Im Rahmen dieser Dissertation wurde in einer prospektiven klinischen Studie bei 110 kardiochirurgischen Patienten, welche sich einer Mitralklappenrekonstruktion [MKR] unterzogen, untersucht, ob mittels transösophagealer Echokardiographie [TEE] die Durchblutung der Koronarien zu Beginn, während und nach der Operation dargestellt werden kann und ob die anatomischen Gegebenheiten gut abzugrenzen sind. Dabei wurden der Ramus Circumflexus [RCX] und der Sinus Coronarius [SC] im gesamten Verlauf verfolgt, der Diameter proximal (nach Abgang der Aorta), im Verlauf (bei Überkreuzung der arteriellen und venösen Gefäße) und distal bestimmt und der Blutfluss mittels Dopplersonographie dargestellt. Ein weiterer Punkt war die Untersuchung, ob anhand des Kalibers der Gefäße verlässliche Rückschlüsse auf den Versorgungstyp geschlossen werden können, was sonst nur mittels Koronarangiographie [CA] unter Einsatz von Kontrastmittel invasiv darzustellen war. Zuletzt wurde beim sich noch in Narkose befindlichen Patienten untersucht, ob evtl. erst postoperativ durch iatrogenen Verschluss aufgetretene Wandbewegungsstörungen mittels TEE minimalinvasiv diagnostiziert werden können, sodass ggf. eine sofortige Intervention erfolgen konnte. In der Phase der Datenerhebung kam es bei drei Patienten zu Komplikationen im Sinne einer Obstruktion bzw. Stenose der RCX, wobei die Befunde der TEE-Untersuchungen zusammenmit den klinischen Symptomen in einer anschließenden Koronarangiographie bestätigt wurden. Die Ergebnisse dieser Studie wurden im Jahr 2010 in „The annals of thoracic surgery“ unter dem Titel „Echocardiographic Identification of Iatrogenic Injury of the Circumflex Artery During Minimally Invasive Mitral Valve Repair“ veröffentlicht (1).

This case study evaluates the potential of recovery and utilization of waste heat from three solvent recovery distillation columns, conducted in collaboration with the biotech company Cytiva Sweden AB. Currently, waste heat from distillation processes is dissipated through conventional air-cooling systems without any heat recovery mechanism. Cytiva are assessing utilizing the waste heat with two distinct methods: using a vapor compression heat pump (HP) in a shared circulating cooling system serving multiple waste heat generating processes and implementing a semi-open mechanical vapor recompression system (MVR) within one of the three distillation processes, thereby substituting the conventional virgin steam-powered reboiler with a waste heat-fed alternative. The study pursues a dual objective. Firstly, it to develops a computational model based on simplified process schematics, fluid flows, and temperatures, encompassing five scenarios, including a baseline scenario devoid of waste heat recuperation or utilization. Two scenarios involving an HP within the cooling system, leveraging waste heat to elevate water temperatures from 50 ⁰C to the requisite 80 ⁰C for subsequent export into a district heating distribution grid. Another scenario integrates an MVR system into one distillation process, while conventionally cooling the remaining waste heat flows. Lastly, a combined scenario incorporates both the HP and MVR systems. Using operational parameters, energy prices, and emissions factors from 2023, the model identifies the optimal alternative based on energy savings, emission reduction, and economic profitability. The combined HP and MVR system emerges as the most favorable option, yielding annual energy savings of 14 500 MWh, a heat export of 9 800 MWh/year generating profits of 4.9 Mkr/year, emissions reductions of 2 000 tonCO2ekv/year, and a yearly total cost savings of 9.9 Mkr. However, the combined system is also the most expensive option. The independent nature of the two systems facilitates ease of installation and operation. These findings provide valuable insights for Cytiva in their efforts to mitigate environmental impact through heat recovery and utilization.

