# [Lagrangian] Injection Model Start of Injection timestep Mistake?

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 June 27, 2014, 04:37 [Lagrangian] Injection Model Start of Injection timestep Mistake? #1 New Member   Emeline Noel Join Date: Dec 2013 Location: Paris Posts: 13 Rep Power: 3 Hi everyone, [OF 2.2.2] Looking at the lagrangian injection Model : InjectionModel.C, I find in the membre function PrepareForTheNextTimestep something I don't Understand : // Make times relative to SOI scalar t0 = timeStep0_ - SOI_; scalar t1 = time - SOI_; In my mind, because timestep0_ is the last time step, so the first delta Time between current time and SOI is miss, indeed function parcelsToinject require t0 > 0 so in my mind, if SOI = 0.5 at first step time =1 (dt=1) timeStep_0=0 so t0=-0.5 so no parcel to inject ... [But we want to inject parcel, no?] at second step time time =2 timestep_0 = 1 so t0 = 0.5 and t1 = 1.5 so inject parcel give us t1-t0 = dt =1 But we have forget the first par of injection from SOI = 0.5 to time =1 Is it right? Where is my missunderstanding? If someone can enlighten me, it will be great! Have a nice day!

October 29, 2014, 17:51
#2
New Member

Chris Sears
Join Date: Oct 2014
Location: Boston
Posts: 4
Rep Power: 2
Has anybody looked into this? InjectionModel seems good, but the derived injection model's parcelsToInject disallows time0<0 as you noted Emeline.

e.g. I am using coneNozzleInjection with SOI = 10.010. See log file, the first injection time step 10.0101 is missed...!? May be a bug? (albeit minor I suppose!)

Quote:
 Courant Number mean: 0.1118990122 max: 1.994706046 deltaT = 0.0003471966024 Time = 10.0101 Solving 3-D cloud reactingCloud1 Cloud: reactingCloud1 Current number of parcels = 0 Current mass in system = 0 Linear momentum = (0 0 0) |Linear momentum| = 0 Linear kinetic energy = 0 model1: number of parcels added = 0 mass introduced = 0 Parcels absorbed into film = 0 New film detached parcels = 0 Parcel fate (number, mass) - escape = 0, 0 - stick = 0, 0 Temperature min/max = 0, 0 Mass transfer phase change = 0 Mass transfer devolatilisation = 0 Mass transfer surface reaction = 0 diagonal: Solving for rho, Initial residual = 0, Final residual = 0, No Iterations 0 rho min/max = 1.113112118, 1.171788043 DILUPBiCG: Solving for Ux, Initial residual = 3.337508174e-006, Final residual = 7.54026209e-008, No Iterations 1 DILUPBiCG: Solving for Uy, Initial residual = 5.504945546e-005, Final residual = 6.941799875e-007, No Iterations 1 DILUPBiCG: Solving for Uz, Initial residual = 2.989294024e-005, Final residual = 1.62292623e-007, No Iterations 2 smoothSolver: Solving for C2H5OH, Initial residual = 0, Final residual = 0, No Iterations 0 DILUPBiCG: Solving for h, Initial residual = 6.731643474e-005, Final residual = 8.670916541e-007, No Iterations 1 T gas min/max = 329.6221401, 330.0232519 GAMG: Solving for p, Initial residual = 2.82501963e-005, Final residual = 8.700497101e-006, No Iterations 1 GAMG: Solving for p, Initial residual = 8.700456195e-006, Final residual = 8.700456195e-006, No Iterations 0 diagonal: Solving for rho, Initial residual = 0, Final residual = 0, No Iterations 0 rho min/max = 1.113112293, 1.171788119 time step continuity errors : sum local = 2.836225714e-007, global = -6.787536111e-009, cumulative = -5.346327795e-007 p min/max = 108937, 114760.7215 GAMG: Solving for p, Initial residual = 9.265208855e-006, Final residual = 9.265208855e-006, No Iterations 0 GAMG: Solving for p, Initial residual = 9.265208855e-006, Final residual = 9.265208855e-006, No Iterations 0 diagonal: Solving for rho, Initial residual = 0, Final residual = 0, No Iterations 0 rho min/max = 1.113112293, 1.171788256 time step continuity errors : sum local = 3.02032656e-007, global = -6.781834716e-009, cumulative = -5.414146142e-007 p min/max = 108937, 114760.7215 smoothSolver: Solving for epsilon, Initial residual = 9.471710755e-006, Final residual = 9.471710755e-006, No Iterations 0 smoothSolver: Solving for k, Initial residual = 3.536078672e-005, Final residual = 1.691882988e-006, No Iterations 1 ExecutionTime = 19.562 s ClockTime = 20 s Courant Number mean: 0.11189953 max: 1.994730392 deltaT = 0.0003471966024 Time = 10.0104 Solving 3-D cloud reactingCloud1 --> Cloud: reactingCloud1 injector: model1 Added 34 new parcels Cloud: reactingCloud1 Current number of parcels = 34 Current mass in system = 1.190824736e-007 Linear momentum = (-4.40729446e-010 3.633447476e-011 -1.927799815e-008) |Linear momentum| = 1.928306965e-008 Linear kinetic energy = 1.593230117e-009 model1: number of parcels added = 34 mass introduced = 1.202654311e-007 Parcels absorbed into film = 0 New film detached parcels = 0 Parcel fate (number, mass) - escape = 0, 0 - stick = 0, 0 Temperature min/max = 295.1830963, 365.007777 Mass transfer phase change = 1.182957479e-009 Mass transfer devolatilisation = 0 Mass transfer surface reaction = 0

 November 5, 2014, 21:53 #3 Senior Member     Kyle Mooney Join Date: Jul 2009 Location: Amherst, MA USA - San Diego, CA USA Posts: 278 Rep Power: 9 The answer to your question should lie in the call to parcelsToInject function in one of the InjectionModel derived classes as opposed to looking at the base class. For example, take a look at the PatchFlowRateInjection derived class. You'll see that the parcesToInject() function won't necessarily return a positive value even if t>SOI. Here it introduces some randomness to the injection process while still meeting the concentration criteria you set in the kinematicCloud dictionary. My understanding is the purpose is to remove a timestep dependency to the injection rates. I actually think its a pretty clever implementation. I hope that helps! Cheers, Kyle

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