16 resultados para Krohn, Pietro

em Queensland University of Technology - ePrints Archive


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Cities have long held a fascination for people – as they grow and develop, there is a desire to know and understand the intricate interplay of elements that makes cities ‘live’. In part, this is a need for even greater efficiency in urban centres, yet the underlying quest is for a sustainable urban form. In order to make sense of the complex entities that we recognise cities to be, they have been compared to buildings, organisms and more recently machines. However the search for better and more elegant urban centres is hardly new, healthier and more efficient settlements were the aim of Modernism’s rational sub-division of functions, which has been translated into horizontal distribution through zoning, or vertical organisation thought highrise developments. However both of these approaches have been found to be unsustainable, as too many resources are required to maintain this kind or urbanisation and social consequences of either horizontal or vertical isolation must also be considered. From being absolute consumers of resources, of energy and of technology, cities need to change, to become sustainable in order to be more resilient and more efficient in supporting culture, society as well as economy. Our urban centres need to be re-imagined, re-conceptualised and re-defined, to match our changing society. One approach is to re-examine the compartmentalised, mono-functional approach of urban Modernism and to begin to investigate cities like ecologies, where every element supports and incorporates another, fulfilling more than just one function. This manner of seeing the city suggests a framework to guide the re-mixing of urban settlements. Beginning to understand the relationships between supporting elements and the nature of the connecting ‘web’ offers an invitation to investigate the often ignored, remnant spaces of cities. This ‘negative space’ is the residual from which space and place are carved out in the Contemporary city, providing the link between elements of urban settlement. Like all successful ecosystems, cities need to evolve and change over time in order to effectively respond to different lifestyles, development in culture and society as well as to meet environmental challenges. This paper seeks to investigate the role that negative space could have in the reorganisation of the re-mixed city. The space ‘in-between’ is analysed as an opportunity for infill development or re-development which provides to the urban settlement the variety that is a pre-requisite for ecosystem resilience. An analysis of the urban form is suggested as an empirical tool to map the opportunities already present in the urban environment and negative space is evaluated as a key element in achieving a positive development able to distribute diverse environmental and social facilities in the city.

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It is often argued that consumption of alcohol, tobacco and drugs is detrimental to the cognitive abilities of teenagers. In order to disentangle a possible causal effect of these substances use from a self-selection bias, we control for pupils previous performance and for their previous rate of progression applying a DiDiD strategy. Using the NELS 1988 panel dataset, we find that the effects of alcohol and tobacco on test scores disappear once the selection bias is controlled for (this does not preclude long term detrimental effects). However, we find reliable evidence that heavy use of drugs (marijuana and cocaine) has direct detrimental effects on educational achievements. Hence, our results may have significant policy implications.

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Presented is the material and gas sensing properties of graphene-like nano-sheets deposited on 36° YX lithium tantalate (LiTaO3) surface acoustic wave (SAW) transducers. The graphene-like nano-sheets were characterized via scanning electron microscopy (SEM), atomic force microscopy(AFM)and X-ray photoelectron spectroscopy (XPS). The graphenelike nano-sheet/SAW sensors were exposed to different concentrations of hydrogen (H2) gas in a synthetic air at room temperature. The developed sensors exhibit good sensitivity towards low concentrations of H2 in ambient conditions, as well as excellent dynamic performance towards H2 at room temperature.

