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Investigation of corrosion of carbon steel under insulation
Full text linkCorrosion of metals under insulation is a serious concern for industries due to the fact that the insulation hides the metal from view which increases the likelihood of sudden failure. Carbon steel is one of the metal alloys frequently used in industries due to economic and technical reasons. However, it is quite susceptible to corrosion under insulation (CUI). The factors affecting corrosion of carbon steel under mineral wool insulation such as temperature, effectiveness of inhibitor, quantity and distribution of electrolyte in the insulation have not been extensively studied in the literature. In fact, studies on corrosion of metals under insulation are quite sparse compared to immersion (uninsulated) conditions. Therefore, the objectives of this study were to assess the effect of temperature (60 oC to 130 oC) on corrosion of carbon steel under insulation, effectiveness of a new commercial inhibitor (VpCI 619) in mitigating CUI of carbon steel, quantity and distribution of electrolyte (1wt. % NaCl) in mineral wool insulation as well as investigation of the drying times of the insulation using galvanic current and electrochemical impedance measurements. In addition, the prediction of CUI rate using Artificial Neural Network (ANN) was carried out with the aim of assessing the accuracy of prediction of different network parameters such as number of hidden layers, number of input parameters and choice of activation function. Prior to CUI studies, the water absorption capacity of mineral wool insulation was determined using standard procedures (ASTM C1511). This was carried out to assess the time it will take for the insulation to be saturated with water, the variability of repeated measurements as well as the total water content in the insulation. The CUI studies were carried out using a test rig that was based on ASTM G189-07 standard. The corrosion rates were estimated using weight loss technique and the effects of temperature, vapour phase inhibitor consisting primarily of sodium molybdate, quantity of electrolyte in insulation were investigated. The drying out profile of the insulation was assessed using galvanic current and electrochemical impedance measurements. Furthermore, the prediction of CUI rate was carried out using Artificial Neural Network and the effect of single and double hidden layers, sigmoid and hyperbolic tangent activation functions, as well as number of input parameters on accuracy of prediction of CUI rate were assessed. The results of the water absorption studies indicated continuous absorption of water even after immersion for 22 days. The water absorption capacity was greater for thermally treated insulation compared to untreated insulation samples due to thermal degradation of the oily additives and polymeric binders. The effect of temperature on CUI indicated an increase in corrosion rate from 60 oC to 80 oC. Further increase in temperature up to 130 oC resulted in a decrease in corrosion rate. The existence of a maximum point in the curve was attributed to the competing effects of two factors which include increased diffusivity of oxygen which dominates at low temperature and decreasing solubility of oxygen and insulation dry-out which dominates at temperatures exceeding 80 oC. The new commercial inhibitor was observed to mitigate the corrosion rate at the temperatures investigated in this study. The inhibition efficiency indicated an average of 89% when a dosage of 5.2 g/m2 of the inhibitor was used. The effectiveness was also observed to be dosage dependent with lower doses having less inhibition efficiency. The drying times of the insulation assessed using galvanic current and impedance methods were observed to decrease as temperature increased. The galvanic current was observed to decrease to zero while the impedance increased to high values as the insulation dries out. However, the drying times obtained from galvanic current method showed a higher variability compared to impedance method.The result of prediction of CUI rate using Artificial Neural Network indicated an increase in accuracy as the number of input parameters increased. Surprisingly, the accuracy of the predicted output from the four input parameters (temperature, dosage of inhibitor, quantity of electrolyte in insulation and sample position) was higher than the accuracy of the most influential parameters (temperature and dosage of inhibitor). This suggests that incorporation of more input parameters having some relationship with the output is more important in achieving a higher accuracy compared to usingthe most influential parameters only. In conclusion, this study indicated that mineral wool insulation absorbs water for a long period without saturation which increases the risk of CUI. Also, CUI rate increased with temperature up to 80 oC but decreased on further increase up to 130 oC. The newcommercial inhibitor was effective in mitigating CUI at the temperatures investigated. Also, more test solution was observed at the lower part of the insulation compared to the upper part when installed on the CUI test rig which increases the risk of severe corrosion at the lower section of the insulation. The prediction of CUI rate using ANN indicated that inclusion of more input parameters could improve prediction accuracy. Moreover, the choice of activation functions also has effect on the accuracy of the predicted output.Corrosion of metals under insulation is a serious concern for industries due to the fact that the insulation hides the metal from view which increases the likelihood of sudden failure. Carbon steel is one of the metal alloys frequently used in industries due to economic and technical reasons. However, it is quite susceptible to corrosion under insulation (CUI). The factors affecting corrosion