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Material parameter estimation for pa...

Choi, Jae Woong.

Material parameter estimation for pavement system.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Material parameter estimation for pavement system.
Author:	Choi, Jae Woong.
Description:	192 p.
Notes:	Adviser: Juan M. Pestana-Nascimento.
Notes:	Source: Dissertation Abstracts International, Volume: 69-10, Section: B, page: .
Contained By:	Dissertation Abstracts International69-10B.
Subject:	Engineering, Civil.
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3331544
ISBN:	9780549833925

Material parameter estimation for pavement system.
Choi, Jae Woong.

Material parameter estimation for pavement system. - 192 p.

Adviser: Juan M. Pestana-Nascimento.

Thesis (Ph.D.)--University of California, Berkeley, 2008.

In the following decades, the practice of pavement engineering faces two main challenges. The first relates to the development of more mechanistic based models and procedures that incorporate the results from complex and sophisticated laboratory tests as well as prediction models incorporating environmental changes for the design of new pavements and the evaluation of existing ones. The second challenge involves the seamless integration of laboratory and field non-destructive testing so that the same set of material properties are used in all phases of pavement design, quality control monitoring, and performance evaluation. As a result, there is an increasing need for a reliable framework for predicting pavement performance using material properties from three main sources: (a) laboratory testing, (b) field and laboratory non-destructive testing and (c) inferred from back-calculation methods of field performance assessment and monitoring. As a result of the development of more sophisticated constitutive models for pavement materials and the increasing use of numerical simulation procedures to predict pavement performance. There is a pressing demand for robust and objective material parameter determination procedures. A methodology, based on the Extended Kalman Filter (EKF), is presented here for the solution of the back-calculation (or inverse) problem of estimating material properties. The methodology is essentially a method of sequential least squares estimation and it was used to determine constitutive model parameters using "simulated" laboratory tests including measurement noise. The EKF model was extended here by constraining the domain of model parameters so that the search for optimal solutions occurs in a reduced space thus increasing the speed and improving the convergence properties of the algorithm. The proposed procedure is shown to provide robust and objective estimation of material properties and may lead, in the near future, to fully-automated laboratory testing of pavement and other geoengineering materials. The methodology is then used to estimate the resilient modulus for three, four and five layer pavement structures using "simulated" and measured data from the Falling Weight Deflectometer (FWD) field test. Comparison with existing back-calculation approaches suggests that the proposed methodology has superior convergence attributes and less dependency on the initial estimates of the material properties.

ISBN: 9780549833925Subjects--Topical Terms:

212394
Engineering, Civil.

Material parameter estimation for pavement system.
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502 $a Thesis (Ph.D.)--University of California, Berkeley, 2008.
520 $a In the following decades, the practice of pavement engineering faces two main challenges. The first relates to the development of more mechanistic based models and procedures that incorporate the results from complex and sophisticated laboratory tests as well as prediction models incorporating environmental changes for the design of new pavements and the evaluation of existing ones. The second challenge involves the seamless integration of laboratory and field non-destructive testing so that the same set of material properties are used in all phases of pavement design, quality control monitoring, and performance evaluation. As a result, there is an increasing need for a reliable framework for predicting pavement performance using material properties from three main sources: (a) laboratory testing, (b) field and laboratory non-destructive testing and (c) inferred from back-calculation methods of field performance assessment and monitoring. As a result of the development of more sophisticated constitutive models for pavement materials and the increasing use of numerical simulation procedures to predict pavement performance. There is a pressing demand for robust and objective material parameter determination procedures. A methodology, based on the Extended Kalman Filter (EKF), is presented here for the solution of the back-calculation (or inverse) problem of estimating material properties. The methodology is essentially a method of sequential least squares estimation and it was used to determine constitutive model parameters using "simulated" laboratory tests including measurement noise. The EKF model was extended here by constraining the domain of model parameters so that the search for optimal solutions occurs in a reduced space thus increasing the speed and improving the convergence properties of the algorithm. The proposed procedure is shown to provide robust and objective estimation of material properties and may lead, in the near future, to fully-automated laboratory testing of pavement and other geoengineering materials. The methodology is then used to estimate the resilient modulus for three, four and five layer pavement structures using "simulated" and measured data from the Falling Weight Deflectometer (FWD) field test. Comparison with existing back-calculation approaches suggests that the proposed methodology has superior convergence attributes and less dependency on the initial estimates of the material properties.
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