title: Micro-mechanical predictive modelling as an aid to CAD based analysis of composite sporting equipment

authors: Ewart, Paul

subjects: CAD

abstract: The sport and leisure industry in New Zealand (NZ) has the potential to become a major user of composite materials. Given the size of NZ industry, design and manufacturing strategies based on virtual engineering should be developed to suit NZ requirements. Virtual methods use computer aided engineering capabilities to find faults, explore alternatives and optimise product performance before detailed design or prototyping. When doing computer aided simulation the required mechanical properties of individual reinforcement and matrix components are well documented. However, the mechanical properties of composite materials are not as simple to obtain. Micro-mechanical modelling could therefore be used to aid the design and development of composite equipment, where mechanical properties are unknown. In this study, solids modelling was used to produce an analog model of a composite, and it was found that it lead to reductions in file size and simulation time. Representing a composite with an analog model implies that the behavioural characteristics are modelled, but not the physical characteristics of the individual components. Three micro-mechanical models were developed to predict the flexural modulus of composite materials, based on perfect, partial and no adhesion. It was found that the partial adhesion model was both practical and consistently accurate. The partial adhesion model accounted for adhesion between components by considering an 'effective shear value' at the interface. Validation of the models was done by flexural testing injection moulded samples of glass, wood and carbon fibre reinforced polyethylene. It was shown that the adhesion coefficient range was 0.1 for carbon fibre, 0.5 for glass fibre and 0.9 for the wood fibre composites. It was concluded that the adhesion coefficient is crucial and it is recommended that further work is done to validate effective shear values by empirical means. The predicted flexural modulus values were used to enable finite element simulation of modelled analog beams as well as commercial kayak paddles. It was determined that accurate simulation is possible for composite equipment using the partial adhesion model.

text: Micro-mechanical predictive modelling as an aid to CAD based analysis of composite sporting equipment The sport and leisure industry in New Zealand (NZ) has the potential to become a major user of composite materials. Given the size of NZ industry, design and manufacturing strategies based on virtual engineering should be developed to suit NZ requirements. Virtual methods use computer aided engineering capabilities to find faults, explore alternatives and optimise product performance before detailed design or prototyping. When doing computer aided simulation the required mechanical properties of individual reinforcement and matrix components are well documented. However, the mechanical properties of composite materials are not as simple to obtain. Micro-mechanical modelling could therefore be used to aid the design and development of composite equipment, where mechanical properties are unknown. In this study, solids modelling was used to produce an analog model of a composite, and it was found that it lead to reductions in file size and simulation time. Representing a composite with an analog model implies that the behavioural characteristics are modelled, but not the physical characteristics of the individual components. Three micro-mechanical models were developed to predict the flexural modulus of composite materials, based on perfect, partial and no adhesion. It was found that the partial adhesion model was both practical and consistently accurate. The partial adhesion model accounted for adhesion between components by considering an 'effective shear value' at the interface. Validation of the models was done by flexural testing injection moulded samples of glass, wood and carbon fibre reinforced polyethylene. It was shown that the adhesion coefficient range was 0.1 for carbon fibre, 0.5 for glass fibre and 0.9 for the wood fibre composites. It was concluded that the adhesion coefficient is crucial and it is recommended that further work is done to validate effective shear values by empirical means. The predicted flexural modulus values were used to enable finite element simulation of modelled analog beams as well as commercial kayak paddles. It was determined that accurate simulation is possible for composite equipment using the partial adhesion model.

year: 2008

title: Unsupervised concept drift detection using a student–teacher approach

authors: Cerqueira, Vitor

abstract: Concept drift detection is a crucial task in data stream evolving environments. Most of state of the art approaches designed to tackle this problem monitor the loss of predictive models. However, this approach falls short in many real-world scenarios, where the true labels are not readily available to compute the loss. In this context, there is increasing attention to approaches that perform concept drift detection in an unsupervised manner, i.e., without access to the true labels after the model is deployed. We propose a novel approach to unsupervised concept drift detection based on a student-teacher learning paradigm. Essentially, we create an auxiliary model (student) to mimic the primary model’s behaviour (teacher). At run-time, our approach is to use the teacher for predicting new instances and monitoring the mimicking loss of the student for concept drift detection. In a set of experiments using 19 data streams, we show that the proposed approach can detect concept drift and present a competitive behaviour relative to the state of the art approaches.

text: Unsupervised concept drift detection using a student–teacher approach Concept drift detection is a crucial task in data stream evolving environments. Most of state of the art approaches designed to tackle this problem monitor the loss of predictive models. However, this approach falls short in many real-world scenarios, where the true labels are not readily available to compute the loss. In this context, there is increasing attention to approaches that perform concept drift detection in an unsupervised manner, i.e., without access to the true labels after the model is deployed. We propose a novel approach to unsupervised concept drift detection based on a student-teacher learning paradigm. Essentially, we create an auxiliary model (student) to mimic the primary model’s behaviour (teacher). At run-time, our approach is to use the teacher for predicting new instances and monitoring the mimicking loss of the student for concept drift detection. In a set of experiments using 19 data streams, we show that the proposed approach can detect concept drift and present a competitive behaviour relative to the state of the art approaches.

year: 2022-01-01

title: Reconnecting whānau: Pathways to recovery for Māori with bipolar disorder

authors: Waitoki, Waikaremoana

subjects: mental health

abstract: While Māori are known to experience a higher burden of mental health and addiction problems compared to non-Māori (Baxter, 2008), little exploratory research has been conducted into Māori experiences of bipolar affective disorder. Bipolar disorder is at times regarded as a “life sentence”, with little hope of recovery. The recovery- focused mental health literature, however, argues wellness is achievable for even the most intractable conditions (Lapsley, Nikora, & Black, 2002; Mental Health Commission, 2001). The aim of this research was to gather information about the experiences of Māori who were diagnosed with bipolar affective disorder. Interviews were conducted with 22 Māori wāhine (women) and tāne (men), and using thematic analyses, themes relevant to their life stories were uncovered. This research sought to contribute to the realisation of Māori potential by explicitly shifting from deficit- focused frameworks to a focus on systemic factors that influenced Māori wellbeing. Highlights were that whānau (participants) who were connected with friends, partners and family were motivated to achieve wellness and to stay well.

text: Reconnecting whānau: Pathways to recovery for Māori with bipolar disorder While Māori are known to experience a higher burden of mental health and addiction problems compared to non-Māori (Baxter, 2008), little exploratory research has been conducted into Māori experiences of bipolar affective disorder. Bipolar disorder is at times regarded as a “life sentence”, with little hope of recovery. The recovery- focused mental health literature, however, argues wellness is achievable for even the most intractable conditions (Lapsley, Nikora, & Black, 2002; Mental Health Commission, 2001). The aim of this research was to gather information about the experiences of Māori who were diagnosed with bipolar affective disorder. Interviews were conducted with 22 Māori wāhine (women) and tāne (men), and using thematic analyses, themes relevant to their life stories were uncovered. This research sought to contribute to the realisation of Māori potential by explicitly shifting from deficit- focused frameworks to a focus on systemic factors that influenced Māori wellbeing. Highlights were that whānau (participants) who were connected with friends, partners and family were motivated to achieve wellness and to stay well.

year: 2015