of carbon steel under mineral wool insulation such as temperature, effectiveness of inhibitor, quantity and distribution of electrolyte in the insulation have not been extensively studied in the literature. In fact, studies on corrosion of metals under insulation are quite sparse compared to immersion (uninsulated) conditions. Therefore, the objectives of this study were to assess the effect of temperature (60 oC to 130 oC) on corrosion of carbon steel under insulation, effectiveness of a new commercial inhibitor (VpCI 619) in mitigating CUI of carbon steel, quantity and distribution of electrolyte (1wt. % NaCl) in mineral wool insulation as well as investigation of the drying times of the insulation using galvanic current and electrochemical impedance measurements. In addition, the prediction of CUI rate using Artificial Neural Network (ANN) was carried out with the aim of assessing the accuracy of prediction of different network parameters such as number of hidden layers, number of input parameters and choice of activation function. Prior to CUI studies, the water absorption capacity of mineral wool insulation was determined using standard procedures (ASTM C1511). This was carried out to assess the time it will take for the insulation to be saturated with water, the variability of repeated measurements as well as the total water content in the insulation. The CUI studies were carried out using a test rig that was based on ASTM G189-07 standard. The corrosion rates were estimated using weight loss technique and the effects of temperature, vapour phase inhibitor consisting primarily of sodium molybdate, quantity of electrolyte in insulation were investigated. The drying out profile of the insulation was assessed using galvanic current and electrochemical impedance measurements. Furthermore, the prediction of CUI rate was carried out using Artificial Neural Network and the effect of single and double hidden layers, sigmoid and hyperbolic tangent activation functions, as well as number of input parameters on accuracy of prediction of CUI rate were assessed. The results of the water absorption studies indicated continuous absorption of water even after immersion for 22 days. The water absorption capacity was greater for thermally treated insulation compared to untreated insulation samples due to thermal degradation of the oily additives and polymeric binders. The effect of temperature on CUI indicated an increase in corrosion rate from 60 oC to 80 oC. Further increase in temperature up to 130 oC resulted in a decrease in corrosion rate. The existence of a maximum point in the curve was attributed to the competing effects of two factors which include increased diffusivity of oxygen which dominates at low temperature and decreasing solubility of oxygen and insulation dry-out which dominates at temperatures exceeding 80 oC. The new commercial inhibitor was observed to mitigate the corrosion rate at the temperatures investigated in this study. The inhibition efficiency indicated an average of 89% when a dosage of 5.2 g/m2 of the inhibitor was used. The effectiveness was also observed to be dosage dependent with lower doses having less inhibition efficiency. The drying times of the insulation assessed using galvanic current and impedance methods were observed to decrease as temperature increased. The galvanic current was observed to decrease to zero while the impedance increased to high values as the insulation dries out. However, the drying times obtained from galvanic current method showed a higher variability compared to impedance method.The result of prediction of CUI rate using Artificial Neural Network indicated an increase in accuracy as the number of input parameters increased. Surprisingly, the accuracy of the predicted output from the four input parameters (temperature, dosage of inhibitor, quantity of electrolyte in insulation and sample position) was higher than the accuracy of the most influential parameters (temperature and dosage of inhibitor). This suggests that incorporation of more input parameters having some relationship with the output is more important in achieving a higher accuracy compared to usingthe most influential parameters only. In conclusion, this study indicated that mineral wool insulation absorbs water for a long period without saturation which increases the risk of CUI. Also, CUI rate increased with temperature up to 80 oC but decreased on further increase up to 130 oC. The newcommercial inhibitor was effective in mitigating CUI at the temperatures investigated. Also, more test solution was observed at the lower part of the insulation compared to the upper part when installed on the CUI test rig which increases the risk of severe corrosion at the lower section of the insulation. The prediction of CUI rate using ANN indicated that inclusion of more input parameters could improve prediction accuracy. Moreover, the choice of activation functions also has effect on the accuracy of the predicted output
Measurement-induced phase transitions and the interplay between coherent and dissipative dynamics
