Design Reliability for Estimating Cost of Pile Foundations

Abstract

As the design process is now developing within the Army Corps of Engineer's, it is becoming necessary to estimate costs with high levels of accuracy at the time of the feasibility report. Experience has shown that the accuracy requirements may not be met current estimating practices. Discussions with designers reveal that the primary cause of poor cost estimates is not a failure to correctly assess unit construction costs but rather a poor judgement of the structure itself. For example, if the foundation type is incorrectly anticipated a large change in cost occurs. In this Phase I report a conceptual model for design reliability was developed. A regression analysis method was used to develop a linear cost function using statistical data. Fuzzy set theory was then used to get both the design fuzzy probability and the design membership function. Sensitivity analysis was also used to identify the critical variables of the problem. A computer program was developed. The program listing and the user manual are given in the appendices. The proposed conceptual model for design reliability will be used to estimate the cost of pile foundations. A particular project will be selected and design uncertainties will be assesses by the researchers working in cooperation with engineers from the New Orleans District who will provide the required data. The membership design function data must be assembled.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1990
Accession Number
ADA230993

Entities

People

  • Ahmed Banafa
  • Dan M. Frangopol
  • George G. Goble

Organizations

  • University of Colorado Boulder

Tags

Communities of Interest

  • Engineered Resilient Systems

DTIC Thesaurus Topics

  • Accuracy
  • Civil Engineering
  • Computer Programs
  • Construction
  • Cost Estimates
  • Costs
  • Engineering
  • Engineers
  • Fuzzy Sets
  • Judgment
  • New York
  • Office Buildings
  • Price Index
  • Regression Analysis
  • Reliability
  • Set Theory
  • Uncertainty

Fields of Study

  • Engineering

Readers

  • Statistical inference.
  • Systems Analysis and Design
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.