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The purpose of this paper is to identify goal conflicts – both actual and potential – between climate and social policies in government strategies in response to the growing significance of climate change as a socioecological issue (IPCC 2007). Both social and climate policies are political responses to long-term societal trends related to capitalist development, industrialisation, and urbanisation (Koch, 2012). Both modify these processes through regulation, fiscal transfers and other measures, thereby affecting conditions for the other. This means that there are fields of tensions and synergies between social policy and climate change policy. Exploring these tensions and synergies is an increasingly important task for navigating genuinely sustainable development. Gough et al (2008) highlight three potential synergies between social and climate change policies: First, income redistribution – a traditional concern of social policy – can facilitate use of and enhance efficiency of carbon pricing. A second area of synergy is housing, transport, urban policies and community development, which all have potential to crucially contribute towards reducing carbon emissions. Finally, climate change mitigation will require substantial and rapid shifts in producer and consumer behaviour. Land use planning policy is a critical bridge between climate change and social policy that provides a means to explore the tensions and synergies that are evolving within this context. This paper will focus on spatial planning as an opportunity to develop strategies to adapt to climate change, and reviews the challenges of such change. Land use and spatial planning involve the allocation of land and the design and control of spatial patterns. Spatial planning is identified as being one of the most effective means of adapting settlements in response to climate change (Hurlimann and March, 2012). It provides the instrumental framework for adaptation (Meyer, et al., 2010) and operates as both a mechanism to achieve adaptation and a forum to negotiate priorities surrounding adaptation (Davoudi, et al., 2009). The acknowledged role of spatial planning in adaptation however has not translated into comparably significant consideration in planning literature (Davoudi, et al., 2009; Hurlimann and March, 2012). The discourse on adaptation specifically through spatial planning is described as ‘missing’ and ‘subordinate’ in national adaptation plans (Greiving and Fleischhauer, 2012),‘underrepresented’ (Roggema, et al., 2012)and ‘limited and disparate’ in planning literature (Davoudi, et al., 2009). Hurlimann and March (2012) suggest this may be due to limited experiences of adaptation in developed nations while Roggema et al. (2012) and Crane and Landis (2010) suggest it is because climate change is a wicked problem involving an unfamiliar problem, various frames of understanding and uncertain solutions. The potential for goal conflicts within this policy forum seem to outweigh the synergies. Yet, spatial planning will be a critical policy tool in the future to both protect and adapt communities to climate change.

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The diagnostics of mechanical components operating in transient conditions is still an open issue, in both research and industrial field. Indeed, the signal processing techniques developed to analyse stationary data are not applicable or are affected by a loss of effectiveness when applied to signal acquired in transient conditions. In this paper, a suitable and original signal processing tool (named EEMED), which can be used for mechanical component diagnostics in whatever operating condition and noise level, is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED) and the analytical approach of the Hilbert transform. The proposed tool is able to supply diagnostic information on the basis of experimental vibrations measured in transient conditions. The tool has been originally developed in order to detect localized faults on bearings installed in high speed train traction equipments and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on spectral kurtosis or envelope analysis, which represent until now the landmark for bearings diagnostics.

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The signal processing techniques developed for the diagnostics of mechanical components operating in stationary conditions are often not applicable or are affected by a loss of effectiveness when applied to signals measured in transient conditions. In this chapter, an original signal processing tool is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition, Minimum Entropy Deconvolution and the analytical approach of the Hilbert transform. The tool has been developed to detect localized faults on bearings of traction systems of high speed trains and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on envelope analysis or spectral kurtosis, which represent until now the landmark for bearings diagnostics.

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In the field of rolling element bearing diagnostics, envelope analysis has gained in the last years a leading role among the different digital signal processing techniques. The original constraint of constant operating speed has been relaxed thanks to the combination of this technique with the computed order tracking, able to resample signals at constant angular increments. In this way, the field of application of this technique has been extended to cases in which small speed fluctuations occur, maintaining high effectiveness and efficiency. In order to make this algorithm suitable to all industrial applications, the constraint on speed has to be removed completely. In fact, in many applications, the coincidence of high bearing loads, and therefore high diagnostic capability, with acceleration-deceleration phases represents a further incentive in this direction. This chapter presents a procedure for the application of envelope analysis to speed transients. The effect of load variation on the proposed technique will be also qualitatively addressed.

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Buffeting response of a cable-stayed bridge under construction is investigated through wind tunnel tests and numerical simulations. Two configurations of the erection stage have been considered and compared in terms of dynamic response and internal forces using the results of the experimental aeroelastic models. Moreover the results of a numerical model able to simulate the simultaneous effects of vortex shedding from tower and aeroelastic response of the deck are compared to the wind tunnel ones.

