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Movement strategy identification in activities of daily living : a clinical investigation of knee bearings
Get PDFIntroduction: Osteoarthritis is one of the leading causes of disability, and the knee joint is the most commonly affected site in the body. The last resort for treatment of end-stage knee osteoarthritis is total knee arthroplasty surgery. Despite the plethora of implant designs, the current evidence on which bearings give the most natural movement and function is still scarce. Aims: the aim of this study was to compare the functional performance of fixed and mobile bearings, with different degrees of congruency. Methods: participants underwent 3D motion capture analysis during two activities of daily living. Patient participants were recorded before, four to six weeks after, and a year after the operation. Pain and satisfaction levels were also surveyed using bespoke questionnaires and the Oxford knee score. Participants' functional performance was accessed by means of an innovative statistical procedure (i.e. hierarchical clustering), that fruitfully classified movement patterns, and discerned healthy from unhealthy movement behaviours. Results: osteoarthritic participants used different movement strategies compared to healthy individuals. Patient participants' arm and feet behaviour was often categorised as asymmetrical, indicating the presence of compensation mechanisms due to weakness of the affected join. Post-operational behaviour tends to converge to the controls' performance. No differences were observed due to knee implant allocation, or anthropometric characteristics. Questionnaire analysis revealed significant improvement post-operatively in the self-assessment of patient participants, but with no eminent correlation between implant design and outcome measures. Conclusion: the proposed hierarchical clustering procedure managed to adequately, rapidly and reliably evaluate changes in the movement habits of patients after total knee arthroplasty, and access their improvement throughout their rehabilitation process.Introduction: Osteoarthritis is one of the leading causes of disability, and the knee joint is the most commonly affected site in the body. The last resort for treatment of end-stage knee osteoarthritis is total knee arthroplasty surgery. Despite the plethora of implant designs, the current evidence on which bearings give the most natural movement and function is still scarce. Aims: the aim of this study was to compare the functional performance of fixed and mobile bearings, with different degrees of congruency. Methods: participants underwent 3D motion capture analysis during two activities of daily living. Patient participants were recorded before, four to six weeks after, and a year after the operation. Pain and satisfaction levels were also surveyed using bespoke questionnaires and the Oxford knee score. Participants' functional performance was accessed by means of an innovative statistical procedure (i.e. hierarchical clustering), that fruitfully classified movement patterns, and discerned healthy from unhealthy movement behaviours. Results: osteoarthritic participants used different movement strategies compared to healthy individuals. Patient participants' arm and feet behaviour was often categorised as asymmetrical, indicating the presence of compensation mechanisms due to weakness of the affected join. Post-operational behaviour tends to converge to the controls' performance. No differences were observed due to knee implant allocation, or anthropometric characteristics. Questionnaire analysis revealed significant improvement post-operatively in the self-assessment of patient participants, but with no eminent correlation between implant design and outcome measures. Conclusion: the proposed hierarchical clustering procedure managed to adequately, rapidly and reliably evaluate changes in the movement habits of patients after total knee arthroplasty, and access their improvement throughout their rehabilitation process
Development of an innovative business-oriented probability-based maintenance (BOPM) methodology for ship machinery systems
Get PDFThroughout the maritime industry, there has been relatively high number of shipping-related incidents. Therefore, numerous international, local and Classification Society based legislations have been developed in order to regulate shipping and reduce accidents. These policies not only dictate ship design methodologies but also inspection and maintenance activities of vessels. These policies on inspection and maintenance have generally increased the cost of shipping in the world. As a result, there has been substantial research on the risk and cost aspects of maintenance in the maritime industry. However, no research has put emphasised risk and technical aspects of maintenance with the business and cost related aspects of maintenance in one unified platform. Therefore, this PhD has developed an overall methodology in order to combine cost and business oriented aspects of a shipping company with their risk and technical aspects. This methodology is called Business Oriented Probability-based Maintenance (BOPM). In this methodology, company business aspects and Maintenance Performance Indicators (MPIs) have been used to modify and personalise maintenance and repair cost values, risk factors (human risk, environmental risk, cost of failure and loss of operation), and component/sub-system performance reading limits. Performance limits from OEM reports modified by company specific inputs are then used to determine probabilistic performance values based on the monitored live values received from vessels. Subsequently, these probabilistic values are placed in a Probabilistic Analysis Unit (PAU) within the BOPM platform to predict the future performance values for each component/sub-system within the system. This PAU model uses an innovative Dynamic Bayesian Network (DBN) with first order Markov Chains to predict the future probabilistic pattern of each system monitored from the vessel. Afterward, net cost analysis is performed using cost values modified by company MPIs inside utility and decision nodes added to the DBN model in order to provide cost-based decisions on the performance of each component and schedule specific maintenance or repair dates if required. In the other section of the BOPM risk values are combined with their probability of failure using a Fuzzy Set Theory (FST) in order to determine a final relevant risk value for each component/sub-system. Finally, obtained risk values are combined with decisions from the cost-based DBN Decision Analysis Unit (DAU) to prioritise tasks that are intervening with each other. The overall methodology was approved and validated by both industrial experts and using results and conclusions made from the INCASS EU FP7 project that I was also involved in. Three similar systems from three vessels have been used as the case studies in order to analyse the effectiveness of the BOPM platform and validate its results. These vessels are two chemical tanker sister ships and one general cargo vessel. Three similar system types from each vessel have been used namely the Lub-oil