11 resultados para domain analysis

em CORA - Cork Open Research Archive - University College Cork - Ireland


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The wave energy industry is entering a new phase of pre-commercial and commercial deployments of full-scale devices, so better understanding of seaway variability is critical to the successful operation of devices. The response of Wave Energy Converters to incident waves govern their operational performance and for many devices, this is highly dependent on spectral shape due to their resonant properties. Various methods of wave measurement are presented, along with analysis techniques and empirical models. Resource assessments, device performance predictions and monitoring of operational devices will often be based on summary statistics and assume a standard spectral shape such as Pierson-Moskowitz or JONSWAP. Furthermore, these are typically derived from the closest available wave data, frequently separated from the site on scales in the order of 1km. Therefore, variability of seaways from standard spectral shapes and spatial inconsistency between the measurement point and the device site will cause inaccuracies in the performance assessment. This thesis categorises time and frequency domain analysis techniques that can be used to identify changes in a sea state from record to record. Device specific issues such as dimensional scaling of sea states and power output are discussed along with potential differences that arise in estimated and actual output power of a WEC due to spectral shape variation. This is investigated using measured data from various phases of device development.

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We analyze the physical-chemical surface properties of single-slit, single-groove subwavelength-structured silver films with high-resolution transmission electron microscopy and calculate exact solutions to Maxwell’s equations corresponding to recent far-field interferometry experiments using these structures. Contrary to a recent suggestion the surface analysis shows that the silver films are free of detectable contaminants. The finite-difference time-domain calculations, in excellent agreement with experiment, show a rapid fringe amplitude decrease in the near zone (slit-groove distance out to 3–4 wavelengths). Extrapolation to slit-groove distances beyond the near zone shows that the surface wave evolves to the expected bound surface plasmon polariton (SPP). Fourier analysis of these results indicates the presence of a distribution of transient, evanescent modes around the SPP that dephase and dissipate as the surface wave evolves from the near to the far zone.

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This work deals with the numerical studies on hydrodynamics of oscillating water column (OWC) wave energy converters and its damping optimization on maximizing wave energy conversion by the OWC device. As a fundamental step, the hydrodynamic problems have been systematically studied by considering the interactions of the wave-structure and of the wave-internal water surface. Our first attention is on how the hydrodynamic performance can be reliably assessed, especially when it comes to the time-domain analysis, and what the physics behind the considerations is. Further on, a damping optimization for the OWC wave energy converter is also present based on the dynamics of the linear system, and a study on how we can optimize the damping for the given sea states so that the power conversion from irregular waves from irregular waves can be maximized.

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This paper presents a study on the numerical simulation of the primary wave energy conversion in the oscillating water column (OWC) wave energy converters (WECs). The new proposed numerical approach consists of three major components: potential flow analysis for the conventional hydrodynamic parameters, such as added mass, damping coefficients, restoring force coefficients and wave excitations; the thermodynamic analysis of the air in the air chamber, which is under the assumptions of the given power take-off characteristics and an isentropic process of air flow. In the formulation, the air compressibility and its effects have been included; and a time-domain analysis by combining the linear potential flow and the thermodynamics of the air flow in the chamber, in which the hydrodynamics and thermodynamics/aerodynamics have been coupled together by the force generated by the pressurised and de-pressurised air in the air chamber, which in turn has effects on the motions of the structure and the internal water surface. As an example, the new developed approach has been applied to a fixed OWC device. The comparisons of the measured data and the simulation results show the new method is very capable of predicting the performance of the OWC devices.

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This paper presents an investigation on air compressibility in the air chamber and its effects on the power conversion of oscillating water column (OWC) devices. As it is well known that for practical OWC plants, their air chambers may be large enough for accommodating significant air compressibility, the “spring effect,” an effect that is frequently and simply regarded to store and release energy during the reciprocating process of a wave cycle. Its insight effects on the device’s performance and power conversion, however, have not been studied in detail. This research will investigate the phenomena with a special focus on the effects of air compressibility on wave energy conversion. Air compressibility itself is a complicated nonlinear process in nature, but it can be linearised for numerical simulations under certain assumptions for frequency domain analysis. In this research work, air compressibility in the OWC devices is first linearised and further coupled with the hydrodynamics of the OWC. It is able to show mathematically that in frequency-domain, air compressibility can increase the spring coefficients of both the water body motion and the device motion (if it is a floating device), and enhance the coupling effects between the water body and the structure. Corresponding to these changes, the OWC performance, the capture power, and the optimised Power Take-off (PTO) damping coefficient in the wave energy conversion can be all modified due to air compressibility. To validate the frequency-domain results and understand the problems better, the more accurate time-domain simulations with fewer assumptions have been used for comparison. It is shown that air compressibility may significantly change the dynamic responses and the capacity of converting wave energy of the OWC devices if the air chamber is very large.

