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Development of fibre and particulate filled aerogel composites for subsea pipeline applications
Get PDFThe aim of this project is to develop an analytical tool through Finite Element Method to understand and guide the design of thermal insulation materials. In particular, fibrous mat and aerogel particle-filled resin are focused in the context of subsea pipe-in-pipe (PiP) application for oil and gas extraction. The former has become part of a novel combination with super-insulating material – aerogel, and found its commercial use in the annulus region of the PiP. The latter is considered to be a form of upgrade to the current nylon-based centraliser stabilising the PiP configuration under hydraulic pressure from the deep seawater.The use of porous materials (e.g. fibrous matt and foam) as thermal insulation has a long history, A randomly orientated fibre mat is effective insulation due to the lack of a straight heat conduction pathway and relatively small pores in the fibrous structure. Recent development of super insulating materials involves combining fibrous mat with aerogel, which has resulted in a flexible and less compressible aerogel-fibre blanket with lower thermal conductivity (14 – 20 mw/mK) than typical conventional fibrous counterparts (35 – 50 mw/mK). However, a fundamental understanding of how the fibrous mat interacts the aerogel has not been extensively studied. The use of porous particle-filled resin composites, particularly with aerogel particles, has received less studies in thermal cases and a similar understanding of such integration must be developed in order to inform the design process.The rationale for carrying out this research was to create a range of simulations that can be easily used to predict the effect of changing properties of these above composites on their thermal and mechanical performance. The use of simulations is less time consuming and allows more parameters to be easily varied to see what the optimal fibre design is for specific applications.In order to simulate the effects of varying the composition of the mats, an algorithm to generate a random fibre mat was produced, based on the work of Arambakam and Tafreshi [1]. This fibre positioning was done in MathWorks’ MATLAB, which was used to generate a script for producing a 3D geometry that can be incorporated in ANSYS APDL. This geometry was then used as the basis for a 3D finite element method model that utilised ANSYS Mechanical to mesh and solve the simulation. The same fibre generation process was used for both the mechanical and the thermal simulations, but with the bounding region being differently shaped to accommodate representing the standard experimental techniques used to measure these values.Simulations were carried out to investigate the effect of various parameters of the fibre mat. Specifically, the fibre orientation and the volume fraction of the mat were the main parameters of importance, with the orientation both in and out of the plane of heat transfer being investigated. The ratio of straight fibres to sinusoidal fibres was also investigated as a key parameter affecting the heat transfer, with the volume of straight fibres to total fibre volume being used to determine the “straight fibre fraction” of the fibres. The effect of the fibre length and diameter were also investigated, though it was found that on the scales investigated, they had very little effect on the thermal conductivity.A study into using fully random fibres, where the fibre can be represented by a continuous curve in 3D space that varies in direction throughout the length, was carried out. However, the high level of complexity of this fibre configuration along with the large number of fibre intersections meant that meshing the geometry produced was very difficult. Some successful meshes were produced; however, they included a number of elements that was too large to successfully produce a solution using finite element analysis.For aerogel particle-filled resin, an effort was made to investigate the effect of dispersing particles of aerogel through a resin matrix, in an effort to reduce the thermal conductivity of the matrix. The results of this showed that it was theoretically possible to achieve significantly lower thermal conductivity. The material properties generated from the FE simulations were then used in modelling the centraliser to determine the insulations effectiveness in pipe in pipe insulation. These simulations included the particle simulation data to guide the addition of aerogel particles in the resin matrix to further reduce the conductivity.The work carried out in this project created an alternative approach to generating and manipulating geometry (shape and size distribution) and spatial position within a representative volume element (RVE) of composites. This has enabled a micro-scale modelling for obtaining such properties as thermal conductivity and modulus of the fibrous matt in itself as well as the particle-filled resin composites. An excellent agreement was found between the modelling results and experimental data.The aim of this project is to develop an analytical tool through Finite Element Method to understand and guide the design of thermal insulation materials. In particular, fibrous mat and aerogel particle-filled resin are focused in the context of subsea pipe-in-pipe (PiP) application for oil and gas extraction. The former has become part of a novel combination with super-insulating material – aerogel, and found its commercial use in the annulus region of the PiP. The latter is considered to be a form of upgrade to the current nylon-based centraliser stabilising the PiP configuration under hydraulic pressure from the deep seawater.The use of porous materials (e.g. fibrous matt and foam) as thermal insulation has a long history, A randomly orientated fibre mat is effective insulation due to the lack of a straight heat conduction pathway and relatively small pores in the fibrous structure. Recent development of super insulating materials involves combining fibrous mat with aerogel, which has resulted in a flexible and less compressible aerogel-fibre blanket with lower thermal conductivity (14 – 20 mw/mK) than typical conventional fibrous counterparts (35 – 50 mw/mK). However, a fundamental understanding of how the fibrous mat interacts the aerogel has not been extensively studied. The use of porous particle-filled resin composites, particularly with aerogel particles, has received less studies in thermal cases and a similar understanding of such integration must be developed in order to inform the design process.The rationale for carrying out this research was to create a range of simulations that can be easily used to predict the effect of changing properties of these above composites on their thermal and mechanical performance. The use of simulations is less time consuming and allows more parameters to be easily varied to see what the optimal fibre design is for specific applications.In order to simulate the effects of varying the composition of the mats, an algorithm to generate a random fibre mat was produced, based on the work of Arambakam and Tafreshi [1]. This fibre positioning was done in MathWorks’ MATLAB, which was used to generate