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Analysis and design of the modular multilevel converter for secure systems
Get PDFThis thesis investigates the operation, dynamics and design of modular multilevel converters (MMCs) for stable and reliable operation. The internal dynamics and control schemes of the conventional MMC is analysed with consideration of passive component tolerances. Detail qualitative and quantitative analysis of MMC internal dynamics with different control strategies, is performed. Inter-arm passive component tolerances lead to fundamental and higher odd-order harmonics in the common-mode loop, which may cause external oscillation in the dclink. Considering the technical characteristics of the half-bridge SM (HB-SM) and fullbridge SM (FB-SM), a T-type MMC (T-MMC) consisting of two SM-based stages is proposed in this research. The first stage of the T-MMC is a conventional MMC; and the second stage is a series-connected flexible AC transmission system (FACTS) device. The reliability and stability of the converter are significantly increased, whereas flexible operation with various modes is attained. Also, converter ac and dc fault-tolerant capabilities become feasible. Two bypassing approaches are presented to reduce the conduction losses of the FB-SMs; therefore, the converter normal mode operation efficiency becomes similar to that of the conventional MMC. The T-MMC integrated with energy storage elements (ESEs) is studied, and it is found that the T-MMC based energy storage system (ESS) can not only isolate faults but maintain continuous power for the normal side, which greatly improves stability and reliability of the connected systems. A T-MMC based multi-terminal high voltage dc (HVDC) network is studied, indicating the effectiveness of the T-MMC in power system scenarios. The presented investigation and design are supported by theoretical analysis, simulation, and experimentation.This thesis investigates the operation, dynamics and design of modular multilevel converters (MMCs) for stable and reliable operation. The internal dynamics and control schemes of the conventional MMC is analysed with consideration of passive component tolerances. Detail qualitative and quantitative analysis of MMC internal dynamics with different control strategies, is performed. Inter-arm passive component tolerances lead to fundamental and higher odd-order harmonics in the common-mode loop, which may cause external oscillation in the dclink. Considering the technical characteristics of the half-bridge SM (HB-SM) and fullbridge SM (FB-SM), a T-type MMC (T-MMC) consisting of two SM-based stages is proposed in this research. The first stage of the T-MMC is a conventional MMC; and the second stage is a series-connected flexible AC transmission system (FACTS) device. The reliability and stability of the converter are significantly increased, whereas flexible operation with various modes is attained. Also, converter ac and dc fault-tolerant capabilities become feasible. Two bypassing approaches are presented to reduce the conduction losses of the FB-SMs; therefore, the converter normal mode operation efficiency becomes similar to that of the conventional MMC. The T-MMC integrated with energy storage elements (ESEs) is studied, and it is found that the T-MMC based energy storage system (ESS) can not only isolate faults but maintain continuous power for the normal side, which greatly improves stability and reliability of the connected systems. A T-MMC based multi-terminal high voltage dc (HVDC) network is studied, indicating the effectiveness of the T-MMC in power system scenarios. The presented investigation and design are supported by theoretical analysis, simulation, and experimentation
Foreign direct investment in an unsettling economic and socio-political environment
Get PDFThis thesis consists of three empirical chapters around the central theme on the role of economic policy shocks and socio-political disruption play in informing foreign direct investment (FDI). The first empirical chapter examines whether economic policy uncertainty (EPU) explains variations in cross-border merger and acquisition (CBA) activities from 20 countries over the period 1997-2017. The results suggest that a higher degree of EPU at home retards the number and volume of inbound CBA deals. However, the inverse relationship between EPU and inward CBA is moderated by the quality of the host country's institutions, business environment, and political risk.;The bilateral acquirer-target country-pair investigation reveals that, while higher EPU in the target's nation deters inbound CBAs, higher EPU in the acquirer nation is positively associated with a higher number and volume of outbound CBA deals. Finally, the market seems to revise the expected synergy from the CBAs negatively (positively) in the form of lower (higher) cumulative returns when the target's (acquirer's) domicile faces higher EPU.;The second empirical chapter investigates how populist government policies, induced by immigration-related fear sentiments (IFS), affect inbound CBAs in 4 countries over the period 1995-2017. Consistent with the economic conjecture that populism creates deadweight costs for potential international investors, the findings strongly indicate that the number of inbound CBAs significantly declines following the escalation of IFS. Using two discrete exogenous shocks that escalated anti-immigration populism, the results show a significant drop in inbound CBAs, reduced likelihood of receiving acquisition bids, and lengthier deal completion period for the target firms located in major developed economies.;The inverse nexus between IFS and CBAs seems to be more pronounced in economies with anti-immigration populist (AIP) governments and in labour intensive industries.;Finally, the third empirical chapter quantifies the effect of geopolitical risk (GPR) on FDI inflows. In terms of empirical identification, I exploit the economic shock of the Arab Spring and use it as a source of exogenous variation in GPR over the period 2005-2015 for 175 countries. Also, I employ a time-varying media-based measure of GPR in 18 countries over the period 1988-2016. The results support the negative link between GPR and FDI in both identifications.;The findings of all three empirical chapters, taken as a whole, supports the notion that uncertainty surrounding government policy, migration fears, and geopolitical tensions have a significant and detrimental effect on FDI flows. I believe the finding of this thesis carry important implications for policy makers as indecision from policy makers, with respect to domestic and global political issues, may negatively impact an economy's ability to efficiently allocate capital.This thesis consists of three empirical chapters around the central theme on the role of economic policy shocks and socio-political disruption play in informing foreign direct investment (FDI). The first empirical chapter examines whether economic policy uncertainty (EPU) explains variations in cross-border merger and acquisition (CBA) activities from 20 countries over the period 1997-2017. The results suggest that a higher degree of EPU at home retards the number and volume of inbound CBA deals. However, the inverse relationship between EPU and inward CBA is moderated by the quality of the host country's institutions, business environment, and political risk.;The bilateral acquirer-target country-pair investigation reveals that, while higher EPU in the target's nation deters inbound CBAs, higher EPU in the acquirer nation is positively associated with a higher number and volume of outbound CBA deals. Finally, the market seems to revise the expected synergy from the CBAs negatively (positively) in the form of lower (higher) cumulative returns when the target's (acquirer's) domicile faces higher EPU.;The second empirical chapter investigates how populist government policies, induced by immigration-related fear sentiments (IFS), affect inbound CBAs in 4 countries over the period 1995-2017. Consistent with the economic conjecture that populism creates deadweight costs for potential international investors, the findings strongly indicate that the number of inbound CBAs significantly declines following the escalation of IFS. Using two discrete exogenous shocks that escalated anti-immigration populism, the results show a significant drop in inbound CBAs, reduced likelihood of receiving acquisition bids, and lengthier deal completion period for the target firms located in major developed economies.;The inverse nexus between IFS and CBAs seems to be more pronounced in economies with anti-immigration populist (AIP) governments and in labour intensive industries.;Finally, the third empirical chapter quantifies the effect of geopolitical risk (GPR) on FDI inflows. In terms of empirical identification, I exploit the economic shock of the Arab Spring and use it as a source of exogenous variation in GPR over the period 2005-2015 for 175 countries. Also, I employ a time-varying media-based measure of GPR in 18 countries over the period 1988-2016. The results support the negative link between GPR and FDI in both identifications.;The findings of all three empirical chapters, taken as a whole, supports the notion that uncertainty surrounding government policy, migration fears, and geopolitical tensions have a significant and detrimental effect on FDI flows. I believe the finding of this thesis carry important implications for policy makers as indecision from policy makers, with respect to domestic and global political issues, may negatively impact an economy's ability to efficiently allocate capital
Dimension reduction methods for non-stationary multivariate time series
Get PDFIn this thesis, we extend the principal component analysis (PCA) to account for both stationary and non-stationary time series data. The dimension reduction methods we propose will employ a moving cross-covariance matrix of data, which can be updated as we move in time. We show that the moving cross-covariance matrix can extract dynamic dependence among variables of both stationary and non-stationary series.;The first two methods we propose can be considered as a generalization of dynamic principal component analysis (DPCA) of Ku et al. (1995) to the nonstationary case. The first method will apply eigenanalysis on the moving crosscovariance matrix of the extended data vector that can be formed by including lagged series into the original data vector. The second method is different from the first one, where we apply eigenanalysis on a quadratic-order of the moving crosscovariance matrix of the extended data vector. In order to optimize the results of our methods, we will propose a new criterion to determine the optimal number of principal components to retain.;Additionally, we are going to introduce the moving cross-correlation function that can be used to evaluate the correlations between non-stationary variables. The third dimension reduction method that we introduce will generalize the principal component analysis for time series (TS-PCA) of Chang et al. (2018) to non-stationary series. This method seeks a linear transformation such that the transformed series is segmented into uncorrelated subseries with lower dimensions that can be separately analysed as they are not correlated. The latter method will account for high-dimensional time series.;Theoretical properties of the proposed methods show the consistency of the used estimators. All methods prove their abilities to dimension reduction of both stationary and non-stationary series based on simulated and real data sets.In this thesis, we extend the principal component analysis (PCA) to account for both stationary and non-stationary time series data. The dimension reduction methods we propose will employ a moving cross-covariance matrix of data, which can be updated as we move in time. We show that the moving cross-covariance matrix can extract dynamic dependence among variables of both stationary and non-stationary series.;The first two methods we propose can be considered as a generalization of dynamic principal component analysis (DPCA) of Ku et al. (1995) to the nonstationary case. The first method will apply eigenanalysis on the moving crosscovariance matrix of the extended data vector that can be formed by including lagged series into the original data vector. The second method is different from the first one, where we apply eigenanalysis on a quadratic-order of the moving crosscovariance matrix of the extended data vector. In order to optimize the results of our methods, we will propose a new criterion to determine the optimal number of principal components to retain.;Additionally, we are going to introduce the moving cross-correlation function that can be used to evaluate the correlations between non-stationary variables. The third dimension reduction method that we introduce will generalize the principal component analysis for time series (TS-PCA) of Chang et al. (2018) to non-stationary series. This method seeks a linear transformation such that the transformed series is segmented into uncorrelated subseries with lower dimensions that can be separately analysed as they are not correlated. The latter method will account for high-dimensional time series.;Theoretical properties of the proposed methods show the consistency of the used estimators. All methods prove their abilities to dimension reduction of both stationary and non-stationary series based on simulated and real data sets
Coupling simulation with machine learning for the development of a proactive HVAC system in the manufacturing sector