Full text linkMeasurement-induced phase transitions arise from the interplay of coherent quantum dynamics and local measurements. For example, coherent dynamics can generate entanglement and long-ranged correlations, while local measurements destroy them. By tuning the strength of the measurements, the system undergoes a phase transition at the level of individual stochastic measurement trajectories. It is only witnessed by non-linear functions in the density operator, and due to the stochastic nature of the measurement outcomes, the average density operator masks the transition. In this thesis, we explore how this type of transition arises in bosonic and fermionic models that are subject to dephasing or measurement and consider ways to detect the transition in experiments. We first give an overview of the transition and describe the difficulties in identifying the exact location of the transition and finding experimental protocols to detect them. We then show that in a homodyne detection setup, it is impossible to reconstruct the nonlinear correlation function that witnesses the transition, using only the linear information from homodyne currents, and we discuss the difficulties that arise when considering the experimental detection of this transition. We finally show that features of the competition between coherent and dissipative dynamics are already present at short times during the system evolution. We also present a protocol that displays the characteristic behaviour of the transition, starting from an infinite temperature state. In all projects, we employ a range of numerical techniques, such as Monte-Carlo wavefunction methods, which allow us to simulate the open quantum systems dynamics and enable us to explore the presented models.Measurement-induced phase transitions arise from the interplay of coherent quantum dynamics and local measurements. For example, coherent dynamics can generate entanglement and long-ranged correlations, while local measurements destroy them. By tuning the strength of the measurements, the system undergoes a phase transition at the level of individual stochastic measurement trajectories. It is only witnessed by non-linear functions in the density operator, and due to the stochastic nature of the measurement outcomes, the average density operator masks the transition. In this thesis, we explore how this type of transition arises in bosonic and fermionic models that are subject to dephasing or measurement and consider ways to detect the transition in experiments. We first give an overview of the transition and describe the difficulties in identifying the exact location of the transition and finding experimental protocols to detect them. We then show that in a homodyne detection setup, it is impossible to reconstruct the nonlinear correlation function that witnesses the transition, using only the linear information from homodyne currents, and we discuss the difficulties that arise when considering the experimental detection of this transition. We finally show that features of the competition between coherent and dissipative dynamics are already present at short times during the system evolution. We also present a protocol that displays the characteristic behaviour of the transition, starting from an infinite temperature state. In all projects, we employ a range of numerical techniques, such as Monte-Carlo wavefunction methods, which allow us to simulate the open quantum systems dynamics and enable us to explore the presented models
Predictive design of stable polymer-based amorphous solid dispersions
Full text linkThe potential of amorphous solid dispersions (ASDs) solving current aqueous solubility challenges within the pharmaceutical industry has been extensively reported. Nonetheless, the difficulty of ensuring long-term physical stability has limited its translation into commercial drug products. One of the main factors that determines ASD physical stability is the solubility of the API in the polymeric carrier. However, there is a scarcity of reliable methods available for its determination. In this thesis, this was directly addressed by developing a novel empirical method to determine the saturated solubility of crystalline API in polymer matrices. Hot melt extrusion and low-frequency Raman (LFR) spectroscopy were combined for the first time for real-time API-polymer solubility determination. This approach enabled construction of solubility phase diagrams that inform safe processing windows to avoid residual API crystallinity, inform maximum drug loadings and aid polymer selection for maximum API solubility and ASD physical stability. The solid-liquid equilibrium depicting the API solubility curve was also compared to state of the art DSC-based methods, including the Flory-Huggins and Kyeremateng modelling approaches, among others. Equilibrium assumptions and potential shortfalls leading to under or overestimations were discussed. In addition, the impact of drug loading and processing temperature on the ASD internal microstructure was investigated by means of synchrotron phase-contrast micro tomography (Sync-PC-μCT). Furthermore, the local distribution evolution of the API and polymer on the ASD surface was investigated through time-of-flight secondary ion mass spectrometry (ToF-SIMS) chemical mapping. Surface phase-separation and crystallisation kinetics were determined and compared to bulk crystallisation phenomena. A close link was established between the coordinates of the solubility phase diagram and ASD properties such as the degree of structural heterogeneity and the crystallisation induction time and rate. Overall, these results suggest the API saturated solubility determined by the LFR method could be used as a physical stability predictor for the design, development and manufacture of stable polymer-based ASDs with desired structure and performance.The potential of amorphous solid dispersions (ASDs) solving current aqueous solubility challenges within the pharmaceutical industry has been extensively reported. Nonetheless, the difficulty of ensuring long-term physical stability has limited its translation into commercial drug products. One of the main factors that determines ASD physical stability is the solubility of the API in the polymeric carrier. However, there is a scarcity of reliable methods available for its determination. In this thesis, this was directly addressed by developing a novel empirical method to determine the saturated solubility of crystalline API in polymer matrices. Hot melt extrusion and low-frequency Raman (LFR) spectroscopy were combined for the first time for real-time API-polymer solubility determination. This approach enabled construction of