Permeability is an important property of a porous medium and it controls the flow of fluid through the medium. Particle characteristics are known to affect the value of the permeability. However, experimental investigation of the effects of these particle characteristics on the value of permeability is time-consuming while analytical predictions have been reported to overestimate it leading to inefficient design. To overcome these challenges, there is the need for the development of new models that can predict permeability based on input variables and process conditions. In this research, data from experiments, Computational Fluid Dynamics (CFD) and literature were employed to develop new models using Multivariate Regression (MVR) and Artificial Neural Networks (ANNs). Experimental measurements of permeability were performed using high and low shear separation processes. Particles of talc, calcium carbonate and titanium dioxide (P25) were used in order to study porous media with different particle characteristics and feed concentrations. The effects of particle characteristics and initial stages of filtration as well as the reliability of filtration techniques (constant pressure filtration, CPF and constant rate filtration, CRF) were investigated. CFD simulations were also performed of porous media for different particle characteristics to generate additional data. The regression and ANN models also included permeability data taken from reliable literature sources. Particle cluster formation was only found in P25 leading to an increase of permeability especially in sedimentation. The constant rate filtration technique was found more suitable for permeability measurement than constant pressure. Analyses of data from the experiments, CFD and correlation showed that Sauter mean diameter (ranging from 0.2 to 168 μm), the fines ratio (x50/x10), particle shape (following Heywood s approach), and voidage of the porous medium (ranging from 98.5 to 37.2%) were the significant parameters for permeability prediction. Using these four parameters as inputs, performance of models based on linear and nonlinear MVR as well as ANN were investigated together with the existing analytical models (Kozeny-Carman, K-C and Happel-Brenner, H-B). The coefficient of correlation (R2), root mean square error (RMSE) and average absolute error (AAE) were used as performance criteria for the models. The K-C and H-B are two-variable models (Sauter mean diameter and voidage) and two variables ANN and MVR showed better predictive performance. Furthermore, four-variable (Sauter mean diameter, the x50/x10, particle shape, and voidage) models developed from the MVR and ANN exhibit excellent performance. The AAE was found with K-C and H-B models to be 35 and 40%, respectively while the results of using ANN2 model reduced the AAE to 14%. The ANN4 model further decreased the AAE to approximately 9% compared to the measured results. The main reason for this reduced error was the addition of a shape coefficient and particle spread (fine ratio) in the ANN4 model. These two parameters are absent in the analytical relations, such as K-C and H-B models. Furthermore, it was found that using the ANN4 (4-5-1) model led to increase in the R2 value from 0.90 to 0.99 and significant decrease in the RMSE value from 0.121 to 0.054. Finally, the investigations and findings of this work demonstrate that relationships between permeability and the particle characteristics of the porous medium are highly nonlinear and complex. The new models possess the capability to predict the permeability of porous media more accurately owing to the incorporation of additional particle characteristics that are missing in the existing models.

The objective of this work is to determine the effect of four process variables on the properties of blends composed of bisphenol-A polycarbonate (PC) and poly (butylene terephthalate) (PBT) polymers which are compounded using a large scale commercial extruder. The four variables studied are blend composition, specific energy consumption, residence time and shear rate. The last three factors were varied using the extruder screw speed and feed rate. The PC/PBT blends, commercially known as XENOY, were compounded using a WP ZSK 58 mm co-rotating twin screw extruder at the facility of SABIC Innovative Plastics in Cobourg Ontario. The extruder was instrumented to measure online the die pressure, specific energy consumption and blend temperature. The blends were characterized using differential scanning calorimetry, (DSC), scanning electron microscopy, (SEM), gel permeation chromatography, (GPC), and melt volume flow rate, (MVR). After processing, the blend properties determined were melting temperature, glass transition temperature, crystallinity, amorphous phase weight fraction, amorphous phase composition, phase morphology, PBT-rich-phase size, blend molecular weight distribution, and MVR. Using principles available in the literature, a linear regression model was developed to relate the process variables with the online measured properties and output blend properties. Fitting this model allowed the relative importance of each process variable to be estimated for each property. An attempt was also made to identify the general type of PC/PBT blend studied and how it compares with published PC/PBT blend data. It was found that the blends studied were well stabilized since there was no evidence of significant co-polymer formation during processing. Small decreases in molecular weight were attributed to mechanical degradation. Blending increased the crystallization and melting temperatures, as well as blend crystallinity. No practically significant difference in melting temperatures was observed between the different processing conditions. Analysis of glass transitions indicated that the blend components were partially miscible. The amorphous phase compositions were unaffected by blend composition or processing; however, the weight fraction PC-rich-phase present in the blend was strongly influenced by the screw speed. The phase structure of as-extruded blends could not be resolved using the SEM. Therefore, the blends were annealed to coarsen the phases. After annealing, a continuous PC-rich-phase and a discrete PBT-rich-phase were observed. The PBT phase size increased with increasing PBT content. No other statistically significant effects on phase size were observed but this is not conclusive due to the large scatter in the measurements. MVR was primarily influenced by blend composition and specific energy consumption, with the effects of composition being dominant. Further study using higher imaging resolution is required if the phase structures of as received blend pellets are to be characterized. Contrary to current practice, it is recommended that the Utracki-Jukes equation be used rather than the Fox equation for determining amorphous phase composition from glass transition data in PC/PBT blends.