system, Fuel-oil system and Turbocharger. Having two sister ships operating in different environments has also created the possibility of evaluating the effects of environmenton performance of each system. Using the overall BOPM analysis platform, relative probabilistic performance and availability of all the sub-systems/components within the main observed systems were predicted for four future time slices. This was then compared with actual observed performance value and it was noted that the overall methodology has an accuracy of 97.8%. Subsequently, using the decision-making part of the methodology, future maintenance tasks were recommended. This was then compared with the maintenance logs of all three vessels and it was observed that they were not simply matching but also exceeding their recommendations and saving the company an extra {dollar}467. Finally, the results obtained also proved that the overall results and scope of the thesis have helped to meet and exceed the overall goals and targets of the company. Keywords: Business-oriented Probability-based Maintenance (BOPM), Dynamic Bayesian Network (DBN), Markov Chain, Net cost analysis, Decision-making, Risk factors, Maintenance Performance Indicators (MPIs), Technical and business aspectsThroughout the maritime industry, there has been relatively high number of shipping-related incidents. Therefore, numerous international, local and Classification Society based legislations have been developed in order to regulate shipping and reduce accidents. These policies not only dictate ship design methodologies but also inspection and maintenance activities of vessels. These policies on inspection and maintenance have generally increased the cost of shipping in the world. As a result, there has been substantial research on the risk and cost aspects of maintenance in the maritime industry. However, no research has put emphasised risk and technical aspects of maintenance with the business and cost related aspects of maintenance in one unified platform. Therefore, this PhD has developed an overall methodology in order to combine cost and business oriented aspects of a shipping company with their risk and technical aspects. This methodology is called Business Oriented Probability-based Maintenance (BOPM). In this methodology, company business aspects and Maintenance Performance Indicators (MPIs) have been used to modify and personalise maintenance and repair cost values, risk factors (human risk, environmental risk, cost of failure and loss of operation), and component/sub-system performance reading limits. Performance limits from OEM reports modified by company specific inputs are then used to determine probabilistic performance values based on the monitored live values received from vessels. Subsequently, these probabilistic values are placed in a Probabilistic Analysis Unit (PAU) within the BOPM platform to predict the future performance values for each component/sub-system within the system. This PAU model uses an innovative Dynamic Bayesian Network (DBN) with first order Markov Chains to predict the future probabilistic pattern of each system monitored from the vessel. Afterward, net cost analysis is performed using cost values modified by company MPIs inside utility and decision nodes added to the DBN model in order to provide cost-based decisions on the performance of each component and schedule specific maintenance or repair dates if required. In the other section of the BOPM risk values are combined with their probability of failure using a Fuzzy Set Theory (FST) in order to determine a final relevant risk value for each component/sub-system. Finally, obtained risk values are combined with decisions from the cost-based DBN Decision Analysis Unit (DAU) to prioritise tasks that are intervening with each other. The overall methodology was approved and validated by both industrial experts and using results and conclusions made from the INCASS EU FP7 project that I was also involved in. Three similar systems from three vessels have been used as the case studies in order to analyse the effectiveness of the BOPM platform and validate its results. These vessels are two chemical tanker sister ships and one general cargo vessel. Three similar system types from each vessel have been used namely the Lub-oil system, Fuel-oil system and Turbocharger. Having two sister ships operating in different environments has also created the possibility of evaluating the effects of environmenton performance of each system. Using the overall BOPM analysis platform, relative probabilistic performance and availability of all the sub-systems/components within the main observed systems were predicted for four future time slices. This was then compared with actual observed performance value and it was noted that the overall methodology has an accuracy of 97.8%. Subsequently, using the decision-making part of the methodology, future maintenance tasks were recommended. This was then compared with the maintenance logs of all three vessels and it was observed that they were not simply matching but also exceeding their recommendations and saving the company an extra {dollar}467. Finally, the results obtained also proved that the overall results and scope of the thesis have helped to meet and exceed the overall goals and targets of the company. Keywords: Business-oriented Probability-based Maintenance (BOPM), Dynamic Bayesian Network (DBN), Markov Chain, Net cost analysis, Decision-making, Risk factors, Maintenance Performance Indicators (MPIs), Technical and business aspect
Investigating the impact of strategic brand management on export performance in the B2B context
Get PDFPreviously held under moratorium from 1st July 2018 until 7th July 2025.Despite an upsurge of interest in the potential benefits of Business to Business (B2B)
branding, research in the area within the context of international trade is practically nonexistent. This study focuses attention on B2B strategic brand management in overseas
markets, using data collected from 34 qualitative interviews and a survey of 208 UK
international B2B goods and service suppliers. Drawing on Resource Based Theory (RBT)
and the Structure Conduct Performance (SCP) framework, this study advances previous
models and presents an innovative new framework which positions strategic brand
management as a fundamental deterministic factor in explaining B2B firm performance in
export markets. Findings show certain organisational resources (financial) and capabilities
(market information, branding, marketing planning) are advantageous antecedents to the
employment of superior strategic brand management in foreign markets which, in turn, leads
to increased financial and market performance internationally. The findings also
demonstrate that certain external environmental conditions (macro enabling, micro
precipitating, foreign market competitiveness) can both positively and negatively directly
influence a B2B firmโs strategic brand management which consequently will impact
performance. In addition, there was not found to be a significant positive moderating effect
from Country of Origin (COO) on the influence of superior strategic brand management on
international firm performance.
