Home

User`s Manual to SPRESSO - Stanford Microfluidics Laboratory

1. 1 7e 008 2 756 0 07 Analyte Analyte2 1 6e 008 2 756 0 03 Analyte Analyte3 1 5e 008 4 756 0 05 Analyte Analyte4 1 4e 008 4 756 0 01 Analyte Analyte5 1 3e 008 4 756 0 06 Analyte The first entry in every row of InputTable is the name of chemical species The species names are shown in GUI to aid data visualization but they do not affect the actual simulation The second entry in each row should be in the following format valence mobility acid dissociation constant Multivalent species can be handled using the following format Parse cee The third entry in each row of the Input Tabl1e is the species concentration in molar units The last entry of each row describes the initial concentration distribution of species The available options for concentration distributions are LE TE Background and Analyte e GUI InputTable can be generated using the GUI by either manually inputting the table rows in the above mentioned format or by using Add and Remove buttons to insert required species from the chemical database 26 cMat 1 etc e Description Initial concentration distribution of all species constructed using the values defined in Input Table and vectors discussed in 21 e Usage Use default values determined by the GUI Unless customized species distributions are required we suggest not editing these
2. platform Note that for running the executable version it is necessary to install the Matlab Component Runtime MCR library MCR is available for free download on the SPRESSO download page Whenever possible we suggest running the code using the source code so as to avoid machine and operating system specific issues 2 Introduction to GUI and input variables As described in Section 1 running SPRESSO causes a GUI to appear on the computer screen The GUI can be used to create and run input files and visualize simulation results in real time We provide several example cases in the Input Files directory to help users familiarize with GUI and the input parameters Throughout this manual we will refer to a model ITP problem described in the Casel_ITPDemo m file in the Input Files directory To load the input file click Load file on GUI and select the above mentioned input file Loading the input file populates various fields in the GUI Figure 1 shows screenshot of the GUI after loading Casel_ ITPDemo m input file The input file can also be viewed by opening it in the MATLAB editor Below we discuss various simulation parameters in a typical input file and the corresponding fields in GUL 1 lonicEffectFlag e Description Determines whether ionic strength corrections on electrophoretic mobility and ionic activity are applied or not e Usage Takes on values 0 ionic strength corrections disabled or 1 ionic strength corrections enable
3. using manually customized input files the GUI plots correct concentration profiles upon starting the simulation 17
4. 2 756 0 0500 LE a 2 ACRYLIC ACID 1 4 27e 08 4 258 injection point 2 ITE 1 25e 009 4 756 0 0200 TE 3 ADIPIC ACID 1 2 46e 08 4 43 25 24e 08 5 277 mn 3 IBG 1 20e 009 6 756 0 1300 Backgrou 5 4 ALLYLACETIC ACID 1 3 39e 08 4 674 22 4 Analytel 1 7e 008 2 756 0 0700 Analyte 5 o AMINOBENZOIC ACID 1 3 16e 08 2 108 1 3 16e 08 4 939 Injection width 5 Analyte 1 6e 008 2 756 0 0300 Analyte 6 p AMINOBENZOIC ACID 13 16e 08 2 413 1 3 16e 08 4 853 im 6 iAnalyte3 1 5e 008 4 7561 0 0500 Analyte im D 22 lt m Figure 2 Screenshot of SPRESSO GUI showing typical parameters for performing fast and approximate ITP simulations discussed in Section 3 Such simulations yield dispersed zone boundaries but correctly predict ITP zone orders and sample accumulation 4 Using SPRESSO for high fidelity simulations of ITP There are two approaches to obtain high accuracy numerical solutions using SPRESSO 1 using the dissipative SLIP scheme with adaptive grid refinement to minimize numerical diffusion and 2 using the non dissipative sixth order compact scheme with adaptive grid refinement to avoid non physical oscillations While SLIP scheme yields robust simulations with no oscillations it requires careful choice grid density to minimize numerical diffusion Whereas the non dissipative compact scheme yields high resolution solutions with minimal numerical diffusion provided that a non oscillato
