999 resultados para backward simulation


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Computational fluid dynamics (CFD) models for ultrahigh velocity waterjets and abrasive waterjets (AWJs) are established using the Fluent 6 flow solver. Jet dynamic characteristics for the flow downstream from a very fine nozzle are then simulated under steady state, turbulent, two-phase and three-phase flow conditions. Water and particle velocities in a jet are obtained under different input and boundary conditions to provide an insight into the jet characteristics and a fundamental understanding of the kerf formation process in AWJ cutting. For the range of downstream distances considered, the results indicate that a jet is characterised by an initial rapid decay of the axial velocity at the jet centre while the cross-sectional flow evolves towards a top-hat profile downstream.

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High fidelity simulation as a teaching and learning approach is being embraced by many schools of nursing. Our school embarked on integrating high fidelity (HF) simulation into the undergraduate clinical education program in 2011. Low and medium fidelity simulation has been used for many years, but this did not simplify the integration of HF simulation. Alongside considerations of how and where HF simulation would be integrated, issues arose with: student consent and participation for observed activities; data management of video files; staff development, and conceptualising how methods for student learning could be researched. Simulation for undergraduate student nurses commenced as a formative learning activity, undertaken in groups of eight, where four students undertake the ‘doing’ role and four are structured observers, who then take a formal role in the simulation debrief. Challenges for integrating simulation into student learning included conceptualising and developing scenarios to trigger students’ decision making and application of skills, knowledge and attitudes explicit to solving clinical ‘problems’. Developing and planning scenarios for students to ‘try out’ skills and make decisions for problem solving lay beyond choosing pre-existing scenarios inbuilt with the software. The supplied scenarios were not concept based but rather knowledge, skills and technology (of the manikin) focussed. Challenges lay in using the technology for the purpose of building conceptual mastery rather than using technology simply because it was available. As we integrated use of HF simulation into the final year of the program, focus was on building skills, knowledge and attitudes that went beyond technical skill, and provided an opportunity to bridge the gap with theory-based knowledge that students often found difficult to link to clinical reality. We wished to provide opportunities to develop experiential knowledge based on application and clinical reasoning processes in team environments where problems are encountered, and to solve them, the nurse must show leadership and direction. Other challenges included students consenting for simulations to be videotaped and ethical considerations of this. For example if one student in a group of eight did not consent, did this mean they missed the opportunity to undertake simulation, or that others in the group may be disadvantaged by being unable to review their performance. This has implications for freely given consent but also for equity of access to learning opportunities for students who wished to be taped and those who did not. Alongside this issue were the details behind data management, storage and access. Developing staff with varying levels of computer skills to use software and undertake a different approach to being the ‘teacher’ required innovation where we took an experiential approach. Considering explicit learning approaches to be trialled for learning was not a difficult proposition, but considering how to enact this as research with issues of blinding, timetabling of blinded groups, and reducing bias for testing results of different learning approaches along with gaining ethical approval was problematic. This presentation presents examples of these challenges and how we overcame them.

