Biomedical subjects

A Mohebbi

Publications and source records attributed to A Mohebbi.

5 recordsLinked to original sources

PubMed2006

Predicting pressure drop in venturi scrubbers with artificial neural networks.

In this study a new approach based on artificial neural networks (ANNs) has been used to predict pressure drop in venturi scrubbers. The main parameters affecting the pressure drop are mainly the gas velocity in the throat of venturi scrubber (V(g)(th)), liquid to gas flow rate ratio (L/G), and axial distance of the venturi scrubber (z). Three sets of experimental data from five different venturi scrubbers have been applied to design three independent ANNs. Comparing the results of these ANNs and the calculated results from available models shows that the results of ANNs have a better agreement with experimental data.

Air Pollution↗

PubMed2006

Measuring and modeling particulate dispersion: a case study of Kerman Cement Plant.

In this study to identify the origin of PM10 in the atmosphere of Kerman and investigate the dispersion conditions for these particles, the variations of the mass concentration and size distribution of PM10 have been measured. This study is focused on the local environmental impact of Kerman Cement Plant. All samples have been taken in the area between the plant and the city entrance at the wind direction. The result of this research shows that the PM10 concentration in the ambient air in distances about 590-1370 m from the stacks is higher than the WHO guidelines of annual average (260 microg/m(3)). Also, concentration of PM10 is computed by using Gaussian plume model that incorporates source related factors and meteorological factors to estimate pollutant concentration from continuous sources. The performance of this model has been compared with the measured data.

Air Pollutants, Occupational↗

PubMed2003

Simulation of an orifice scrubber performance based on Eulerian/Lagrangian method.

A mathematical model based on Eulerian/Lagrangian method has been developed to predict particle collection efficiency from a gas stream in an orifice scrubber. This model takes into account Eulerian approach for particle dispersion, Lagrangian approach for droplet movement and particle-source-in-cell (PSI-CELL) model for calculating droplet concentration distribution. In order to compute fluid velocity profiles, the normal k-epsilon turbulent flow model with inclusion of body force due to drag force between fluid and droplets has been used. Experimental data of Taheri et al. [J. Air Pollut. Control Assoc. 23 (11) (1973) 963] have been used to test the results of the mathematical model. The results from the model are in good agreement with the experimental data. After validating the model the effect of operating parameters such as liquid to gas flow rate ratio, gas velocity at orifice opening, and particle diameter were obtained on the collection efficiency.

Air Movements↗

PubMed2002

Prediction of pressure drop in an orifice scrubber based on a Lagrangian approach.

A mathematical model has been developed to predict pressure drop in an orifice scrubber. This model is based on a Lagrangian approach for droplet movement and a particle-source-in-cell (PSI-CELL) model for calculating droplet concentration distribution. The k-epsilon turbulent model including body force due to the drag force between fluid and droplets was used to evaluate the fluid velocity distribution. The effect of orifice size on pressure drop and the correlations for mean droplet diameter have been studied. The results from the model have been compared with experimental data. This comparison shows excellent agreement between the calculated results and the experimental data.

Air Pollution↗

PubMed1997

In vivo phosphorus polarization transfer and decoupling from protons in three-dimensional localized nuclear magnetic resonance spectroscopy of human brain.

Refocused insensitive nucleus enhancement by polarization transfer (RINEPT) from protons (1H) to a J-coupled phosphorus (31P) has been incorporated into three-dimensional (3D) chemical-shift-imaging (CSI) sequence on a clinical imager. The technique is demonstrated on a phantom and in in vivo human brain. The polarization-transfer efficiency (approximately 1.2) is lower than the theoretical maximum of gamma1H/gamma31P approximately 2.4 resulting from 1H-1H homonuclear J couplings of similar magnitude competing with the 1H --> 31P transfer. Nevertheless, compared with direct 31P Ernst-angle excitation, signal gains of up to x1.8 were obtained mainly as a result of T1 differences between 31P and the 1H. Spectral interpretation is simplified by editing out all non-proton-coupled 31P signals. The duration, approximately 50 min, and power deposition, approximately 1 W x kg(-1), make the application suitable for human studies.

Brain↗