The performance of solid oxide fuel cells (SOFCs) at the cell and system levels is studied using computer simulation. At the cell level, a new model combining the cell micro and macro models is developed. Using this model, the microstructural variables of porous composite electrodes can be linked to the cell performance. In this approach, the electrochemical performance of porous composite electrodes is predicted using a micro-model. In the micro-model, the random-packing sphere method is used to estimate the microstructural properties of porous composite electrodes from the independent microstructural variables. These variables are the electrode porosity, thickness, particle size ratio, and size and volume fraction of electron-conducting particles. Then, the complex interdependency among the multi-component mass transport, electron and ion transports, and the electrochemical and chemical reactions in the microstructure of electrodes is taken into account to predict the electrochemical performance of electrodes. The temperature distribution in the solid structure of the cell and the temperature and species partial pressure distributions in the bulk fuel and air streams are predicted using the cell macro-model. In the macro-model, the energy transport is considered for the cell solid structure and the mass and energy transports are considered for the fuel and air streams. To demonstrate the application of the cell level model developed, entitled the combined micro- and micro-model, several anode-supported co-flow planar cells with a range of microstructures of porous composite electrodes are simulated. The mean total polarization resistance, the mean total power density, and the temperature distribution in the cells are predicted. The results of this study reveal that there is an optimum value for most of the microstructural variables of the electrodes at which the mean total polarization resistance of the cell is minimized. There is also an optimum value for most of the microstructural variables of the electrodes at which the mean total power density of the cell is maximized. The microstructure of porous composite electrodes also plays a significant role in the mean temperature, the temperature difference between the hottest and coldest spots, and the maximum temperature gradient in the solid structure of the cell. Overall, using the combined micro- and micro-model, an appropriate microstructure for porous composite electrodes to enhance the cell performance can be designed. At the system level, the full load operation of two SOFC systems is studied. To model these systems, the basic cell model is used for SOFCs at the cell level, the repeated-cell stack model is used for SOFCs at the stack level, and the thermodynamic model is used for the balance of plant components of the system. In addition to these models, a carbon deposition model based on the thermodynamic equilibrium assumption is employed. For the system level model, the first SOFC system considered is a combined heat and power (CHP) system that operates with biogas fuel. The performance of this system at three different configurations is evaluated. These configurations are different in the fuel processing method to prevent carbon deposition on the anode catalyst. The fuel processing methods considered in these configurations are the anode gas recirculation (AGR), steam reforming (SR), and partial oxidation reformer (POX) methods. The application of this system is studied for operation in a wastewater treatment plant (WWTP) and in single-family detached dwellings. The evaluation of this system for operation in a WWTP indicates that if the entire biogas produced in the WWTP is used in the system with AGR or SR fuel processors, the electric power and heat required to operate the plant can be completely supplied and the extra electric power generated can be sold to the electrical grid. The evaluation of this system for operation in single-family detached dwellings indicates that, depending on the size, location, and building type and design, this system with all configurations studied is suitable to provide the domestic hot water and electric power demands. The second SOFC system is a novel portable electric power generation system that operates with liquid ammonia fuel. Size, simplicity, and high electrical efficiency are the main advantages of this environmentally friendly system. Using a sensitivity analysis, the effects of the cell voltage at several fuel utilization ratios on the number of cells required for the SOFC stack, system efficiency and voltage, and excess air required for thermal management of the SOFC stack are studied.

