Formulation of load factors based on optimum reliability

Kanda, Jun; Ellingwood, Bruce R.

doi:10.1016/0167-4730(91)90043-9

Cited by 55 publications

(19 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The investigation of the optimum seismic design level for buildings is not new and has been investigated in Rosenblueth [1,2], Liu et al [3], Rosenblueth and Jara [4], Kanda and Ellingwood [5], Ang and De Leon [6], Rackwitz [7], Kang and Wen [8], Ellingwood [9], Esteva et al [10,11], Liu et al [12], Ellingwood and Wen [13] and Goda and Hong [14,15]. In these studies, the selection of the seismic design load level takes into account the safety and the economic issues that balance benefit and cost for the structural lifecycle.…”

Section: Introductionmentioning

confidence: 99%

Seismic design and importance factor: Benefit/cost for overall service time versus per unit service time

et al. 2016

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

Seismic design and importance factor: Benefit/cost for overall service time versus per unit service time

et al. 2016

View full text Add to dashboard Cite

“…The interpolation points for this function may, for example, be determined by the response-surface methodology along with, e.g., importance sampling techniques. The procedure was shown to provide sufficient accuracy for structural optimization (see, e.g., [45]). …”

Section: Reliability-based Optimization (Rbo) Proceduresmentioning

confidence: 99%

Developments in stochastic structural mechanics

Schuëller¹

2006

Arch Appl Mech

112

View full text Add to dashboard Cite

Uncertainties are a central element in structural analysis and design. But even today they are frequently dealt with in an intuitive or qualitative way only. However, as already suggested 80 years ago, these uncertainties may be quantified by statistical and stochastic procedures. This contribution attempts to shed light on some of the recent advances in the now established field of stochastic structural mechanics and also solicit ideas on possible future developments.

show abstract

“…There are two weaknesses with this: first, a technique is required to choose which of the three distributions is most appropriate for the data at hand; second, once such a decision is made, subsequent inferences presume this choice to be correct, and do not allow for the uncertainty such a selection involves, even though this uncertainty may be substantial (Coles, 2001). Nevertheless, many studies (Caprani & OBrien, 2006, Caprani et al, 2008, Kanda & Ellingwood, 1991, O'Connor & OBrien, 2005 indicate that LE data is either Weibull or Gumbel and, given that Gumbel is a special case of Weibull (with shape parameter, ξ = 0), an assumption that LE is always of the form of Equation 1, with ξ ≤ 0, seems reasonable.…”

Section: Block Maximum -Extreme Value Distributionsmentioning

confidence: 99%

A review of probabilistic methods of assessment of load effects in bridges

Schmidt²,

et al. 2015

View full text Add to dashboard Cite

This paper reviews a range of statistical approaches to illustrate the influence of data quality and quantity on the probabilistic modelling of traffic load effects. It also aims to demonstrate the importance of long-run simulations in calculating characteristic traffic load effects. The popular methods of Peaks Over Threshold and Generalized Extreme Value are considered but also other methods including the Box-Cox approach, fitting to a Normal distribution and the Rice formula. For these five methods, curves are fitted to the tails of the daily maximum data.Bayesian Updating and Predictive Likelihood are also assessed, which require the entire data for fittings. The accuracy of each method in calculating 75-year characteristic values and probability of failure, using different quantities of data, is assessed. The nature of the problem is first introduced by a simple numerical example with a known theoretical answer. It is then extended to more realistic problems, where long-run simulations are used to provide benchmark results, against which each method is compared. Increasing the number of data in the sample results in higher accuracy of approximations but it is not able to completely eliminate the uncertainty associated with the extrapolation. Results also show that the accuracy of estimations of characteristic value and probabilities of failure are more a function of data quality than extrapolation technique. This highlights the importance of long-run simulations as a means of reducing the errors associated with the extrapolation process.

show abstract

Formulation of load factors based on optimum reliability

Cited by 55 publications

References 7 publications

Seismic design and importance factor: Benefit/cost for overall service time versus per unit service time

Seismic design and importance factor: Benefit/cost for overall service time versus per unit service time

Developments in stochastic structural mechanics

A review of probabilistic methods of assessment of load effects in bridges

Contact Info

Product

Resources

About