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AIMS This paper reports on the implementation of a research project that trials an educational strategy implemented over six months of an undergraduate third year nursing curriculum. This project aims to explore the effectiveness of ‘think aloud’ as a strategy for learning clinical reasoning for students in simulated clinical settings. BACKGROUND Nurses are required to apply and utilise critical thinking skills to enable clinical reasoning and problem solving in the clinical setting [1]. Nursing students are expected to develop and display clinical reasoning skills in practice, but may struggle articulating reasons behind decisions about patient care. For students learning to manage complex clinical situations, teaching approaches are required that make these instinctive cognitive processes explicit and clear [2-5]. In line with professional expectations, nursing students in third year at Queensland University of Technology (QUT) are expected to display clinical reasoning skills in practice. This can be a complex proposition for students in practice situations, particularly as the degree of uncertainty or decision complexity increases [6-7]. The ‘think aloud’ approach is an innovative learning/teaching method which can create an environment suitable for developing clinical reasoning skills in students [4, 8]. This project aims to use the ‘think aloud’ strategy within a simulation context to provide a safe learning environment in which third year students are assisted to uncover cognitive approaches that best assist them to make effective patient care decisions, and improve their confidence, clinical reasoning and active critical reflection on their practice. MEHODS In semester 2 2011 at QUT, third year nursing students will undertake high fidelity simulation, some for the first time commencing in September of 2011. There will be two cohorts for strategy implementation (group 1= use think aloud as a strategy within the simulation, group 2= not given a specific strategy outside of nursing assessment frameworks) in relation to problem solving patient needs. Students will be briefed about the scenario, given a nursing handover, placed into a simulation group and an observer group, and the facilitator/teacher will run the simulation from a control room, and not have contact (as a ‘teacher’) with students during the simulation. Then debriefing will occur as a whole group outside of the simulation room where the session can be reviewed on screen. The think aloud strategy will be described to students in their pre-simulation briefing and allow for clarification of this strategy at this time. All other aspects of the simulations remain the same, (resources, suggested nursing assessment frameworks, simulation session duration, size of simulation teams, preparatory materials). RESULTS Methodology of the project and the challenges of implementation will be the focus of this presentation. This will include ethical considerations in designing the project, recruitment of students and implementation of a voluntary research project within a busy educational curriculum which in third year targets 669 students over two campuses. CONCLUSIONS In an environment of increasingly constrained clinical placement opportunities, exploration of alternate strategies to improve critical thinking skills and develop clinical reasoning and problem solving for nursing students is imperative in preparing nurses to respond to changing patient needs. References 1. Lasater, K., High-fidelity simulation and the development of clinical judgement: students' experiences. Journal of Nursing Education, 2007. 46(6): p. 269-276. 2. Lapkin, S., et al., Effectiveness of patient simulation manikins in teaching clinical reasoning skills to undergraduate nursing students: a systematic review. Clinical Simulation in Nursing, 2010. 6(6): p. e207-22. 3. Kaddoura, M.P.C.M.S.N.R.N., New Graduate Nurses' Perceptions of the Effects of Clinical Simulation on Their Critical Thinking, Learning, and Confidence. The Journal of Continuing Education in Nursing, 2010. 41(11): p. 506. 4. Banning, M., The think aloud approach as an educational tool to develop and assess clinical reasoning in undergraduate students. Nurse Education Today, 2008. 28: p. 8-14. 5. Porter-O'Grady, T., Profound change:21st century nursing. Nursing Outlook, 2001. 49(4): p. 182-186. 6. Andersson, A.K., M. Omberg, and M. Svedlund, Triage in the emergency department-a qualitative study of the factors which nurses consider when making decisions. Nursing in Critical Care, 2006. 11(3): p. 136-145. 7. O'Neill, E.S., N.M. Dluhy, and C. Chin, Modelling novice clinical reasoning for a computerized decision support system. Journal of Advanced Nursing, 2005. 49(1): p. 68-77. 8. Lee, J.E. and N. Ryan-Wenger, The "Think Aloud" seminar for teaching clinical reasoning: a case study of a child with pharyngitis. J Pediatr Health Care, 1997. 11(3): p. 101-10.

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Emerging from the challenge to reduce energy consumption in buildings is a need for research and development into the more effective use of simulation as a decision-support tool. Despite significant research, persistent limitations in process and software inhibit the integration of energy simulation in early architectural design. This paper presents a green star case study to highlight the obstacles commonly encountered with current integration strategies. It then examines simulation-based design in the aerospace industry, which has overcome similar limitations. Finally, it proposes a design system based on this contrasting approach, coupling parametric modelling and energy simulation software for rapid and iterative performance assessment of early design options.

