994 resultados para Spatial diffusion


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The flow structure of cold and ignited jets issuing into a co-flowing air stream was experimentally studied using a laser Doppler velocimeter. Methane was employed as the jet fluid discharging from circular and elliptic nozzles with aspect ratios varying from 1.29 to 1.60. The diameter of the circular nozzle was 4.6 mm and the elliptic nozzles had approximately the same exit area as that of the circular nozzle. These non-circular nozzles were employed in order to increase the stability of attached jet diffusion flames. The time-averaged velocity and r.m.s. value of the velocity fluctuation in the streamwise and transverse directions were measured over the range of co-flowing stream velocities corresponding to different modes of flame blowout that are identified as either lifted or attached flames. On the basis of these measurements, attempts were made to explain the existence of an apparent optimum aspect ratio for the blowout of attached flames observed at higher values of co-flowing stream velocities. The insensitivity of the blowout limits of lifted flames to nozzle geometry observed in our previous work at low co-flowing stream velocities was also explained. Measurements of the fuel concentration at the jet centerline indicated that the mixing process was enhanced with the 1.38 aspect ratio jet compared with the 1.60 aspect ratio jet. On the basis of the obtained experimental data, it was suggested that the higher blowout limits of attached flames for an elliptic jet of 1.38 aspect ratio was due to higher entrainment rates.

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The Mathematica system (version 4.0) is employed in the solution of nonlinear difusion and convection-difusion problems, formulated as transient one-dimensional partial diferential equations with potential dependent equation coefficients. The Generalized Integral Transform Technique (GITT) is first implemented for the hybrid numerical-analytical solution of such classes of problems, through the symbolic integral transformation and elimination of the space variable, followed by the utilization of the built-in Mathematica function NDSolve for handling the resulting transformed ODE system. This approach ofers an error-controlled final numerical solution, through the simultaneous control of local errors in this reliable ODE's solver and of the proposed eigenfunction expansion truncation order. For covalidation purposes, the same built-in function NDSolve is employed in the direct solution of these partial diferential equations, as made possible by the algorithms implemented in Mathematica (versions 3.0 and up), based on application of the method of lines. Various numerical experiments are performed and relative merits of each approach are critically pointed out.

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Wind power is a low-carbon energy production form that reduces the dependence of society on fossil fuels. Finland has adopted wind energy production into its climate change mitigation policy, and that has lead to changes in legislation, guidelines, regional wind power areas allocation and establishing a feed-in tariff. Wind power production has indeed boosted in Finland after two decades of relatively slow growth, for instance from 2010 to 2011 wind energy production increased with 64 %, but there is still a long way to the national goal of 6 TWh by 2020. This thesis introduces a GIS-based decision-support methodology for the preliminary identification of suitable areas for wind energy production including estimation of their level of risk. The goal of this study was to define the least risky places for wind energy development within Kemiönsaari municipality in Southwest Finland. Spatial multicriteria decision analysis (SMCDA) has been used for searching suitable wind power areas along with many other location-allocation problems. SMCDA scrutinizes complex ill-structured decision problems in GIS environment using constraints and evaluation criteria, which are aggregated using weighted linear combination (WLC). Weights for the evaluation criteria were acquired using analytic hierarchy process (AHP) with nine expert interviews. Subsequently, feasible alternatives were ranked in order to provide a recommendation and finally, a sensitivity analysis was conducted for the determination of recommendation robustness. The first study aim was to scrutinize the suitability and necessity of existing data for this SMCDA study. Most of the available data sets were of sufficient resolution and quality. Input data necessity was evaluated qualitatively for each data set based on e.g. constraint coverage and attribute weights. Attribute quality was estimated mainly qualitatively by attribute comprehensiveness, operationality, measurability, completeness, decomposability, minimality and redundancy. The most significant quality issue was redundancy as interdependencies are not tolerated by WLC and AHP does not include measures to detect them. The third aim was to define the least risky areas for wind power development within the study area. The two highest ranking areas were Nordanå-Lövböle and Påvalsby followed by Helgeboda, Degerdal, Pungböle, Björkboda, and Östanå-Labböle. The fourth aim was to assess the recommendation reliability, and the top-ranking two areas proved robust whereas the other ones were more sensitive.

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