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I have been trying to get sustained combustion in ANSYS using the Species Transport Model and Finite Rate Mechanism. However, even when i manage to get ignition the flame eventually dies out. I'm using the following boundary conditions:
Inlet : velocity inlet of Methane at room Temperature.
Free air flow in the surroundings at room temperature.
Initially the domain has air and methane comes in at room temperature. I can add a high temperature zone to get ignition and once i remove that high temperature zone the flame goes out.
If anyone can guide me on how to sustain this flame to mimic actual experiments where once ignition is achieved the flame is sustained. Thanks.
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Hi Mostak, Thank you for your response. I have been using Chemkin defined reaction rate for Finite Rate Kinetics. So i haven't been changing the coeffcicients and simply using the values defined by chemkin. However the problem is that even after getting ignition the flame dies out in subsequent iterations and if add too much energy to get ignition the solution diverges. Not really sure how to get around this problem.
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Hi everyone, I've been running this Sdevice code to obtain a 14 nm finFET thermal simulation, but the results doesn't match with the expected. Do you have any suggestions or tips that I could use to run this simulation? Thanks in advance.
#==================================================
# dessis.tpl
#
# for use with run_dessis.tel
#==================================================
#setdep @node|iClassDDmodToxWf@
#setdep @node|xreflect@
#define _Hmodel_ Hydrodynamic(eTemperature)
#define _EQUATIONSET_ Poisson Electron Hole eTemperature Temperature
#define _QC_ eQuantumPotential
File
{
Grid= "n@node|xreflect@_reflectx_msh.tdr"
Piezo= "n@node|xreflect@_reflectx_msh.tdr"
Parameter="@parameter@"
Current= "@plot@"
Save= "@save@"
Plot= "@tdrdat@"
Output= "@log@"
}
electrode {
#if "@Type@" == "nMOS"
{ name=gate voltage=0.7 }
#else
{ name=gate voltage=-0.6 }
#endif
{ name=substrate voltage=0}
{ name=source voltage=0 Resistor=40 }
{ name=drain voltage=0 Resistor=40}
}
Thermode{
{ Name="substrate" Temperature=300 SurfaceResistance=1e-4 }
}
Physics{
_Hmodel_
_QC_
RecGenHeat
AnalyticTEP
ThermalConductivity()
Temperature=300
EffectiveIntrinsicDensity( BandGapNarrowing(OldSlotboom) )
Mobility(
DopingDep
eHighFieldsaturation( CarrierTempDrive )
Enormal(Lombardi)
)
Recombination(
SRH( DopingDep TempDependence )
)
}
physics(Material=SiliconGermanium){
Piezo( Model( DeformationPotential( minimum ekp hkp )
DOS (eMass hMass)
#if "@Type@" == "nMOS"
mobility(esaturationfactor=0.0 efactor(kanda sfactor=MCmob(Type=0)))
#else
mobility(hsaturationfactor=0.0 hfactor(kanda sfactor=MCmob(Type=1)))
#endif
)
Stress=(@Sxx_Pa@,@Syy_Pa@,@Szz_Pa@,0.0,0.0,0.0)
)
mobility (
highfieldsaturation
Enormal(Lombardi(AutoOrientation) )
PhuMob
)
EffectiveIntrinsicDensity ( Slotboom NoFermi )
Recombination ( SRH(DopingDep) Auger )
}
Math {
-CheckUndefinedModels
Method=blocked
Submethod=pardiso
Digits=6
Extrapolate
Derivatives
Iterations=50
Notdamped=50
NumberOfThreads= 8
-ExitOnUnknownParameterRegion
ExitOnFailure
}
Plot{
*--Density and Currents, etc
eDensity hDensity
TotalCurrent/Vector eCurrent/Vector hCurrent/Vector
eMobility hMobility
eVelocity hVelocity
eQuasiFermi hQuasiFermi
*--Temperature
eTemperature Temperature *
*--Fields and charges
ElectricField/Vector Potential SpaceCharge
*--Doping Profiles
Doping DonorConcentration AcceptorConcentration
*--Generation/Recombination
SRH Band2Band * Auger
AvalancheGeneration eAvalancheGeneration hAvalancheGeneration
*--Driving forces
eGradQuasiFermi/Vector hGradQuasiFermi/Vector
eEparallel hEparallel eENormal hENormal
*--Band structure/Composition
BandGap
BandGapNarrowing
Affinity
ConductionBand ValenceBand
eQuantumPotential
}
#if "@Type@" == "nMOS"
Solve {
*- Build-up of initial solution:
NewCurrentPrefix="init_"
Coupled(Iterations=100){ Poisson _QC_ }
Coupled{ _EQUATIONSET_ _QC_ }
*- Bias drain to target bias
Quasistationary(
InitialStep=0.01 MinStep=1e-5 MaxStep=1
Goal{ Name="drain" Voltage= 0.7 }
) { Coupled { _EQUATIONSET_ _QC_ } }
}
#else
Solve {
*- Build-up of initial solution:
NewCurrentPrefix="init_"
Coupled(Iterations=100){ Poisson _QC_ }
Coupled{ _EQUATIONSET_ _QC_ }
*- Bias drain to target bias
Quasistationary(
InitialStep=0.01 MinStep=1e-5 MaxStep=1
Goal{ Name="gate" Voltage= -0.7 }
) { Coupled { _EQUATIONSET_ _QC_ } }
}
#endif
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Hello, I would like to ask how to set the value of SurfaceResistance. I noticed that you only set the substrate part when setting the Thermode, but the source dran gate area is not set. In addition, I would like to ask why the value is set to 1e-4, this How is the value determined?
Thank u!
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I am looking for a way to connect a classic 4-step transport model (macro) with a micro-level model. The purpose is to capture a behavioural response (change in travel behaviour) of people to some specific policy change (road charges…) and feed this information into another micro-level model (microsimulation model with individuals grouped into households). The difficulty is that the 4-step transport model is a macro model, where we have aggregate flows of people (# of trips), not individuals. The output is in form of OD matrices between different geographical zones (of a studied area) before and after reform. They show the number of trips between zones and the total matrix is subdivided into OD matrices for different travel modes and some combinations of socio-economic profile and trip purpose.
My question is what would be the best approach to extract information from aggregate OD matrices to feed into micro-level dataset? I wish to capture how modal choice will change (e.g. if we introduce road tax, how each individual in micro dataset will adapt, maybe he will choose public transport?…)
What would be your suggestions? Maybe someone already tried to do something similar? I couldn’t find anything. Your suggestions would be very appreciated!
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To extract information from aggregate OD matrices and feed it into a micro-level dataset, you could use a technique called disaggregation. Disaggregation involves breaking down aggregate data into smaller units, such as individual households or trips, to capture more detailed information about travel behavior. Here are a few possible approaches to consider:
  1. Gravity model: The gravity model is a common method for disaggregating OD matrices. The model uses factors such as distance, population, and economic activity to estimate the flow of people or goods between origin-destination pairs. You could use a gravity model to estimate the number of trips between each pair of zones in your OD matrix and then allocate those trips to individuals in your micro dataset based on their characteristics (e.g. income, age, gender, etc.). You could then simulate the effect of a road tax on travel behavior by adjusting the cost or attractiveness of different modes in the model.
