Journal Articles
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 | Ipar Ferhat; Rodrigo Sarlo; Pablo A Tarazaga 3D Modal Analysis of a Loaded Tire with Binary Random Noise Excitation Journal Article Tire Science And Technology, 48 (3), pp. 207–223, 2020. Links | BibTeX @article{ferhat20203d,
title = {3D Modal Analysis of a Loaded Tire with Binary Random Noise Excitation},
author = {Ipar Ferhat and Rodrigo Sarlo and Pablo A Tarazaga},
doi = {https://doi.org/10.2346/tire.19.170166},
year = {2020},
date = {2020-01-01},
journal = {Tire Science And Technology},
volume = {48},
number = {3},
pages = {207--223},
publisher = {The Tire Society},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
 | Rodrigo Sarlo; Pablo A Tarazaga; Mary E Kasarda High Resolution Operational Modal Analysis on a Five-Story Smart Building under Wind and Human Induced Excitation Journal Article Engineering Structures, 2018. Links | BibTeX @article{Sarlo2018,
title = {High Resolution Operational Modal Analysis on a Five-Story Smart Building under Wind and Human Induced Excitation},
author = {Rodrigo Sarlo and Pablo A Tarazaga and Mary E Kasarda},
doi = {https://doi.org/10.1016/j.engstruct.2018.08.060},
year = {2018},
date = {2018-01-01},
journal = {Engineering Structures},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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Inproceedings
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| E Kessler; V V N S Malladi; Rodrigo Sarlo; L A Martin; Pablo A Tarazaga Comparison of modal parameters of a concrete slab floor from ema and oma Inproceedings Conference Proceedings of the Society for Experimental Mechanics Series, 2021, ISSN: 21915652. Abstract | Links | BibTeX @inproceedings{Kessler2021,
title = {Comparison of modal parameters of a concrete slab floor from ema and oma},
author = {E Kessler and V V N S Malladi and Rodrigo Sarlo and L A Martin and Pablo A Tarazaga},
doi = {10.1007/978-3-030-47634-2_27},
issn = {21915652},
year = {2021},
date = {2021-01-01},
booktitle = {Conference Proceedings of the Society for Experimental Mechanics Series},
abstract = {textcopyright 2021, The Society for Experimental Mechanics, Inc. In this study, the modal parameters of a hallway floor in Goodwin Hall are compared with experimental modal analysis (EMA) and operational modal analysis (OMA). A set of 17 high sensitivity accelerometers mounted to structural beams under the floor of the hallway will be used to measure the floor response. In EMA an instrumented hammer was used to measure the input, while in OMA ambient excitation was used to excite the floor. The natural frequency, damping ratio, and mode shape estimates for the first five modes of the floor will be compared between the two methods. Despite limitations with generating enough energy to excite standing waves, the modal parameters between EMA and OMA match well. Frequency differences are less than 10%, and all the damping ratio estimates between 2% and 10%. Mode shapes also match well visually, and the MAC shows agreement between methods. Both EMA and OMA show the ability to extract modal parameters from the floor, where the mode shapes show global motion of the floor instead of only local motion between supports.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
textcopyright 2021, The Society for Experimental Mechanics, Inc. In this study, the modal parameters of a hallway floor in Goodwin Hall are compared with experimental modal analysis (EMA) and operational modal analysis (OMA). A set of 17 high sensitivity accelerometers mounted to structural beams under the floor of the hallway will be used to measure the floor response. In EMA an instrumented hammer was used to measure the input, while in OMA ambient excitation was used to excite the floor. The natural frequency, damping ratio, and mode shape estimates for the first five modes of the floor will be compared between the two methods. Despite limitations with generating enough energy to excite standing waves, the modal parameters between EMA and OMA match well. Frequency differences are less than 10%, and all the damping ratio estimates between 2% and 10%. Mode shapes also match well visually, and the MAC shows agreement between methods. Both EMA and OMA show the ability to extract modal parameters from the floor, where the mode shapes show global motion of the floor instead of only local motion between supports. |
| Rodrigo Sarlo; Pablo A Tarazaga Modal parameter uncertainty estimates as a tool for automated operational modal analysis: Applications to a smart building Inproceedings Conference Proceedings of the Society for Experimental Mechanics Series, 2019, ISSN: 21915652. Abstract | Links | BibTeX @inproceedings{Sarlo2019b,
title = {Modal parameter uncertainty estimates as a tool for automated operational modal analysis: Applications to a smart building},
author = {Rodrigo Sarlo and Pablo A Tarazaga},
doi = {10.1007/978-3-319-74421-6_23},
issn = {21915652},
year = {2019},
date = {2019-01-01},
booktitle = {Conference Proceedings of the Society for Experimental Mechanics Series},
abstract = {textcopyright The Society for Experimental Mechanics, Inc 2019. The knowledge of modal parameter uncertainties derived from operational modal analysis (OMA) can greatly improve automated decisions by providing information about the quality of the modal identification. Yet so far, this information has been largely ignored in continuous monitoring studies on civil infrastructure, especially with respect to buildings. In this paper, we implement an automated version of Covariance Based Stochastic Subspace Identification on a highly instrumented smart building. An expansion of the technique estimates uncertainty bounds for all modal parameters. Through a series of full scale experiments, we demonstrate how uncertainties are valuable tools in various contexts of automation. These include the identification and removal of badly-fitted modes, the identification of periods of high signal-to-noise ratio, and the validation of reference sensors selection.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
