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A graphical framework for component selection in mechatronic design of robotic systems
Get PDFThe successful function of complex engineering systems, particularly those which provide a dynamic performance capability to a system, is usually largely dependent on the correct specification and selection of components to be used in that system. Whilst material selection and part design for housings, etc. are critical tasks, in any system required to provide some physical capability (displacement, pressure, measurement capability, etc.) it is entirely likely that components selected to achieve this - such as motors, bearings, etc. - will be instrumental in defining the extent to which performance goals are met for that system. Unlike material selection and part design tasks, there are noted to be markedly fewer strategies and methods to support engineers through successful and effective completion of this task. Despite acknowledgement of the absolute significance of this task and the outputs it yields in many design methodologies, academic literature which explores this topic is found to be limited. Commercial solutions to the problem are also found to have various issues, as is explored in this project. The components selected in a system have an extremely large role to play in the capability of the system to perform as needed, therefore providence of solutions which improve the effectiveness of engineers in effective completion of this task are argued to be of upmost significance. At its core, this thesis contributes a framework to support component selection in the design of mechatronic actuators, supporting a process where step-by-step guidance is offered through concept and embodiment design stages. Underlying the core framework and its process guidance, a number of other novel methods are proposed as a means to enhance effectiveness and efficiency in approaching and completing discrete tasks within the overall selection procedure. In this thesis, particular focus is given to the use of a novel graphical method of conveying component performance criteria in a way which supports informative and intuitive interrogation of the information they present. Application of the framework is completed in the context of mechatronic actuators utilised in robotic sub-systems. The contributed framework is assessed through 3 separate case studies undertaken to assess the effectiveness of this approach. These case studies vary in use case and requirement, allowing the adaptability of the proposed approach to be assessed. From these case studies, analysis takes place through discussion, simulation, and physical testing of the developed systems, allowing for a wealth of qualitative and quantitative information to be gathered upon which assertions can be made. Discussion is presented surrounding the overall performance, and conclusions are delivered to provide a verdict on the interpretations of the solution's effectiveness.The successful function of complex engineering systems, particularly those which provide a dynamic performance capability to a system, is usually largely dependent on the correct specification and selection of components to be used in that system. Whilst material selection and part design for housings, etc. are critical tasks, in any system required to provide some physical capability (displacement, pressure, measurement capability, etc.) it is entirely likely that components selected to achieve this - such as motors, bearings, etc. - will be instrumental in defining the extent to which performance goals are met for that system. Unlike material selection and part design tasks, there are noted to be markedly fewer strategies and methods to support engineers through successful and effective completion of this task. Despite acknowledgement of the absolute significance of this task and the outputs it yields in many design methodologies, academic literature which explores this topic is found to be limited. Commercial solutions to the problem are also found to have various issues, as is explored in this project. The components selected in a system have an extremely large role to play in the capability of the system to perform as needed, therefore providence of solutions which improve the effectiveness of engineers in effective completion of this task are argued to be of upmost significance. At its core, this thesis contributes a framework to support component selection in the design of mechatronic actuators, supporting a process where step-by-step guidance is offered through concept and embodiment design stages. Underlying the core framework and its process guidance, a number of other novel methods are proposed as a means to enhance effectiveness and efficiency in approaching and completing discrete tasks within the overall selection procedure. In this thesis, particular focus is given to the use of a novel graphical method of conveying component performance criteria in a way which supports informative and intuitive interrogation of the information they present. Application of the framework is completed in the context of mechatronic actuators utilised in robotic sub-systems. The contributed framework is assessed through 3 separate case studies undertaken to assess the effectiveness of this approach. These case studies vary in use case and requirement, allowing the adaptability of the proposed approach to be assessed. From these case studies, analysis takes place through discussion, simulation, and physical testing of the developed systems, allowing for a wealth of qualitative and quantitative information to be gathered upon which assertions can be made. Discussion is presented surrounding the overall performance, and conclusions are delivered to provide a verdict on the interpretations of the solution's effectiveness