solubility phase diagrams that inform safe processing windows to avoid residual API crystallinity, inform maximum drug loadings and aid polymer selection for maximum API solubility and ASD physical stability. The solid-liquid equilibrium depicting the API solubility curve was also compared to state of the art DSC-based methods, including the Flory-Huggins and Kyeremateng modelling approaches, among others. Equilibrium assumptions and potential shortfalls leading to under or overestimations were discussed. In addition, the impact of drug loading and processing temperature on the ASD internal microstructure was investigated by means of synchrotron phase-contrast micro tomography (Sync-PC-μCT). Furthermore, the local distribution evolution of the API and polymer on the ASD surface was investigated through time-of-flight secondary ion mass spectrometry (ToF-SIMS) chemical mapping. Surface phase-separation and crystallisation kinetics were determined and compared to bulk crystallisation phenomena. A close link was established between the coordinates of the solubility phase diagram and ASD properties such as the degree of structural heterogeneity and the crystallisation induction time and rate. Overall, these results suggest the API saturated solubility determined by the LFR method could be used as a physical stability predictor for the design, development and manufacture of stable polymer-based ASDs with desired structure and performance
Automated manufacturing of smart tunnel segments
Full text linkTunnels, essential infrastructures, require regular inspections and maintenance to ensure their prolonged service life. While conventional methods heavily rely on expert human manpower, modern tunnel structural monitoring techniques, such as sensor-based Structural Health Monitoring (SHM), are increasingly utilized in both existing and newly constructed tunnels. Despite providing valuable insights into post-construction structural behaviour, these methods often overlook the behaviour of individual precast elements, such as tunnel segments, before their installation. This thesis explores the concept of smart tunnel segments instrumented by robotic means to address this gap. In this project lab-scale tunnel segments were instrumented using a 6-axis robotic arm making them smart enabling their properties to be tracked from manufacturing through the operational phase of the tunnel. The research involves a comprehensive review of current tunnel instrumentation practices, identifying structural strains as the most monitored parameters. Vibrating Wire Strain Gauges (VWSGs) were identified as the most suitable sensors for this application due to their compatibility with a modular system and superior long-term properties, especially when embedded in concrete. Furthermore, the study identifies untapped potential in fully automated precast factories
and proposes repurposing certain features of industrial robots to deploy VWSGs nodes via robotic pick-and-place. Through a novel evaluation framework, the research demonstrates the effectiveness of automated sensor deployment by robots. This includes the robotic installation of a pair of embedded VWSGs in lab-scale tunnel segments, thereby rendering them "smart," and subjecting them to repetitive flexural loadings to evaluate their performance and accuracy. The calculated strain transfer exhibits consistent and repeatable behaviour across segments. Finally, the thesis outlines the economic justification for smart segments, which outperform traditional on-site wired and wireless alternatives, thereby contributing to a more comprehensive and cost-effective tunnel maintenance strategyTunnels, essential infrastructures, require regular inspections and maintenance to ensure their prolonged service life. While conventional methods heavily rely on expert human manpower, modern tunnel structural monitoring techniques, such as sensor-based Structural Health Monitoring (SHM), are increasingly utilized in both existing and newly constructed tunnels. Despite providing valuable insights into post-construction structural behaviour, these methods often overlook the behaviour of individual precast elements, such as tunnel segments, before their installation. This thesis explores the concept of smart tunnel segments instrumented by robotic means to address this gap. In this project lab-scale tunnel segments were instrumented using a 6-axis robotic arm making them smart enabling their properties to be tracked from manufacturing through the operational phase of the tunnel. The research involves a comprehensive review of current tunnel instrumentation practices, identifying structural strains as the most monitored parameters. Vibrating Wire Strain Gauges (VWSGs) were identified as the most suitable sensors for this application due to their compatibility with a modular system and superior long-term properties, especially when embedded in concrete. Furthermore, the study identifies untapped potential in fully automated precast factories
and proposes repurposing certain features of industrial robots to deploy VWSGs nodes via robotic pick-and-place. Through a novel evaluation framework, the research demonstrates the effectiveness of automated sensor deployment by robots. This includes the robotic installation of a pair of embedded VWSGs in lab-scale tunnel segments, thereby rendering them "smart," and subjecting them to repetitive flexural loadings to evaluate their performance and accuracy. The calculated strain transfer exhibits consistent and repeatable behaviour across segments. Finally, the thesis outlines the economic justification for smart segments, which outperform traditional on-site wired and wireless alternatives, thereby contributing to a more comprehensive and cost-effective tunnel maintenance strateg
Recrystallisation and γ′ precipitation during industrial open die forging of the nickel based superalloy AD730