Get PDFThe industrial sector consumes 55% of the world's energy consumption [1]. Following manufacturing processes, the HVAC system is the second largest energy consumer in manufacturing facilities, yet is generally uncounted for and considered an indirect cost to maintain a facility [2]. Any current efforts at reducing energy demand in the manufacturing sector have been focused towards process machines rather than on the manufacturing building as a holistic energy system. Currently, HVAC systems are reactive, responding to changes to the environment as they happen, based upon requirements for thermal comfort. Manufacturing facility environments however are subject to complex interactions between machine level resources, water, heat and compressed air.;This study questions the suitability of the reactive thermal comfort based HVAC system, and proposes a proactive manufacturing based HVAC control system, utilising predicted optimum HVAC set points. Through the use of simulation, a holistic analysis of a manufacturing facility was performed, based on building location and layout, building fabrics, weather conditions and manufacturing demand in order to determine the relationship between manufacturing demand and HVAC control. A number of predictive models were analysed for suitability for use in the manufacturing, before being trained on simulation data for the prediction of optimum HVAC set points and corresponding facility indoor conditions.;Simulation was coupled with predictive modelling in order to predict building energy and HVAC energy demand, allowing for the identification of potential future spikes in consumption, followed by subsequent HVAC and manufacturing schedule optimisation, allowing for a 15.1 % reduction in peak energy demand. Through simulation and predictive modelling, the research has demonstrated the potential energy savings achieved by adopting a proactive HVAC system in the manufacturing sector. Such a methodology achieved 14.1 % energy savings over a 12-month period for an analysed case study environment. [See thesis text for references]The industrial sector consumes 55% of the world's energy consumption [1]. Following manufacturing processes, the HVAC system is the second largest energy consumer in manufacturing facilities, yet is generally uncounted for and considered an indirect cost to maintain a facility [2]. Any current efforts at reducing energy demand in the manufacturing sector have been focused towards process machines rather than on the manufacturing building as a holistic energy system. Currently, HVAC systems are reactive, responding to changes to the environment as they happen, based upon requirements for thermal comfort. Manufacturing facility environments however are subject to complex interactions between machine level resources, water, heat and compressed air.;This study questions the suitability of the reactive thermal comfort based HVAC system, and proposes a proactive manufacturing based HVAC control system, utilising predicted optimum HVAC set points. Through the use of simulation, a holistic analysis of a manufacturing facility was performed, based on building location and layout, building fabrics, weather conditions and manufacturing demand in order to determine the relationship between manufacturing demand and HVAC control. A number of predictive models were analysed for suitability for use in the manufacturing, before being trained on simulation data for the prediction of optimum HVAC set points and corresponding facility indoor conditions.;Simulation was coupled with predictive modelling in order to predict building energy and HVAC energy demand, allowing for the identification of potential future spikes in consumption, followed by subsequent HVAC and manufacturing schedule optimisation, allowing for a 15.1 % reduction in peak energy demand. Through simulation and predictive modelling, the research has demonstrated the potential energy savings achieved by adopting a proactive HVAC system in the manufacturing sector. Such a methodology achieved 14.1 % energy savings over a 12-month period for an analysed case study environment. [See thesis text for references
Mixed methods evaluation of the cost benefit of a telehealth programme for chronic obstructive pulmonary disease in NHS Highland
Get PDFThis thesis examines the potential cost-benefit of the Home and Mobile Health Monitoring (HMHM) programme, which is a telehealth programme for patients with chronic obstructive pulmonary disease (COPD) in NHS Highland. COPD was chosen as it is a common and expensive long-term condition. The HMHM programme could be a solution for better monitoring of COPD if it could provide economic savings for NHS Highland for patients with severe COPD who used the programme to monitor their condition. Mixed methods were used to conduct an economic evaluation. Quantitative and qualitative methods were used to collect costs and benefits data for the economic evaluation through interviews and an online survey with experts on the HMHM programme for COPD patients. Interviews were also used to gather patient perspectives (by proxy) as well as those of clinicians, academics, and service managers, and to ask them to highlight the perceived benefits for the patients, clinicians and NHS Highland. From the interviews, it was found that patients and clinicians are satisfied with the programme. Furthermore, the both the patients and clinicians involved in the programme are reported as having gained various benefits from the programme, for example patients felt satisfied with that programme and also clinicians supported that this programme was less labour intensive. The challenges of implementing the programme in NHS Highland and Scotland and more generally of measuring the costs and benefits of the HMHM programme were explored. Some of these challenges include the difficulty to persuade patients to use their mobile phone for texting, another was that the NHS do not have actual proof that the programme works, and other challenge was that the participants were not representable of the whole COPD population as they had at least one hospital admission. This thesis found that the HMHM programme is a beneficial solution for the NHS, as it enabled the NHS to achieve estimated cost savings of £8,819.55 for the group of people who used the HMHM programme in NHS Highland. Interventions such as the HMHM programme can help patients who have severe long-term conditions to have better control of their disease and to be more independent, while the NHS can achieve cost savings because of the reduced need for hospitalisation from acute exacerbations This thesis has demonstrated that while challenges still exist around properly measuring the costs and benefits of telehealth it is possible that the HMHM programme worked and provide a cost-effective solution for the NHS. The contribution of this thesis was the cost benefit analysis that is an economic evaluation method which is not used very often because of the limitations that they face. The CBA is a valuable method why indicate in monetary units whether it worth it or not to do an intervention.This thesis examines the potential cost-benefit of the Home and Mobile Health Monitoring (HMHM) programme, which is a telehealth programme for patients with chronic obstructive pulmonary disease (COPD) in NHS Highland. COPD was chosen as it is a common and