Probabilistic study of the behavior of steel frames with partially restrained connections

Sakurai, Shuji; Ellingwood, Bruce R.; Kushiyama, Shigeru

doi:10.1016/s0141-0296(01)00052-9

Cited by 25 publications

(5 citation statements)

References 9 publications

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“…In this academic example, the frame is constructed with vertical columns that rest on fixed supports with beams that are semi-rigidly connected to the columns at both levels. In steel frame structures, the variability of the material properties, member sizes and construction practices results in highly uncertain connection stiffness values (Sakurai et al , 2001; Díaz et al , 2012). Hence, in our proof-of-concept example, the connection stiffness of the two first story joints is represented using linear rotational springs with uncertain and independent stiffness constants.…”

Section: Proof-of-concept Demonstration: Steel Moment Resisting Framementioning

confidence: 99%

Model assessment in scientific computing

Prabhu

Atamturktur

Cogan

2017

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Purpose This paper aims to focus on the assessment of the ability of computer models with imperfect functional forms and uncertain input parameters to represent reality. Design/methodology/approach In this assessment, both the agreement between a model’s predictions and available experiments and the robustness of this agreement to uncertainty have been evaluated. The concept of satisfying boundaries to represent input parameter sets that yield model predictions with acceptable fidelity to observed experiments has been introduced. Findings Satisfying boundaries provide several useful indicators for model assessment, and when calculated for varying fidelity thresholds and input parameter uncertainties, reveal the trade-off between the robustness to uncertainty in model parameters, the threshold for satisfactory fidelity and the probability of satisfying the given fidelity threshold. Using a controlled case-study example, important modeling decisions such as acceptable level of uncertainty, fidelity requirements and resource allocation for additional experiments are shown. Originality/value Traditional methods of model assessment are solely based on fidelity to experiments, leading to a single parameter set that is considered fidelity-optimal, which essentially represents the values which yield the optimal compensation between various sources of errors and uncertainties. Rather than maximizing fidelity, this study advocates for basing model assessment on the model’s ability to satisfy a required fidelity (or error tolerance). Evaluating the trade-off between error tolerance, parameter uncertainty and probability of satisfying this predefined error threshold provides us with a powerful tool for model assessment and resource allocation.

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Section: Proof-of-concept Demonstration: Steel Moment Resisting Framementioning

confidence: 99%

Model assessment in scientific computing

Prabhu

Atamturktur

Cogan

2017

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“…As reported, the buckling load or the equivalent buckling length factor of steel-frame structures is greatly influenced by stiffness of bracing elements and semi-rigid connections (Goto & Miyashita 1998;Raftoyiannis 2005;Lien et al 2012). Moreover, many studies (Tucker & Bennett 1990;Rauscher & Gerstle 1992;Gao & Haldar 1995;Sakurai & Ellingwood 2001;Huh & Haldar 2001) indicated that the stiffness of semi-rigid connections is actually uncertain, and this can influence the behavior of the structure significantly. Therefore, the uncertainty of the rigidity of the connections has to be taken into account in the analysis and design.…”

Section: Introductionmentioning

confidence: 99%

Evidence theory and differential evolution based uncertainty quantification for buckling load of semi-rigid jointed frames

Tang

Wang

2015

Sadhana

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The paper describes a procedure for the uncertainty quantification (UQ) using evidence theory in buckling analysis of semi-rigid jointed frame structures under mixed epistemic-aleatory uncertainty. The design uncertainties (geometrical, material, strength, and manufacturing) are often prevalent in engineering applications. Due to lack of knowledge or incomplete, inaccurate, unclear information in the modeling, simulation, measurement, and design, there are limitations in using only one framework (probability theory) to quantify uncertainty in a system because of the impreciseness of data or knowledge. Evidence theory provides an alternative to probability theory for the representation of epistemic uncertainty that derives from a lack of knowledge with respect to the appropriate values to use for various inputs to the model. Unfortunately, propagation of an evidence theory representation for uncertainty through a model is more computationally demanding than propagation of a probabilistic representation for uncertainty. In order to alleviate the computational difficulties in the evidence theory based UQ analysis, a differential evolution-based computational strategy for propagation of epistemic uncertainty in a system with evidence theory is presented here. A UQ analysis for the buckling load of steelplane frames with semi-rigid connections is given herein to demonstrate accuracy and efficiency of the proposed method.

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“…This means these values changes in the borders of a standard deviation. In spite of extensive research into deterministic analysis of PR connections composite construction [2][3][4][5][6][7][8][9], the stochastic dynamic analysis and design of this type of construction form cannot be fully utilized by engineers unless an efficient, robust and accurate method of analysis is available.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Finite Element Analysis of Composite Structures with Partially Restrained Connections under Earthquake Loads

Çavdar¹

2020

IJSEA

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The stochastic analysis of composite structures with partially restrained (PR) connections under seismic loads present some interesting and challenging issues to practicing engineers. This paper proposes an efficient, robust, and accurate method for stochastic finite element analysis of concrete–steel composite structures allowing for PR connections. These are followed by suitable numerical example which indicates that employment of such a stochastic finite element analysis. The Kocaeli earthquake in 1999 is considered as a ground motion. The connections parameters and material properties are random variables. It is essential to properly consider the PR connections in the stochastic dynamic analysis and design of the steel-concrete composite structures since design forces change significantly. The assumption that the connections are rigid, which is routinely used in the application, is not proper. The effect of the variability connection stiffness on the composite structures responses is sufficiently important for consideration in structural safety.

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Probabilistic study of the behavior of steel frames with partially restrained connections

Cited by 25 publications

References 9 publications

Model assessment in scientific computing

Model assessment in scientific computing

Evidence theory and differential evolution based uncertainty quantification for buckling load of semi-rigid jointed frames

Stochastic Finite Element Analysis of Composite Structures with Partially Restrained Connections under Earthquake Loads

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