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Weibull distribution

About: Weibull distribution is a(n) research topic. Over the lifetime, 12161 publication(s) have been published within this topic receiving 202541 citation(s). The topic is also known as: Weibull model & Weibull regression.

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Papers
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Journal ArticleDOI: 10.1007/BF02663302
F. M. Beremin1, André Pineau1, F. Mudry1, Jean-Claude Devaux2  +2 moreInstitutions (2)
Abstract: Experiments were performed on three heats of A508 class 3 steel in order to determine the mechanical conditions for cleavage fracture. These tests were carried out on various geometries including 4-point bend specimens and axisymmetric notched tensile bars with different notch radii which have been modelized using the finite element method. In one heat, the temperature range investigated was from 77 K to 233 K. It is shown that the cleavage resistance is increased by tensile straining. Moreover, the probability of fracture obeys the Weibull statistical distribution. All the results can be accounted for in terms of a local criterion based on Weibull theory and which takes into account the effect of plastic strain. In this criterion, the parameters which were experimentally determined are found to be temperature independent over the range 77 K to 170 K. The applicability of the approach proposed for cleavage fracture at the crack tip is also examined. It is shown that the experimental results published in the literature giving the variation of fracture toughness with temperature can be explained by the proposed criterion which predicts reasonably well both the scatter in the experimental results and theKICtemperature dependence.

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Topics: Fracture mechanics (60%), Fracture toughness (55%), Fracture (geology) (54%) ...read more

1,031 Citations


Journal ArticleDOI: 10.1111/1467-842X.00072
Rameshwar D. Gupta1, Debasis Kundu2Institutions (2)
Abstract: Summary The three-parameter gamma and three-parameter Weibull distributions are commonly used for analysing any lifetime data or skewed data. Both distributions have several desirable properties, and nice physical interpretations. Because of the scale and shape parameters, both have quite a bit of flexibility for analysing different types of lifetime data. They have increasing as well as decreasing hazard rate depending on the shape parameter. Unfortunately both distributions also have certain drawbacks. This paper considers a three-parameter distribution which is a particular case of the exponentiated Weibull distribution originally proposed by Mudholkar, Srivastava & Freimer (1995) when the location parameter is not present. The study examines different properties of this model and observes that this family has some interesting features which are quite similar to those of the gamma family and the Weibull family, and certain distinct properties also. It appears this model can be used as an alternative to the gamma model or the Weibull model in many situations. One dataset is provided where the three-parameter generalized exponential distribution fits better than the three-parameter Weibull distribution or the three-parameter gamma distribution.

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984 Citations


Open accessBook
01 Jan 1977-
Abstract: Introduction. Reliability Measures. Static Reliability Models. Probabilistic Engineering Design. Combination of Random Variable's in Design. Interference Theory and Reliability Computations. Reliability Design Examples. Time Dependent Stress-Strength Models. Dynamic Reliability Models. Reliability Estimation: Exponential Distribution. Reliability Estimation: Weibull Distribution. Sequential Life Testing. Bayesian Reliability in Design and Testing. Reliability Optimization. Author Index. Subject Index.

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938 Citations


Journal ArticleDOI: 10.1109/24.229504
G.S. Mudholkar1, D.K. Srivastava1Institutions (1)
Abstract: A simple generalization of the Weibull distribution is presented. The distribution is well suited for modeling bathtub failure rate lifetime data and for testing goodness-of-fit of the Weibull and negative exponential models as subhypotheses. >

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Topics: Exponentiated Weibull distribution (79%), Bathtub curve (67%), Weibull fading (65%) ...read more

910 Citations


Journal ArticleDOI: 10.1093/BIOMET/84.3.641
Albert W. Marshall, Ingram Olkin1Institutions (1)
01 Sep 1997-Biometrika
Abstract: SUMMARY A new way of introducing a parameter to expand a family of distributions is introduced and applied to yield a new two-parameter extension of the exponential distribution which may serve as a competitor to such commonly-used two-parameter families of life distributions as the Weibull, gamma and lognormal distributions. In addition, the general method is applied to yield a new three-parameter Weibull distribution. Families expanded using the method introduced here have the property that the minimum of a geometric number of independent random variables with common distribution in the family has a distribution again in the family. Bivariate versions are also considered.

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856 Citations


Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202222
2021598
2020608
2019653
2018633
2017637

Top Attributes

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Topic's top 5 most impactful authors

Gauss M. Cordeiro

86 papers, 3.2K citations

Narayanaswamy Balakrishnan

43 papers, 1.1K citations

Saralees Nadarajah

41 papers, 1.3K citations

Debasis Kundu

32 papers, 1.6K citations

Edwin M. M. Ortega

27 papers, 836 citations

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