5. AB gives the following error on clicking GUI buttons ag Undefined function SpressoGUI for input arguments of type struct Error in guidemfile hObject eventdata SpressoGUI StartButton Callback hObject eventdata guidata hObject Error while evaluating uicontrol Callback Solution Such runtime errors are caused when users navigate to a different working directory in MATLAB and try using SPRESSO GUI To run SPRESSO it is necessary that the present working directory in MATLAB is the one containing Spresso mfile Problem ITP zones are not stationary while simulating in a moving frame of reference Solution SPRESSO uses the electromigration speed of the first species defined in InputTable to define the speed of moving frame of reference Therefore for ITP simulations with moving frame of reference the first species in the InputTable should be the leading electrolyte LE Problem Simulation of ITP shows zone boundaries dispersing over time and not sharpening as expected Solution Switch the current direction by changing the sign of input current 16 5 6 7 8 Problem Simulations take extremely long time to complete Solution This issue usually results while using large number of points 1000 or more SPRESSO includes adaptive grid refinement scheme which enables faster simulations with order 100 grid points without compromising accuracy Also using extreme grid adaptati
6. User s Manual to SPRESSO Supreet Singh Bahga January 2013 1 Download and Installation 1 SPRESSO is a MATLAB based open source nonlinear electrophoresis solver The source code and its executable binary file can be downloaded for free at http microfluidics stanford edu spresso 2 Download the code and unzip the file to a desired directory To run SPRESSO using the source code first navigate to the directory containing the file Soresso m Then run Spresso m by opening the file in MATLAB editor and hitting the run command F5 Alternatively SPRESSO can be run by giving Spresso command on the MATLAB command line Running SPRESSO will cause a graphical user interface GUI to appear as shown in Figure 1 Hy spresso TASON seve Seay Toggle Menus Basics Numerics Pressure Dispersion Filename afs userhome Downloads Spresso_v3 nput Files Case1_ TPDer Reload file Current uA 0 75 Grid Points 250 Data file aA oyna ee Simulation time s Spatial Discretization SUP SPRESSO oe i Start Domain Length mm 40 Moving Frame Yes version 3 stopoicar chanel shape DShape pi Prepare Grid Yes Adaptive Grid Clustering Stop Save Pause Dim 1 um 20 Dim 2 umj 50 5 1 ph lonic Strength Dependence Pot Concentraton m Plotingintervat 100 M eo 1 on No t NaN s At NaNs AV NaN V AP Pa Ionic Strength Change 10 0 2 T T T T T T Message box Lo
7. ZOIC ACID 1 3 16e 08 2 108 1316e 084939 injection Wi 1 6 008 2756 0 0300 Analyte 6 p AMINOBENZOIC ACID 1 3 16e 08 2 413 13 16e 08 4 853 Analyte l 1 5e 008 4 756 0 0500 Analyte 7 lt i 4 m Figure 3 Screenshot of SPRESSO GUI showing typical parameters for performing a high fidelity simulation of ITP using compact scheme For this particular simulation data from the simulation shown in Figure 2 was used as the initial condition Simulating a steady state ITP problem with an initial condition resembling the final solution yields significant computational efficiencies 5 Analyzing simulation data Simulation data is saved by SPRESSO in MAT file format of MATLAB For a simulation based on an input file named Input m simulation data are saved as Input mat in the directory containing the corresponding input file Data are usually saved automatically at the completion of simulation However users can also terminate the simulation before completion and save the data by clicking Stop Save button 14 Table 1 describes the variables in data file corresponding to different physicochemical quantities Table 1 Important variables in SPRESSO data file corresponding to various physicochemical quantities Data are saved at all N grid points and different time steps The number of times steps at which data are saved is given by Ntimes length tVecOut and the number of species is given by Nspecie
8. ad file reads an existing input file and fills all the GUI boxes with that information If a corresponding mat file is found you will be able to choose whether to load it or not Choosing Yes will automatically check the Loat mat box so that the data will be loaded after hitting Start You may still ignore the data by unchecking the box in which case only the input file will be processed after c mol lit 20 25 40 Name Valence I Add gt Name Valence Mobility pKa c M Locatio T ACETIC ACID _ i 1 4 24e 08 4 756 IT remove OLE 1 80e 009 2756 0 0500 LE 2 2 ACRYLIC ACID 1 4 27e 08 4 258 TO 2 ITE 1 25e 009 4 756 0 0200 TE i 3 ADIPIC ACID 1 2 46e 08 4 43 25 24e 08 5 277 imm 3 BG 20e 009 6 756 0 1300 Backgroui 4 ALLYLACETIC ACID 1 3 39e 08 4 674 22 4 Analytel 1 7e 008 2 756 0 0700 Analyte 5 o AMINOBENZOIC ACID 1 3 16e 08 2 108 1 3 16e 08 4 939 Injection width 5 Analyte2 1 6e 008 2 756 0 0300 Analyte 6 p AMINOBENZOIC ACID 1 3 16e 08 2 413 1 3 16e 08 4 853 6 iAnalyte3 1 5e 008 4 7561 0 0500 Analyte 7 lt m g m Figure 1 Graphical user interface of SPRESSO code The screenshot was taken after loading a sample input file Casel_ ITPDemo m provided in Input Files directory 3 To run SPRESSO using the executable version double click on Spresso exe file Executable version of the code works only on the Microsoft Windows
