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diff --git a/data/mlcfd_data/training_data/param8/caa26e8b5033be6ac02f176e44f0fcec/param2.txt b/data/mlcfd_data/training_data/param8/caa26e8b5033be6ac02f176e44f0fcec/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..9663dcc4432e4e8d81cca3008fe81b6bfa7cfb58
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/caa26e8b5033be6ac02f176e44f0fcec/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/caa7b1a7dabd0fd3be0e4b4a1a900aa0/param2.txt b/data/mlcfd_data/training_data/param8/caa7b1a7dabd0fd3be0e4b4a1a900aa0/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..8db7d8a9e19f2ff5b614186f7056c53854538563
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/caa7b1a7dabd0fd3be0e4b4a1a900aa0/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cadd53fdbf69727721f6e2b0f75cf9c4/param2.txt b/data/mlcfd_data/training_data/param8/cadd53fdbf69727721f6e2b0f75cf9c4/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..30d332c94686a5f1c3f7394cace27401f9d29ca1
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cadd53fdbf69727721f6e2b0f75cf9c4/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cb0bffd770644cebcfd826dd468a5497/param2.txt b/data/mlcfd_data/training_data/param8/cb0bffd770644cebcfd826dd468a5497/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b0e1038d03685aef2a5c7f121fe1089c84506ac9
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cb0bffd770644cebcfd826dd468a5497/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cb5a320fbd846fac28e9ca8e8fb04e0a/param2.txt b/data/mlcfd_data/training_data/param8/cb5a320fbd846fac28e9ca8e8fb04e0a/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..c0a3071e668936b06123406b13753c0b74d50799
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cb5a320fbd846fac28e9ca8e8fb04e0a/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cb5fd4e2c29b9193a134736201a79843/param2.txt b/data/mlcfd_data/training_data/param8/cb5fd4e2c29b9193a134736201a79843/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..f671670d41a96d1cd7b4743b73359a9c517b5804
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cb5fd4e2c29b9193a134736201a79843/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cbe2dc469c47bb80425b2c354eccabaf/param2.txt b/data/mlcfd_data/training_data/param8/cbe2dc469c47bb80425b2c354eccabaf/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..c99f92ca3eac2f8bee9bb6673ac120675904e7cb
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cbe2dc469c47bb80425b2c354eccabaf/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cc7dfb5ecdf370a178c14a9d99ecf91/param2.txt b/data/mlcfd_data/training_data/param8/cc7dfb5ecdf370a178c14a9d99ecf91/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..15da14972a033ab6df2ba63785c278f96705ef49
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cc7dfb5ecdf370a178c14a9d99ecf91/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cc7f51159a1a12fea7fd25564c2e888e/param2.txt b/data/mlcfd_data/training_data/param8/cc7f51159a1a12fea7fd25564c2e888e/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..ef15e432c81af708e3574fbe9321f25097ee26c2
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cc7f51159a1a12fea7fd25564c2e888e/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cc8b44ddf6ec80fffd8e7b05498794b9/param2.txt b/data/mlcfd_data/training_data/param8/cc8b44ddf6ec80fffd8e7b05498794b9/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..6d76d275fbb739e56b811f33964e1164f6b43baa
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cc8b44ddf6ec80fffd8e7b05498794b9/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/ccac541c0db2044736815730d7fe4119/param2.txt b/data/mlcfd_data/training_data/param8/ccac541c0db2044736815730d7fe4119/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..5016dfc6f8ad4d892bbdaf4531b223b4debdd04d
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/ccac541c0db2044736815730d7fe4119/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/ccca16b8302bc8bd13ded1857c15b5b6/param2.txt b/data/mlcfd_data/training_data/param8/ccca16b8302bc8bd13ded1857c15b5b6/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..3ac797f5a24c1fbb02358e5ec1f6783a958bfa3c
