Capturing the overarm throw in darts employing wireless inertial measurement

This work employs a custom built body area network of wireless inertial measurement technology to conduct a biomechanical analysis of precision targeted throwing in competitive and recreational darts. The solution is shown to be capable of measuring key biomechanical factors including speed, acceleration and timing. These parameters are subsequently correlated with scoring performance to determine the affect each variable has on outcome. For validation purposes an optical 3D motion capture system provides a complete kinematic model of the subject and enables concurrent benchmarking of the 'gold standard' optical inertial measurement system with the more affordable and proactive wireless inertial measurement solution developed as part of this work.

Specification of optimum holistic building environmental and energy performance information to support informed decision making

Political drivers such as the Kyoto protocol, the EU Energy Performance of Buildings Directive and the Energy end use and Services Directive have been implemented in response to an identified need for a reduction in human related CO2 emissions. Buildings account for a significant portion of global CO2 emissions, approximately 25-30%, and it is widely acknowledged by industry and research organisations that they operate inefficiently. In parallel, unsatisfactory indoor environmental conditions have proven to negatively impact occupant productivity. Legislative drivers and client education are seen as the key motivating factors for an improvement in the holistic environmental and energy performance of a building. A symbiotic relationship exists between building indoor environmental conditions and building energy consumption. However traditional Building Management Systems and Energy Management Systems treat these separately. Conventional performance analysis compares building energy consumption with a previously recorded value or with the consumption of a similar building and does not recognise the fact that all buildings are unique. Therefore what is required is a new framework which incorporates performance comparison against a theoretical building specific ideal benchmark. Traditionally Energy Managers, who work at the operational level of organisations with respect to building performance, do not have access to ideal performance benchmark information and as a result cannot optimally operate buildings. This thesis systematically defines Holistic Environmental and Energy Management and specifies the Scenario Modelling Technique which in turn uses an ideal performance benchmark. The holistic technique uses quantified expressions of building performance and by doing so enables the profiled Energy Manager to visualise his actions and the downstream consequences of his actions in the context of overall building operation. The Ideal Building Framework facilitates the use of this technique by acting as a Building Life Cycle (BLC) data repository through which ideal building performance benchmarks are systematically structured and stored in parallel with actual performance data. The Ideal Building Framework utilises transformed data in the form of the Ideal Set of Performance Objectives and Metrics which are capable of defining the performance of any building at any stage of the BLC. It is proposed that the union of Scenario Models for an individual building would result in a building specific Combination of Performance Metrics which would in turn be stored in the BLC data repository. The Ideal Data Set underpins the Ideal Set of Performance Objectives and Metrics and is the set of measurements required to monitor the performance of the Ideal Building. A Model View describes the unique building specific data relevant to a particular project stakeholder. The energy management data and information exchange requirements that underlie a Model View implementation are detailed and incorporate traditional and proposed energy management. This thesis also specifies the Model View Methodology which complements the Ideal Building Framework. The developed Model View and Rule Set methodology process utilises stakeholder specific rule sets to define stakeholder pertinent environmental and energy performance data. This generic process further enables each stakeholder to define the resolution of data desired. For example, basic, intermediate or detailed. The Model View methodology is applicable for all project stakeholders, each requiring its own customised rule set. Two rule sets are defined in detail, the Energy Manager rule set and the LEED Accreditor rule set. This particular measurement generation process accompanied by defined View would filter and expedite data access for all stakeholders involved in building performance. Information presentation is critical for effective use of the data provided by the Ideal Building Framework and the Energy Management View definition. The specifications for a customised Information Delivery Tool account for the established profile of Energy Managers and best practice user interface design. Components of the developed tool could also be used by Facility Managers working at the tactical and strategic levels of organisations. Informed decision making is made possible through specified decision assistance processes which incorporate the Scenario Modelling and Benchmarking techniques, the Ideal Building Framework, the Energy Manager Model View, the Information Delivery Tool and the established profile of Energy Managers. The Model View and Rule Set Methodology is effectively demonstrated on an appropriate mixed use existing ‘green’ building, the Environmental Research Institute at University College Cork, using the Energy Management and LEED rule sets. Informed Decision Making is also demonstrated using a prototype scenario for the demonstration building.