9. d e GUI Select Yes or No from the Ionic Strength Correction drop down menu to switch between 1 and 0 respectively 2 PcentIonicChange 3 Tink 4 L2 Description Controls the change in local ionic strength during simulation after which ionic strength corrections are applied This option is applicable only if ionic strength effects are activated using lonicEffectFlag Usage Takes on non negative values in terms of percentage change For example Pcent lonicChange 10 indicates that ionic strength effects will be evaluated if ionic strength of solution changes by more than 10 during simulation GUI Input value in the Ionic Strength Change box Input is available only if Yes is selected in the Ionic Strength Dependence drop down menu Description Leftmost coordinate of the computational domain Usage Default value is 0 and we suggest not changing this parameter in the input file GUI Not available in GUI Description Rightmost coordinate of the computational domain Usage Value corresponds to the length of computational domain in meter unit GUI Input value in the Domain Length box Description Number of grid points Usage Takes on non negative integer values Typical values range from 100 to 1000 grid points GUI Input value in the Grid Points box 6 DChannel e Description Width of the separation channel for D shaped cross section and diameter for circular cross section e Usage Takes on non ne
10. gative values in meter unit e GUI Input value in the Dim 2 box 7 hChannel e Description Depth of the separation channel for D shaped cross section and diameter for circular cross section e Usage Takes on non negative values in meter unit e GUI Input value inthe Dim 1 box 8 ChannelShape e Description Describes whether channel cross section is D shaped or circular e Usage Takes on values 1 for circular channel and 2 for D shaped channel e GUI Choose the cross section shape in the Channel Shape drop down menu 9 Current e Description Current applied through the system e Usage Takes on positive and negative values in ampere unit Positive values of Current signify rightwards pointing electric field and negative values for electric leftward pointing electric field e GUI Input value in the Current box 10 tEnd e Description Physical time for which problem is simulated e Usage Takes on positive values in seconds e GUI Input value in the Simulation time box 11 SteadyStateFlag e Description Indicates whether simulation is solved in a moving reference frame or stationary laboratory frame e Usage Takes on values 0 and 1 The value 1 indicates that simulation is solved in a frame of reference moving with the first species mentioned in the InputTable The value 0 indicates that simulation is performed in a stationary laboratory frame e GUI Choose Yes or No from the Moving Frame drop do
11. inement Figure 2 shows screenshot of the GUI with necessary simulation parameters and simulated concentration profiles Next save the simulation data by clicking the Stop Save button The simulation data are automatically saved if the simulation reaches completion Step2 Edit the input file by choosing the following simulation parameters on GUI Grid Points 250 Spatial Discretization Compact Moving Frame Yes Prepare Grid Yes Adaptive Grid Speed 2 Clustering Level 2 Step 3 Save the input parameters to the same input file by clicking Save Also turn on the Load mat option on GUI to load data saved from the previous simulation The simulated data from Step will then be used as the initial condition for next simulation Next click Start to run the simulation Figure 3 shows screenshot of the GUI with simulation parameters discussed in Step 2 along with simulated concentration profiles This simulation took approximately 13 60 s to attain steady state on a standard desktop computer Combined with 15 s of computational time taken by Step 1 the hybrid approach leveraging the SLIP and compact schemes takes approximately 75 s of computational time Whereas simulating the same problem with compact scheme alone takes over 120 s We note that for simulations involving complex transients the hybrid approach will yield further speed enhancement gJ spresso BA Ow Input file Toggle Menus Basics Nu
12. ion gradients at the domain boundaries This ensures proper imposition of boundary conditions GUI Input value in the Injection width box Note that the GUI allows only one injection point However multiple sample injection points can be inserted by manually customizing the input file e g using the MATLAB text editor 19 Pressurehead Description Pressure head across the length of computational domain to include hydrodynamic flow Usage Takes on negative and positive values in millimeters of water column GUI Click the Pressure Dispersion button and then input the value in Pressure head box 20 bPressure Description Hydraulic resistance coefficient in Poiseuille s Law Usage Dimensionless parameter that takes on positive values Use value of 32 for channels with circular cross section GUI Click the Pressure Dispersion button and then input the value in b coeff box 21 betaDispersion Description Taylor Aris dispersion coefficient described by Bercovici et al 63 e Usage Dimensionless parameter that takes on positive values e GUI Click the Pressure Dispersion button and then input the value in beta coeff box 22 zVec phiVec AnalyteVec TEVec LEVec BackgroundVec e Description Vectors that define initial distribution of analytes trailing electrolyte and leading electrolyte e Usage Vectors normalized with the highest term i e maximum term should be 1 User can change these vectors and save
