The Experts below are selected from a list of 1083 Experts worldwide ranked by ideXlab platform
D G Kroger - One of the best experts on this subject based on the ideXlab platform.
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packed bed pressure drop dependence on particle shape size distribution packing arrangement and roughness
Powder Technology, 2013Co-Authors: K G Allen, T W Von Backstrom, D G KrogerAbstract:Abstract Packed beds have been used or proposed for many different applications, including thermal storage in buildings and in solar thermal power plants. In order to size the blowers and predict the operating and capital cost, the packed bed pressure drop must be known. The Ergun Equation, commonly used for predicting packed bed pressure drop, over-predicts the pressure drop through randomly packed or structured beds of smooth spheres at Ergun Reynolds numbers in excess of ≈ 700, and previous work has found it to under-predict the pressure drop through beds of rock by a factor as high as 5. Present measurements of the pressure drop for air flow through beds of rough spheres, smooth cylinders, cubes and crushed rock are significantly higher than those for smooth spheres, and all differ from the Ergun Equation. Particle shape, arrangement (including packing method) and surface roughness are shown to influence the pressure drop. Recent correlations for non-spherical particles are shown to differ significantly from present measurements. Different pressure drop measurements obtained for irregularly shaped rock packed into the test section in two different directions relative to the flow direction show that random packing is not necessarily isotropic. In order to predict the pressure drop over a packed bed of irregular particles such as crushed rock with any degree of accuracy, an empirical Equation must be obtained from a sample of the particles for a given packing arrangement.
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packed bed pressure drop dependence on particle shape size distribution packing arrangement and roughness
Powder Technology, 2013Co-Authors: K G Allen, T W Von Backstrom, D G KrogerAbstract:Abstract Packed beds have been used or proposed for many different applications, including thermal storage in buildings and in solar thermal power plants. In order to size the blowers and predict the operating and capital cost, the packed bed pressure drop must be known. The Ergun Equation, commonly used for predicting packed bed pressure drop, over-predicts the pressure drop through randomly packed or structured beds of smooth spheres at Ergun Reynolds numbers in excess of ≈ 700, and previous work has found it to under-predict the pressure drop through beds of rock by a factor as high as 5. Present measurements of the pressure drop for air flow through beds of rough spheres, smooth cylinders, cubes and crushed rock are significantly higher than those for smooth spheres, and all differ from the Ergun Equation. Particle shape, arrangement (including packing method) and surface roughness are shown to influence the pressure drop. Recent correlations for non-spherical particles are shown to differ significantly from present measurements. Different pressure drop measurements obtained for irregularly shaped rock packed into the test section in two different directions relative to the flow direction show that random packing is not necessarily isotropic. In order to predict the pressure drop over a packed bed of irregular particles such as crushed rock with any degree of accuracy, an empirical Equation must be obtained from a sample of the particles for a given packing arrangement.
K G Allen - One of the best experts on this subject based on the ideXlab platform.
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packed bed pressure drop dependence on particle shape size distribution packing arrangement and roughness
Powder Technology, 2013Co-Authors: K G Allen, T W Von Backstrom, D G KrogerAbstract:Abstract Packed beds have been used or proposed for many different applications, including thermal storage in buildings and in solar thermal power plants. In order to size the blowers and predict the operating and capital cost, the packed bed pressure drop must be known. The Ergun Equation, commonly used for predicting packed bed pressure drop, over-predicts the pressure drop through randomly packed or structured beds of smooth spheres at Ergun Reynolds numbers in excess of ≈ 700, and previous work has found it to under-predict the pressure drop through beds of rock by a factor as high as 5. Present measurements of the pressure drop for air flow through beds of rough spheres, smooth cylinders, cubes and crushed rock are significantly higher than those for smooth spheres, and all differ from the Ergun Equation. Particle shape, arrangement (including packing method) and surface roughness are shown to influence the pressure drop. Recent correlations for non-spherical particles are shown to differ significantly from present measurements. Different pressure drop measurements obtained for irregularly shaped rock packed into the test section in two different directions relative to the flow direction show that random packing is not necessarily isotropic. In order to predict the pressure drop over a packed bed of irregular particles such as crushed rock with any degree of accuracy, an empirical Equation must be obtained from a sample of the particles for a given packing arrangement.
