Off-campus UNL users: To download campus access dissertations, please use the following link to log into our proxy server with your NU ID and password. When you are done browsing please remember to return to this page and log out.
Non-UNL users: Please talk to your librarian about requesting this dissertation through interlibrary loan.
Preparing, characterizing, on-line digital image processing of residence time distribution and modeling of mechanical properties of nanocomposite foams
The objectives of this research were to prepare, characterize and to study the effects of organoclay and extrusion variables on the physical, mechanical, structural, thermal and functional properties of tapioca starch (TS)/poly(lactic acid) (PLA) nanocomposite foams. On-line digital imaging processing was used to determine residence time distribution (RTD). Adaptive neuro-fuzzy inference system (ANFIS) was used to model the mechanical properties of nanocomposite foams.^ Four different organoclays (Cloisite 10A, 25A, 93A, 15A) were used to produce nanocomposite foams by melt-intercalation. The properties were characterized using X-ray diffraction, scanning electron microscopy, differential scanning calorimetric, and Instron universal testing machine. The properties were influenced significantly with the addition of different organoclays. TS/PLA/Cloisite 30B nanocomposite foams, with four clay contents of 1, 3, 5, 7 wt%, were prepared by a melt-intercalation method. Among the four nanocomposites, 3 wt% clay content produced significantly different properties.^ Screw speed, screw configuration, die nozzle diameter and moisture content were varied to determine their effects on organoclay intercalation. These extrusion variables had significant effects on the properties of TS/PLA/Cloisite 10A nanocomposite foams due to the intercalation of organoclay.^ Multiple inputs single output (MISO) models were developed to predict mechanical properties of nanocomposite foams. Four individual ANFIS models were developed. All models preformed well with R2 values > 0.71 and had very low root mean squared errors (RMSE). Effects of screw configurations and barrel temperatures on the RTD and MISO models were developed to predict mechanical properties. The influence of the extrusion variables had a significant effect on the mean residence time (MTR).^ On-line digital image processing (DIP) technique was developed to measure the RTD as compared to the colorimeter method. R2 showed a correlation of 0.88 of a* values from both methods. The influence of screw configuration and temperature on RTD were analyzed by the MRT and variance for both methods. Mixing screws and lower temperature resulted in higher MRT and variance for both methods.^
Lee, Siew Yoong, "Preparing, characterizing, on-line digital image processing of residence time distribution and modeling of mechanical properties of nanocomposite foams" (2008). ETD collection for University of Nebraska - Lincoln. AAI3315262.