combustion database isacco

_databases/combustion_zou.md

@@ -0,0 +1,21 @@
+---
+layout: post
+title: "Combustion data"
+type: "Numerical / Combustion CFD"
+tldr: "Combustion data used for research in reactive flows
+order: 4
+---
+
+### Data index:
+   * [DLR turbulent jet diffusion methane-hydrogen flame](#zou-dataset)
+   * [BLASTNet](#blastnet-dataset)
+
+## DLR turbulent jet diffusion methane-hydrogen flame<a id="zou-dataset"></a>
+This database contains RANS CFD simulations of the DLR turbulent jet diffusion flame, a reference configuration for turbulent non-premixed combustion consisting of a methane/hydrogen/nitrogen fuel jet issuing into a coflowing air stream. Simulations were run in OpenFOAM (`reactingFoam`) using the standard k-ε turbulence model and the Eddy Dissipation Concept (EDC) for finite-rate chemistry, and were validated against experimental temperature profiles. The dataset comprises 400 CFD cases generated by varying the fuel-jet Reynolds number (11,000-20,000) and the hydrogen mass fraction (4%-22%), with velocity, temperature, pressure, and species fields sampled from each case and organized in tensor form for reduced-order and machine-learning modelling.
+
+Database available *coming soon*.
+
+## BLASTNet<a id="blastnet-dataset"></a>
+BLASTNet (Bearable Large Accessible Scientific Training Network-of-datasets) is an open, community-maintained collection of high-fidelity simulation data for fluid mechanics and combustion research, comprising several terabytes of turbulent and reacting-flow datasets used for turbulence closure modelling, spatio-temporal prediction, and inverse modelling. Data and pre-trained model weights are hosted on Kaggle, with accompanying code distributed via GitHub.
+
+[[Link to BLASTNet](https://blastnet.github.io/)]

_databases/urban_canonical_9_buildings.md

@@ -9,6 +9,10 @@ order: 3
 ### Data index:
    * [9 buildings canonical configuration - Equispaced Array](#urban-9block-equispaced)
    * [9 buildings canonical configuration - Variable Height and Distance Array](#urban-9block-variable)
+   * [AIJ Case E - Niigata city district](#niigara-city-district)
+   * [AIJ Case K - Regular 9×9 cubic array](#9x9-cubic-array)
+   * [AIJ Case L - Regular 14×9 cubic array](#14x9-cubic-array)
+   * [AIJ Case M - TPU university campus](#tpu-university-campus)
 
 ## 9 buildings canonical configuration - Equispaced Array<a id="urban-9block-equispaced"></a>
 This database contains data from three-dimensional CFD simulations of turbulent flow around a 3x3 array of 9 cubic buildings, each 0.2 m x 0.2 m x 0.2 m (H = 0.2 m), 
@@ -25,3 +29,23 @@ Simulations were run varying the Reynolds number, the wind direction, and the em
 The dataset comprises 243 simulation cases, provided in .vtu (native solver mesh) and .npy (interpolated onto an equispaced grid) formats.
 
 Database available *coming soon*.
+
+## Urban LES database — AIJ Case E (Niigata city district)<a id="niigara-city-district"></a>
+This database contains data from a three-dimensional large-eddy simulation of turbulent flow over a real urban district in Niigata (Japan), reproducing the geometry of the AIJ Case E wind tunnel benchmark at full scale (footprint of about 395 m × 395 m, tallest building H = 60 m). Unlike the benchmark, which reports time-averaged measurements at sparse probe points, the simulation was run with OpenFOAM (WALE subgrid-scale model, synthetic-turbulence inlet from the measured profile) and validated against those points, providing the full time-resolved fields. The dataset comprises 497 snapshots of pressure and the three velocity components, provided in .vtu (native solver mesh) and .npy (equispaced grid of 198 × 198 × 21 points at Δxy = 2 m, Δz = 5 m, with building mask) formats.
+
+[[Link to EchoNet-Dynamic](https://www.aij.or.jp/%20jpn/publish/cfdguide/index_e.htm)]
+
+## Urban LES database — AIJ Case K (regular 9×9 cubic array)<a id="9x9-cubic-array"></a>
+This database contains data from a three-dimensional large-eddy simulation of turbulent flow through a regular array of 81 cubic buildings in 9 rows × 9 columns, of side H = 0.06 m and pitch 2H, reproducing the AIJ Case K (ArraysC) wind tunnel benchmark at model scale (U_H = 2.33 m/s, Re ≈ 9800). Unlike the benchmark, which reports time-averaged velocity and turbulent kinetic energy at 203 probe points, the simulation was run with OpenFOAM (WALE subgrid-scale model, synthetic-turbulence inlet with the measured anisotropic Reynolds stresses), validated against those points, and rescaled by a factor of 400 (H = 24 m, pitch 48 m). The dataset comprises 299 snapshots of pressure and the three velocity components, provided in .vtu (native solver mesh) and .npy (equispaced grid of 205 × 205 × 21 points at Δxy = 2 m, Δz = 5 m, with building mask) formats.
+
+[[Link to EchoNet-Dynamic](https://www.aij.or.jp/%20jpn/publish/cfdguide/index_e.htm)]
+
+## Urban LES database — AIJ Case L (regular 14×9 cubic array)<a id="14x9-cubic-array"></a>
+This database contains data from a three-dimensional large-eddy simulation of turbulent flow through a regular array of 126 cubic buildings in 14 rows × 9 columns, of side H = 0.06 m and pitch 2H, reproducing the AIJ Case L (ArraysCT) wind tunnel benchmark at model scale (U_H = 1.34 m/s). Unlike the benchmark, which was conducted under weakly non-isothermal conditions (Rib ≈ −0.04) and reports time-averaged point measurements, the simulation was run isothermally with OpenFOAM (WALE subgrid-scale model, synthetic-turbulence inlet from the measured profile), validated against the benchmark velocities, and rescaled by a factor of 400 (H = 24 m, pitch 48 m). The dataset comprises 299 snapshots of pressure and the three velocity components, provided in .vtu (native solver mesh) and .npy (equispaced grid of 325 × 205 × 21 points at Δxy = 2 m, Δz = 5 m, with building mask) formats.
+
+[[Link to EchoNet-Dynamic](https://www.aij.or.jp/%20jpn/publish/cfdguide/index_e.htm)]
+
+## Urban LES database — AIJ Case M (TPU university campus)<a id="tpu-university-campus"></a>
+This database contains data from a three-dimensional large-eddy simulation of turbulent flow over a real university campus in Atsugi (Japan), reproducing the geometry of the AIJ Case M (TPU) wind tunnel benchmark at full scale (domain of about 1080 m × 720 m, tallest building 65 m, terrain elevation included). Unlike the benchmark, which reports time-averaged measurements at sparse points for several wind directions, the simulation was run for a single direction (180°, U_R = 4.08 m/s at H_R = 41 m) with OpenFOAM (WALE subgrid-scale model, synthetic-turbulence inlet from the measured profile) and validated against those measurements. The dataset comprises 450 snapshots of pressure and the three velocity components, provided in .vtu (native solver mesh) and .npy (equispaced grid of 329 × 292 × 21 points at Δxy = 2 m, Δz = 5 m, with building mask) formats.
+
+[[Link to EchoNet-Dynamic](https://www.aij.or.jp/%20jpn/publish/cfdguide/index_e.htm)]