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Abstract: To study transient mass transfers inside buildings equipped with ventilation systems, reduced-scale experiments have been performed by applying the scaling down methodology developed for studying isothermal airflows in a steady or a transient state [1]. Transient tests have been carried out both on simplified cases considered for the validation of the methodology and on two reference industrial configurations representative of real industrial facilities. In this article, focus is made on transient results obtained on simplified and reference industrial cases subjected to wind and internal overpressure effects. The main objectives are firstly to identify the internal transient airflow behaviour, compared with Helmholtz oscillated phenomena underlined from natural ventilation studies, secondly to analyse the pollutant containment of reference industrial configurations subjected to wind and/or internal overpressure effects due to an accident, and finally to check the ability of the SYLVIA code to model these transient phenomena. [Copyright &y& Elsevier]

The performance of an aeration system generally depends upon the geometric and dynamic parameters. The main purpose of doing experiment in the area of surface aeration system is to interpret the laboratory results for the field application that is to scale-up the results. This requires a geometrical similarity conditions. Finding geometrical optimal conditions of a surface aeration system through experiments involves physical constraints and classically parameters can be optimized by varying one variable at a time and keeping others as constants. In the real experimental process, it is not possible to vary all others geometric parameters simultaneously. In such a case, the model of the system is built through computer simulation, assuming that the model will result in adequate determination of the optimum conditions for the real system. In this paper, two approaches have been used to model the phenomena: i) Multiple regression and ii) Neural network. It has been found that neural network approach is showing better predictability compared to the multiple regression approach. In process of optimization, the pertinent dynamic parameter is divided into a finite number of segments over the entire range of observations. For each segment of the dynamic parameter, the neural network model is optimized for the geometrical parameters spanning over the entire range of observations. Thus each segment of the dynamic parameter has its set of optimal geometrical conditions. Results obtained are having less variation among them and they are very nearer to the experimental optimal conditions. Input parameter significance test of neural network model reveals that, in general the blade width of rotor is a major geometric parameter to enhance the aeration process. [ABSTRACT FROM AUTHOR]

The present paper attempts to give a broad review of tests performed with air as a cheaper and more accurate option when compared with tests using incompressible flows. The work presents a description of an aerodynamic test- bench for examining models of hydraulic machines. Experimental and theoretical values of local velocity and density were determined at several axial planes. Test results were also used to show how water machine models can be equally tested in air tunnels. Analysis is supported by the theory of dynamic similarity. The work presents a qualitative and quantitative description of actual cases based on model tests. With special emphasis on conditions of similarity, which have a fundamental significance in the design of hydraulic machines, the author explains the possibility of supplementing them by using air as the working medium. The influence of Reynolds number, roughness and turbulence is also discussed. [ABSTRACT FROM AUTHOR]

This paper presents a preliminary design method based on dynamic similarity and quasi-static simulation. The proposal improves methods based on Beale and West correlations and provides the engine speeds corresponding to the maximum indicated powers and the achievement of indicated power maps. The dimensionless factor of indicated power losses provides a new viewpoint for engine analysis and design. In support of the method, experimental GPU-3 test results have been reanalysed, proving the accuracy of maximum indicated power predictions and providing values of the dimensionless factor of indicated power losses. Scaling factors corresponding to strict dynamic similarity are supplied for several typical cases. Similarity relaxation criteria are also recommended to be used when strict dynamic similarity leads to inadequate specifications for the derivative. Some numerical examples illustrate the method. [ABSTRACT FROM AUTHOR]