996 resultados para Fire Monitoring
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It is essential to keep track of the movements we make, and one way to do that is to monitor correlates, or corollary discharges, of neuronal movement commands. We hypothesized that a previously identified pathway from brainstem to frontal cortex might carry corollary discharge signals. We found that neuronal activity in this pathway encodes upcoming eye movements and that inactivating the pathway impairs sequential eye movements consistent with loss of corollary discharge without affecting single eye movements. These results identify a pathway in the brain of the primate Macaca mulatta that conveys corollary discharge signals.
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CONCLUSION Radiation dose reduction, while saving image quality could be easily implemented with this approach. Furthermore, the availability of a dosimetric data archive provides immediate feedbacks, related to the implemented optimization strategies. Background JCI Standards and European Legislation (EURATOM 59/2013) require the implementation of patient radiation protection programs in diagnostic radiology. Aim of this study is to demonstrate the possibility to reduce patients radiation exposure without decreasing image quality, through a multidisciplinary team (MT), which analyzes dosimetric data of diagnostic examinations. Evaluation Data from CT examinations performed with two different scanners (Siemens DefinitionTM and GE LightSpeed UltraTM) between November and December 2013 are considered. CT scanners are configured to automatically send images to DoseWatch© software, which is able to store output parameters (e.g. kVp, mAs, pitch ) and exposure data (e.g. CTDIvol, DLP, SSDE). Data are analyzed and discussed by a MT composed by Medical Physicists and Radiologists, to identify protocols which show critical dosimetric values, then suggest possible improvement actions to be implemented. Furthermore, the large amount of data available allows to monitor diagnostic protocols currently in use and to identify different statistic populations for each of them. Discussion We identified critical values of average CTDIvol for head and facial bones examinations (respectively 61.8 mGy, 151 scans; 61.6 mGy, 72 scans), performed with the GE LightSpeed CTTM. Statistic analysis allowed us to identify the presence of two different populations for head scan, one of which was only 10% of the total number of scans and corresponded to lower exposure values. The MT adopted this protocol as standard. Moreover, the constant output parameters monitoring allowed us to identify unusual values in facial bones exams, due to changes during maintenance service, which the team promptly suggested to correct. This resulted in a substantial dose saving in CTDIvol average values of approximately 15% and 50% for head and facial bones exams, respectively. Diagnostic image quality was deemed suitable for clinical use by radiologists.
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info:eu-repo/semantics/published
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Computer based mathematical models describing the aircraft evacuation process and aircraft fire have a role to play in the design and development of safer aircraft, in the implementaion of safer and more rigorous certification criteria and in post mortuum accident investigation. As the cost and risk involved in performing large-scale fire/evacuation experiments for the next generation 'Very Large Aircraft' (VLA) are expected to be high, the development and use of these modelling tools may become essential if these aircraft are to prove a viable reality. By describing the present capabililties and limitations of the EXODUS evacuation model and associated fire models, this paper will examine the future development and data requirements of these models.
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The mathematical simulation of the evacuation process has a wide and largely untapped scope of application within the aircraft industry. The function of the mathematical model is to provide insight into complex behaviour by allowing designers, legislators, and investigators to ask ‘what if’ questions. Such a model, EXODUS, is currently under development, and this paper describes its evolution and potential applications. EXODUS is an egress model designed to simulate the evacuation of large numbers of individuals from an enclosure, such as an aircraft. The model tracks the trajectory of each individual as they make their way out of the enclosure or are overcome by fire hazards, such as heat and toxic gases. The software is expert system-based, the progressive motion and behaviour of each individual being determined by a set of heuristics or rules. EXODUS comprises five core interacting components: (i) the Movement Submodel — controls the physical movement of individual passengers from their current position to the most suitable neighbouring location; (ii) the Behaviour Submodel — determines an individual's response to the current prevailing situation; (iii) the Passenger Submodel — describes an individual as a collection of 22 defining attributes and variables; (iv) the Hazard Submodel — controls the atmospheric and physical environment; and (v) the Toxicity Submodel — determines the effects on an individual exposed to the fire products, heat, and narcotic gases through the Fractional Effective Dose calculations. These components are briefly described and their capabilities and limitations are demonstrated through comparison with experimental data and several hypothetical evacuation scenarios.
