GfsOutputScalarStats
From Gerris
GfsOutputScalarStats is used to write the volume-weighted statistics over the whole domain of a given scalar.
The statistics are written using the following formatting:
DESCRIPTION time: T min: MIN avg: AVG | STDEV max: MAX
with:
DESCRIPTION
- a description of the scalar field (without any spaces),
T
- the physical time,
MIN
- the minimum value,
AVG
- the volume-weighted average value,
STDEV
- the volume-weighted standard deviation,
MAX
- the maximum value.
The syntax in parameter files is:
[ GfsOutputScalar ]
Examples
- Savart--Plateau--Rayleigh instability of a water column
- Forced isotropic turbulence in a triply-periodic box
- Tsunami runup onto a complex three-dimensional beach
- The 2004 Indian Ocean tsunami
- "Garden sprinkler effect" in wave model
- Cyclone-generated wave field
- Conservation of diffusive tracer
- Coriolis formulation in 3-D
- Wind-driven lake
- Circular droplet in equilibrium
- Axisymmetric spherical droplet in equilibrium
- Scalings for Plateau--Rayleigh pinchoff
- Sessile drop
- Dielectric-dieletric planar balance
- Balance with solid boundaries
OutputScalarStats { istep = 1 } r {
v = (T > 1e-2 && T < 1. - 1e-2 ?
(sqrt((Y + 0.5)*(Y + 0.5) + (Z + 0.5)*(Z + 0.5))/RADIUS - 1.)/EPSILON : 0)
}
OutputScalarStats { istep = 1 } k { v = K }
OutputScalarStats { istep = 1 } kmax { v = Kmax }
OutputScalarStats { istep = 1 } log { v = Unbar }
OutputScalarStats { istep = 1 } log { v = U }
OutputScalarStats { istep = 1 } Reynolds.dat {
v = 2./3.*FluctKinEn/VOLUME/MU*sqrt(15*MU/(Dissipation/VOLUME))
}
OutputScalarStats { istep = 1 } Dissipation.dat { v = Dissipation/VOLUME }
OutputScalarStats { istep = 1 } Energy.dat { v = FluctKinEn/VOLUME }
OutputScalarStats { istep = 1 } Vorticity.dat { v = Vorticity }
OutputScalarStats { istep = 1 } p { v = (Zb > 0. ? P : P + Zb) }
OutputScalarStats { istep = 1 } p { v = P }
OutputScalarStats { step = 12 } hs-MINLEVEL-NTHETA { v = Hs }
OutputScalarStats { step = 0.25 } hs { v = Hs }
OutputScalarStats { step = 0.25 } vr { v = sqrt(U10*U10 + V10*V10) }
OutputScalarStats { istep = 1 } t { v = T }
OutputScalarStats { istep = 1 } te { v = T }
OutputScalarStats { step = 3000 } { awk '{print $3, $7}' > u.dat } { v = U }
OutputScalarStats { step = 3000 } { awk '{print $3, $7}' > v.dat } { v = V }
OutputScalarStats { step = 3000 } { awk '{print $3, $7}' > w.dat } { v = W }
OutputScalarStats { istep = 10 } { awk '{print $3,$7}' > error.dat } {
v = sqrt((U - Usol0)*(U - Usol0) + (V - Vsol0)*(V - Vsol0) + (W - Wsol0)*(W - Wsol0))
}
OutputScalarStats { istep = 1 } p { v = P }
OutputScalarStats { istep = 1 } {
awk '{ print MU*$3/(0.8*0.8), $5, $7, $9, $11 }' > K-LAPLACE-LEVEL
} { v = (K - 2.50771) }
OutputScalarStats { istep = 1 } {
awk '{ print MU*$3/(0.8*0.8), $5, $7, $9, $11; fflush (stdout); }' > K-LAPLACE-LEVEL
} { v = (K - 2.50771) }
OutputScalarStats { istep = 1 } p { v = P }
OutputScalarStats { istep = 1 } y { v = Y format = "%10.6e" }
OutputScalarStats { istep = 1 } k { v = K }
OutputScalarStats { istep = 10 } k { v = (T > 0.05 && T < 0.95 ? K : NODATA) }
OutputScalarStats { start = end } p { v = P }
OutputScalarStats { start = end } ey { v = Ey }
OutputScalarStats { start = end } p { v = P }
OutputScalarStats { start = end } ey { v = Ey }