Abstract
Motivated by an engineering pullout test applied to a steel strip embedded in earth, we show how the resulting linearly decreasing force leads naturally to a new distribution, if the force under constant stress is modeled via a three-parameter Weibull. We term this the LDSWeibull distribution, and show that inference on the parameters of the underlying Weibull can be made upon collection of data from such pullout tests. Various classical finite-sample and asymptotic properties of the LDSWeibull are studied, including existence of moments, distribution of extremes, and maximum likelihood based inference under different regimes. The LDSWeibull is shown to have many similarities with the Weibull, but does not suffer from the problem of having an unbounded likelihood function under certain parameter configurations. We demonstrate that the quality of its fit can also be very competitive with that of the Weibull in certain applications.
Highlights
Mechanically stabilized earth is a method of constructing vertical retaining walls which is often seen in overpasses in populated metropolitan areas where space is at a premium
It consists of reinforcements which are buried in soil in layers. These reinforcements are attached to a vertical facing wall
Of interest here are the steel reinforcements which are generally flat steel strips, flat steel strips with ribs on them, or welded wire mats which look like a ladder or a grid
Summary
Stabilized earth is a method of constructing vertical retaining walls which is often seen in overpasses in populated metropolitan areas where space is at a premium. Note that this bridges the gap and allows us to estimate the reliability of in-service steel strip reinforcements (which are exposed to a constant stress along its length and have a Weibull survival distribution) via the results of pullout tests (which expose the strip to a linearly decreasing stress along its length and have the distribution derived above).
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of Statistical Distributions and Applications
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
