943 resultados para Dynamic Capabilities


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This thesis presents a new approach to compute and optimize feasible three dimensional (3D) flight trajectories using aspects of Human Decision Making (HDM) strategies, for fixed wing Unmanned Aircraft (UA) operating in low altitude environments in the presence of real time planning deadlines. The underlying trajectory generation strategy involves the application of Manoeuvre Automaton (MA) theory to create sets of candidate flight manoeuvres which implicitly incorporate platform dynamic constraints. Feasible trajectories are formed through the concatenation of predefined flight manoeuvres in an optimized manner. During typical UAS operations, multiple objectives may exist, therefore the use of multi-objective optimization can potentially allow for convergence to a solution which better reflects overall mission requirements and HDM preferences. A GUI interface was developed to allow for knowledge capture from a human expert during simulated mission scenarios. The expert decision data captured is converted into value functions and corresponding criteria weightings using UTilite Additive (UTA) theory. The inclusion of preferences elicited from HDM decision data within an Automated Decision System (ADS) allows for the generation of trajectories which more closely represent the candidate HDM’s decision strategies. A novel Computationally Adaptive Trajectory Decision optimization System (CATDS) has been developed and implemented in simulation to dynamically manage, calculate and schedule system execution parameters to ensure that the trajectory solution search can generate a feasible solution, if one exists, within a given length of time. The inclusion of the CATDS potentially increases overall mission efficiency and may allow for the implementation of the system on different UAS platforms with varying onboard computational capabilities. These approaches have been demonstrated in simulation using a fixed wing UAS operating in low altitude environments with obstacles present.

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The serviceability and safety of bridges are crucial to people’s daily lives and to the national economy. Every effort should be taken to make sure that bridges function safely and properly as any damage or fault during the service life can lead to transport paralysis, catastrophic loss of property or even casualties. Nonetheless, aggressive environmental conditions, ever-increasing and changing traffic loads and aging can all contribute to bridge deterioration. With often constrained budget, it is of significance to identify bridges and bridge elements that should be given higher priority for maintenance, rehabilitation or replacement, and to select optimal strategy. Bridge health prediction is an essential underpinning science to bridge maintenance optimization, since the effectiveness of optimal maintenance decision is largely dependent on the forecasting accuracy of bridge health performance. The current approaches for bridge health prediction can be categorised into two groups: condition ratings based and structural reliability based. A comprehensive literature review has revealed the following limitations of the current modelling approaches: (1) it is not evident in literature to date that any integrated approaches exist for modelling both serviceability and safety aspects so that both performance criteria can be evaluated coherently; (2) complex system modelling approaches have not been successfully applied to bridge deterioration modelling though a bridge is a complex system composed of many inter-related bridge elements; (3) multiple bridge deterioration factors, such as deterioration dependencies among different bridge elements, observed information, maintenance actions and environmental effects have not been considered jointly; (4) the existing approaches are lacking in Bayesian updating ability to incorporate a variety of event information; (5) the assumption of series and/or parallel relationship for bridge level reliability is always held in all structural reliability estimation of bridge systems. To address the deficiencies listed above, this research proposes three novel models based on the Dynamic Object Oriented Bayesian Networks (DOOBNs) approach. Model I aims to address bridge deterioration in serviceability using condition ratings as the health index. The bridge deterioration is represented in a hierarchical relationship, in accordance with the physical structure, so that the contribution of each bridge element to bridge deterioration can be tracked. A discrete-time Markov process is employed to model deterioration of bridge elements over time. In Model II, bridge deterioration in terms of safety is addressed. The structural reliability of bridge systems is estimated from bridge elements to the entire bridge. By means of conditional probability tables (CPTs), not only series-parallel relationship but also complex probabilistic relationship in bridge systems can be effectively modelled. The structural reliability of each bridge element is evaluated from its limit state functions, considering the probability distributions of resistance and applied load. Both Models I and II are designed in three steps: modelling consideration, DOOBN development and parameters estimation. Model III integrates Models I and II to address bridge health performance in both serviceability and safety aspects jointly. The modelling of bridge ratings is modified so that every basic modelling unit denotes one physical bridge element. According to the specific materials used, the integration of condition ratings and structural reliability is implemented through critical failure modes. Three case studies have been conducted to validate the proposed models, respectively. Carefully selected data and knowledge from bridge experts, the National Bridge Inventory (NBI) and existing literature were utilised for model validation. In addition, event information was generated using simulation to demonstrate the Bayesian updating ability of the proposed models. The prediction results of condition ratings and structural reliability were presented and interpreted for basic bridge elements and the whole bridge system. The results obtained from Model II were compared with the ones obtained from traditional structural reliability methods. Overall, the prediction results demonstrate the feasibility of the proposed modelling approach for bridge health prediction and underpin the assertion that the three models can be used separately or integrated and are more effective than the current bridge deterioration modelling approaches. The primary contribution of this work is to enhance the knowledge in the field of bridge health prediction, where more comprehensive health performance in both serviceability and safety aspects are addressed jointly. The proposed models, characterised by probabilistic representation of bridge deterioration in hierarchical ways, demonstrated the effectiveness and pledge of DOOBNs approach to bridge health management. Additionally, the proposed models have significant potential for bridge maintenance optimization. Working together with advanced monitoring and inspection techniques, and a comprehensive bridge inventory, the proposed models can be used by bridge practitioners to achieve increased serviceability and safety as well as maintenance cost effectiveness.

