rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    non sort: A
    title: time-variant probabilistic model for predicting the longer-term performance of GFRP reinforcing bars embedded in concrete
  name:
    name part: Kim, Jeongjoo.
    role:
      role term: creator
  name:
    name part: Trejo, David
    role:
      role term: thesis advisor.
  name:
    name part: Gardoni, Paolo
    role:
      role term: thesis advisor.
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: txu
    date issued: 2011
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource.
  abstract: Although Glass Fiber Reinforced Polymer (GFRP) has many potential advantages as reinforcement in concrete structures, the loss in tensile strength of the GFRP reinforcing bar can be significant when exposed to the high alkali environments. Much effort was made to estimate the durability performance of GFRP in concrete; however, it is widely believed the data from accelerated aging tests is not appropriate to predict the longer-term performance of GFRP reinforcing bars. The lack of validated long-term data is the major obstacle for broad application of GFRP reinforcement in civil engineering practices. The main purpose of this study is to evaluate the longer-term deterioration rate of GFRP bars embedded in concrete, and to develop an accurate model that can provide better information to predict the longer-term performance of GFRP bars. In previous studies performed by Trejo, three GFRP bar types (V1, V2, and P type) with two different diameters (16 and 19 mm [0.625, and 0.7 in. referred as #5 and #6, respectively]) provided by different manufacturers were embedded in concrete beams. After pre-cracking by bending tests, specimens were stored outdoors at the Riverside Campus of Texas A&M University in College Station, Texas. After 7 years of outdoor exposure, the GFRP bars were extracted from the concrete beams and tension tests were performed to estimate the residual tensile strength. Several physical tests were also performed to assess the potential changes in the material. It was found that the tensile capacity of the GFRP bars embedded in concrete decreased; however, no significant changes in modulus of elasticity (MOE) were observed. Using this data and limited data from the literature, a probabilistic capacity model was developed using Bayesian updating. The developed probabilistic capacity model appropriately accounts for statistical uncertainties, considering the influence of the missing variables and remaining error due to the inexact model form. In this study…
  note: by Jeongjoo Kim.
  note: "Major Subject: Civil Engineering"
  note: Title from author supplied metadata (automated record created 2011-08-09 15:09:44).
  note: Electronic resource.
  note: Master of Science Texas A&M University 2010 http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-7943
  note: Includes bibliographical references.
  note: Text (Thesis)
  subject:
    topic: Major civil engineering
  subject:
    topic: Bayesian updating
  subject:
    topic: Durability
  subject:
    topic: Longer-term performance
  subject:
    topic: Glass fiber reinforced polymer(GFRP)
  subject:
    topic: Probabilistic model
  subject:
    topic: Concrete
  identifier: http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-7943
  record info:
    record content source: TXA
    record creation date: 110819
    record change date: 20151202142327.0
    record identifier: in00002717711