expensive long-term condition. The HMHM programme could be a solution for better monitoring of COPD if it could provide economic savings for NHS Highland for patients with severe COPD who used the programme to monitor their condition. Mixed methods were used to conduct an economic evaluation. Quantitative and qualitative methods were used to collect costs and benefits data for the economic evaluation through interviews and an online survey with experts on the HMHM programme for COPD patients. Interviews were also used to gather patient perspectives (by proxy) as well as those of clinicians, academics, and service managers, and to ask them to highlight the perceived benefits for the patients, clinicians and NHS Highland. From the interviews, it was found that patients and clinicians are satisfied with the programme. Furthermore, the both the patients and clinicians involved in the programme are reported as having gained various benefits from the programme, for example patients felt satisfied with that programme and also clinicians supported that this programme was less labour intensive. The challenges of implementing the programme in NHS Highland and Scotland and more generally of measuring the costs and benefits of the HMHM programme were explored. Some of these challenges include the difficulty to persuade patients to use their mobile phone for texting, another was that the NHS do not have actual proof that the programme works, and other challenge was that the participants were not representable of the whole COPD population as they had at least one hospital admission. This thesis found that the HMHM programme is a beneficial solution for the NHS, as it enabled the NHS to achieve estimated cost savings of £8,819.55 for the group of people who used the HMHM programme in NHS Highland. Interventions such as the HMHM programme can help patients who have severe long-term conditions to have better control of their disease and to be more independent, while the NHS can achieve cost savings because of the reduced need for hospitalisation from acute exacerbations This thesis has demonstrated that while challenges still exist around properly measuring the costs and benefits of telehealth it is possible that the HMHM programme worked and provide a cost-effective solution for the NHS. The contribution of this thesis was the cost benefit analysis that is an economic evaluation method which is not used very often because of the limitations that they face. The CBA is a valuable method why indicate in monetary units whether it worth it or not to do an intervention
Control and operation of HVDC connected offshore windfarm with particular emphasis on faults and black start
Get PDFHigh voltage direct current (HVDC) technology has been identified as a preferred choice for long-distance offshore wind power transmission. However, compared with conventional onshore networks, the dynamic behaviour and operation of power electronic based offshore network is significantly different, especially during offshore grid disturbances. Thus, to ensure a secure and reliable power transmission, this thesis investigates the different fault characteristics of HVDC connected offshore windfarm systems and proposes several fault rides through control and system recovery schemes.;The first topic discussed in this thesis is the offshore AC fault ride through operation. When modular multilevel converter (MMC) based HVDC connection is used for offshore windfarm system, the responses of both the offshore MMC station and wind turbine (WT) converters need to be carefully designed to ensure their safety operation during offshore AC faults. Maintain balanced and controlled current contribution to offshore AC grid during asymmetrical AC fault is possible, but it has several drawbacks such as increased risk of protection failure due to the absence of sufficient fault currents, and the inability of post-fault AC voltage recovery. Therefore, based on a detailed sequence network analysis, an enhanced control strategy is proposed during offshore asymmetrical faults to exploit the induced negative sequence and zero sequence voltages to facilitate controlled injection of negative sequence current while avoiding excessive overvoltage in the healthy phases. By adopting the proposed control, the AC fault current can be well regulated and the voltage restoration after fault clearance can be achieved as demonstrated by detailed simulation studies.;After the evaluation of offshore AC faults, the second research topic of this thesis moves to the offshore DC fault ride through operation. In a multi-terminal DC (MTDC) grid that connects multiple offshore windfarms, continued operation in an effort to retain large proportion of power transfer during a DC fault is very important for critical power corridors. Partially selective protection which only installs fast acting DC circuit breakers (DCCBs) in limited cable locations while the main protection uses cheap DC disconnectors and AC circuit breakers (ACCBs), is a cost-effective solution. However, such protection scheme requires significant modifications to WTs control in order to retain the offshore AC network to ensure fast system recovery after fault isolation. Detailed analysis reveals that the sudden MMC blocking or opening of ACCBs due to the DC fault clearance can cause significant over-voltage and over-frequency in the offshore AC grid, which could necessitate immediate shutdown of the wind farm and damage the offshore infrastructure. To tackle these issues, an enhanced control for wind turbine (WT) converters is proposed to facilitate seamless transition of the WT converters between grid following and forming modes to maintain the offshore AC grid stable when the control from the offshore MMC is lost. The viability of the proposed control is demonstrated in wider context of partially selective DC fault protection in a meshed DC grid. The proposed control method ensures the continuous control of the offshore AC networks and enables the fast power transfer restoration.;Finally, a black start service aiming to support the onshore power networks restoration provided by the diode rectifier (DR) based HVDC connected windfarm is studied. A new frequency-AC voltage (f-V) droop control of WT converters is proposed to dynamically regulate the offshore AC voltage to ensure the DC voltage of the DR-HVDC link remains in the safe range when the active power consumption by the onshore network varies during black start. The detailed sequential black start is demonstrated, including DR-HVDC link energization, onshore AC voltage build-up and load pick up. Comprehensive simulation results confirm the validity of the proposed black start scheme using DR-HVDC connected offshore wind farms.High voltage direct current (HVDC) technology has been identified as a preferred choice for long-distance offshore wind power transmission. However, compared with conventional onshore networks, the dynamic behaviour and operation of power electronic based offshore network is