Adaptive task planning and motion planning for robots in dynamic environments
Get PDFEmerging applications involving a high degree of uncertainty, dynamics, variability and unpredictability have begun to impart greater complexity to tasks performed by robots. In these kinds of environments, one of the most common causes for robot failures has been linked to the inability of the underlying planner to adapt to changing conditions in the environment. While an extensive range of methods have been developed to solve static planning problems in the robotics domain, until now solving the dynamic counterparts of these problems remain mostly elusive. Motivated by these challenges, this thesis presents developments that advance the state-of-the-art in optimal task and motion planning to address the dynamic variant of common robotic planning problems. Studies into adaptive planning problems are conducted to investigate the challenges that arise when extending planning methods from offline planning to online planning. In particular, this research seeks to characterise the interactions between plan quality and computational efficiency when solving dynamic planning problems and to identify the practical considerations for implementing adaptive planning algorithms in physical systems. The contributions of this thesis are a number of fast yet practical planning techniques and methods that provide and maintain near-optimal, collision-free solutions to complex planning problems involving dynamic environments. In this thesis I first describe a case study that examines the challenges unique to dynamic motion planning through a robotic pick and place task. The observations derived from this case study inspired the development of two new methods for solving complex task planning problems. The first of these is an adaptive task and path planning framework that addresses the optimal task planning problem for mobile robots under dynamic conditions. This framework integrates a sampling-based multi-goal path planning algorithm with symbolic task planning to incrementally find high-quality task plans. Crucially, the framework supports anytime-like planning and dynamic re-planning of both tasks and low-level motions to enable fast and adaptive computation of optimal solutions. To support this, a tree pruning technique is proposed for multi-goal planning problems to substantially reduce the time and memory complexity of the planner. In the second half of this thesis, I present a highly competitive clustering-based algorithm for robotic task sequencing problems (RTSPs). Unlike existing methods, the algorithm is capable of finding near-optimal solutions for complex tasks involving hard spatial constraints. With a view towards dynamic robotic task sequencing, I go on to introduce two new concepts to the RTSP. The first is partial planning, which adopts the idea of planning-during-execution to reduce the pre-execution planning time of an algorithm for online applications. The second is the concept of dynamic RTSPs, a new sub-class of RTSPs that involve dynamically-changing problem variables. I subsequently present an adaptive algorithm for online tracking of near-optimal RTSP solutions under dynamic influences. As a pioneering work within the scope of dynamic task sequencing, I provide a quantitative evaluation of the algorithm for the purpose of benchmarking in future developments.Emerging applications involving a high degree of uncertainty, dynamics, variability and unpredictability have begun to impart greater complexity to tasks performed by robots. In these kinds of environments, one of the most common causes for robot failures has been linked to the inability of the underlying planner to adapt to changing conditions in the environment. While an extensive range of methods have been developed to solve static planning problems in the robotics domain, until now solving the dynamic counterparts of these problems remain mostly elusive. Motivated by these challenges, this thesis presents developments that advance the state-of-the-art in optimal task and motion planning to address the dynamic variant of common robotic planning problems. Studies into adaptive planning problems are conducted to investigate the challenges that arise when extending planning methods from offline planning to online planning. In particular, this research seeks to characterise the interactions between plan quality and computational efficiency when solving dynamic planning problems and to identify the practical considerations for implementing adaptive planning algorithms in physical systems. The contributions of this thesis are a number of fast yet practical planning techniques and methods that provide and maintain near-optimal, collision-free solutions to complex planning problems involving dynamic environments. In this thesis I first describe a case study that examines the challenges unique to dynamic motion planning through a robotic pick and place task. The observations derived from this case study inspired the development of two new methods for solving complex task planning problems. The first of these is an adaptive task and path planning framework that addresses the optimal task planning problem for mobile robots under dynamic conditions. This framework integrates a sampling-based multi-goal path planning algorithm with symbolic task planning to incrementally find high-quality task plans. Crucially, the framework supports anytime-like planning and dynamic re-planning of both tasks and low-level motions to enable fast and adaptive computation of optimal solutions. To support this, a