On the Material Properties for Piping Load and Resistance Factor Design

2021 ◽  
Author(s):  
Kleio Avrithi
Keyword(s):  
Reliability Index ◽  
Room Temperature ◽  
Mean Value ◽  
Resistance Factor ◽  
Low Alloy Steel ◽  
Factor Design ◽  
The Mean ◽  
Load And Resistance Factor ◽  
The Impact ◽  
Steel Properties

Abstract The probabilistic properties of steel, namely the mean value, coefficient of variation, and probability distribution are needed for the development of Load and Resistance Factor Design (LRFD) equations for Class 2 and 3 nuclear piping and for probabilistic and risk analysis studies. This work investigates the probabilistic properties for the most representative steels used for nuclear piping, such as carbon, stainless austenitic, and low alloy. Steel properties at room temperature and up to temperature 700oF are examined through reported mechanical behavior. The work concludes with the impact of the stainless steels' probabilistic properties on the reliability index or else probability of failure for the piping. The presented data can help organize steel materials for LRFD and reduce the variability of the reliability index.

Probabilistic Properties of Steel for Nuclear Piping

2018 ◽  
Author(s):  
Kleio Avrithi
Keyword(s):  
Mean Value ◽  
Background Information ◽  
Low Alloy Steels ◽  
Target Reliability Index ◽  
Alloy Steels ◽  
Factor Design ◽  
The Mean ◽  
Materials Used ◽  
Load And Resistance Factor ◽  
The Impact

For the development of design rules for nuclear piping using the Load and Resistance Factor Design (LRFD) method, the probabilistic properties of steel, namely, the mean value, bias, coefficient of variation, and probability distribution are needed. The paper presents background information for the existing material tables in the ASME Boiler and Pressure Vessel Code, Section II. Then it investigates the probabilistic properties for the most representative materials used for nuclear piping such as a carbon, stainless austenitic, and low alloy steels. Properties up to temperature 700°F are examined through a review of studies for the mechanical behavior of these materials. The paper discusses approaches for grouping materials in broader categories than the consideration of each type of steel separately. The impact of the steel probabilistic properties on the development of LRFD equations and the associated target reliability index is provided.

Application of the Bayesian Updating to the Load and Resistance Factor Design (LRFD) Method

2013 ◽  
Author(s):  
Yuji Nakasone
Keyword(s):  
Reliability Index ◽  
Statistical Data ◽  
Design Method ◽  
Bayesian Updating ◽  
Fracture Probability ◽  
Resistance Factor ◽  
Factor Design ◽  
Index Value ◽  
Load And Resistance Factor ◽  
Adequate Reliability

The present study has attempted to apply the Bayesian updating to the LRFD, or Load and Resistance Factor Design method. The LRFD method takes into account the statistical distribution of the material resistance and those of the applied loads. The LRFD method can reflect the degrees of different uncertainties of the resistances of the materials and the loads. Thus, the LRFD method can attain the optimal design which can keep up an adequate reliability level of the components designed, whereas the conventional allowable stress design (ASD) method cannot. The LFRD method, however, requires vast amount of statistical data for the material resistances and the applied loadings of different kinds. The present study proposes the Bayesian updating scheme which requires only a small amount of statistical data for the material resistance and the various load item distributions to calculate the values of the partial design factors used in the LRFD method. It is revealed that the median of the updated distributions of the estimated standard deviations can give adequate reliability index values higher than the target reliability index value corresponding to a fracture probability of 0.01% even for a small number of the statistical data, say, less than 20. This paper also compares and discusses the LRFD method with the updating scheme and the conventional ASD method, showing that the updated LRFD method can maintain the reliability index value higher than the target index value whereas the ASD method cannot.

Target Reliability Index for Load and Resistance Factor Design of Class 2 Carbon Steel Pipes

2017 ◽  
Author(s):  
Kleio Avrithi ◽  
Ramiro Mendoza
Keyword(s):  
Carbon Steel ◽  
Internal Pressure ◽  
Reliability Index ◽  
Safety Margin ◽  
Resistance Factor ◽  
Safety Factors ◽  
Target Reliability Index ◽  
Partial Safety Factors ◽  
Factor Design ◽  
Load And Resistance Factor

The use of the Load and Resistance Factor Design (LRFD) for Class 2 nuclear piping can be an alternative of the traditional Allowable Stress Design (ASD) method currently used in the ASME Boiler Pressure Vessel Code, Section III, Div. 1 providing the benefit of a known and consistent reliability for the designed piping. The design uncertainties and the necessary safety margin are evaluated for each equation for all service levels by considering the applied loads (e.g., earthquake, deadweight, internal pressure, etc.) and the resistance of steel, in the form of either the yield or ultimate strength, as separate variables described by their mean value, distribution, and coefficient of variation. The procedure yields different partial safety factors for each load and the resistance in opposition to the one safety factor used in each of the ASD equations of the Code. Although LRFD equations have been developed in the past, a range of possible partial safety factors were assigned to the variables, corresponding to different levels of reliability. This paper discusses the method used, namely calibration, for achieving same reliability as in the Code equations, and the progress made to assess a minimum target reliability index or else acceptable probability of failure for the LRFD equations that consider the earthquake load for pressurized pipes as well as the design for internal pressure for Class 2 nuclear pipes made of carbon steel.