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In this paper we present some early work concerned with the development of a simple solid fuel combustion model incorporated within a Computational Fluid Dynamics (CFD) framework. The model is intended for use in engineering applications of fire field modelling and represents an extension of this technique to situations involving the combustion of solid cellulosic hels A simple solid &el combustion model consisting of a thermal pyrolysis model, a six flux radiation model and an eddydissipation model for gaseous combustion have been developed and implemented within the CFD code CFDS-FLOW3D The model is briefly described and demonstrated through two applications involving fire spread in a compartment with a plywood lined ceiling. The two scenarios considered involve a fire in an open and closed compartment The model is shown to be able to qualitatively predict behaviours similar to flashover - in the case of the open room - and backdrafl - in the case of the initially closed room.
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This paper describes a project aimed at making Computational Fluid Dynamics (CFD) based fire simulation accessible to members of the fire safety engineering community. Over the past few years, the practise of CFD based fire simulation has begun the transition from the confines of the research laboratory to the desk of the fire safety engineer. To a certain extent, this move has been driven by the demands of performance based building codes. However, while CFD modelling has many benefits over other forms of fire simulation, it requires a great deal of expertise on the user’s part to obtain reasonable simulation results. The project described in this paper, SMARTFIRE, aims to relieve some of this dependence on expertise so that users are less concerned with the details of CFD analysis and can concentrate on results. This aim is achieved by the use of an expert system component as part of the software suite which takes some of the expertise burden away from the user. SMARTFIRE also makes use of the latest developments in CFD technology in order to make the CFD analysis more efficient. This paper describes design considerations of the SMARTFIRE software, emphasising its open architecture, CFD engine and knowledge based systems.
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This paper presents a comparison of fire field model predictions with experiment for the case of a fire within a compartment which is vented (buoyancydriven) to the outside by a single horizontal ceiling vent. Unlike previous work, the mathematical model does not employ a mixing ratio to represent vent temperatures but allows the model to predict vent temperatures a priori. The experiment suggests that the flow through the vent produces oscillatory behaviour in vent temperatures with puffs of smoke emerging from the fire compartment. This type of flow is also predicted by the fire field model. While the numerical predictions are in good qualitative agreement with observations, they overpredict the amplitudes of the temperature oscillations within the vent and also the compartment temperatures. The discrepancies are thought to be due to three-dimensional effects not accounted for in this model as well as using standard ‘practices’ normally used by the community with regards to discretization and turbulence models. Furthermore, it is important to note that the use of the k–ε turbulence model in a transient mode, as is used here, may have a significant effect on the results. The numerical results also suggest that a linear relationship exists between the frequency of vent temperature oscillation (n) and the heat release rate (Q0) of the type n∝Q0.290, similar to that observed for compartments with two horizontal vents. This relationship is predicted to occur only for heat release rates below a critical value. Furthermore, the vent discharge coefficient is found to vary in an oscillatory fashion with a mean value of 0.58. Below the critical heat release rate the mean discharge coefficient is found to be insensitive to fire size.
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In this paper, we present some early work concerned with the development of a simple solid fuel combustion model incorporated within a Computational Fluid Dynamics (CFD) framework. The model is intended for use in engineering applications of fire field modeling and represents an extension of this technique to situations involving the combustion of solid cellulosic fuels. A simple solid fuel combustion model consisting of a thermal pyrolysis model, a six flux radiation model and an eddy-dissipation model for gaseous combustion have been developed and implemented within the CFD code CFDS-FLOW3D. The model is briefly described and demonstrated through two applications involving fire spread in a compartment with a plywood lined ceiling. The two scenarios considered involve a fire in an open and closed compartment. The model is shown to be able to qualitatively predict behaviors similar to "flashover"—in the case of the open room—and "backdraft"— in the case of the initially closed room.