significantly different, especially during offshore grid disturbances. Thus, to ensure a secure and reliable power transmission, this thesis investigates the different fault characteristics of HVDC connected offshore windfarm systems and proposes several fault rides through control and system recovery schemes.;The first topic discussed in this thesis is the offshore AC fault ride through operation. When modular multilevel converter (MMC) based HVDC connection is used for offshore windfarm system, the responses of both the offshore MMC station and wind turbine (WT) converters need to be carefully designed to ensure their safety operation during offshore AC faults. Maintain balanced and controlled current contribution to offshore AC grid during asymmetrical AC fault is possible, but it has several drawbacks such as increased risk of protection failure due to the absence of sufficient fault currents, and the inability of post-fault AC voltage recovery. Therefore, based on a detailed sequence network analysis, an enhanced control strategy is proposed during offshore asymmetrical faults to exploit the induced negative sequence and zero sequence voltages to facilitate controlled injection of negative sequence current while avoiding excessive overvoltage in the healthy phases. By adopting the proposed control, the AC fault current can be well regulated and the voltage restoration after fault clearance can be achieved as demonstrated by detailed simulation studies.;After the evaluation of offshore AC faults, the second research topic of this thesis moves to the offshore DC fault ride through operation. In a multi-terminal DC (MTDC) grid that connects multiple offshore windfarms, continued operation in an effort to retain large proportion of power transfer during a DC fault is very important for critical power corridors. Partially selective protection which only installs fast acting DC circuit breakers (DCCBs) in limited cable locations while the main protection uses cheap DC disconnectors and AC circuit breakers (ACCBs), is a cost-effective solution. However, such protection scheme requires significant modifications to WTs control in order to retain the offshore AC network to ensure fast system recovery after fault isolation. Detailed analysis reveals that the sudden MMC blocking or opening of ACCBs due to the DC fault clearance can cause significant over-voltage and over-frequency in the offshore AC grid, which could necessitate immediate shutdown of the wind farm and damage the offshore infrastructure. To tackle these issues, an enhanced control for wind turbine (WT) converters is proposed to facilitate seamless transition of the WT converters between grid following and forming modes to maintain the offshore AC grid stable when the control from the offshore MMC is lost. The viability of the proposed control is demonstrated in wider context of partially selective DC fault protection in a meshed DC grid. The proposed control method ensures the continuous control of the offshore AC networks and enables the fast power transfer restoration.;Finally, a black start service aiming to support the onshore power networks restoration provided by the diode rectifier (DR) based HVDC connected windfarm is studied. A new frequency-AC voltage (f-V) droop control of WT converters is proposed to dynamically regulate the offshore AC voltage to ensure the DC voltage of the DR-HVDC link remains in the safe range when the active power consumption by the onshore network varies during black start. The detailed sequential black start is demonstrated, including DR-HVDC link energization, onshore AC voltage build-up and load pick up. Comprehensive simulation results confirm the validity of the proposed black start scheme using DR-HVDC connected offshore wind farms
Enhanced iridium complexes for amino acid and peptide isotope labelling processes
No full textOver the last decade, the number of new chemical entities approved as drugs within the
pharmaceutical industry has greatly increased. Although this may seem promising, the
attrition rate remains obtusely high, posing a major issue for pharmaceutical drug
development. In an attempt to combat these problems, metabolism studies are utilised much
earlier in the drug discovery process, to enable the identification of potential issues before a
candidate is entered into expensive pre-clinical or clinical trials. The use of heavy isotopes to
label drug candidates play a central role in metabolism studies and as such methods of
synthesising these are incredibly useful. Hydrogen isotopes are often utilised for this purpose,
and are often introduced via hydrogen isotope exchange (HIE).
Iridium has adopted a central role in HIE processes, and a large library of iridium(I) catalysts
have been developed within the Kerr group for the efficient ortho-labelling of a large array of
aromatic compounds. Iridium catalysed HIE utilises a directing group within a molecule,
meaning a large range of functionality can be employed. The Kerr group have presented an
impressive advancement within the area of HIE, with efficient catalysts under mild
conditions and high levels of labelling, however, labelling of sp3
-rich, and more biologically
relevant, molecules remains in its infancy.
More and more peptides are emerging on the market as therapeutics, providing a ‘sweet’ spot
between small molecules and large biologics. Therefore, it is imperative that such molecules
can also be istopically labelled to allow metabolism studies much like their small molecule
counterparts. In a similar vein, amino acids, the building blocks of peptide molecules, also
represent an important class of molecules to be labelled.
This report describes development of a method to label amino acid and small peptide
substrates under iridium(I) catalysis, with high incorporations observed under mild
conditions. Isotopic labelling of peptides on solid resin support has been investigated in an
attempt to combat the solubility issues associated with these HIE substrates. In addition,
Density Functional Theory (DFT) studies have been utilised to design new Ir(I) catalysts,
targeted for the labelling of more complex amino acid and peptide motifs, which are, to date,
significantly more challenging.Over the last decade, the number of new chemical entities approved as drugs within the
pharmaceutical industry has greatly increased. Although this may seem promising, the
attrition rate remains obtusely high, posing a major issue for pharmaceutical drug
development. In an attempt to combat these problems, metabolism studies are utilised much
earlier in the drug discovery process, to enable the identification of potential issues before a
candidate is entered into expensive pre-clinical or clinical trials. The use of heavy isotopes to
label drug candidates play a central role in metabolism studies and as such methods of
synthesising these are incredibly useful. Hydrogen isotopes are often utilised for this purpose,
and are often introduced via hydrogen isotope exchange (HIE).