Keywords: B2B, Strategic Brand Management, International Branding, International
Marketing, Export Performance, Resource Based Theory, Structure Conduct Performance,
Country of Origin.Despite an upsurge of interest in the potential benefits of Business to Business (B2B)
branding, research in the area within the context of international trade is practically nonexistent. This study focuses attention on B2B strategic brand management in overseas
markets, using data collected from 34 qualitative interviews and a survey of 208 UK
international B2B goods and service suppliers. Drawing on Resource Based Theory (RBT)
and the Structure Conduct Performance (SCP) framework, this study advances previous
models and presents an innovative new framework which positions strategic brand
management as a fundamental deterministic factor in explaining B2B firm performance in
export markets. Findings show certain organisational resources (financial) and capabilities
(market information, branding, marketing planning) are advantageous antecedents to the
employment of superior strategic brand management in foreign markets which, in turn, leads
to increased financial and market performance internationally. The findings also
demonstrate that certain external environmental conditions (macro enabling, micro
precipitating, foreign market competitiveness) can both positively and negatively directly
influence a B2B firmโs strategic brand management which consequently will impact
performance. In addition, there was not found to be a significant positive moderating effect
from Country of Origin (COO) on the influence of superior strategic brand management on
international firm performance.
Keywords: B2B, Strategic Brand Management, International Branding, International
Marketing, Export Performance, Resource Based Theory, Structure Conduct Performance,
Country of Origin
Mooring lines analysis and design for wave energy converters
Get PDFSoon, wave energy converters will be anchored in several offshore locations for extended periods of time, where high wave energy exist. These devices moored in such areas experience continuous dynamic loads exerted mainly by colliding waves. Therefore, their mooring system is a fundamental component, which inuences overall performance characteristics through its dynamic behaviour.;The mooring component of wave power devices has been typically analysed and designed by using a simplified static and quasistatic based approach and thus independent from the design of the oating structure dynamics. Given the peculiarities of mooring system design and analysis for wave energy devices, no particular available tools are suitable for analysing and design the mooring component as an integral active part of the entire moored system. All commercial software and codes available are in fact developed by having in mind different mooring requirements.;Through this project, opportunities to improve entire moored system design were investigated. This study aimed to consider the potential option of designing mooring component as an integral dynamic part of the whole wave energy converter system. An overview of relevant existing studies is delineated, and a generic methodology, aiming at analysis and design moored wave energy system based on a fully dynamic approach, is proposed.;For showing on how this can be applied, a particular focus on an Earth-reacting type of wave energy devices is made. Thus, a numerical code capable of analysing the dynamics, and predict performances of specific single tethered Earth-reacting wave energy converters, was developed. Through this code moored devices of any shape under regular or irregular seas' loads can be analysed.;Both frequency-domain and time-domain mathematical formulations of the system considered are resolved by the proposed method. By using the comparison of numerical predictions with experimental data, the numerical code was validated for the specific cases of both, a half submerged and a fully submerged, spherical oaters. The accuracy of the proposed method was quantified.;Results showed that the numerical method proposed is accurate, computationally efficient and well validated by the extensive experimental data, which was beside acquired during this project. Following the validation of the numerical tool, this last was used in two case studies. The outcome of these studies indicated that by using the proposed method, the trade-off between oater's immersion depth and mooring load peaks could be examined so that the optimal system design can be identified.;The main advantage of the developed tool, compared to existing codes, is that this is tailored to the specific case of analysis and design for Earth-reacting wave energy converters. The new generic methodology proposed showed to be useful and suitable for analysing and design wave energy converters by including the mooring system as an integral component.Soon, wave energy converters will be anchored in several offshore locations for extended periods of time, where high wave energy exist. These devices moored in such areas experience continuous dynamic loads exerted mainly by colliding waves. Therefore, their mooring system is a fundamental component, which inuences overall performance characteristics through its dynamic behaviour.;The mooring component of wave power devices has been typically analysed and designed by using a simplified static and quasistatic based approach and thus independent from the design of the oating structure dynamics. Given the peculiarities of mooring system design and analysis for wave energy devices, no particular available tools are suitable for analysing and design the mooring component as an integral active part of the entire moored system. All commercial software and codes available are in fact developed by having in mind different mooring requirements.;Through this project, opportunities to improve entire moored system design were investigated. This study aimed to consider the potential option of designing mooring component as an integral dynamic part of the whole wave energy converter system. An overview of relevant existing studies is delineated, and a generic methodology, aiming at analysis and design moored wave energy system based on a fully dynamic approach, is proposed.;For showing on how this can be applied, a particular focus on an Earth-reacting type of wave energy devices is made. Thus, a numerical code capable of analysing the dynamics, and predict performances of specific single tethered Earth-reacting wave energy converters, was developed. Through this code moored devices of any shape under regular or irregular seas' loads can be analysed.;Both frequency-domain and time-domain mathematical formulations of the system considered are resolved by the proposed method. By using the comparison of numerical predictions with experimental data, the numerical code was validated for the specific cases of both, a half submerged and a fully submerged, spherical oaters. The accuracy of the proposed method was quantified.;Results showed that the numerical method proposed is accurate, computationally efficient and well validated by the extensive experimental data, which was beside acquired during this project. Following the validation of the numerical tool, this last was used in two case studies. The outcome of these studies indicated that by using the proposed method, the trade-off between oater's immersion depth and mooring load peaks could be examined so that the optimal system design can be identified.;The main advantage of the developed tool, compared to existing codes, is that this is tailored to the specific case of analysis and design for Earth-reacting wave energy converters. The new generic methodology proposed showed to be useful and suitable for analysing and design wave energy converters by including the mooring system as an integral component