The performance of solid oxide fuel cells (SOFCs) at the cell and system levels is studied using computer simulation. At the cell level, a new model combining the cell micro and macro models is developed. Using this model, the microstructural variables of porous composite electrodes can be linked to the cell performance. In this approach, the electrochemical performance of porous composite electrodes is predicted using a micro-model. In the micro-model, the random-packing sphere method is used to estimate the microstructural properties of porous composite electrodes from the independent microstructural variables. These variables are the electrode porosity, thickness, particle size ratio, and size and volume fraction of electron-conducting particles. Then, the complex interdependency among the multi-component mass transport, electron and ion transports, and the electrochemical and chemical reactions in the microstructure of electrodes is taken into account to predict the electrochemical performance of electrodes. The temperature distribution in the solid structure of the cell and the temperature and species partial pressure distributions in the bulk fuel and air streams are predicted using the cell macro-model. In the macro-model, the energy transport is considered for the cell solid structure and the mass and energy transports are considered for the fuel and air streams. To demonstrate the application of the cell level model developed, entitled the combined micro- and micro-model, several anode-supported co-flow planar cells with a range of microstructures of porous composite electrodes are simulated. The mean total polarization resistance, the mean total power density, and the temperature distribution in the cells are predicted. The results of this study reveal that there is an optimum value for most of the microstructural variables of the electrodes at which the mean total polarization resistance of the cell is minimized. There is also an optimum value for most of the microstructural variables of the electrodes at which the mean total power density of the cell is maximized. The microstructure of porous composite electrodes also plays a significant role in the mean temperature, the temperature difference between the hottest and coldest spots, and the maximum temperature gradient in the solid structure of the cell. Overall, using the combined micro- and micro-model, an appropriate microstructure for porous composite electrodes to enhance the cell performance can be designed. At the system level, the full load operation of two SOFC systems is studied. To model these systems, the basic cell model is used for SOFCs at the cell level, the repeated-cell stack model is used for SOFCs at the stack level, and the thermodynamic model is used for the balance of plant components of the system. In addition to these models, a carbon deposition model based on the thermodynamic equilibrium assumption is employed. For the system level model, the first SOFC system considered is a combined heat and power (CHP) system that operates with biogas fuel. The performance of this system at three different configurations is evaluated. These configurations are different in the fuel processing method to prevent carbon deposition on the anode catalyst. The fuel processing methods considered in these configurations are the anode gas recirculation (AGR), steam reforming (SR), and partial oxidation reformer (POX) methods. The application of this system is studied for operation in a wastewater treatment plant (WWTP) and in single-family detached dwellings. The evaluation of this system for operation in a WWTP indicates that if the entire biogas produced in the WWTP is used in the system with AGR or SR fuel processors, the electric power and heat required to operate the plant can be completely supplied and the extra electric power generated can be sold to the electrical grid. The evaluation of this system for operation in single-family detached dwellings indicates that, depending on the size, location, and building type and design, this system with all configurations studied is suitable to provide the domestic hot water and electric power demands. The second SOFC system is a novel portable electric power generation system that operates with liquid ammonia fuel. Size, simplicity, and high electrical efficiency are the main advantages of this environmentally friendly system. Using a sensitivity analysis, the effects of the cell voltage at several fuel utilization ratios on the number of cells required for the SOFC stack, system efficiency and voltage, and excess air required for thermal management of the SOFC stack are studied.

Slags plays a significant role at high temperature processes. The estimation of the slag viscosity is vital for the safe run of e.g. entrained flow gasifiers. One opportunity of determination is rotational viscometry. This technique is disadvantageous in view of elevated temperatures, applied materials and the necessary time. Additionally, the viscosity can be predicted by the help of viscosity models, where viscosity is a function of slag composition and temperature. Due to changing slag properties within the technical processes, the calculated viscosities can hugely differ from measured ones. In this work, the viscosities of 42 slags where measured up to 100 Pa s and temperatures up to 1700 °C. Oxidizing and reducing conditions were applied. Additionally, selected slag samples were quenched at defined temperatures to qualitatively and quantitatively determine the formed minerals by X-ray diffraction (XRD). Differential temperature analysis (DTA) was applied to find the onset of crystallization for the complementation of investigations. The Einstein-Roscoe equation was chosen to improve the classic viscosity models. Reducing atmosphere decreased viscosity and the number of formed minerals was increased. Slags show a shear-thinning behavior above ca. 10 vol.-% of solid mineral matter. Also, Newtonian behavior was observed up to 60 vol.-%. To overcome problems with the kinetic cooling behavior of the slags, a viscosity approximation method was applied afterwards. This can result in optimized viscosity predictions when several preconditions are fulfilled.

Slags plays a significant role at high temperature processes. The estimation of the slag viscosity is vital for the safe run of e.g. entrained flow gasifiers. One opportunity of determination is rotational viscometry. This technique is disadvantageous in view of elevated temperatures, applied materials and the necessary time. Additionally, the viscosity can be predicted by the help of viscosity models, where viscosity is a function of slag composition and temperature. Due to changing slag properties within the technical processes, the calculated viscosities can hugely differ from measured ones. In this work, the viscosities of 42 slags where measured up to 100 Pa s and temperatures up to 1700 °C. Oxidizing and reducing conditions were applied. Additionally, selected slag samples were quenched at defined temperatures to qualitatively and quantitatively determine the formed minerals by X-ray diffraction (XRD). Differential temperature analysis (DTA) was applied to find the onset of crystallization for the complementation of investigations. The Einstein-Roscoe equation was chosen to improve the classic viscosity models. Reducing atmosphere decreased viscosity and the number of formed minerals was increased. Slags show a shear-thinning behavior above ca. 10 vol.-% of solid mineral matter. Also, Newtonian behavior was observed up to 60 vol.-%. To overcome problems with the kinetic cooling behavior of the slags, a viscosity approximation method was applied afterwards. This can result in optimized viscosity predictions when several preconditions are fulfilled.:List of Tables ............................................................................................................ vi List of Figures ........................................................................................................ viii Symbols and Abbreviations .................................................................................. xviii 1. Introduction and Aim ....................................................................................... 