a script for producing a 3D geometry that can be incorporated in ANSYS APDL. This geometry was then used as the basis for a 3D finite element method model that utilised ANSYS Mechanical to mesh and solve the simulation. The same fibre generation process was used for both the mechanical and the thermal simulations, but with the bounding region being differently shaped to accommodate representing the standard experimental techniques used to measure these values.Simulations were carried out to investigate the effect of various parameters of the fibre mat. Specifically, the fibre orientation and the volume fraction of the mat were the main parameters of importance, with the orientation both in and out of the plane of heat transfer being investigated. The ratio of straight fibres to sinusoidal fibres was also investigated as a key parameter affecting the heat transfer, with the volume of straight fibres to total fibre volume being used to determine the “straight fibre fraction” of the fibres. The effect of the fibre length and diameter were also investigated, though it was found that on the scales investigated, they had very little effect on the thermal conductivity.A study into using fully random fibres, where the fibre can be represented by a continuous curve in 3D space that varies in direction throughout the length, was carried out. However, the high level of complexity of this fibre configuration along with the large number of fibre intersections meant that meshing the geometry produced was very difficult. Some successful meshes were produced; however, they included a number of elements that was too large to successfully produce a solution using finite element analysis.For aerogel particle-filled resin, an effort was made to investigate the effect of dispersing particles of aerogel through a resin matrix, in an effort to reduce the thermal conductivity of the matrix. The results of this showed that it was theoretically possible to achieve significantly lower thermal conductivity. The material properties generated from the FE simulations were then used in modelling the centraliser to determine the insulations effectiveness in pipe in pipe insulation. These simulations included the particle simulation data to guide the addition of aerogel particles in the resin matrix to further reduce the conductivity.The work carried out in this project created an alternative approach to generating and manipulating geometry (shape and size distribution) and spatial position within a representative volume element (RVE) of composites. This has enabled a micro-scale modelling for obtaining such properties as thermal conductivity and modulus of the fibrous matt in itself as well as the particle-filled resin composites. An excellent agreement was found between the modelling results and experimental data
Treadmill training augmented with real-time visualisation feedback and function electrical stimulation for gait rehabilitation after stroke : a feasibility study
Get PDFMotor rehabilitation typically requires patients to perform task-specific training, in which biofeedback can be instrumental for encouraging neuroplasticity after stroke. Treadmill training augmented with real-time visual feedback and functional electrical stimulation (FES) may have a beneficial synergistic effect on this process. This study aims to develop a multi-channel FES (MFES) system with stimulation triggers based on the phase of gait cycle, determined using a 3D motion capture system. A feasibility study was conducted to determine whether this enhanced treadmill gait training systemis suitable for stroke survivors in clinical practice. The real-time biomechanical visual feedback system with computerised MFES was developed using six motion-capture cameras installed around a treadmill.;This system was designed to stimulate the pretibial muscle for correcting foot drop problems, gastro-soleus for facilitating push-off, and quadriceps and hamstring for improving knee stability. Dynamic avatar movement and step length/ratio were displayed on a monitor, providing patients with real-time visual biofeedback. Participants received up to 20 minutes of enhanced treadmill training once or twice per week for 6 weeks. Training programme, pre- and post-training ability, and adverse events of each participant were recorded. Feedback was also collected from participants and physiotherapists regarding their experience. Eight out of ten participants fully completed their programme.;In total, 67 training sessions were carried out. All participants had a good attendance rate. The number and duration of training sessions ranged from 5 to 20, and 11 to 20 minutes, respectively. The MFES system successfully improved gait patterns during training, and feedback from participants and physiotherapists regarding their experience of the research intervention was overwhelmingly positive. In conclusion, this enhanced treadmill gait training system is feasible for use in gait rehabilitation after stroke. However, a well-designed clinical trial with a larger sample size is needed to determine clinical efficacy on gait recovery.Motor rehabilitation typically requires patients to perform task-specific training, in which biofeedback can be instrumental for encouraging neuroplasticity after stroke. Treadmill training augmented with real-time visual feedback and functional electrical stimulation (FES) may have a beneficial synergistic effect on this process. This study aims to develop a multi-channel FES (MFES) system with stimulation triggers based on the phase of gait cycle, determined using a 3D motion capture system. A feasibility study was conducted to determine whether this enhanced treadmill gait training systemis suitable for stroke survivors in clinical practice. The real-time biomechanical visual feedback system with computerised MFES was developed using six motion-capture cameras installed around a treadmill.;This system was designed to stimulate the pretibial muscle for correcting foot drop problems, gastro-soleus for facilitating push-off, and quadriceps and hamstring for improving knee stability. Dynamic avatar movement and step length/ratio were displayed on a monitor, providing patients with real-time visual biofeedback. Participants received up to 20 minutes of enhanced treadmill training once or twice per week for 6 weeks. Training programme, pre- and post-training ability, and adverse events of each participant were recorded. Feedback was also collected from participants and physiotherapists regarding their experience. Eight out of ten participants fully completed their programme.;In total, 67 training sessions were carried out. All participants had a good attendance rate. The number and duration of training sessions ranged from 5 to 20, and 11 to 20 minutes, respectively. The MFES system successfully improved gait patterns during training, and feedback from participants and physiotherapists regarding their experience of the research intervention was overwhelmingly positive. In conclusion, this enhanced treadmill gait training system is feasible for use in gait rehabilitation after stroke. However, a well-designed clinical trial with a larger sample size is needed to determine clinical efficacy on gait recovery
COVID-19: Why are the Media Obsessed with Vitamin D?