A comprehensive optimum integrated water resources management approach at a river basin level : application at Diylala river basin in Iraq
Get PDFThis thesis was previously held under moratorium from 7TH FEBRUARY 2019 to 7TH AUGUST 2019.Integrated Water Resources Management (IWRM) was broadly adopted, however nature's complexity, multidisciplinary stakeholders' demands, legislation policy, etc. restrained the success of holistic integration. Recently, Multi-Objectives Evolutionary Algorithms (MOEAs) were presented as a powerful decision making tool to generate a trade-off (or Pareto-front) for complex problems. Even so, problematics may develop in MOEAs for high-dimension problems. Thus, a new MOEA is developed and employed with a novel optimum comprehensive IWRM(OP-IWRM) approach to assemble: water demands, water resources and water control infrastructures for decision making trade-off production. To evaluate the approach pragmatically, Diyala River basin is selected, which has an area about 17000 km2 in central Iraq and two multipurpose dams: Derbendikhan in the north, and Himren in the middle part of the basin. A new methodology of "Epsilon-Dominance-Driven Self-Adaptive Evolutionary Algorithm for Many-Objective Optimization" (ั-DSEA) to address MOEAs' dilemmas is first presented. Three operational management targets are modelled for Derbendikhan dam for initial algorithm's performance assessment incomparison with the state-of-the-art optimization algorithm Borg MOEA.Competitive results achieved by ั-DSEA for the considered problem. Then, long-term ground water exploitation in the middle part of the basin is modelled by three operational management targets with two alternatives of irrigation system, open furrows and drip. The results show sustainable management could be achieved when farms' water demands are reduced by at least 45%. Further, ั-DSEA outperforms Borg MOEA an almost all proposed alternatives. A novel socio-environmental management approach is then developed to improve Himren downstream river environment. Nine multi-sectors' operational targets subjected to two inflows alternatives are formulated. An improvement is evident in downstream river environment, however dam's upstream shed needs to be integrated with the model, including groundwater. The ั-DSEA competitive performance is also endorsed. Finally, a holistic approach including seventeen management targets combining surface and groundwater basin system with more than 1500 decision variables is developed to assess future climate's change, and water monopolizing in upstream region impacts at the river basin environment. The results demonstrate significant crises of upstream development projects on all river basin sectors and environment, even with the use of both surface and groundwater resources. Thus, the government needs to adopt future policy: to set an international agreement for watersharing with Iran for the current River basin, to adopt new irrigation techniques for the existing farms, and to rehabilitate the current water conveyance infrastructures to reduce water losses. This approach could be a gateway to develop a comprehensive sustainable development plan at a country-scale to improve the 17th goals announced by the United Nations, since only limited approaches were developed previously.Integrated Water Resources Management (IWRM) was broadly adopted, however nature's complexity, multidisciplinary stakeholders' demands, legislation policy, etc. restrained the success of holistic integration. Recently, Multi-Objectives Evolutionary Algorithms (MOEAs) were presented as a powerful decision making tool to generate a trade-off (or Pareto-front) for complex problems. Even so, problematics may develop in MOEAs for high-dimension problems. Thus, a new MOEA is developed and employed with a novel optimum comprehensive IWRM(OP-IWRM) approach to assemble: water demands, water resources and water control infrastructures for decision making trade-off production. To evaluate the approach pragmatically, Diyala River basin is selected, which has an area about 17000 km2 in central Iraq and two multipurpose dams: Derbendikhan in the north, and Himren in the middle part of the basin. A new methodology of "Epsilon-Dominance-Driven Self-Adaptive Evolutionary Algorithm for Many-Objective Optimization" (ั-DSEA) to address MOEAs' dilemmas is first presented. Three operational management targets are modelled for Derbendikhan dam for initial algorithm's performance assessment incomparison with the state-of-the-art optimization algorithm Borg MOEA.Competitive results achieved by ั-DSEA for the considered problem. Then, long-term ground water exploitation in the middle part of the basin is modelled by three operational management targets with two alternatives of irrigation system, open furrows and drip. The results show sustainable management could be achieved when farms' water demands are reduced by at least 45%. Further, ั-DSEA outperforms Borg MOEA an almost all proposed alternatives. A novel socio-environmental management approach is then developed to improve Himren downstream river environment. Nine multi-sectors' operational targets subjected to two inflows alternatives are formulated. An improvement is evident in downstream river environment, however dam's upstream shed needs to be integrated with the model, including groundwater. The ั-DSEA competitive performance is also endorsed. Finally, a holistic approach including seventeen management targets combining surface and groundwater basin system with more than 1500 decision variables is developed to assess future climate's change, and water monopolizing in upstream region impacts at the river basin environment. The results demonstrate significant crises of upstream development projects on all river basin sectors and environment, even with the use of both surface and groundwater resources. Thus, the government needs to adopt future policy: to set an international agreement for watersharing with Iran for the current River basin, to adopt new irrigation techniques for the existing farms, and to rehabilitate the current water conveyance infrastructures to reduce water losses. This approach could be a gateway to develop a comprehensive sustainable development plan at a country-scale to improve the 17th goals announced by the United Nations, since only limited approaches were developed previously