textcopyright The Society for Experimental Mechanics, Inc 2019. The knowledge of modal parameter uncertainties derived from operational modal analysis (OMA) can greatly improve automated decisions by providing information about the quality of the modal identification. Yet so far, this information has been largely ignored in continuous monitoring studies on civil infrastructure, especially with respect to buildings. In this paper, we implement an automated version of Covariance Based Stochastic Subspace Identification on a highly instrumented smart building. An expansion of the technique estimates uncertainty bounds for all modal parameters. Through a series of full scale experiments, we demonstrate how uncertainties are valuable tools in various contexts of automation. These include the identification and removal of badly-fitted modes, the identification of periods of high signal-to-noise ratio, and the validation of reference sensors selection. |
| Rodrigo Sarlo; Pablo A Tarazaga Modal Parameter Uncertainty Estimates as a Tool for Automated Operational Modal Analysis : Applications to a Smart Building Inproceedings Proceedings of 36th International Modal Analysis Conference (IMAC-XXXVI): A Conference on Structural Dynamics, Vol. 1, Springer, Orlando, Florida, 2018. BibTeX @inproceedings{SarloIMAC2018,
title = {Modal Parameter Uncertainty Estimates as a Tool for Automated Operational Modal Analysis : Applications to a Smart Building},
author = {Rodrigo Sarlo and Pablo A Tarazaga},
year = {2018},
date = {2018-01-01},
booktitle = {Proceedings of 36th International Modal Analysis Conference (IMAC-XXXVI): A Conference on Structural Dynamics, Vol. 1},
publisher = {Springer},
address = {Orlando, Florida},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
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| Rodrigo Sarlo; Pablo A Tarazaga; M E Kasarda Operational modal analysis of a steel-frame, low-rise building with L-shaped construction Inproceedings Proceedings of SPIE - The International Society for Optical Engineering, 2017, ISSN: 1996756X. Abstract | Links | BibTeX @inproceedings{Sarlo2017,
title = {Operational modal analysis of a steel-frame, low-rise building with L-shaped construction},
author = {Rodrigo Sarlo and Pablo A Tarazaga and M E Kasarda},
doi = {10.1117/12.2260340},
issn = {1996756X},
year = {2017},
date = {2017-01-01},
booktitle = {Proceedings of SPIE - The International Society for Optical Engineering},
volume = {10168},
abstract = {textcopyright 2017 SPIE. The Goodwin Hall Smart Infrastructure facility at Virginia Tech is a five-story "smart building" with an integrated network of 213 wired accelerometers. We utilize a subset of 68 sensors to perform high-resolution Operational Modal Analysis (OMA) of the structure under windy conditions. The low-rise, L-shaped construction and high mass, high stiffness properties of Goodwin Hall provide a unique case study in comparison to typical cases of building OMA in literature, which generally feature high-rise buildings with rectangular architectures. Our work focuses on data acquisition and feature extraction, which are two critical steps within a complete structural health monitoring approach. Our detailed methodology establishes guidelines for sensor selection and data processing applicable to this and more general cases. Modal parameters extraction using Stochastic Subspace Identification shows the first four natural frequencies, damping values, participation factors and mode shapes of the building. We hypothesize that high damping values and large differences in the participation of fundamental modes are related to the nature of the wind excitation.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
textcopyright 2017 SPIE. The Goodwin Hall Smart Infrastructure facility at Virginia Tech is a five-story "smart building" with an integrated network of 213 wired accelerometers. We utilize a subset of 68 sensors to perform high-resolution Operational Modal Analysis (OMA) of the structure under windy conditions. The low-rise, L-shaped construction and high mass, high stiffness properties of Goodwin Hall provide a unique case study in comparison to typical cases of building OMA in literature, which generally feature high-rise buildings with rectangular architectures. Our work focuses on data acquisition and feature extraction, which are two critical steps within a complete structural health monitoring approach. Our detailed methodology establishes guidelines for sensor selection and data processing applicable to this and more general cases. Modal parameters extraction using Stochastic Subspace Identification shows the first four natural frequencies, damping values, participation factors and mode shapes of the building. We hypothesize that high damping values and large differences in the participation of fundamental modes are related to the nature of the wind excitation. |
PhD Theses
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| Rodrigo Sarlo High-Resolution , High-Frequency Modal Analysis for Instrumented Buildings PhD Thesis Virginia Tech, 2018. Links | BibTeX @phdthesis{SarloThesis2018,
title = {High-Resolution , High-Frequency Modal Analysis for Instrumented Buildings},
author = {Rodrigo Sarlo},
url = {https://vtechworks.lib.vt.edu/handle/10919/84477},
year = {2018},
date = {2018-01-01},
school = {Virginia Tech},
keywords = {},
pubstate = {published},
tppubtype = {phdthesis}
}
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