Load and Resistance Factor Design Criteria for Connectors

1978 ◽  
Vol 104 (9) ◽  
pp. 1427-1441
Author(s):  
John W. Fisher ◽  
Theodore V. Galambos ◽  
Geoffrey L. Kulak ◽  
Mayasandra K. Ravindra
Keyword(s):  
Resistance Factor ◽  
Design Criteria ◽  
Factor Design ◽  
Load And Resistance Factor

Closure to “Load and Resistance Factor Design Criteria for Connectors”

1980 ◽  
Vol 106 (9) ◽  
pp. 1985-1986
Author(s):  
John W. Fisher ◽  
Theodore V. Galambos ◽  
Geoffrey L. Kulak ◽  
Mayasandra K. Ravindra
Keyword(s):  
Resistance Factor ◽  
Design Criteria ◽  
Factor Design ◽  
Load And Resistance Factor

scholarly journals Perturbation analysis of a variable M/M/1 queue: a probabilistic approach

2006 ◽  
Vol 38 (01) ◽  
pp. 263-283 ◽  
Author(s):  
Nelson Antunes ◽  
Christine Fricker ◽  
Fabrice Guillemin ◽  
Philippe Robert
Keyword(s):  
Power Series ◽  
Busy Period ◽  
Stationary Process ◽  
Probabilistic Approach ◽  
Power Series Expansion ◽  
Mean Value ◽  
Service Rate ◽  
The Mean ◽  
The Impact ◽  
Period Duration

In this paper, motivated by the problem of the coexistence on transmission links of telecommunications networks of elastic and unresponsive traffic, we study the impact on the busy period of an M/M/1 queue of a small perturbation in the service rate. The perturbation depends upon an independent stationary process (X(t)) and is quantified by means of a parameter ε ≪ 1. We specifically compute the two first terms of the power series expansion in ε of the mean value of the busy period duration. This allows us to study the validity of the reduced service rate approximation, which consists in comparing the perturbed M/M/1 queue with the M/M/1 queue whose service rate is constant and equal to the mean value of the perturbation. For the first term of the expansion, the two systems are equivalent. For the second term, the situation is more complex and it is shown that the correlations of the environment process (X(t)) play a key role.

A procedure for incorporating setup into load and resistance factor design of driven piles

2015 ◽  
Vol 11 (2) ◽  
pp. 347-358 ◽  
Author(s):  
Kam W. Ng ◽  
Sri Sritharan
Keyword(s):  
Resistance Factor ◽  
Driven Piles ◽  
Factor Design ◽  
Load And Resistance Factor

scholarly journals THE LUCK IN “TALENT VERSUS LUCK” MODELING

2020 ◽  
Vol 23 (03) ◽  
pp. 2050007
Author(s):  
SEAN ELVIDGE
Keyword(s):  
Mean Value ◽  
Maximum Amount ◽  
Random Numbers ◽  
Individual Parameter ◽  
Input Parameters ◽  
The Mean ◽  
Model Variability ◽  
The Impact ◽  
The Relationship

This paper further investigates the Talent versus Luck (TvL) model described by [Pluchino et al. Talent versus luck: The role of randomness in success and failure, Adv. Complex Syst. 21 (2018) 1850014] which models the relationship between ‘talent’ and ‘luck’ on the impact of an individuals career. It is shown that the model is very sensitive to both random sampling and the choice of value for the input parameters. Running the model repeatedly with the same set of input parameters gives a range of output values of over 50% of the mean value. The sensitivity of the inputs of the model is analyzed using a variance-based approach based upon generating Sobol sequences of quasi-random numbers. When using the model to look at the talent associated with an individual who has the maximum capital over a model run it has been shown that the choice for the standard deviation of the talent distribution contributes to 67% of the model variability. When investigating the maximum amount of capital returned by the model the probability of a lucky event at any given epoch has the largest impact on the model, almost three times more than any other individual parameter. Consequently, during the analysis of the model results one must keep in mind the impact that only small changes in the input parameters can have on the model output.

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