79 resultados para Simulation analysis

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


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A strain gauge instrumentation trial on a high pressure die casting ‘HPDC’ die was compared to a corresponding simulation model using Magmasoft® casting simulation software at two strain gauge rosette locations. The strains were measured during the casting cycle, from which the von Mises stress was determined and then compared to the simulation model. The von Mises stress from the simulation model correlated well with the findings from the instrumentation trial, showing a difference of 5.5%, ~ 10 MPa for one strain gauge rosette located in an area of low stress gradient. The second rosette was in a region of steep stress gradient, which resulted in a difference of up to 40%, ~40 MPa between the simulation and instrumentation results. Factors such as additional loading from die closure force or metal injection pressure which are not modelled by Magmasoft® were seen to have very little influence on the stress in the die, less than 7%.

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Background and purpose: Currently, optimal use of virtual simulation for all treatment sites is not entirely clear. This study presents data to identify specific patient groups for whom conventional simulation may be completely eliminated and replaced by virtual simulation. Sampling and method: Two hundred and sixty patients were recruited from four treatment sites (head and neck, breast, pelvis, and thorax). Patients were randomly assigned to be treated using the usual treatment process involving conventional simulation, or a treatment process differing only in the replacement of conventional plan verification with virtual verification. Data were collected on set-up accuracy at verification, and the number of unsatisfactory verifications requiring a return to the conventional simulator. A micro-economic costing analysis was also undertaken, whereby data for each treatment process episode were also collected: number and grade of staff present, and the time for each treatment episode. Results: The study shows no statistically significant difference in the number of returns to the conventional simulator for each site and study arm. Image registration data show similar quality of verification for each study arm. The micro-costing data show no statistical difference between the virtual and conventional simulation processes. Conclusions: At our institution, virtual simulation including virtual verification for the sites investigated presents no disadvantage compared to conventional simulation.

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Previous papers have noted the difficulty in obtaining neural models which are stable under simulation when trained using prediction-error-based methods. Here the differences between series-parallel and parallel identification structures for training neural models are investigated. The effect of the error surface shape on training convergence and simulation performance is analysed using a standard algorithm operating in both training modes. A combined series-parallel/parallel training scheme is proposed, aiming to provide a more effective means of obtaining accurate neural simulation models. Simulation examples show the combined scheme is advantageous in circumstances where the solution space is known or suspected to be complex. (c) 2006 Elsevier B.V. All rights reserved.

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Microscopic simulation models are often evaluated based on visual inspection of the results. This paper presents formal econometric techniques to compare microscopic simulation (MS) models with real-life data. A related result is a methodology to compare different MS models with each other. For this purpose, possible parameters of interest, such as mean returns, or autocorrelation patterns, are classified and characterized. For each class of characteristics, the appropriate techniques are presented. We illustrate the methodology by comparing the MS model developed by He and Li [J. Econ. Dynam. Control, 2007, 31, 3396-3426, Quant. Finance, 2008, 8, 59-79] with actual data.

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In this paper the use of eigenvalue stability analysis of very large dimension aeroelastic numerical models arising from the exploitation of computational fluid dynamics is reviewed. A formulation based on a block reduction of the system Jacobian proves powerful to allow various numerical algorithms to be exploited, including frequency domain solvers, reconstruction of a term describing the fluid–structure interaction from the sparse data which incurs the main computational cost, and sampling to place the expensive samples where they are most needed. The stability formulation also allows non-deterministic analysis to be carried out very efficiently through the use of an approximate Newton solver. Finally, the system eigenvectors are exploited to produce nonlinear and parameterised reduced order models for computing limit cycle responses. The performance of the methods is illustrated with results from a number of academic and large dimension aircraft test cases.

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Background
Medical students transitioning into professional practice feel underprepared to deal with the emotional complexities of real-life ethical situations. Simulation-based learning (SBL) may provide a safe environment for students to probe the boundaries of ethical encounters. Published studies of ethics simulation have not generated sufficiently deep accounts of student experience to inform pedagogy. The aim of this study was to understand students’ lived experiences as they engaged with the emotional challenges of managing clinical ethical dilemmas within a SBL environment.

Methods
This qualitative study was underpinned by an interpretivist epistemology. Eight senior medical students participated in an interprofessional ward-based SBL activity incorporating a series of ethically challenging encounters. Each student wore digital video glasses to capture point-of-view (PoV) film footage. Students were interviewed immediately after the simulation and the PoV footage played back to them. Interviews were transcribed verbatim. An interpretative phenomenological approach, using an established template analysis approach, was used to iteratively analyse the data.

Results
Four main themes emerged from the analysis: (1) ‘Authentic on all levels?’, (2)‘Letting the emotions flow’, (3) ‘Ethical alarm bells’ and (4) ‘Voices of children and ghosts’. Students recognised many explicit ethical dilemmas during the SBL activity but had difficulty navigating more subtle ethical and professional boundaries. In emotionally complex situations, instances of moral compromise were observed (such as telling an untruth). Some participants felt unable to raise concerns or challenge unethical behaviour within the scenarios due to prior negative undergraduate experiences.

Conclusions
This study provided deep insights into medical students’ immersive and embodied experiences of ethical reasoning during an authentic SBL activity. By layering on the human dimensions of ethical decision-making, students can understand their personal responses to emotion, complexity and interprofessional working. This could assist them in framing and observing appropriate ethical and professional boundaries and help smooth the transition into clinical practice.