No full textNi-based superalloys are used in very challenging operating conditions in jet turbine engines. In order to withstand these challenging operating conditions, and be used in safety critical parts such as turbine discs, the microstructure of such alloys must be well controlled. Much of this control is achieved during open die forging, where as-cast ingots are converted into billets. During this process the coarse as-cast structure is massively refined through recrystallisation. To design an effective forging route, and produce the desired, refined, uniform microstructure, the microstructural evolutions happening during the open die forging must be investigated; that is the aim of this thesis. The Ni-based superalloy AD730, produced by Aubert&Duval is studied. The microstructure from different stages of the industrial forging process is analysed, and stages of this process are simulated on the lab scale to allow microstructural mechanisms to be investigated. The precipitate distribution which forms during first cooling through the solvus temperature is characterised, including with 3D observations. It is observed that this distribution is very inhomogeneous, comprising a mixture of continuous and discontinuous precipitates and some regions with no precipitation. The potential role of chemical segregation in producing the inhomogeneous precipitate distribution is investigated. It is found that the regions without precipitates have lower concentrations of the γ′ forming elements. A key finding is that cooling through the γ′ solvus temperature has a significant effect on grain size and morphology, with grain size decreasing and grain boundaries becoming more serrated. The interaction of this inhomogeneous distribution with recrystallisation during compression is studied, and it is seen that regions with different precipitation show different mechanisms and kinetics of recrystallisation. A key finding is that regions with discontinuous precipitation are harder to recrystallise than those with continuous precipitation. Local crystallographic texture also influences the kinetics of recrystallisation during compression, grains with a ⟨110⟩ axis close to the macroscopic compression direction being harder to recrystallise than grains without. The role of annealing twin formation in assisting the nucleation and growth of recrystallised grains is discussed, and examples of its effect are shown. The effect of forging parameters (cooling rate after forging, number of forging strokes used) is also investigated. A detailed study is performed on the interaction between recrystallisation and precipitates during the final sub-solvus forging stage of the industrial forging process. It is observed that precipitates can interact in at least four different ways with recrystallisation. Suggestions are made for future work, and for ways to exploit the observations made in an industrial forging process.Ni-based superalloys are used in very challenging operating conditions in jet turbine engines. In order to withstand these challenging operating conditions, and be used in safety critical parts such as turbine discs, the microstructure of such alloys must be well controlled. Much of this control is achieved during open die forging, where as-cast ingots are converted into billets. During this process the coarse as-cast structure is massively refined through recrystallisation. To design an effective forging route, and produce the desired, refined, uniform microstructure, the microstructural evolutions happening during the open die forging must be investigated; that is the aim of this thesis. The Ni-based superalloy AD730, produced by Aubert&Duval is studied. The microstructure from different stages of the industrial forging process is analysed, and stages of this process are simulated on the lab scale to allow microstructural mechanisms to be investigated. The precipitate distribution which forms during first cooling through the solvus temperature is characterised, including with 3D observations. It is observed that this distribution is very inhomogeneous, comprising a mixture of continuous and discontinuous precipitates and some regions with no precipitation. The potential role of chemical segregation in producing the inhomogeneous precipitate distribution is investigated. It is found that the regions without precipitates have lower concentrations of the γ′ forming elements. A key finding is that cooling through the γ′ solvus temperature has a significant effect on grain size and morphology, with grain size decreasing and grain boundaries becoming more serrated. The interaction of this inhomogeneous distribution with recrystallisation during compression is studied, and it is seen that regions with different precipitation show different mechanisms and kinetics of recrystallisation. A key finding is that regions with discontinuous precipitation are harder to recrystallise than those with continuous precipitation. Local crystallographic texture also influences the kinetics of recrystallisation during compression, grains with a ⟨110⟩ axis close to the macroscopic compression direction being harder to recrystallise than grains without. The role of annealing twin formation in assisting the nucleation and growth of recrystallised grains is discussed, and examples of its effect are shown. The effect of forging parameters (cooling rate after forging, number of forging strokes used) is also investigated. A detailed study is performed on the interaction between recrystallisation and precipitates during the final sub-solvus forging stage of the industrial forging process. It is observed that precipitates can interact in at least four different ways with recrystallisation. Suggestions are made for future work, and for ways to exploit the observations made in an industrial forging process
Facilitating a creative pedagogical space to engage children with the topic of death and dying in schools
