9 resultados para 080603 Conceptual Modelling

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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One habitat management requirement forced by 21st century relative sea-level rise (RSLR), will be the need to re-comprehend the dimensions of long-term transgressive behaviour of coastal systems being forced by such RSLR. Fresh approaches to the conceptual modelling and subsequent implementation of new coastal and peri-marine habitats will be required. There is concern that existing approaches to forecasting coastal systems development (and by implication their associated scarce coastal habitats) over the next century depend on a certain premise of orderly spatial succession of habitats. This assumption is shown to be questionable given the possible future rates of RSLR, magnitude of shoreline retreat and the lack of coastal sediment to maintain the protective morphologies to low-energy coastal habitats. Of these issues, sediment deficiency is regarded as one of the major problem for future habitat development. Examples of contemporary behaviour of UK coasts show evidence of coastal sediment starvation resulting from relatively stable RSLR, anthropogenic sealing of coastal sources, and intercepted coastal sediment pathways, which together force segmentation of coastal systems. From these examples key principles are deduced which may prejudice the existence of future habitats: accelerated future sediment demand due to RSLR may not be met by supply and, if short- to medium-term hold-the-line policies predominate, long-term strategies for managed realignment and habitat enhancement may prove impossible goals. Methods of contemporary sediment husbandry may help sustain some habitats in place but otherwise, instead of integrated coastal organization, managers may need to consider coastal breakdown, segmentation and habitat reduction as the basis of 21st century coastal evolution and planning.

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The article presents cost modeling results from the application of the Genetic-Causal cost modeling principle. Industrial results from redesign are also presented to verify the opportunity for early concept cost optimization by using Genetic-Causal cost drivers to guide the conceptual design process for structural assemblies. The acquisition cost is considered through the modeling of the recurring unit cost and non-recurring design cost. The operational cost is modeled relative to acquisition cost and fuel burn for predominately metal or composites designs. The main contribution of this study is the application of the Genetic-Causal principle to the modeling of cost, helping to understand how conceptual design parameters impact on cost, and linking that to customer requirements and life cycle cost.

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Multivariate classification techniques have proven to be powerful tools for distinguishing experimental conditions in single sessions of functional magnetic resonance imaging (fMRI) data. But they are vulnerable to a considerable penalty in classification accuracy when applied across sessions or participants, calling into question the degree to which fine-grained encodings are shared across subjects. Here, we introduce joint learning techniques, where feature selection is carried out using a held-out subset of a target dataset, before training a linear classifier on a source dataset. Single trials of functional MRI data from a covert property generation task are classified with regularized regression techniques to predict the semantic class of stimuli. With our selection techniques (joint ranking feature selection (JRFS) and disjoint feature selection (DJFS)), classification performance during cross-session prediction improved greatly, relative to feature selection on the source session data only. Compared with JRFS, DJFS showed significant improvements for cross-participant classification. And when using a groupwise training, DJFS approached the accuracies seen for prediction across different sessions from the same participant. Comparing several feature selection strategies, we found that a simple univariate ANOVA selection technique or a minimal searchlight (one voxel in size) is appropriate, compared with larger searchlights.

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The work presented is concerned with the estimation of manufacturing cost at the concept design stage, when little technical information is readily available. The work focuses on the nose cowl sections of a wide range of engine nacelles built at Bombardier Aerospace Shorts of Belfast. A core methodology is presented that: defines manufacturing cost elements that are prominent; utilises technical parameters that are highly influential in generating those costs; establishes the linkage between these two; and builds the associated cost estimating relations into models. The methodology is readily adapted to deal with both the early and more mature conceptual design phases, which thereby highlights the generic, flexible and fundamental nature of the method. The early concept cost model simplifies cost as a cumulative element that can be estimated using higher level complexity ratings, while the mature concept cost model breaks manufacturing cost down into a number of constituents that are each driven by their own specific drivers. Both methodologies have an average error of less that ten percent when correlated with actual findings, thus achieving an acceptable level of accuracy. By way of validity and application, the research is firmly based on industrial case studies and practice and addresses the integration of design and manufacture through cost. The main contribution of the paper is the cost modelling methodology. The elemental modelling of the cost breakdown structure through materials, part fabrication, assembly and their associated drivers is relevant to the analytical design procedure, as it utilises design definition and complexity that is understood by engineers.

