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Interaction and Multiscale Mechanics
  Volume 5, Number 3, September 2012, pages 211-228
open access

Parameter estimation of four-parameter viscoelastic Burger model by inverse analysis: case studies of four oil-refineries
Arindam Dey and Prabir Kr. Basudhar

    This paper reports the development of a generalized inverse analysis formulation for the parameter estimation of four-parameter Burger model. The analysis is carried out by formulating the problem as a mathematical programming formulation in terms of identification of the design vector, the objective function and the design constraints. Thereafter, the formulated constrained nonlinear multivariable problem is solved with the aid of fmincon: an in-built constrained optimization solver module available in MatLab. In order to gain experience, a synthetic case-study is considered wherein key issues such as the determination and setting up of variable bounds, global optimality of the solution and minimum number of data-points required for prediction of parameters is addressed. The results reveal that the developed technique is quite efficient in predicting the model parameters. The best result is obtained when the design variables are subjected to a lower bound without any upper bound. Global optimality of the solution is achieved using the developed technique. A minimum of 4-5 randomly selected data-points are required to achieve the optimal solution. The above technique has also been adopted for real-time settlement of four oil refineries with encouraging results.
Key Words
    inverse analysis; four-parameter Burger model; mathematical programming; constrained nonlinear multivariable problem; variable bounds; global optimality.
Arindam Dey: Department of Civil Engineering, Indian Institute of Technology Guwahati, Assam-781039, India; Prabir Kr. Basudhar: Department of Civil Engineering, Indian Institute of Technology Kanpur, UP-208016, India

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