No full textThe current COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a subject of global concern. On the 30th of January 2020, the World Health Organization (WHO) declared the outbreak of SARS-CoV-2 a public health emergency of international concern, WHO's highest level of alarm (“Timeline: WHO's COVID-19 response”, 2020). As of the 3rd of November 2020, there have been over 46 million confirmed cases ofCOVID-19, including approximately 1.2 million deaths, reported to the WHO with cases exponentially rising on a global scale ("WHO Coronavirus Disease (COVID19) Dashboard", 2020). Due to the rising number of cases, there has been an unprecedented response by governments to slow the incidence of infection and mortality. This response has included large scale efforts across several sectors to develop targeted therapeutics. In that context, one modifiable lifestyle intervention that has received a lot of interest is vitamin D, based on the potential association between vitamin D supplementation and improved healthoutcomes in COVID-19 sufferers. [Abstract from Introduction]The current COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a subject of global concern. On the 30th of January 2020, the World Health Organization (WHO) declared the outbreak of SARS-CoV-2 a public health emergency of international concern, WHO's highest level of alarm (“Timeline: WHO's COVID-19 response”, 2020). As of the 3rd of November 2020, there have been over 46 million confirmed cases ofCOVID-19, including approximately 1.2 million deaths, reported to the WHO with cases exponentially rising on a global scale ("WHO Coronavirus Disease (COVID19) Dashboard", 2020). Due to the rising number of cases, there has been an unprecedented response by governments to slow the incidence of infection and mortality. This response has included large scale efforts across several sectors to develop targeted therapeutics. In that context, one modifiable lifestyle intervention that has received a lot of interest is vitamin D, based on the potential association between vitamin D supplementation and improved healthoutcomes in COVID-19 sufferers. [Abstract from Introduction
Development of electrochemiluminescent sensors as screening tools for the identification of drug species within complex matrices for forensic investigations
No full textAlternative substances of abuse such as novel psychoactive substances (NPS) still pose a significant public health risk, despite increased legislative controls. Therefore, the ability to identify such substances is vital in order to limit their circulation. Current screening methods are often inadequate for NPS and incompatible with a range of complex matrices. As such, it has become necessary to develop a robust screening methodology, applicable to a range of matrices. To this extent, the development of an electrochemiluminescent (ECL) sensor is detailed within, utilising the traditional [Ru(bpy)3]2+ luminophore. The developed sensor was successfully applied for the detection of tropane alkaloids, atropine and scopolamine, at forensically and clinically relevant concentrations within commercial drink samples (tonic water and Coca-Cola®), herbal plant material and biological fluids including human serum, artificial saliva, urine and sweat. Focus was placed upon the ability of the sensor to be utilised by non-experts outwith a laboratory facility.;Hence, all analysis was performed without extraction, purification or separation strategies. The abrasive ECL technique developed, allowed direct detection of the alkaloids, following collection from a roughened skin surface and mechanical application of herbal material, without any surface damage or signal detriment observed. Finally, increased specificity was coined through the development of pH controlled ECL, which facilitated the detection and quantification of scopolamine, in the presence of atropine through suppression of its emission. This provided greater specificity previously unachievable with single luminophore ECL analysis.Alternative substances of abuse such as novel psychoactive substances (NPS) still pose a significant public health risk, despite increased legislative controls. Therefore, the ability to identify such substances is vital in order to limit their circulation. Current screening methods are often inadequate for NPS and incompatible with a range of complex matrices. As such, it has become necessary to develop a robust screening methodology, applicable to a range of matrices. To this extent, the development of an electrochemiluminescent (ECL) sensor is detailed within, utilising the traditional [Ru(bpy)3]2+ luminophore. The developed sensor was successfully applied for the detection of tropane alkaloids, atropine and scopolamine, at forensically and clinically relevant concentrations within commercial drink samples (tonic water and Coca-Cola®), herbal plant material and biological fluids including human serum, artificial saliva, urine and sweat. Focus was placed upon the ability of the sensor to be utilised by non-experts outwith a laboratory facility.;Hence, all analysis was performed without extraction, purification or separation strategies. The abrasive ECL technique developed, allowed direct detection of the alkaloids, following collection from a roughened skin surface and mechanical application of herbal material, without any surface damage or signal detriment observed. Finally, increased specificity was coined through the development of pH controlled ECL, which facilitated the detection and quantification of scopolamine, in the presence of atropine through suppression of its emission. This provided greater specificity previously unachievable with single luminophore ECL analysis
Mathematical modelling of active nematic liquid crystals in confined regions