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Traditionally, design has been centred within the manufacturing and production areas of companies and or as a styling afterthought. Increasingly, design is viewed as a vital and important strategic business resource (Dell’Era, Marchesi & Verganti, 2010) and consequently companies worldwide look to design to help them innovate, differentiate and compete in the global marketplace. The role of the professional designer is evolving to a point where they are needed to work beyond being a specialist in the manufacturing and aesthetics of an artefact (Wrigley & Bucolo, 2011). This paper challenges the values held by academics and industry regarding the traditional role of designers in business. It investigates the emerging transitional engineering framework and puts forward a proposal for the next generation designer in the future era of design. Questions surrounding how designers will develop these new skills and how the Authors’ new framework of design led innovation can contribute to the future of design will be presented. This research is needed to better equip future designers to have a more central role in business.

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The application of nanotechnology products has increased significantly in recent years. With their broad range of applications, including electronics, food and agriculture, power and energy, scientific instruments, clothing, cosmetics, buildings, biomedical and health, etc (Catanzariti, 2008), nanomaterials are an indispensible part of human life.

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This article investigates the role of information communication technologies (ICTs) in establishing a well-aligned, authentic learning environment for a diverse cohort of non-cognate and cognate students studying event management in a higher education context. Based on a case study which examined the way ICTs assisted in accommodating diverse learning needs, styles and stages in an event management subject offered in the Creative Industries Faculty at Queensland University of Technology in Brisbane, Australia, the article uses an action research approach to generate grounded, empirical data on the effectiveness of the dynamic, individualised curriculum frameworks that the use of ICTs makes possible. The study provides insights into the way non-cognate and cognate students respond to different learning tools. It finds that whilst non-cognate and cognate students do respond to learning tools differently, due to a differing degree of emphasis on technical, task or theoretical competencies, the use of ICTs allows all students to improve their performance by providing multiple points of entry into the content. In this respect, whilst the article focuses on the way ICTs can be used to develop an authentic, well-aligned curriculum model that meets the needs of event management students in a higher education context, with findings relevant for event educators in Business, Hospitality, Tourism and Creative Industries, the strategies outlined may also be useful for educators in other fields who are faced with similar challenges when designing and developing curriculum for diverse cohorts.

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To ensure the small-signal stability of a power system, power system stabilizers (PSSs) are extensively applied for damping low frequency power oscillations through modulating the excitation supplied to synchronous machines, and increasing interest has been focused on developing different PSS schemes to tackle the threat of damping oscillations to power system stability. This paper examines four different PSS models and investigates their performances on damping power system dynamics using both small-signal eigenvalue analysis and large-signal dynamic simulations. The four kinds of PSSs examined include the Conventional PSS (CPSS), Single Neuron based PSS (SNPSS), Adaptive PSS (APSS) and Multi-band PSS (MBPSS). A steep descent parameter optimization algorithm is employed to seek the optimal PSS design parameters. To evaluate the effects of these PSSs on improving power system dynamic behaviors, case studies are carried out on an 8-unit 24-bus power system through both small-signal eigenvalue analysis and large-signal time-domain simulations.