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packed bed pressure drop dependence on particle shape size distribution packing arrangement and roughness
Powder Technology, 2013Co-Authors: K G Allen, T W Von Backstrom, D G KrogerAbstract:Abstract Packed beds have been used or proposed for many different applications, including thermal storage in buildings and in solar thermal power plants. In order to size the blowers and predict the operating and capital cost, the packed bed pressure drop must be known. The Ergun Equation, commonly used for predicting packed bed pressure drop, over-predicts the pressure drop through randomly packed or structured beds of smooth spheres at Ergun Reynolds numbers in excess of ≈ 700, and previous work has found it to under-predict the pressure drop through beds of rock by a factor as high as 5. Present measurements of the pressure drop for air flow through beds of rough spheres, smooth cylinders, cubes and crushed rock are significantly higher than those for smooth spheres, and all differ from the Ergun Equation. Particle shape, arrangement (including packing method) and surface roughness are shown to influence the pressure drop. Recent correlations for non-spherical particles are shown to differ significantly from present measurements. Different pressure drop measurements obtained for irregularly shaped rock packed into the test section in two different directions relative to the flow direction show that random packing is not necessarily isotropic. In order to predict the pressure drop over a packed bed of irregular particles such as crushed rock with any degree of accuracy, an empirical Equation must be obtained from a sample of the particles for a given packing arrangement.
Fengqi You - One of the best experts on this subject based on the ideXlab platform.
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optimization of two stage pressure vacuum swing adsorption with variable dehydration level for postcombustion carbon capture
Industrial & Engineering Chemistry Research, 2016Co-Authors: Karson T Leperi, Randall Q Snurr, Fengqi YouAbstract:To investigate postcombustion capture of CO2 in the presence of water, we developed a pressure/vacuum swing adsorption (P/VSA) cycle model consisting of a system of partial differential algebraic Equations incorporating mass and energy balances, the Ergun Equation for pressure changes, competitive Langmuir isotherms, and the linear driving force model. Four potential adsorbents, zeolites 13X and 5A and the MOFs HKUST-1 and Ni-MOF-74, are investigated, evaluated, and compared. Using this simulation, a two-stage Skarstrom cycle, coupled with an upstream dehydration unit and a downstream compression unit, is optimized using a nondominant sorting genetic algorithm, NSGA-II, to minimize the overall cost of capturing 90% of CO2 from flue gas at a purity of 90% and compressing it for pipeline transportation at 110 bar. The results show that under dry flue gas conditions, zeolite 13X is the best performing adsorbent with an overall cost of $32.1/ton of CO2. Under humid flue gas conditions, zeolites 13X and 5A per...
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Optimization of Two-Stage Pressure/Vacuum Swing Adsorption with Variable Dehydration Level for Postcombustion Carbon Capture
2015Co-Authors: Karson T Leperi, Randall Q Snurr, Fengqi YouAbstract:To investigate postcombustion capture of CO2 in the presence of water, we developed a pressure/vacuum swing adsorption (P/VSA) cycle model consisting of a system of partial differential algebraic Equations incorporating mass and energy balances, the Ergun Equation for pressure changes, competitive Langmuir isotherms, and the linear driving force model. Four potential adsorbents, zeolites 13X and 5A and the MOFs HKUST-1 and Ni-MOF-74, are investigated, evaluated, and compared. Using this simulation, a two-stage Skarstrom cycle, coupled with an upstream dehydration unit and a downstream compression unit, is optimized using a nondominant sorting genetic algorithm, NSGA-II, to minimize the overall cost of capturing 90% of CO2 from flue gas at a purity of 90% and compressing it for pipeline transportation at 110 bar. The results show that under dry flue gas conditions, zeolite 13X is the best performing adsorbent with an overall cost of $32.1/ton of CO2. Under humid flue gas conditions, zeolites 13X and 5A performed equally well with overall costs of capturing CO2 of approximately $34.1/ton of CO2
Sonia Woudberg - One of the best experts on this subject based on the ideXlab platform.