  2. Synthetic population: Another approach is to create a synthetic population that represents the characteristics and travel patterns of individuals in your study area. A synthetic population is generated by combining data from various sources (e.g. census, surveys, etc.) to create a representative sample of the population. Once you have a synthetic population, you could use it to simulate the effect of different policy scenarios on travel behavior. For example, you could introduce a road tax and see how individuals in the synthetic population respond by choosing different modes of transportation.
  3. Activity-based modeling: Activity-based modeling is a more detailed approach to disaggregation that takes into account the various activities that individuals engage in throughout the day (e.g. work, school, shopping, leisure, etc.) and how those activities influence their travel behavior. Activity-based models typically use data from travel surveys and other sources to estimate the frequency, duration, and timing of different activities for individuals in the study area. You could use an activity-based model to simulate the effect of a road tax on travel behavior by adjusting the cost or availability of different modes for each activity.
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I am trying to  include some attitudinal in mode choice models. Does anybody know which software package can be used to estimate the model?
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Shafinaz Naim, Liao Wang all Biogeme codes are availavle here : https://github.com/michelbierlaire/biogeme/tree/master/examples, including Integrated Choice and Latent Variable (ICLV) models.
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Came across an article where authors used TOUGHREACT for geochemical modelling.
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Hi Sabina,
Not easy to compare as each one is dedicated to different applications.
PHREEQC is widely popular among the geochemical modeling community and is considered by far the most complete geochemical modeling package. It is very flexible and easy to use. In version 3, there is support for modeling high-pressure-temperature systems.
TOUGHREACT couples a geochemical engine (REACT) with the well-known multiphase and multicomponent TOUGH2 code (developed by LBNL) which has well-known applications in geothermal reservoir engineering and CO2 storage applications.
The code REACT has fewer capabilities for pure geochemical modeling compared to PHREEQC, and to my best knowledge, it is not (or much less) maintained than PHREEQC. Hence, the latter is better for pure geochemical models or 1D fully saturated reactive transport simulations.
TOUGHREACT is advised for multi-dimensional (2D or 3D) reactive transport applications possibly with multiphase fluid flow and transport.
Hope this can help you.
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I am trying to simulate miscible liquids in fluent. I am trying to reproduce the results of a paper, but I am not getting the same mass fraction plots as in the paper. I am using species transport model with laminar flow model. I have set the viscosity and molecular diffusion coefficient values as given in the paper. I have tried 4 different sets of mesh based on cell count and refinement. I cannot seem to know what may be the problem
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I've tried both VOF and mixture but there isn't any difference
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Hi. i want to simulate methane-hydrogen combustion in fluent using species transport model. how should I define two fuels with separate reaction mechanism which enter combustion chamber through same inlet?
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from species transport . you can add or remove species from the mixture material by using species dialog box
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In shallow regions near the coast, sediment transport models require some geomorphological properties of the sea bed. Is there any database that contains d50, d16, d84, some cores to know the kind of material in layers?
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Perhaps USGS websites are useful.
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Hello everyone,
I am creating a sediment transport model using HEC-RAS (v 6.1) in 1D.
I want to compare a simulation in a fixed bed condition (erosion not allowed) with another in a mobile bed condition (erosion allowed).
In order to consider the fixed bed, I have set the value of the Max Depth to zero in each section. Unexpectedly, the model shows that Mass (Vol) Out Cum is greater than Mass (Vol) In Cum. (Attached images)
How can I explain this? Have I set the wrong condition for a fixed bed?
Thank you for your answer
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Dear Daniele,
Please let us know if you have fixed it.
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Hi,
I have read about coupling PEST++ software with transport models, such as MODFLOW, for estimating the uncertainty of the state variables etc. Is it possible to couple PEST++ software with a surrogate model, and if yes, is there any link that I can use for guidance?
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Dear Jana,
thank you very much for your response. I was looking for coupling PEST with surrogate models (e.g. AI models that emulate physically-based models). I have also seen examples of coupling PEST with MODFLOW. My understanding is that I need to use a model that uses the same input data as MODFLOW and then replace it.
Regards,
K
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the traffic light sometimes is easier to cause the traffic jam problem, if the designer don't make to many change to the both side of the road,such as the house and block building, what other aspect of things can be done to mitigate the traffic jam problem.
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Dear Dr. Yang Ying ,
I suggest you to have a look at the following, interesting reference:
- Reducing Traffic Congestion and Pollution in Urban Areas
Modern, sophisticated initiatives that are better than typical ‘big ideas’ include:
  • Optimise traffic-light management
  • Use CCTV to monitor road conditions
  • Enforce existing road traffic laws
  • Improve perceptions of buses
  • Extend residents’ parking zones
  • Charge for workplace parking
  • Improve cycling infrastructure
  • Improve bus services
  • Develop and refine park-and-ride
  • Use Inbound Flow Control
  • Rationalise distribution and deliveries
  • Existing rail network
  • Light rail
  • Strategic Road Network resilience
  • Road pricing
It is often incorrectly suggested that congestion may be solved with one big idea, such as:
  • Widen roads
  • Narrow roads
  • Add bus lanes
  • Remove bus lanes
  • Build tunnels
  • Build a new ring road
  • Build a light rail network
  • Switch off traffic lights
  • Ban cycling
  • Ban cars from city centres
  • Close through-routes to private vehicles
  • Close car parks
  • Build more car parks
  • Build more park-and-rides
  • Make buses free
  • Make park-and-ride free
  • Introduce a congestion charge/road pricing
- Reducing Traffic Congestion and Pollution in Urban Areas
My best regards, Amir Beketov.
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If you are using application software or code that is fine but you are not really learning much as all you do is learning how to enter the input data and produce the output results. The inside details such as knowing how the governing differential equation is treated mathematically or numerically, how the domain of analysis is represented, and how the code is written using a computer programming language are not really known. This problem is overcome here by offering computer source codes, where all the steps from A to Z in solving many engineering, applied math, physics and mechanics problems are presented. If you are interested or have a question please contact me at youssefhafez995@gmail.com.
The computer codes and numerical models listed herein represents over 25 years of hard work in the field of applied mathematics, numerical methods and computer programming in FORTRAN. They have been used in many large scale projects and validated against analytical solutions and field data.
Computer Models using the Finite Element Method and coding in FORTRAN Programming Language:
1- WAVES-2D Model: A two – dimensional unsteady Finite Element (FE) hydraulic model for calculating the two dimensional (2D) horizontal velocity components and the water depth in lakes and river channels. It does 2D flood modeling and overland flow. It also does 2D river, lake, and channel hydrodynamic flow modeling.
2- TurbFlow: A three-dimensional velocities (U, V and W velocity components) and pressure distributions in the cross section of a fully developed flow region. It uses Finite Element (FE) numerical model for solving Navier-Stokes equations in ducts, pipes, closed conduits and open channels using a non-linear K-E turbulence modeling (used in Ph.D. Dissertation, CSU, Fort Collins, CO, USA). This program constitutes the ultimate modeling of transport phenomena and finite element modeling of highly non-linear convective flows. It does model very accurately secondary currents in ducts and open channels at corners and roughness discontinuity areas. In addition it simulates effects of the free surface on turbulence (dampening effect of the free surface).
3- NERVE–1D Model:A one–dimensional hydraulic and morphologic model for calculating water levels, velocity, and scour and deposition in river Channels. This program has an advantage over other models in that it does the roughness coefficients calibration process automatically without need for the commonly used trial and error approach.