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An aim of proactive risk management strategies is the timely identification of safety related risks. One way to achieve this is by deploying early warning systems. Early warning systems aim to provide useful information on the presence of potential threats to the system, the level of vulnerability of a system, or both of these, in a timely manner. This information can then be used to take proactive safety measures. The United Nation’s has recommended that any early warning system need to have four essential elements, which are the risk knowledge element, a monitoring and warning service, dissemination and communication and a response capability. This research deals with the risk knowledge element of an early warning system. The risk knowledge element of an early warning system contains models of possible accident scenarios. These accident scenarios are created by using hazard analysis techniques, which are categorised as traditional and contemporary. The assumption in traditional hazard analysis techniques is that accidents are occurred due to a sequence of events, whereas, the assumption of contemporary hazard analysis techniques is that safety is an emergent property of complex systems. The problem is that there is no availability of a software editor which can be used by analysts to create models of accident scenarios based on contemporary hazard analysis techniques and generate computer code that represent the models at the same time. This research aims to enhance the process of generating computer code based on graphical models that associate early warning signs and causal factors to a hazard, based on contemporary hazard analyses techniques. For this purpose, the thesis investigates the use of Domain Specific Modeling (DSM) technologies. The contributions of this thesis is the design and development of a set of three graphical Domain Specific Modeling languages (DSML)s, that when combined together, provide all of the necessary constructs that will enable safety experts and practitioners to conduct hazard and early warning analysis based on a contemporary hazard analysis approach. The languages represent those elements and relations necessary to define accident scenarios and their associated early warning signs. The three DSMLs were incorporated in to a prototype software editor that enables safety scientists and practitioners to create and edit hazard and early warning analysis models in a usable manner and as a result to generate executable code automatically. This research proves that the DSM technologies can be used to develop a set of three DSMLs which can allow user to conduct hazard and early warning analysis in more usable manner. Furthermore, the three DSMLs and their dedicated editor, which are presented in this thesis, may provide a significant enhancement to the process of creating the risk knowledge element of computer based early warning systems.

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The second messenger c-di-GMP is implicated in regulation of various aspects of the lifestyles and virulence of Gram-negative bacteria. Cyclic di-GMP is formed by diguanylate cyclases with a GGDEF domain and degraded by phosphodiesterases with either an EAL or HD-GYP domain. Proteins with tandem GGDEF-EAL domains occur in many bacteria, where they may be involved in c-di-GMP turnover or act as enzymatically-inactive c-di-GMP effectors. Here, we report a systematic study of the regulatory action of the eleven GGDEF-EAL proteins in Xanthomonas oryzae pv. oryzicola, an important rice pathogen causing bacterial leaf streak. Mutational analysis revealed that XOC_2335 and XOC_2393 positively regulate bacterial swimming motility, while XOC_2102, XOC_2393 and XOC_4190 negatively control sliding motility. The ΔXOC_2335/XOC_2393 mutant that had a higher intracellular c-di-GMP level than the wild type and the ΔXOC_4190 mutant exhibited reduced virulence to rice after pressure inoculation. In vitro purified XOC_4190 and XOC_2102 have little or no diguanylate cyclase or phosphodiesterase activity, which is consistent with unaltered c-di-GMP concentration in ΔXOC_4190. Nevertheless, both proteins can bind to c-di-GMP with high affinity, indicating a potential role as c-di-GMP effectors. Overall our findings advance understanding of c-di-GMP signaling and its links to virulence in an important rice pathogen.

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Motivated by accurate average-case analysis, MOdular Quantitative Analysis (MOQA) is developed at the Centre for Efficiency Oriented Languages (CEOL). In essence, MOQA allows the programmer to determine the average running time of a broad class of programmes directly from the code in a (semi-)automated way. The MOQA approach has the property of randomness preservation which means that applying any operation to a random structure, results in an output isomorphic to one or more random structures, which is key to systematic timing. Based on original MOQA research, we discuss the design and implementation of a new domain specific scripting language based on randomness preserving operations and random structures. It is designed to facilitate compositional timing by systematically tracking the distributions of inputs and outputs. The notion of a labelled partial order (LPO) is the basic data type in the language. The programmer uses built-in MOQA operations together with restricted control flow statements to design MOQA programs. This MOQA language is formally specified both syntactically and semantically in this thesis. A practical language interpreter implementation is provided and discussed. By analysing new algorithms and data restructuring operations, we demonstrate the wide applicability of the MOQA approach. Also we extend MOQA theory to a number of other domains besides average-case analysis. We show the strong connection between MOQA and parallel computing, reversible computing and data entropy analysis.