1 2. General Overview of Slag ............................................................................... 2 2.1 Viscosity ...................................................................................................... 2 2.1.1 Viscosity Introduction ........................................................................... 2 2.1.2 Flow behavior of fluids ......................................................................... 3 2.2 Slag Definition and Phase Diagrams ........................................................... 4 2.3 Solid Slag Structure .................................................................................... 5 2.4 Liquid Slag Structure ................................................................................. 10 2.5 Basicity and B/A-ratio ................................................................................ 11 2.6 Slag Components...................................................................................... 13 2.6.1 Silicon dioxide .................................................................................... 13 2.6.2 Aluminum oxide ................................................................................. 13 2.6.3 Calcium oxide .................................................................................... 15 2.6.4 Iron oxide ........................................................................................... 16 2.6.5 Magnesium Oxide .............................................................................. 18 2.6.6 Potassium Oxide ................................................................................ 19 2.6.7 Sodium Oxide .................................................................................... 20 2.6.8 Titanium Oxide ................................................................................... 21 2.6.9 Phosphorous ...................................................................................... 22 2.6.10 Sulfur .............................................................................................. 22 2.7 Summary of Last Chapters ........................................................................ 23 3. Slag Viscosity Toolbox .................................................................................. 25 3.1 Slag Viscosity Predictor............................................................................. 25 3.2 Slag Viscosity Database............................................................................ 26 3.3 Prediction Quality of Viscosity Models ....................................................... 27 4. Classic Slag Viscosity Modelling ................................................................... 30 4.1 Selected Classic Viscosity Models ............................................................ 31 4.1.1 S2 ....................................................................................................... 32 4.1.2 Watt-Fereday ..................................................................................... 32 4.1.3 Bomkamp ........................................................................................... 32 4.1.4 Shaw .................................................................................................. 32 4.1.5 Lakatos .............................................................................................. 33 4.1.6 Urbain ................................................................................................ 33 4.1.7 Riboud ............................................................................................... 33 4.1.8 Streeter .............................................................................................. 34 4.1.9 Kalmanovitch-Frank ........................................................................... 34 4.1.10 BBHLW .......................................................................................... 34 4.1.11 Duchesne ....................................................................................... 34 4.1.12 ANNliq ............................................................................................ 35 4.2 Need of Improvement in Viscosity Literature ............................................. 35 4.3 Summary of Last Chapters ........................................................................ 36 5. Advanced Slag Viscosity Modelling .............................................................. 37 5.1 Crystallization ............................................................................................ 37 5.1.1 Nucleation .......................................................................................... 38 5.1.2 Crystallization Rate ............................................................................ 39 5.1.3 Crystallization Measurement Methods ............................................... 39 5.2 Slag Properties Changes During Crystallization ........................................ 40 5.2.1 Slag Density ....................................................................................... 40 5.2.2 Solid Volume Fraction ........................................................................ 46 5.2.3 Estimation of Slag Composition During Cooling ................................. 46 5.3 Viscosity Depending on Particles and Shear Rate..................................... 47 5.3.1 Einstein-Roscoe Equation .................................................................. 48 5.3.2 Improved Modelling Approach by Modified Einstein-Roscoe .............. 49 5.4 Summary of Last Chapters ........................................................................ 50 6. Experimental Procedures ............................................................................. 52 6.1 Viscosity Measurements ........................................................................... 52 6.1.1 Estimating Parameter Ranges of Viscosity Measurements ................ 53 6.1.2 Viscosity Measurement Procedure ..................................................... 54 6.2 Thermal Analysis of Slags ......................................................................... 55 6.2.1 Experimental Conditions of DTA ........................................................ 55 6.3 Phase Determination ................................................................................. 55 6.3.1 Quench Experiment Processing ......................................................... 56 6.3.2 Phase Determination on XRD Results ............................................... 56 6.4 Summary of Last Chapters ........................................................................ 57 7. Results and Discussion ................................................................................ 58 7.1 Selected Slag Samples ............................................................................. 58 7.1.1 Slag Sample Composition Before Viscosity Measurements ............... 58 7.1.2 Slag Sample Composition After Viscosity Measurements .................. 59 7.2 General Results of Viscosity Measurements ............................................. 60 7.2.1 Viscosity under Air Atmosphere ......................................................... 63 7.2.2 Viscosity under Reducing Atmospheres ............................................. 65 7.2.3 Viscosity under Constant Partial Oxygen Pressure ............................ 66 7.2.4 Summary of Last Chapter .................................................................. 68 7.3 Mineral Formation ..................................................................................... 69 7.3.1 General Results on Primarily Mineral Formation ................................ 69 7.3.2 Influences on Primarily Mineral Formation ......................................... 