4- Non-Linear-Networks: Non-Linear Discrete FE model for network analyses such as water distribution systems and flow of polymer melts through processing units. It is validated for New York and Hanoi water networks.
5- Water/Soil Quality – 1D: A one –dimensional unsteady water quality FE transport model used in predicting the spatial and temporal distributions of BOD TDS and CI along the stream channel. It does soil quality modeling of the transport of Radon gas in soils.
6- SUITE-3D: A three-dimensional unsteady FE model for simulating the three-dimensional momentum transport. It solves the three-dimensional advection-diffusion transport differential equation. It uses Finite Element (FE) numerical model for solving the full Navier-Stokes equations in three-dimensions. It does air pollution dispersion modeling, and heat transfer analysis.
7- SUITE – 2D: A two – Dimensional Hydrodynamic and transport FE model incorporating turbulence for detailed flow and large scale eddy structures around hydraulic structures. It also solves for the heat and mass transport equations.
8- Poisson/Laplace 2D: Finite Element 2D model for solving Poisson’s PDE and Laplace’s PDE, application to ground water flow in porous media, heat transfer, and viscous flows.
9- ODE2: General Differential Equation Solver for Second Order Ordinary Differential Equation using the Finite Element method applied to heat transport in pipe flows, deflection of tight wires, and beams on elastic foundations.
10- Heat 1D: One dimensional Finite Element Model for solving the heat partial differential Equation applied now to simulate Radon gas transport in porous media.
11- Wave 1D: FE one-dimensional model for the Wave PDE used for non-linear Fourier heat analyses in Skin tissues.
12- Networks: Discrete FE model Solves network problems as water pipes networks, electrical networks & spring systems.
13- Continua-2D: solves 2D stress-strain analysis for deformations of elastic solids.
14- Nonlinear Dynamics: It solves nonlinear dynamical equations such as the pendulum differential equation including also resistance forces such as friction and form drag forces in addition to electromagnetic forces.
15- Local scour prediction: It calculates bridge pier scour, plunge pool scour, scour downstream of barrages and grade control structures, and abutment scour.
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Kudos for posting this! I couldn't agree more. Knowing how to run Fluent isn't the same as understanding CFD. I created codes like that when none existed. I have written millions of lines of code but I'm not a "computer programmer" and have never sat through a single class on programming. I'm an applied mathematician. I would never write anything in object-oriented code or Python. I'm far too spoiled, expecting fast and predictable results. If I weren't so darn lazy, I'd write everything in assembler.
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Hi,
I'm trying to model a shock tube which consists of the driver and driven area. The driver and driven area contains helium at high pressure and nitrogen at low pressure respectively. They are separated by a diaphragm, which will rupture at t=0. This is a high speed flow problem with speed reaching 4-5 mach no.
So which solver should I use? I was previously using rhoCentralFoam but can I make it work with 2 gases, assuming no reaction at the moment?
I read thru the forum and some suggested rhoReactingFoam or rhoPimpleFoam.
cfdvenkatesh in the Cfd-online forum suggested :
"You could use Species Transport model to simulate mixing of 2 different gases. If your application is not IC engine related, I would suggest to use General Species Transport. In the inlets you can specify the mass fractions for the gases you like."
So which is the more appropriate solver to use?
Thanks!
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Hi, you can try:
1) reactingPimpleCentralFoam, which is a part of https://github.com/unicfdlab/hybridCentralSolvers
2) reactingLagrangianQGDFoam, which is a part of https://github.com/unicfdlab/QGDsolver#QGDsolver-library-brief
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Hello? I'm trying to simulate tar reforming in Ansys Fluent using the species transport model. I have toluene and naphthalene as tar species with a number of reactions. I was using the mixture template, but there is a problem that the last species in the mixture list shows the biggest fraction at the outlet in the results. May I consider using another approach? Please help me to figure out this problem.
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Usually, in fluent the last specie in the list is calculated by algebraic equations for mass balance which is given as- 1- the sum of all species calculated through specific PDEs. This could lead to error in the last species calculation if its value is very small compared to other species since the residual error of all the species will be accumulated in the last. To avoid such an issue always consider the last species some bulk species like for instance N2 or any other species which has a large percentage throughout the domain.
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I need to use runkel's solute transport result as benchmark results. Can anyone provide me algorithm for runkel's solute transport model. Thanks in advance.
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Dear Mr. Modi!
I found the following article free to access:
Tinet, AJ, Collon, P, Philippe, C, Dewaide, L & Hallet, V 2019, 'OM-MADE: An open-source program to simulate one-dimensional solute transport in multiple exchanging conduits and storage zones', Computers and Geosciences, vol. 127, pp. 23-35. https://doi.org/10.1016/j.cageo.2019.03.001 Free access:
Yours sincerely, Bulcsu Szekely
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Hello everyone,
My name is Caner, and I'm a PhD student. I need help with the simulation aspect of my dissertation. Simply put, I need to model a ferry line. I've got the following information:
- Ferry specifications including power, speed, fuel capacity, fuel consumption in litres per nautical mile, passenger and car capacity, and more.
- Price of fuel per litre,
- Coordinates or distances of piers,
- Where ferries are moored,
- Timetables of all lines.
What I need to do first:
- Define piers and ferries,
- Setup lines between piers,
- Define timetables to those lines,
- Make each ferry pick up a line, depart from the pier as per the timetable,
- Go back to the starting positions after completing the schedule.
Second step:
- Set different schedules for weekdays and weekends,
- Define fuel capacity, fuel consumption and monitor fuel usage of each ferry,
Third step:
- Make a ferry go to refuel when fuel capacity reaches a certain threshold: e.g. if the fuel is less than 1 trips worth, alert another ferry to take over its next scheduled departure and go to refuel)
- Get a report of when and how much fuel the ferry got refuelled.
Fourth Step:
- Introduce passenger and cars to be carried for each trip as per a demand formula. Get a report about how many passengers transported.
Fifth Step:
-Remove fossil fuel ferries and introduce electric ferries to the same model.
-Add recharging ability to the piers.
-See the results and calculate the lowest required power and fuel (battery) capacity for the lowest yearly cost of operating electric ferries.
So far I've looked into FlexSim, Promodel, Process Simulator, PTV Vissim, Any Logic and a few other sim software I couldn't get to run properly. My problem is that it will take quite a long time for me to learn to code for each software and I don't have any time to waste.
Looking for suggestions on using which software and how to obtain each step.
All help is appreciated.
Note: At this point, I'm thinking about ship simulation games. Ship Simulator Extremes had great sea and weather simulation options. Is there a way that I could directly design the above scenarios on such a ship simulation game? Maybe that could bring more reliable results and easier configuration.
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In HEC RAS model the software run my 1D-2D coupled data, but in RAS mapper result section this problem arise. How can i resolve this?
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Hello Arnab,
With respect to this issue, I suggest you share this as a public post via "https://www.kleinschmidtgroup.com/the-ras-solution]
where you can get more feedbacks from sediment modeling experts.
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I want to define a CO + H2 mixture fuel for a combustor. How can I define this in ansys fluent mixture template ? Normal database does not include this mixture . eg. if I want to define a mixture of 20% CO and 80% H2 how do I proceed without using a UDF ?
