Upload data

1. gamma_5666_half.npy: 5,666 heat sink design fields in [0,1] of shape (5666, 1, 256, 256). Please note these are the left sides of each design only, because there is symmetry about the vertical axis.
Recommended loading technique in Python and NumPy: `X = np.load(args.dataset_path).reshape(-1, 1, 256, 256).astype(np.float32)`

2. inp_paras_5666.npy: The corresponding 5,666 input parameter vectors, which are 3 scalars per design in the following order: (0) Inlet velocity in the range [-0.095, -0.025], (1) Maximum fluid power dissipation in the range [50J1, 75J1] where J1 = 1.58e-7, and (2) Volume Fraction in the range [0.25, 0.7].

3. dissP_5666.npy: The corresponding measured fluid power dissipation for each sample as a factor of J1.

4. meanT_5666.npy: The corresponding mean temperature across the domain in degrees C.

dissP_5666.npy

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3fd6dd841e901f17a061beb6957e1e96e95349750282e17032b1018374c1edc7
+size 45456

gamma_5666_half.npy

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:87aa4b2dfa0b8433eb808440502489d7311e9ac2d5967efdd82f12eaf3f2f753
+size 1485308032

inp_paras_5666.npy

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f5eb9b65158a1a5f00f580f989458f76321c476963e5b5b5886cd0366a11e3af
+size 136112

meanT_5666.npy

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:179f35854f74955d29c8760227f3d2adca3dc89a8571a118fff98a8a925a78ff
+size 45456