Quantity uncertainties in reinforcement works – Comparison of public versus private clients

Markus Kummer*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Uncertainties are systematically considered and dealt with by applying probabilistic calculation methods, such as Monte Carlo simulations. When selecting appropriate distribution functions for input parameters, users are constantly faced with the issue of having to choose the “right” distribution function for the relevant parameter. Quantities of individual works play a crucial role for costing and pricing, but also for construction process and logistics planning purposes. Quantities stated by the client in its structural specifications are fraught with uncertainties owing to, for instance, incomplete plans at the time of specification, inaccurate calculations, or mere estimates. This is why actual quantities can either be greater or smaller than the specified quantities. This paper demonstrates how distribution functions can be derived from expert surveys delivering responses from actual construction practice. Specific reference is made to reinforcement works whilst distinguishing between public and private clients. The outcomes of the survey presented and discussed in this paper include descriptive data analyses as well as violin plots and fitted distribution functions.

Original languageEnglish
Title of host publicationISEC 2019 - 10th International Structural Engineering and Construction Conference
EditorsDidem Ozevin, Hossein Ataei, Asli Pelin Gurgun, Mehdi Modares, Siamak Yazdani, Amarjit Singh
PublisherISEC Press
ISBN (Electronic)9780996043762
Publication statusPublished - 1 Jan 2019
Event10th International Structural Engineering and Construction Conference, ISEC 2019 - Chicago, United States
Duration: 20 May 201925 May 2019

Conference

Conference10th International Structural Engineering and Construction Conference, ISEC 2019
CountryUnited States
CityChicago
Period20/05/1925/05/19

Keywords

  • Data fitting
  • Distribution functions
  • Expert survey
  • Management of chances and risks
  • Monte Carlo simulation

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction

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