The melt rheological behavior of structurally defined starblock polymers was investigated using the experimental design technique of response surface methodology. A rotatable central composite design (ccd) was employed with linear 2⁵ factorial structure and with axial points to fit the pure quadratic terms. Regression analysis of rheological data from styrene-isoprene and t-butyl styrene-isoprene starblock polymers was used to generate four models whose terms have a p-value ≤ 0.1. The fitted models of viscosity and elasticity were a function of temperature, weight percent uncombined diblock, frequency, casting solvent, and annealing time. Changes in melt behavior were hypothesized to be dependent on mechanisms related to phase separation and/or architecture. The modeled behavior verified the proposed mechanisms enabling a generalization of the results to the melt behavior of block polymer systems. The guidelines for the applicability of the well known Cox-Mertz relation and WLF superposition technique, as well as the transition to the Forced High Elasticity State, are discussed in terms of melt connectivity and elasticity. / M.S.

Thesis (PhD (Process Engineering))--Stellenbosch University, 2008. / The feasibility of predicting paint properties directly from the raw material formulation as well as the rheological data is investigated in this study. Although extensive work has been carried out on the prediction of paint properties in terms of the raw material data, very little research has been carried out on the prediction of paint properties in terms of the rheological data. Little is known about the relationship between fundamental rheological properties and real-world performance. The paint under investigation consists of fourteen raw materials. These raw materials interact in a very complex manner to produce certain desired paint properties. Evaluation of these interactions in terms of constitutive equations is almost impossible and the relationships between paint properties, raw materials and rheology can only be modelled in a statistical way. Linear relationships are investigated with linear parameter estimation techniques such as multiple linear regression. However, it has been found that many of these relationships are non-linear and that linear modelling techniques are no longer applicable for certain situations, e.g. at very high concentrations of specific raw materials. Non-linear techniques such as neural networks are used in these situations. The relationship between the raw materials, paint properties and rheology are evaluated using the following three models: · MODEL 1: The relationship between rheology and raw materials · MODEL 2: The relationship between paint properties and raw materials · MODEL 3: The relationship between paint properties and rheology MODEL 1 makes use of techniques such as principal component analysis and preliminary modelling to respectively reduce redundancy and to capture as much data as possible. MODELS 2 and 3 make use of linear screening techniques in order to identify relevant raw materials and paint properties. The validity of every model is checked to ensure that predictions and interpretations are unbiased and efficient. MODEL 1 revealed that emulsion, extender particles, pigment, water, organic pigment and solvent are the six most important raw materials affecting the rheology of the specific paint. The rheology curves that are predicted most accurately by means of multiple linear regression are the “Amplitude Sweep” (AS), “3-Interval-Thixotropy-Test” (3-ITT) and the “Flow Curve” (FC). Non-linear rheological behaviour is encountered at high pigment volume concentrations (PVC) and volume solids (VS), due to the strong dependency of the rheology of the paint on these properties. It has been shown that neural networks perform better than multiple linear regression in predicting the rheological behaviour of these paint samples for which the raw materials vary by more than 20% from the standard formulation. On average, neural networks improve predictability of the rheological parameters of these samples by 54%. The largest improvement in predictability is made on the rheological variable “Extra Low Frequency” value (CXLF), where multiple linear regression resulted in relative errors of 59%, while neural networks resulted in errors of only 5%. Other predictions of rheology curves where neural networks have shown a major improvement on predictability are the “Time Sweep” (TS) – 68% increase in accuracy and “Low Shear” curve (LS) – 63% increase in accuracy. The smallest increase that the neural network had on the predictability of a rheology curve, was a 33% increase in accuracy of the “Amplitude Sweep” (AS) predictions. Multiple linear regression models of MODEL 2 predict the critical paint properties of Opacity, Gloss, Krebs Viscosity and Dry Film Thickness with relative errors smaller than 10%. It has been shown that 90% of all new predictions fall within the allowable error margin set by the paint manufacturer. Paint properties that can be predicted with an expected error of between 10% and 20% are Dry and Wet Burnish, Open Time and Water Permeability. Paint properties that are predicted the most inaccurately by MLR, that results in errors larger than 20% are Dirt Pick-Up and Sagging. Non-linear techniques such as neural networks are used to predict the paint properties of these paint samples for which the raw materials vary by more than 20% from the standard formulation. The neural networks show a major improvement on the predictability of the paint properties for those paint samples that vary more than 20% from the standard formulation. On average, neural networks improve predictability of the paint properties by 47%. The largest improvement in predictability is made on the Wet Burnish20 prediction, where multiple linear regression resulted in relative errors of 66%, while neural networks resulted in errors of only 0.6%. Other paint property predictions where neural networks have shown a major improvement on predictability of 80% or more in accuracy are Gloss – 80% increase in accuracy and Dry Film Thickness – 81% increase in accuracy. The smallest increase that the neural network had on the predictability of a paint property, was a 33% increase in accuracy of the Sag predictions. MODEL 2 makes it possible for the paint manufacturer to test tolerances around certain paint properties during manufacturing. Rheology is still a very under-utilised tool for explaining certain paint properties. MODEL 3 quantified the correlation between fundamental rheological properties and real world performance of a paint. It has been shown that rheological measurements can be used accurately to predict certain critical paint properties such as Opacity, Krebs Viscosity, Dry Film Thickness and Gloss within the allowable error margin given by the paint manufacturer. Multiple linear regression models predict the paint properties of Opacity, Krebs Viscosity and Dry Film Thickness with relative errors smaller than 10%, with rheology as input to the model. A neural network of MODEL 3 was developed to predict the paint properties of those paint samples that vary more than 20% from the standard formulation, by using rheology data as input to the model. The neural networks perform better than multiple linear regression in predicting the paint properties of these paint samples. On average, neural networks that use rheology data as input, predict the paint properties 49% more accurate than equivalent multiple linear regression models. The greatest improvement in model predictability is for Water Permeability - 73% increase in accuracy and Gloss - 70% increase in accuracy....