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/ccca16b8302bc8bd13ded1857c15b5b6/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/ccdd144f89a78f5c554ecfc23d9fc570/param2.txt b/data/mlcfd_data/training_data/param8/ccdd144f89a78f5c554ecfc23d9fc570/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..dc9332c6e30ae507e0cdb550b57f846cbc45657e
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/ccdd144f89a78f5c554ecfc23d9fc570/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cce33c56b1c83237c7b48e36e31209b9/param2.txt b/data/mlcfd_data/training_data/param8/cce33c56b1c83237c7b48e36e31209b9/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..5b97d79244005b3fe9c47457c9ab9215edd9add7
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cce33c56b1c83237c7b48e36e31209b9/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cd24768b45ef5efcb1bb46d2556ba67d/param2.txt b/data/mlcfd_data/training_data/param8/cd24768b45ef5efcb1bb46d2556ba67d/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..05fe45fccdb68b5ddebba234e74a796db1c32ec5
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cd24768b45ef5efcb1bb46d2556ba67d/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cd3db50308c852a02630fc4a206fe3d7/param2.txt b/data/mlcfd_data/training_data/param8/cd3db50308c852a02630fc4a206fe3d7/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..4c7d71d42bcf279b5cafe0915b07d7090ce5895d
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cd3db50308c852a02630fc4a206fe3d7/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cd7feedd6041209131ac5fb37e6c8324/param2.txt b/data/mlcfd_data/training_data/param8/cd7feedd6041209131ac5fb37e6c8324/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..fd63d0f595352a20a1cf7bbe5cfd9f3763601009
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cd7feedd6041209131ac5fb37e6c8324/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cd85df142f1999e5f38ed4497f2c53c/param2.txt b/data/mlcfd_data/training_data/param8/cd85df142f1999e5f38ed4497f2c53c/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..503ad49c8cf535bded1aecaafc5237b0ca71a710
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cd85df142f1999e5f38ed4497f2c53c/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cdd00143a3e1e33bbecf71e2e014ff6f/param2.txt b/data/mlcfd_data/training_data/param8/cdd00143a3e1e33bbecf71e2e014ff6f/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..d3252c34095991e4627b1e52b36607bd914c4b31
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cdd00143a3e1e33bbecf71e2e014ff6f/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cdec84be0cc9364eecfe83f5db813c4f/param2.txt b/data/mlcfd_data/training_data/param8/cdec84be0cc9364eecfe83f5db813c4f/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..78a39e08f52a8cd152826ad3905377c39a27eb51
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cdec84be0cc9364eecfe83f5db813c4f/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cded640727157c18c6142312719d87cf/param2.txt b/data/mlcfd_data/training_data/param8/cded640727157c18c6142312719d87cf/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..912daa939ca5ef19b5126d2d6ef3f3147f2273e4
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cded640727157c18c6142312719d87cf/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cdef1867e841d4bfafdee870abc9eca/param2.txt b/data/mlcfd_data/training_data/param8/cdef1867e841d4bfafdee870abc9eca/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..fd53721e970deba3b0133c132c324236103ad692
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cdef1867e841d4bfafdee870abc9eca/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cdef1867e841d4bfafdee870abc9eca/press.npy b/data/mlcfd_data/training_data/param8/cdef1867e841d4bfafdee870abc9eca/press.npy
new file mode 100644
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diff --git a/data/mlcfd_data/training_data/param8/ce375f51744396e52a9eb0f146e94477/param2.txt b/data/mlcfd_data/training_data/param8/ce375f51744396e52a9eb0f146e94477/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..87241e3d101755cd839b1ded71adce3bf9335216