Iridium has adopted a central role in HIE processes, and a large library of iridium(I) catalysts
have been developed within the Kerr group for the efficient ortho-labelling of a large array of
aromatic compounds. Iridium catalysed HIE utilises a directing group within a molecule,
meaning a large range of functionality can be employed. The Kerr group have presented an
impressive advancement within the area of HIE, with efficient catalysts under mild
conditions and high levels of labelling, however, labelling of sp3
-rich, and more biologically
relevant, molecules remains in its infancy.
More and more peptides are emerging on the market as therapeutics, providing a ‘sweet’ spot
between small molecules and large biologics. Therefore, it is imperative that such molecules
can also be istopically labelled to allow metabolism studies much like their small molecule
counterparts. In a similar vein, amino acids, the building blocks of peptide molecules, also
represent an important class of molecules to be labelled.
This report describes development of a method to label amino acid and small peptide
substrates under iridium(I) catalysis, with high incorporations observed under mild
conditions. Isotopic labelling of peptides on solid resin support has been investigated in an
attempt to combat the solubility issues associated with these HIE substrates. In addition,
Density Functional Theory (DFT) studies have been utilised to design new Ir(I) catalysts,
targeted for the labelling of more complex amino acid and peptide motifs, which are, to date,
significantly more challenging
Dynamics in many-body quantum systems with long-range interactions
Get PDFThe ability to realise quantum simulation experimentally at extremely low temperature provides the capability to microscopically control macroscopic quantum phenomena. The control over cold atoms in optical lattices offers an excellent platform to study the out-of-equilibrium behaviour of strongly correlated systems, especially spin physics that can be realised with multicomponent gases. In this field a major ambition is to observe sensitive many-body phenomena such as quantum magnetism. This thesis contains theoretical and numerical studies of many-body dynamical phenomena of spin models with two-component bosonic atoms in optical lattices. Firstly, beginning from a state with all effective magnetic spins in the same direction, we investigate dynamics of spin-spin correlations, and how they behave for different spin models.;Most of the results explored in this thesis use reduced Hilbert space techniques, basedon the Density Matrix Renormalisation Group, and the representation of Matrix Product States and Matrix Product Operators. Using numerical methods in 1D we compute non-equilibrium dynamics, ground states, and thermal states for these systems. We also study and compare their behaviour in terms of spin correlation functions and induced currents. We find in some cases, where the current is non-decaying for the ground state, a decay for the rotated state with time, since the decay of the long-range correlations becomes important. Furthermore, we explore changes that occur when we add long range interactions to the models, and analyse how the correlations can be affected by the presence of disorder. We found that in the regime of short and intermediate range interactions, the correlations are affected by the disorder, whereas these effects were suppressed for long-range interactions. One of the challenges in ongoing experiments remains reaching the low temperatures/entropies necessary for some particularly sensitive interacting states.;We investigate the magnetically ordered quantum states that can be engineered in these two-species bosonic models, studying techniques to prepare states with a very low entropy using a diabatic and near-adiabatic protocols. We compute the corresponding dynamics, modelling these techniques for realistic experimental parameters. We also show how the same models can give rise to entanglement that is potentially useful for quantum enhanced metrology, and characterise the states we can prepare in terms of their Quantum Fisher Information. Lastly, we analyse the effect of dissipation in these models. Our results provide an interesting experimental perspective to probe the difference between mean-field spin states and the true ground states for effective spin models. In summary, our studies offer innovative new results to study spin models in optical lattices, which should be feasible with current experimental techniques.The ability to realise quantum simulation experimentally at extremely low temperature provides the capability to microscopically control macroscopic quantum phenomena. The control over cold atoms in optical lattices offers an excellent platform to study the out-of-equilibrium behaviour of strongly correlated systems, especially spin physics that can be realised with multicomponent gases. In this field a major ambition is to observe sensitive many-body phenomena such as quantum magnetism. This thesis contains theoretical and numerical studies of many-body dynamical phenomena of spin models with two-component bosonic atoms in optical lattices. Firstly, beginning from a state with all effective magnetic spins in the same direction, we investigate dynamics of spin-spin correlations, and how they behave for different spin models.;Most of the results explored in this thesis use reduced Hilbert space techniques, basedon the Density Matrix Renormalisation Group, and the representation of Matrix Product States and Matrix Product Operators. Using numerical methods in 1D we compute non-equilibrium dynamics, ground states, and thermal states for these systems. We also study and compare their behaviour in terms of spin correlation functions and induced currents. We find in some cases, where the current is non-decaying for the ground state, a decay for the rotated state with time, since the decay of the long-range correlations becomes important. Furthermore, we explore changes that occur when we add long range interactions to the models, and analyse how the correlations can be affected by the presence of disorder. We found that in the regime of short and intermediate range interactions, the correlations are affected by the disorder, whereas these effects were suppressed for long-range interactions. One of the challenges in ongoing experiments remains reaching the low temperatures/entropies necessary for some particularly sensitive interacting states.;We investigate the magnetically ordered quantum states that can be engineered in these two-species bosonic models, studying techniques to prepare states with a very low entropy using a diabatic and near-adiabatic protocols. We compute the corresponding dynamics, modelling these techniques for realistic experimental parameters. We also show how the same models can give rise to entanglement that is potentially useful for quantum enhanced metrology, and characterise the states we can prepare in terms of their Quantum Fisher Information. Lastly, we analyse the effect of dissipation in these models. Our results provide an interesting experimental perspective to probe the difference between mean-field spin states and the true ground states for effective spin models. In summary, our studies offer innovative new results to study spin models in optical lattices, which should be feasible with current experimental techniques