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You need to choose an appropriate reaction mechanism which contains both CO and H2. Fluent does offer the 4-step Jones-Lindstedt mechanism, if I recall correctly. Alternatively, use one of the model choices you can find under "non-premixed combustion"... if you have a non-premixed combustion process.
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Hey all,
I am trying to add two models (Unified equilibrium land-use transport & Bus operator behavior model). Unified equilibrium land-use transport model is a minimization problem subject to multiple equality constraints. However, Bus operator behavior model is a maximization problem subject to one inequality constraints. For the purpose of combining both models, I just need to change user travel cost (C_ijk) in the first model, perhaps. But, I am not sure how to add common constraint (equality or inequality) in the combined model? Both of these models as based on nested-logit-theory.
Any help will be appreciated.
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Following ^^
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Hi world, I'm currently doing a research for my final year project. And currently I'm having trouble in looking for a transport model for COMSOL regarding a reverse osmosis desalination membrane.
Could any kind soul please help me with this? It will be greatly appreciated.
Thanks :)
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Hi Hock Chee Lu,
I think this article may help you a lot. Here, Molecular transport through a single nanopore in lipid membranes of vesicle has here been studied by COMSOL simulation
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I am looking for a new mixture template which is not in the data base of Ansys Fluent species transport model. How could I add new template?
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There are two ways to do that.
1. Find/create a chemkin import for your mixture template. A chemkin import is generally set of three files containing kinetics, thermodynamics and transport properties.
2. The second way is to create the mixture template inside the fluent itself using fluent library.
Read my and others answers for more details on the link attached below for clarity
If still you have a doubt, drop a inbox me, we can discuss it further.
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We're developing a distributed sediment transport model but lack an effective way of estimating D50, which is a sensible parameter in most transport capacity equations. Data that we have includes river width, stream order and upstream area as well as daily runoff and water level.
Would there be a simple way to estimate D50 in each river cell based on these parameters? Thank you very much!
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To caveat my answer, I'm a fluvial geomorphologist, and field data is essential to model development and application. Given that some models are developed without field data, but rely on remotely sensed data, I offer the following suggestions with the caveat that the model outputs will only be estimates and should be calibrated with field data.
1. You can develop a proxy relationship between stream slope and stream power to arrive at an estimated D50 using literature derived values of reported grainsize data or attempt a correlation with Shields (which would then necessitate flow and depth data).
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I am trying to model sediment transport through a porous breakwater device in a laboratory tank. Which software would be most efficient in solving sediment transport problems? 
I attached the CFD model wave actions using one software. This software does not have to function to solve sediment transport related problems. I now need to add sediment particles in the water (with the model shown) and measure the rate/mass of transport. 
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OpenFOAM
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a transport model (e.g logit model or ...) is based on statistical data and field works or merely based on mathematical theories or both of them?
If I want to define a model ( e.g. a new model in freight transportation ), what actions should I do? what kinds of data should I gather?
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Obviously you need to define in detail which parts of the enormous system, that we may call "the logistics network." What do you want to capture with your model?
Also: before you start something new, do you know what parts of this enormous system you would like to provide a model for? You will definitely need to scale down from the global chains of transport and logistics - so what parts are you interested in? What is the purpose of this exercise? Could you, for example, start by reading the recent years of logistics networks papers, so that you can see what the models need, in terms of data, for example? Do you want to collaborate with a logistics partner, in order to obtain real data?
There are lots of questions to be answered, as what model you end up with will determine what questions will be possible to answer. This is not a five-minute exercise, but a PhD project, perhaps with actual partners from logistics.
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I want to use reactive transport for simulation of CO2 storage. We have not selected geological formation yet, but most probably it will be CO2 with Enhanced Oil Recovery or depleted oil reservoir. I am considering two options at the moment: PHREEQC and TOUGHREACT. Which one is better for my case? Could you describe pros and cons of softs mentioned?
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Toughreact is a very good software for mumtiphase reacgive flow, so for CO2 storage it is a good option. However, it is not user friendly and requires a lot of time of pre- and post-processing.
Phreeqc is perhaps the most well known geochemical simulator, but to use ut in your field would require the coupling with a multiphase flow model. There are some options for that, for example the iCP framework, which couples Phreeqc and Comsol Multiphysics. This tool is being used for CO2 storage simulations and is potentially able to include thermo-hydro-chemo-mechanical couplings.
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In the calculation of vapor penetration length multiphase eulerian model with species transport model is the best choice or not? And also how to add injection and breakup model with using above model?
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Following
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Hi
I have run PCA for 3 years of data so by this I got factor scores for each item/subject for every year. Now, I need a single value to use in my model from three values.
Should i take average of factor scores or should i use a recent value? What is an appropriate way to use factor scores for transport delay data analysis?
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Great. You are progressing quite rapidly. Keep Going and good luck By the way Monash Univ. has a great statistics dept. The greatest statistician of all time (R.A. Fisher) is buried there
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Dear All
I just need some urgent guidance at the initial stage of modeling. See below for description
I am having a domain (just a simple box domain). Inside the domain there are some chemical reactions taking place which results in release of heat, water vapor, carbon-di-oxide and ammonia. I want to disperse the CO2, NH and the water vapor out of the domain
Now i am blowing dry air through one end of the box which will help me carry away the contaminants (CO2, NH and water vapor). The other end of the box is exposed to atmosphere. So one side is Velocity Inlet(for air), other side is pressure outlet(as exposed to atmosphere).
I want to study the effectiveness of the air at a certain velocity to disperse the contaminants
I am not sure which model should i go for VOF or species transport model in ansys fluent?
Kindly advise
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Dear Nikhil,
You need to opt for species transport model with all the equation with reaction terms.
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Hello,
I will need to implement Transport Mode Detection (TMD) on a smartphone accelerometers, gps, etc. in order to detect if the user is traveling on foot, on bicycle, by car, by bus, etc. Here are my two questions:
1) Is there some public data available to train and benchmark algorithms for this task?
2) Is there some commercially usable libraries/services implementing TMD? Something under MIT licence would be great but commercial solutions could also work.
Thanks for your time,
Bruno
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I found the Sussex-Huawei Locomotion Dataset
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I want to calculate traffic density of roadways near intersections and also midblock sections on urban roads. I have video recordings for different locations. So, I want to know about any reliable methods to calculate road density from the videos.
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Please prefer to this link. Hope that is useful for you.
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Basically, this is my problem: I have two MATLAB programs, program A is able to calculate the concentrations of chemical species by solving a system of non-linear equations, given an initial value of an input parameter.
MATLAB Program B, uses the value of the chemical species concentrations mentioned in program A and calculates the value of the parameter.
on the other hand, I would like to solve a non-steady state 1D transport model in COMSOL a interval from (0,L) at all the nodes of my geometry.
I would like to couple MATLAB with COMSOL in such way that the initial concentrations provided by the MATLAB program, can be used as the initial concentrations in my COMSOL transport model, solve my transport equations and move to the next node and time step and use now the concentrations obtained by COMSOL and feed them into the MATLAB program to calculate again the desired parameter.
And I would like to continue solving the model through all the geometry distance.
Thank you very much for your comments and suggestions.
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Attached is a regression model by full factorial design which has 4 factors and 144 runs..But the final equation too long and adjusted-R is not feasible.
How can I find the best equation and fitted model in Matlab?