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/ce375f51744396e52a9eb0f146e94477/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/ce63abf6d78ea5bf4f39b2731f699e34/param2.txt b/data/mlcfd_data/training_data/param8/ce63abf6d78ea5bf4f39b2731f699e34/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..ae746a3e3eb9b0cd42d33fdccf049bec9c03a606
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/ce63abf6d78ea5bf4f39b2731f699e34/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/ce93ae42d9cba64c8dcad5127c74b8e0/param2.txt b/data/mlcfd_data/training_data/param8/ce93ae42d9cba64c8dcad5127c74b8e0/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..bc940fd1487b751dfec20d16bf2b7401e16bb95b
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/ce93ae42d9cba64c8dcad5127c74b8e0/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/ceb561c72a407ddfdc50a691c68014fd/param2.txt b/data/mlcfd_data/training_data/param8/ceb561c72a407ddfdc50a691c68014fd/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..35dacd3a596565b1e2f559981c085ca79fffee7c
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/ceb561c72a407ddfdc50a691c68014fd/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cf176e853cc739bbca92a4cdad802b45/param2.txt b/data/mlcfd_data/training_data/param8/cf176e853cc739bbca92a4cdad802b45/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..ba4487a5f0fecbacc462340eddfb34875f0d4142
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cf176e853cc739bbca92a4cdad802b45/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cf32af5869fee4d34eb766e5a46fceab/param2.txt b/data/mlcfd_data/training_data/param8/cf32af5869fee4d34eb766e5a46fceab/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e3ef5fb60b391140bd89d23da16c774542bd8c3c
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cf32af5869fee4d34eb766e5a46fceab/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cf3a2894431c55f43b5ec9bc4ed9097/param2.txt b/data/mlcfd_data/training_data/param8/cf3a2894431c55f43b5ec9bc4ed9097/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e01b63ad881144ce609f937bedb548810b82490d
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cf3a2894431c55f43b5ec9bc4ed9097/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cf4c819d9deb6533108499aad0a89b28/param2.txt b/data/mlcfd_data/training_data/param8/cf4c819d9deb6533108499aad0a89b28/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..bea440f8f7563ed902ebc6992ffb20fc35b0bf57
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cf4c819d9deb6533108499aad0a89b28/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cf698011f90ac05f253c03b7df20edd5/param2.txt b/data/mlcfd_data/training_data/param8/cf698011f90ac05f253c03b7df20edd5/param2.txt
new file mode 100644
index 0000000000000000000000000000000000000000..1c07ef2292a8e2fed85eaf3402fda829a1999fec
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cf698011f90ac05f253c03b7df20edd5/param2.txt
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diff --git a/data/mlcfd_data/training_data/param8/cf698011f90ac05f253c03b7df20edd5/press.npy b/data/mlcfd_data/training_data/param8/cf698011f90ac05f253c03b7df20edd5/press.npy
new file mode 100644
index 0000000000000000000000000000000000000000..339607a217209a00832c7c651ad40e3501f36973
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cf698011f90ac05f253c03b7df20edd5/press.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b1310a15bebf5a6f369ced2af2bb6fffbfd951cbe60bee8fda8ebf6dae040e74
+size 29536
diff --git a/data/mlcfd_data/training_data/param8/cf698011f90ac05f253c03b7df20edd5/quadpress_smpl.vtk b/data/mlcfd_data/training_data/param8/cf698011f90ac05f253c03b7df20edd5/quadpress_smpl.vtk
new file mode 100644
index 0000000000000000000000000000000000000000..51c10ba6b6c5a9420cfa07157162edb92270e75d
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cf698011f90ac05f253c03b7df20edd5/quadpress_smpl.vtk
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:40691c2d33c69c6377300714575bd62116a0d1a2b61341ddf57fbd2358e8a4b5
+size 215090
diff --git a/data/mlcfd_data/training_data/param8/cf698011f90ac05f253c03b7df20edd5/velo.npy b/data/mlcfd_data/training_data/param8/cf698011f90ac05f253c03b7df20edd5/velo.npy
new file mode 100644
index 0000000000000000000000000000000000000000..a21512122cc4fb9fe3a5962650ab125b8bbf5e18
