Refinement and Validation of the Simple Lateral Mechanism Analysis (SLaMA) Procedure for RC Frames

Pampanin

Raffaele

et al. 2019

Bull Earthquake Eng

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The simple lateral mechanism analysis (SLaMA) is an analytical method to assess the force-displacement capacity curve of Reinforced Concrete (RC) structures composed of frames, cantilever walls or dual wall/frame systems. The current version of the method was proposed in the 2017 New Zealand guidelines for the seismic assessment (NZSEE in New Zealand Society for Earthquake Engineering, the seismic assessment of existing buildings-technical guidelines for engineering assessments, Wellington, 2017). Regarding frame structures, the possible influence of infill walls is currently considered locally with checks on the RC members. However, it is universally known that infills have a major effect on the global capacity curve of the frame. In this paper, a comprehensive SLaMA method for infilled frames is proposed, which allows considering the influence of the infills on the global force-displacement curve without any numerical algorithm. The extended SLaMA method is herein formalised and it is validated in a companion paper (part 2) through an extensive parametric analysis. The extended SLaMA is based on the possibility to separately calculate the base shear contributions of the frame and the infills, in turn based on global equilibrium considerations. Such considerations also allow defining a novel procedure to post-process the results of pushover or time-history analyses where infills are modelled as diagonal struts, or to interpret experimental tests. This allows, within a single numerical analysis, to decouple the frame and infills contributions to the base-shear capacity. The decoupling procedure is herein demonstrated for an ideal two-storey, one-bay masonry-infilled frame with different infills configurations.Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Section: Slama Procedures For Infilled Framesmentioning

confidence: 99%

Section: Global Mechanisms Capacity Curves: Beam-sway and Mixed-swaymentioning

confidence: 99%

Section: Global Mechanisms Capacity Curves: Beam-sway and Mixed-swaymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Non-linear analysis of RC masonry-infilled frames using the SLaMA method: part 1—mechanical interpretation of the infill/frame interaction and formulation of the procedure

Pampanin

Raffaele

et al. 2019

Bull Earthquake Eng

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Hysteretic energy‐based state‐dependent fragility for ground‐motion sequences

Earthq Engng Struct Dyn

Galasso

2020

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A framework to derive state‐dependent fragility relationships of structures subjected to ground‐motion sequences (e.g. mainshock‐aftershock (MS‐AS) or triggered earthquakes) is proposed. The hysteretic energy dissipated in the sequence is adopted as the main demand parameter, as it is a cumulative measure monotonically increasing with the length of the excitation. For a structure subjected to earthquake‐induced ground motions, it is not possible to define a closed‐form representation of the hysteretic energy as a function of the peak deformation. However, based on theoretical considerations, the hysteretic energy‐peak deformation trend is discussed, highlighting that (a) the significant duration of the ground motion explains the variability of the hysteretic energy for a given peak deformation; (b) the hysteretic energy dissipated in an AS decreases (for a given AS peak displacement) if the peak displacement in the MS increases. A vector‐valued probabilistic seismic demand model consistent with these considerations is proposed in the form of a surface relating the hysteretic energy in the sequence to the peak deformation in the MS and a ground‐motion intensity measure of the AS. This is calibrated via sequential cloud‐based time‐history analyses. The framework is demonstrated for 14 reinforced concrete frame buildings with different height, plastic mechanisms, and infill distributions. The results show the feasibility of the proposed approach, effectively capturing damage accumulation without inconsistencies in the obtained statistical model. The framework may be used for risk‐assessment applications explicitly incorporating ground‐motion sequences. The hysteretic energy versus peak deformation relationship may also be exploited in problems involving long‐duration ground motions or soft soils.

A multi‐fidelity Bayesian framework for robust seismic fragility analysis

Sevieri

Earthq Engng Struct Dyn

Galasso

2021

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Fragility analysis of structures via numerical methods involves a complex trade‐off between the desired accuracy, the explicit consideration of uncertainties (both epistemic and aleatory) related to the numerical structural model and the available computational performance. This paper introduces a framework for deriving numerical fragility relationships based on multi‐fidelity non‐linear models of the structure under investigation and response‐analysis types. The proposed framework aims to reduce the computational burden while achieving a desired accuracy of the fragility estimates without neglecting aleatory and epistemic uncertainties. The proposed approach is an extension of the well‐known robust fragility (RF) analysis framework. Different model classes, each characterised by increasing refinement, are used to define multi‐fidelity polynomial expansions of the fragility model parameters. Each analysis result is then considered as a ‘new observation’ in a Bayesian framework and used to update the coefficients of the polynomial expansions. An adaptive sampling algorithm is also proposed to futher improve the performance of the multi‐fidelity framework. Specifically, such an adaptive sampling algorithm relies on partitioning the sample space and the Kullback–Leibler divergence to find the optimal sampling path. The sample space partitioning allows an analyst to specify different criteria and parameters of the algorithm for different regions, thus further improving the performance of the procedure. The proposed approach is illustrated for an archetype reinforced concrete (RC) frame for which two model classes are developed/analysed: the simple lateral mechanism analysis (SLaMA), coupled with the capacity spectrum method, and non‐linear dynamic analysis. Both model classes involve a cloud‐based approach employing unscaled real (i.e. recorded) ground motions. The fragility relationships derived with the proposed procedure are finally compared to those calculated by using only the most advanced/high‐fidelity (HF) model class, thus quantifying the performance of the proposed approach and highlighting further research needs.