Original Research Paper
CFD simulation of solid–liquid stirred tanks
Divyamaan Wadnerkar,Ranjeet P.Utikar ?,1,Moses O.Tade,Vishnu K.Pareek
Department of Chemical Engineering,Curtin University,Perth 6102,Australia
a r t i c l e i n f o Article history:
Received 31October 2011
Received in revised form 6March 2012Accepted 17March 2012
Available online 25April 2012Keywords:
Solid–liquid suspension Stirred tanks
Hydrodynamic study Drag models Homogeneity Cloud height CFD
a b s t r a c t
Solid liquid stirred tanks are commonly used in the minerals industry for operations like concentration,leaching,adsorption,ef?uent treatment,https://www.doczj.com/doc/ae473375.html,putational Fluid Dynamics (CFD)is increasingly being used to predict the hydrodynamics and performance of these systems.Accounting for the solid–liquid interaction is critical for accurate predictions of these systems.Therefore,a careful selection of models for turbulence and drag is required.In this study,the effect of drag model was studied.The Eulerian–Eule-rian multiphase model is used to simulate the solid suspension in stirred tanks.Multiple reference frame (MRF)approach is used to simulate the impeller rotation in a fully baf?ed tank.Simulations are con-ducted using commercial CFD solver ANSYS Fluent 12.1.The CFD simulations are conducted for concen-tration 1%and 7%v/v and the impeller speeds above the ‘‘just suspension speed’’.It is observed that high turbulence can increase the drag coef?cient as high as forty times when compared with a still ?uid.The drag force was modi?ed to account for the increase in drag at high turbulent intensities.The modi?ed drag is a function of particle diameter to Kolmogorov length scale ratio,which,on a volume averaged basis,was found to be around 13in the cases simulated.The modi?ed drag law was found to be useful to simulate the low solids holdup in stirred tanks.The predictions in terms of velocity pro?les and the solids distribution are found to be in reasonable agreement with the literature experimental data.Turbu-lent kinetic energy,homogeneity and cloud height in the stirred tanks are studied and discussed in the paper.The presence of solids resulted in dampening of turbulence and the maximum deviation was observed in the impeller plane.The cloud height and homogeneity were found to increase with an increase in impeller speed.The work provides an insight into the solid liquid ?ow in stirred tanks.
ó2012The Society of Powder Technology Japan.Published by Elsevier B.V.and The Society of Powder
Technology Japan.All rights reserved.
1.Introduction
Solid–liquid mixing systems are amongst the common opera-tions used in the ?eld of chemical and mineral industry.The main purpose of mixing is the contact between the solid and liquid phase for facilitating mass transfer.In industrial processes effective mixing is necessary at both micro and macro level for adequate performance.At the micro level,micromixing governs the chemical and mass transfer reactions.Micromixing is facilitated by mixing at macro level.Numerous factors such as the just suspension speed,critical suspension speed,solids distribution,etc.dictate the mix-ing performance.CFD has proved to be a useful tool in analyzing the impact of these factors on the ?ow characteristics of such sys-tems [1–7].Proper evaluation of interphase drag is essential for accurate predictions using the CFD model.In this study four differ-ent drag models are analysed and their validity is checked by com-paring the results of CFD simulations at low concentrations of solid with the experimental data available in the literature [8].The behaviour of turbulence kinetic energy,suspension quality and cloud height are extensively discussed.2.Literature review
Micale et al.[5]used Settling Velocity Model (SVM)and Multi ?uid Model (MFM)approaches to analyse the particle distribution in stirred tanks.In SVM,it is assumed that the particles are trans-ported as a passive scalar or molecular species but with a superim-posed sedimentation ?ow,whereas in MFM,momentum balances are solved for both https://www.doczj.com/doc/ae473375.html,putationally intensive MFM was found to be better than SVM,but for both the models it was neces-sary to take into account the increase in drag with the increasing turbulence.Micale et al.[4]simulated the solids suspension of 9.6%and 20%volume fractions using the MFM approach and slid-ing grid (SG)approach using the Schillar Nauman drag model.Schillar Nauman is applicable on spherical particles in an in?nite stagnant ?uid and accounts for the inertial effect on the drag force acting on it.It provided satisfactory results at low impeller speed.Derksen [9]conducted Eulerian–Lagrangian simulations to study the velocity ?eld,turbulence,solid distribution and particle-impeller and particle–particle collision and frequencies
0921-8831/$-see front matter ó2012The Society of Powder Technology Japan.Published by Elsevier B.V.and The Society of Powder Technology Japan.All rights reserved.https://www.doczj.com/doc/ae473375.html,/10.1016/j.apt.2012.03.007
?Corresponding author.Tel.:+61892669837;fax:+61892662681.
E-mail address:r.utikar@https://www.doczj.com/doc/ae473375.html,.au (R.P.Utikar).1
Present address.
in a stirred tank system.Inertial,gravitational and drag forces were included,but Saffman,Magnus and stress forces were kept condi-tional and their effect were studied.The effect of these forces was found to be negligible due to the high magnitude of drag,inertial and gravitational force.
Ochieng and Lewis[7]simulated nickel solids loading of 1–20%w/w with impeller speeds between200and700rpm using both steady and transient simulations and found out that transient simulations,although time consuming,are better for stirred tank simulations.The initial?ow?eld was generated using the multiple reference frame(MRF)approach and then the simulations were carried out using SG.The Gidaspow model was used for the drag factor,which is a combination of the Wen and Yu model and the Ergun equation[10].Wen and Yu drag is appropriate for dilute systems and Ergun is used for dense packing.For the study of just suspended of solids using solids at the bottom of the tank as an initial condition,it provided satisfactory results.
The suspension can also be modelled as a continuous phase using a viscosity law and the shear induced migration phenomenon generated by gradients in shear rates or concentration gradients can be captured at a macroscopic scale.For the prediction of shear-induced particle migration,the Shear Induced Migration Model(SIMM)was used,which states that,in a viscous concen-trated suspension,small but non-Brownian particles migrate from regions of high shear rate to regions of low shear rate,and from re-gions of high concentrations to regions of low concentrations in addition to which settling by gravity is added.In the case of a mix-ing process,owing to the action of shear and inertia,the particles may segregate and demix,thereby generating concentration gradi-ents in the vessel.This shear-induced migration phenomenon can be simulated at the macroscopic scale,where the suspension is modelled as one continuous phase through a viscosity law[1]. However,this model shows potentially erratic behaviour in close-to-zero shear rate and high concentration zones.
The dependency of the drag on the turbulence was numerically investigated by Khopkar et al.[3]by conducting experiments using single phase?ow through regularly arranged cylindrical objects.A relationship between the drag,particle diameter and Kolmogorov length scale was?t into the expression given by Brucato et al.
[11].They found that the drag predicted by the original Brucato drag model needs to be reduced by a factor of10.This modi?ed Brucato model was then used for the simulation of liquid?ow?eld in stirred tanks[2].It was able to capture the key features of liquid phase mixing process.
Panneerselvam et al.[12]used the Brucato drag law to simulate 7%v/v solids in liquid.MRF approach was used with Eulerian–Eule-rian model.There was mismatch in the radial and tangential com-ponents of velocity at impeller plane.This discrepancy was attributed to the turbulent?uctuations that dominate the impeller region,which the model was not able to capture successfully.
Guha[13]conducted numerical simulations and assessed dif-ferent approaches viz.LES and Eulerian–Eulerian(using Schiller–Nauman drag model)to simulate turbulent solid–liquid?ow in a low solid loading(1%by volume)stirred tank by comparing with results from the CARPT experiment.Either of the simulation ap-proach was not able to predict a stronger lower circulation loop as is observed in the experiments.The stronger loop is because of the high magnitude axial velocities striking the walls,which is not the case in the region above https://www.doczj.com/doc/ae473375.html,parisons were done with respect to the solids velocities,turbulent kinetic energy,and solids sojourn times at various parts of the tank.LES predicted radial velocities better than the Euler–Euler in the impeller plane. Elsewhere,both the predictions were comparable.It was because of the high turbulent?uctuations in this region that was not taken into account by the drag formulation used.
It is quite clear from the review that solids suspension and dis-tribution is highly dependent on the turbulence and interphase drag in the tank.At low impeller speeds,turbulent?uctuations are less and hence do not affect the predictions much.However, at higher impeller speeds,the drag and turbulence become increas-ingly important.Moreover,there is no consensus on the appropri-ate drag for liquid–solid stirred tanks.Therefore,in this study,the impact of drag model on the?ow distribution and the velocity ?elds is investigated.Different drag models are assessed to provide a clear understanding of the selection criterion of drag in a partic-ular case.
3.CFD model
3.1.Model equations
The hydrodynamic study is simulated using Eulerian–Eulerian multiphase model.The phases,in this model,are treated as inter-penetrating continua represented by a volume fraction at each point of the system.The Reynolds averaged mass and momentum balance equations are solved for each of the phases.The governing equations are given below:
Continuity equation:
@
ea q q qTtr:a q q q~u q
?0
Momentum equation:
@
@t
a q q
q
~u
q
tr:a q q q~u q~u q
?àa q r Ptr:s qta q q q~g
t~F tdt~F qt~F lift;qt~F v m;q
t~F12 where q is1or2for primary or secondary phase,respectively,a is volume fraction,q is density,~u is the velocity vector,P is pressure and is shared by both the phases,s is the stress tensor because of viscosity and velocity?uctuations,g is gravity,~F td is force due to turbulent dissipation,~F q is external force,~F lift;q is lift force,~F v m;q is virtual mass force and~F12is interphase interaction force.
The stress–strain tensor is due to viscosity and Reynolds stres-ses that include the effect of turbulent?https://www.doczj.com/doc/ae473375.html,ing the Boussinesq’s eddy viscosity hypothesis the closure can be given to the above momentum transfer equation.The equation can be gi-ven as:
s q?a q l
q
r~u qtr~u T
q
ta q k qà
2
3
l
q
r:~u q I
where l is the shear viscosity,k is bulk viscosity and is the unit stress tensor.
3.2.Equations for turbulence
k-e mixture turbulence and k-e dispersed turbulence models are used in the present study.The mixture turbulence model assumes the domain as a mixture and solves for k and e values which are common for both the phases.In the dispersed turbulence model, the modi?ed k-e equations are solved for the continuous phase and the turbulence quantities of dispersed phase are calculated using Tchen-theory correlations.It also takes the?uctuations due to turbulence by solving for the interphase turbulent momentum transfer.For the sake of brevity,only the equations of mixture model for turbulence are given below.Other equations can be found in the Fluent user guide[14].