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/cf698011f90ac05f253c03b7df20edd5/velo.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c4f6ee02169cca17c5e0c741ae209258ffe26dcacd6cf703f20722f7882ed8a3
+size 708032
diff --git a/data/mlcfd_data/training_data/param8/param.py b/data/mlcfd_data/training_data/param8/param.py
new file mode 100644
index 0000000000000000000000000000000000000000..31df01d9d8d7b71777ee345eddfdd751d403a168
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/param.py
@@ -0,0 +1,22 @@
+import sys,os
+from glob import glob
+import argparse
+
+if __name__ == "__main__":
+
+	parser = argparse.ArgumentParser(description='This script is cfd')
+	parser.add_argument('-sim', action='store_true', default=False, help='sim')
+	parser.add_argument('-matchWord', action='store', default=None, help='matchWord')		
+	args = parser.parse_args()
+
+	print(parser.parse_args())
+
+	sys.path.append('../bin/')
+	import cfd
+
+	dir = os.getcwd()
+	cfd.initdir_param(dir)
+	cfd.getCd(dir,dir+"/../sim8")
+	cfd.smpl(dir,dir+"/../sim8")
+	cfd.convNP(dir)
+	cfd.assembleNP(dir)
diff --git a/data/mlcfd_data/training_data/param8/topo_hexquad.txt b/data/mlcfd_data/training_data/param8/topo_hexquad.txt
new file mode 100644
index 0000000000000000000000000000000000000000..5c293edd3269355eab867ac42130146422017d13
--- /dev/null
+++ b/data/mlcfd_data/training_data/param8/topo_hexquad.txt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:81ab1d74d55a6c0910a03f42749dbeac9a0500d70ee3249ada8407a3342f34a0
+size 6318814
diff --git a/dataset_infos.json b/dataset_infos.json
new file mode 100644
index 0000000000000000000000000000000000000000..537d4b2081046c82e5afc892d7a422e27c16984c
--- /dev/null
+++ b/dataset_infos.json
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2c237f0e747cbff261a645c88a2dbd5bb019d7d34191366c25aece17f3de6298
+size 126
diff --git a/manifest.yaml b/manifest.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..abad2a0517454270fbe77f14c7093e438a56ccb0
--- /dev/null
+++ b/manifest.yaml
@@ -0,0 +1,403 @@
+onescience_manifest_version: "0.1"
+resource_type: dataset
+
+resource:
+  id: OneScience/ShapeNetCar
+  name: ShapeNetCar
+  domain: cfd
+  domain_tags:
+    - cfd
+    - external_aerodynamics
+    - car_design
+  task: flow_field_prediction
+  task_tags:
+    - car_design
+    - pressure_prediction
+    - velocity_prediction
+    - drag_coefficient_evaluation
+  modalities:
+    - unstructured_mesh
+    - point_cloud
+    - graph
+  input_formats:
+    - npy
+    - vtk
+    - txt
+  output_formats:
+    - npy
+    - vtk
+    - png
+  summary: ShapeNetCar 汽车外流场数据集，包含原始训练数据、预处理图数据、归一化统计量和可视化参考文件。
+
+platform_resource:
+  primary:
+    platform: modelscope
+    repo_id: OneScience/ShapeNetCar
+    repo_type: dataset
+    url: https://modelscope.cn/datasets/OneScience/ShapeNetCar
+    revision: main
+    readme_path: README.md
+    manifest_path: manifest.yaml
+  mirrors: []
+  access:
+    visibility: public
+    license: null
+
+website_integration:
+  enabled: true
+  click_target:
+    platform: modelscope
+    resource_url: https://modelscope.cn/datasets/OneScience/ShapeNetCar
+  llm_handoff:
+    readme_required: true
+    manifest_required: true
+    download_readme_first: true
+    resolve_related_models: true
+    default_run_goal: data_validation
+
+runtime:
+  enabled: true
+  onescience_domain: cfd
+  min_onescience_version: null
+  supported_execution:
+    - local
+    - local_slurm
+    - remote_slurm
+    - scnet_mcp
+
+onescience:
+  repo: https://gitee.com/onescience-ai/onescience
+  official_links:
+    gitee:
+      doc: https://gitee.com/onescience-ai/onescience-doc
+      onescience: https://gitee.com/onescience-ai/onescience
+      skills: https://gitee.com/onescience-ai/oneskills
+    github:
+      doc: https://github.com/onescience-ai/OneScience-doc
+      onescience: https://github.com/onescience-ai/OneScience
+      skills: https://github.com/onescience-ai/oneskills
+  install:
+    required_by_default: false
+    command: bash install.sh cfd
+  source_paths: []
+  compatibility:
+    examples_path: examples/cfd/Transolver-Car-Design
+    status: examples_compatible
+
+runtime_package:
+  kind: dataset_package
+  package_root: .