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The purpose of this study is to survey the use of networks and network-based methods in systems biology. This study starts with an introduction to graph theory and basic measures allowing to quantify structural properties of networks. Then, the authors present important network classes and gene networks as well as methods for their analysis. In the last part of this study, the authors review approaches that aim at analysing the functional organisation of gene networks and the use of networks in medicine. In addition to this, the authors advocate networks as a systematic approach to general problems in systems biology, because networks are capable of assuming multiple roles that are very beneficial connecting experimental data with a functional interpretation in biological terms.

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Reliable prediction of long-term medical device performance using computer simulation requires consideration of variability in surgical procedure, as well as patient-specific factors. However, even deterministic simulation of long-term failure processes for such devices is time and resource consuming so that including variability can lead to excessive time to achieve useful predictions. This study investigates the use of an accelerated probabilistic framework for predicting the likely performance envelope of a device and applies it to femoral prosthesis loosening in cemented hip arthroplasty.
A creep and fatigue damage failure model for bone cement, in conjunction with an interfacial fatigue model for the implant–cement interface, was used to simulate loosening of a prosthesis within a cement mantle. A deterministic set of trial simulations was used to account for variability of a set of surgical and patient factors, and a response surface method was used to perform and accelerate a Monte Carlo simulation to achieve an estimate of the likely range of prosthesis loosening. The proposed framework was used to conceptually investigate the influence of prosthesis selection and surgical placement on prosthesis migration.
Results demonstrate that the response surface method is capable of dramatically reducing the time to achieve convergence in mean and variance of predicted response variables. A critical requirement for realistic predictions is the size and quality of the initial training dataset used to generate the response surface and further work is required to determine the recommendations for a minimum number of initial trials. Results of this conceptual application predicted that loosening was sensitive to the implant size and femoral width. Furthermore, different rankings of implant performance were predicted when only individual simulations (e.g. an average condition) were used to rank implants, compared with when stochastic simulations were used. In conclusion, the proposed framework provides a viable approach to predicting realistic ranges of loosening behaviour for orthopaedic implants in reduced timeframes compared with conventional Monte Carlo simulations.

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Approach:
In-situ passive gradient comparative artificial tracer testing, undertaken using solutes (Uranine and Iodide), Bacteria (E.coli and P.putida) and bacteriophage (H40/1), permitted comparison of the mobility of different sized microorganisms relative to solutes in the sand and gravel aquifer underlying Dornach, Germany.
Tracer breakthrough curves reveal that even though uranine initially arrived at observation wells at the same time as microbiological tracers, maximum relative concentrations were sometimes less than those of microbiological tracers, while solute breakthrough curves proved more disperse.
Monitoring uranine breakthrough with depth suggested tracers arrived in observation wells in discrete 0.5m-1m thick intervals, over the aquifer’s 12m saturated thickness. Nearby exposures of aquifer material suggested that the aquifer consisted of sandy gravels enveloping sequences of open framework (OW) gravel up to 1m thick. Detailed examination of OW units revealed that they contained lenses of silty sand up to 1m long x 30cm thick., while granulometric data suggested that the gravel was two to three orders of magnitude more permeable than the enveloping sandy gravel.
Solute and microorganism tracer responses could not be simulated using conventional advective-dispersive equation solutions employing the same velocity and dispersion terms. By contrast solute tracer responses, modelled using a dual porosity approach for fractured media (DP-1D) corresponded well to observed field data. Simulating microorganism responses using the same transport terms, but no dual porosity term, generated good model fits and explained the higher relative concentration of the bacteria, compared to the non-reactive solute, even with first order removal to account for lower RR. Geologically, model results indicate that the silty units within open framework gravels are accessible to solute tracers, but not to microorganisms.
Importance:
Results highlight the benefits of geological observations developing appropriate conceptual models of solute and micro organism transport and in developing suitable numerical approaches to quantifying microorganism mobility at scales appropriate for the development of groundwater supply (wellhead) protection zones.

