Slides for A2e FY17 Kickoff Matt Churchfield Mesoscale-Coupled

Slides for A2e FY17 Kickoff Matt Churchfield Mesoscale-Coupled

Slides for A2e FY17 Kickoff Matt Churchfield Mesoscale-Coupled Microscale Simulation of SWiFT Nov 11 Case Study using SOWFA Mesoscale grid cell (as viewed from above) Approach 3-5km Microscale/wind plant domain footprint fits roughly within a single or a few mesoscale grid cell footprints 3-5km Approach 1 (Subject of this work) Approach 2 Outflow Internal mesoscale source terms Mean inflow profiles interpolated from mesoscale weather model + Perturbations to initiate resolved turbulence Laterally periodic boundaries 3 Simulation Details

SWiFT November 8, 2013 case Simulation runs from 12:00 to 24:00 UTC 5 km x 5 km x 2 km domain 10 m resolution 50 M mesh cells run on 1000 cores Coupling method: Internally forced to mean WRF solution o o o Periodic domain Time history of vertical profiles of velocity and temperature are known from WRF Planar averaged mean solution is forced to WRF solution at all time through source terms, turbulence is free to react to the imposed mean shear and temperature profile. Sampling o o Horizontal and vertical slices of velocity and potential temperature at 1 min frequency (to quantify turbulent structural changes) 5 virtual met masts at 2 Hz frequency 4 Fundamental Studies of Inflow Perturbation Using TurbSim and Temperature Perturbations Approach Systematic method to test inflow perturbation strategies: Canonical laterally periodic precursor simulation Once developed, use mean vertical profiles as mesoscale model input and truth solution outflow -Mean vertical profiles -Truth Solution

Inflow/outflow simulation Use mesoscale model input mean vertical profiles from precursor Apply different perturbations to the smooth mean vertical profile input Monitor development of resolved turbulence with downstream distance Are downstream mean profiles/statistics same as the truth solution? mesoscale + = perturbation inflow input 6 Approach TurbSim o NREL-developed synthetic inflow generator. o Creates space and time-correlated turbulence that follows the Kaimal spectrum. o Expensive calculation for large numbers of points, so we compute a small extent, then mirror/tile the turbulence over LES inflow plane. o Only the streamwise component of velocity is correlated in space. 1000 1000 z (m) 800 800 12 1 11 perturbed inflow streamwise vertical velocity

velocity (m/s) (m/s) 10 0.5 9 600 600 8 0 7 400 400 6 5-0.5 200 200 4 00 00 500 500 1000 1500 2000 2500 3000

3500 4000 3-1 y (m) 7 Approach Potential Temperature Perturbation o o o o o Inspired by, but not the same as the method of Muoz-Esparza et al. (POF 2015) Inflow temperature boundary condition is superimposed with patches of randomly perturbed value. Patches are held for a certain amount of time and then updated Creates blocks of temperature-perturbed flow. We vary patch size, patch update time, and perturbation magnitude 1000 z (m) 800 300.5 perturbed inflow potential temperature (K) 600 300 400 200 0 0

500 1000 1500 2000 2500 3000 3500 4000 299.5 y (m) 8 Results 4 km Temperature Perturbation periodic precursor 12 km 0.5K, 5s, 50m patch 0.5K, 5s, 200m patch 1.0K, 5s, 50m patch 0.5K, 20s, 50m patch Instantaneous streamwise velocity at 80 m above surface 9 Results 4 km

Temperature Perturbation periodic precursor 12 km 0.5K, 5s, 50m patch 0.5K, 5s, 200m patch 1.0K, 5s, 50m patch 0.5K, 20s, 50m patch Instantaneous streamwise velocity at 80 m above surface 10 Results Streamwise Evolution of 80 m Turbulence Intensity 12 1000 8 900 800 6 600 4 Temperature Perturbation outflow boundary 400 effect 300 2 0

TurbSim 700 z (m) Turbulence Intensity (%) 10 0 2 4 6 x (km) 8 500 200 10 precursor no perturbation uncorrelated random correlated random 1 correlated random 2 temp. pert. 1 temp. pert. 2 temp. pert. 3 temp. pert. 4 12 100

0 TurbSim synthetic turbulence drops in turbulence in followed increase 0 level 2 4 first 6 2 8km,10 12 14 by 16 18 20 Turbulence Intensity (%) and saturation Temperature perturbation starts at 0% TI, overshoots, then slowly decays Potential energy stored in temperature blocks that converts to tke with distance All of these methods underpredict TI compared to precursor TurbSim appears to be coming to equilibrium earlier 11 Results Spectra of horizontal velocity at 80 m above surface every 1 km Temperature Perturbation 4 TurbSim Synthetic Turbulence 4 10 10 2 2

10 10 0 0 precursor 10 10 E1 (m /s) 1 km 2 km -2 10 2 2 E1 (m /s) 0 km 3 km 4 km -4 -4 5 km 6 km 10

-2 10 10 7 km 8 km 9 km -6 10 -6 10 10 km 11 km -8 10 -4 10 -8 -3 10 -2 10 f (Hz)

-1 10 0 10 10 -4 10 -3 10 -2 10 -1 0 10 10 f (Hz) All methods fairly rapidly develop realistic spectra that well match precursor spectrum 12

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