tree pruning technique is proposed for multi-goal planning problems to substantially reduce the time and memory complexity of the planner. In the second half of this thesis, I present a highly competitive clustering-based algorithm for robotic task sequencing problems (RTSPs). Unlike existing methods, the algorithm is capable of finding near-optimal solutions for complex tasks involving hard spatial constraints. With a view towards dynamic robotic task sequencing, I go on to introduce two new concepts to the RTSP. The first is partial planning, which adopts the idea of planning-during-execution to reduce the pre-execution planning time of an algorithm for online applications. The second is the concept of dynamic RTSPs, a new sub-class of RTSPs that involve dynamically-changing problem variables. I subsequently present an adaptive algorithm for online tracking of near-optimal RTSP solutions under dynamic influences. As a pioneering work within the scope of dynamic task sequencing, I provide a quantitative evaluation of the algorithm for the purpose of benchmarking in future developments
An investigation of relational behaviours and supply chain risk information sharing : a mixed method study of firms in Nigeria
Get PDFSupply chain risk information sharing is one of the proactive strategies for mitigating risks and making supply chains more resilient. The ability to sense threats before they disrupt the supply chain is strengthened by risk information from supply chain partners and other stakeholders who are usually not mandated to share risk information. This study responds to calls (Sheffi and Rice Jr., 2005; Juttner and Maklan, 2011; Johnson, Elliott and Drake, 2013) for advancing the research on supply chain risk management especially in the developing country context which Tukamuhabwa, Stevenson and Busby(2017) argues that the way in which threats are handled may differ. Antecedents such as trust, relationship length, commitment and reciprocity have been identified as relational enablers in the literature; however, they might not be sufficient or be the only enablers for firms to share supply chain risk information from the onset of a supply chain relationship, especially in the context of Nigeria. Apart from the cultural peculiarities of Nigeria, which affect business practices and relationships, there is on-going insurgency in the North-east and other human-made risk events that disrupt supply chains in the country. Hence, there is the need to carry out research of this kind that investigates how firms in Nigeria mitigate supply chain risk by leveraging on their informal relationships to share and receive risk information.;This thesis addresses this research gap by first focussing on collecting qualitative data through semistructured interviews from supply chain managers, about the relational behaviours they leverage for supply chain risk information sharing. Data from the interviews were transcribed and coded for thematic analysis. Three propositions relating to relational closeness, relational incentive, and collective prosperity emerged. Subsequently, the result of the qualitative strand was used to develop a survey instrument and was administered to members of the Chartered Institute of Procurement and Supply in Nigeria. Data for the quantitative strand was collected through an online and self-administered questionnaire. Partial least squares structural equation modelling was used to analyse the quantitative data. The result indicated that relational closeness and collective prosperity have a significant influence on supply chain risk information sharing. However, the result does not find support for the relationship between relational incentive and supply chain risk information sharing. A mixed method discussion was further presented to explain how the quantitative findings generalised the qualitative result.;The originality of this research lies in its attempt to integrate social capital and social network theories with supply chain management literature to create new knowledge of how to mitigate supply chain risk in the Nigerian context. The overall theoretical implication of this study is that it contributes to supply chain management literature by identifying new relational attributes that are vital in enhancing supply chain risk information sharing. Regarding the managerial implication, this research highlights the need to consider investing in social relationships, particularly through relational closeness and collective prosperity as a means of receiving and sharing supply chain risk information in the sample firms. Although the findings of this study are only generalised to the sample, the findings could be insightful to multinational firms operating or expanding their supply chain to Nigeria on the need to enhance relational closeness and collective prosperity for supply chain risk information sharing. In light of the findings of this study, limitations and areas for future research were outlined.Supply chain risk information sharing is one of the proactive strategies for mitigating risks and making supply chains more resilient. The ability to sense threats before they disrupt the supply chain is strengthened by risk information from supply chain partners and other stakeholders who are usually not mandated to share risk information. This study responds to calls (Sheffi and Rice Jr., 2005; Juttner and Maklan, 2011; Johnson, Elliott and Drake, 2013) for advancing the research on supply chain risk management especially in the developing country context which Tukamuhabwa, Stevenson and Busby(2017) argues that the way in which threats are handled may differ. Antecedents such as trust, relationship length, commitment and reciprocity have