Get PDFThis thesis focusses on the application of continuum theories and modelling techniques of liquid crystalline fluids to the area of anisotropy and self-organisation derived from active agents. The research involves a continuum description of anisotropic active fluids, using adapted forms of continuum hydrodynamic theories of liquid crystals.;We first consider the director structures of inactive nematic liquid crystals confined in rectangular regions. We use a mixture of analytical and numerical calculations to examine the energies of non-trivial nematic equilibria which exchange stabilities with constant equilibria at critical anchoring strengths. For the remainder of the thesis, we consider active nematic liquid crystals in confined regions.;We first use an adapted Ericksen-Leslie theory to investigate spontaneous flow transitions of active nematics, with the liquid crystal confined in a one-dimensional shallow channel. We examine how internally generated flows induced by activity are affected by externally induced flows due to, pressure gradients and external orienting fields. We then investigate a shallow channel of active nematic in terms of an adapted Q-tensor theory for uniaxial nematic liquid crystals.;Such a model allows for an investigation into the effects of variable ordering caused by changes in the temperature. Finally, we investigate active nematics confined in two-dimensional regions. We first consider wedge geometries containing an active nematic with a singularity at the wedge corner, deriving analytic solutions of a simplified version of the Ericksen-Leslie equations. We then employ numerical calculations to find steady solutions of the full non-linear Ericksen-Leslie equations for active nematics confined in rectangular regions.This thesis focusses on the application of continuum theories and modelling techniques of liquid crystalline fluids to the area of anisotropy and self-organisation derived from active agents. The research involves a continuum description of anisotropic active fluids, using adapted forms of continuum hydrodynamic theories of liquid crystals.;We first consider the director structures of inactive nematic liquid crystals confined in rectangular regions. We use a mixture of analytical and numerical calculations to examine the energies of non-trivial nematic equilibria which exchange stabilities with constant equilibria at critical anchoring strengths. For the remainder of the thesis, we consider active nematic liquid crystals in confined regions.;We first use an adapted Ericksen-Leslie theory to investigate spontaneous flow transitions of active nematics, with the liquid crystal confined in a one-dimensional shallow channel. We examine how internally generated flows induced by activity are affected by externally induced flows due to, pressure gradients and external orienting fields. We then investigate a shallow channel of active nematic in terms of an adapted Q-tensor theory for uniaxial nematic liquid crystals.;Such a model allows for an investigation into the effects of variable ordering caused by changes in the temperature. Finally, we investigate active nematics confined in two-dimensional regions. We first consider wedge geometries containing an active nematic with a singularity at the wedge corner, deriving analytic solutions of a simplified version of the Ericksen-Leslie equations. We then employ numerical calculations to find steady solutions of the full non-linear Ericksen-Leslie equations for active nematics confined in rectangular regions
Sex-influenced histopathological changes and the immunity during Toxoplasma gondii infection
Get PDFThis thesis was previously held under moratorium from 8th April 2020 until 8th April 2022Studies indicate female mice are more susceptible to T. gondii infection in comparison to male mice. The following studies were undertaken to enhance our understanding about the influence of sex in the immune response during T. gondii infection and the disease outcome in BALB/c mice. Early parasite replication and immunological events were studied in parallel through applying an in vivo imaging system (IVIS) with luciferase expressing T. gondii and a cytometric bead array to quantify key immunological mediators. The results confirmed female mice to be more susceptible to acute infection, as determined by higher mortality rates and weight loss compared with males. However, conflicting with expectations female mice had lower parasite burdens during the acute infection than male mice. Female mice also exhibited a significantly increased production of MCP-1, IFN-y and TNF-a than male mice. These results suggest that a stronger immune response in females results in better parasite control, but has detrimental effects on health and mortality. Brain tissue of male and female mice chronically infected with T. gondii cysts were compared by using histopathological examination and RNAseq technologies to determine transcriptomic changes. The data indicate that female mice had increased pathology and developed more tissue cysts. The transcript analysis indicate that infected females had increased transcript levels of genes associated with PI3K/AKT/mTOR pathway, T cell exhaustion and apoptosis/pyroptosis. Consistent with these observations, female mice developed greater levels of DNA fragmentation as determined by TUNNEL and increased expression of NLRP3 in their brains. Overall, the results suggest that female mice mount a stronger immune response that controls parasite levels, but causes increased weight loss and mortality. In addition, the increased inflammation in the early stages of infection might account for the increased markers of T cell exhaustion that correlates with increased pathology in brains of female mice during T. gondii chronic stage.Studies indicate female mice are more susceptible to T. gondii infection in comparison to male mice. The following studies were undertaken to enhance our understanding about the influence of sex in the immune response during T. gondii infection and the disease outcome in BALB/c mice. Early parasite replication and immunological events were studied in parallel through applying an in vivo imaging system (IVIS) with luciferase expressing T. gondii and a cytometric bead array to quantify key immunological mediators. The results confirmed female mice to be more susceptible to acute infection, as determined by higher mortality rates and weight loss compared with males. However, conflicting with expectations female mice had lower parasite burdens during the acute infection than male mice. Female mice also exhibited a significantly increased production of MCP-1, IFN-y and TNF-a than male mice. These results suggest that a stronger immune response in females results in better parasite control, but has detrimental effects on health and mortality. Brain tissue of male and female mice chronically infected with T. gondii cysts were compared by using histopathological examination and RNAseq technologies to determine transcriptomic changes. The data indicate that female mice had increased pathology and developed more tissue cysts. The transcript analysis indicate that infected females had increased transcript levels of genes associated with PI3K/AKT/mTOR pathway, T cell exhaustion and apoptosis/pyroptosis. Consistent with these observations, female mice developed greater levels of DNA fragmentation as determined by TUNNEL and increased expression of NLRP3 in their brains. Overall, the results suggest that female mice mount a stronger immune response that controls parasite levels, but causes increased weight loss and mortality. In addition, the increased inflammation in the early stages of infection might account for the increased markers of T cell exhaustion that correlates with increased pathology in brains of female mice during T. gondii chronic stage