70 7.3.3 Mineral Formation over Wide Temperature Ranges ........................... 71 7.3.4 Summary of Last Chapter .................................................................. 77 7.4 Results Obtained by DTA .......................................................................... 78 7.4.1 Comparing Results obtained by DTA and Quenching ........................ 80 7.4.2 Summary of Last Chapter .................................................................. 82 7.5 Shear Rate Influence on Slag Viscosity ..................................................... 82 7.5.1 Shear Rate Influence under Oxidizing Atmospheres .......................... 83 7.5.2 Shear Rate Influence under Reducing Atmospheres .......................... 87 7.5.3 Shear Rate Influence under Constant Atmospheres .......................... 91 7.5.4 Summary of chapter ........................................................................... 92 7.6 Atmospheric Influence on Viscosity ........................................................... 93 7.6.1 Summary of Last Chapter .................................................................. 95 7.7 Cooling Rate Influence on Slag Viscosity .................................................. 95 7.7.1 Summary of Last Chapter .................................................................. 97 8. Advanced Viscosity Modelling Approach ...................................................... 99 8.1 Prediction Quality of Classical Viscosity Models ........................................ 99 8.1.1 Selecting the Best Viscosity Model for Newtonian Flow ..................... 99 8.1.2 Summary of Last Chapter ................................................................ 103 8.2 Predicting Liquidus Temperature ............................................................. 103 8.2.1 Comparing Liquidus Calculations and Quenching Experiments ....... 103 8.2.2 Comparing DTA Results and Liquidus Calculations ......................... 105 8.2.3 Summary of Last Chapter ................................................................ 107 8.3 Predicting Liquid Slag Composition ......................................................... 108 8.3.1 Results of Slag Composition Calculations at Oxidizing Conditions ... 108 8.3.2 Results of Slag Composition Calculations at Reducing Conditions ... 110 8.3.3 Summary of Last Chapter ................................................................ 111 8.4 Modelling Approach ................................................................................ 112 8.4.1 Development of Datasets for Advanced Viscosity Modeling ............. 113 8.4.2 Summary of Last Chapter ................................................................ 116 8.5 Results of Advanced Slag Viscosity Modelling Approach ........................ 116 8.5.1 Summary of Last Chapter ................................................................ 121 9. Summary .................................................................................................... 123 10. Appendix: Information on Classic Viscosity Modelling ................................. 126 10.1 Backgrounds of Applied Viscosity Models............................................ 126 10.2 Viscosity Model of the BCURA (S2) ..................................................... 129 10.3 Watt-Fereday ....................................................................................... 130 10.4 Bomkamp ............................................................................................ 130 10.5 Shaw ................................................................................................... 131 10.6 Lakatos Model ..................................................................................... 132 10.7 Urbain Model ....................................................................................... 133 10.8 Riboud Model ...................................................................................... 134 10.9 Streeter Model ..................................................................................... 136 10.10 Kalmanovitch-Frank Model .................................................................. 137 10.11 BBHLW Model ..................................................................................... 137 10.12 Duchesne Model .................................................................................. 139 10.13 ANNliq Model ...................................................................................... 141 11. Appendix: Settings of Equilibrium Calculations ........................................... 143 12. Appendix: Parameters of Einstein-Roscoe Equation ................................... 153 13. Appendix: Ash and Slag Sample Preparation ............................................. 155 14. Appendix: Experimental Procedures: Viscometer ....................................... 159 14.1 General Viscometer Description .......................................................... 159 14.2 Temperature Calibration ...................................................................... 160 14.3 Viscometer Calibration ......................................................................... 160 14.4 Accuracy and Reproducibility of HT-Viscosity Measurements .............. 161 14.5 Influence of Inductive Heating .............................................................. 163 14.6 Influence of Measurement System Materials ....................................... 164 15. Appendix: Experimental Procedures: Quenching Furnace .......................... 167 16. Appendix: Slag Sample Parameters and Composition ................................ 168 17. Appendix: Slag Viscosity Measurements Results ....................................... 175 18. Appendix: Viscosities at Different Cooling Rates ........................................ 182 19. Appendix: Slag Viscosity Modelling: AALE Calculations ............................. 187 20. Appendix: Advanced Viscosity Modelling: a-factors .................................... 193 21. Appendix: Slag Mineral Phase Investigations and Modelling ...................... 197 22. Appendix: Results of DTA Measurements on Slags .................................... 207 23. Appendix: Advanced Slag Viscosity Modelling Approach ............................ 211 References ........................................................................................................... 228

Trace component analysis in gasification processes are important part of elemental component balances in order to understand the fate of these participating compounds in the feedstock. Residual traces in the raw synthesis gas after quench could bring about the poisoning of catalysts and corrosion effects on plant facilities. The objective of this work is to investigate the effects of quenching operation on the trace components during test campaigns of the autothermal non-catalytic reforming of natural gas (Gas-POX) mode in the HP POX (high pressure partial oxidation) test plant. In order to achieve this, Aspen Plus simulation model of the quench chamber of the HP POX test plant was developed to re-calculate the quench chamber input amount of different trace compounds from their output amount measured during test points of the Gas-POX campaigns. Variation in quench water temperatures from 130 °C to 220 °C and pH value of quench water as well as the resulting variation in Henry´s and Dissociation constant of the traces (CO2, H2S, NH3 and HCN) changed the distribution of traces calculated in the quench water. The formation of traces of organic acid (formic acid and acetic acid) and traces of BTEX, PAHs and soot in the quench water effluent were discussed. The discrepancies between equilibrium constant and reaction quotient (non-equilibrium or real) for the formation of NH3 and HCN at the exit of the gasifier were discussed. The assessment of the results in this work should lead to the improvement in the understanding of trace components and concepts that could be employed to influence their formation and reduction.