been identified as relational enablers in the literature; however, they might not be sufficient or be the only enablers for firms to share supply chain risk information from the onset of a supply chain relationship, especially in the context of Nigeria. Apart from the cultural peculiarities of Nigeria, which affect business practices and relationships, there is on-going insurgency in the North-east and other human-made risk events that disrupt supply chains in the country. Hence, there is the need to carry out research of this kind that investigates how firms in Nigeria mitigate supply chain risk by leveraging on their informal relationships to share and receive risk information.;This thesis addresses this research gap by first focussing on collecting qualitative data through semistructured interviews from supply chain managers, about the relational behaviours they leverage for supply chain risk information sharing. Data from the interviews were transcribed and coded for thematic analysis. Three propositions relating to relational closeness, relational incentive, and collective prosperity emerged. Subsequently, the result of the qualitative strand was used to develop a survey instrument and was administered to members of the Chartered Institute of Procurement and Supply in Nigeria. Data for the quantitative strand was collected through an online and self-administered questionnaire. Partial least squares structural equation modelling was used to analyse the quantitative data. The result indicated that relational closeness and collective prosperity have a significant influence on supply chain risk information sharing. However, the result does not find support for the relationship between relational incentive and supply chain risk information sharing. A mixed method discussion was further presented to explain how the quantitative findings generalised the qualitative result.;The originality of this research lies in its attempt to integrate social capital and social network theories with supply chain management literature to create new knowledge of how to mitigate supply chain risk in the Nigerian context. The overall theoretical implication of this study is that it contributes to supply chain management literature by identifying new relational attributes that are vital in enhancing supply chain risk information sharing. Regarding the managerial implication, this research highlights the need to consider investing in social relationships, particularly through relational closeness and collective prosperity as a means of receiving and sharing supply chain risk information in the sample firms. Although the findings of this study are only generalised to the sample, the findings could be insightful to multinational firms operating or expanding their supply chain to Nigeria on the need to enhance relational closeness and collective prosperity for supply chain risk information sharing. In light of the findings of this study, limitations and areas for future research were outlined
Accommodating maintenance in prognostics
Get PDFSteam turbines are an important asset of nuclear power plants, and are required tooperate reliably and efficiently. Unplanned outages have a significant impact on theability of the plant to generate electricity. Therefore, condition-based maintenance (CBM)can be used for predictive and proactive maintenance to avoid unplanned outages whilereducing operating costs and increasing the reliability and availability of the plant. InCBM, the information gathered can be interpreted for prognostics (the prediction offailure time or remaining useful life (RUL)).The aim of this project was to address two areas of challenges in prognostics, theselection of predictive technique and accommodation of post-maintenance effects, toimprove the efficacy of prognostics. The selection of an appropriate predictive algorithmis a key activity for an effective development of prognostics. In this research, a formalapproach for the evaluation and selection of predictive techniques is developed tofacilitate a methodic selection process of predictive techniques by engineering experts.This approach is then implemented for a case study provided by the engineering experts.Therefore, as a result of formal evaluation, a probabilistic technique the Bayesian LinearRegression (BLR) and a non-probabilistic technique the Support Vector Regression (SVR)were selected for prognostics implementation.In this project, the knowledge of prognostics implementation is extended by includingpost maintenance affects into prognostics. Maintenance aims to restore a machine into astate where it is safe and reliable to operate while recovering the health of the machine.However, such activities result in introduction of uncertainties that are associated withpredictions due to deviations in degradation model. Thus, affecting accuracy and efficacyof predictions. Therefore, such vulnerabilities must be addressed by incorporating theinformation from maintenance events for accurate and reliable predictions. This thesispresents two frameworks which are adapted for probabilistic and non-probabilisticprognostic techniques to accommodate maintenance. Two case studies: a real-world casestudy from a nuclear power plant in the UK and a synthetic case study which wasgenerated based on the characteristics of a real-world case study are used for theimplementation and validation of the frameworks. The results of the implementationhold a promise for predicting remaining useful life while accommodating maintenancerepairs. Therefore, ensuring increased asset availability with higher reliability,maintenance cost effectiveness and operational safety.Steam turbines are an important asset of nuclear power plants, and