@
eq m kTtr:q m~u m k
eT?r:
l
t;m
r
k
r k
tG k;màq m e
446 D.Wadnerkar et al./Advanced Powder Technology23(2012)445–453
@
@t eq m
e Ttr :q m ~u m e eT?r :l t ;m r e r e
te k
C 1e G k ;m àC 2e q m e à
áC 1e and C 2e are constants,r k and r e are turbulent Prandtl numbers.
The mixture density,q m and velocity,~u m are computed from the equations below:
q m ?
X N i ?1a i q i
~u m ?X N i ?1
a i q i ~u i =X N i ?1
a i q i
Turbulent viscosity,l t ;m and turbulence kinetic energy,G k ;m are computed from equations below:
l t ;m ?q m C l
k
2
e
G k ;m ?l t ;m er ~u m tr ~u T m T:r ~u m
3.3.Turbulent dispersion force
In the simulation of solid suspension in stirred tanks,the turbu-lent dispersion force is signi?cant when the size of turbulence ed-dies is larger than the particle size [2].Its signi?cance is also
highlighted in some previous studies [15].The role of this force is also analysed in this study.It is incorporated along with the momentum equation and is given as follows:
~F t ;d ?K pq ~u dr
where drift velocity,~dr
is given by,~u dr ?à
D p r pq a p r a p àD q
r pq a q
r a q
D p and D q are diffusivities and r pq is dispersion Prandtl number.3.4.Interphase drag force
The drag force represents interphase momentum transfer due to the disturbance created by each phase.For dilute systems and low Reynolds number,particle drag is given by Stokes law and for high Reynolds number,the Schillar Nauman drag model can be used.In the literature review other drag models such as Gidas-pow model [10]and Wen and Yu model [16]have also been dis-cussed.But for stirred tank systems,there should be a model that takes turbulence into account as with increasing Reynolds number and with the increase in the eddy sizes,the impact of tur-bulence on the drag increases.Considering this Brucato et al.[11]proposed a new drag model making drag coef?cient as a function of ratio of particle diameter and Kolmogorov length scales.So,with the change in the turbulence at some local point in the system,the drag will also change.The drag coef?cient proposed by Brucato et al.is given below:
C D àC Do C Do ?K
d p
k
3where,K is constant with value of 8.76?10à4,d P is particle diam-eter and k is Kolmogorov length scale.
Khopkar et al.[3]performed DNS simulations for conditions closer to those in stirred tanks.Based on these simulations they ob-tained a modi?ed version of Brucato drag that is more appropriate for stirred tanks.This modi?ed drag has a constant value of 8.76?10à5.Few more drag correlations that also take the depen-dency of drag on volume fraction and density into consideration
are available in the literature [17,18].For the conditions studied
in this paper,the drag force calculated using these models was similar to the modi?ed Brucato drag model.Therefore,Brucato and modi?ed Brucato models were used for further study.
In this paper,the Gidaspow,Wen and Yu,Brucato and modi?ed Brucato Drag models are assessed.The implementation of Brucato drag model uses Kolmogorov length scale calculated for each cell,rather than using a value from the mean power dissipated in the system and applying it all over the domain as is commonly practiced.
4.Methodology and boundary conditions 4.1.Vessel geometry
In the current study,a ?at bottomed cylindrical tank was simu-lated.The dimensions used are tank diameter,T =0.2m and tank height,H =T.The tank has four baf?es mounted on the wall of width T /10.The shaft of the impeller (of diameter =0.01m)was concentric with the axis of the tank.A six-bladed Rushton turbine was used as an impeller.The Rushton turbine has a diameter,D =T/3.For each blade,the length =T /12and the height =T /15.The impeller off-bottom clearance was (C =T/3)measured from the level of the impeller disc.The ?uid for the system was water (q =1000kg/m 3,l =0.001Pa.s)and the solids were small glass particles of density 2550kg/m 3and diameter of 0.3mm.4.2.Numerical simulations
Fig.1shows half of the computational domain with baf?es and stirrer.Owing to the rotationally periodic nature,half of the tank was simulated.Multiple reference frame (MRF)approach was used.A reference moving zone with dimensions r =0.06m and 0.03995 Table 1 Details of cases simulated.Case Impeller speed (rpm)Reynolds number Power number Single phase ?ow 100073926 4.9724031%Solids 100075071.85 4.9501417%Solids 1000 81946.97 4.63385 D.Wadnerkar et al./Advanced Powder Technology 23(2012)445–453447 value of power number that did not ment of the grid.The details of cases the paper are given in Table 1.5.Results and discussion 5.1.Preliminary numerical simulations Initial simulations were conducted to lence dispersion force.The ?ow ?eld found that there was negligible effect of this case of 0.01volume fraction.The higher in?uence at higher concentration of tude will be high enough to be being exerted on the secondary phase [15]. In order to verify that the residuals as well as additional parameters sipation over the volume and torque on the Once the residuals and additional simulation was deemed to be converged.5.2.Flow ?eld Fig.2shows the velocity vectors on a centre plane.For the Rushton turbine,an outward jet stream is formed due to the out-ward thrust of the impeller.This high velocity jet approaches to-wards the wall of the stirred tank and strikes it.The jet splits into two streams.One stream moves in axially upward and another in axially downward direction.It creates an anticlockwise velocity ?eld in the region above the impeller and a clockwise velocity ?eld in the region below the impeller.The velocity near walls for the re-gion above impeller is upwards and below the impeller is down-wards.It is opposite when the velocity ?eld is observed near the centre.The intensity of the recirculation in the region below the impeller is stronger than that above the impeller.Converged solu-tion showed similar ?ow ?eld (velocity ?eld vectors)as compared to that available in the literature [8].All the ?ow characteristics discussed above were captured by the CFD simulation and of the ?ow are clearly visible in Fig.2.The simulations were also able to capture the upward inclination of the jet and its asymmetry (Fig.2).This inclination is the result of the imbalance in the forces exerted on the ?ow due to the presence of bottom wall and ab-sence of top wall.In the simulations,different boundary conditions imposed on the vessel on the top wall (free slip)and bottom wall (no slip)result in this angular inclination.This effect was also shown in the simulation of Sbrizzai et al.[19].The velocity vectors near the top surface of the stirred tank show a very weak ?ow ?eld in this region. 5.3.Analysis of drag models 5.3.1.Slip velocity The slip velocity in the stirred tanks was analysed using Gidas-pow,Brucato and modi?ed Brucato drag models.A signi?cant dif-ference in the magnitude of slip velocity was observed between Gidaspow and Brucato drag model in the impeller zone (Fig.3).The reason behind the disparity in the predictions of drag models is the basis.Brucato drag correlation is entirely dependent on the turbulence and is calculated from the ratio of diameter to Kol-mogorov length scale.Gidaspow drag model is valid when the Inner Rotating Domain Outer Stationary Domain https://www.doczj.com/doc/ae473375.html,putational domain and grid distribution in stirred tank. Fig.2.Solid velocity vectors on plane between the baf?es for solid volume fraction of 0.01and 1000rpm. 448 D. internal forces are negligible which means that the viscous forces dominate the?ow behaviour.The?ow in the stirred tank is mainly turbulent.Although k-e turbulence model is not able to simulate turbulence effects at the Kolmogorov length scale,this effect has been taken into account in the modi?ed Brucato drag model. Khopkar et al.