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For latest information see the attached. Best, D. Booth
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I have started working on the above mentioned model, I would like if someone can guide me on this, how to pursue this modelling by use of some kind of software.
Thank you
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For a 3-D numerical model, you can model groundwater hydraulics with MODFLOW. Then, that output can be used to model contaminant transport with MT3DMS. Both models are freely available from USGS. However, it is advisable to use a GUI to operate the models. Commercial software for this exists. For example, GroundwaterVistas. The licenses are expensive, though. USGS offers some free operating software (MODELMUSE), but they won't be as easy as commercial GUI (but free!). Check out USGS website: https://water.usgs.gov/nrp/software.php
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I want use the libradtran to calculate the aerosol radiation effects. So, I intend to import the outputs from atmospheric chemistry transport model to the libradtran. Who can tell me how to dispose? Thank you!
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Ok. Thanks for your reply!
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In the bubble column reactor, gas phase is dispersed into the reactive liquid solution. then, the gas is dissolved in the liquid and react with a specie in the liquid phase. bubbles in the column decreases in size because of mass transfer of gas into the liquid.
In the CFX which model should be used for gas phase? (dispersed fluid model or particle transport fluid model)
can anyone explain the required specification for this system?
Thank you
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Your basic question is, whether to use an Euler-Euler modeling scheme of Lagrange particle tracking (LPTM) of bubbles?
The main issue with using LPTM for bubble columns is, that in its basic formulation the LPTM is not taking into account the volumetric extend of bubbles. It works with the abstraction of mass points for tracked bubbles. There are some tricks and approaches to overcome this underlying limitation, but people were not very successful with that in the past, because than the CFD simulation quickly becomes much more demanding than an Euler-Euler modeling approach, i.e. a very large number (in the order of many millions of bubbles) are required and computational time intensive iterative coupling between the tracked particles and the fluid motion.
Consequently most work on bubble columns was done in the past using Eulerian schemes. You will find the appropriate set of fluid-bubble interaction models by downloading and reading some of the many publications which are stored here at Research Gate under my own account. Publications by Eckhard Krepper and the research group at HZDR, Dresden-Rossendorf, Germany might be a very good reference as well. Publications include vast validation of all these bubbly flow models, so that with this very well tested set of models you should be on the safe side for your modeling and you will be able to concentrate to incorporate in addition the effects of chemical reactions.
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Hydrodesulfurization in packed beds takes place according to the following general reaction:
Sulfur Compound (ArS) + 2H2 --- H2S + Aromatic (Ar)
The kinetic rate is given by:
rHDS = (−KHDS) [ArS]^1.6 * [H2]^0.56 / (1+kad * [H2S]) [kmol/(kgs • s)]
The adsorption coefficient (kad = 50, 000 [m3/kmol]) does not depend on the temperature.
KHDS = 2.5•10^12 • exp(-19.384/Ta) [(m3)^2.16/(kg •(kmol)^1.16 • s)]
The geometry is a 3D cylinder and assembly meshing gives me a minimum orthogonal quality of 0.92, which is a desirable mesh. I have activated the Eulerian 2 phase and species transport models, and selected the mixture template for both the phases in the species transport model. Next in the materials section, all four materials (ArS, H2, Ar, and H2S) are defined inside the mixture template. The porous media is selected in the cell zone conditions and the appropriate UDF is loaded for the same.
Following this step I have attempted two different ways to execute the simulation:
1. Selecting mixture template for both gas and liquid phases and defining the materials in the same. Then, defining the reaction by defining the stoichiometric coefficients in the mixture template in the materials section. The following UDF for the reaction rate taken from the ANSYS manual was modified according to my reaction and defined and loaded as a function hook:
#include "udf.h"
#include "mem.h"
#define KHDS 0.005083992078
DEFINE_VR_RATE(vol_reac_rate,c,t,r,mole_weight,species_mf,rate,rr_t)
{
begin_c_loop(c,t)
{
real X_ars=C_YI(c,t,3)*C_R(c,t);
real X_h2=C_YI(c,t,1)*C_R(c,t);
real X_h2s=C_YI(c,t,0)*C_R(c,t);
if (FLUID_THREAD_P(t) && THREAD_VAR(t).fluid.porous)
*rate=((-KHDS)*(pow(X_ars,1.6))*(pow(X_h2,0.56)))/(1+(kad*X_h2s));
else
*rate = 0;
*rr_t = *rate;
}
end_c_loop(c,t)
}
2. Selecting two different templates to define the materials and following the remaining steps as it was in point no. 1.
I am using ANSYS Fluent for the simulations and maintaining a time step size of 1e-08, but there is no change in the mass fraction of the reactants. In other words the mass fractions of ArS and H2 are 1.0 throughout the simulation and mass fractions of Ar and H2S are 0.
Any kind of support regarding this would be reallyhelpful.
Thanks.
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Performing calculations with the assumption of plug flow and additionally assuming that the process takes place in one phase - the gas phase, will allow you easily to test the kinetic equation. The mass balance equation will take the form:
ArS/dz = (mc/(FovcArSo)) rArSArS), αArS(0) = 0,
where αArS - conversion of ArS, z = m/mc, mc - total mass of catalyst, FoV - volumetric flow rate, cArSo - initial concentration of ArS.
It is necessary to know the values of cArSo, cH2o, FoV, mc and temperature for calculations. It is also necessary to specify the stoichiometric equation (in particular, the number of hydrogen moles), because without this the stoichiometric analysis will be impossible. Regards,
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Hello guys, currently i am doing a simulation regarding the mixing between two fluids in a mixing channel. I am validating my model against an experimental work. The case is in 3D and i am using laminar model. In addition, i m using species transport model for the mixture. However, for my simulation cases, it failed to capture those swirling flow that can be observed from the experimental work. is there any solution or setting which can help me to capture those swirling flow in my visualization result? The visualization results are attached as below: top (present simulation), bottom (experimental work)
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The flow is unsteady, I wonder if you have waited enough in the simulation to let the flow to develop fully.
However, you should also check carefully if the the experiments is correctly modelled in your simulation by proper BCs.
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The most promising combination of models for freight transport forecasting and evaluation in my view is a fast and relatively straight forward policy analysis model, developed as a system dynamics model and/or a model integrating outputs from other more detailed models.
Can you share research papers related to this.
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Can anyone give reference procedure or an illustrative example for the estimation of OD Demand matrices through CUBE.
Probably they are estimated through extension CUBE Analyst/Analyst Drive.
Input Data available to me: A prior yearly OD matrix & Traffic Counts (Not Average values)
And lastly, how are the results of output matrix. Are the results reliable and statistically significant?
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followed
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I am working on the heptane simulation in a constant combustion chamber. I have created a reduced chemkin pro file (192 species and 1112 reactions) from a detailed one.
I want to inject heptane spray into a pressurized closed chamber to create chemical reactions and combustion. For that I have prepared every think (geometry, mesh, boundary conds, ..).
I applied these set up in Fluent:
1. Energy equation
2. k epslon viscous flow model
3. operating condition of chamber 21 bar
4.constant temperatures at chamber walls
5. Air is taken as an ideal gas
Run for steady state to get the initial condition, Then:
a. Change to unsteady state
b. using species transport model -imported chemkin mechanism (reduced heptane file)
c. using DPM to create heptane injection (used point cone)
d. apply time step size and number of them and run calculation
I got the spray but no combustion?