Full text linkIn recent years, a significant amount of attention has been drawn to the topic of death and dying in schools from a rights perspective: concerning how children’s rights to be heard, to access information and receive timely support are not being met. From a practitioner enquiry stance, this study aimed to increase children’s engagement with the topic of death and dying by encouraging their participation in research through creative methods. Challenges faced by school staff are outlined in my practitioner enquiry and, subsequently, a systematic review was undertaken with a focus on qualitative literature involving children aged 3-18 and creative approaches to engaging children with the topic of death and dying. This concluded ways in which a range of creative methods were used with children in contrast to conventional research methods that are unfamiliar to them. Drawing on creative methodologies, the data collection tools used in this study linked directly to children’s classroom experiences. Resultantly, art, drama and music were used as creative methods to explore children’s engagement with death. In a group environment, children’s views were collectively considered through participative research design, methods and analysis. Thematic analysis was then used to discover prevalent themes from the creative data, and I worked with the participants to create a performance as part of this process. This approach resulted in a script which formed the basis of the findings. The findings indicated that children valued the opportunity to express themselves through the creative opportunities arising in the practitioner enquiry. This study outlines the quality dimensions of a pedagogic creative space that can be facilitated with children to explore topics such as death and dying. These include, not extensively: comfort zones, collaboration, elements of risk-taking in safe environment, non-judgemental practice and stimulating resources. When putting these recommendations into practice in a creative and pedagogic space, practitioners should consider the child’s social world which will determine how they perceive death and process grief.In recent years, a significant amount of attention has been drawn to the topic of death and dying in schools from a rights perspective: concerning how children’s rights to be heard, to access information and receive timely support are not being met. From a practitioner enquiry stance, this study aimed to increase children’s engagement with the topic of death and dying by encouraging their participation in research through creative methods. Challenges faced by school staff are outlined in my practitioner enquiry and, subsequently, a systematic review was undertaken with a focus on qualitative literature involving children aged 3-18 and creative approaches to engaging children with the topic of death and dying. This concluded ways in which a range of creative methods were used with children in contrast to conventional research methods that are unfamiliar to them. Drawing on creative methodologies, the data collection tools used in this study linked directly to children’s classroom experiences. Resultantly, art, drama and music were used as creative methods to explore children’s engagement with death. In a group environment, children’s views were collectively considered through participative research design, methods and analysis. Thematic analysis was then used to discover prevalent themes from the creative data, and I worked with the participants to create a performance as part of this process. This approach resulted in a script which formed the basis of the findings. The findings indicated that children valued the opportunity to express themselves through the creative opportunities arising in the practitioner enquiry. This study outlines the quality dimensions of a pedagogic creative space that can be facilitated with children to explore topics such as death and dying. These include, not extensively: comfort zones, collaboration, elements of risk-taking in safe environment, non-judgemental practice and stimulating resources. When putting these recommendations into practice in a creative and pedagogic space, practitioners should consider the child’s social world which will determine how they perceive death and process grief
Entrepreneurial households : the economic organisation of domestic life
Full text linkThis study explores the economic organisation of the domestic lives of entrepreneurs as a foundation for understanding how entrepreneurs make a living and sustain the economic well-being of their households. To contribute to a greater appreciation of the daily experiences of ‘everyday’ entrepreneurs and their households, the study addresses three core questions. Firstly, it examines whether entrepreneurial households have different patterns of income generation and wealth accumulation compared to non-entrepreneurial households. Secondly, it explores how entrepreneurial households earn their livelihoods, and thirdly, how provisioning is undertaken within entrepreneurial households. The study adopts a qualitative dominant mixed methods design. Answering the first question entailed a secondary analysis of the UK Wealth & Assets Survey to explore the wealth and income distribution among private households in Great Britain. This enabled an understanding of the distinctiveness of economic organisation within