[3],while simulating the array of cylinders,have incorporated a source term in order to keep the lambda of the or-der as is observed in a stirred tank.As a result,the underprediction of slip velocities in the impeller zone is addressed by using the Bru-cato and modi?ed Brucato drag model.The magnitude of the drag increases with turbulence and hence,in?uences the slip velocity between primary and secondary phase.As seen from Fig.3,the Brucato drag modi?es the Wen–Yu drag to a greater extent than the modi?ed Brucato drag,but still the value of slip velocity it is predicting is below that predicted by modi?ed Brucato drag model. This is because of the impact of these models on the turbulence. Brucato drag,due to its magnitude,has a higher in?uence on the turbulence.The simulations show a high value of turbulent kinetic energy with the modi?ed Brucato drag rather than the Brucato drag model.And the dissipation noticed in the former case was smaller than the latter case.It has a negative impact on the drag calculated and hence the drag is underpredicted due to the low turbulence calculated in the stirred tank.In the cases simulated, the maximum observed difference in dampening of turbulence was10%.The impact of turbulence on drag is maximum visible in the impeller plane where turbulence is dominant.In this region, the ratio d p/k is greater than10and for d p/k>10,the interaction between energy dissipating eddies and particles become important for the solids concentration distribution[20].Derksen et al.[9] have compared the slip velocities in terms of linear and rotational Reynolds number and pointed out the dominance of high slip velocity in this impeller zone.All the compared drag models were able to capture the high slip velocities in this region.But,only modi?ed Brucato drag model predicted reasonable values of slip velocities.When compared with the linear slip velocity values for vertical plane midway between two baf?es,predictions by the Gidaspow and Brucato drag model were below the respective values from Derksen et al.[9].The maximum slip velocity values obtained were0.58,0.63and0.72for Gidaspow,Brucato and mod-i?ed Brucato drag models,respectively in the plane as compared to 0.75in case of Derksen et al.[9]. Another zone of higher slip velocities is the region in which the direction of axial velocities is upwards.In this zone,the velocity of the particles is against the force of gravity and increases the differ-ence in the velocity of continuous phase and the dispersed phase. The observed phenomenon is exactly opposite in the regions with axial velocity vectors pointing downwards[15,20–24].The slip velocities for1%volume fraction and7%volume fraction at 1000rpm were compared.All the parameters of the study were kept the same for the two cases except the solid volume fraction. Since,the velocity in the case of1%volume fraction case was greater than the just suspension speed and that in the case of7% volume fraction was below the speed of just suspension,a greater non-uniformity was observed in the solid concentration in the stirred tank.It resulted in an increased local value of slip velocity in regions with low solid concentration in the cases of higher average concentration of solids.Although the increase in concen-tration should result in the decrease in slip velocity,but for cases with impeller speed below and above the just suspension speed, local regions with higher slip velocities can be noticed.This behaviour was also observed by Sardeshpande et al.[25]. 5.3.2.Velocity components The simulations were run using different drag models and the results were then compared with the experimental data.Guha et al.[8]used CARPT technique,in which a single particle is intro-duced in the?ow with the ability to mimic the motion in the phase of interest.Considering the limitation of CARPT technique which has a spatial resolution of the data is7mm[26],the CFD results are reported on ensemble average basis in a7mm zone around the centreline of the measurement point. The radial velocity of the solid particles at impeller plane is shown in Fig.4.On x axis,r is radial position,Ri is impeller radius and R is stirred tank radius.Out of the four drag models wide disparity with experimental data was observed when using the Wen and Yu and the Gidaspow model.These two models predicted the highest radial velocities.Guha et al.[27]observed similar overprediction of radial velocities while using the Schiller–Nauman drag model.The Brucato drag model slightly overpredicted the radial velocity,whereas the predictions from the modi?ed Brucato drag were in reasonable agreement with experimental data.The solid velocities are higher at the impeller tip.As the solids approach towards wall,the velocity gradually decreases.Due to no slip condition on the wall,the velocity should gradually reach zero value at wall.But,quantitatively,there is an over-prediction of the velocities in simulations in near wall region.The disparity can be attributed to lesser number of data points available for averaging in experiments.The experiments clearly show a zero ensemble averaged value even at(ràRi)/(RàRi)=0.8,which is not reasonable. At low solid concentrations,Gidaspow drag model acts like Wen and Yu model and at higher concentrations it takes the form of the Ergun equation.Therefore,both Wen and Yu model and Gidaspow models predict the same result.The modi?ed Brucato drag model accounts for the effect of solid phase on the turbulence.At higher impeller speed,the role of turbulence in calculation of drag is vital factor,hence,the modi?ed Brucato drag model predicts better re-sults as compared to the other drag models. Fig.5shows the comparison between the simulations results and experimental data for radial velocity at axial plane r/R=à0.5.A po-sitive radial velocity is expected in the upper zone of the impeller.As compared to the negative velocity in the region higher than the impeller zone where the magnitude of negative velocity is merely 2%of the maximum velocity attained by the solids,the negative ra-dial velocity in the bottom of the tank is10%of the maximum veloc-ity.This corresponds to a relatively stronger?ow towards the centre in the bottom of the tank.It indicates the presence of stronger clock-wise currents.All the drag models could qualitatively capture this ?ow behaviour.For the experimental data,the highest tangential velocity is observed at z/T=0.36±0.04.This compares well the sim-ulation result of z/T=0.34.In the lower region of the stirred tank, D.Wadnerkar et al./Advanced Powder Technology23(2012)445–453449 where the effect of turbulence is not as prominent as the upper