13. lines in the input file e GUI Default values are used when input file is saved from the GUI These variables cannot be changed though GUI 27 Miscellaneous features available in GUI e Load mat Checking this option allows starting simulation from the point where last simulation ended e Stop Save Stops the simulation and saves the data The data are automatically saved if the simulation reaches time tEnd e Stop Discarad Stops the simulation without saving the data e Pause Temporarily stops the simulation to allow data visualization Hitting the Pause button for the second time will restart the simulation from the point where it was paused e Plot This drop down menu allows visualization of axial variations in species concentration pH effective mobility electric field conductivity grid density and cross sectional area e Caution Saving the input file through GUI will overwrite any manual changes made to the input file For manually customized input file the GUI can still be used to run and visualize the simulation as usual 3 Using SPRESSO to explore electrolyte chemistries for ITP SPRESSO allows fast simulations of ITP and thereby minimizes the time required for selection of optimal electrolyte chemistries When the goal of simulations is to explore LE TE electrolyte systems for focusing given analytes in ITP we suggest using the dissipative SLIP scheme without adaptive grid refinement Although this approach yield
14. maller values will slow the simulation as more resources will be required for plotting the data GUI Input value in the Plotting Interval box 16 SpatialDiscFlag Description Indicates the spatial discretization scheme Usage Use SLIP for finite volume SLIP scheme Compact for sixth order compact scheme Upwind for first order upwind scheme and 2nd for centered second order scheme Note that only the SLIP scheme allows solving problems with variable cross sectional area channels GUI Select desired numerical scheme from the Spatial Discretization box 17 InjLen Description Thickness of the initial concentration boundary at the sample injection point Usage Takes on positive values in millimeter The value must be chosen to ensure that the concentration boundary lies completely inside the computation domain and there are no concentration gradients at the domain boundaries This ensures proper imposition of boundary conditions GUI Input value in the Injection width box Note that the GUI allows only one injection point However multiple sample injection points can be inserted by manually customizing the input file e g using the MATLAB text editor 18 InjLoc Description Location of the initial concentration boundary Usage Takes on positive values in millimeter The value must be chosen to ensure that the concentration boundary lies completely inside the computation domain and there are no concentrat
15. merics C Pressure Dispersion Current uA 0 75 Grid Points 250 Data file ote Simulation time s Spatial Discretization 6th orde v SPRESSO es Start Domain Length mm 40 bia 7 3 Stop Discard Channel Shape DShepe fy Prepare Grid fi e a Adaptive Grid Clustering I om see onz 2 gt lonic Strength Dependence onanie SE seves Filename afs userhome Downloads Spresso_v3 nput Files Case1_TPDer_ Reload file Plot Concentration Plotting intervat 100 ArealWariations cx 1 0 No t 142 8322 s At 0 018943s AV 141 6 V AP 0 Pa bonic Strengih Change 1p T T Message box Pressing the Stop Save button will stop a the simulation and will save the simulation data as a mat file with the same name as the input file 2 S D The mat file includes the grid spacing and the concentration profiles for all previous times and may be used for postprocessing of the data c mol lit The mat file can also be used to resume the simulation form the time it was last stopped by checking the Load ma box Valence Mobility pKa c M Locatio T ACETIC ACID JI 4 24e 08 4 756 1 80e 009 2756 0 0500 LE gt 2 ACRYLIC ACID 1 4 27e 08 4 258 1 25e 009 4 756 0 0200 TE 3 ADIPIC ACID 1 2 46e 08 4 43 25 24e 08 5 277 20e 009 6 756 0 1300 Backgrou 4 ALLYLACETIC ACID 1 3 39e 08 4 674 1 7e008 2756 0 0700 Analyte 5 o AMINOBEN
