Pressure drop of structured packing in pilot column and comparison to common correlations

Packed columns are widely used in the chemical industry such as absorption,stripping,distillation,and extraction in the production of e.g.organic chemicals,and pharmaceuticals.Pressure loss and pressure drop correlations are of special interest when it comes to the hydrodynamic properties of a column.The pressure loss across the column is of interest in the design phase when the size of the blower to drive the gas stream through the column has to be decided.The loading point and flooding point are also influenced by the pressure loss and the area of operation is determined from these points.This work examines four different correlations on pressure drop.The correlations are(i)Ergun’s equation(1952),(ii)an improved version of Ergun’s equation by Stichlmair,Bravo,and Fair(1989),(iii)an equation developed by Billet and Schultes(1999),and(iv)an equation by Rocha,Bravo,and Fair(1993).The complexity of the correlations is increasing in the mentioned order,Ergun’s equation being the simplest one.This study investigates if the more complicated correlations give better predictions to pressure drop in packed columns.This is determined by comparing the correlations to experimental data for pressure drop in a packed column with 8.2 m of structured packing using water as the liquid and atmospheric air as the gas.Seven experiments were carried out for determining the pressure drop in the column with liquid flows varying from 0 to 500 kg·h^(-1).At constant liquid flow,the gas flow was varied from approximately 10 to 70 kg·h^(-1).The pressure drop across the non-wetted column was best described by the correlation by Rocha et al.while the pressure drop for liquid flows from 100 to 500 kg·h^(-1)was,in general,best described by Stichlmair’s equation.For an irrigated column,the highest deviation was a predicted pressure drop 69.6%lower than measured.The best prediction was 0.1%higher than the measured.This study shows,surprisingly,that for a system of water and atmospheric air,complicated correlations on pressure drop determination do not provide better estimates than simple equations.

Correlation Factor Analysis of Retinal Microvascular Changes in Patients With Essential Hypertension

Objectives To investigate correlation between retinal microvascular signs and essential hypertension classification. Methods The retinal microvascular signs in patients with essential hypertension were assessed with the indirect biomicroscopy lens, the direct and the indirect ophthalmoscopes were used to determine the hypertensive retinopathy grades and retinal arteriosclerosis grades. The rank correlation analysis was used to analysis the correlation these grades with the risk factors concerned with hypertension. Results Of 72 cases with essential hypertension, 28 cases complicated with coronary disease, 20 cases diabetes, 41 cases stroke, 17 cases renal malfunction. Varying extent retinal arterioscleroses were found in 71 cases, 1 case with retinal hemorrhage, 2 cases with retina edema, 4 cases with retinal hard exudation, 5 cases with retinal hemorrhage complicated by hard exudation, 2 cases with retinal hemorrhage complicated by hard exudation and cotton wool spot, 1 case with retinal hemorrhage complicated by hard exudation and microaneurysms, 1 case with retinal edema and hard exudation, 1 case with retinal microaneurysms, 1 case with branch retinal vein occlusion. The rank correlation analysis showed that either hypertensive retinopathy grades or retinal arteriosclerosis grades were correlated with risk factor lamination of hypertension （r=0.25 or 0.31, P 〈0.05）, other correlation factors included age and blood high density lipoprotein concerned about hypertensive retinopathy grades or retinal arteriosclerosis grades, but other parameters, namely systolic or diastolic pressure, total cholesterol, triglyceride, low density lipoprotein cholesterol, fasting blood glucose, blood urea nitrogen and blood creatinine were not confirmed in this correlation analysis （P 〉 0.05）. Conclusions Either hypertensive retinopathy grade or retinal arteriosclerosis grade is close with the hypertension risk factor lamination, suggesting that the fundus examination of patients with hypertension plays a important part in predicting the incidence of cardiovascular events.

Analysis of the relationship between water level fluctuation and seismicity in the Three Gorges Reservoir(China)