Trace component analysis in gasification processes are important part of elemental component balances in order to understand the fate of these participating compounds in the feedstock. Residual traces in the raw synthesis gas after quench could bring about the poisoning of catalysts and corrosion effects on plant facilities. The objective of this work is to investigate the effects of quenching operation on the trace components during test campaigns of the autothermal non-catalytic reforming of natural gas (Gas-POX) mode in the HP POX (high pressure partial oxidation) test plant. In order to achieve this, Aspen Plus simulation model of the quench chamber of the HP POX test plant was developed to re-calculate the quench chamber input amount of different trace compounds from their output amount measured during test points of the Gas-POX campaigns. Variation in quench water temperatures from 130 °C to 220 °C and pH value of quench water as well as the resulting variation in Henry´s and Dissociation constant of the traces (CO2, H2S, NH3 and HCN) changed the distribution of traces calculated in the quench water. The formation of traces of organic acid (formic acid and acetic acid) and traces of BTEX, PAHs and soot in the quench water effluent were discussed. The discrepancies between equilibrium constant and reaction quotient (non-equilibrium or real) for the formation of NH3 and HCN at the exit of the gasifier were discussed. The assessment of the results in this work should lead to the improvement in the understanding of trace components and concepts that could be employed to influence their formation and reduction.:List of Figures vii List of Tables xii List of Abbreviations and Symbols xiii 1 Introduction 1 1.1 Background 1 1.2 Objective of the Work 4 1.3 Overview of the Work 5 2 Process and test conditions 6 2.1 HP POX test plant 6 2.2 Test campaign procedure 8 2.2.1 Gas-POX operating parameter range 8 2.2.2 Gas-POX experiments 9 2.2.3 Net reactions of partial oxidation 9 2.3 Gaseous feedstock characterization 11 2.3.1 Natural gas feedstock composition 11 2.4 Analytical methods for gaseous products 12 2.4.1 Hot gas sampling 12 2.4.2 Raw synthesis gas analysis after quench 13 2.5 Aqueous phase product analysis 14 2.5.1 Molecularly dissolved trace compounds and their ions trace analysis 14 2.5.2 Other trace analysis 15 2.6 Limit of accuracy in measurement systems 15 2.7 Summary 17 3 Simulation and methods 18 3.1 Test points calculation of the HP POX test campaign 18 3.1.1 Aspen Plus model for HP POX quench water system 19 3.2 Gas-POX 201 VP1 quench water system model simulation by Aspen Plus 23 3.2.1 Measured and calculated input parameters 23 3.2.2 Calculated sensitivity studies of species and their distribution for test point (VP1) 24 3.3 Used calculation tools related to the work 25 3.3.1 VBA in Excel 25 3.3.2 Python as interface between Aspen Plus and Microsoft Excel 26 3.3.3 Aspen Simulation Workbook 27 3.4 Summary 29 4 Trace components in quench water system 30 4.1 Physico-chemical parameters of quench water 31 4.1.1 Quench water pH adjustment 32 4.1.2 Henry constant 34 4.1.3 Dissociation constant 35 4.1.4 Organic acids in quench water 38 4.2 Carbon dioxide (CO2) 39 4.2.1 Results of sensitivity study: quench water temperature variation effects on CO2 41 4.2.2 Results of sensitivity study: quench water pH variation influence on CO2 42 4.3 Nitrogen compounds 43 4.3.1 Ammonia (NH3) 44 4.3.2 Results of sensitivity study: quench water temperature variation effects on NH3 46 4.3.3 Results of sensitivity study: quench water pH variation influence on NH3 47 4.3.4 Hydrogen Cyanide (HCN) 48 4.3.5 Results of sensitivity study: quench water temperature variation effects on HCN 50 4.3.6 Results of sensitivity study: quench water pH variation influence on HCN 50 4.4 Sulphur compounds: H2S 51 4.4.1 Results of sensitivity study: quench water temperature variation effects on H2S 53 4.4.2 Results of sensitivity study: quench water pH variation influence on H2S 54 4.5 Summary 55 5 Organic acids trace studies in quench water 57 5.1 Organic acids interaction with ammonia compounds in the quench water 57 5.2 Formic acid 62 5.2.1 Trace of formic acid in quench water 64 5.3 Acetic acid 67 5.3.1 Trace of acetic acid in quench water 69 5.4 Summary 72 6 Temperature