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This paper proposes a new approach for state estimation of angles and frequencies of equivalent areas in large power systems with synchronized phasor measurement units. Defining coherent generators and their correspondent areas, generators are aggregated and system reduction is performed in each area of inter-connected power systems. The structure of the reduced system is obtained based on the characteristics of the reduced linear model and measurement data to form the non-linear model of the reduced system. Then a Kalman estimator is designed for the reduced system to provide an equivalent dynamic system state estimation using the synchronized phasor measurement data. The method is simulated on two test systems to evaluate the feasibility of the proposed method.

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The growing awareness of sustainability issues around the world has put extensive pressure on the construction industry to improve its sustainable practice. Sustainability principles need to be applied to not just during design and construction phase but the entire life cycle of a construction project. Compared to sustainability endeavours on earlier development phases, the pace to implement sustainability agenda during the operation and maintenance phase has not been as fast during past practices of facilities management (FM). Literature study suggests that sustainable practices in FM activities can bring substantial benefits such as reducing energy consumptions and waste, while increasing productivity, financial return and standing in the community. It also suggests several barriers which inhibit the implementation of sustainability in FM practices, including the lack of knowledge, discrepancy between capability and skills, and unwillingness of the FM personnel and organizations to adapt to new routines in order to implement sustainability in their business. The capabilities of FM personnel and organizations were regarded as the key enablers in managing sustainability knowledge. In a sustainable development context, capabilities are vital to the fostering of competency in an organization to innovate in a more sustainable way and support the agenda in an organization. Additionally, research which focused on people’s capabilities and skills is still lagging behind the efforts to develop guidelines, technical manuals and knowledge portals. Therefore, it is beneficial to explore the issues of capabilities in dealing with the implementation of sustainable practices in FM. This paper introduces a research project which is aimed at establishing a knowledge capabilities framework for promoting sustainability measures in FM practices. It will explore and highlight challenges to integrate sustainability as well as the personnel and organizational capabilities that are vital in dealing with knowledge issues in implementing sustainability agenda in FM practices. The expected outcome of this research has the potential to further sustainability endeavours in FM practices, while providing a useful source of knowledge to the FM personnel and organizations.

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Distributed Genetic Algorithms (DGAs) designed for the Internet have to take its high communication cost into consideration. For island model GAs, the migration topology has a major impact on DGA performance. This paper describes and evaluates an adaptive migration topology optimizer that keeps the communication load low while maintaining high solution quality. Experiments on benchmark problems show that the optimized topology outperforms static or random topologies of the same degree of connectivity. The applicability of the method on real-world problems is demonstrated on a hard optimization problem in VLSI design.

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The objective of this research was to investigate the effect of suspension parameters on dynamic load-sharing of longitudinal-connected air suspensions of a tri-axle semi-trailer. A novel nonlinear model of a multi-axle semi-trailer with longitudinal-connected air suspension was formulated based on fluid mechanics and thermodynamics and was validated through test results. The effects of suspension parameters on dynamic load-sharing and road-friendliness of the semi-trailer were analyzed. Simulation results indicate that the road-friendliness metric DLC (Dynamic Load Coefficient), is generally in accordance with the load-sharing metric - DLSC (Dynamic Load Sharing Coefficient). When the static height or static pressure increases, the DLSC optimization ratio declines monotonically. The effect of employing larger air lines and connectors on the DLSC optimization ratio gives varying results as road roughness increases and as driving speed increases. The results also indicate that if the air line diameter is always assumed to be larger than the connector diameter, the influence of air line diameter on load-sharing is more significant than that of the connector.