The Three Gorges Reservoir is a good site for the further researches on reservoir induced seismicity due to decades＇ seismic monitoring. After the first water impounding in 2003, seismic activity becomes more frequent than that before water impoundment. In order to quantitatively study, the relationship between the water level fluctuation and earthquakes in TGR, we introduced statistical methods to attain the goal. First of all, we relocated the earthquakes in TGR region with double difference method and divided the earthquakes into 5 clusters with clustering analysis method. Secondly, to examine the impacts of water level fluctuation in different water filling stages on the seismic activity in the 5 clusters, a series of statistical analyses are applied. Pearson correlation results show that only the 175 m water level fluc- tuation has significantly positive impacts on the seismic activity in clusters I, II, III and V with correlation coefficients of 0.44, 0.38, 0.66 and 0.63. Cross-correlation analysis demonstrates that 0, ], 0 and 0 month time delay separately for the clusters I, II, III and V exists. It illustrated the influences of the water loading and pore pressure diffusion on induced earthquakes. Cointegration tests and impulse response analysis denoted that the 175 m water level only had long term and significant effects just on the seismic events in the intersection region of the Fairy Mount Fault and Nine-brook Fault. One standard deviation shock to 175 m water level increased the seismic activity in cluster V for the first 3 months, and then the negative influence was shown. After 7 months, the negative impulse response becomes stable. The long-term effect of the 175 m water impoundment also proved the important role of pore pressure diffusion in RIS with time.

An EPR Study on Intramolecular Spin Exchange and Rotational Mobility of Nitroxides Linked by a Long-chain

The effects of pressure and solvent on the intramolecular spin exchange of biradicals having two nitroxide fragments linked by a long flexible chain were studied by means of highpressure EPR technique.It was found that the intramolecular exchange interaction between nitroxides of biradical took place through the direct contact between them.By analyzing the observed EPR spectra,we have estimated the ratio(in/out)value of the average lifetime of the radical fragments inside a cage(in)to that outside the cage(out).The in/out values decreased with decreasing temperature and increasing pressure.The results suggest that the nearly cyclic conformation in a cage is favorable in solution.Further,the rotational correlation time of individual nitroxide was estimated from the anisotropic EPR signal,and the information on the segmental motion of the nitroxide group in biradical was obtained.

ERRATUM TO “CHARACTERISTICS OF PRESSURE DROP AND CORRELATION OF FRICTION FACTORS FOR SINGLE-PHASE FLOW IN ROLLING HORIZONTAL PIPE”

This is the erratum to the article [zhang Jin-hong, Yan Chang-qi, Gao Pu-zhen, Journal of Hydrodynamics, 2009, 21(5)]. The Fig.5 is corrected.

Evaluation of machine learning algorithms for predictive Reynolds stress transport modeling

The application of machine learning(ML)algorithms to turbulence modeling has shown promise over the last few years,but their application has been restricted to eddy viscosity based closure approaches.In this article,we discuss the rationale for the application of machine learning with high-fidelity turbulence data to develop models at the level of Reynolds stress transport modeling.Based on these rationales,we compare different machine learning algorithms to determine their efficacy and robustness at modeling the different transport processes in the Reynolds stress transport equations.Those data-driven algorithms include Random forests,gradient boosted trees,and neural networks.The direct numerical simulation(DNS)data for flow in channels are used both as training and testing of the ML models.The optimal hyper-parameters of the ML algorithms are determined using Bayesian optimization.The efficacy of the above-mentioned algorithms is assessed in the modeling and prediction of the terms in the Reynolds stress transport equations.It was observed that all three algorithms predict the turbulence parameters with an acceptable level of accuracy.These ML models are then applied for the prediction of the pressure strain correlation of flow cases that are different from the flows used for training,to assess their robustness and generalizability.This explores the assertion that ML-based data-driven turbulence models can overcome the modeling limitations associated with the traditional turbulence models and ML models trained with large amounts of data with different classes of flows can predict flow field with reasonable accuracy for unknown flows with similar flow physics.In addition to this verification,we carry out validation for the final ML models by assessing the importance of different input features for prediction.

Magnetically assisted gas-solid fluidization in a tapered vessel:Part II Dimensionless bed expansion scaling

The article presents an effort to create dimensionless scaling correlations of the overall bed porosity in the case of magnetically assisted fluidization in a tapered vessel with external transverse magnetic field. This is a stand of portion of new branch in the magnetically assisted fluidization recently created concerning employment of tapered vessels. Dimensional analysis based on ＂pressure transform＂ of the initial set of variables and involving the magnetic granular Bond number has been applied to develop scaling relationships of dimensionless groups representing ratios of pressures created by the fluid flow, gravity and the magnetic field over an elementary volume of the fluidized bed. Special attention has been paid on the existing data correlations developed for non-magnetic beds and the links to the new ones especially developed for tapered magnetic counterparts. A special dimensionless variable Xp = （Ar△Dbt）1/3√RgMQ combining Archimedes and Rosensweig numbers has been conceived for porosity correlation. Data correlations have been performed by power-law, exponential decay and asymptotic functions with analysis of their adequacies and accuracies of approximation.