approach studies for NH3 and HCN formation in gasifier 74 6.1 Nitrogen compounds: NH3 and HCN 74 6.2 Ammonia (NH3) formation in the gasifer 77 6.3 Hydrogen cyanide (HCN) formation in the gasifier 79 6.4 Discrepancies between back-calculated reaction quotients and equilibrium constants of the NH3 formation 81 6.4.1 Case 1: calculated equilibrium distribution between N2, NH3 and HCN 81 6.4.2 Case 2: calculated equilibrium distribution between NH3 and HCN 83 6.5 Summary 84 7 Traces of BTEX, PAHs and soot in quench water 86 7.1 Quench water behaviour 87 7.2 BTEX compounds 88 7.2.1 BTEX in quench water effluent 90 7.3 PAH compounds 93 7.3.1 PAHs in quench water effluent 95 7.4 Soot formation 99 7.4.1 Soots in quench water effluent 101 7.5 Summary 102 8 Summary and outlook 103 Bibliography 106 9 Appendix 135 List of Figures Figure 2.1: HP POX test plant main facility components and material flow courtesy of [Lurgi GmbH, 2008] 6 Figure 2.2: Simplified scheme of HP POX plant (including quench system) [Lurgi GmbH, 2008] 7 Figure 2.3: Overview of reactions of methane 10 Figure 3.1: Simplified scheme for HP POX quench water system 18 Figure 3.2: Aspen Plus flow diagrams of simulated HP POX quench water system 19 Figure 3.3: Integration of information and functions in VBA via Microsoft Excel to Aspen Plus model 25 Figure 3.4: Integration of information and functions in Python via Microsoft Excel to Aspen Plus model 26 Figure 3.5: ASW enables Excel users to rapidly run scenarios using the underlying rigorous models to analyze plant data, monitor performance, and make better decisions. 27 Figure 4.1: Vapour-liquid equilibria system of CO2, H2S, NH3, HCN and organic acids in the quench water and extended mechanisms according to [Kamps et al., 2001], [Alvaro et al., 2000], [Kuranov et al., 1996], [Xia et al., 1999] and [Edwards et al., 1978]. 30 Figure 4.2: HP POX quench water system with pH regulator for sensitivity studies 34 Figure 4.3: Henry´s constant for CO2, H2S, NH3 and HCN derived from [Edwards et al., 1978] for CO2, [Alvaro et al., 2000] for NH3, [Kamps et al., 2001] for H2S, and [Rumpf et al., 1992] for HCN 35 Figure 4.4: Dissociation constants for CO2, H2S, NH3, HCN and H2O derived from [Alvaro et al., 2000], [Kamps et al., 2001], and [Edwards et al., 1978] 37 Figure 4.5: The flow of CO2 in the quench water cycle (test point VP1). 40 Figure 4.6: Calculated quench water temperature variation and effects on CO2 distribution 42 Figure 4.7: Calculated influence of pH regulation and effects on CO2 distribution 43 Figure 4.8: The flow of NH3 in the quench water cycle (test point VP1). 46 Figure 4.9: Calculated quench water temperature variation and effects on NH3 distribution 47 Figure 4.10: Calculated influence of pH regulation and effects on NH3 distribution 48 Figure 4.11: The flow of HCN in the quench water cycle (test point VP1). 49 Figure 4.12: Calculated quench water temperature variation and effects on HCN distribution 50 Figure 4.13: Calculated influence of pH regulation and effects on HCN distribution 51 Figure 4.14: The flow of H2S in the quench water cycle (test point VP1) 53 Figure 4.15: Calculated quench water temperature variation and effects on H2S distribution 54 Figure 4.16: Calculated influence of pH regulation and effects on H2S distribution 55 Figure 5.1: Aspen Plus back-calculated (real) formic acid concentration, quench water temperature and the calculated equilibrium formic acid concentration against back-calculated (real) ammonia concentration for the 47 test points (using amongst others sampled HCOO- and NH4+ values according to Table 2.6). 59 Figure 5.2: Aspen plus back-calculated (real) formic acid concentration, back-calculated (real) ammonia concentration and the calculated equilibrium formic acid concentration against quench water temperature for the 47 test points (using amongst others sampled HCOO- and NH4+ values according to Table 2.6). 60 Figure 5.3: Aspen plus back-calculated (real) acetic acid concentration, quench water temperature and the calculated equilibrium acetic acid concentration against back-calculated (real) ammonia concentration for the 47 test points. 61 Figure 5.4: Aspen plus back-calculated (real) acetic acid concentration, back-calculated (real) ammonia concentration and the calculated equilibrium acetic acid concentration against quench water temperature for the 47 test points. 