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18 April 2023 Long-term strain prediction in high-rise buildings (Conference Presentation)
Mauricio Pereira, Branko Glisic
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Proceedings Volume 12486, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2023; 124860K (2023) https://doi.org/10.1117/12.2659094
Event: SPIE Smart Structures + Nondestructive Evaluation, 2023, Long Beach, California, United States
Abstract
The long-term behavior of concrete is driven by rheological effects and impacts the safety and serviceability of high-rise buildings. Rheological effects are difficult to predict due to their dependence on environmental conditions and loading history. Recently, data-driven prediction using long-term structural health monitoring data have shown success in prestressed bridges. In this work, calibration of rheology models using long-term monitoring data towards forecasting of long-term behavior of high-rise buildings is investigated. A calibration strategy is identified that enables improved long-term forecast. The method is evaluated on data from two residential high-rise buildings.
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Mauricio Pereira and Branko Glisic "Long-term strain prediction in high-rise buildings (Conference Presentation)", Proc. SPIE 12486, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2023, 124860K (18 April 2023); https://doi.org/10.1117/12.2659094
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KEYWORDS
Buildings
Data modeling
Calibration
Structural health monitoring
Bridges
Earthquakes
Monte Carlo methods
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