Citation
Mohiuddin Khan, Shibli Russel
(2007)
Development of Regression Models for Predicting Properties of High Strength Concrete Using Nondestructive Tests.
PhD thesis, Universiti Putra Malaysia.
Abstract
High strength concrete (HSC) is a relatively recent development in concrete
technology. It is being used increasingly in major civil engineering and building
projects. This leads to the need for quality assurance of the insitu concrete. Testing
of concrete traditionally involved compression testing of cylinders or cubes to obtain
the properties and these may not adequately represent the insitu properties of
concrete. This necessitates the use of nondestructive test (NDT). There are no
standard relationships that had been established for high strength concrete physical
and mechanical properties using Sclerometer test, Ultrasonic Pulse Velocity (UPV)
methods and Pullout test. Prediction models need to be developed for concrete
strength, density and static elastic modulus estimation. They are normally required in
building or structural assessment, especially with the present trend of constructing
modern structures using high strength concrete.
Eight different mix proportions of HSC containing sandstone aggregate of nominal
sizes of 10mm and 19mm and silica fume content were investigated in this study.The silica fume contents were varied at 0%, 5%, 10% and 15%. These mixes
produced concrete at 28day strength between 40 MPa to 100 MPa. A total of 360
standard cubes (150mm), 144 cylinders (150 x 300mm) and 16 reinforced beams
were cast for this study. A total of fortyfive standard cube specimens for each mix
were tested at the age of 3, 7, 14, 28 and 56 days in both, nondestructive and
destructive manner. On the other hand, eighteen cylinder specimens for each mix
were tested at the age of 28 and 56 days in both, nondestructive and destructive
manner. As for the pullout test some fortyfive inserts were prepared for each mix at
the age of 3, 7, 14, 28 and 56 days. For each destructive test, an average of 45 values
of nondestructive tests was obtained, which depends on the type of NDT techniques
used. The results were analyzed using statistical tools (SPSS ver.13). The prediction
models for each NDT technique were developed based on the obtained experimental
results. Statistical tests of significance on the predicted models were performed to
ascertain their reliability in estimating the concrete properties. Predicted models were
also further validated using data from other researchers.
The models developed in this study are expected to be used to estimate strength,
density and static elastic modulus parameters using Sclerometer test, UPV method
and Pullout test. The generalized power models for strength, density and modulus of
elasticity prediction using Sclerometer and Pullout test were found to be unaffected
by the aggregate sizes. The maximum error of these models were found to be
±12.5% for strengthSclerometer test, ±25% for strengthPullout test, ±3% for
densitySclerometer test, ±2% for densityPullout test and ±5% for static elastic
modulusSclerometer test.Strength, density and static modulus of elasticity prediction for direct and indirect
UPV methods indicated that aggregate sizes should be known in advance.
Generalized quadratic models were proposed for concrete mix with nominal
aggregate size 10mm (series A10) for strength, density and modulus of elasticity
prediction using UPV direct method. The maximum error of these models was found
to be ±20% for strength, ±3% and ±5% for density and static modulus of elasticity
respectively. A linear model for strength, a power model for density and a
logarithmic model for static elastic modulus was proposed for 19mm maximum
aggregate size. The quadratic models are valid for pulse velocity range between 4.7
to 6.1 km/sec and the other models are 4.3 to 5.5 km/sec. All of these models are
found to be capable of predicting strength between 30 to 110 MPa, density between
2320 to 2525 kg/m3 and static elastic modulus between 28 to 40 GPa. Combined
NDT methods were found to improve some of strength prediction.
Statistical significant tests on the prediction models have been carried out to
ascertain their reliability in estimating strength, density and static elastic modulus
properties of concrete. Moreover, validation of the predicted models with other
researchers further enhances reliability of each model. Thus, the proposed models for
different NDT techniques can be used as a practical guide in the assessment of insitu
concrete properties.
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Additional Metadata
Item Type: 
Thesis
(PhD)

Subject: 
Concrete construction  Malaysia  High strength concrete  case studies 
Call Number: 
FK 2007 29 
Chairman Supervisor: 
Associate Professor Ir. Mohd Saleh Jaafar, PhD 
Divisions: 
Faculty of Engineering 
Depositing User: 
Nurul Hayatie Hashim

Date Deposited: 
07 Apr 2010 03:00 
Last Modified: 
27 May 2013 07:21 
URI: 
http://psasir.upm.edu.my/id/eprint/5216 
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