62 Figure 5.5: Concentration of formic acid (Aspen plus calculated m_eq and back-calculted m_real) formation in the quench and quench water temperature for the 47 test points. 64 Figure 5.6: Concentration of formic acid (Aspen plus calculated m_eq and back-calculted m_real) in the quench against quench water temperature for the 47 test points (as in Fig.5.2). 65 Figure 5.7: Comparison between formic acid equilibrium constant (Keq), reaction quotient (Kreal) and the quench water temperature for the 47 test points. 66 Figure 5.8: Comparison between formic acid equilibrium constant (Keq) and reaction quotient (Kreal) against quench water temperatures for the 47 test points. 67 Figure 5.9: Concentration of acetic acid (Aspen plus calculated m_eq and back-calculted m_real) in the quench and quench water temperature for the 47 test points. 69 Figure 5.10: Concentration of acetic acid (Aspen plus calculated m_eq and back-calculted m_real) in the quench against quench water temperature for the 47 test points (as in Fig.5.4). 70 Figure 5.11: Comparison between acetic acid equilibrium constant (Keq), reaction quotient (Kreal) and the quench water temperature for the 47 test points. 71 Figure 5.12: Comparison between acetic acid equilibrium constant (Keq) and reaction quotient (Kreal) against quench water temperatures for the 47 test points. 72 Figure 6.1: Mole fraction of gas compoents in the hot gas outlet out of gasifier against hot gas temperature for the 47 test points 76 Figure 6.2: Calculated reaction quotient (Q) and equlibrium constant (Keq) for NH3 against hot gas temperature for the 47 test points (see Fig. 9.10 in Appendix) 77 Figure 6.3: NH3 temperature approach against hot gas temperature for the 47 test points (see Fig. 9.11 in Appendix) 78 Figure 6.4: Calculated reaction quotient (Q) and equlibrium constant (Keq) for HCN against hot gas temperature for the 47 test points (see Fig. 9.13 in Appendix) 79 Figure 6.5: HCN temperature approach against hot gas temperature for the 47 test points (see Fig. 9.14 in Appendix) 80 Figure 6.6: Comparison between calculated real and equilibrium hot gas N2, NH3 and HCN mol fractions against their respective hot gas temperature (case 1). 82 Figure 6.7: Relations between back-calculated real and equilibrium hot gas N2, NH3 and HCN mol fractions (for chemical equilibrium according to equations (6.1) and (6.4)) against their respective hot gas temperature (see Case 1, Section 6.4.1, and Fig. 6.6) 82 Figure 6.8: Comparison between calculated real and equilibrium hot gas HCN mol fraction against their respective hot gas temperature (case 2). 83 Figure 6.9: Relations between back-calculated real and equilibrium hot gas HCN mol fractions, and change in NH3 mol fractions (for chemical equilibrium according to equation (6.4)), against their respective hot gas temperature (see. Case 2, Section 6.4.2 and Fig. 6.7) 84 Figure 6.10 Comparison between NH3 and HCN formation (mole fraction) calculated equilibrium constant (Keq) and calculated reaction quotient (Q), N2 consumption and hot gas temperatures for the 47 test points (case 1 and case 2). 85 Figure 7.1: HP POX test plant quench water system 88 Figure 7.2: Traces of BTEX measured in the Gas-POX 203 – 207 quench water effluent sample. 91 Figure 7.3: Individual component of BTEX measured in the Gas-POX 203 – 207 quench water effluent sample. 92 Figure 7.4: (a) Alkyl radical decomposition and (b) C1 and C2 hydrocarbons oxidation mechanism [Warnatz et al., 2000] 93 Figure 7.5: Recombination of C3H3 to form benzene 94 Figure 7.6: The Diels - Alder reaction for the formation of PAHs 95 Figure 7.7: Amount of PAHs that were detected in Gas-POX 203 – 207 test points quench water effluent samples. 97 Figure 7.8: Distribution of PAH compounds in Gas-POX 203 – 207 quench water effluent samples. 98 Figure 7.9: Some steps in soot formation [McEnally et al., 2006]. 99 Figure 7.10: Illustration of soot formation path in homogenous mixture [Bockhorn et al., 1994] 100 Figure 9.1: Aspen flow sheet set up for HP POX quench system GasPOX 201 VP1 (simplified and extension of Fig. 3.2, organic acids not taken into account). Tabulated values are given in Table 9.11. 