Effective parameter estimation within a multi-dimensional population balance model framework

Chemical Engineering Science

Volumn 65, Issue 16, 2010, Pages 4884-4893

  Ramachandran, Rohit ^a   Barton, Paul I ^b  

^a The State University of New Jersey   (United States)

^b Massachusetts Institute of Technology Cambridge   (United States)

Author keywords

Automatic differentiation; Granulation; Kernels; Multi dimensional population balance model; Optimization; Parameter estimation

Indexed keywords

AUTOMATIC DIFFERENTIATION; AUTOMATIC DIFFERENTIATIONS; BEST FIT; COMPUTATIONAL BURDEN; DERIVATIVE INFORMATION; DERIVATIVE-FREE METHODS; EFFECTIVE PARAMETERS; FINITE DIFFERENCE; GAUSS-NEWTON; GRADIENT-BASED METHOD; JACOBIANS; LEAST SQUARE; LEVENBERG-MARQUARDT; MODEL PARAMETERS; MULTIDIMENSIONAL POPULATION BALANCE; NELDER-MEAD SIMPLEX METHODS; NON-SMOOTHNESS; NUMERICAL ERRORS; NUMERICAL INSTABILITY; OBJECTIVE FUNCTIONS; OPTIMAL PARAMETER ESTIMATION; OPTIMAL SOLUTIONS; OPTIMIZATION PROBLEMS; OPTIMIZATION STRATEGY; OPTIMIZATION TECHNIQUES; PARAMETER IDENTIFIABILITY; PROBLEM FORMULATION; QUASI-NEWTON; SIMULATED MODEL; STEP SIZE;

COMPUTER SIMULATION; CONVERGENCE OF NUMERICAL METHODS; FISHER INFORMATION MATRIX; GRANULATION; METAL ANALYSIS; OPTIMIZATION; SENSITIVITY ANALYSIS; STAINLESS STEEL;

PARAMETER ESTIMATION;

EID: 77954383034     PISSN: 00092509     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ces.2010.05.039     Document Type: Article

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