re-gion,the predictions from all the drag models compared well with experimental data.In the upper region,discrepancy was observed.Around the impeller zone,where,the turbulence and velocity ?uc-tuations are higher,the Wen and Yu and Gidaspow drag models show large overprediction compared to the experimental data.On the other hand,the Brucato and modi?ed Brucato drag show reason-able agreement.Fig.6shows the comparison between the simula-tions results and experimental data for tangential velocity at axial plane r /R =à0.5.Similar trend to that observed in radial velocity is observed. The axial velocity pro?le is shown in Fig.7.The reversal of ?ow can be clearly seen.Above the impeller,the axial velocities are neg-ative that means the ?ow is in downward direction.It reverses in the region below impeller.At the impeller,the axial velocity is zero and is distributed as the other two components of velocities viz.ra-dial and tangential.All the drag models were able to capture the ?ow reversal qualitatively.Moreover,the predictions of all the drag models were comparable.The experiments show higher axial velocity in the lower region compared to the upper region.Whereas,the simulations predicted similar velocities in the lower and upper region of the impeller.Although this phenomenon is vis- ible in Fig.2,the axial velocities shown in Fig.6fail to predict it.It is because of the bigger circular loop in the lower region of the impeller clearly seen in Fig.2,which also affects the ensemble averaging of values in this particular zone.At the impeller plane,the axial velocity is zero as it is distributed as the other two com-ponents of velocities. Modi?ed Brucato drag model was found to be the most appro-priate drag model and,therefore,the remaining analysis showed in the paper is based on the simulations conducted using this drag model. 5.3.3.Turbulent kinetic energy (TKE) The ?ow in a stirred tank is turbulent ?ow that results in the ?uctuating components of velocity due to formation of eddies.The k-e model used in the RANS simulation assumes isotropic tur-bulence and uses the Boussinesq hypothesis to relate the Reynolds stresses to the mean velocity gradients.The TKE represents the magnitude of turbulence present in the system.The presence of particles dampens turbulence.In order to access the impact of par-ticles,the TKE for single phase ?ow is compared with the TKE at solid loadings of 1%and 7%. For a single phase system,the liquid is agitated by the impeller.The high velocity and trailing vortices result in large velocity ?uc-tuations in the impeller plane.For this reason TKE was found to be the maximum at the blade tip (Fig.8(a)).As the velocity decrease radially in this plane,the TKE also decreases.The magnitude of TKE in the other parts of the tank is approximately 103times lower than those in the impeller plane.Michelleti et al.[28]used LDA technique to measure dissipation rates at various points in the stir-red tank and found the variation by more than 2orders of magni-tude between impeller region and the bulk.Dissipation rate follows the same trend as TKE not only in the impeller region but in the other regions of the stirred tanks as well.The TKE,sim-ilar to the trend observed by Michelleti et al.[28]for turbulence dissipation rate,is comparatively high near the walls and near the axially centre line where the axial velocity ?eld is dominant.Similar behaviour is observed in presence of particles (Fig.8(b)).However,the magnitude of TKE is much lower. Fig.9shows the comparison between the TKE pro?le at impel-ler plane for 0%,1%and 7%solids volume fraction.Within the impeller radius,the TKE increases due to the increase in turbu-lence.Initially,rate of increase is low as the impeller disc offers resistance.After the disc,the TKE increases steeply and reaches a maximum slightly beyond impeller radius.This behaviour is 450 D.Wadnerkar et al./Advanced Powder Technology 23(2012)445–453 attributed the vortices leaving the impeller blade that result in high magnitude ?uctuating velocities.After this point,the TKE gradually decreases along the radius due to decrease in velocities.As the velocity jet hits the vessel wall,it creates eddies resulting in ?uctuating velocities.As a result a small peak in the TKE is ob-served near the wall. The kinetic energy in the liquid is imparted to solids resulting in the solids following the jet.It is also the reason of maximum energy dissipation in this zone.The comparison shows 50%and 65%decrease in the kinetic energy observed for 1%and 7%vol-ume fraction of solids,respectively in the impeller plane.The kinetic energy of the liquid is dissipated in the suspension and dispersion of solid particles.This results in the decrease in the level of turbulence and is visible as lower levels of TKE.Nouri and Whitelaw [21]measured and analysed liquid and solid phase velocities in stirred vessels with solid concentration up to 0.02%.The effect of presence of particles,particle concentration and density is studied on the slip velocities and turbulence and the turbulence was found to decrease by up to 25%.Speci?cally,they found the dampening in the turbulence in impeller zone.In the impeller zone,both the TKE and particle concentration are maxi-mum.As a result,the dissipation of energy is the maximum in this region and leads to the maximum decrease in turbulence as particle concentration increases.The dampening of turbulence found by Derksen et al.[9]was around 15%.This value is far low-er than as observed in this paper.Similar observations were made by Michelleti et al.[29]that presented the turbulence dampening values between 50and 70%.The decrease in turbulence with increase in solid concentration was also observed by Barresi and Baldi [30],Micheletti et al.[29,31]and Ayazi Shamlou and Koutsakos [32].Micheletti et al.[29]conducted experiments to study velocity characteristics in stirred solid liquid suspension.The ?ow ?eld measurement in the presence of solids revealed signi?cant in?uence of their presence.The maximum difference was observed in the impeller plane that diminished with increas-ing radial distance.These points support the ?ndings in this paper where the turbulence is the maximum in the single phase ?ow and corresponding lower values of turbulence is observed for higher solid concentration.The difference in turbulence also decreases with the increase in the radial distance.In practical conditions,due to the increase in solids concentration,the dissipation of energy will be higher due to the high frequency of particle–particle,particle-wall and particle blades collision.The turbulence dampens in the presence of solids and the magni-tude of vortices leaving the impeller decreases.For the same reason,a shift in the peak of TKE is observed with increase in solid concentration. 