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The development planning process under Law No. 25/2004 is said to be a new approach to increase public participation in decentralised Indonesia. This Law has introduced planning mechanisms, called Musyawarah Perencanaan Pembangunan (Musrenbang), to provide a forum for development planning. In spite of the expressed intention of these mechanisms to improve public participation, some empirical observations have cast doubt on the outcomes. As a result, some local governments have tried to provide alternative mechanisms to promote for participation in local development planning. Since planning is often said to be one of the most effective ways to improve community empowerment, it is of particular concern, to examine the extent to which the current local development planning processes in Indonesia provide sufficient opportunities to improve the self organising capabilities of communities to sustain development programs to meet local needs. With this objective in mind, this paper examines problems encountered by the new local planning mechanism (Musrenbang) in increasing local community empowerment particularly regarding their self organising capabilities. The concept of community empowerment as a pathway to social justice is explored to identify its key elements and approaches and to show how they can be incorporated within planning processes. Having discussed this, it is then argued that to change current unfavorable outcomes, procedural justice and social learning approaches need to be adopted as pathways to community empowerment. Lastly it is also suggested that an alternative local planning process, called Sistem Dukungan (SISDUK), introduced in South Suluwezi in collaboration with JAICA in 2006 (?) offers scope to incorporate such procedural justice and social learning approaches to improve the self organizing capabilities of local communities.

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Significant wheel-rail dynamic forces occur because of imperfections in the wheels and/or rail. One of the key responses to the transmission of these forces down through the track is impact force on the sleepers. Dynamic analysis of nonlinear systems is very complicated and does not lend itself easily to a classical solution of multiple equations. Trying to deduce the behaviour of track components from experimental data is very difficult because such data is hard to obtain and applies to only the particular conditions of the track being tested. The finite element method can be the best solution to this dilemma. This paper describes a finite element model using the software package ANSYS for various sized flat defects in the tread of a wheel rolling at a typical speed on heavy haul track. The paper explores the dynamic response of a prestressed concrete sleeper to these defects.

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Wheel–rail interaction is one of the most important research topics in railway engineering. It involves track impact response, track vibration and track safety. Track structure failures caused by wheel–rail impact forces can lead to significant economic loss for track owners through damage to rails and to the sleepers beneath. Wheel–rail impact forces occur because of imperfections in the wheels or rails such as wheel flats, irregular wheel profiles, rail corrugations and differences in the heights of rails connected at a welded joint. A wheel flat can cause a large dynamic impact force as well as a forced vibration with a high frequency, which can cause damage to the track structure. In the present work, a three-dimensional (3-D) finite element (FE) model for the impact analysis induced by the wheel flat is developed by use of the finite element analysis (FEA) software package ANSYS and validated by another validated simulation. The effect of wheel flats on impact forces is thoroughly investigated. It is found that the presence of a wheel flat will significantly increase the dynamic impact force on both rail and sleeper. The impact force will monotonically increase with the size of wheel flats. The relationships between the impact force and the wheel flat size are explored from this finite element analysis and they are important for track engineers to improve their understanding of the design and maintenance of the track system.

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Regional innovation systems (RISs) literature has emphasized the critical role of interactive learning and knowledge exchange amongst firms and a variety of spatially connected innovation institutions as the foundation of regional innovation. Knowledge intermediaries have been analysed in terms of the technology-transaction services they provide firms and/or knowledge producers such as universities and therefore the role they play in facilitating interaction within the RIS. However, innovation also depends on the capability of the firm to learn. Some studies have suggested that intermediaries also play a role in that regard as participation in intermediary knowledge transfer programmes can contribute to the development of firm capabilities for problem-solving and learning. Our research is based on two case study intermediary programmes involving interviews with facilitators and participants. Our data show that knowledge intermediaries affect organizational learning capabilities by impacting on firms' network relationships, internal and external communication channels and internal learning processes which in turn affect the ability to interpret and use knowledge within the firm. This suggests that the role of knowledge intermediaries might be greater than facilitating interactions in the innovation system, as knowledge intermediation may affect the ability of firms to learn and absorb knowledge from their environment.

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This paper argues that, despite its strengths, the UK Department of Culture, Media and Sport (DCMS) classification of the creative industries contains inconsistencies which need to be addressed to make it fully fit for purpose. It presents an improved methodology which retains the strengths of the DCMS's approach while addressing its deficiencies. We focus on creative intensity: the proportion of total employment within an industry that is engaged in creative occupations.