A methodology for the experimental characterisation and computational modelling of Nitinol wires used in stent-graft devices
Get PDFStent-grafts are medical devices designed to treat abdominal aortic aneurysms (AAAs). These devices are usually composed of a Nitinol wireframe and a fabric graft. The design of next generation stent-grafts is directed towards a very low-profile when compacted. Such devices can treat narrow access vessels and tortuous anatomies while inducing less trauma to patients. Therefore, Nitinol stents are required to undergo greater deformations during manufacture without compromising the performance and durability of the medical device.Experimental characterisation of the material is required to demonstrate its mechanical behavioural characteristics. Since Nitinol wires are subjected to multi-mode loading conditions, investigation should incorporate all loading modes and thermomechanical conditions that a device encounters during its life cycle. The resulting data can then enable the derivation of the material’s constitutive properties which are necessary for computational analyses. Finite element analysis (FEA) has become an integral part of the design of medical devices and computational analyses reports are used nowadays as scientific evidence to support medical device submissions. The Nitinol constitutive model that is implemented in the finite element software Abaqus is considered the industry standard. However, its capabilities and limitations are not fully explored since there are no experimental data available for this purpose.In the present work, a methodology was developed to characterise medical grade Nitinol wires in tension, compression, bending and torsion. The mechanical behaviour of the material was examined under high-strain tensile deformation. The relevant constitutive parameters were identified from the experimental results and the Abaqus Nitinol model was assessed, including its superelastic-plastic modelling capabilities, by simulating the mechanical tests of all loading modes. The key findings from the present work are summarised below.High straining of the material during compaction results in decreased austenite stiffness, decreased load and unload plateaus and increased residual strain. These features are more pronounced when multiple compaction attempts take place. A recommendation is made, to limit the compaction strain to 10%, if possible. This is because if more than one compaction attempts take place at 10% strain, the effect on the unload plateau, which influences the radial strength of the stent, will be small. In addition, up to 10% compaction strain there is only a small, gradual increase of residual strain. The bending response of the material is load-rate sensitive. Therefore, compaction should take place slowly in order to avoid potential rate effects. Sterilization is not expected to have a negative impact on the stress levels experienced by Nitinol wires during this process, since temperature sensitivity was not observed within the post-transformation region.The Abaqus Nitinol model provided results that were in agreement with the experiments when modelling tension within the superelastic range, as only minor qualitative differences were identified between computational and experimental responses. However, the material model was incapable of forecasting the sensitivity of the unload plateau to the high strain loading. The present work shows that this limitation can be overcome by implementing Fortran subroutines that modify the transformation stresses during unloading as a function of the plastic strain reached during the simulation. Tension-compression asymmetry was also exhibited in the FEA results. The austenite stiffness and the start of the transformation during loading in compression agreed quantitatively with the experimental results, exhibiting negligible errors. However, the unloading transformation stresses in compression were underpredicted by up to 36.6% compared to the experimental data.The flexural stiffness of austenite was also underestimated in the computational bending responses by up to 28.8%, although the transformation during loading started at the same force levels for FEA and experimental results. Results show that the loading path of the bending response can be improved if the flexural modulus of austenite is used as input parameter. However, the unloading path of the bending response was not captured correctly since it took place at lower forces compared to the experimental curves. The computational response in torsion was also not in agreement with the experimental results, as the torsional stiffness was underestimated by 11.2% while the loading and unloading paths took place in lower load levels. The model however, was able to capture the qualitative features of the combined tension-torsion deformation.Stent-grafts are medical devices designed to treat abdominal aortic aneurysms (AAAs). These devices are usually composed of a Nitinol wireframe and a fabric graft. The design of next generation stent-grafts is directed towards a very low-profile when compacted. Such devices can treat narrow access vessels and tortuous anatomies while inducing less trauma to patients. Therefore, Nitinol stents are required to undergo greater deformations during manufacture without compromising the performance and durability of the medical device.Experimental characterisation of the material is required to demonstrate its mechanical behavioural characteristics. Since Nitinol wires are subjected to multi-mode loading conditions, investigation should incorporate all loading modes and thermomechanical conditions that a device encounters during its life cycle. The resulting data can then enable the derivation of the material’s constitutive properties which are necessary for computational analyses. Finite element analysis (FEA) has become an integral part of the design of medical devices and computational analyses reports are used nowadays as scientific evidence to support medical device submissions. The Nitinol constitutive model that is implemented in the finite element software Abaqus is