Nanoparticulate materials for environmental remediation : adsorption vs. advanced oxidation techniques
Get PDFThis thesis was previously restricted to Strathclyde users only until 27th November 2023.The research presented in this thesis examines the performance of silica-based materials as adsorbents in the remediation of air and water environments alongside conventionally used sorbents. In addition, photocatalytic oxidation (PCO) is investigated as an alternative remediation technique.;The use of mesoporous silica materials, MCM-41 and SBA-15, as sorbents for the removal of volatile organic compounds (VOCs) from indoor air was assessed. SBA-15 was found to possess the best dynamic adsorption capacity; trapping 12.5 ng cm-3 of toluene and was shown to perform better as a scavenger sorbent than the commercially available material, Tenax TA.;A mesoporous titanium dioxide (TiO2) photocatalyst was prepared via a surfactant templated, sol-gel synthesis approach. Optimum photocatalytic activity for the degradation of VOCs required five coatings of TiO2 film on glass bead support material. High photocatalytic activity and long-term performance were demonstrated with respect to the degradation of toluene, ethylbenzene and cumene (96 - 100 %). Reaction intermediates and a possible degradation mechanism were successfully identified. Regeneration proved to be a simple process, achieved by cooling down the system.;The aqueous adsorption of pharmaceuticals or nitrobenzene onto powdered activated carbon (PAC) and silica materials; as-synthesised (As-syn) and calcined (Calc) MCM-41, bioinspired silica (Bio-Si) and iron incorporated Bio-Si (Fe Bio-Si) was assessed. The four target pharmaceuticals in the multi-analyte solution were acetaminophen, caffeine, sulfamethoxazole and carbamazepine. Bio-Si and Fe Bio-Si displayed the lowest adsorption capacities, Calc MCM-41> As-syn MCM-41 > As-syn Bio-Si and Fe Bio-Si > Calc Bio-Si and Fe Bio-Si. Both investigations revealed commercially available PAC to be the dominant sorbent in aqueous adsorption.;Fe Bio-Si, applied as a heterogeneous Fenton catalyst, was shown to be highly effective for the degradation of nitrobenzene exhibiting long-term catalytic activity ~ 95 % and 85 % degradation at pH 3 and 7 respectively, with no loss in performance after 15 successive recycle runs. Furthermore, the catalyst was shown to successfully mineralise pharmaceutical targets at pH 3, reaching 100 % degradation for all compounds after the initial cycle.;Finally, the process of visible-light induced photocatalytic oxidation, using a Fe-TiO2 thin film as a photocatalyst, displayed potential for the degradation of nitrobenzene in aqueous solutions, achieving 49.1 and 54.9 % degradation for 20 and 50 % Fe-TiO2. Where the mesoporous silica materials failed, in large, to compete with commercially available sorbents, the developed PCO systems, for both indoor air and water treatment, excelled and proved to be very simple yet highly effective techniques that could be easily applied industrially for the efficient degradation of organic pollutants.The research presented in this thesis examines the performance of silica-based materials as adsorbents in the remediation of air and water environments alongside conventionally used sorbents. In addition, photocatalytic oxidation (PCO) is investigated as an alternative remediation technique.;The use of mesoporous silica materials, MCM-41 and SBA-15, as sorbents for the removal of volatile organic compounds (VOCs) from indoor air was assessed. SBA-15 was found to possess the best dynamic adsorption capacity; trapping 12.5 ng cm-3 of toluene and was shown to perform better as a scavenger sorbent than the commercially available material, Tenax TA.;A mesoporous titanium dioxide (TiO2) photocatalyst was prepared via a surfactant templated, sol-gel synthesis approach. Optimum photocatalytic activity for the degradation of VOCs required five coatings of TiO2 film on glass bead support material. High photocatalytic activity and long-term performance were demonstrated with respect to the degradation of toluene, ethylbenzene and cumene (96 - 100 %). Reaction intermediates and a possible degradation mechanism were successfully identified. Regeneration proved to be a simple process, achieved by cooling down the system.;The aqueous adsorption of pharmaceuticals or nitrobenzene onto powdered activated carbon (PAC) and silica materials; as-synthesised (As-syn) and calcined (Calc) MCM-41, bioinspired silica (Bio-Si) and iron incorporated Bio-Si (Fe Bio-Si) was assessed. The four target pharmaceuticals in the multi-analyte solution were acetaminophen, caffeine, sulfamethoxazole and carbamazepine. Bio-Si and Fe Bio-Si displayed the lowest adsorption capacities, Calc MCM-41> As-syn MCM-41 > As-syn Bio-Si and Fe Bio-Si > Calc Bio-Si and Fe Bio-Si. Both investigations revealed commercially available PAC to be the dominant sorbent in aqueous adsorption.;Fe Bio-Si, applied as a heterogeneous Fenton catalyst, was shown to be highly effective for the degradation of nitrobenzene exhibiting long-term catalytic activity ~ 95 % and 85 % degradation at pH 3 and 7 respectively, with no loss in performance after 15 successive recycle runs. Furthermore, the catalyst was shown to successfully mineralise pharmaceutical targets at pH 3, reaching 100 % degradation for all compounds after the initial cycle.;Finally, the process of visible-light induced photocatalytic oxidation, using a Fe-TiO2 thin film as a photocatalyst, displayed potential for the degradation of nitrobenzene in aqueous solutions, achieving 49.1 and 54.9 % degradation for 20 and 50 % Fe-TiO2. Where the mesoporous silica materials failed, in large, to compete with commercially available sorbents, the developed PCO systems, for both indoor air and water treatment, excelled and proved to be very simple yet highly effective techniques that could be easily applied industrially for the efficient degradation of organic pollutants
Novel ultrasonic transducers and array designs using self-similar fractal geometries
