Remaining stiffness estimation of buildings using incomplete measurements

Abstract

After hazardous events, it is important to be able to quickly identify the remaining stiffness of affected structures for condition evaluation. Model updating can be used to update structural models to reflect current conditions based upon experimental measurements. Direct model updating is a simple and quick method of damage detection, but does not guarantee physical relevance. Least-squares optimization can be used to accurately identify damage with physical relevance, but needs more measurements then updating parameters in order to produce an accurate solution. However, after an extreme event sensors on the structure may be damaged, creating a scenario with limited measurements which can render optimization techniques incapable of assessing the remaining stiffness. To address this issue, this paper proposes a two-phase method to localize and then quantify the remaining stiffness of the structure. Direct model updating with limited measurements is used to localize potential damage to a subset of parameters, and a least-squares optimization using the localized parameters is used to quantify the remaining stiffness in the structure. Numerical simulations using a simplified model based upon the phase I IASCE-ASCE structural health monitoring benchmark problem with missing first floor sensors have been employed to demonstrate, and experiments using a five-story steel frame structure are conducted to validate the methodology.

Remaining capacity estimation for buildings after an explosion using the adaptive alternate path analysis

“…The adaptive AP analysis utilizes an updated numerical model of the post-blast structure to incorporate additional elemental damage into the AP method. In this work, the numerical model is updated using a two-phase damage localization and quantification method developed by the authors (Eskew and Jang, 2017). The adaptive AP analysis is then performed on the updated numerical model.…”

Static structural system identification for beam-like structures using compatibility conditions

“…It is to highlight that a different set (e.g. {v 7 , w 8 , v 11 } or {v 9 , v 12 , v 13 }) does not affect the result. The general equations (Equation 4) corresponding with this FEM and {w 7 , v 10, w 13 } are obtained first (not shown here for the sake of brevity).…”

“…A comprehensive description and the associated categories of SSI are provided in the technical report of the American Society of Civil Engineers. [1] These categories include static [2][3][4][5][6][7] and dynamic excitations, [8][9][10][11][12][13][14] parametric [3,5] and non-parametric models, [8,[15][16][17] deterministic [2,[4][5][6]9,18,19] and probabilistic approaches. [10,[20][21][22][23][24] For both static and dynamic SSI methods, structural responses have to be measured to provide the necessary information.…”

“…In both probabilistic and deterministic methods, optimization technique is closely involved. The objective of the optimization might be minimizing the discrepancy between the measured response and the predicted response, for example, displacements, [4,5] strains, [2,5] loads vector, [5,6] acceleration, [18] mode shapes and frequencies, [9] or maximizing the sensitivity of the frequency response functions. [19] Observability Method (OM) is a mathematical tool dealing with the observability, that is, the existence and the uniqueness of the solution of a system of equations (or a subset of it).…”

“…In both probabilistic and deterministic methods, optimization technique is closely involved. The objective of the optimization might be minimizing the discrepancy between the measured response and the predicted response, for example, displacements, strains, loads vector, acceleration, mode shapes and frequencies, or maximizing the sensitivity of the frequency response functions …”