5.3.4.Cloud height and homogeneity The velocities of the jet in the region above the impeller begin to decay after reaching a certain height.Negative buoyant jet behaviour is observed at this point and it results in a sudden con-centration gradient and is termed as ‘cloud height’.Beyond this height the velocity is not able to drag the solids.The cloud height was calculated for the stirred tanks at volume fractions 0.01and 0.07.Apart from just suspension speed,the cloud height is an important parameter for the representation of homogeneity.The cloud height between 0.45and 0.55T shows just suspension.The cloud height below this height shows poor homogeneity.And a cloud height that reaches 0.9T or above shows the highest quality of homogeneity.The cloud height in the stirred tank is shown as the iso-contours of the average volume fraction in the stirred tank (Fig.10). Fluctuations in the velocity and the solid concentration below the cloud height was observed to be negligible.Due to the sudden change in the ?ow ?eld and concentration,a zone of high turbulent ?uctuations and macroinstabilities forms at the cloud height.The velocity changes frequently and the cloud height ?uctuate around a constant value. At low solid concentration,the in?uence of solids on the liquid ?ow ?eld is less.At the same time the kinetic energy dissipation of the continuous phase for the suspension of the dispersed phase is lesser as compared to the high loading systems.As a result,the magnitude of the axial velocity is not altered to a great extent.The homogeneity in the stirred tank is,therefore,achievable at (a) Single Phase Flow (b) Solid- Liquid System (1% v/v) 1.1120.2810.0050.0710.0180.001J kg Fig.8.Turbulent kinetic energy contours stirred tanks at 1000rpm. Impeller Radius D.Wadnerkar et al./Advanced Powder Technology 23(2012)445–453451 low impeller speeds.The cloud height in this case is observed to be higher for the low solid loading system than the high solid loading system(Fig.10). Homogeneity is a measure of quality of suspension.The qual-ity of suspension increases with the impeller speed.The increase in the impeller speed results in a higher kinetic energy of the con-tinuous phase which is available for disposal to the solids.A strong velocity?eld for continuous phase is present at high impeller speeds in various zones of a stirred tank.The velocity of the jet near the top surface is also larger.The magnitude of up-ward axial velocity near the walls is found to be higher when compared with those at lower impeller speeds.This result in the attainment of a higher cloud height at higher impeller speeds as is evident from Fig.10.It is in accordance with the results ob-tained by Sardeshpande et al.[33]for impeller speeds above ‘speed of just suspension’.The non-monotonic behaviour in the cloud height is observed at very low impeller speeds[33].This ef-fect is due to the presence of pseudo-bottom formed because of the accumulation of undispersed solids at the bottom causing ‘false-bottom’effect.As a result the off-bottom clearance and the amount of suspended solids increases with increasing the impeller speed and hence,the cloud height decreases.Since,the impeller speed studied were not very low that can cause‘false bottom effect’,this non-monotonic behaviour was not observed. The height of the interface between the clear liquid layer and the solid suspension layer is lower in the region above the impel-ler as the recirculating jet forces solids downwards near the axis. This phenomenon is prominent at low impeller speeds due to the weak upward axial?ow and the dominance of the drawing action right above the impeller. 6.Conclusion CFD simulations of solid suspension in stirred tank were per-formed.The predictions of four different drag models were com-pared.It was observed that turbulence dispersion force had negligible effect due to a low volume fraction of solids.Axial,radial and tangential velocities were compared at different axial loca-tions.It was observed that all four models could qualitatively cap-ture the?ow in stirred tank.The Wen and Yu and Gidaspow model showed biggest deviation from the experimental data while results from the modi?ed Brucato drag model were in reasonable agree-ment for the liquid?ow?elds. Maximum turbulence kinetic energy was found in the impeller zone.The turbulence dampens with the increase in the solids con-centration and this effect was the most signi?cant in this zone.For achieving homogeneity at low loading stirred tanks,a low impeller speed is adequate.However,high impeller speed is needed for high solid loading systems,as the energy dissipation is signi?cant due to more number of particles and high frequency of particle–particle, particle-wall and particle-blade collisions. References [1]L.Fradette,P.A.Tanguy,F.O.Bertrand,F.Thibault,J.-B.T.Ritz,E.Giraud,CFD phenomenological model of solid-liquid mixing in stirred vessels,Computers and Chemical Engineering31(2007)334–345. [2]G.R.Kasat,A.R.Khopkar,V.V.Ranade,A.B.Pandit,CFD simulation of liquid- phase mixing in solid-liquid stirred reactor,Chemical Engineering Science63 (2008)3877–3885. [3]A.R.Khopkar,G.R.Kasat, A.B.Pandit,V.V.Ranade,Computational?uid dynamics simulation of the solid suspension in a stirred slurry reactor, Industrial and Engineering Chemistry Research45(2006)4416–4428. [4]G.Micale, F.Grisa?,L.Rizzuti, A.Brucato,CFD simulation of particle suspension height in stirred vessels,Chemical Engineering Research and Design82(2004)1204–1213. [5]G.Micale,G.Montante,F.Grisa?,A.Brucato,J.Godfrey,CFD simulation of particle distribution in stirred vessels,Chemical Engineering Research and Design78(2000)435–444. [6]G.Montante,G.Micale,F.Magelli,A.Brucato,Experiments and CFD predictions of solid particle distribution in a vessel agitated with four pitched blade turbines,Chemical Engineering Research and Design79(2001)1005–1010. [7]A.Ochieng,A.E.Lewis,CFD simulation of solids off-bottom suspension and cloud height,Hydrometallurgy82(2006)1–12. [8]D.Guha,P.A.Ramachandran,M.P.Dudukovic,Flow?eld of suspended solids in a stirred tank reactor by Lagrangian tracking,Chemical Engineering Science62 (2007)6143–6154. [9]J.J.Derksen,Numerical simulation of solids suspension in a stirred tank, American Institute of Chemical Engineers,AIChE Journal49(2003)2700. [10]J.Ding,D.Gidaspow,A bubbling?uidization model using kinetic theory of granular?ow,AIChE Journal36(1990)523–538. [11]A.Brucato,F.Grisa?,G.Montante,Particle drag coef?cients in turbulent?uids, Chemical Engineering Science53(1998)3295–3314. [12]R.Panneerselvam,S.Savithri,G.D.Surender,CFD modeling of gas–liquid–solid mechanically agitated contactor,Chemical Engineering Research and Design 86(2008)1331–1344. [13]D.Guha,Evaluation of large Eddy simulation and Euler–Euler CFD models for solids?ow dynamics in a stirred tank reactor,American Institute of Chemical Engineers,AIChE Journal54(2008)766–778. [14]ANSYS,Fluent User Guide,in:ANSYS Inc.,Canonsburg,PA,http:// www.?https://www.doczj.com/doc/ae473375.html,,2009. [15]M.Ljungqvist,A.Rasmuson,Numerical simulation of the two-phase?ow in an axially stirred vessel,Chemical Engineering Research and Design79(2001) 533–546. [16]C.Y.Wen,Y.H.Yu,Mechanics of?uidization,in:Chemical Engineering Progress Symposium Series,1966,pp.100–111. [17]https://www.doczj.com/doc/ae473375.html,ne,M.P.Schwarz,G.M.Evans,Numerical modelling of gas and liquid ?ow in stirred tanks,Chemical Engineering Science60(2005)2203–2214. [18]D.Fajner,D.Pinelli,R.S.Ghadge,G.Montante,A.Paglianti,F.Magelli,Solids distribution and rising velocity of buoyant solid particles in a vessel stirred with multiple impellers,Chemical Engineering Science63(2008)5876–5882. [19]F.Sbrizzai,https://www.doczj.com/doc/ae473375.html,vezzo,R.Verzicco,M.Campolo,A.Soldati,Direct numerical simulation of turbulent particle dispersion in an unbaf?ed stirred-tank reactor, Chemical Engineering Science61(2006)2843–2851. [20]A.Ochieng,M.S.Onyango,Drag models,solids concentration and velocity distribution in a stirred tank,Powder Technology181(2008)1–8. [21]J.M.Nouri,J.H.Whitelaw,Particle velocity characteristics of dilute to moderately dense suspension?ows in stirred reactors,International Journal of Multiphase Flow18(1992)21–33. [22]P.Guiraud,J.Costes,J.Bertrand,Local measurements of?uid and particle velocities in a stirred suspension,Chemical Engineering Journal68(1997)75– 86. height in stirred tanks.