Parameter estimation of four-parameter viscoelastic Burger model by inverse analysis: case studies of four oil-refineries

2012 ◽  
Vol 5 (3) ◽  
pp. 211-228 ◽  
Author(s):  
Arindam Dey ◽  
Prabir Kr. Basudhar
Keyword(s):  
Parameter Estimation ◽  
Case Studies ◽  
Inverse Analysis ◽  
Burger Model ◽  
Oil Refineries

Inverse analysis for parameter estimation of sandy soil with axially loaded pile using nonlinear programming

Sadhana ◽  
2021 ◽  
Vol 47 (1) ◽  
Author(s):  
Shantanu Hati ◽  
Sarat Kumar Panda ◽  
Lohitkumar Nainegali
Keyword(s):  
Parameter Estimation ◽  
Nonlinear Programming ◽  
Sandy Soil ◽  
Inverse Analysis ◽  
Axially Loaded

scholarly journals Estimation of Functional Form of Time-Dependent Heat Transfer Coefficient Using an Accurate and Robust Parameter Estimation Approach: An Inverse Analysis

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 5073
Author(s):  
Farzad Mohebbi ◽  
Mathieu Sellier
Keyword(s):  
Heat Transfer ◽  
Parameter Estimation ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Inverse Analysis ◽  
Functional Form ◽  
Transfer Problem ◽  
Function Estimation ◽  
Inverse Heat Transfer ◽  
Inverse Heat Transfer Problem

This paper presents a numerical method to address function estimation problems in inverse heat transfer problems using parameter estimation approach without prior information on the functional form of the variable to be estimated. Using an inverse analysis, the functional form of a time-dependent heat transfer coefficient is estimated efficiently and accurately. The functional form of the heat transfer coefficient is assumed unknown and the inverse heat transfer problem should be treated using a function estimation approach by solving sensitivity and adjoint problems during the minimization process. Based on proposing a new sensitivity matrix, however, the functional form can be estimated in an accurate and very efficient manner using a parameter estimation approach without the need for solving the sensitivity and adjoint problems and imposing extra computational cost, mathematical complexity, and implementation efforts. In the proposed sensitivity analysis scheme, all sensitivity coefficients can be computed in only one direct problem solution at each iteration. In this inverse heat transfer problem, the body shape is irregular and meshed using a body-fitted grid generation method. The direct heat conduction problem is solved using the finite-difference method. The steepest-descent method is used as a minimization algorithm to minimize the defined objective function and the termination of the minimization process is carried out based on the discrepancy principle. A test case with three different functional forms and two different measurement errors is considered to show the accuracy and efficiency of the used inverse analysis.

scholarly journals Making the Most of Parameter Estimation: Terpolymerization Troubleshooting Tips

Processes ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 444 ◽  
Author(s):  
Scott ◽  
Gabriel ◽  
Dubé ◽  
Penlidis
Keyword(s):  
Parameter Estimation ◽  
Case Studies ◽  
Ternary Systems ◽  
Reactivity Ratio ◽  
Prediction Performance ◽  
Reactivity Ratios ◽  
Ratio Estimation ◽  
New Material ◽  
Future Work ◽  
Good Agreement

Multi-component polymers can provide many advantages over their homopolymer counterparts. Terpolymers are formed from the combination of three unique monomers, thus creating a new material that will exhibit desirable properties based on all three of the original comonomers. To ensure that all three comonomers are incorporated (and to understand and/or predict the degree of incorporation of each comonomer), accurate reactivity ratios are vital. In this study, five terpolymerization studies from the literature are revisited and the ‘ternary’ reactivity ratios are re-estimated. Some recent studies have shown that binary reactivity ratios (that is, from the related copolymer systems) do not always apply to ternary systems. In other reports, binary reactivity ratios are in good agreement with terpolymer data. This investigation allows for the comparison between previously determined binary reactivity ratios and newly estimated ‘ternary’ reactivity ratios for several systems. In some of the case studies presented herein, reactivity ratio estimation directly from terpolymerization data is limited by composition restrictions or ill-conditioned systems. In other cases, we observe similar or improved prediction performance (for ternary systems) when ‘ternary’ reactivity ratios are estimated directly from terpolymerization data (compared to the traditionally used binary reactivity ratios). In order to demonstrate the advantages and challenges associated with ‘ternary’ reactivity ratio estimation, five case studies are presented (with examples and counter-examples) and troubleshooting suggestions are provided to inform future work.

An Inverse Analysis for Parameter Estimation Applied to a Non-Fourier Conduction–Radiation Problem

2011 ◽  
Vol 32 (6) ◽  
pp. 455-466 ◽  
Author(s):  
Ranjan Das ◽  
Subhash C. Mishra ◽  
T. B. Pavan Kumar ◽  
Ramgopal Uppaluri
Keyword(s):  
Parameter Estimation ◽  
Inverse Analysis ◽  
Radiation Problem

Case Studies: the Ensemble-based Approach to History Matching and Model Parameter Estimation

2014 ◽  
Author(s):  
Yanfen Zhang ◽  
Eric Whittet Bhark ◽  
Hemant Ashok Phale ◽  
Kaveh Dehghani
Keyword(s):  
Parameter Estimation ◽  
Case Studies ◽  
History Matching ◽  
Model Parameter ◽  
Model Parameter Estimation
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