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an analytical Ergun type Equation for porous foams
Chemical Engineering Science, 2016Co-Authors: Sonia Woudberg, J P Du PlessisAbstract:Abstract The empirical coefficients of the Ergun Equation for granular packed beds have often been adjusted in the literature towards quantitative agreement with experimental pressure drop data of porous foams. Adjusting the coefficients of the Ergun Equation is not good practice since it resembles a fudge factor approach for which the coefficients have to be adjusted for every new application. In this study an analytical Ergun-type Equation is proposed for porous foams. The interstitial geometric configuration and accompanying flow conditions are remodelled to yield an Equation for the pressure gradient that have different functional dependencies on porosity, than in the case of granular media. Comparison of the pressure gradient predicted by the proposed model with an Ergun type Equation available in the literature enables quantification of the empirical coefficients of the latter Equation in terms of porosity. It is thereby illustrated that the constant empirical coefficients relate to the pore-scale geometry and therefore have physical meaning. The proposed model results from adaptations made to existing pore-scale models resembling porous foams. The model predictions are compared to experimental data and empirical models from the literature for the Darcy permeability and non-Darcy coefficient. The satisfactory correspondence provides confidence in the analytical modelling procedure. The proposed model follows a similar trend as an empirical model proposed in the literature for which the coefficients of the Ergun Equation have been adjusted for porous foams. Improvement in the predictive capability of the model is illustrated through comparison of the pressure gradient predicted by the proposed model with that of the existing models.
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an adaptable analytical Ergun type Equation for high porosity spongelike porous media
POROUS MEDIA AND ITS APPLICATIONS IN SCIENCE ENGINEERING AND INDUSTRY: 3rd International Conference, 2010Co-Authors: Sonia Woudberg, Prieur J Du PlessisAbstract:An analytical Ergun‐type Equation for spongelike media is introduced in which developing flow in the short ducts of high porosity metallic foams are accounted for. Instead of the customary procedure of adjusting the empirical coefficients of the Ergun Equation to apply to consolidated spongelike media, a pore scale model is introduced and the physical flow conditions remodelled. The pore‐scale linear dimensions are expressed as a function of porosity and the dependence of the form drag coefficient on porosity is incorporated into the model which leads to satisfactory predictions for the inertial coefficient. The model predictions are compared to experimental data from the literature and the satisfactory correspondence provides confidence in the physical adaptability of the model.
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Pore-scale derivation of the Ergun Equation to enhance its adaptability and generalization
Chemical Engineering Science, 2008Co-Authors: J. Prieur Du Plessis, Sonia WoudbergAbstract:The empirical nature of the well-known Ergun Equation for prediction of the permeability of granular materials inhibits the straightforward generalization to other geometries of the pore space and non-Newtonian effects of traversing fluids. In this paper the results are discussed of a pore-scale model that can be regarded as qualitative and quantitative proof of the Ergun Equation. The pore-scale model has superior adaptive capabilities and also allows investigation of the porosity dependence of the empirical coefficients of the Ergun Equation. Some advantages, based on physical grounds, of the pore-scale model are outlined.
Adam Luckos - One of the best experts on this subject based on the ideXlab platform.
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effect of material type and particle size distribution on pressure drop in packed beds of large particles extending the Ergun Equation
Fuel, 2015Co-Authors: Andrei Frederik Koekemoer, Adam LuckosAbstract:Abstract The dependence of packed bed pressure drop on variables such as particle size distribution (PSD) and material type are of vital importance in the design of industrial equipment including fixed- and fluidized-bed reactors, blast furnaces and fixed-bed gasifiers. The pressure drop across a packed bed is commonly calculated using the Ergun Equation that was developed using experimental data from laboratory-scale beds comprised of small, mono-sized, smooth, non-porous, spherical or nearly spherical particles. In the industrial applications much larger poly-dispersed particles are used, raising the need for a correlation based on more relevant measurements. This study deals with an extension of the Ergun Equation to packed beds of large coal, char and ash particles with different average particle diameters and different PSD widths. The research presented here has shown the influence of material type and PSD on both particle properties (sphericity) and packed bed properties (voidage and Sauter mean diameter). In turn these have a significant impact on the subsequent bed pressure drop. It was determined that a bed of ash particles has the highest voidage, followed by the char bed and then coal bed with the lowest voidage. The difference may be attributed to differences in particle sphericity as well as the surface roughness of the particles. In all cases the particle diameter had a lesser effect on bed voidage compared to PSD width, as wider PSD was associated with a lower bed voidage due to smaller particles filling the spaces between the larger particles. New values of the Ergun Equation constants were obtained via regression analysis from pressure drop data generated for coal, ash and char particles. The values applicable to coal (77.4 and 2.8), char (160.4 and 2.8) and ash (229.7 and 2.3) particles were found to better approximate bed pressure drop compared to those used in the original form of the Ergun Equation (150 and 1.75). The modified Ergun Equation can successfully be used to predict pressure drop in a composite packed bed of coal, char and ash particles mimicking the bed structure in an industrial packed-bed gasifier.