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In attempting to build intelligent litigation support tools, we have moved beyond first generation, production rule legal expert systems. Our work supplements rule-based reasoning with case based reasoning and intelligent information retrieval. This research, specifies an approach to the case based retrieval problem which relies heavily on an extended object-oriented / rule-based system architecture that is supplemented with causal background information. Machine learning techniques and a distributed agent architecture are used to help simulate the reasoning process of lawyers. In this paper, we outline our implementation of the hybrid IKBALS II Rule Based Reasoning / Case Based Reasoning system. It makes extensive use of an automated case representation editor and background information.

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Fault identification in industrial machine is a topic of major importance under engineering point of view. In fact, the possibility to identify not only the type, but also the severity and the position of a fault occurred along a shaft-line allows quick maintenance and shorten the downtime. This is really important in the power generation industry where the units are often of several tenths of meters long and where the rotors are enclosed by heavy and pressure-sealed casings. In this paper, an industrial experimental case is presented related to the identification of the unbalance on a large size steam turbine of about 1.3 GW, belonging to a nuclear power plant. The case history is analyzed by considering the vibrations measured by the condition monitoring system of the unit. A model-based method in the frequency domain, developed by the authors, is introduced in detail and it is then used to identify the position of the fault and its severity along the shaft-line. The complete model of the unit (rotor – modeled by means of finite elements, bearings – modeled by linearized damping and stiffness coefficients and foundation – modeled by means of pedestals) is analyzed and discussed before being used for the fault identification. The assessment of the actual fault was done by inspection during a scheduled maintenance and excellent correspondence was found with the identified one by means of authors’ proposed method. Finally a complete discussion is presented about the effectiveness of the method, even in presence of a not fine tuned machine model and considering only few measuring planes for the machine vibration.

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Rolling element bearings are the most critical components in the traction system of high speed trains. Monitoring their integrity is a fundamental operation in order to avoid catastrophic failures and to implement effective condition based maintenance strategies. Generally, diagnostics of rolling element bearings is usually performed by analyzing vibration signals measured by accelerometers placed in the proximity of the bearing under investigation. Several papers have been published on this subject in the last two decades, mainly devoted to the development and assessment of signal processing techniques for diagnostics. The experimental validation of such techniques has been traditionally performed by means of laboratory tests on artificially damaged bearings, while their actual effectiveness in specific industrial applications, particularly in rail industry, remains scarcely investigated. This paper is aimed at filling this knowledge gap, by addressing the diagnostics of bearings taken from the service after a long term operation on the traction system of a high speed train. Moreover, in order to test the effectiveness of the diagnostic procedures in the environmental conditions peculiar to the rail application, a specific test-rig has been built, consisting of a complete full-scale train traction system, able to reproduce the effects of wheeltrack interaction and bogie-wheelset dynamics. The results of the experimental campaign show that suitable signal processing techniques are able to diagnose bearing failures even in this harsh and noisy application. Moreover, the most suitable location of the sensors on the traction system is proposed, in order to limit their number.

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Any kind of imbalance in the operation of a wind turbine has adverse effect on the downstream torsional components as well as tower structure. It is crucial to detect imbalance at its very inception. The identification of the type of imbalance is also required so that appropriate measures of fault accommodation can be performed in the control system. In particular, it is important to distinguish between mass and aerodynamic imbalance. While the former is gradually caused by a structural anomaly (e.g. ice deposition, moisture accumulation inside blade), the latter is generally associated to a fault in the pitch control system. This paper proposes a technique for the detection and identification of imbalance fault in large scale wind turbines. Unlike most other existing method it requires only the rotor speed signal which is readily available in existing turbines. Signature frequencies have been proposed in this work to identify imbalance type based on their physical phenomenology. The performance of this technique has been evaluated by simulations using an existing benchmark model. The effectiveness of the proposed method has been confirmed by the simulation results.

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The new furnace at the Materials Characterization by X-ray Diffraction beamline at Elettra has been designed for powder diffraction measurements at high temperature (up to 1373 K at the present state). Around the measurement region the geometry of the radiative heating element assures a negligible temperature gradient along the capillary and can accommodate either powder samples in capillary or small flat samples. A double capillary holder allows flow-through of gas in the inner sample capillary while the outer one serves as the reaction chamber. The furnace is coupled to a translating curved imaging-plate detector, allowing the collection of diffraction patterns up to 2[theta] [asymptotically equal to] 130°.