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Helicobacter pylori is a gastric pathogen which infects ~50% of the global population and can lead to the development of gastritis, gastric and duodenal ulcers and carcinoma. Genome sequencing of H. pylori revealed high levels of genetic variability; this pathogen is known for its adaptability due to mechanisms including phase variation, recombination and horizontal gene transfer. Motility is essential for efficient colonisation by H. pylori. The flagellum is a complex nanomachine which has been studied in detail in E. coli and Salmonella. In H. pylori, key differences have been identified in the regulation of flagellum biogenesis, warranting further investigation. In this study, the genomes of two H. pylori strains (CCUG 17874 and P79) were sequenced and published as draft genome sequences. Comparative studies identified the potential role of restriction modification systems and the comB locus in transformation efficiency differences between these strains. Core genome analysis of 43 H. pylori strains including 17874 and P79 defined a more refined core genome for the species than previously published. Comparative analysis of the genome sequences of strains isolated from individuals suffering from H. pylori related diseases resulted in the identification of “disease-specific” genes. Structure-function analysis of the essential motility protein HP0958 was performed to elucidate its role during flagellum assembly in H. pylori. The previously reported HP0958-FliH interaction could not be substantiated in this study and appears to be a false positive. Site-directed mutagenesis confirmed that the coiled-coil domain of HP0958 is involved in the interaction with RpoN (74-284), while the Zn-finger domain is required for direct interaction with the full length flaA mRNA transcript. Complementation of a non-motile hp0958-null derivative strain of P79 with site-directed mutant alleles of hp0958 resulted in cells producing flagellar-type extrusions from non-polar positions. Thus, HP0958 may have a novel function in spatial localisation of flagella in H. pylori

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It is estimated that the quantity of digital data being transferred, processed or stored at any one time currently stands at 4.4 zettabytes (4.4 × 2 70 bytes) and this figure is expected to have grown by a factor of 10 to 44 zettabytes by 2020. Exploiting this data is, and will remain, a significant challenge. At present there is the capacity to store 33% of digital data in existence at any one time; by 2020 this capacity is expected to fall to 15%. These statistics suggest that, in the era of Big Data, the identification of important, exploitable data will need to be done in a timely manner. Systems for the monitoring and analysis of data, e.g. stock markets, smart grids and sensor networks, can be made up of massive numbers of individual components. These components can be geographically distributed yet may interact with one another via continuous data streams, which in turn may affect the state of the sender or receiver. This introduces a dynamic causality, which further complicates the overall system by introducing a temporal constraint that is difficult to accommodate. Practical approaches to realising the system described above have led to a multiplicity of analysis techniques, each of which concentrates on specific characteristics of the system being analysed and treats these characteristics as the dominant component affecting the results being sought. The multiplicity of analysis techniques introduces another layer of heterogeneity, that is heterogeneity of approach, partitioning the field to the extent that results from one domain are difficult to exploit in another. The question is asked can a generic solution for the monitoring and analysis of data that: accommodates temporal constraints; bridges the gap between expert knowledge and raw data; and enables data to be effectively interpreted and exploited in a transparent manner, be identified? The approach proposed in this dissertation acquires, analyses and processes data in a manner that is free of the constraints of any particular analysis technique, while at the same time facilitating these techniques where appropriate. Constraints are applied by defining a workflow based on the production, interpretation and consumption of data. This supports the application of different analysis techniques on the same raw data without the danger of incorporating hidden bias that may exist. To illustrate and to realise this approach a software platform has been created that allows for the transparent analysis of data, combining analysis techniques with a maintainable record of provenance so that independent third party analysis can be applied to verify any derived conclusions. In order to demonstrate these concepts, a complex real world example involving the near real-time capturing and analysis of neurophysiological data from a neonatal intensive care unit (NICU) was chosen. A system was engineered to gather raw data, analyse that data using different analysis techniques, uncover information, incorporate that information into the system and curate the evolution of the discovered knowledge. The application domain was chosen for three reasons: firstly because it is complex and no comprehensive solution exists; secondly, it requires tight interaction with domain experts, thus requiring the handling of subjective knowledge and inference; and thirdly, given the dearth of neurophysiologists, there is a real world need to provide a solution for this domain

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The Leaving Certificate (LC) is the national, standardised state examination in Ireland necessary for entry to third level education – this presents a massive, raw corpus of data with the potential to yield invaluable insight into the phenomena of learner interlanguage. With samples of official LC Spanish examination data, this project has compiled a digitised corpus of learner Spanish comprised of the written and oral production of 100 candidates. This corpus was then analysed using a specific investigative corpus technique, Computer-aided Error Analysis (CEA, Dagneaux et al, 1998). CEA is a powerful apparatus in that it greatly facilitates the quantification and analysis of a large learner corpus in digital format. The corpus was both compiled and analysed with the use of UAM Corpus Tool (O’Donnell 2013). This Tool allows for the recording of candidate-specific variables such as grade, examination level, task type and gender, therefore allowing for critical analysis of the corpus as one unit, as separate written and oral sub corpora and also of performance per task, level and gender. This is an interdisciplinary work combining aspects of Applied Linguistics, Learner Corpus Research and Foreign Language (FL) Learning. Beginning with a review of the context of FL learning in Ireland and Europe, I go on to discuss the disciplinary context and theoretical framework for this work and outline the methodology applied. I then perform detailed quantitative and qualitative analyses before going on to combine all research findings outlining principal conclusions. This investigation does not make a priori assumptions about the data set, the LC Spanish examination, the context of FLs or of any aspect of learner competence. It undertakes to provide the linguistic research community and the domain of Spanish language learning and pedagogy in Ireland with an empirical, descriptive profile of real learner performance, characterising learner difficulty.