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In this study, we characterize the dependence of modeling parameters that define a structure's nonlinear response at a component level, and the interactions of multiple components associated with a structure's response.
This study revealed that the most important modeling parameters that affect critical components responses of MSC and MSSS bridges are the isolator effective stiffness, the abutment stiffness, and the gap between abutment and deck, in addition to the variation in gross bridge geometry and ground-motion contents.
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In (7), the distributions and are the model parameters that should be estimated from training data.
They are usually implemented with the model parameters that are extracted offline.
Covariances of model parameters that can be estimated are strongly dependent on the physics.
Model parameters that have some level of uncertainty are probabilistically described.
A procedure is described for calibration of the model parameters that uses information from isothermal experiments.
The model parameters that are necessary are adapted to one single experiment.
The first one is based on learning the model parameters that maximizes the likelihood of the training data.
b s, b f, and b p are model parameters that depend on the video content [33, 34].
Repeat step 2 to obtain the model parameters that would be used to develop the response surface function.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com