are required tooperate reliably and efficiently. Unplanned outages have a significant impact on theability of the plant to generate electricity. Therefore, condition-based maintenance (CBM)can be used for predictive and proactive maintenance to avoid unplanned outages whilereducing operating costs and increasing the reliability and availability of the plant. InCBM, the information gathered can be interpreted for prognostics (the prediction offailure time or remaining useful life (RUL)).The aim of this project was to address two areas of challenges in prognostics, theselection of predictive technique and accommodation of post-maintenance effects, toimprove the efficacy of prognostics. The selection of an appropriate predictive algorithmis a key activity for an effective development of prognostics. In this research, a formalapproach for the evaluation and selection of predictive techniques is developed tofacilitate a methodic selection process of predictive techniques by engineering experts.This approach is then implemented for a case study provided by the engineering experts.Therefore, as a result of formal evaluation, a probabilistic technique the Bayesian LinearRegression (BLR) and a non-probabilistic technique the Support Vector Regression (SVR)were selected for prognostics implementation.In this project, the knowledge of prognostics implementation is extended by includingpost maintenance affects into prognostics. Maintenance aims to restore a machine into astate where it is safe and reliable to operate while recovering the health of the machine.However, such activities result in introduction of uncertainties that are associated withpredictions due to deviations in degradation model. Thus, affecting accuracy and efficacyof predictions. Therefore, such vulnerabilities must be addressed by incorporating theinformation from maintenance events for accurate and reliable predictions. This thesispresents two frameworks which are adapted for probabilistic and non-probabilisticprognostic techniques to accommodate maintenance. Two case studies: a real-world casestudy from a nuclear power plant in the UK and a synthetic case study which wasgenerated based on the characteristics of a real-world case study are used for theimplementation and validation of the frameworks. The results of the implementationhold a promise for predicting remaining useful life while accommodating maintenancerepairs. Therefore, ensuring increased asset availability with higher reliability,maintenance cost effectiveness and operational safety
'An inkling of hope' : understanding personal recovery in individuals transitioning out of chronic homelessness : a transatlantic qualitative study
Get PDFPreviously held under moratorium from 28th August 2020 until 28th August 2023.Individuals with serious mental illness (SMI) who are homeless are a client group withcomplex but often misunderstood and unmet health and social care needs. Althoughadopted by mental health policies and programmes in many developed countries,personal (mental health) recovery has remained markedly underresearched andundertheorised in relation to socio-structural disadvantage such as homelessness. Thistransatlantic qualitative participatory study aimed to address those knowledge andexplanatory deficits by exploring how individuals with a history of SMI and chronichomelessness made sense of their personal recovery, as well as what the barriers to,and facilitators of, their recovery were. This study also endeavoured to unravel thesocio-structural and contextual influences shaping recovery, as well as how individualsnavigated and negotiated those to enable better well-being and recovery. The lifestories and present-day narratives of 18 clients of temporary accommodation servicesin the U.S. and Scotland were elicited using in-depth interviews and a mobile phonediary between February and September 2018. Data from 45 interviews and more than200 diary entries were analysed using interpretative phenomenological analysis (IPA)and abductive-retroductive, critical realist analysis. The IPA revealed the significance of‘owning’ one’s recovery, as well as that of safety and constancy, insight, coping andsymptom management, nurturing a strong and positive sense of self, meaning in life,and feeling ‘wanted, accepted and needed’. Those super-ordinate themes captured theprocesses of envisioning and enacting recovery amidst homelessness. The criticalrealist analysis produced an explanatory model of personal recovery, whereby recoverywas the emergent outcome of the interplay between the conditioning effects of certainsocial structures and cultures and participants’ own agential capacities manifested inautonomous or fractured reflexive deliberations. Mental health and homelessnessservices should be designed and delivered in ways that enable clients’ intrinsiccapacities for self-reflection, self-directedness and emotional connectedness.Individuals with serious mental illness (SMI) who are homeless are a client group withcomplex but often misunderstood and unmet health and social care needs. Althoughadopted by mental health policies and programmes in many developed countries,personal (mental health) recovery has remained markedly underresearched andundertheorised in relation to socio-structural disadvantage such as homelessness. Thistransatlantic qualitative participatory study aimed to address those knowledge andexplanatory deficits by exploring how individuals with a history of SMI and chronichomelessness made sense of their personal recovery, as well as what the barriers to,and facilitators of, their recovery were. This study also endeavoured to unravel thesocio-structural and contextual influences shaping recovery, as well as how