On the impacts of climate change on water resources, lessons from the River Nith Catchment and Shire River Basin
Get PDFOne of the most complex and challenging problems faced by the world today is that of water scarcity which has been recognized as a global risk. According to experts, freshwater scarcity affects close to two-thirds of the world's population at least one month of the year while half a billion people are estimated to be living under water scarcity throughout the year. Climate change, population growth, increased reliance on irrigated agriculture and changes in land-use threaten to exacerbate water scarcity risk. In recent decades, solutions to these challenges and threats have been proposed through various interventions such as the Millennium Development and Sustainable Development Goals (MDGs and SDGs respectively).;Responsible management of water systems and resources entails having a thorough understanding of the quantity and quality of these resources. Researchers have used simplistic 1-dimensional models to complex semi-distributed models to understand how water systems such as lakes, rivers and entire basins are replenished. However, most studies have focussed on only one aspect of the hydrologic cycle when quantifying freshwater resources. In the past decade or so, the issue of integrated hydrologic modelling (IHM) where surface and groundwater is modelled as an integrated unit has gained traction in the research community.;More recently, it has become fashionable to couple integrated hydrologic models coupled with atmospheric models to account for climate change. Notwithstanding this development, there is still no unified and systematic methodology and/or framework that has been adopted by the water research community for integrated hydrologic modelling. This, coupled with the challenge of filtering through the many spatial climate data products offered by the climate research centres, makes the task all the more challenging. This has led to a slow adoption of these models by the water resources community.;This thesis applies integrated hydrologic models (SWAT-MODFLOW) coupled with atmospheric models to two watersheds (River Nith Catchment and Shire RiverBasin) from different climatic settings to determine the quantity and availability of future water resources. The River Nith Catchment (RNC) is located in South-West Scotland, UK while the Shire River Basin (SRB) is located in Southern Malawi. Downscaling of Global Circulation Models (GCMs) that were used to force the integrated hydrologic models was done using the quantile mapping method. Six GCMs and a total of thirty-six climate scenarios and hydrological models under RCP4.5 and RCP8.5 were developed for the SRB while five GCMs and a total of thirty climate and hydrological models under RCP4.5 and RCP8.5 were developed for the RNC. In total, sixty-six models were developed for the two study are as encompassing climate change and variability analyses, surface-water modelling and groundwater recharge modelling. The methodology was found to be applicable in both temperate and semi-arid climates.;This thesis documents methods that can be used to model climate change impacts on groundwater resources using a multi-GCM and integrated hydrologic modelling approach using freely available data and tools within an Integrated Water Resources Management (IWRM) framework. It is the hope of the authorthat these tools and methodologies will be adopted by the wider IWRM community in an effort to meet Sustainable Development Goal number 6 (SDG 6) by 2030. The contribution to research of this thesis can be viewed from four perspectives. Firstly, a novel method for GCM subset selection incorporating Symmetrical Uncertainty (SU), Probability Density Function (PDF) ranking and the Random Forest Algorithm was developed.;Secondly, this is the first time such a model has been applied for future water resources quantification in both the RNC and SRB. Thirdly, this work has demonstrated that it is possible to do high quality predictive hydrological modelling that can be incorporated into climate adaptability planning using freely available remotely-sensed climate data. Fourthly, the methodology developed in this thesis provides a basis for a unified framework (i.e. software tools adopted in this work including related software) and methodology for integrated hydrologic modelling that can be applied in different climatic settings using freely available hydro-climatic data products.One of the most complex and challenging problems faced by the world today is that of water scarcity which has been recognized as a global risk. According to experts, freshwater scarcity affects close to two-thirds of the world's population at least one month of the year while half a billion people are estimated to be living under water scarcity throughout the year. Climate change, population growth, increased reliance on irrigated agriculture and changes in land-use threaten to exacerbate water scarcity risk. In recent decades, solutions to these challenges and threats have been proposed through various interventions such as the Millennium Development and Sustainable Development Goals (MDGs and SDGs respectively).;Responsible management of water systems and resources entails having a thorough understanding of the quantity and quality of these resources. Researchers have used simplistic 1-dimensional models to complex semi-distributed models to understand how water systems such as lakes, rivers and entire basins are replenished. However, most studies have focussed on only one aspect of the hydrologic cycle when quantifying freshwater resources. In the past decade or so, the issue of integrated hydrologic modelling (IHM) where surface and groundwater is modelled as an integrated unit has gained traction in the research community.;More recently, it has become fashionable to couple integrated hydrologic models coupled with atmospheric models to account for climate change. Notwithstanding this development, there is still no unified and systematic methodology and/or framework that has been adopted by the water research community for integrated hydrologic modelling. This, coupled with the challenge of