Thesis (MScEng)--Stellenbosch University, 2003. / ENGLISH ABSTRACT: Desired behaviour of paint during processing, storage, application and after application is of great importance in the coatings industry. Rheology (the study of flow and deformation behaviour) is used as a method to investigate the behaviour of the flow and deformation properties of the paint during these stages. Some of the more important phenomena that can occur during these stages, which were examined rheologically, are: 1. The rheological behaviour of certain complex raw materials during processing - vesiculated beads suspensions 11. The paint behaviour during storage - in-can stability, e.g. phase separation and sedimentation of particles; Ill. The paint during application - ease of application, spatter, etc.; IV. The paint behaviour after application - sag, layer thickness, levelling (ability to hide brush marks), etc. A rheometer was used to obtain rheological curves from a paint sample (± 1 ml). Correct interpretation of these curves, which display rheological properties of the sample such as the viscosity, shear stress, structural strength and many more, produced information about the properties mentioned in i, ii, iii and iv above. It was found that the rheological data correlated well with empirical tests carried out in the laboratory for spatter, sag, levelling behaviour and in-can stability of the paint. A wide variety of paints were studied ranging from tough/durable outdoor paints to smooth/velvety indoor paints. The rheological behaviour explained the specific end-use properties of the paints. Paints from two different companies were compared on a rheological basis. In some cases large differences in rheological behaviour were observed. Rheology modifiers were tested on a new paint. It was found that specific rheology modifiers could be incorporated into the formulation to give the specific rheological behaviour required. Rheological modelling was performed and it was found that the flow behaviour of paint cou1d be modelled accurately with existing viscosity models (Ostwald/de Waal, Bingham, Casson, Herschel-Bulkley, Cross and Philips-Deutsch). Other rheological properties of paint were also modelled successfully with a simple linear regression model. Rheology was also used as a method to examine the flow and deformation properties of vesiculated beads, a component of paint with very complex rheology. The most important factors that influence the rheological behaviour of the vesiculated beads were determined. It was found that the type of manufacturing process for the beads affected the rheological behaviour. The effect of the raw materials used to manufacture the vesiculated beads were rheologically determined. / AFRIKAANSE OPSOMMING: Dit is baie belangrik dat verf die gewenste gedrag moet toon tydens berging, vervaardiging, tydens aanwending en direk na aanwending. Reologie (die studie van vloei- en vervorming) word gebruik as a metode om die vloei- en vervormingseienskappe van verf gedurende bogenoemde stadia te ondersoek. Sommige van die belangriker verskynsels wat gedurende hierdie stadia kan plaasvind, is d.m.v reologiese toetse ondersoek. Die verskynsels is as volg: i. Die reologiese gedrag van komplekse grondstowwe soos gevesikuleerde partikel suspensies. ll. Verfgedrag tydens berging - stabiliteit van verf in die blik, bv. faseskeiding en sedimentasie van partikels lll. Verfgedrag tydens aanwending - gemak van aanwending, spatsels IV. Verfgedrag direk na aanwending - afsakking, dikte van verflaag, vloei-eienskappe 'n Reometer is gebruik om die reologiese kurwes te bepaal deur gebruik te maak van ± 1 ml monster. Korrekte interpretasie van hierdie kurwes, wat onder meer eienskappe soos viskositeit, spanning en struktuursterkte insluit, lei tot inligting wat die verskynsels in i, ii, iii en iv kan verklaar. Daar is gevind dat inligting wat verkry is i.v.m die verskynsel van spatsels, afsakking, vloei en die stabiliteit van verf in die blik, goed korreleer met empiriese toetse wat in die laboratorium uitgevoer is. 'n Groot verskeidenheid van verwe, wat wissel van duursame/sterk buitemuurse verf, tot fluweelsagte binnenshuise verf, isondersoek. Die reologiese toetse het daarin geslaag om die eienskappe van die eindproduk suksesvol te verduidelik. Verf van twee verskillende maatskappye is ook met mekaar vergelyk op 'n reologiese grondslag. Daar is by sommige van die verwe aansienlike verskille in die reologiese gedrag gevind. 'n Nuwe verf is gebruik om die uitwerking van reologie modifiseerders te ondersoek. Daar is gevind dat daar spesifieke reologie modifiseerders bestaan wat unieke reologiese gedrag verseker. Reologiese modellering is gedoen op verf en daar is gevind dat die vloeigedrag van die verf akkuraat gemodelleer kan word deur van die bestaande viskositeitsmodelle gebruik te maak (Ostwald/de Waal, Bingham, Casson, Herschel- Bulkley, Cross en Philips-Deutsch). Ander reologiese eienskappe is gemodelleer deur gebruik te maak van eenvoudige regressie modelle. Daar is ook van reologiese tegnieke gebruik gemaak om die vloei en vervormingseienskappe van gesuspendeerde gevesikuleerde partikels, wat as 'n grondstof vir verf gebruik word, te ondersoek. Die belangrikste faktore wat die reologiese gedrag beïnvloed het, was onder meer die verskillende prosesse waarmee die gevesikuleerde partikels vervaardig is. Die effek van sekere van die grondstowwe wat gebruik word om die gevesikuleerde partikels te vervaardig, is ook reologies ondersoek.