Pretty good governance: balancing policy drivers and stakeholder interests in developing fisheries ecosystem plans

The central research question that this thesis addresses is whether there is a significant gap between fishery stakeholder values and the principles and policy goals implicit in an Ecosystem Approach to Fisheries Management (EAFM). The implications of such a gap for fisheries governance are explored. Furthermore an assessment is made of what may be practically achievable in the implementation of an EAFM in fisheries in general and in a case study fishery in particular. The research was mainly focused on a particular case study, the Celtic Sea Herring fishery and its management committee, the Celtic Sea Herring Management Advisory Committee (CSHMAC). The Celtic Sea Herring fishery exhibits many aspects of an EAFM and the fish stock has successfully recovered to healthy levels in the past 5 years. However there are increasing levels of governance related conflict within the fishery which threaten the future sustainability of the stock. Previous research on EAFM governance has tended to focus either on higher levels of EAFM governance or on individual behaviour but very little research has attempted to link the two spheres or explore the relationship between them. Two main themes within this study aimed to address this gap. The first was what role governance could play in facilitating EAFM implementation. The second theme concerned the degree of convergence between high-level EAFM goals and stakeholder values. The first method applied was governance benchmarking to analyse systemic risks to EAFM implementation. This found that there are no real EU or national level policies which provide stakeholders or managers with clear targets for EAFM implementation. The second method applied was the use of cognitive mapping to explore stakeholders understandings of the main ecological, economic and institutional driving forces in the Celtic Sea Herring fishery. The main finding from this was that a long-term outlook can and has been incentivised through a combination of policy drivers and participatory management. However the fundamental principle of EAFM, accounting for ecosystem linkages rather than target stocks was not reflected in stakeholders cognitive maps. This was confirmed in a prioritisation of stakeholders management priorities using Analytic Hierarchy Process which found that the overriding concern is for protection of target stock status but that wider ecosystem health was not a priority for most management participants. The conclusion reached is that moving to sustainable fisheries may be a more complex process than envisioned in much of the literature and may consist of two phases. The first phase is a transition to a long-term but still target stock focused approach. This achievable transition is mainly a strategic change, which can be incentivised by policies and supported by stakeholders. In the Celtic Sea Herring fishery, and an increasing number of global and European fisheries, such transitions have contributed to successful stock recoveries. The second phase however, implementation of an ecosystem approach, may present a greater challenge in terms of governability, as this research highlights some fundamental conflicts between stakeholder perceptions and values and those inherent in an EAFM. This phase may involve the setting aside of fish for non-valued ecosystem elements and will require either a pronounced mind-set and value change or some strong top-down policy incentives in order to succeed. Fisheries governance frameworks will need to carefully explore the most effective balance between such endogenous and exogenous solutions. This finding of low prioritisation of wider ecosystem elements has implications for rights based management within an ecosystem approach, regardless of whether those rights are individual or collective.

Current methods and advances in forecasting of wind power generation

Wind power generation differs from conventional thermal generation due to the stochastic nature of wind. Thus wind power forecasting plays a key role in dealing with the challenges of balancing supply and demand in any electricity system, given the uncertainty associated with the wind farm power output. Accurate wind power forecasting reduces the need for additional balancing energy and reserve power to integrate wind power. Wind power forecasting tools enable better dispatch, scheduling and unit commitment of thermal generators, hydro plant and energy storage plant and more competitive market trading as wind power ramps up and down on the grid. This paper presents an in-depth review of the current methods and advances in wind power forecasting and prediction. Firstly, numerical wind prediction methods from global to local scales, ensemble forecasting, upscaling and downscaling processes are discussed. Next the statistical and machine learning approach methods are detailed. Then the techniques used for benchmarking and uncertainty analysis of forecasts are overviewed, and the performance of various approaches over different forecast time horizons is examined. Finally, current research activities, challenges and potential future developments are appraised.