entrepreneurial households, in comparison to their employee counterparts. The second and third research questions were addressed through comparative case studies of five entrepreneurial households. Qualitative data enabled a deeper understanding of the economic behaviour and organisation of entrepreneurial households within its real-life context. The secondary analysis uncovered notable differences in wealth accumulation patterns and income sources between entrepreneurial and employee households, indicating variations in their internal economic organisation and behaviour. The subsequent comparative multiple case study analysis went beyond economic determinism and expanded traditional economic and money-metric measures of material living conditions to capture the processual and multi-dimensional nature of provisioning in entrepreneurial households. Through a detailed examination of the lived experiences of the research participants, the study revealed the ambiguity surrounding the
dominant business activity within households, asymmetric participation in work, and the variety of earned and non-earned income sources. The findings question the contribution of the business to household livelihood and situated household economic functioning within a broader spectrum of relationships, including other households, the formal economy, and the state.This study explores the economic organisation of the domestic lives of entrepreneurs as a foundation for understanding how entrepreneurs make a living and sustain the economic well-being of their households. To contribute to a greater appreciation of the daily experiences of ‘everyday’ entrepreneurs and their households, the study addresses three core questions. Firstly, it examines whether entrepreneurial households have different patterns of income generation and wealth accumulation compared to non-entrepreneurial households. Secondly, it explores how entrepreneurial households earn their livelihoods, and thirdly, how provisioning is undertaken within entrepreneurial households. The study adopts a qualitative dominant mixed methods design. Answering the first question entailed a secondary analysis of the UK Wealth & Assets Survey to explore the wealth and income distribution among private households in Great Britain. This enabled an understanding of the distinctiveness of economic organisation within
entrepreneurial households, in comparison to their employee counterparts. The second and third research questions were addressed through comparative case studies of five entrepreneurial households. Qualitative data enabled a deeper understanding of the economic behaviour and organisation of entrepreneurial households within its real-life context. The secondary analysis uncovered notable differences in wealth accumulation patterns and income sources between entrepreneurial and employee households, indicating variations in their internal economic organisation and behaviour. The subsequent comparative multiple case study analysis went beyond economic determinism and expanded traditional economic and money-metric measures of material living conditions to capture the processual and multi-dimensional nature of provisioning in entrepreneurial households. Through a detailed examination of the lived experiences of the research participants, the study revealed the ambiguity surrounding the
dominant business activity within households, asymmetric participation in work, and the variety of earned and non-earned income sources. The findings question the contribution of the business to household livelihood and situated household economic functioning within a broader spectrum of relationships, including other households, the formal economy, and the state
Friction Stir Welding (FSW) of dissimilar metals and alloys
Full text linkThis thesis presents a comprehensive investigation into the Friction Stir Welding (FSW)
process of dissimilar materials, specifically aluminium and copper. The research
employed a combination of experimental and numerical methods to evaluate the weld
quality through metallurgical and mechanical analyses. Finite Element (FE) methods
were utilised as an auxiliary tool, supplementing the experimental work to simulate the
FSW process and facilitating the prediction of IMCs formation.
The study begins with a literature review emphasising the importance of placing copper
on the advancing side (AS) to achieve defect-free dissimilar aluminium to copper FSW
joints. However, tool offsetting on the retreating side (RS) or AS was found impractical
for industrial applications due to varying tool offsets. Alternatively, researchers
achieved defect-free joints by placing aluminium on the AS without tool offset.
However, limited research has focused on this configuration, despite its benefits for
joint mechanical properties. Further investigation is needed to understand the
relationship between intermetallic compound microstructure and mechanical properties.
To address these gaps, the research focused on dissimilar FSW between AA5083
aluminium and copper, exploring the influence of tool rotational and traverse speeds on
joint quality without introducing tool offsetting. The findings revealed successful weld
joints between the dissimilar materials using specific parameter combinations,
including rotational speed levels of 1000 rpm (at welding speeds of 100 and 120
mm/min), 1200 rpm (at 80 mm/min), and 1400 rpm (at welding speeds of 80 and 120
mm/min). An inhomogeneous microstructure was observed within the weld, with the
predominant intermetallic compounds (IMCs) identified as Al2Cu and Al4Cu9. The volume fraction of IMCs increased with higher tool rotational speeds, leading to
improved ultimate tensile strength (UTS) and joint efficiency.
Additionally, the study employed a novel approach to predict and validate the formation
of IMCs during FSW of AA6061 aluminium to copper. The use of a Coupled Eulerian
Lagrangian (CEL) model, combined with a modified friction law, provided good
agreement with experimental data. The predicted IMCs, including AlCu, Al2Cu, and
Al4Cu9, were confirmed through the comparison of temperature distribution, Al-Cu
phase diagram, and elemental concentration. The research demonstrated that defect-free
joints could be achieved at specific rotational speeds and traverse speed, where the
softer material (AA6061) was placed on the AS.