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On the road, near collision events (also close calls or near-miss incidents) largely outnumber actual crashes, yet most of them can never be recorded by current traffic data collection technologies or crashes analysis tools. The analysis of near collisions data is an important step in the process of reducing the crash rate. There have been several studies that have investigated near collisions; to our knowledge, this is the first study that uses the functionalities provided by cooperative vehicles to collect near misses information. We use the VISSIM traffic simulator and a custom C++ engine to simulate cooperative vehicles and their ability to detect near collision events. Our results showed that, within a simple simulated environment, adequate information on near collision events can be collected using the functionalities of cooperative perception systems. The relationship between the ratio of detected events and the ratio of equipped vehicle was shown to closely follow a squared law, and the largest source of nondetection was packet loss instead of packet delays and GPS imprecision.

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Electricity has been the major source of power in most railway systems. Reliable, efficient and safe power distribution to the trains is vitally important to the overall quality of railway service. Like any large-scale engineering system, design, operation and planning of traction power systems rely heavily on computer simulation. This paper reviews the major features on modelling and the general practices for traction power system simulation; and introduces the development of the latest simulation approach with discussions on simulation results and practical applications. Remarks will also be given on the future challenges on traction power system simulation.

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Evaluating the safety of different traffic facilities is a complex and crucial task. Microscopic simulation models have been widely used for traffic management but have been largely neglected in traffic safety studies. Micro simulation to study safety is more ethical and accessible than the traditional safety studies, which only assess historical crash data. However, current microscopic models are unable to mimic unsafe driver behavior, as they are based on presumptions of safe driver behavior. This highlights the need for a critical examination of the current microscopic models to determine which components and parameters have an effect on safety indicator reproduction. The question then arises whether these safety indicators are valid indicators of traffic safety. The safety indicators were therefore selected and tested for straight motorway segments in Brisbane, Australia. This test examined the capability of a micro-simulation model and presents a better understanding of micro-simulation models and how such models, in particular car following models can be enriched to present more accurate safety indicators.

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Nursing training for an Intensive Care Unit (ICU) is a resource intensive process. High demands are made on staff, students and physical resources. Interactive, 3D computer simulations, known as virtual worlds, are increasingly being used to supplement training regimes in the health sciences; especially in areas such as complex hospital ward processes. Such worlds have been found to be very useful in maximising the utilisation of training resources. Our aim is to design and develop a novel virtual world application for teaching and training Intensive Care nurses in the approach and method for shift handover, to provide an independent, but rigorous approach to teaching these important skills. In this paper we present a virtual world simulator for students to practice key steps in handing over the 24/7 care requirements of intensive care patients during the commencing first hour of a shift. We describe the modelling process to provide a convincing interactive simulation of the handover steps involved. The virtual world provides a practice tool for students to test their analytical skills with scenarios previously provided by simple physical simulations, and live on the job training. Additional educational benefits include facilitation of remote learning, high flexibility in study hours and the automatic recording of a reviewable log from the session. To the best of our knowledge, we believe this is a novel and original application of virtual worlds to an ICU handover process. The major outcome of the work was a virtual world environment for training nurses in the shift handover process, designed and developed for use by postgraduate nurses in training.

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In recent years, the advent of new tools for musculoskeletal simulation has increased the potential for significantly improving the ergonomic design process and ergonomic assessment of design. In this paper we investigate the use of one such tool, ‘The AnyBody Modeling System’, applied to solve a one-parameter and yet, complex ergonomic design problem. The aim of this paper is to investigate the potential of computer-aided musculoskeletal modelling in the ergonomic design process, in the same way as CAE technology has been applied to engineering design.

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When compared with other arthoplasties, Total Ankle Joint Replacement (TAR) is much less successful. Attempts to remedy this situation by modifying the implant design, for example by making its form more akin to the original ankle anatomy, have largely met with failure. One of the major obstacles is a gap in current knowledge relating to ankle joint force. Specifically this is the lack of reliable data quantifying forces and moments acting on the ankle, in both the healthy and diseased joints. The limited data that does exist is thought to be inaccurate [1] and is based upon simplistic two dimensional discrete and outdated techniques.