Get PDFWider operational bandwidth is an important requirement of an ultrasound transducer across many applications. Naturally occurring resonating systems utilise structures containing a range of length scales to produce a broad operating bandwidth. In this work, a novel concept of designing a piezoelectric composite using a fractal geometry is proposed in order to explore the potential of enhancing the operational performance, particularly in terms of transducer bandwidth and sensitivity.Piezoelectric composite configurations were designed using four well-known fractal geometries: Sierpinski Gasket, Sierpinski Carpet, Cantor Set and Cantor Tartan. The fractal composite devices were realised as either 1-3 connectivity or 2-2 connectivity configurations and compared with their corresponding equivalent conventional composite counterpart. Finite element modelling was utilised to design and explore the behaviour of these four fractal composite designs. A single element ultrasound transducer with SG fractal geometry and an ultrasound array with CS fractal geometry were fabricated and importantly, their experimental performance correlated well with the FE predictions.In this study, fractal composites, with a nominal central operating frequency of 1MHz, have been designed and fabricated with improved bandwidth (and in some case, sensitivity also) when compared to equivalent conventional composite devices. Moreover, the enhanced bandwidth is shown to provide higher resolution imaging performance. Overall, the careful selection of different resonant frequencies within a composite structure has been shown to improve operational performance and it is anticipated that this transducer concept will become more prevalent as 3D piezoelectric fabrication processes mature.Wider operational bandwidth is an important requirement of an ultrasound transducer across many applications. Naturally occurring resonating systems utilise structures containing a range of length scales to produce a broad operating bandwidth. In this work, a novel concept of designing a piezoelectric composite using a fractal geometry is proposed in order to explore the potential of enhancing the operational performance, particularly in terms of transducer bandwidth and sensitivity.Piezoelectric composite configurations were designed using four well-known fractal geometries: Sierpinski Gasket, Sierpinski Carpet, Cantor Set and Cantor Tartan. The fractal composite devices were realised as either 1-3 connectivity or 2-2 connectivity configurations and compared with their corresponding equivalent conventional composite counterpart. Finite element modelling was utilised to design and explore the behaviour of these four fractal composite designs. A single element ultrasound transducer with SG fractal geometry and an ultrasound array with CS fractal geometry were fabricated and importantly, their experimental performance correlated well with the FE predictions.In this study, fractal composites, with a nominal central operating frequency of 1MHz, have been designed and fabricated with improved bandwidth (and in some case, sensitivity also) when compared to equivalent conventional composite devices. Moreover, the enhanced bandwidth is shown to provide higher resolution imaging performance. Overall, the careful selection of different resonant frequencies within a composite structure has been shown to improve operational performance and it is anticipated that this transducer concept will become more prevalent as 3D piezoelectric fabrication processes mature
The treatment of bacterial disease of plants by bacteriophage coated nanoparticles
Get PDFBacterial phytopathogens are a recurring issue for agricultural plants.Traditional control measures include copper treatment and use of pesticides and antibiotics. The use of bacteriophages that selectively kill the causative pathogen as an alternative treatment has been delayed by technical difficulties associated with phage stability and deployment methods. In this project, we developed phage-coated nanoparticles for the control of tomato plant soft rot, caused by Pectobacterium carotovorum, as a model system.Scottish crops were used as a source to isolate new bacteriophages,followed by triple isolation of single plaques formed after infection. Using the enrichment technique, that uses bacteria to isolate the virus from a soil sample, twelve potentially different bacteriophages were recovered and fully characterised. All of the phages isolated resemble T7 based on morphology by transmission electron microscopy; consistent with the genomic characterisation, electron microscopy revealed that the phages displayed a morphology characteristic of the Podoviridae. Subsequently, we covalently bound a collection of phages to the surface of different nanoparticles and the capacity of these phage coated nanoparticles to control bacterial plant disease was assessed.This new technology fully retains the antimicrobial capacity of the bacteriophages and enhances its stability, particularly against dehydration,making this technology a potentially good candidate for use of biocontrol agents for crop pathogen treatment.Bacterial phytopathogens are a recurring issue for agricultural plants.Traditional control measures include copper treatment and use of pesticides and antibiotics. The use of bacteriophages that selectively kill the causative pathogen as an alternative treatment has been delayed by technical difficulties associated with phage stability and deployment methods. In this project, we developed phage-coated nanoparticles for the control of tomato plant soft rot, caused by Pectobacterium carotovorum, as a model system.Scottish crops were used as a source to isolate new bacteriophages,followed by triple isolation of single plaques formed after infection. Using the enrichment technique, that uses bacteria to isolate the virus from a soil sample, twelve potentially different bacteriophages were recovered and fully characterised. All of the phages isolated resemble T7 based on morphology by transmission electron microscopy; consistent with the genomic characterisation, electron microscopy revealed that the phages displayed a morphology characteristic of the Podoviridae. Subsequently, we covalently bound a collection of phages to the surface of different nanoparticles and the capacity of these phage coated nanoparticles to control bacterial plant disease was assessed.This new technology fully retains the antimicrobial capacity of the bacteriophages and enhances its stability, particularly against dehydration,making this technology a potentially good candidate for use of biocontrol agents for crop pathogen treatment
Through barrier detection using surface enhanced spatially offset Raman spectroscopy