(a)0.01volume fraction1000rpm(b)0.07volume fraction600rpm(c)0.07volume fraction800rpm [23]M.Ljungqvist,A.Rasmuson,The two-phase?ow in an axially stirred vessel investigated using phase-doppler anemometry,The Canadian Journal of Chemical Engineering82(2004)275–288. [24]P.Pianko-Oprych, A.W.Nienow,M.Barigou,Positron emission particle tracking(PEPT)compared to particle image velocimetry(PIV)for studying the?ow generated by a pitched-blade turbine in single phase and multi-phase systems,Chemical Engineering Science64(2009)4955–4968. [25]M.V.Sardeshpande,V.A.Juvekar,V.V.Ranade,Solid suspension in stirred tanks:UVP measurements and CFD simulations,The Canadian Journal of Chemical Engineering89(2011)1112–1121. [26]J.Chaouki, https://www.doczj.com/doc/ae473375.html,rachi,M.P.Dudukovic,Noninvasive tomographic and velocimetric monitoring of multiphase?ows,Industrial and engineering chemistry research36(1997)4476–4503. [27]D.Guha,Evaluation of large Eddy simulation and Euler–Euler CFD models for solids?ow dynamics in a stirred tank reactor,American Institute of Chemical Engineers,AIChE Journal54(2008).766-766. [28]M.Micheletti,S.Baldi,S.L.Yeoh,A.Ducci,G.Papadakis,K.C.Lee,M.Yianneskis, On spatial and temporal variations and estimates of energy dissipation in stirred reactors,Chemical Engineering Research and Design82(2004)1188–1198.https://www.doczj.com/doc/ae473375.html,/science/article/pii/S0263876204726064. [29]M.Micheletti,M.Yianneskis,Study of?uid velocity characteristics in stirred solid-liquid suspensions with a refractive index matching technique, Proceedings of the Institution of Mechanical Engineers,Part E:Journal of Process Mechanical Engineering218(2004)191–204. [30]A.Barresi,G.Baldi,Solid dispersion in an agitated vessel,Chemical Engineering Science42(1987)2949–2956. [31]M.Micheletti,Particle concentration and mixing characteristics of moderate- to-dense solid–liquid suspensions,Industrial and Engineering Chemistry Research42(2003).6236-6236. [32]P.Ayazi Shamlou,E.Koutsakos,Solids suspension and distribution in liquids under turbulent agitation,Chemical Engineering Science44(1989) 529–542. [33]M.V.Sardeshpande,A.R.Sagi,V.A.Juvekar,V.V.Ranade,Solid suspension and liquid phase mixing in solid–liquid stirred tanks,Industrial and Engineering Chemistry Research48(2009)9713. D.Wadnerkar et al./Advanced Powder Technology23(2012)445–453453 第七章CFD仿真模拟 一．初识CFD CFD是英文Computational Fluid Dynamics（计算流体动力学）的简称。它是伴随着计算机技术、数值计算技术的发展而发展的。简单地说，CFD相当于"虚拟"地在计算机做实验，用以模拟仿真实际的流体流动情况。而其基本原理则是数值求解控制流体流动的微分方程，得出流体流动的流场在连续区域上的离散分布，从而近似模拟流体流动情况。可以认为CFD是现代模拟仿真技术的一种。 1933年，英国人Thom首次用手摇计算机数值求解了二维粘性流体偏微分方程，CFD由此而生。1974年，丹麦的Nielsen首次将CFD用于暖通空调工程领域，对通风房间内的空气流动进行模拟。之后短短的20多年内，CFD技术在暖通空调工程中的研究和应用进行得如火如荼。如今，CFD技术逐渐成为广大空调工程师和建筑师解决分析工程问题的有力工具。 二．为什么用CFD CFD是一种模拟仿真技术，在暖通空调工程中的应用主要在于模拟预测室内外或设备内的空气或其他工质流体的流动情况。以预测室内空气分布为例，目前在暖通空调工程中采用的方法主要有四种：射流公式，Zonal model，CFD以及模型实验。 由于建筑空间越来越向复杂化、多样化和大型化发展，实际空调通风房间的气流组织形式变化多样，而传统的射流理论分析方法采用的是基于某些标准或理想条件理论分析或试验得到的射流公式对空调送风口射流的轴心速度和温度、射流轨迹等进行预测，势必会带来较大的误差。并且，射流分析方法只能给出室内的一些集总参数性的信息，不能给出设计人员所需的详细资料，无法满足设计者详细了解室内空气分布情况的要求； Zonal model是将房间划分为一些有限的宏观区域，认为区域内的相关参数如温度、浓度相等，而区域间存在热质交换，通过建立质量和能量守恒方程并充分考虑了区域间压差和流动的关系来研究房间内的温度分布以及流动情况，因此模拟得到的实际上还只是一种相对"精确"的集总结果，且在机械通风中的应用还存在较多问题； 模型实验虽然能够得到设计人员所需要的各种数据，但需要较长的实验周期和昂贵的实验费用，搭建实验模型耗资很大，有文献指出单个实验通常耗资3000～20000美元，而对于不同的条件，可能还需要多个实验，耗资更多，周期也长达数月以上，难于在工程设计中广泛采用。 另一方面，CFD具有成本低、速度快、资料完备且可模拟各种不同的工况等独特的优点，故其逐渐受到人们的青睐。由表1给出的四种室内空气分布预测方法的对比可见，就目前的三种理论预测室内空气分布的方法而言，CFD方法确实具有不可比拟的优点，且由于当前计算机技术的发展，CFD方法的计算周期和成本完全可以为工程应用所接受。尽管CFD方法还存在可靠性和对实际问题的可算性等问题，但这些问题已经逐步得到发展和解决。因此，CFD方法可应用于对室内空气分布情况进行模拟和预测，从而得到房间内速度、温度、湿度以及有害物浓度等物理量的详细分布情况。 进一步而言，对于室外空气流动以及其它设备内的流体流动的模拟预测，一般只有模型实验或CFD方法适用。表1的比较同样表明了CFD方法比模型实验的优越性。故此，CFD方法可作为解决暖通空调工程的流动和传热传质问题的强有力工具而推广应用。 表1四种暖通空调房间空气分布的预测方法比较 比较项目 1射流公式 2 ZONAL MODEL 3CFD 4模型实验 房间形状复杂程度简单较复杂基本不限基本不限 ?对经验参数的依赖性几乎完全很依赖一些不依赖 医药工业洁净厂房设计规范 第一章总则 第1.0.1条为了贯彻执行国家《药品生产质量管理规范》（以下简称ＧＭＰ），提出符合ＧＭＰ要求的生产厂房、设施及设备的设计要求，特制订本规范。 第1.0.2条本规范适用于新建、改建和扩建的医药制剂、原料药和药用辅料的精制、干燥、包装工序，直接接触药品的药用包装材料、无菌医疗器械等医药工业洁净厂房的设计。 第1.0.3条医药工业洁净厂房诉设计必须贯彻国家有关方针、政策。做到技术先进、确保质量、安全实用、经济合理，符合节约能源和保护环境的要求。 第1.0.4条医药工业洁净厂房的设计，既要满足当前产品生产的工艺要求，也应适当考虑今后生产发展和工艺改进的需要。 第1.0.5条在利用原有建筑和设施进行洁净技术改造时，可根据生产工艺要求，从实际出发，充分利用现有的技术设施，符合因地制宜的原则。 第1.0.6条医药工业洁净厂房的设计应为施工安装、维护、管理、检修、测试和安全运行创造必要的条件。 第1.0.7条医药工业洁净厂房的设计除应执行本规范外，还应符合现行的国家标准、规范和规定的有关要求。 第二章生产区域的环境参数 第一节一般规定 第2.1.1条为了保证医药产品生产质量，防止生产环境对产品的污染，生产区域必须满足规定的环境参数标准。 注2：空气洁净度的测试以静态条件为依据，测试方法应符合国家医药管理工业洁净室和洁净区悬浮粒子的测试方法》中有关规定； 注3：对于空气洁净度为100级的洁净室，室内大于等于5μm尘粒的计数，应进行多次采样，当其多次出现时，方可认为该测试数值是可靠的。 第2．2．2条药品生产有关工序和环境区域的空气洁净度等级按国家CMP等有关规定确定。 第2．2．3条洁净室内的温度和湿度应符合下列规定： 一、生产工艺对温度和湿度无特殊要求时，以穿着洁净工作服不产生不舒服感为宜。空气洁净度100级、10000级区域一般控制温度为20～24℃，相对湿度为45～60%。100000级区域一般控制温度为18～28℃，相对湿度为50～65%。 二、生产工艺对温度和湿度有特殊要求时，应根据工艺要求确定。 第2．2．4条洁净室内应保持一定的新鲜空气量，其数值应取下列风量中的最大值： 一、非单向流洁净室总送风量的10～30%，单向流洁净室总送风量的2～4%； 二、补偿室内排风和保持室内正压值所需的新鲜空气量； 三、保证室内每人每小时的新鲜空气量不小于40m3。 第2．2．5条洁净室必须维持一定的正压。不同空气洁净度的洁净区之间以及洁净区与非洁净区之间的静压差不应小于5Pa,洁净区与室外的静压差不应小于10Pa。 青霉素等特殊药物生产洁净区，固体口服制剂配料、制粒、压片等工序洁净区的气压控制，应符合第8.5.1条要求。 第2．2．6条洁净室和洁净区应根据生产要求提供足够的照度。主要工作室一般照明的照度值不宜低于300LX；辅助工作室、走廊、气闸室、人员净化和物料净化用室可低于300LX，但不宜低于150LX。对照度要求高的部位可增加局部照明。 CFD simulation in Laval nozzle SIAE 090441313 Abstract We aim to simulate the quasi one dimension flow in the Laval nozzle based on CFD computation in this paper .We consider the change of the temperature ,the pressure ,the density and the speed of the flow to study the flow.The analytic solution of the flow in the Laval nozzle is provided when the input velocity is supersonic.We use the Mac-Cormack Explicit Difference Scheme to slove the question. Key words :Laval nozzle ,CFD,throat narrow. Contents Abstract .................................................. . (1) Introduction .............................................. .. (2) Simulation of one-dimensional steady flow (3) Basis equations ................................................. (3) Dimensionless .......................................... . (10) Mac -Cormack Explicit Difference Scheme (11) Boundary conditions ................................................ (13) Reference .............................................. (13) Annex .................................................. .. (14) Introduction Laval nozzle is the most commonly used components of rocket engines and aero-engine, constituted by two tapered tube, one shrink tube, another expansion tube. Laval nozzle is an important part of the thrust chamber. The first half of the nozzle from large to small contraction to a narrow throat to the middle. Narrow throat and then expand 1 总则 1.0.1为在医药工业洁浄厂房设计中贯彻执行国家有关方针政策,做到技术先进、安全可靠、确保质量、节能环保,制定本标准 1.0.2本标准适用于新建、扩建和改建的医药工业洁净厂房设计。