16. on 1 e with high grid adaptation parameters can decrease simulation speed We encourage users to run numerical experiments to find optimal number of grid points and adaptive grid refinement parameters to achieve shorter simulation times Numerical parameters are often problem specific and we provide typical values of these parameters in Section 1 Problem Simulations with sixth order compact scheme yield oscillatory solutions Solution The sixth order compact scheme is not unconditionally stable and can yield oscillatory solutions due to insufficient grid density Oscillatory solutions can be avoided by increasing the number of grid points or increasing the value of adaptive grid parameters Also for fast and approximate simulations we suggest using the unconditionally stable SLIP scheme which does not yield oscillations Problem GUI overwrites manually customized input file Solution When input file is saved through GUI the code uses input values in GUI to write a new input file This overwrites manual changes made to the input file Therefore we suggest saving the customized input file through a text editor and not the GUI Problem While using a customized input file GUI plots incorrect initial conditions Solution The code in its current form uses the inputs from GUI to plot initial conditions using a set of predefined concentration distributions However this does not affect simulations or real time data visualization While
17. p computer Note that the zone boundaries are significantly diffused Nevertheless the simulation shows that the model electrolyte chemistry enables focusing of analytes ITP 11 g spresso Ye amp 2 7 W TE save e Toggle Menus Basics Numerics C Pressure Dispersion Flename afswserhomeDownloads Spresso_v3input Fles Case1_1rPDer Recea me es Current uA 0 75 Grid Points 250 Data file VONE Simulation time s 250 Spatial Discretization SUP x Start Domain Length mm 40 Moving Frame Yes X version 3 Seomar Trane Steps DShape Prepare Grid No M 3 Adaptive Grid Clustering St top Save Pause Dim 1 um 20 Dim 2 um 50 5 0 0 lonic Strength Dependence N Bak concentration PONG mIeNae 100 A eo 1 ox o t 250s At 0 42851s AV 141 5 V AP 0 Pa oo PEITO Ea T T T Message box 01 When hitting the Start button the a x program will process the input file 2 specified in the Filename field and NOT the content of the GUI Therefore any E 0 05 changes in the GUI fields disables the a g Start button until the Save or Save as buttons are pressed If the Load ma box is checked the 0 corresponding data file mat will be 0 5 10 15 20 25 30 35 40 loaded after processing the input file x mm Name Valence I Add gt Name Valence Mobility pKa c M Locatio 1 JACETIC ACID 1 4 24e 08 4 756 Be Re 1 le LE 1 80e 009
18. ry solution is achieved Unlike the SLIP scheme the sixth order compact scheme is not unconditionally stable and therefore it is necessary to vary the grid density by changing the number of grid points and or varying adaptive grid parameters to ensure a non oscillatory solution 12 For unsteady ITP problems either of the above approach can be used Whereas for steady state ITP problems a hybrid approach based on SLIP and compact schemes can allow faster simulations In this hybrid approach we first simulate the ITP problem using the SLIP scheme without adaptive grid in a moving frame of reference Once an approximate steady state is attained we stop the simulation save the data and restart the simulation using the compact scheme This approach yields faster simulations because the first step involving the SLIP scheme without adaptive grid gets past the initial transients with relative ease Simulating such transients with compact scheme would take significantly longer duration Whereas the second step involving compact scheme starts with an initial condition resembling the actual steady state solution Better initial starting condition for the steady state simulation speedup up convergence to actual solution Below we discuss an example of steady state ITP simulation using hybrid SLIP and compact scheme approach Step 1 Follow the steps outlined in Section 3 to solve the required ITP problem with SLIP scheme and no adaptive grid ref
19. s Variable in Data Physicochemical Data Type and Usage File Quantity phiVecAl1Times Coordinates of grid Matrix Size Nx2xNtimes points in physical Coordinates in moving frame domain phiVecAllTimes 1 at different time Coordinates in stationary frame steps phiVecAllTimes 2 tVecOut Physical time Vector Length N at which data are saved pHVecAllTimes pH at all grid points Matrix Size NxNtimes at different time steps SigVecAl1lTime Electrical Matrix Size NxNtimes conductivity at all grid points at different time steps cMatAllTimes Species Matrix Size concentrations Nx NSpecies 1 xNtimes at all grid points at different time steps 15 Concentration of species j 1 2 Nspecies cMatAllTimes j Hydronium ion concentration cMatAllTimes end 6 Routinely encountered issues with SPRESSO Several runtime issues with SPRESSO have been reported over the past and we have done our best to address them in the latest version of code Issues with SPRESSO often stem from erroneous user inputs We here document routinely committed input errors and their remedies 1 2 3 4 Problem The most commonly committed error is to input the species concentrations in millimolar mM units in the InputTable This might be the due to common usage of millimolar units in electrophoresis community Solution Input species concentrations in molar M units Problem MATL