The objective of this work is to determine the effect of four process variables on the properties of blends composed of bisphenol-A polycarbonate (PC) and poly (butylene terephthalate) (PBT) polymers which are compounded using a large scale commercial extruder. The four variables studied are blend composition, specific energy consumption, residence time and shear rate. The last three factors were varied using the extruder screw speed and feed rate. The PC/PBT blends, commercially known as XENOY, were compounded using a WP ZSK 58 mm co-rotating twin screw extruder at the facility of SABIC Innovative Plastics in Cobourg Ontario. The extruder was instrumented to measure online the die pressure, specific energy consumption and blend temperature. The blends were characterized using differential scanning calorimetry, (DSC), scanning electron microscopy, (SEM), gel permeation chromatography, (GPC), and melt volume flow rate, (MVR). After processing, the blend properties determined were melting temperature, glass transition temperature, crystallinity, amorphous phase weight fraction, amorphous phase composition, phase morphology, PBT-rich-phase size, blend molecular weight distribution, and MVR. Using principles available in the literature, a linear regression model was developed to relate the process variables with the online measured properties and output blend properties. Fitting this model allowed the relative importance of each process variable to be estimated for each property. An attempt was also made to identify the general type of PC/PBT blend studied and how it compares with published PC/PBT blend data. It was found that the blends studied were well stabilized since there was no evidence of significant co-polymer formation during processing. Small decreases in molecular weight were attributed to mechanical degradation. Blending increased the crystallization and melting temperatures, as well as blend crystallinity. No practically significant difference in melting temperatures was observed between the different processing conditions. Analysis of glass transitions indicated that the blend components were partially miscible. The amorphous phase compositions were unaffected by blend composition or processing; however, the weight fraction PC-rich-phase present in the blend was strongly influenced by the screw speed. The phase structure of as-extruded blends could not be resolved using the SEM. Therefore, the blends were annealed to coarsen the phases. After annealing, a continuous PC-rich-phase and a discrete PBT-rich-phase were observed. The PBT phase size increased with increasing PBT content. No other statistically significant effects on phase size were observed but this is not conclusive due to the large scatter in the measurements. MVR was primarily influenced by blend composition and specific energy consumption, with the effects of composition being dominant. Further study using higher imaging resolution is required if the phase structures of as received blend pellets are to be characterized. Contrary to current practice, it is recommended that the Utracki-Jukes equation be used rather than the Fox equation for determining amorphous phase composition from glass transition data in PC/PBT blends.

Im Rahmen dieser Dissertation wurde in einer prospektiven klinischen Studie bei 110 kardiochirurgischen Patienten, welche sich einer Mitralklappenrekonstruktion [MKR] unterzogen, untersucht, ob mittels transösophagealer Echokardiographie [TEE] die Durchblutung der Koronarien zu Beginn, während und nach der Operation dargestellt werden kann und ob die anatomischen Gegebenheiten gut abzugrenzen sind. Dabei wurden der Ramus Circumflexus [RCX] und der Sinus Coronarius [SC] im gesamten Verlauf verfolgt, der Diameter proximal (nach Abgang der Aorta), im Verlauf (bei Überkreuzung der arteriellen und venösen Gefäße) und distal bestimmt und der Blutfluss mittels Dopplersonographie dargestellt. Ein weiterer Punkt war die Untersuchung, ob anhand des Kalibers der Gefäße verlässliche Rückschlüsse auf den Versorgungstyp geschlossen werden können, was sonst nur mittels Koronarangiographie [CA] unter Einsatz von Kontrastmittel invasiv darzustellen war. Zuletzt wurde beim sich noch in Narkose befindlichen Patienten untersucht, ob evtl. erst postoperativ durch iatrogenen Verschluss aufgetretene Wandbewegungsstörungen mittels TEE minimalinvasiv diagnostiziert werden können, sodass ggf. eine sofortige Intervention erfolgen konnte. In der Phase der Datenerhebung kam es bei drei Patienten zu Komplikationen im Sinne einer Obstruktion bzw. Stenose der RCX, wobei die Befunde der TEE-Untersuchungen zusammenmit den klinischen Symptomen in einer anschließenden Koronarangiographie bestätigt wurden. Die Ergebnisse dieser Studie wurden im Jahr 2010 in „The annals of thoracic surgery“ unter dem Titel „Echocardiographic Identification of Iatrogenic Injury of the Circumflex Artery During Minimally Invasive Mitral Valve Repair“ veröffentlicht (1).