filtering through the many spatial climate data products offered by the climate research centres, makes the task all the more challenging. This has led to a slow adoption of these models by the water resources community.;This thesis applies integrated hydrologic models (SWAT-MODFLOW) coupled with atmospheric models to two watersheds (River Nith Catchment and Shire RiverBasin) from different climatic settings to determine the quantity and availability of future water resources. The River Nith Catchment (RNC) is located in South-West Scotland, UK while the Shire River Basin (SRB) is located in Southern Malawi. Downscaling of Global Circulation Models (GCMs) that were used to force the integrated hydrologic models was done using the quantile mapping method. Six GCMs and a total of thirty-six climate scenarios and hydrological models under RCP4.5 and RCP8.5 were developed for the SRB while five GCMs and a total of thirty climate and hydrological models under RCP4.5 and RCP8.5 were developed for the RNC. In total, sixty-six models were developed for the two study are as encompassing climate change and variability analyses, surface-water modelling and groundwater recharge modelling. The methodology was found to be applicable in both temperate and semi-arid climates.;This thesis documents methods that can be used to model climate change impacts on groundwater resources using a multi-GCM and integrated hydrologic modelling approach using freely available data and tools within an Integrated Water Resources Management (IWRM) framework. It is the hope of the authorthat these tools and methodologies will be adopted by the wider IWRM community in an effort to meet Sustainable Development Goal number 6 (SDG 6) by 2030. The contribution to research of this thesis can be viewed from four perspectives. Firstly, a novel method for GCM subset selection incorporating Symmetrical Uncertainty (SU), Probability Density Function (PDF) ranking and the Random Forest Algorithm was developed.;Secondly, this is the first time such a model has been applied for future water resources quantification in both the RNC and SRB. Thirdly, this work has demonstrated that it is possible to do high quality predictive hydrological modelling that can be incorporated into climate adaptability planning using freely available remotely-sensed climate data. Fourthly, the methodology developed in this thesis provides a basis for a unified framework (i.e. software tools adopted in this work including related software) and methodology for integrated hydrologic modelling that can be applied in different climatic settings using freely available hydro-climatic data products
Mixed formulations for the convection-diffusion equation
Get PDFThis thesis explores the numerical stability of the stationary Convection-Diffusion-Reaction (CDR) equation in mixed form, where the second-order equation is expressed as two first-order equations using a second variable relating to a derivative of the primary variable. This first-order system uses either a total or diffusive flux formulation. Westart by numerically testing the unstabilised Douglas and Roberts classical discretisation of the mixed CDR equation using Raviart-Thomas elements. The results indicate that,as expected, for both total and diffusive flux, the stability of the formulation degrades dramatically as diffusion decreases.Next, we investigate stabilised formulations that are designed to improve the ability of the discrete problem to cope with problems containing layers. We test the Masud and Kwack method that uses Lagrangian elements but whose analysis has not been developed.We then significantly modify the formulation to allow us to prove existence of a solution and facilitate the analysis. Our new method, which uses total flux, is then tested for convergence with standard tests and found to converge satisfactorily over a range of values of diffusion.Another family of first-order methods called First-Order System of Least-Squares (FOSLS/LSFEM) is also investigated in relation to solving the CDR equation. These symmetric,elliptic methods do not require stabilisation but also do not cope well with sharp layers and small diffusion. Modifications have been proposed and this study includes aversion of Chen et al. which uses diffusive flux, imposing boundary conditions weakly in a weighted formulation.We test our new method against all the aforementioned methods, but we find that other methods do not cope well with layers in standard tests. Our method compares favourably with the standard Streamline-Upwind-Petrov-Galerkin method (SUPG/SDFEM), but overall is not a significant improvement. With further fine-tuning, our method could improve but it has more computational overhead than SUPG.This thesis explores the numerical stability of the stationary Convection-Diffusion-Reaction (CDR) equation in mixed form, where the second-order equation is expressed as two first-order equations using a second variable relating to a derivative of the primary variable. This first-order system uses either a total or diffusive flux formulation. Westart by numerically testing the unstabilised Douglas and Roberts classical discretisation of the mixed CDR equation using Raviart-Thomas elements. The results indicate that,as expected, for both total and diffusive flux, the stability of the formulation degrades dramatically as diffusion decreases.Next, we investigate stabilised formulations that are designed to improve the ability of the discrete problem to cope with problems containing layers. We test the Masud and Kwack method that uses Lagrangian elements but whose analysis has not been developed.We then significantly modify the formulation to allow us to prove existence of a solution and facilitate the analysis. Our new method, which uses total flux, is then tested for convergence with standard tests and found to converge satisfactorily over a range of values of diffusion.Another family of first-order methods called First-Order System of Least-Squares (FOSLS/LSFEM) is also investigated in relation to solving the CDR equation. These symmetric,elliptic methods do not require stabilisation but also do not cope well with sharp layers and small diffusion. Modifications have been proposed and this study includes aversion of Chen et al. which uses diffusive flux, imposing boundary conditions weakly in a weighted formulation.We test our new method against all the aforementioned methods, but we find that other methods do not cope well with layers in standard tests. Our method compares favourably with the standard Streamline-Upwind-Petrov-Galerkin method (SUPG/SDFEM), but overall is not a significant improvement. With further fine-tuning, our method could improve but it has more computational overhead than SUPG
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