生物制品、毒性药品、精神药品、麻醉药品以及放射性药品的生产和质量检验设施除应执行本标准外,尚应符合国家有关的监管规定。 1.0.3医药工业洁净厂房的设计应为施工安装、系统设施验证、维护管理、检修测试和安全运行创造必要的条件 1.0.4医药工业洁净厂房的设计除应符合本标准外,尚应符合国家现行有关标准规范的规定。 2术语 2.0.1医药洁净室pharmaceutical clean room 空气悬浮粒子和微生物浓度,以及温度、湿度、压力等参数受控的医药生产房间或限定的空间。 2.0.2医药工业洁净厂房pharmaceutical industry clean room 包含医药洁净室的用于药品生产及质量控制的建筑物 2.0.3人员净化用室room forcleaning personne 人员在进人医药洁净室之前按一定程序进行净化的房间 2.0.4物料净化用室room forcleaning materia 物料在进入医药洁净室之前按一定程序进行净化的房间 2.0.5受控环境controlled environment 以规定方法对污染源进行控制的特定区域 2.0.6悬浮粒子airborne particles 用于空气洁净度分级的空气悬浮粒子尺寸范围在0.1um~1000um 的固体和液体粒子。 2.0.7微生物microorganIsms 能够复制或传递基因物质的细菌或非细菌的微小生物实体 2.0.8含尘浓度particle concentration 单位体积空气中悬浮粒子的数量 CFD仿真验证及有效性指南 摘要 本文提出评估CFD建模和仿真可信性的指导方法。评估可信度的两个主要原则是：验证和有效。验证，即确定计算模拟是否准确表现概念模型的过程，但不要求仿真和现实世界相关联。有效，即确定计算模拟是否表现真实世界的过程。本文定义一些重要术语，讨论基本概念，并指定进行CFD仿真验证和有效的一般程序。本文目的在于提供验证和有效的重要问题和概念的基础，因为一些尚未解决的重要问题，本文不建议作为该领域的标准。希望该指南通过建立验证和有效的共同术语和方法，以助于CFD仿真的研究、发展和使用。这些术语和方法也可用于其他工程和科学学科。 前言 现在，使用计算机模拟流体的流动过程，用于设计，研究和工程系统的运行，并确定这些系统在不同工况下的性能。CFD模拟也用于提高对流体物理和化学性质的理解，如湍流和燃烧，有助于天气预报和海洋。虽然CFD模拟广泛用于工业、政府和学术界，但目前评估其可信度的方法还很少。这些指导原则基于以下概念，没有适用于所有CFD模拟的固定的可信度和精确度。模拟所需的精确度取决于模拟的目的。 建立可信度的两个主要原则是验证和有效（V&V）。这里定义，验证即确定模型能准确表现设计者概念模型的描述和模型解决方案的过程，有效即确定预期模型对现实世界表现的准确度的过程。该定义表明，V&V的定义还在变动，还没有一个明确的最终定义。通常完成或充分由实际问题决定，如预算限制和模型的预期用途。复合建模和计算模拟没有任何包括准确性的证明，如在数学分析方面的发展。V&V的定义也强调准确度的评价，一般在验证过程中，准确度以对简化模型问题的基准解决方法符合性确定；有效性时，准确度以对实验数据即现实的符合性确定。 通常，不确定性和误差可视为与建模和仿真准确度相关的正常损失。不确定性，即在任一建模过程中由于缺乏知识导致的潜在缺陷。知识缺乏通常是由对物理特性或参数的不完全了解造成的，如对涡轮叶片表面粗糙度分布的不充分描述。知识缺乏的另一个原因是物理过程的复杂性，如湍流燃烧。误差即在建模和 2006年用户年会论文 基于ANSYS流体动力学的车流量仿真分析1 [刘长虹，郑杰,朱晓华，张海波，黄虎，陈力华] [上海工程技术大学汽车工程学院，上海，201600] [ 摘要 ] 将交通流比拟为管道流体模型并且利用有限元分析软件ANSYS中的FLOTRAN CFD流体分析模块对隧道口交通流进行比拟及仿真，得出相应交通流量模型和车辆流动模拟图。并对不同车速下 交叉道口的通行能力进行模拟，确定出最佳车速比。且对不同入口形状进行车流通畅度的 ANSYA软件比较模拟，通过模拟直观的展示出不同道路入口形状对车流和道路的影响。最后对 高峰路段路口设计提出有关建议。 [ 关键词]交通流，交通流模型，ANSYS，模拟 Simulating to Traffic Flux By the ANSYS Fluid Dynamic Analysis [Liu Changhong, Zheng Jie, Zhu Xiaohua, Zhang Haibo, Huang Hu, Chen Lihua] [Automobile College Shanghai University of Engineering Science, Shanghai 201600] [Abstract ] Firstly, based on the fluid dynamic mechanics of channel, a traffic flow model is built. Secondly, the traffic flow model on cross road is simulated with the finite element method software (ANSYS). Then according to the calculating results, the simulating traffic ability at the entrance of the roadl in different speed and the different entrance figures are calculated directly. Finally, some suggestions of designing the heavy road are given. [ Keyword ] traffic flow, traffic flow simulation, ANSYS, Simulation. 1.前言 当前，社会经济的迅速发展与交通建设的相对滞后，已经构成非常突出的世界性矛盾，在发展中国家尤其突出。在我国许多大城市中，交通堵塞，事故频繁，成了众所周知的“都市顽症”。以上海市为例，上世纪九十年代的资料表明，在交通高峰期，市中心机动车平均车速不到15km/h，最低的车速仅仅为4km/h，即低于正常的步行速度。解决这个矛盾的一个重要办法是大力进行市政交通建设，实现交通的立体化，现代化。同时还要保证建设道路的合理性。交通流理论是解决这类方法的一种理论方法[1,2]，其中有根据流体动力学理 1上海市教委基金项目(041NE31)和上海市科委基金项目(04QMX1452)资助 医药工业洁净厂房设计规 范 Jenny was compiled in January 2021 医药工业洁净厂房设计规范 第一章总则 第条为了贯彻执行国家《药品生产质量管理规范》（以下简称ＧＭＰ），提出符合ＧＭＰ要求的生产厂房、设施及设备的设计要求，特制订本规范。 第条本规范适用于新建、改建和扩建的医药制剂、原料药和药用辅料的精制、干燥、包装工序，直接接触药品的药用包装材料、无菌医疗器械等医药工业洁净厂房的设计。 第条医药工业洁净厂房诉设计必须贯彻国家有关方针、政策。做到技术先进、确保质量、安全实用、经济合理，符合节约能源和保护环境的要求。 第条医药工业洁净厂房的设计，既要满足当前产品生产的工艺要求，也应适当考虑今后生产发展和工艺改进的需要。 第条在利用原有建筑和设施进行洁净技术改造时，可根据生产工艺要求，从实际出发，充分利用现有的技术设施，符合因地制宜的原则。 第条医药工业洁净厂房的设计应为施工安装、维护、管理、检修、测试和安全运行创造必要的条件。 第条医药工业洁净厂房的设计除应执行本规范外，还应符合现行的国家标准、规范和规定的有关要求。 第二章生产区域的环境参数 第一节一般规定 第条为了保证医药产品生产质量，防止生产环境对产品的污染，生产区 注3：对于空气洁净度为100级的洁净室，室内大于等于5μm尘粒的计数，应进行多次采样，当其多次出现时，方可认为该测试数值是可靠的。 第2．2．2条药品生产有关工序和环境区域的空气洁净度等级按国家CMP等有关规定确定。 第2．2．3条洁净室内的温度和湿度应符合下列规定： 一、生产工艺对温度和湿度无特殊要求时，以穿着洁净工作服不产生不舒服感为宜。空气洁净度100级、10000级区域一般控制温度为20～24℃，相对湿度为45～60%。100000级区域一般控制温度为18～28℃，相对湿度为50～65%。 二、生产工艺对温度和湿度有特殊要求时，应根据工艺要求确定。 第2．2．4条洁净室内应保持一定的新鲜空气量，其数值应取下列风量中的最大值： 一、非单向流洁净室总送风量的10～30%，单向流洁净室总送风量的2～4%； 二、补偿室内排风和保持室内正压值所需的新鲜空气量； 三、保证室内每人每小时的新鲜空气量不小于40m3。 第2．2．5条洁净室必须维持一定的正压。不同空气洁净度的洁净区之间以及洁净区与非洁净区之间的静压差不应小于5Pa,洁净区与室外的静压差不应小于10Pa。 青霉素等特殊药物生产洁净区，固体口服制剂配料、制粒、压片等工序洁净区的气压控制，应符合第条要求。 医药工业洁净厂房设计规范 GMP—97 目录 医药工业洁净厂房设计规范 (1) 第一章总则 (2) 第二章生产区域的环境参数 (2) 第一节一般规定 (2) 第二节环境参数的设计要求 (2) 第三章厂址选择和总平面布置 (3) 第一节厂址选择 (3) 第二节总平面布置 (4) 第四章工艺设计 (4) 第一节工艺布局 (4) 第二节人员净化 (5) 第三节物料净化 (6) 第五章设备 (6) 第六章工艺管道 (8) 第一节一般规定 (8) 第二节管道材料、阀门和附件 (8) 第三节管道的安装、保温 (8) 第四节安全 (9) 第七章建筑 (9) 第一节一般规定 (9) 第二节防火和疏散 (9) 第三节室内装修 (10) 第八章空气净化 (11) 第一节一般规定 (11) 第二节净化空气调节系统 (11) 第三节气流组织 (12) 第四节风管和附件 (13) 第五节青霉素等药物生产洁净室的特殊要求 (13) 第九章给水排水 (14) 第一节一般规定 (14) 第二节给水 (14) 第三节排水 (14) 第四节工艺用水 (14) 第五节消防设施 (15) 第十章电气 (16) 第一节配电 (16) 第二节照明 (16) 第三节其它电气 (17) 附录一名词解释 (18) 附录二本规范用词说明 (19) 第一章总则 第1.0.1条为了贯彻执行国家《药品生产质量管理规范》（以下简称ＧＭＰ），提出符合ＧＭＰ要求的生产厂房、设施及设备的设计要求，特制订本规范。 第1.0.2条本规范适用于新建、改建和扩建的医药制剂、原料药和药用辅料的精制、干燥、包装工序，直接接触药品的药用包装材料、无菌医疗器械等医药工业洁净厂房的设计。 第1.0.3条医药工业洁净厂房诉设计必须贯彻国家有关方针、政策。做到技术先进、确保质量、安全实用、经济合理，符合节约能源和保护环境的要求。 第1.0.4条医药工业洁净厂房的设计，既要满足当前产品生产的工艺要求，也应适当考虑今后生产发展和工艺改进的需要。 第1.0.5条在利用原有建筑和设施进行洁净技术改造时，可根据生产工艺要求，从实际出发，充分利用现有的技术设施，符合因地制宜的原则。 第1.0.6条医药工业洁净厂房的设计应为施工安装、维护、管理、检修、测试和安全运行创造必要的条件。 第1.0.7条医药工业洁净厂房的设计除应执行本规范外，还应符合现行的国家标准、规范和规定的有关要求。 第二章生产区域的环境参数 第一节一般规定 第2.1.1条为了保证医药产品生产质量，防止生产环境对产品的污染，生产区域必须满足规定的环境参数标准。 第2.1.2条医药工业洁净室和洁净区应以微粒和微生物为主要控制对象，同时还应对其环境的温度、湿度、新鲜空气量、状差、照度、噪场院等参数作出必要的规定。 第2.1.3条环境空气中不应有不愉快气味以及有碍药品质量和人体健康的气体。 第二节环境参数的设计要求 第2.2.1条医药工业洁净厂房空气洁净度按表2.2.1规定分为三个等级。 医药工业洁净厂房空气洁净度等级表2.2.1 国家医药管理局医药工业洁净厂房设计规范 默认分类 2008-07-13 12:25 阅读1075 评论3 字号: 大中小 主编部门:国家医药管理局上海医药设计院 批准部门:国家医药管理局 施行日期:１９９７年１月１日 编制说明 为在我国医药行业深入实施ＧＭＰ,适应医药工业洁净厂房建设的需要,国家医药局推行ＧＭＰ、ＧＳＰ委员会设计规范专业组决定组织编写《医药工业洁净厂房设计规范》。 本规范由上海医药设计院主编,缪德华同志执笔,武汉医药设计院、重庆医药设计院等单位参与。在编写过程中广泛眚注医药行业内有关方面意见,并先后数次组织医药设计单位与大中型骨干企业的专家进行了认真的讲座修改,由局推行ＧＭＰ、ＧＳＰ委员会寓言并原则通过。之后,局综合经济司(原局计划)就规范主要内容向卫生部药政局、药品监督办公室的领导、专家征询了意见并得到了她们的理解与支持。在此基础上,局ＧＭＰ设计规范专业组对本规范作了修改定稿。 本规范编制工作结合国内外ＧＭＰ的进展与医药工业洁净厂房建设、使用的实践经验,提出了我国医药工业洁净厂房设计的基本要求。各单位在新建、改建与扩建的工程设计中遵照执行。并认真总结经验,提出修改意见,以使本规范日臻完善。 国家医药管理局 第一章总则 第1、0、1条为了贯彻执行国家《药品生产质量管理规范》(以下简称ＧＭＰ),提出符合ＧＭＰ要求的生产厂房、设施及设备的设计要求,特制订本规范。 第1、0、2条本规范适用于新建、改建与扩建的医药制剂、原料药与药用辅料的精制、干燥、包装工序,直接接触药品的药用包装材料、无菌医疗器械等医药工业洁净厂房的设计。 第1、0、3条医药工业洁净厂房诉设计必须贯彻国家有关方针、政策。做到技术先进、确保质量、安全实用、经济合理,符合节约能源与保护环境的要求。 第1、0、4条医药工业洁净厂房的设计,既要满足当前产品生产的工艺要求,也应适当考虑今后生产发展与工艺改进的需要。 第1、0、5条在利用原有建筑与设施进行洁净技术改造时,可根据生产工艺要求,从实际出 医药工业洁净厂房设计规范 GB/T14294-1993 主编部门：国家医药管理局上海医药设计院 批准部门：国家医药管理局 施行日期：１９９７年１月１日 编制说明 为在我国医药行业深入实施ＧＭＰ，适应医药工业洁净厂房建设的需要，国家医药局推行ＧＭＰ.ＧＳＰ委员会设计规范专业组决定组织编写《医药工业洁净厂房设计规范》。 本规范由上海医药设计院主编，缪德华同志执笔，武汉医药设计院、重庆医药设计院等单位参与。在编写过程中广泛眚注医药行业内有关方面意见，并先后数次组织医药设计单位和大中型骨干企业的专家进行了认真的讲座修改，由局推行ＧＭＰ.ＧＳＰ委员会寓言并原则通过。之后，局综合经济司（原局计划）就规范主要内容向卫生部药政局、药品监督办公室的领导、专家征询了意见并得到了他们的理解和支持。在此基础上，局ＧＭＰ设计规范专业组对本规范作了修改定稿。 本规范编制工作结合国内外ＧＭＰ的进展和医药工业洁净厂房建设、使用的实践经验，提出了我国医药工业洁净厂房设计的基本要求。各单位在新建、改建和扩建的工程设计中遵照执行。并认真总结经验，提出修改意见，以使本规范日臻完善。 国家医药管理局 第一章总则 第1.0.1条为了贯彻执行国家《药品生产质量管理规范》（以下简称ＧＭＰ），提出符合ＧＭＰ要求的生产厂房、设施及设备的设计要求，特制订本规范。 第1.0.2条本规范适用于新建、改建和扩建的医药制剂、原料药和药用辅料的精制、干燥、包装工序，直接接触药品的药用包装材料、无菌医疗器械等医药工业洁净厂房的设计。 第1.0.3条医药工业洁净厂房诉设计必须贯彻国家有关方针、政策。做到技术先进、确保质量、安全实用、经济合理，符合节约能源和保护环境的要求。 第1.0.4条医药工业洁净厂房的设计，既要满足当前产品生产的工艺要求，也应适当考虑今后生产发展和工艺改进的需要。 第1.0.5条在利用原有建筑和设施进行洁净技术改造时，可根据生产工艺要求，从实际出发，充分利用现有的技术设施，符合因地制宜的原则。 第1.0.6条医药工业洁净厂房的设计应为施工安装、维护、管理、检修、测试和安全运行创造必要的条件。 第1.0.7条医药工业洁净厂房的设计除应执行本规范外，还应符合现行的国家标准、规范和规定的有关要求。 