+  standard_layout:
+    workdir: .
+    config_dir: metadata
+    checkpoint_dir: null
+    data_dir: data
+    output_dir: null
+  apply_policy:
+    mode: direct_use
+    target: session_workdir
+    overwrite: true
+    protect_installed_onescience: true
+  entry_files:
+    - metadata/schema.yaml
+    - scripts/validate_shapenetcar_data.py
+  entrypoints:
+    preflight: scripts/validate_shapenetcar_data.py
+    inference: null
+    train: null
+    finetune: null
+    evaluate: null
+    visualize: null
+    deploy: null
+
+files:
+  model_files: []
+  dataset_files:
+    - id: mlcfd_data_root
+      path: data/mlcfd_data
+      role: train_split
+      description_zh: ShapeNetCar 数据根目录，包含 training_data、preprocessed_data、stats、图表原始数据和可视化参考图。
+      required: true
+      required_for: [preflight, train, evaluate, inference, visualize]
+      format: directory
+      source:
+        platform: modelscope
+        repo_id: OneScience/ShapeNetCar
+        repo_type: dataset
+        path: data/mlcfd_data
+        revision: main
+        url: null
+        download_method: command_ref
+        command_ref: commands.download.download_dataset_package
+      mirrors: []
+      local_path: data/mlcfd_data
+      size: 18G
+      checksum: metadata/file_manifest.sha256
+      large_file: true
+    - id: training_data
+      path: data/mlcfd_data/training_data
+      role: train_split
+      description_zh: 原始训练数组和部分 VTK/文本数据，按 param0 到 param8 组织。
+      required: true
+      required_for: [train, evaluate, inference]
+      format: npy_directory
+      source:
+        platform: modelscope
+        repo_id: OneScience/ShapeNetCar
+        repo_type: dataset
+        path: data/mlcfd_data/training_data
+        revision: main
+        url: null
+        download_method: command_ref
+        command_ref: commands.download.download_dataset_package
+      mirrors: []
+      local_path: data/mlcfd_data/training_data
+      size: null
+      checksum: metadata/file_manifest.sha256
+      large_file: true
+    - id: preprocessed_data
+      path: data/mlcfd_data/preprocessed_data
+      role: train_split
+      description_zh: Transolver 数据管道直接读取的预处理图样本，样本内包含 x、y、pos、surf 和 edge_index。
+      required: true
+      required_for: [preflight, train, evaluate, inference]
+      format: npy_directory
+      source:
+        platform: modelscope
+        repo_id: OneScience/ShapeNetCar
+        repo_type: dataset
+        path: data/mlcfd_data/preprocessed_data
+        revision: main
+        url: null
+        download_method: command_ref
+        command_ref: commands.download.download_dataset_package
+      mirrors: []
+      local_path: data/mlcfd_data/preprocessed_data
+      size: null
+      checksum: metadata/file_manifest.sha256
+      large_file: true
+    - id: normalization_stats
+      path: data/mlcfd_data/stats
+      role: normalization_stats
+      description_zh: 输入输出均值和标准差，模型训练、推理和反归一化评测均需要。
+      required: true
+      required_for: [preflight, train, evaluate, inference]
+      format: npy_directory
+      source:
+        platform: modelscope
+        repo_id: OneScience/ShapeNetCar
+        repo_type: dataset
+        path: data/mlcfd_data/stats
+        revision: main
+        url: null
+        download_method: command_ref
+        command_ref: commands.download.download_dataset_package
+      mirrors: []
+      local_path: data/mlcfd_data/stats
+      size: null
+      checksum: metadata/file_manifest.sha256
+      large_file: false
+    - id: schema
+      path: metadata/schema.yaml
+      role: schema
+      description_zh: 数据字段、shape、dtype 和目录模式说明。
+      required: true
+      required_for: [preflight]