individualsnavigated and negotiated those to enable better well-being and recovery. The lifestories and present-day narratives of 18 clients of temporary accommodation servicesin the U.S. and Scotland were elicited using in-depth interviews and a mobile phonediary between February and September 2018. Data from 45 interviews and more than200 diary entries were analysed using interpretative phenomenological analysis (IPA)and abductive-retroductive, critical realist analysis. The IPA revealed the significance of‘owning’ one’s recovery, as well as that of safety and constancy, insight, coping andsymptom management, nurturing a strong and positive sense of self, meaning in life,and feeling ‘wanted, accepted and needed’. Those super-ordinate themes captured theprocesses of envisioning and enacting recovery amidst homelessness. The criticalrealist analysis produced an explanatory model of personal recovery, whereby recoverywas the emergent outcome of the interplay between the conditioning effects of certainsocial structures and cultures and participants’ own agential capacities manifested inautonomous or fractured reflexive deliberations. Mental health and homelessnessservices should be designed and delivered in ways that enable clients’ intrinsiccapacities for self-reflection, self-directedness and emotional connectedness
Understanding cholesterol modified nanoparticles as photothermal agents for cardiovascular disease studies
No full textAtherosclerosis is the primary reason for Cardiovascular disease, in which arteries become narrowed due to plaque development. Accumulation of low-density lipoprotein (LDL-C) at the site of damage (the endothelium) is known to be a key factor in the pathogenesis of atherosclerosis. By targeting the site of damage, subsequently utilising photothermal therapy should effectively halt or stop the atherosclerotic process. Lipid modifications are known in the literature to increase cellular interactions. Cholesterol is a lipid which can be functionalised onto nanoparticles potentially increasing uptake of gold nanoparticles. This essentially creates a 'fatty nanoparticle' which can also imitate LDL-C, hence being able to target plaques. Herein, the research focus was to investigate the cellular uptake of cholesterol modified nanoparticles and upon success, their capabilities as photothermal agents for targeting plaque sites. Gold nanoparticles were functionalised with cholesterol-DNA.;Thereafter, a series of in vitro studies were carried out using two cell lines: RAWs and HUVECs, to determine cellular uptake. Using 2D and 3D SERRS mapping, the first study determined successful uptake and the second study determined that the uptake was greater in endothelial cells. A 'semi-quantitative' method was applied to calculate the % relative SERRS response from each cell line, allowing for comparisons to be made. Cell viability studies confirmed the non-toxic nature of these probes. In the second part of this research, HGNs were used as the core for these 'fatty nanoparticles' due to their LSPR in the NIR, and commendable photothermal properties. Cholesterol modified HGNs displayed efficient cellular ablation with an in-house photothermal set up. This work successfully provided the basis for using cholesterol modified nanoparticles as photothermal agents in the treatment of CVD.Atherosclerosis is the primary reason for Cardiovascular disease, in which arteries become narrowed due to plaque development. Accumulation of low-density lipoprotein (LDL-C) at the site of damage (the endothelium) is known to be a key factor in the pathogenesis of atherosclerosis. By targeting the site of damage, subsequently utilising photothermal therapy should effectively halt or stop the atherosclerotic process. Lipid modifications are known in the literature to increase cellular interactions. Cholesterol is a lipid which can be functionalised onto nanoparticles potentially increasing uptake of gold nanoparticles. This essentially creates a 'fatty nanoparticle' which can also imitate LDL-C, hence being able to target plaques. Herein, the research focus was to investigate the cellular uptake of cholesterol modified nanoparticles and upon success, their capabilities as photothermal agents for targeting plaque sites. Gold nanoparticles were functionalised with cholesterol-DNA.;Thereafter, a series of in vitro studies were carried out using two cell lines: RAWs and HUVECs, to determine cellular uptake. Using 2D and 3D SERRS mapping, the first study determined successful uptake and the second study determined that the uptake was greater in endothelial cells. A 'semi-quantitative' method was applied to calculate the % relative SERRS response from each cell line, allowing for comparisons to be made. Cell viability studies confirmed the non-toxic nature of these probes. In the second part of this research, HGNs were used as the core for these 'fatty nanoparticles' due to their LSPR in the NIR, and commendable photothermal properties. Cholesterol modified HGNs displayed efficient cellular ablation with an in-house photothermal set up. This work successfully provided the basis for using cholesterol modified nanoparticles as photothermal agents in the treatment of CVD
A blade-resolved, partitioned-approach fluid-structure interaction analysis of a ducted, high solidity tidal turbine in real flow conditions
Get PDFThe affordances and contraints of distributive leadership in effecting school improvement in Saudi Arabian primary schools for boys : a focus upon school culture and values