135 Figure 9.2: Comparison between the Henry´s constant profiles: Aspen Plus (markers) and Literatures (solid lines) ([Edwards et al., 1978] for CO2, [Alvaro et al., 2000] for NH3, [Kamps et al., 2001] for H2S, and [Rumpf et al., 1992] for HCN as it can be seen in Fig. 4.3) 137 Figure 9.3: Henry´s constant profiles derived from literatures ([Edwards et al., 1978] for CO2, [Alvaro Pérez-Salado et al., 2000] for NH3, [Kamps et al., 2001] for H2S, and [Rumpf et al., 1992] for HCN as it can be seen in Fig. 4.3) 137 Figure 9.4: Comparison between the dissociation constant profiles: Aspen Plus (markers) and Literatures (solid or dashed lines) [Alvaro et al., 2000], [Kamps et al., 2001], and [Edwards et al., 1978] as in Fig.4.4. 138 Figure 9.5: Dissociation constant profiles derived from literatures [Kamps et al., 2001], and [Edwards et al., 1978] as in Fig.4.4. 138 Figure 9.6: Calculated pH values, temperature range and species 139 Figure 9.7: Aspen Plus flow sheet setup for organic acid compounds calculations (GasPOX 201 VP1, see also Table 9.12) 142 Figure 9.8: Aspen Plus flow sheet setup for nitrogen compounds calculations (GasPOX 201 VP1, see also Table 9.12, organic acids are taken into account in the aqueous streams of the quench system) 145 Figure 9.9: Yield of ammonia in gasifier (calculated real) and hot gas temperature against the 47 test points 146 Figure 9.10: Kreal or reaction quotient for ammonia formation in the gasifier against the 47 test points. 146 Figure 9.11: Temperature approach studies for ammonia and the 47 test points 147 Figure 9.12: Yield of HCN from the gasifier (calculated real and equilibrium) and hot gas temperature and the 47 test points 147 Figure 9.13: Comparison between equilibrium constant and reaction quotient for HCN and 47 test points 148 Figure 9.14: Temperature approach studies for HCN and the 47 test points 148 Figure 9.15: Comparison among equilibrium constants of reactions against temperature, T [°C] 149 Figure 9.16: Comparison among equilibrium constants of reactions against temperature, 1/T [1/K] 150 List of Tables Table 2.1: Outline of Gas-POX mode operating parameter range 8 Table 2.2: Outline of test runs operating mode and parameters of chosen test campaigns 9 Table 2.3: Natural gas feedstock compositions 12 Table 2.4: Product synthesis gas analysis method (hot gas before quench) [Brüggemann, 2010] 12 Table 2.5: Analysis methods for raw synthesis gas [Brüggemann, 2010] 13 Table 2.6: Analysis methods for aqueous phase products [Brüggemann, 2010] 14 Table 2.7: Relative accuracy for the measured value for temperature, pressure and flow of each feed and product stream [Meyer, 2007] and [Brüggemann, 2010] 17 Table 3.1: Description of blocks used in Aspen Plus simulation. 20 Table 3.2: HP POX test plant quench water cycle parameters Gas-POX 201 VP1* 23 Table 3.3: pH regulator parameters 24 Table 4.1: Organic acids distribution in streams for VP1 based on calculation from Aspen Plus. 38 Table 4.2: The distribution of CO2 and its ions in all the streams 40 Table 4.3: The distribution of NH3 and its ions in all the streams 45 Table 4.4: The distribution of HCN and its ions in all the streams 49 Table 4.5: The distribution of H2S and its ions in all the streams 52 Table 7.1: Relative sooting tendency [Tesner et al., 2010] 101 Table 9.1: Natural gas feed analysis method [Brüggemann, 2010] 135 Table 9.2: pH scale with examples of solution [NALCO 2008] 136 Table 9.3: Gas-POX test campaigns and with designated serial numbers 140 Table 9.4: Summary of correlation coefficient (r) from Figures in Chapter 5 144 Table 9.5: Comparison among reactions temperatures and heat of reactions 149 Table 9.6: Content of BTEX compounds in Gas-POX quench water samples 151 Table 9.7: BTEX in quench water effluent samples results 152 Table 9.8: Content of PAH compounds in Gas-POX quench water samples 157 Table 9.9: PAHs in quench water effluent samples results 160 Table 9.10: Soot in quench water effluent samples results 169 Table 9.11: Aspen Plus flow sheet setup stream details (GasPOX 201 VP1, according to Fig.3.2 and Fig.9.1, organic acids not taken into account) 170 Table 9.12: Aspen Plus flow sheet setup for organic acid and nitrogen compounds calculations for GasPOX 201 VP1 (according to Figures 9.7 and 9.8, organic acids are taken into account) 174