Biotechnologies potentially have significant benefits for developing countries but many countries lack complete regulatory processes to allow their release. In evaluating the potential benefits of genetically modified crops, one must be able to measure the true cost of regulations in addition to the other costs associated with bringing the crop to market. The objectives of this paper are to (1) identify the direct costs of the regulation of Bt eggplant, Bt rice, ringspot virus resistant (PRSV) papaya and virus resistant tomatoes in the Philippines, and (2) estimate the opportunity cost of time lost in the regulatory process. The study compares the cost of regulations as they differ by factors such as the existence of previous studies on the product or the intention for export or domestic use. It is hypothesized that the costs are greater for products that are intended for export or human consumption or are produced by the private sector. It is also hypothesized that these factors increase the time to complete the regulatory process, therefore increasing the opportunity cost of time. This study evaluates the economic impact of the GMO regulatory process on the change in producer surplus, the net present value and the internal rate return using an economic surplus model. Scientists and other experts in the field of GMOs and regulation were interviewed to obtain the necessary data on the regulatory process. The evaluation was carried out for four different commodities in the Philippines, Bt Rice, Bt Eggplant, PRSV Papaya and MVR Tomato. The results for the open economy model revealed a change in producer surplus, as a result of the GMO research, of $418.3 million for Bt Rice and $353.7 million for PRSV Papaya. The closed economy model of Bt Eggplant has a change in producer surplus of $25.1 million and a change in total surplus of $40.8 million while the result for the change in producer surplus for MVR Tomato is $19.3 million and the change in total surplus is $51.6 million. A sensitivity analysis of the results was then carried out in which the elasticity of supply, the cost of regulation, and the release date were each varied in order to show the welfare impact of such changes. The sensitivity analysis revealed limited changes in surplus when elasticity and regulatory costs were changed. However, changing the date of release or commercialization resulted in monumental changes in surplus. / Master of Science

Blends of poly butylene terephthalate (PBT) and polycarbonate (PC) form a very important class of commercial blends in numerous applications requiring materials with good chemical resistance, impact resistance even at low temperatures, and aesthetic and flow characteristics. PC and PBT are usually blended in a twin screw extruder (TSE). Product melt volume flow rate (MVR) is a property used to monitor product quality while blending the PC/PBT in a twin screw extruder. It is usually measured off line in a quality control laboratory using extrusion plastometer on samples collected discretely during the compounding operation. Typically a target value representing the desired value of the quality characteristics for an in-control process, along with upper and lower control limits are specified. As long as the MVR measurement is within the control limits, the sample is approved and the whole compounded blend is assumed to meet the specification. Otherwise, the blend is rejected. Because of infrequent discrete sampling, corrective actions are usually applied with delay, thus resulting in wasted material. It is important that the produced PC/PBT blend pellets have consistent properties. Variability and fault usually arise from three sources: human errors, feed material variability, and machine operation (i.e. steady state variation). Among these, the latter two are the major ones affecting product quality. The resulting variation in resin properties contributes to increased waste products, larger production cost and dissatisfied customers. Motivated by this, the objective of this project was to study the compounding operation of PC/PBT blend in a twin screw extruder and to develop a feasible methodology that can be applied on-line for monitoring properties of blends on industrial compounding operations employing available extruder input and output variables such as screw speed, material flow rate, die pressure and torque. To achieve this objective, a physics-based model for a twin screw extruder along with a MVR model were developed, examined and adapted for this study, and verified through designed experiments. This dynamic model for a TSE captures the important dynamics, and relates measurable process variables (screw speed, torque, feed rates, pressure etc.) to ones that are not being measured (material holdups and compositions at the partially and filled section along a TSE barrel). This model also provides product quality sensors or inferential estimation techniques for prediction of viscosity and accordingly MVR. The usefulness of the model for inferential MVR sensing and fault diagnosis was demonstrated on experiments performed on a 58 mm co-rotating twin-screw extruder for an industrial compounding operation at a SABIC Innovative Plastics plant involving polycarbonate – poly butylene terephthalate blends. The results showed that the model has the capability of identifying faults (i.e., process deviation from the nominal conditions) in polymer compounding operations with the twin screw extruder. For instance, the die pressure exhibited a change as a function of changes in raw materials and feed composition of PC and PBT. In the presence of deviations from nominal conditions, the die pressure parameters are updated. These die pressure model parameters were identified and updated using the recursive parameter estimation method. The recursive identification of the die pressure parameters was able to capture very well the effects of changes in raw material and/or composition on the die pressure. In addition, the developed MVR model showed a good ability in monitoring product MVR on-line and inferentially from output process variables such as die pressure which enables quick quality control to maintain products within specification limits and to minimize waste production.