Should I use another species model or what to do?
The help is really appreciated.
Osama
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For semiconductor transport modelling using the drift-diffusion equations, the Scharfetter-Gummel discretization for the current flow equations appears everywhere.
Is there a particular reason why this method is so overwhelmingly popular as compared to the many other techniques available and used in the fluid dynamics community (Galerkin Least Squares stabilization appears to be one)?
I'm given to understand that the Scharfetter-Gummel scheme makes it easy to get stable differences in regions of exponentially varying carrier densities. Are there any known alternative schemes?
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Nice comments, Alrik Stegmaier. I have to add one detail for 2D and 3D drift-diffusion simulations. When using triangular meshes in 2D, for instance, one has to avoid at all costs the presence of obtuse angles. This is known to degrade the numerical discretizations and invalidate conservation of charge/current. Some of the most prominent groups (e.g. Fichtner's at ETH) have shown that density may spike unphysically near the obtuse triangulation. It may be a particularly bad problem when both electron and holes are included in the model. If I remember correctly one may see huge spikes of minority carriers. A similar issue with rectangular discretization arises when rectangles are too skinny. The rule of thumb is that the aspect ratio between the sides of the rectangle should never exceed 10.
In 3D, tetrahedral discretization is even more complicated, because it may be quite difficult to avoid the equivalent of obtuse angles in 3D. Again, the work by Fichtner's group showed ways to develop safe gridding. These approaches are in some of the major commercial software (Fichtner's company, ISE, merged with Synopsys years ago). If you are interested, you can start from the original work in the early 1990's by Paolo Conti, developed for his thesis with Fichtner at ETH. This work is referenced in Research Gate.
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Hello guys, i am new to CFD ANSYS FLUENT, currently i am doing a simulation regarding the mixing between two types of water streams from two different inlets. I am using species transport model to simulate my case. At first, i am trying to output the mass fraction at one of the output plane in the mixing channel. But i have found that the mass fraction of species A at the plane is very small (Near to zero, 10^-30) even though the mass fraction of species A from the inlet is equal to 1. Afterwards, when i change the setting in the mixing template---> Density---> Volume-weighted mixing law, the mass fraction of species A in the output plane becomes larger (10^-2), but the solution is not converging even after i reduce the relaxation factor. Is there any inappropriate settings that i have set in my case? or is there any way to resolve the converging issues ? The details of my settings are shown as below:
Model : 3D, viscous laminar, species transport
Materials : species A (from inlet 1, mass fraction of A =1), species B (from inlet 2, mass fraction of A =0), species B is the bulk fluid
Inlet Velocity : Inlet 1 and 2 have the same inlet velocity=0.01m/s
Solution methods : PISO, second order for all spatial discretization
Any help or guidance are much appreciated!
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Hello everyone, I have found the root of the problem. The low concentration of species A at the output plane is due to insufficient time for the species to reach the plane from the inlet as i am using a very time step size. Hence, now i resolve the problem by using a larger time step size.
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Hello guys, i am new to CFD ANSYS FLUENT, currently i am doing a simulation regarding the mixing between two types of water streams from two different inlets. I am using species transport model to simulate my case. At first, i am trying to output the mass fraction at one of the output plane in the mixing channel. But i have found that the mass fraction of species A at the plane is very small (Near to zero, 10^-30) even though the mass fraction of species A from the inlet is equal to 1. Afterwards, when i change the setting in the mixing template---> Density---> Volume-weighted mixing law, the mass fraction of species A in the output plane becomes larger (10^-2), but the solution is not converging even after i reduce the relaxation factor. Is there any inappropriate settings that i have set in my case? or is there any way to resolve the converging issues ? The details of my settings are shown as below:
Model : 3D, viscous laminar, species transport
Materials : species A (from inlet 1, mass fraction of A =1), species B (from inlet 2, mass fraction of A =0), species B is the bulk fluid
Inlet Velocity : Inlet 1 and 2 have the same inlet velocity=0.01m/s
Solution methods : PISO, second order for all spatial discretization
Any help or guidance are much appreciated!
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Dear El-Hachemi Amara, I have found the root of the problem. The low concentration of species A at the output plane is due to insufficient time for the species to reach the plane from the inlet as i am using a very time step size. Hence, now i resolve the problem by using a larger time step size.
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Hello guys, currently i am doing a simulation by using species transport in ANSYS FLUENT...however, i have found that if i change the setting from steady to transient model, the concentration of one of the species at the outlet became relatively small (10^-250)...i was wondering is it species transport model cannot be applied in transient case? The settings of my case is shown as below:
Inlet 1: fluid A Inlet 2: fluid B (Bulk species)
Output results (mass fraction of A) at the outlet: Steady case: 0.5-0.6 Transient case: 0
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Mr. Mamdouh, i have found the solution for my problems, the root of the problem is due to insufficient time of the concentration of species A to reach the output plane as i was using a very small time step size. Now i have resolved the problem by using a larger time step size.
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Non premixed is understood theoretically but practically (physically) I am unable to imagine what is species transport model.
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Hi Anirudh Singh,
The difference between the "species transport model" and the "non premixed model" has been explained clearly in the "Theory Manual of Fluent". It seems to me that you did not check the "Theory Manual and User manual" of Fluent in a careful manner.
However, let's assume that you would like to simulate "CH4-Air non-premixed combustion" event in a domain of your interest by employing the "detailed reaction mechanism" of GRI-Mech 3.0. (http://combustion.berkeley.edu/gri-mech/version30/text30.html).
In this reaction mechanism, 53 species are involved! So, in order to predict the transport of all species (53) and their consumption/production in the combustion zone, technically, you have to solve the conservation equation of all Chemical species involved in your system (in this example, it is 53). If you want to do so, then you have to use the "Species transport model" in Fluent.
On the other hand, the "Non-premixed combustion model" of Fluent, which does not solve the conservation equation for individual species during the simulation of the "non-premixed combustion" event in the combustors. Instead, the concentration of individual species (and the associated issues with the chemical species) involved in the combustion system is estimated from the predicted "mixture fraction fields". After this point, naturally, a question would arise in your mind: What is the mixture fraction field? It can be addressed here (!), but I am not going to address it here as it is available in the open literature of Combustion. If you are really interested in this topic, then please take a look at the books on "Combustion" (any book of Combustion will be fine!). Anyway, all the best for your research.
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Transport models are classified as Lagrangian and Eulerian models. Both are functioning in different manner. What are the major difference between these two models? Which one is the best method to describe the transport of CO2 in the atmosphere?
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In order to complete this interesting debate it is quite relevant to mention the semi-Lagrangian models where the advection step is accomplished in the Lagrangian frame of reference with the trajectories originating at the fixed set of points usually coinciding with a grid system. The concentrations are then remapped after each time step back to the Eulerian frame of reference. There are numerous examples of semi-Lagrangian Chemical Transport Models (SL CTM). The main advantages of SL CTM include computational efficiency, natural incorporation of the sub-grid-scale sources and flexibility of including different parameterizations of physical processes and chemistry.
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Passenger drones are sometimes heralded as the new miracle solution to traffic congestion. But one can just as well argue that, together with other automated transport technologies, they will just induce new traffic and congestion will move from the roads to the skies. I wonder whether there is any systematic thinking about this ongoing already, both in terms of policy work and in terms of transport modelling.