considered the industry standard. However, its capabilities and limitations are not fully explored since there are no experimental data available for this purpose.In the present work, a methodology was developed to characterise medical grade Nitinol wires in tension, compression, bending and torsion. The mechanical behaviour of the material was examined under high-strain tensile deformation. The relevant constitutive parameters were identified from the experimental results and the Abaqus Nitinol model was assessed, including its superelastic-plastic modelling capabilities, by simulating the mechanical tests of all loading modes. The key findings from the present work are summarised below.High straining of the material during compaction results in decreased austenite stiffness, decreased load and unload plateaus and increased residual strain. These features are more pronounced when multiple compaction attempts take place. A recommendation is made, to limit the compaction strain to 10%, if possible. This is because if more than one compaction attempts take place at 10% strain, the effect on the unload plateau, which influences the radial strength of the stent, will be small. In addition, up to 10% compaction strain there is only a small, gradual increase of residual strain. The bending response of the material is load-rate sensitive. Therefore, compaction should take place slowly in order to avoid potential rate effects. Sterilization is not expected to have a negative impact on the stress levels experienced by Nitinol wires during this process, since temperature sensitivity was not observed within the post-transformation region.The Abaqus Nitinol model provided results that were in agreement with the experiments when modelling tension within the superelastic range, as only minor qualitative differences were identified between computational and experimental responses. However, the material model was incapable of forecasting the sensitivity of the unload plateau to the high strain loading. The present work shows that this limitation can be overcome by implementing Fortran subroutines that modify the transformation stresses during unloading as a function of the plastic strain reached during the simulation. Tension-compression asymmetry was also exhibited in the FEA results. The austenite stiffness and the start of the transformation during loading in compression agreed quantitatively with the experimental results, exhibiting negligible errors. However, the unloading transformation stresses in compression were underpredicted by up to 36.6% compared to the experimental data.The flexural stiffness of austenite was also underestimated in the computational bending responses by up to 28.8%, although the transformation during loading started at the same force levels for FEA and experimental results. Results show that the loading path of the bending response can be improved if the flexural modulus of austenite is used as input parameter. However, the unloading path of the bending response was not captured correctly since it took place at lower forces compared to the experimental curves. The computational response in torsion was also not in agreement with the experimental results, as the torsional stiffness was underestimated by 11.2% while the loading and unloading paths took place in lower load levels. The model however, was able to capture the qualitative features of the combined tension-torsion deformation
Is virtue its own reward? : Exploring philanthropic family foundations & the two faces of altruism
Get PDFPreviously held under moratorium from 25th March 2021 until 1st November 2022.Located at the nexus of family business and philanthropy research, this study explores thedynamics and influences that combine to shape giving within Philanthropic FamilyFoundations (PFFs). These under-researched organisations represent one structured vesselthrough which successful family enterprises can contribute to society beyond the commercialobjectives of wealth creation and economic development. Recognising the distinctiveness oftheir familial roots and commercial genesis, this study argues that PFFs can provide furtherinsights into the relationship between the accumulation and redistribution of privately-heldwealth. It therefore seeks to provide greater clarity to extant understanding of family businessphilanthropy by exploring issues pertaining to the extent to which ‘family’ influencescontemporary PFF grant-making; succession and intergenerational transfer;conceptualisations of successful philanthropy; and the motivations underpinning thedivestment of privately-held familial wealth.Consistent with the exploratory nature of the study, a qualitative approach underpinned bymultiple case studies is used to provide nascent insights into contemporary PFF giving. Indepth, semi-structured interviews with key decision-makers within UK-based PFFs wereundertaken. Additionally, secondary data (including, for example: trust deeds, archivaldocuments, internal publications, and press releases) was used to support the development of14 case studies of UK-based PFFs. This followed an inductive approach, with analysisconducted within and across cases. Subsequently, findings from an extensive cross-caseanalysis into the dynamics and influences of contemporary PFF grant-making are discussedwithin this thesis.Accordingly, this study identifies a number of factors that combine to shape contemporaryPFF giving, with the influence of ‘family’ and the distinctiveness of this mode ofphilanthropy emerging in a number of interesting ways. In doing so, it contributes to extantunderstanding of family enterprise philanthropy, conceptualising PFFs as familialorganisations unburdened by the long-term orientation typical of their family businesscounterparts, resulting in a form of philanthropy that eschews some expected organisationalreturns in favour of involvement, engagement, learning, and ultimately, emotionalalternatives.Located at the nexus of family business and philanthropy research, this study explores thedynamics and influences that combine to shape giving within Philanthropic FamilyFoundations (PFFs). These under-researched organisations represent one structured vesselthrough which successful family enterprises can contribute to society beyond the commercialobjectives of wealth creation and economic development. Recognising the distinctiveness oftheir familial roots and commercial genesis, this study argues that PFFs can provide furtherinsights into the relationship between the accumulation and redistribution of privately-heldwealth. It therefore seeks