales, por lo que se considera un edificio flexible. El edificio fue inicialmente diseñado para cumplir con los requerimientos de la normativa vigente para efectos inducidos por terremotos (R-001) sin tomar en consideración los efectos inducidos por vientos huracanados; subsecuentemente, las demandas inducidas por viento fueron estimadas usando el procedimiento direccional del ASCE 07-10, utilizando como base la velocidad de diseño en recientes mapas de amenaza de viento desarrollados para la región del Caribe. Los resultados muestran que para la estructura analizada los efectos de vientos son significativamente mayores a los efectos sísmicos, lo que evidencia la urgencia de actualizar la actual normativa que define las cargas mínimas de diseño por viento de la República Dominicana. La justificación de dicha urgencia es el auge en la construcción de estructuras flexibles (principalmente edificios esbeltos) cuyo comportamiento tiende a ser dominado por efectos inducidos por viento, en especial en regiones de alta recurrencia de huracanes. Las demandas estructurales comparadas incluyen desplazamientos laterales, derivas de entrepiso, cortante basal y momento de vuelco. 2021 spa info:eu-repo/semantics/bookPart book-chapter cris:cris-99940002 Ciencia, ingenierías & aplicaciones Ciencia, ingenierías & aplicaciones urn:issn:2636-218X (impreso) urn:issn:2636-2171 (en linea) Ciencia, ingenierías & aplicaciones, 2021 info:eu-repo/semantics/openAccess openAccess https://revistas.intec.edu.do/index.php/cite/article/view/2247/2646 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal Experimental verification of a finite element model based functional observer for structural systems 2013 info:eu-repo/semantics/conferenceObject proceedings-article cris:cris-bc276454 Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, 2013 Instituto Tecnológico de Santo Domingo https://www.intec.edu.do/portal