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published_or_final_version / Mechanical Engineering / Master / Master of Philosophy

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Diss. (sammanfattning) Uppsala : Univ., 2001. / Härtill 6 uppsatser.

Une étude numérique des suspensions diluées à base d'un fluide à matrice non newtonienne et de particules sphéroïdales rigides est réalisée. Un fluide de Carreau décrit la matrice non newtonienne. Le cas particulier des particules sphériques rigides est pris en compte. Ici, on simule un écoulement élongationnel uniaxial autour d'une sphère et on utilise l'homogénéisation numérique pour obtenir la viscosité apparente de la suspension diluée pour différents taux de déformation appliqués et différents exposants de dilution. Dans le régime newtonien, on obtient le fameux résultat d'Einstein pour la viscosité d'une suspension diluée de particules sphériques rigides. Dans le régime de la loi sur la puissance, on constate que la viscosité intrinsèque ne dépend que de l'exposant d'amincissement. En utilisant les résultats de la simulation, une modification du modèle de Carreau pour les suspensions diluées avec un fluide de matrice non newtonienne est proposée. Pour étudier l'influence de la forme des particules, une autre étude numérique est réalisée. En particulier, différents écoulements autour de particules sphéroïdales de différentes orientations sont simulés et une homogénéisation numérique est utilisée pour obtenir la viscosité intrinsèque de la suspension en fonction de la vitesse de déformation appliquée, de l'exposant d'amincissement et du rapport de forme. A partir des résultats, il est possible d'extraire les coefficients rhéologiques du modèle Lipscomb. Dans le régime newtonien, les résultats de simulation coïncident avec les prévisions de Lipscomb. Dans le régime de la loi de puissance, les coefficients rhéologiques dépendent fortement de l'exposant d'éclaircie. De plus, les résultats de la simulation indiquent que les coefficients rhéologiques dépendent en outre de l'orientation des particules en régime non linéaire. / A numerical study of dilute suspensions based on a non-Newtonian matrix fluid and rigid spheroidal particles is performed. A Carreau fluid describes the non-Newtonian matrix. The special case of rigid spherical particles is considered. Here, a uniaxial elongational flow around a sphere is simulated and numerical homogenization is used to obtain the bulk viscosity of the dilute suspension for different applied rates of deformation and different thinning exponents. In the Newtonian regime the well-known Einstein result for the viscosity of a dilute suspension of rigid spherical particles is obtained. In the power-law regime it is found that the intrinsic viscosity depends only on the thinning exponent. Utilizing the simulation results a modification of the Carreau model for dilute suspensions with a non-Newtonian matrix fluid is proposed. To investigate the influence of the particle shape another numerical study is performed. In particular, different flows around spheroidal particles with different orientations are simulated and numerical homogenization is used to obtain the intrinsic viscosity of the suspension as function of applied rate of deformation, thinning exponent and aspect ratio. From the results it is possible to extract the rheological coefficients of the Lipscomb model. In the Newtonian regime the simulation results coincide with Lipscomb’s predictions. In the power-law regime the rheological coefficients depend strongly on the thinning exponent. Furthermore, simulation results indicate that the rheological coefficients additionally depend on the particle orientation in the non-linear regime.

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