Get PDFIn the fields of security and biomedical imaging there is a significant need to non-invasively probe through barriers, e.g. plastic, glass or tissue. Raman spectroscopy provides a means to solving this challenge since it provides a unique chemical fingerprint without the need to destroy the sample. In spite of this, conventional Raman can be limited by sample volume and thickness, often failing to probe beneath the surface or through samples obscured by an opaque barrier.;Spatially offset Raman spectroscopy provides a means of overcoming the limitation associated with conventional Raman spectroscopy since it is capable of providing a unique chemical fingerprint of the analyte understudy, even when obscuring barriers such as plastic or tissue are present. Furthermore, by combining the depth penetration benefits of SORS with the signal enhancing capabilities of SERS, SESORS is capable of achieving sample interrogation at even greater depth.;Therefore, the focus of this research is to probe through barriers, specifically plastic and tissue, using both handheld CR and SORS instruments. The ability of both techniques to detect Raman and SERS analytes through barriers is explored and compared for applications involving security and biomedicine.;The use of conventional Raman and SORS to detect ethanol through varying thicknesses of plastic is investigated. Raman signals from an ethanol solution through plastic was detected through thicknesses of up to 21 mm using SORS in combination with multivariate analysis. SORS was compared to conventional Raman, where through barrier detection of ethanol took place through depths up to 9 mm.;Using a handheld SORS spectrometer, the detection of ex vivo breast cancer tumour models containing SERRS active nanotags through 15 mm of porcine tissue is demonstrated. In addition, SERRS-active nanotags were tracked through porcine tissue to depths of up to 25 mm. To date, this is the largest thickness that SERRS nanotags have been tracked through using a backscattering approach.;This unprecedented performance is due to the use of red-shifted chalcogenpyrylium-based Raman reporters to demonstrate the novel technique of surface enhanced spatially offset resonance Raman spectroscopy (SESORRS) for the first time. The same ex vivo tumour models are also used to demonstrate a multiplexed imaging system through depths of 10 mm using back scattering SESORRS.;The benefit of using red-shifted chalcogenpyrylium based Raman reporters for probing through large thicknesses of plastic and tissue barriers using SERS is also highlighted. Raman signals were collected from SERRS active nanotags through plastic thicknesses of up to 20 mm. The detection of SERRS-active nanotags taken up into ex vivo tumour models through depths of 5 mm of tissue is also shown.;The advantages of applying multivariate analysis for through barrier detection when discriminating analytes with similar spectral features as the barrier is also clearly demonstrated.;Finally, resonant chalcogenpyrylium nanotags were used to demonstrate the benefit of using a resonant Raman reporter for superior low-level limits of detection using SESORS. Nanotags containing chalcogenpyrylium dye were observed at concentrations as low as 1 pM through 5 mm of tissue. This is compared to the non-resonant small molecule Raman reporter BPE which could only be detected at concentrations of 11 pM.;Calculated limits of detection suggest that these SERRS nanotags can be detected at concentrations as low as 104 fM using SESORRS.In the fields of security and biomedical imaging there is a significant need to non-invasively probe through barriers, e.g. plastic, glass or tissue. Raman spectroscopy provides a means to solving this challenge since it provides a unique chemical fingerprint without the need to destroy the sample. In spite of this, conventional Raman can be limited by sample volume and thickness, often failing to probe beneath the surface or through samples obscured by an opaque barrier.;Spatially offset Raman spectroscopy provides a means of overcoming the limitation associated with conventional Raman spectroscopy since it is capable of providing a unique chemical fingerprint of the analyte understudy, even when obscuring barriers such as plastic or tissue are present. Furthermore, by combining the depth penetration benefits of SORS with the signal enhancing capabilities of SERS, SESORS is capable of achieving sample interrogation at even greater depth.;Therefore, the focus of this research is to probe through barriers, specifically plastic and tissue, using both handheld CR and SORS instruments. The ability of both techniques to detect Raman and SERS analytes through barriers is explored and compared for applications involving security and biomedicine.;The use of conventional Raman and SORS to detect ethanol through varying thicknesses of plastic is investigated. Raman signals from an ethanol solution through plastic was detected through thicknesses of up to 21 mm using SORS in combination with multivariate analysis. SORS was compared to conventional Raman, where through barrier detection of ethanol took place through depths up to 9 mm.;Using a handheld SORS spectrometer, the detection of ex vivo breast cancer tumour models containing SERRS active nanotags through 15 mm of porcine tissue is demonstrated. In addition, SERRS-active nanotags were tracked through porcine tissue to depths of up to 25 mm. To date, this is the largest thickness that SERRS nanotags have been tracked through using a backscattering approach.;This unprecedented performance is due to the use of red-shifted chalcogenpyrylium-based Raman reporters to demonstrate the novel technique of surface enhanced spatially offset resonance Raman spectroscopy (SESORRS) for the first time. The same ex vivo tumour models are also used to demonstrate a multiplexed imaging system through depths of 10 mm using back scattering SESORRS.;The benefit of using red-shifted chalcogenpyrylium based Raman reporters for probing through large thicknesses of plastic and tissue barriers using SERS is also highlighted. Raman signals were collected from SERRS active nanotags through plastic thicknesses of up to 20 mm. The detection of SERRS-active nanotags taken up into ex vivo tumour models through depths of 5 mm of tissue is also shown.;The advantages of applying multivariate analysis for through barrier detection when discriminating analytes with similar spectral features as the barrier is also clearly demonstrated.;Finally, resonant chalcogenpyrylium nanotags were used to demonstrate the benefit of using a resonant Raman reporter for superior low-level limits of detection using SESORS. Nanotags containing chalcogenpyrylium dye were observed at concentrations as low as 1 pM through 5 mm of tissue. This is compared to the non-resonant small molecule Raman reporter BPE which could only be detected at concentrations of 11 pM.;Calculated limits of detection suggest that these SERRS nanotags can be detected at concentrations as low as 104 fM using SESORRS
Novel control approaches for the next generation computer numerical control (CNC) system for hybrid micro-machines
