Comparison of random pore model, modified grain model, and volume reaction model predictions with experimental results of SO2 removal reaction by CuO

2015 ◽  
Vol 30 ◽  
pp. 372-378 ◽  
Author(s):  
R. Bahrami ◽  
H. Ale Ebrahim ◽  
R. Halladj
1990 ◽  
Vol 181 ◽  
Author(s):  
Timothy S. Cale ◽  
Gregory B. Raupp

ABSTRACTA modified line-of-sight model for transport and deposition during LPCVD is used to predict step coverage and film composition uniformity of tungsten silicide barrier layers. Predictions are compared with experimental results for 2 μim wide by 6 μm deep trenches with barrier layers of 0.2 μm nominal thickness. Model predictions are in quantitative agreement with those of a diffusion-reaction model and are in qualitative agreement with experiment.


2014 ◽  
Vol 53 (42) ◽  
pp. 16285-16292 ◽  
Author(s):  
Reza Bahrami ◽  
Habib Ale Ebrahim ◽  
Rouein Halladj ◽  
Mohammad Ali Ale Ebrahim

2014 ◽  
Vol 618 ◽  
pp. 316-320
Author(s):  
Hua Fei ◽  
Jin Ming Shi ◽  
Yuan Lin Li ◽  
Kai Luo

The gasification of straw stalk in CO2 environment was studied by isothermal thermogravimetric analysis. The characteristics of rice straw and maize stalk gasification at different temperatures were examined under CO2 atmosphere. The relationship between reaction time and carbon conversion of two biomass chars was analyzed by the random pore model (RPM), and compared with the simulation of the shrinking core reaction model (SCRM). The results show that the random pore model is better to predict the experimental data at different temperatures. This means that the characteristics of pore structure for the influence of biomass chars gasification is well reflected by parameter ψ used in RPM. It indicates that the RPM can be applied to the comprehensive simulation of biomass chars gasification in CO2 environment.


2016 ◽  
Vol 41 (4) ◽  
pp. 385-397 ◽  
Author(s):  
Reza Bahrami ◽  
Habib Ale Ebrahim ◽  
Rouein Halladj ◽  
Ali Afshar

An experimental investigation of the SO2 removal reaction by pure CuO was performed by thermogravimetry. In addition, mathematical modelling of this non-catalytic gas-solid reaction was performed using the random pore model. Modelling predictions of CuO conversion-time profiles at various temperatures and SO2 partial pressures compared well with the experimental results. The inherent rate constants and the product layer diffusivities were estimated between 400 and 600 °C.


2021 ◽  
Author(s):  
Iman Omidi ◽  
Habib Ale Ebrahim

Abstract An experimental investigation of low temperature SO2 removal by porous sodium carbonate was carried out by thermogravimetry. As well as, applied mathematical modeling based on the random pore model was employed to kinetic study of this reaction. The experiments were performed at various temperatures (100-250 oC) and different SO2 concentrations (0.13-1.12 vol%). The initial slopes procedure was used to determine dependency of the reaction rate constants versus temperature. First-order kinetic with respect to gaseous reactant was found and value of activation energy was attained as 22.5 kJ mol-1. Product layer diffusion coefficients were evaluated by the best fitting of experimental data with the model predictions. These random pore model predictions indicated good agreement with experimental conversion-time data at various conditions. The resulted kinetic parameters were avail abled for engineering calculations of SO2 abatement from the coal-based power plants by low-temperature flue gas desulfurization.


2014 ◽  
Vol 92 (6) ◽  
pp. 938-947 ◽  
Author(s):  
R. Bahrami ◽  
H. Ale Ebrahim ◽  
R. Halladj

2011 ◽  
Vol 31 (5) ◽  
pp. 537-544 ◽  
Author(s):  
Alp Akonur ◽  
J. Ken Leypoldt

BackgroundRecently, bimodal peritoneal dialysis (PD) solutions containing low concentrations of Na have been shown to increase 24-hour ultrafiltration (UF) or UF efficiency (UF volume per gram of carbohydrate or CHO absorbed) and Na removal in high (“fast”) transport patients during automated PD therapy. We used computer simulations to compare UF efficiency and Na removal at equivalent 24-hour UF volumes using either a generic bimodal solution (2.27% glucose + 7.5% icodextrin) during the long dwell or an increase in the glucose concentration during the short dwells, with all solutions containing Na at the conventional concentration (132 mEq/L).MethodsThe 3-pore model has been shown to accurately predict peritoneal transport for PD solutions containing glucose or icodextrin, or both. Here, we used that model to calculate 24-hour UF volume, CHO absorption, and Na removal for high (H), high-average (HA), and low-average (LA) transport patients on automated PD. Nighttime therapy consisted of 1.36% or 2.27% glucose solution (or both), and daytime therapy consisted of either Extraneal (Baxter Healthcare Corporation, Deerfield, IL, USA) or a bimodal solution.ResultsAs expected, addition of glucose to either the long dwell or the short dwells resulted in increased UF volume and glucose absorption. The increase in UF was a function of patient transport type (bimodal range: 288 – 490 mL; short-dwell range: 323 – 350 mL), and the increase in CHO absorption was smaller with glucose added to short dwells than with bimodal solution (range: 18 – 30 g vs. 34 – 39 g). The 24-hour UF efficiency was higher when high glucose concentrations were used during short-dwell exchanges than when a bimodal PD solution was used for the long dwell (0.6 to 1.2 mL/g vs. –0.1 to 0.5 mL/g). By contrast, Na removal was lower with the short-dwell exchanges (28.3 – 30.7 mmol vs. 36.2 – 53.3 mmol), likely because of more pronounced Na sieving.ConclusionsOur modeling studies predict that generic bimodal PD solutions will provide higher Na removal but not higher 24-hour UF efficiency compared with current automated PD prescriptions using Extraneal for the long dwell and glucose-containing solutions for the short dwells. The modeling predictions from this study require clinical validation.


Author(s):  
Michaela Regneri ◽  
Marcus Rohrbach ◽  
Dominikus Wetzel ◽  
Stefan Thater ◽  
Bernt Schiele ◽  
...  

Recent work has shown that the integration of visual information into text-based models can substantially improve model predictions, but so far only visual information extracted from static images has been used. In this paper, we consider the problem of grounding sentences describing actions in visual information extracted from videos. We present a general purpose corpus that aligns high quality videos with multiple natural language descriptions of the actions portrayed in the videos, together with an annotation of how similar the action descriptions are to each other. Experimental results demonstrate that a text-based model of similarity between actions improves substantially when combined with visual information from videos depicting the described actions.


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