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Thanks for the tip Scott.
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I have carried out the inbound & out bound survey of region and having the details of all different vehicle trips, Now I would like to convert these data of vehicle trips in to persons trips, so what are the ways / IS codes / standard codes of converting vehicle trip data in to person trip data ? 
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Dear Prof.
Would you be able to provide me with the code? Actually I need this information the other way round meaning I need to find a factor to convert person trips into vehicle trips....
Regards,
Alireza
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In the simulation of railway vehicle driving profile, coupler force calculation is required. Without the real time data, how to calculate coupler force coefficients and forces.
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Please go through the below article which contains the useful references and information related to this question:
Second-order sliding mode controller with model reference adaptation for automatic train operation
Article, Jun 2017, Vehicle System Dynamics, 10.1080/00423114.2017.1330482
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Can soil column experiments for contaminants transport be used to validate VLEACH model since, the minimum time step for this model is 1 year. Whereas the samples from column study are analysed at hourly or daily basis. 
I would like to know how to correlate the results for this case.
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May be next research ya Mr Saiful.
best regards,
Nurrohman
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Unlike pollutant transport modeling in soil, and water bodies, where it is possible to predict the pollutant levels at any given point at a given time period, the air pollutant dispersion models lack the time factor. 
Are there any models, where in the downwind pollutant concentration be predicted at a given time?
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most Air models  provide dispersion as a function of down wind distance..  The dispersion coefficient is a function of distance from the source.  Time can be introduced by  using the idea that Time = X/U where X is distance from source and U is wind speed. In these models the minimum time is usually 10 to 15 minute averages to account for all of the dispersion.The EPA  CALPUF  model follow the individual puffs from a source as a function of time. 
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see above
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4 steps model is usually used all over the country. it is easy to use but this model has some disadvantage too.  for this model, we need data for 2% of total population. so that it is too costly in higher population country. there are some model also but those are not easy for their algorithm.  
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I am working on Simplified Trip on Project Software(STOPS) which is for the estimation of transit demand. Unfortunately, I could not find any resource to find this software conceptually, although it is easy to work. If any one understands this chart conceptually, please explain.
Also, I found that highway supply part is computed by following formula:
PMHT(I,J) = ∑ [highway person-trips(i,j) x highway distance(i,j) + auto-access trips(i,j) x auto-access distance(i,s)]
Where:  I, i = production district and zone
 J, j = attraction district and zone
 s = stop used for park-ride or kiss-ride access
 ∑ = sum over all i,j within each I,J 
PHMT change(I,J)  = Build PMHT(I,J) minus No-build PMHT(I,J)
And the Home-Based-Work part for demand:
Normalized CTPP transit share x [C x t(a) x CTPP workers(a)]
= linked HBW transit trips in rider-survey datasets
Can anyone introduce some resources that explain these formula and their usage to know about the inputs and outputs?
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Probably the transit flow (n representing the number of vehicles). Did you have a look to http://i26alt.org/wp-content/uploads/APPENDIX_6C_Travel-Demand-Forecasting-Memorandum.pdf ?
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A more economical and alternative approach for gathering aquifer parameters such as regional aquifer extent, recharge and discharge points, flow direction and velocity, hydraulic permeability, thickness etc. 
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Hi,
I am working on optimization approaches on an intersection. And I have been getting some questionnable results on the simulator. I get some high troughputs of vehicle in the intersection but with big average delay of vehicles e.g : 
In a scenario I get a throughput of 4544 with an average delay of 31.22 seconds and average queue length per phase of 41 meters
And in another scenario I get a 4551 throughput with an average delay of 31.26 seconds with an average queue length per phase of 39.68 meters
This compared to the average study of the same intersection we see different results, e.g  in a scenario a throughput of 4343 with an average delay of 30.7 seconds and an average queue length per phase of 21.1 meters.
I am starting to question my results performance. Doesn't higher throughput mean minimum average delay and lesser queues on lanes ?
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Dear Saad,
There is a mathematical theorem linking some quantities: Little's law for queuing systems isL=λW: the average queue length equals the average arrival rate times the average waiting time in the system.
It means you should not diverge too much from that without clearly violating at least one hypothesis. Usual deviations are:
  • bad definition/calculation of quantities (throughput...)
  • using the wrong quantities (what is the delay?)
  • your system is not stationary (i.e. the simulation is not long enough or you don't cut the first part that is usually very non-stationary)
  • you do not compare the same quantities.
Then, I can discuss more about interpreting results, because cooperative intersection is a topic I have highly investigated. But before going to theory (optimization criteria, mathematical tools, hypotheses...), check the simple issues I have mentioned.
Best regards,
Arnaud
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Usually the ride comfort is evaluated in terms of rms acceleration at seat level. Our (my) experience is that, the ride is more uncomfortable due to jerk than acceleration.
Is there any work on the effect of jerk on ride comfort ?
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For European values, the requirements are in EN 13803
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Essentially, this relates to the mathematical problem of naturally poor correlation between low value continuous values (e.g. 0.003) with discrete values (0, 1, 2, etc). Has anyone come up with a workable solution to this in road safety?
I attach a map of local road crashes in parts of Melbourne, Australia, to demonstrate. The local roads (within the squares defined by arterials) have hardly any crashes. Models come up with low values no matter how good the model is. Poor correlation/model fit is guaranteed. Solution?
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Amir, big thanks for a very comprehensive answer. These are all techniques we considered or used at one time or another. i think Markov Switching models is something I'll look into more closely. 
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The question refers to workload management from different perspectives: organisational, individual, operational demand. I'm just interesting in different viewpoints on this question
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Thanks!
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Hello freinds,
I want to generate mobility (nodes movements) and  create traffic pattern for 100 nodes in leach protocol but i don't knouw what's the parameters i can give to setdest command and cbrgen.tcl/tcpgen.tcl.
how I can use to configure the parameters bonnmotion ?
Thanks
Have a nice day
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thank you Dear kolita for the answer
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metro train services suffers delay or cancellation in services due to mechanical failures. am interesting to evaluate the most critical failure that often become cause of interruption in service. which technique is best to use between FMEA and FTA? What's criteria of selection?
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A variety of ways of assessing reliability / survivability are covered in good research by Kim and Song (and there are other papers using this reliability approach)
"Examining Accessibility and Reliability in the Evolution of Subway Systems"
It is available here
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I want to build a system for managing traffic lights.
Genetic Algorithms will optimize green times according to recent congestion and road priority.
I had already a touch with GA by implementing 0-1 knapsack problem,
but in this case i really dont know how to implement this in order to output optimized timings for a intersection (4 roads / 4 lights)
I would appreciate any help as a roadmap.
Thank you. 
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Don't forget to reach out to the authors of this research:
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Hello there,
I am new to the combustion analysis. I am working on a simulation of a rotary compression ignition engine on Fluent. The problem description is as below.
The air enters in the combustion chamber at 350K. Diesel is sprayed at 300K. The mixture gets compressed and temperature increases to around 800K and pressure increases to 32 Bar. I tried the whole simulation with the Species transport model by keeping volumetric reaction (Eddy dissipation) enabled. Next when I try to plot the species graph for mass fraction of Co2 and Mass fraction of H20, it shows zero.