to provide greater clarity to extant understanding of family businessphilanthropy by exploring issues pertaining to the extent to which ‘family’ influencescontemporary PFF grant-making; succession and intergenerational transfer;conceptualisations of successful philanthropy; and the motivations underpinning thedivestment of privately-held familial wealth.Consistent with the exploratory nature of the study, a qualitative approach underpinned bymultiple case studies is used to provide nascent insights into contemporary PFF giving. Indepth, semi-structured interviews with key decision-makers within UK-based PFFs wereundertaken. Additionally, secondary data (including, for example: trust deeds, archivaldocuments, internal publications, and press releases) was used to support the development of14 case studies of UK-based PFFs. This followed an inductive approach, with analysisconducted within and across cases. Subsequently, findings from an extensive cross-caseanalysis into the dynamics and influences of contemporary PFF grant-making are discussedwithin this thesis.Accordingly, this study identifies a number of factors that combine to shape contemporaryPFF giving, with the influence of ‘family’ and the distinctiveness of this mode ofphilanthropy emerging in a number of interesting ways. In doing so, it contributes to extantunderstanding of family enterprise philanthropy, conceptualising PFFs as familialorganisations unburdened by the long-term orientation typical of their family businesscounterparts, resulting in a form of philanthropy that eschews some expected organisationalreturns in favour of involvement, engagement, learning, and ultimately, emotionalalternatives
The impacts of energy systems and services on sustainable development in developing countries
Get PDFThis thesis was previously held under moratorium from 1st February 2021 until 1st February 2023Enabling access to energy has been recognised as vital in addressing many of the present global development issues which affect people’s economic, health and social well-being as well as the ability to meet the goal of reducing carbon emissions through clean energy use. Lack of access to energy, termed energy poverty, in the developing world has several key aspects – lack of access on demand to electricity is one aspect, but lack of access to clean cooking fuels is also a critical factor that leads to continued use of solid fuels. Yet, in spite of increased attention from multiple agencies and governments on the energy poverty issue, the strong praise for action, and the deployment of largescaleenergy programs and interventions, lack of access to clean cooking fuels continues to be an overlooked aspect of the energy poverty. Currently, over 2.8 billion people lack access to clean energy for cooking. However, despite this, few studies have shed light on the barriers to, the enablers of, and the impacts of inaccessibility to clean cooking alternatives on development outcomes, using rigorous methodologies. This thesis addresses this recent strand of research. The contributions of this thesis are multi-fold. Firstly, it performs and presents the results of the first quantitative analyses which examine the impacts of household use of solid fuels on the economic and social pillars of sustainable developments: in the most impoverished countries. Secondly, it provides evidences of the effects of current non-energy policies and interventions on addressing the issue. Lastly, it reviews the trends of and barriers to household accessibility to clean cooking fuels. The results obtained from the analyses vary across the countries investigated but generally speaking, it is observed that the household use of solid fuels significantly affects aspects of sustainable development such as education and life expectancy.Enabling access to energy has been recognised as vital in addressing many of the present global development issues which affect people’s economic, health and social well-being as well as the ability to meet the goal of reducing carbon emissions through clean energy use. Lack of access to energy, termed energy poverty, in the developing world has several key aspects – lack of access on demand to electricity is one aspect, but lack of access to clean cooking fuels is also a critical factor that leads to continued use of solid fuels. Yet, in spite of increased attention from multiple agencies and governments on the energy poverty issue, the strong praise for action, and the deployment of largescaleenergy programs and interventions, lack of access to clean cooking fuels continues to be an overlooked aspect of the energy poverty. Currently, over 2.8 billion people lack access to clean energy for cooking. However, despite this, few studies have shed light on the barriers to, the enablers of, and the impacts of inaccessibility to clean cooking alternatives on development outcomes, using rigorous methodologies. This thesis addresses this recent strand of research. The contributions of this thesis are multi-fold. Firstly, it performs and presents the results of the first quantitative analyses which examine the impacts of household use of solid fuels on the economic and social pillars of sustainable developments: in the most impoverished countries. Secondly, it provides evidences of the effects of current non-energy policies and interventions on addressing the issue. Lastly, it reviews the trends of and barriers to household accessibility to clean cooking fuels. The results obtained from the analyses vary across the countries investigated but generally speaking, it is observed that the household use of solid fuels significantly affects aspects of sustainable development such as education and life expectancy
A compound novel data-driven and reliability-based predictive maintenance framework for ship machinery systems