Get PDFThis study addresses the concept of distributive leadership within the context of education. It explores and explains the values which underpin school culture and the extent and ways in which these values promote or inhibit distributive leadership. The research also considers the contrasts between Islamic values and the values that are purported to be promoted within distributive leadership. The main aim is to examine the relationship between school culture values and distributive leadership values, so as to suggest how improvement in schools can be furthered. Many scholars have postulated that distributive leadership could be the best solution for the improvement of leadership in schools (Harris, 2009; Hairon & Goh, 2014).;Nevertheless, the concept of distributive leadership is yet to gain consensus and, therefore, it can be said that it lacks a rational platform within the literature (Hartley, 2010; Woods et al., 2004; Gunter et al., 2008; Bennet et al., 2003; Bolden, 2011; Harris & Spillane, 2008). The formulation of a theoretical framework for the research can be done by focusing on the commonly accepted values of distributive leadership. For instant trust and accountability, sharing and empowerment (Harris, 2014; Day & Sammons, 2016), equality and justice (Torrance, 2013a; Harris, 2014), motivation and sense-making (Harris, 2014; Mascall et al., 2008), tender and autonomy (Tschannen-Moran &Gareis, 2015). To achieve these main aims, this research undertook a qualitative case study with triangulation tools in three primary schools for boys in Riyadh.This study addresses the concept of distributive leadership within the context of education. It explores and explains the values which underpin school culture and the extent and ways in which these values promote or inhibit distributive leadership. The research also considers the contrasts between Islamic values and the values that are purported to be promoted within distributive leadership. The main aim is to examine the relationship between school culture values and distributive leadership values, so as to suggest how improvement in schools can be furthered. Many scholars have postulated that distributive leadership could be the best solution for the improvement of leadership in schools (Harris, 2009; Hairon & Goh, 2014).;Nevertheless, the concept of distributive leadership is yet to gain consensus and, therefore, it can be said that it lacks a rational platform within the literature (Hartley, 2010; Woods et al., 2004; Gunter et al., 2008; Bennet et al., 2003; Bolden, 2011; Harris & Spillane, 2008). The formulation of a theoretical framework for the research can be done by focusing on the commonly accepted values of distributive leadership. For instant trust and accountability, sharing and empowerment (Harris, 2014; Day & Sammons, 2016), equality and justice (Torrance, 2013a; Harris, 2014), motivation and sense-making (Harris, 2014; Mascall et al., 2008), tender and autonomy (Tschannen-Moran &Gareis, 2015). To achieve these main aims, this research undertook a qualitative case study with triangulation tools in three primary schools for boys in Riyadh
Pedagogies of affect in physical education : exploring teaching for affective learing in the curriculum area of health and wellbeing
Get PDFThe purpose of this thesis is to explore the practice of pedagogies of affect in secondary school physical education. The decision to consider the affective domain as the main focus was in response to current issues relating to mental health among young people. This thesis has the overarching concern of how physical education is producing affective learning outcomes with a sample of Scottish secondary schools. In the Scottish context, physical education may make a significant contribution to the area of health and wellbeing, which is one of the cross-curricular priorities. This thesis includes three findings chapters as a result of adopting a pragmatic mixed methods approach to investigate the complexity of the practice.;The first findings chapter (Chapter 4) considered the question of the degree to which twenty teachers engaged in pedagogies of affect and how their teaching behaviour influenced pupils' affective learning outcomes, with the use of Self-Determination Theory (SDT) as a lens. The findings indicated that observed need-supportive teaching behaviour had a direct impact on pupils' affective learning outcomes. The second findings chapter (Chapter 5) was to build upon the previous chapter by revealing eight teachers' reflections on their observed lessons. This chapter focuses on the questions to what extent the teachers were aware of their teaching behaviour and why they behaved in the ways they did, which is a gap that previous studies have not covered yet.;One of the key findings in this chapter was how well teachers know their pupils' feelings and how important it is to build trusting relationships with their pupils in order to teach for positive affective learning. The third findings chapter (Chapter 6) centred on how teachers' and pupils' conceptualisation of health and wellbeing was enacted in their teaching and learning in consideration of the Scottish context. A holistic understanding of health emphasised the importance of building confidence, a growth mindset, and relationships with others, which could strengthen teaching and learning of health and wellbeing, particularly in the affective domain.The purpose of this thesis is to explore the practice of pedagogies of affect in secondary school physical education. The decision to consider the affective domain as the main focus was in response to current issues relating to mental health among young people. This thesis has the overarching concern of how physical education is producing affective learning outcomes with a sample of Scottish secondary schools. In the Scottish context, physical education may make a significant contribution