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In most materials, short stress waves are generated during the process of plastic deformation, phase transformation, crack formation and crack growth. These phenomena are applied in acoustic emission (AE) for the detection of material defects in wide spectrum areas, ranging from non-destructive testing for the detection of materials defects to monitoring of microeismical activity. AE technique is also used for defect source identification and for failure detection. AE waves consist of P waves (primary/longitudinal waves), S waves (shear/transverse waves) and Rayleight (surface) waves as well as reflected and diffracted waves. The propagation of AE waves in various modes has made the determination of source location difficult. In order to use the acoustic emission technique for accurate identification of source location, an understanding of wave propagation of the AE signals at various locations in a plate structure is essential. Furthermore, an understanding of wave propagation can also assist in sensor location for optimum detection of AE signals. In real life, as the AE signals radiate from the source it will result in stress waves. Unless the type of stress wave is known, it is very difficult to locate the source when using the classical propagation velocity equations. This paper describes the simulation of AE waves to identify the source location in steel plate as well as the wave modes. The finite element analysis (FEA) is used for the numerical simulation of wave propagation in thin plate. By knowing the type of wave generated, it is possible to apply the appropriate wave equations to determine the location of the source. For a single plate structure, the results show that the simulation algorithm is effective to simulate different stress waves.

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The subtalar joint has been presumed to account for most of the pathologic motion in the foot and ankle, but research has shown that motion at other foot joints is greater than traditionally expected. Although recent research demonstrates the complexity of the kinematic variables in the foot and ankle, it still fails to expand our knowledge of the role of the musculotendinous structures in the biomechanics of the foot and ankle and how this is affected by in-shoe orthoses. The aim of this study was to simulate the effect of in-shoe foot orthoses by manipulation of the ground reaction force (GRF) components and centre of pressure (CoP) to demonstrate the resultant effect on muscle force in selected muscles during both the rearfoot loading response and stance phase of the gait cycle. We found that any medial wedge increases ankle joint load during gait cycle, while a lateral wedge decreases the joint load during the stance phase.

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Purpose. To investigate how temporal processing is altered in myopia and during myopic progression. Methods. In backward visual masking, a target's visibility is reduced by a mask presented quickly after the target. Thirty emmetropes, 40 low myopes, and 22 high myopes aged 18 to 26 years completed location and resolution masking tasks. The location task examined the ability to detect letters with low contrast and large stimulus size. The resolution task involved identifying a small letter and tested resolution and color discrimination. Target and mask stimuli were presented at nine short interstimulus intervals (12 to 259 ms) and at 1000 ms (long interstimulus interval condition). Results. In comparison with emmetropes, myopes had reduced ability in both locating and identifying briefly presented stimuli but were more affected by backward masking for a low contrast location task than for a resolution task. Performances of low and high myopes, as well as stable and progressing myopes, were similar for both masking tasks. Task performance was not correlated with myopia magnitude. Conclusions. Myopes were more affected than emmetropes by masking stimuli for the location task. This was not affected by magnitude or progression rate of myopia, suggesting that myopes have the propensity for poor performance in locating briefly presented low contrast objects at an early stage of myopia development.

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The impact of weather on traffic and its behavior is not well studied in literature primarily due to lack of integrated traffic and weather data. Weather can significant effect the traffic and traffic management measures developed for fine weather might not be optimal for adverse weather. Simulation is an efficient tool for analyzing traffic management measures even before their actual implementation. Therefore, in order to develop and test traffic management measures for adverse weather condition we need to first analyze the effect of weather on fundamental traffic parameters and thereafter, calibrate the simulation model parameters in order to simulate the traffic under adverse weather conditions. In this paper we first, analyses the impact of weather on motorway traffic flow and drivers’ behaviour with traffic data from Swiss motorways and weather data from MeteoSuisse. Thereafter, we develop methodology to calibrate a microscopic simulation model with the aim to utilize the simulation model for simulating traffic under adverse weather conditions. Here, study is performed using AIMSUN, a microscopic traffic simulator.