Get PDFIt is well-recognised that micro-machining is a key enabling technology for manufacturing high value-added 3D micro-products, such as optics, moulds/dies and biomedical implants etc. These products are usually made of a wide range of engineering materials and possess complex freeform surfaces with tight tolerance on form accuracy and surface finish.In recent years, hybrid micro-machining technology has been developed to integrate several machining processes on one platform to tackle the manufacturing challenges for the aforementioned micro-products. However, the complexity of system integration and ever increasing demand for further enhanced productivity impose great challenges on current CNC systems. This thesis develops, implements and evaluates three novel control approaches to overcome the identified three major challenges, i.e. system integration, parametric interpolation and toolpath smoothing. These new control approaches provide solid foundation for the development of next generation CNC system for hybrid micro-machines.There is a growing trend for hybrid micro-machines to integrate more functional modules. Machine developers tend to choose modules from different vendors to satisfy the performance and cost requirements. However, those modules often possess proprietary hardware and software interfaces and the lack of plug-and-play solutions lead to tremendous difficulty in system integration. This thesis proposes a novel three-layer control architecture with component-based approach for system integration. The interaction of hardware is encapsulated into software components, while the data flow among different components is standardised. This approach therefore can significantly enhance the system flexibility. It has been successfully verified through the integration of a six-axis hybrid micro-machine. Parametric curves have been proven to be the optimal toolpath representation method for machining 3D micro-products with freeform surfaces, as they can eliminate the high-frequency fluctuation of feedrate and acceleration caused by the discontinuity in the first derivatives along linear or circular segmented toolpath. The interpolation for parametric curves is essentially an optimization problem, which is extremely difficult to get the time-optimal solution. This thesis develops a novel real-time interpolator for parametric curves (RTIPC), which provides a near time-optimal solution. It limits the machine dynamics (axial velocities, axial accelerations and jerk) and contour error through feedrate lookahead and acceleration lookahead operations. Experiments show that the RTIPC can simplify the coding significantly, and achieve up to ten times productivity than the industry standard linear interpolator. Furthermore, it is as efficient as the state-of-the-art Position-Velocity-Time (PVT) interpolator, while achieving much smoother motion profiles.Despite the fact that parametric curves have huge advantage in toolpath continuity, linear segmented toolpath is still dominantly used on the factory floor due to its straightforward coding and excellent compatibility with various CNC systems. This thesis presents a new real-time global toolpath smoothing algorithm, which bridges the gap in toolpath representation for CNC systems. This approach uses a cubic B-spline to approximate a sequence of linear segments. The approximation deviation is controlled by inserting and moving new control points on the control polygon. Experiments show that the proposed approach can increase the productivity by more than three times than the standard toolpath traversing algorithm, and 40% than the state-of-the-art corner blending algorithm, while achieving excellent surface finish.Finally, some further improvements for CNC systems, such as adaptive cutting force control and on-line machining parameters adjustment with metrology, are discussed in the future work section.It is well-recognised that micro-machining is a key enabling technology for manufacturing high value-added 3D micro-products, such as optics, moulds/dies and biomedical implants etc. These products are usually made of a wide range of engineering materials and possess complex freeform surfaces with tight tolerance on form accuracy and surface finish.In recent years, hybrid micro-machining technology has been developed to integrate several machining processes on one platform to tackle the manufacturing challenges for the aforementioned micro-products. However, the complexity of system integration and ever increasing demand for further enhanced productivity impose great challenges on current CNC systems. This thesis develops, implements and evaluates three novel control approaches to overcome the identified three major challenges, i.e. system integration, parametric interpolation and toolpath smoothing. These new control approaches provide solid foundation for the development of next generation CNC system for hybrid micro-machines.There is a growing trend for hybrid micro-machines to integrate more functional modules. Machine developers tend to choose modules from different vendors to satisfy the performance and cost requirements. However, those modules often possess proprietary hardware and software interfaces and the lack of plug-and-play solutions lead to tremendous difficulty in system integration. This thesis proposes a novel three-layer control architecture with component-based approach for system integration. The interaction of hardware is encapsulated into software components, while the data flow among different components is standardised. This approach therefore can significantly enhance the system flexibility. It has been successfully verified through the integration of a six-axis hybrid micro-machine. Parametric curves have been proven to be the optimal toolpath representation method for machining 3D micro-products with freeform surfaces, as they can eliminate the high-frequency fluctuation of feedrate and acceleration caused by the discontinuity in the first derivatives along linear or circular segmented toolpath. The interpolation for parametric curves is essentially an optimization problem, which is extremely difficult to get the time-optimal solution. This thesis develops a novel real-time interpolator for parametric curves (RTIPC), which provides a near time-optimal solution. It limits the machine dynamics (axial velocities, axial accelerations and jerk) and contour error through feedrate lookahead and acceleration lookahead operations. Experiments show that the RTIPC can simplify the coding significantly, and achieve up to ten times productivity than the industry standard linear interpolator. Furthermore, it is as efficient as the state-of-the-art Position-Velocity-Time (PVT) interpolator, while achieving much smoother motion profiles.Despite the fact that parametric curves have huge advantage in toolpath continuity, linear segmented toolpath is still dominantly used on the factory floor due to its straightforward coding and excellent compatibility with various CNC systems. This thesis presents a new real-time global toolpath smoothing algorithm, which bridges the gap in toolpath representation for CNC systems. This approach uses a cubic B-spline to approximate a sequence of linear segments. The approximation deviation is controlled by inserting and moving new control points on the control polygon. Experiments show that the proposed approach can increase the productivity by more than three times than the standard toolpath traversing algorithm, and 40% than the state-of-the-art corner blending algorithm, while achieving excellent surface finish.Finally, some further improvements for CNC systems, such as adaptive cutting force control and on-line machining parameters adjustment with metrology, are discussed in the future work section
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