In this work, the compounding of polycarbonate (PC) / poly-butylene terephthalate (PBT) blends was studied for the purpose of improving quality of products with reduced wastage and finally to satisfaction of end users. The effect of material rheological characteristics and processing conditions on compounding of PC /PBT was investigated through statistical experiments carried out on a 58 mm twin-screw extruder at SABIC Innovative Plastics Limited (formerly GE Plastics Limited) in Cobourg, Ontario. Melt Volume-Flow Rate (MVR) is the most commonly used property to monitor the quality of products of PC/PBT blends. The MVR was studied with different sampling times and correlations between product properties (melt flow) and processing conditions (screw speed, flow rates) were discussed. The rheological behavior of PC/PBT blends was investigated by dynamic and capillary rheometers. The effects of processing conditions (screw speed, feed rate) on viscosity were measured and it was found that the Cox-Merz rule is not valid for PC/PBT blends. The change of morphology of PC/PBT blends was observed under a scanning electron microscope (SEM) by using different types of samples. Those samples were (i) PC/PBT blends pellets, (ii) PC/PBT blend samples, but collected after completing the rheological tests in the parallel plate rheometer, and (iii) PC/PBT blend samples, but collected after completing the rheological tests in the capillary rheometer. There was evidence that the samples collected after completing the tests in the parallel and capillary rheometer might be degraded due to temperature and time.

Blends of poly butylene terephthalate (PBT) and polycarbonate (PC) form a very important class of commercial blends in numerous applications requiring materials with good chemical resistance, impact resistance even at low temperatures, and aesthetic and flow characteristics. PC and PBT are usually blended in a twin screw extruder (TSE). Product melt volume flow rate (MVR) is a property used to monitor product quality while blending the PC/PBT in a twin screw extruder. It is usually measured off line in a quality control laboratory using extrusion plastometer on samples collected discretely during the compounding operation. Typically a target value representing the desired value of the quality characteristics for an in-control process, along with upper and lower control limits are specified. As long as the MVR measurement is within the control limits, the sample is approved and the whole compounded blend is assumed to meet the specification. Otherwise, the blend is rejected. Because of infrequent discrete sampling, corrective actions are usually applied with delay, thus resulting in wasted material. It is important that the produced PC/PBT blend pellets have consistent properties. Variability and fault usually arise from three sources: human errors, feed material variability, and machine operation (i.e. steady state variation). Among these, the latter two are the major ones affecting product quality. The resulting variation in resin properties contributes to increased waste products, larger production cost and dissatisfied customers. Motivated by this, the objective of this project was to study the compounding operation of PC/PBT blend in a twin screw extruder and to develop a feasible methodology that can be applied on-line for monitoring properties of blends on industrial compounding operations employing available extruder input and output variables such as screw speed, material flow rate, die pressure and torque. To achieve this objective, a physics-based model for a twin screw extruder along with a MVR model were developed, examined and adapted for this study, and verified through designed experiments. This dynamic model for a TSE captures the important dynamics, and relates measurable process variables (screw speed, torque, feed rates, pressure etc.) to ones that are not being measured (material holdups and compositions at the partially and filled section along a TSE barrel). This model also provides product quality sensors or inferential estimation techniques for prediction of viscosity and accordingly MVR. The usefulness of the model for inferential MVR sensing and fault diagnosis was demonstrated on experiments performed on a 58 mm co-rotating twin-screw extruder for an industrial compounding operation at a SABIC Innovative Plastics plant involving polycarbonate – poly butylene terephthalate blends. The results showed that the model has the capability of identifying faults (i.e., process deviation from the nominal conditions) in polymer compounding operations with the twin screw extruder. For instance, the die pressure exhibited a change as a function of changes in raw materials and feed composition of PC and PBT. In the presence of deviations from nominal conditions, the die pressure parameters are updated. These die pressure model parameters were identified and updated using the recursive parameter estimation method. The recursive identification of the die pressure parameters was able to capture very well the effects of changes in raw material and/or composition on the die pressure. In addition, the developed MVR model showed a good ability in monitoring product MVR on-line and inferentially from output process variables such as die pressure which enables quick quality control to maintain products within specification limits and to minimize waste production.