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Executive Summary
The Pathways Project field studies were targeted at improving the understanding of contaminant transport along different hydrological pathways in Irish catchments, including their associated impacts on water quality and river ecology. The contaminants of interest were phosphorus, nitrogen and sediment. The working Pathways conceptual model included overland flow, interflow, shallow groundwater flow, and deep groundwater flow. This research informed the development of a set of Catchment Management Support Tools (CMSTs) comprising an Exploratory Tool, Catchment Characterization Tool (CCT) and Catchment Modelling Tool (CMT) as outlined in Pathways Project Final Reports Volumes 3 and 4.
In order to inform the CMST, four suitable study catchments were selected following an extensive selection process, namely the Mattock catchment, Co. Louth/Meath; Gortinlieve catchment, Co. Donegal; Nuenna catchment, Co. Kilkenny and the Glen Burn catchment, Co. Down. The Nuenna catchment is well drained as it is underlain by a regionally important karstified limestone aquifer with permeable limestone tills and gravels, while the other three catchments are underlain by poorly productive aquifers and low permeability clayey tills, and are poorly drained.
All catchments were instrumented, and groundwater, surface and near-surface water and aquatic ecology were monitored for a period of two years. Intensive water quality sampling during rainfall events was used to investigate the pathways delivering nutrients. The proportion of flow along each pathway was determined using chemical and physical hydrograph separation techniques, supported by numerical modelling.
The outcome of the field studies broadly supported the use of the initial four-pathway conceptual model used in the Pathways CMT (time-variant model). The artificial drainage network was found to be a significant contributing pathway in the poorly drained catchments, at low flows and during peak flows in wet antecedent conditions. The transition zone (TZ), i.e. the broken up weathered zone at the top of the bedrock, was also found to be an important pathway. It was observed to operate in two contrasting hydrogeological scenarios: in groundwater discharge zones the TZ can be regarded as being part of the shallow groundwater pathway, whereas in groundwater recharge zones it behaves more like interflow.
In the catchments overlying poorly productive aquifers, only a few fractures or fracture zones were found to be hydraulically active and the TZ, where present, was the main groundwater pathway. In the karstified Nuenna catchment, the springs, which are linked to conduits as well as to a diffuse fracture network, delivered the majority of the flow. These findings confirm the two-component groundwater contribution from bedrock but suggest that the size and nature of the hydraulically active fractures and the nature of the TZ are the dominant factors at the scale of a stream flow event.
Diffuse sources of nitrate were found to be typically delivered via the subsurface pathways, especially in the TZ and land drains in the poorly productive aquifer catchments, and via the bedrock groundwater in the Nuenna. Phosphorus was primarily transported via overland flow in both particulate and soluble forms. Where preferential flow paths existed in the soil and subsoil, soluble P, and to a lesser extent particulate P, were also transported via the TZ and in drains and ditches. Arable land was found to be the most important land use for
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the delivery of sediment, although channel bank and in-stream sources were the most significant in the Glen Burn catchment. Overland flow was found to be the predominant transport sediment pathway in the poorly productive catchments. These findings informed the development of the transport and attenuation equations used in the CCT and CMT. From an assessment of the relationship between physico-chemical and biological conditions, it is suggested that in the Nuenna, Glen Burn and Gortinlieve catchments, a relationship may exist between biological water quality and nitrogen concentrations, as well as with P. In the Nuenna, there was also a relationship between macroinvertebrate status and alkalinity.
Further research is recommended on the transport and delivery of phosphorus in groundwater, the transport and attenuation dynamics in the TZ in different hydrogeological settings and the relationship between macroinvertebrates and co-limiting factors. High resolution temporal and spatial sampling was found to be important for constraining the conceptual understanding of nutrient and sediment dynamics which should also be considered in future studies.

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The Consideration of Future Consequences construct has been found to relate meaningfully to several positive outcomes in temporal research. Researchers have proposed 1-factor, 2-factor, and bifactor solutions to the Consideration of Future Consequences Scale (CFCS). Using 313 British University undergraduates, we tested four competing models: (a) a 12-item unidimensional model, (b) a model fitted for two uncorrelated factors (CFC-Immediate and CFC-Future), (c) a model fitted for two correlated factors (CFC-I and CFC-F), and (d) a bifactor model. Results supported the bifactor model, suggesting that the two hypothesized factors are better understood as grouping factors. Accordingly, the present study supports the CFCS as a unidimensional global future orientation measure. These results have important implications for the study of future orientation using the CFCS. Researchers using the CFCS are encouraged to examine a bifactor solution for the scores.