20. s relatively dispersed concentration gradients it correctly predicts zone orders and 10 sample accumulation Moreover the SLIP scheme being unconditional stable even without adaptive grid refinement yields significant reduction in computational time Below we provide guidelines for performing fast and approximate ITP simulations to explore electrolyte chemistries Step 1 One of the simplest methods for setting up SPRESSO simulation is by loading and editing an existing input file in the GUI In this example we will use the input file named Casel_ ITPDemo m Figure 1 shows screenshot of GUI after loading this input file Step2 Edit the input file by choosing the following simulation parameters on GUI Grid Points 250 Spatial Discretization SLIP Moving Frame Yes Prepare Grid No Adaptive Grid Speed 0 Clustering Level 0 These are the typical numerical parameters that are required for fast but approximate ITP simulations Disabling adaptive grid refinement yields significant reduction in computation time Also simulating ITP in moving frame of reference allows use of smaller computational domain and lesser number of grid points Step 3 Save the input parameters to a different input file by clicking the Save As button and then click Start to run the simulation Figure 2 shows the GUI with updated simulation parameters along with simulated concentration profiles This simulation took less than 15 s on a standard deskto
21. the input file using a text editor Saving the input file from GUI will overwrite the user defined vectors with default values e GUI Default values are used when the input file is saved from GUI 23 AreaFunctionText e Description Function defining axial variation of channel cross sectional area e Usage The function must be defined in the following format x f x Here f x is a user defined function written in a form to allow vectorized arithmetic operations Default value is x 1 O x which corresponds to axially uniform cross section This function is later automatically scaled such that the cross sectional area of left channel inlet is that given by DChannel and hChannel dimensions e GUI Input the desired function in the Area Variation box 24 A and AreaRatio e Description Variables to evaluate cross sectional area variation defined by AreaFunctionText e Usage Use the values initialized by GUI We suggest not changing these parameters e GUI Default values are used when the input file is saved from GUI These variables cannot be changed though the GUI 25 InputTable e Description Describes chemical species their ionization states mobilities acid dissociation constants and concentrations e Usage Example input from Casel ITPDemo m is as follows InputTable LE 1 80e 009 2 756 0 05 LE CTE ere 25e 009 4 756 0 02 TE BG 1 20e 009 6 756 0 13 Background Analytel
22. wn menu 12 PrepareGridStage e Description Indicates whether grid should be refined prior to the application of electric field e Usage Takes on values 0 and 1 The value 1 enables adaptive grid refinement and value 0 disables grid refinement e GUI Choose Yes or No from the Prepare Grid drop down menu 13 AdaptGrid Coeff e Description Controls the speed of grid adaptation e Usage Takes on non negative values Speed of grid adaptation increases with increase in value of AdaptGrid Coeff Typical values range from 0 10 The value 0 indicates no grid adaptation Typical value for ITP problems is 1 and for CZE problems is 0 1 e GUI Input value in the Adaptive Grid Speed box 14 AdaptGrid PointsAtInterface e Description Controls the clustering of grid points during adaptive grid refinement e Usage Takes on non negative values Higher values lead to greater clustering of grid points at regions with large gradients Typical values range from 0 10 The value 0 indicates no grid adaptation Typical value for ITP problems is 1 and for CZE problems is 0 1 GUI Input value in the Clustering Level box 15 DeltaCounterNextPlot Description Controls the number of simulation time steps after which data are saved and plotted on GUI Data are saved in the directory containing the input file The data file has the same name as input file but with mat extension Usage Takes on positive integer values Typical value is 100 S

User`s Manual to SPRESSO - Stanford Microfluidics Laboratory

Contents

Download Pdf Manuals

Related Search

Related Contents