to the area of health and wellbeing, which is one of the cross-curricular priorities. This thesis includes three findings chapters as a result of adopting a pragmatic mixed methods approach to investigate the complexity of the practice.;The first findings chapter (Chapter 4) considered the question of the degree to which twenty teachers engaged in pedagogies of affect and how their teaching behaviour influenced pupils' affective learning outcomes, with the use of Self-Determination Theory (SDT) as a lens. The findings indicated that observed need-supportive teaching behaviour had a direct impact on pupils' affective learning outcomes. The second findings chapter (Chapter 5) was to build upon the previous chapter by revealing eight teachers' reflections on their observed lessons. This chapter focuses on the questions to what extent the teachers were aware of their teaching behaviour and why they behaved in the ways they did, which is a gap that previous studies have not covered yet.;One of the key findings in this chapter was how well teachers know their pupils' feelings and how important it is to build trusting relationships with their pupils in order to teach for positive affective learning. The third findings chapter (Chapter 6) centred on how teachers' and pupils' conceptualisation of health and wellbeing was enacted in their teaching and learning in consideration of the Scottish context. A holistic understanding of health emphasised the importance of building confidence, a growth mindset, and relationships with others, which could strengthen teaching and learning of health and wellbeing, particularly in the affective domain
Electrical fault management orientated design of future electrical propulsion aircraft
Get PDFElectrical propulsion aircraft (EPA) have been cited as the future of aviation, enabling greener, quieter, more efficient aircraft. However, due to the stringent requirements surrounding aircraft certification, these novel EPA concepts will need to demonstrate high levels of safety and reliability if electrified flight is ever to become a mainstream mode of passenger transportation. Therefore, robust electrical fault management (FM) is necessary to maintain critical levels of aircraft thrust and to enable high confidence in the reliability and safety of future EPA designs. To date, electrical FM for EPA has been done at a first-pass, minimal level or not at all. For electrical FM to be effective, it must be integrated into the aircraft design from an early stage. This dictates that a novel approach to the design of electrical architectures for EPA is required which addresses the current uncertainty in the availability of suitable FM technologies for future EPA electrical architectures. Therefore, a first-of-kind FM strategy map is presented which identifies projections on the progression of key areas of future EPA-specific FM technology development and acts as a pre-cursor to future FM technology roadmaps. Furthermore, the FM orientated early-stage electrical architecture design methodology presented in this thesis derives feasible, FM-capable electrical architectures for a given EPA concept and captures significant assumptions which impact the down selection process. Since any novel EPA electrical architecture will require some form of testing in hardware, a novel framework for strategic FM demonstrator development is then proposed and the FM test goals for different levels of demonstrator are identified. This strategic development of critical aspects of FM and early integration of FM requires a portfolio of FM demonstrators and test beds for EPA and is crucial if unproven, future EPA electrical architectures are to reach high confidence.Electrical propulsion aircraft (EPA) have been cited as the future of aviation, enabling greener, quieter, more efficient aircraft. However, due to the stringent requirements surrounding aircraft certification, these novel EPA concepts will need to demonstrate high levels of safety and reliability if electrified flight is ever to become a mainstream mode of passenger transportation. Therefore, robust electrical fault management (FM) is necessary to maintain critical levels of aircraft thrust and to enable high confidence in the reliability and safety of future EPA designs. To date, electrical FM for EPA has been done at a first-pass, minimal level or not at all. For electrical FM to be effective, it must be integrated into the aircraft design from an early stage. This dictates that a novel approach to the design of electrical architectures for EPA is required which addresses the current uncertainty in the availability of suitable FM technologies for future EPA electrical architectures. Therefore, a first-of-kind FM strategy map is presented which identifies projections on the progression of key areas of future EPA-specific FM technology development and acts as a pre-cursor to future FM technology roadmaps. Furthermore, the FM orientated early-stage electrical architecture design methodology presented in this thesis derives feasible, FM-capable electrical architectures for a given EPA concept and captures significant assumptions which impact the down selection process. Since any novel EPA electrical architecture will require some form of testing in hardware, a novel framework for strategic FM demonstrator development is then proposed and the FM test goals for different levels of demonstrator are identified. This strategic development of critical aspects of FM and early integration of FM requires a portfolio of FM demonstrators and test beds for EPA and is crucial if unproven, future EPA electrical architectures are to reach high confidence
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