Furthermore, the research focused on optimising the FSW parameters for dissimilar
joints between AA5083 and copper using the Taguchi design of experiments (DoE)
method. By considering tool rotational speed, welding speed, and FSW tool design, the
study successfully identified the significant parameters affecting joint mechanical
strength. The optimised parameter combinations resulted in enhanced UTS, and flexure
stress compared to the initial parameter sets. Linear regression analysis further
confirmed the agreement between predicted and actual values of UTS and flexure stress.
Finally, the study investigated the influence of different aluminium grades (AA5083
and AA6061) on dissimilar FSW of aluminium to magnesium AZ31B. Placing the
softer material (AZ31B) on the AS consistently produced defect-free joints, and the
joint mechanical strength improved when AZ31B was joined to the harder aluminium
grade (AA6061). The presence of intermetallic compounds, such as Al3Mg2 and Al12Mg17, contributed to higher hardness values in the weld nugget, resulting in
improved joint mechanical efficiency.
The findings of this research have advanced the understanding of dissimilar materials
FSW and provided insights into optimising the FSW process parameters for enhanced
joint quality. The conclusions drawn from this study offer valuable guidance for future
research and advancements in the field of dissimilar materials FSW process.This thesis presents a comprehensive investigation into the Friction Stir Welding (FSW)
process of dissimilar materials, specifically aluminium and copper. The research
employed a combination of experimental and numerical methods to evaluate the weld
quality through metallurgical and mechanical analyses. Finite Element (FE) methods
were utilised as an auxiliary tool, supplementing the experimental work to simulate the
FSW process and facilitating the prediction of IMCs formation.
The study begins with a literature review emphasising the importance of placing copper
on the advancing side (AS) to achieve defect-free dissimilar aluminium to copper FSW
joints. However, tool offsetting on the retreating side (RS) or AS was found impractical
for industrial applications due to varying tool offsets. Alternatively, researchers
achieved defect-free joints by placing aluminium on the AS without tool offset.
However, limited research has focused on this configuration, despite its benefits for
joint mechanical properties. Further investigation is needed to understand the
relationship between intermetallic compound microstructure and mechanical properties.
To address these gaps, the research focused on dissimilar FSW between AA5083
aluminium and copper, exploring the influence of tool rotational and traverse speeds on
joint quality without introducing tool offsetting. The findings revealed successful weld
joints between the dissimilar materials using specific parameter combinations,
including rotational speed levels of 1000 rpm (at welding speeds of 100 and 120
mm/min), 1200 rpm (at 80 mm/min), and 1400 rpm (at welding speeds of 80 and 120
mm/min). An inhomogeneous microstructure was observed within the weld, with the
predominant intermetallic compounds (IMCs) identified as Al2Cu and Al4Cu9. The volume fraction of IMCs increased with higher tool rotational speeds, leading to
improved ultimate tensile strength (UTS) and joint efficiency.
Additionally, the study employed a novel approach to predict and validate the formation
of IMCs during FSW of AA6061 aluminium to copper. The use of a Coupled Eulerian
Lagrangian (CEL) model, combined with a modified friction law, provided good
agreement with experimental data. The predicted IMCs, including AlCu, Al2Cu, and
Al4Cu9, were confirmed through the comparison of temperature distribution, Al-Cu
phase diagram, and elemental concentration. The research demonstrated that defect-free
joints could be achieved at specific rotational speeds and traverse speed, where the
softer material (AA6061) was placed on the AS.
Furthermore, the research focused on optimising the FSW parameters for dissimilar
joints between AA5083 and copper using the Taguchi design of experiments (DoE)
method. By considering tool rotational speed, welding speed, and FSW tool design, the
study successfully identified the significant parameters affecting joint mechanical
strength. The optimised parameter combinations resulted in enhanced UTS, and flexure
stress compared to the initial parameter sets. Linear regression analysis further
confirmed the agreement between predicted and actual values of UTS and flexure stress.
Finally, the study investigated the influence of different aluminium grades (AA5083
and AA6061) on dissimilar FSW of aluminium to magnesium AZ31B. Placing the
softer material (AZ31B) on the AS consistently produced defect-free joints, and the
joint mechanical strength improved when AZ31B was joined to the harder aluminium
grade (AA6061). The presence of intermetallic compounds, such as Al3Mg2 and Al12Mg17, contributed to higher hardness values in the weld nugget, resulting in
improved joint mechanical efficiency.
The findings of this research have advanced the understanding of dissimilar materials
FSW and provided insights into optimising the FSW process parameters for enhanced
joint quality. The conclusions drawn from this study offer valuable guidance for future
research and advancements in the field of dissimilar materials FSW process
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