第二章生产区域的环境参数 第一节一般规定 第2.1.1条为了保证医药产品生产质量，防止生产环境对产品的污染，生产区域必须满足规定的环境参数标准。 第2.1.2条医药工业洁净室和洁净区应以微粒和微生物为主要控制对象，同时还应对其环境的温度、湿度、新鲜空气量、状差、照度、噪场院等参数作出必要的规定。 第2.1.3条环境空气中不应有不愉快气味以及有碍药品质量和人体健康的气体。 药厂的建筑要求 主编部门：国家医药管理局上海医药设计院 批准部门：国家医药管理局 施行日期：１９９７年１月１日 编制说明 为在我国医药行业深入实施ＧＭＰ，适应医药工业洁净厂房建设的需要，国家医药局推行ＧＭＰ.ＧＳＰ委员会设计规范专业组决定组织编写《医药工业洁净厂房设计规范》。 本规范由上海医药设计院主编，缪德华同志执笔，武汉医药设计院、重庆医药设计院等单位参与。在编写过程中广泛眚注医药行业内有关方面意见，并先后数次组织医药设计单位和大中型骨干企业的专家进行了认真的讲座修改，由局推行ＧＭＰ.ＧＳＰ委员会寓言并原则通过。之后，局综合经济司（原局计划）就规范主要内容向卫生部药政局、药品监督办公室的领导、专家征询了意见并得到了他们的理解和支持。在此基础上，局ＧＭＰ设计规范专业组对本规范作了修改定稿。 本规范编制工作结合国内外ＧＭＰ的进展和医药工业洁净厂房建设、使用的实践经验，提出了我国医药工业洁净厂房设计的基本要求。各单位在新建、改建和扩建的工程设计中遵照执行。并认真总结经验，提出修改意见，以使本规范日臻完善。 ?国家医药管理局 ?１９９６北京 目录 第一章总则 第二章生产区域的环境参数 第一节一般规定 第二节环境参数的设计要求 第三章厂址选择和总平面布置 第一节厂址选择 第二节总平面布置 第四章工艺设计 第一节工艺布局 第二节人员净化 第三节物料净化 第五章设备 第六章工艺管道 第一节一般规定 第二节管道材料、阀门和附件 第三节管道的安装、保温 第四节安全 第六章建筑 第一节一般规定 第二节防火和疏散 第三节室内装修 第七章建筑 1. 一般规定 2. 防火和疏散 第三节室内装修 第八章空气净化 第一节一般规定 第二节净化空气调节系统 第三节气流组织 第四节风管和附件 第五节青霉素等药物生产洁净室的特殊要求 第九章给水排水 第一节一般规定 第二节给水 第三节排水 第四节工艺用水 第五节消防设施 第十章电气 第一节配电 第二节照明 第三节其它电气 附录一名词解释 附录二本规范用词说明 第一章总则 第1.0.1条为了贯彻执行国家《药品生产质量管理规范》（以下简称ＧＭＰ），提出符合ＧＭＰ要求的生产厂房、设施及设备的设计要 ANSYS对航空工业解决方案（三）航空发动机仿真方案_2 发表时间：2008-10-23 作者: 安世亚太来源: 安世亚太 关键字: 航空航天 CAE 仿真解决方案 ANSYS 安世亚太 第三章航空发动机仿真方案航空发动机行业概况航空发动机研制中的典型CAE问题航空发动机结构力学计算需求及ANSYS实现航空发动机流体力学和温度场的计算需求及ANSYS实现航空发动机电磁场计算需求及ANSYS实现航空发动机耦合场计算需求及ANSYS实现航空发动机关键零部件的设计分析流程简要说明 4航空发动机流体力学和温度场的计算需求及ANSYS实现 航空燃气涡轮发动机内的流场很复杂，不仅动静流场同时存在，同时还伴有多相流、传热、燃烧等现象，即使从物理上进行很大的简化，模型最后仍然是三维、有粘、非定常的可压流动。航空发动机流场数值计算的发展经历了S2流面法、基于一元管道的流线曲率法、有限差分方法求解非正交曲线坐标系中的S1、S2流面基本方程、有限差分、有限体积和有限差分与流线曲率混合的方法对S1流面跨音速流场的计算，而现在由S1与S2流面相互迭代形成的准三元和全三元计算也发展起来了。现在的采用有限体积法求解NS方程全三维流场计算已经广泛采用，航空发动机的流场数值计算已趋于成熟，可以充分考虑旋转流动、转静干涉问题、多相流、燃烧、亚超跨音速等复杂现象。而且现在求解的规模也不断扩大，利用并行等成熟的CFD技术可以计算达几千万甚至上亿的计算网格。因此结果也更为真实有效。 ANSYSCFX凭借TASCFLOW在叶轮机旋转流动的传统优势，结合更为先进的网格处理技术和高效的求解器，更适合航空发动机流动的复杂性，求解问题的规模和计算精度大大提高，一直处于航空发动机流动模拟的最前沿。 洁净厂房洁净区设计规 范 Document serial number【KKGB-LBS98YT-BS8CB-BSUT-BST108】 国家医药管理局医药工业洁净厂房设计规范主编部门：国家医药管理局上海医药设计院 批准部门：国家医药管理局 施行日期：１９９７年１月１日 编制说明： 为在我国医药行业深入实施ＧＭＰ，适应医药工业洁净厂房建设的需要，国家医药局推行ＧＭＰ.ＧＳＰ委员会设计规范专业组决定组织编写《医药工业洁净厂房设计规范》。 本规范由上海医药设计院主编，缪德华同志执笔，武汉医药设计院、重庆医药设计院等单位参与。在编写过程中广泛眚注医药行业内有关方面意见，并先后数次组织医药设计单位和大中型骨干企业的专家进行了认真的讲座修改，由局推行ＧＭＰ.ＧＳＰ委员会寓言并原则通过。之后，局综合经济司（原局计划）就规范主要内容向卫生部药政局、药品监督办公室的领导、专家征询了意见并得到了他们的理解和支持。在此基础上，局ＧＭＰ设计规范专业组对本规范作了修改定稿。 本规范编制工作结合国内外ＧＭＰ的进展和医药工业洁净厂房建设、使用的实践经验，提出了我国医药工业洁净厂房设计的基本要求。各单位在新建、改建和扩建的工程设计中遵照执行。并认真总结经验，提出修改意见，以使本规范日臻完善。 国家医药管理局 第一章总则 为了贯彻执行国家《药品生产质量管理规范》（以下简称ＧＭＰ），提出符合ＧＭＰ要求的生产厂房、设施及设备的设计要求，特制订本规范。 本规范适用于新建、改建和扩建的医药制剂、原料药和药用辅料的精制、干燥、包装工序，直接接触药品的药用包装材料、无菌医疗器械等医药工业洁净厂房的设计。 医药工业洁净厂房诉设计必须贯彻国家有关方针、政策。做到技术先进、确保质量、安全实用、经济合理，符合节约能源和保护环境的要求。 CFD仿真技术在航空发动机中的应用 摘要：随着科学技术的发展，航空航天和空间技术有了飞跃的发展，在这些飞 跃的发展技术中主要的技术就是CAE技术。航空工业可以说是CAE技术发展的摇篮，各种CAE技术正是在以航空工业为主的实际工业应用的推动下在不到半个世 纪时间里迅猛发展起来的。以ANSYS、LS-DYNA、Nastran、CFX、Fluent等为代表 的高端CAE软件早已活跃在全球航空工业中。 关键词：CFD仿真技术；航空发动机；应用 1 引言 目前国际知名企业的航空发动机研制周期从过去的10～15年缩短到6～8年 甚至4～5年，试验机也从过去的40～50台减少到10台左右。在发达国家的航 空企业里CAE已经作为产品研发设计与制造流程中不可逾越的一种强制性的工艺 规范加以实施，在生产实践作为必备工具普遍应用。 2、CFD技术国内外使用状况简介 CFD作为CAE技术的一种，已经越来越多的被国内外航空企业广泛的得以应用。第一个商用CFD软件包FLUENT，由与美国空军合作的流体技术服务公司Creare公司于1983年推出的。商业CFD软件的开发及应用，加速了航空工业的 发展，使得基于虚拟样机仿真的现代设计方法成为了可能。以波音公司航空研发 发展历史为例，不难发现，波音公司先后采用了经典的实验测试方法、半经验的 方法、空气动力学的计算、政府内部及企业的CFD代码及广泛的采用CFD商业代码。在波音公司2005年的软件应用报告中明确指明，在1998至2005年内，其 公司每年数值仿真成果的增加量都接近84%左右，采用CAE/CFD的速度超过了工 业的成长速度，CFD技术已经成为其设计的主要手段之一。另外从美国软件公司ANSYS公司的销售业绩报告上显示，航空工业上的应用产值是其公司的主要收益 来源之一。 CFD软件正以其强大的优势在研发中发挥的巨大的作用，例如在NISA的报告 中提到，原本需要7年完成的维吉尼亚级潜水艇的设计，通过CFD技术的应用， 5年就顺利完成；而预计需要11年完成的B-2轰炸机的飞行测试，则在短短的4 年内就通过了测试。 国内在CFD技术上的应用一般，特别是在航空发动方面的使用上，起步与国 外相比较晚，力度上也相差较多。 3、CFD技术的应用 目前在航空发动机的实际应用中是最广泛的一款CFD商业软件是ANSYS旗下 的商业软件FLUENT，其不仅容易使用，而且其准确性及行业的广泛性都是其它商业软件所不能比拟的。CFD软件的使用已经遍及了航空发动机的各个部分的研究，接下来本文通过对其它文献的分析逐一介绍CFD在航空发动机中的使用。 3.1 CFD技术在压缩机、涡轮方面的应用 气动稳定性的设计是当代航空发动机发展研制过程中的重要技术问题之一。 在航空发动机中，对气流最敏感的部件是风扇、压气机和涡轮。在以上3个部件中，CFD的主要应用集中在对压气机和涡轮效率分析上，多级压气机/涡轮最主要 的气动问题就是各级流动是否匹配，总的效率是否达到设计要求。在涡轮方面，CFD不仅可以计算涡轮效率，而且对涡轮叶片的冷却效果分析有着重要的应用。 仅供参考[整理] 安全管理文书 医药工业洁净厂房的消防设计 日期：__________________ 单位：__________________ 第1 页共6 页 医药工业洁净厂房的消防设计 摘要：介绍了医药工业洁净厂房的特点，分析了其火灾危险性及存在的问题，提出了在消防设计上应注意的事项，探讨 关键词：医药洁净厂房；火灾危险；消防设计 目前，我国正在推行药品GMP(药品生产管理规范)认证，此项认证对厂房洁净度的要求应达标。而医药工业生产工艺复杂，生产过程中使用多种化学危险物品，火灾危险性较大，有的药品价格昂贵，一旦发生火灾，损失严重。医药洁净厂房的设计依据是GB50073—2001《洁净厂房设计规范》，并参照执行国家医药管理局发布的《医药工业洁净厂房设计规范》，笔者就此类厂房的火灾危险性、消防设计及审核应注意的问题做一探讨。医药工业洁净厂房的火灾危险性大 (1)医药工业洁净厂房经常使用各种易燃易爆化学危险物品，且本身化学反应也有燃烧爆炸危险，如使用环氧乙烷、酒精、煤气活性镍、钯炭等极易引起燃烧的物品，制剂工艺灭菌工序中的火焰法和环氧乙烷法的火灾危险性都较大。 (2)建筑或装修材料采用易燃材料。由于洁净厂房需要特殊，加之很多新型复合材料的使用，而建设单位缺乏消防知识，有些选用了有机复合材料，或彩钢板加泡沫，增加了火灾荷载，这些材料燃烧后，又会产生大量的有毒气体。 (3)医药洁净厂房由于洁净无菌的工艺要求，密封性好，但易造成发生火灾后，有毒高温烟气不易及时扩散，甚至会使轰燃提前发生。 (4)人员人口不能满足疏散的要求。医药洁净厂房必须经过清洗、男(女)更衣、消毒等隔离间方可进入，且由于洁净无菌的要求，该疏散门不能采用向疏散方向开启的门，火灾时从人口疏散极为复杂和困难。 第 2 页共 6 页 洁净厂房设计规范（GB50073-2013） 4. 1 洁净厂房位置选择和总平面布置 4.1. 1 洁净厂房位置选择应符合下列规定，并经技术经济方案比较后确定：1）应在大气含尘和有害气体浓度较低、自然环境较好的 区域。 2)应远离铁路、码头、飞机场、交通要道以及散发大量粉尘和有害气体的工厂、贮仓、堆场等有严重空气污染、振动或噪声干扰的区域。当不能远离严重空气污染源时，应位于最大频率风向上风侧，或全年最小频率风向下风侧。 3)应布置在厂区内环境清洁，人流、物流不穿越或少穿越的 地段。 4.1.2对于兼有微振控制要求的洁净厂房的位置选择，应实际测定周围现有振源的振动影响，并应与精密设备、精密仪器仪表容许振动值分析比较后确定。 4.1.3洁净厂房新风口与交通干道边沿的最近距离宜大于 50m。 4.1.4洁净厂房周围宜设置环形消防车道，也可沿厂房的两个长边设置消防车道。 4.1.5洁净厂房周围的道路面层应选用整体性能好、发尘少的材 料。 4.1.6洁净厂房周围应进行绿化。可铺植草坪，不应种植对生产有害的植物，并不得妨碍消防作业。 4.2 工艺平面布置和设计综合协调 4.2.1工艺平面布置应符合下列规定： 1)工艺平面布置应合理、紧凑。洁净室或洁净区内应只布置必要的工艺设备，以及有空气洁净度等级要求的工序和工作室。 2) 在满足生产工艺和噪声要求的前提下，对空气洁净度要求 严格的洁净室或洁净区宜靠近空气调节机房，空气洁净度等级相同的工序和工作室宜集中布置。 3) 洁净室内对空气洁净度要求严格的工序应布置在上风侧， 易产生污染的工艺设备应布置在靠近回风口位置。 4) 应考虑大型设备安装和维修的运输路线，并预留设备安装口和检修口。 5) 不同空气洁净度等级房间之间联系频繁时，宜设有防止污 染的措施，如气闸室、传递窗等。 6) 应设置单独的物料入口，物料传递路线应最短，物料进入洁净室（区）之前应进行清洁处理。 4.2.2洁净厂房的平面和空间设计应满足生产工艺和空气洁净度等级要求。洁净区、人员净化、物料净化和其他辅助用房应分区布置,并应与生产操作、工艺设备安装和维修、管线布置、气流流型以及净化空调系统等各种技术设施进行综合协调。 4.2.3洁净厂房内应少设隔间，但在下列情况下应进行分隔： 1)按生产的火灾危险性分类，甲、乙类与非甲、乙类相邻的生产区段之间，或有防火分隔要求者。 2) 按产品生产工艺需要有分憬要求时。 CFD总结一 CFD是英文computational Fluid Dynamics（计算流体力学）的简称。它是伴随着计算机技术和数值计算技术的发展而发展的。简单地说，CFD相当于虚拟的在计算机内做实验，用它模拟仿真实际流体的流动情况。而其基本的原理是数值求解控制流体的微分方程，得出流体流动的流场在连续区域上的离散分布，从而近似模拟流体流动的情况。即CFD=流体力学+热学+数值分析+计算机科学。 流体力学就不用多说了，很多专业都要用到，主要的概念有层流和湍流，牛顿流体和非牛顿流体等等。热学包括热力学和传热学。数值分析就是如何用计算机解人工很难完成的计算，如何处理无解析解得方程。计算机科学主要是计算机语言，如c、fortran）还包括一些图形处理技术，如在后处理，为了使用户对结论有一个很直观的认识，就需要若干图表。以下就对经常在CFD使用的软件做简单的介绍。 一、CFD的结构： 1、提出问题——流动性质（内流、外流；层流、湍流；单相流、多项流；可压、不可压……），流体属性（牛顿流体：液体、单组分气体、多组分气体、化学反应气体；非牛顿流体） 2、分析问题——建模——N-S方程（连续性假设），Boltzmann方程（稀薄气体流动），各类本构方程与封闭模型。 3、解决问题——差分格式的构造/选择，程序的具体编写/软件的选用，后处理的完成。 4、成果说明——形成文字，提交报告，赚取应得的回报。 二、CFD实现过程： （一）建模——物理空间到计算空间的映射。 主要软件： 二维： AutoCAD： 大家不要小看它，非常有用。一般的网格生成软件建模都是它这个思路，很少有参数化建模的。相比之下 AutoCAD的优点在于精度高，草图处理灵活。可以这样说，任何一个网格生成软件自带的建模工具都是非参数化的，而对于非参数化建模来说，AutoCAD应该说是最好的，毕竟它发展了很多很多年！ 三维： 1、CATIA： 航空航天界CAD的老大，法国人的东西，NB，实体建模厉害，曲面建模独步武林。本身可以生成有限元网格，前几天又发布了支持ICEM-CFD的插件ICEM-CFD CAA V5。有了它和ICEM-CFD，可以做任何建模与网格划分！ 2、UG： 软件本身不错，大公司用得也多，可是就这么打市场，早晚是走下坡路。按CAD建模的功能来说它排不上第一，也不能屈居第二，尤其是加上了I－DEAS更是如虎添翼。现在关键是看市场了。 3、Solidworks： Solidworks讲的是实用主义，中端CAD软件它功能最强，Solidedge功能是不比它差，但是Solidworks的合作伙伴可能是SE的十几倍，接口也比SE多很多，相比之下Solidworks是最佳选择。Autodesk Inventor也只能算是中端软件，目前说来，我是处于观望态度，看发展再决定。总之，Solidworks目前的发展如日中天，合作伙伴多如牛毛。用起来极其顺手。这里极力向大家推荐的是ICEM-CFD DCI FOR Solidworks！有了这个东西画个全机网格也很容易了。第七 章 CFD仿真模拟
医药工业洁净厂房设计要求规范
一维CFD模拟仿真设计
洁净厂房设计规范2019
CFD仿真验证及有效性指南
车流量仿真分析-Flotran CFD
医药工业洁净厂房设计规范
医药工业洁净厂房设计规范GMP-97
医药工业洁净厂房设计规范
医药行业洁净车间设计规范
医药厂房建筑要求
CFD案例5-发动机仿真
洁净厂房洁净区设计规范
CFD仿真技术在航空发动机中的应用
医药工业洁净厂房的消防设计
洁净厂房设计规范(GB50073-2013)
传热模拟CFD 总结
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