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
CFL = 0.8/2.784*0.2
+TimeStep = 0.0
+NumSteps = 100
+IO_InfoSteps = 100
+IO_CheckSteps = 0
+SteadyStateTol = 1e-7
+ +Gamma = 1.4
+GasConstant = 287.058
+ + +pIn = 1e5
+pOut = 0.83049*pIn
+TIn = 288
+MachIn = 0.239543
+ +rhoIn = pIn/(GasConstant*TIn)
+cIn = sqrt(Gamma*pIn/rhoIn)
+vIn = MachIn*cIn
+pStagIn = pIn * (1 + (Gamma-1)/2 * MachIn^2)^(Gamma/(Gamma-1))
+rhoStagIn = rhoIn * (pStagIn/pIn)^(1/Gamma)
+ +rhoInf = 1.225
+pInf = pIn
+vInf = 1
+uInf = 0
+ + +Skappa = -4.5
+Kappa = 1.5
+mu0 = 2
+SensorOffset = 2
+ + +FilterAlpha = 36
+FilterCutoff = 0.0
+FilterExponent = 16
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
CFL = 0.8/2.784*0.2
+TimeStep = 0.0
+NumSteps = 100
+IO_InfoSteps = 100
+IO_CheckSteps = 0
+SteadyStateTol = 1e-7
+ +Gamma = 1.4
+GasConstant = 287.058
+ + +pIn = 1e5
+pOut = 0.83049*pIn
+TIn = 288
+MachIn = 0.239543
+ +rhoIn = pIn/(GasConstant*TIn)
+cIn = sqrt(Gamma*pIn/rhoIn)
+vIn = MachIn*cIn
+pStagIn = pIn * (1 + (Gamma-1)/2 * MachIn^2)^(Gamma/(Gamma-1))
+rhoStagIn = rhoIn * (pStagIn/pIn)^(1/Gamma)
+ +rhoInf = 1.225
+pInf = pIn
+vInf = 1
+uInf = 0
+wInf = 0
+ + +Skappa = -4.5
+Kappa = 1.5
+mu0 = 2
+SensorOffset = 2
+ + +FilterAlpha = 36
+FilterCutoff = 0.0
+FilterExponent = 16
+TimeStep = 1e-5
+NumSteps = 100
+IO_InfoSteps = 100
+IO_CheckSteps = 0
+SteadyStateTol = 1e-7
+ + +Gamma = 1.4
+GasConstant = 287.058
+ + +pIn = 1e5
+pOut = 0.83049*pIn
+TIn = 288
+MachIn = 0.239543
+ +rhoIn = pIn/(GasConstant*TIn)
+cIn = sqrt(Gamma*pIn/rhoIn)
+uIn = MachIn*cIn
+pStagIn = pIn * (1 + (Gamma-1)/2 * MachIn^2)^(Gamma/(Gamma-1))
+rhoStagIn = rhoIn * (pStagIn/pIn)^(1/Gamma)
+ +rhoInf = 1.225
+pInf = pIn
+uInf = 1
+ + +Skappa = -4.5
+Kappa = 1.5
+mu0 = 2
+SensorOffset = 2
+ + +FilterAlpha = 36
+FilterCutoff = 0.0
+FilterExponent = 16
+