Revised survival probability in design practice

Kudzys, Antanas; Kliukas, Romualdas; Kudzys, Algirdas

Use this URL to cite this publication: https://hdl.handle.net/20.500.14911/140074

Revised survival probability in design practice

Details

Publication Type (CRIS)

Straipsnis recenzuojamoje užsienio tarptautinės konferencijos medžiagoje / Article in peer-reviewed foreign international conference proceedings (P1d)

Publication Type (eLABa)

Straipsnis recenzuotame konferencijos darbų leidinyje / Article published in peer-reviewed conference proceedings (P1d)

Author(s)

Author	Affiliation
Kudzys, Antanas	Kauno technologijos universiteto Architektūros ir statybos institutas	Vilniaus Gedimino technikos universitetas / Vilnius Gediminas Technical University (111950243)
Kliukas, Romualdas	Taikomosios mechanikos katedra / Department of Applied Mechanics (0260)
Kudzys, Algirdas	Architektūros fakultetas / Faculty of Architecture (01)

Title

Revised survival probability in design practice

[en]

A. Kudzys, R. Kliukas & Alg. Kudzys

Is part of

ICOSSAR 2005 : proceedings of the ninth international conference on structural safety and reliability, Rome, Italy, June 19-23, 2005

Published In

Year	Start Page	End Page
2005	3759	3763

Publisher

Rotterdam : Millpress, 2005

Extent

p. 3759-3763

URI

URI
https://hdl.handle.net/20.500.14911/140074

Cited references

Science / Art Area

Technologijos mokslai / Technological sciences (T)

Field of Science / Art

Statybos inžinerija / Civil engineering (T002)

Keywords (en)

Abstract (en)

A revised survival probability of particular (sections, bars, connections) and structural (beams, columns, slabs) members as a residual safety parameter of existing structures is discussed. The conventional resistances, safety margins and time-dependent survival probabilities of particular members are analysed. The effect of two intermittent rectangular pulse action processes on a long-term survival probability of members is considered. It is recommended to assess the time-dependent probabilistic structural safety of members by the method of transformed conditional probabilities. The revised survival probability prediction of members during their residual service life is based on the truncated distribution and Bayes theorem approaches.