My question is: Is there still no burning of fuel due to high pressure ?
or the model I am using is inappropriate ? I am really need your suggestions.
Thank you in advance. 
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Thank you Shubham. 
I will try doing so. I was just wondering if you know any link where I can find the auto ignition temperature of C10H22 at 30 bar pressure ? Because I doubt that my pressure is high as 30bar and temperature is 800K. At this temperature with 30Bar pressure, C10H22 might not get its auto ignition. If you know something about this, please let me know.
Thank you,
Parth
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Dear colleagues!
I'm developing a tool building (near-) optimal routes for an existing set of vehicles which serve a fixed hub-and-spoke network with two hubs. A mathematical formulation of the corresponding problem is required. Which papers would you recommend to consider?
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Maybe the following literature survey is helpful for you as a starting point:
Cuda, R., Guastaroba, G., and Speranza, M. G. (2015). A survey on two-echelon
routing problems. Computers & Operations Research, 55:185–199.
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I am trying to develop a overtaking behavior micro-simulation  model for non lane based heterogeneous traffic environment using VISSIM to define the number and nature of conflict. I am planing to use COM interface. How can I proceed from the very beginning and what type data need to be collected? Any manual or tutorial is appreciated (if available). 
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I wonder if you really mean non-lane based mixed traffic. Without lanes and if bigger vehicles (trucks) occupy more lateral space than smaller vehicles (particularly motorcycles and the like), the notion of lane changing becomes meaningless. Instead, it is replaced by a continuous lateral motion  with the objective of passing at a later time. This means, rather than using a car-following and associated  lane-changing model, one has a fully two-dimensional dynamic model. Notice that the ynamics of this situation iressembles more unidirectional pedestrian flow rather than classical lane-based vehicular traffic.
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i mean the use of PHREEQC model without the coupling of other hydrological (maybe?) models.
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I have one paper, which is attached. I would review the PHREEQC webpages http://wwwbrr.cr.usgs.gov/projects/GWC_coupled/phreeqc/. I think they have mailarchive and FAQ that have some info on prior applications.
Also, the other USGS model for surface water reactive transport is OTIS http://water.usgs.gov/software/OTIS/ and there may be some way to couple them.
Other models coupled with PHREEQC include PHT3D http://www.pht3d.org/pht3d_about.html, PHAST http://wwwbrr.cr.usgs.gov/projects/GWC_coupled/phast/, and HP1 http://www.pc-progress.com/en/Default.aspx?h1d-hp1 , but these are generally for groundwater.
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Hello there,
I am modeling an evaporating spray. The problem description is as follows. 
There are two inlets into the flow path. One is air inlet and other is diesel inlet (Spray). Diesel is at 300K temperature and air is at 350K temperature.  I am using species transport model with the DPM. I have few queries for the problem mentioned.
1. I am using species transport model with the diesel-air mixture. When I select this model, by default it takes cell zone fluid as diesel-air. But in real, initially there is only air. Then spray of diesel starts at a particular time. Can anybody suggest me the right way to do this ?
2. Is there any other way to model the evaporating spray without using species model ? I am not interested in to the species and chemical equilibrium at this stage. I am using this model just because I can select the droplets in the DPM model. If i do not select species model, I will have only one option in the DPM, that is Inert.
Thank you in advance.
Parth 
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I suppose diesel-air is a mixture that you define in the Materials tab. The properties of the mixture are calculated based on the volume fractions of all elements (air and diesel in your case) in each computational cell. So if you initiate the calculation with pure air, there is really only pure air. Fluent takes it as diesel-air mixture with zero fraction of diesel, which is the same. Once you inject diesel, the properties change according to the diesel volume fraction.
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In the following reference,
Todosiev, E.P., 1963. The action point model of the driver-vehicle system (Doctoral dissertation, The Ohio State University).
on page 16, an idealized relative acceleration-relative speed diagram is shown (figure 1 attached below). On this figure, the vertical axis is:
relative acceleration = acceleration of lead vehicle - acceleration of following vehicle.
And the horizontal axis is:
relative speed = speed of lead vehicle - speed of following vehicle
The assumption is that the lead vehicle is moving at uniform speed, therefore the change in the relative acceleration is brought about only by the acceleration of following vehicle. Following is the definition of action point in the above reference:
"The action point is defined as the point where the acceleration changes sign".
In the figure 1, the sign of acceleration at point A changes only because the following vehicle decelerates. So, the action point is A. It is easily identifiable on figure 1 using da-dv diagram.
But in the observed vehicle trajectories, the lead vehicle does not move at a uniform speed. Consider figure 2 which is a smoothed version of an observed vehicle trajectory. The axes are same as figure 1, except the units.
What should be considered an action point now? 
1) Is it the point where relative acceleration changes sign?
2) Is it the point where the relative acceleration changes magnitude (regardless of sign)?
3) Or do we have to look at the acceleration of following vehicle only to see when it changes sign (and figure 2 is of no use)?
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@Nirmala, Thank you. The second reference is up to the point.
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I was using "Thermodynamic Transport" Model as given in Sentaurus Device Tutorial as "Thermo_des.cmd". It was showing different lattice temperatures in "@node@_des.tdr" file. Temperature was 707 to 745 K. Is this approach correct? If no then how to turn ON self heating?
But if Yes, then how to turn OFF self heating? I have deleted the "Temperature" word from the line "Coupled{ Poisson Electron Hole Temperature }" in three places of "Solve" section. 1) "*- Build-up of initial solution:", 2) "*- Bias gate to target bias", and 3) "*- drain voltage sweep". Then "@node@_des.tdr" file is NOT showing different lattice temperatures. It is 300 K. But the problem is drain current has decreased.
We know that higher temperature changes the temperature dependent material properties like band-gap and mobility, leading to the degradation of device performance. The reduction in mobility leads to a reduction in output current as the operation voltage is increased.
But in my case self heating off showing lower current and self heating on showing higher current.
I was simulating an NMOSFET of conventional structure taking parameters from ITRS 2013.
Please inform how to do self heating ON and OFF.
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Actually, when you just add "thermodynamic" without including any temperature-dependent mobility models, thermodynamic tutorial has higher drain current than drift-diffusion because of band-gap narrowing and carrier-generation.
Well... there is an other method to force the limit called "lT_Range" but I am not sure whether this works or not.
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I am modeling a corridor with eight 4 leg and one RCUT intersection. the corridor is coded in VISSIM. I used the SSAM, but does it work for RCUT intersections too? The values I get are not very convencing, Is there any other way to measure safety from VISSIM output?
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We have assisted Minnesota DOT with the calibration of their HSM predictive models. They should have calibration factors for Rural two lanes, and rural multilane.
The beauty of the HSM Part C is that you can apply the HSM predictive models to estimate the predicted number of crashes as a function of exposure and geometric elements of the site. You can adjust the prediction to Minnesota conditions by applying the local calibration factors. I would just calculate the prediction using the 2040 volumes for the no build condition, and then apply the CMFs to the prediction to come up with the RCUT safety performance.
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I am interested in applying UNA to Colombo. But still I could not find the exact way of doing it. The available tutorials in the internet only explain the GIS steps in applying it. I am worried on preparation on the weighted attribute table. So if anyone can help me in finalising the required database for the UNA will help me a lot
Thanks
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You can create by arcgis network analys, but which one type you want to analys? Because every type need different variables..