Nonlinear Multiresponse Parameter Estimation Using Simplex Optimization Method

A. Al Saleh Mohammad; A. Yussuf Abdirahman

doi:10.4028/www.scientific.net/AMR.1105.299

Paper Titles

Ultrananocrystalline Diamond/Amorphous Carbon Composite Films Prepared by Laser Ablation of Graphite in Nitrogen and Hydrogen Atmosphere
p.274

Thermal Conductivity of Silicon-Graphene Nanoribbon (SiGNR): An Equilibrium Molecular Dynamics (EMD) Simulation
p.280

Molecular Dynamics Simulation of the Thermal Conductivity of Silicon-Germanene Nanoribbon (SiGeNR): A Comparison with Silicene Nanoribbon (SiNR) and Germanene Nanoribbon (GeNR)
p.285

2-(Methacryloyloxyethyl) Trimethyl Ammonium Chloride Grafted onto Natural Rubber in Latex State
p.293

Nonlinear Multiresponse Parameter Estimation Using Simplex Optimization Method
p.299

Effect of Biogas Volume Flow Rate and Burner Temperature on Moisture Content of Organic Fertilizer in a Rotary Drying Process
p.305

Electroactive Polymer Actuator Based on PVDF and Graphene through Electrospinning
p.311

Improvement of Geotechnical Characteristics of Clay Soils Using Lime
p.315

Physical Parameters Affecting on the Electrode Performance for Proton Exchange Membrane Fuel Cells (PEMFCs)
p.320

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 1105Nonlinear Multiresponse Parameter Estimation Using...

Nonlinear Multiresponse Parameter Estimation Using Simplex Optimization Method

Abstract:

Polyolefin molecular architectures are designed according to customer needs and demands. Hence, it is essential to determine the catalytic behavior that gives the polymer the characteristics it needs to meet the market requirements. Today most of the industrial polyolefin production depends on multiple-site-type catalysts such as Ziegler-Natta catalysts. In this work a methodology to estimate parameters for polyolefin multiple-site-type catalysts was presented. The sequence length distribution data were simulated using Zeroth-order and First-order Markovian models. These simulated data were used to test the robustness of the optimization method. The optimization method used was able to retrieve and comprehend the proper probabilistic models and provide acceptable polymerization parameters estimates.