Get PDFShipping is a major driving force of the global economy, as seen by the 90% of the volume of the yearly trade transported by ships. As a result, shipping has a significant financial, environmental impact. Maritime maintenance can be used to safeguard shipping’s impact by improving safety and avoiding accidents. This is especially true, when considering that nearly 22% of all the accidents between 2011 and 2017 were attributed to improper maintenance. Consequently, maritime maintenance can be used as a hazard mitigation tool, improve ship safety by reducing accidents. Modern maritime maintenance is best applied through predictive maintenance schemes, which take advantage of the developments of Shipping 4.0. Under this scope, the goal of this thesis is the development of a compound novel data-driven and reliability-based predictive maintenance framework for ship machinery system. The novel framework tackles the areas of maritime predictive maintenance holistically by addressing the topics of critical equipment selection, data preparation, fault detection and diagnostics. Each of the framework’s topics are developed in individual methodologies and assessed in unique case studies demonstrating their effectiveness in the respective tasks. Initially, the methodology for the critical equipment selection includes the novel combination of Fault Tree Analysis with data clustering for the identification of critical equipment, as applied in the case of an LNG Carrier. As a result, the most critical components are identified by taking into account reliability indices and repair costs for the considered components. Identifying critical components improves safety, as it focuses the maintenance efforts in items whose failures can have economic consequences and safety implications. Next, the methodology for the data preparation is developed, which includes the novel integration of the kNN and MICE algorithms for the imputation of missing data. Combining these two algorithms al lows for the novel integration a data-driven approach with domain knowledge in a single imputation model. The imputation methodology is applied in the case of a Chemical Tanker, showcasing the effectiveness of the novel method against a pure MICE and pure kNN approach. The treatment of missing values can improve ship safety, as it safeguards information contained within datasets and leads to more accurate condition assessing models. Following that, a novel Fault Detection methodology is established based on Expected Behaviour models, using Machine Learning, and Exponentially Weighted Moving Average control charts. This methodology aims at detecting developing faults in their early stages while avoiding the shortcomings of black-box approaches and having reasonable data requirements for training. Lastly, the diagnostics methodology is formed, which includes the novel integration of pre-processing and Machine Learning-based Fault detection with a diagnostic network using Bayesian Networks. The resulting methodology can identify the root cause of a detected fault, without using black-box Neural Network approaches, nor complicated and time-consuming physics-based models. Even though the Fault Detection and diagnostics methodologies are developed individually, they are both evaluated in the same case of a Bulk Carrier. The use of the same case study was dictated by restrictions in collecting additional data and by the use of the output of the Fault Detection methodology in the diagnostics. The detection of developing faults and the identification of their root-cause has a profound effect on ship safety, while also allowing for targeted maintenance actions.Shipping is a major driving force of the global economy, as seen by the 90% of the volume of the yearly trade transported by ships. As a result, shipping has a significant financial, environmental impact. Maritime maintenance can be used to safeguard shipping’s impact by improving safety and avoiding accidents. This is especially true, when considering that nearly 22% of all the accidents between 2011 and 2017 were attributed to improper maintenance. Consequently, maritime maintenance can be used as a hazard mitigation tool, improve ship safety by reducing accidents. Modern maritime maintenance is best applied through predictive maintenance schemes, which take advantage of the developments of Shipping 4.0. Under this scope, the goal of this thesis is the development of a compound novel data-driven and reliability-based predictive maintenance framework for ship machinery system. The novel framework tackles the areas of maritime predictive maintenance holistically by addressing the topics of critical equipment selection, data preparation, fault detection and diagnostics. Each of the framework’s topics are developed in individual methodologies and assessed in unique case studies demonstrating their effectiveness in the respective tasks. Initially, the methodology for the critical equipment selection includes the novel combination of Fault Tree Analysis with data clustering for the identification of critical equipment, as applied in the case of an LNG Carrier. As a result, the most critical components are identified by taking into account reliability indices and repair costs for the considered components. Identifying critical components improves safety, as it focuses the maintenance efforts in items whose failures can have economic consequences and safety implications. Next, the methodology for the data preparation is developed, which includes the novel integration of the kNN and MICE algorithms for the imputation of missing data. Combining these two algorithms al lows for the novel integration a data-driven approach with domain knowledge in a single imputation model. The imputation methodology is applied in the case of a Chemical Tanker, showcasing the effectiveness of the novel method against a pure MICE and pure kNN approach. The treatment of missing values can improve ship safety, as it safeguards information contained within datasets and leads to more accurate condition assessing models. Following that, a novel Fault Detection methodology is established based on Expected Behaviour models, using Machine Learning, and Exponentially Weighted Moving Average control charts. This methodology aims at detecting developing faults in their early stages while avoiding the shortcomings of black-box approaches and having reasonable data requirements for training. Lastly, the diagnostics methodology is formed, which includes the novel integration of pre-processing and Machine Learning-based Fault detection with a diagnostic network using Bayesian Networks. The resulting methodology can identify the root cause of a detected fault, without using black-box Neural Network approaches, nor complicated and time-consuming physics-based models. Even though the Fault Detection and diagnostics methodologies are developed individually, they are both evaluated in the same case of a Bulk Carrier. The use of the same case study was dictated by restrictions in collecting additional data and by the use of the output of the Fault Detection methodology in the diagnostics. The detection of developing faults and the identification of their root-cause has a profound effect on ship safety, while also allowing for targeted maintenance actions
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