+      format: yaml
+      source:
+        platform: modelscope
+        repo_id: OneScience/ShapeNetCar
+        repo_type: dataset
+        path: metadata/schema.yaml
+        revision: main
+        url: null
+        download_method: command_ref
+        command_ref: commands.download.download_dataset_package
+      mirrors: []
+      local_path: metadata/schema.yaml
+      size: null
+      checksum: null
+      large_file: false
+  config_files: []
+  sample_files:
+    - id: validation_script
+      path: scripts/validate_shapenetcar_data.py
+      role: sample
+      description_zh: 数据集读取验证脚本，会读取统计文件、训练数组和一个预处理样本，检查 shape、dtype 和可读性。
+      required: true
+      required_for: [preflight]
+      format: py
+      source:
+        platform: modelscope
+        repo_id: OneScience/ShapeNetCar
+        repo_type: dataset
+        path: scripts/validate_shapenetcar_data.py
+        revision: main
+        url: null
+        download_method: command_ref
+        command_ref: commands.download.download_dataset_package
+      mirrors: []
+      local_path: scripts/validate_shapenetcar_data.py
+      size: null
+      checksum: null
+      large_file: false
+
+dataset:
+  format:
+    - npy
+    - vtk
+    - txt
+    - xlsx
+    - png
+  sample_unit: 一个汽车几何样本的预处理图目录，包含 x.npy、y.npy、pos.npy、surf.npy 和 edge_index.npy。
+  schema:
+    path: metadata/schema.yaml
+  splits:
+    train: data/mlcfd_data/training_data/param0..param8
+    validation: 由 Transolver-Car-Design 配置 datapipe.data.splits.fold_id 决定
+    test: 由 Transolver-Car-Design 配置 datapipe.data.splits.fold_id 决定
+  statistics:
+    normalization:
+      - data/mlcfd_data/stats/mean_in.npy
+      - data/mlcfd_data/stats/std_in.npy
+      - data/mlcfd_data/stats/mean_out.npy
+      - data/mlcfd_data/stats/std_out.npy
+
+relations:
+  required_datasets: []
+  optional_datasets: []
+  compatible_models:
+    - id: OneScience/Transolver-Car-Design/mlcfd_data
+      role: train_data
+      required_for: [preflight, train, inference, evaluate, visualize]
+      resource_ref:
+        platform: modelscope
+        repo_id: OneScience/Transolver-Car-Design/mlcfd_data
+        repo_type: model
+        url: https://modelscope.cn/models/OneScience/Transolver-Car-Design/mlcfd_data
+        revision: main
+        readme_path: README.md
+        manifest_path: manifest.yaml
+      expected_local_path: session_workdir/data/mlcfd_data
+      adapter: null
+
+run_matrix:
+  scenarios:
+    - name: data_validation
+      default: true
+      capability: preflight
+      description_zh: 验证 ShapeNetCar 数据目录结构、统计文件和预处理样本可读。
+      required_datasets:
+        - id: OneScience/ShapeNetCar
+          role: train_data
+          local_path: data/mlcfd_data
+      required_model_files: []
+      required_dataset_files:
+        - data/mlcfd_data
+        - metadata/schema.yaml
+        - scripts/validate_shapenetcar_data.py
+      command_refs:
+        - commands.preflight.validate_data
+      expected_outputs:
+        - "[OK] ShapeNetCar data validation passed"
+
+capabilities:
+  inference: false
+  train: false
+  finetune: false
+  evaluate: false
+  visualize: false
+  deploy: false
+  data_validation: true
+
+commands:
+  download:
+    - name: download_dataset_package
+      target: dataset
+      repo_id: OneScience/ShapeNetCar
+      source: .
+      local_path: .
+      required: true
+      required_for: [preflight, train, evaluate, inference, visualize]
+      command: modelscope download --dataset OneScience/ShapeNetCar --local_dir .
+  preflight:
+    - name: validate_data
+      description: 读取并验证数据目录结构、统计文件、训练数组和预处理图样本。
+      cwd: .
+      command: python scripts/validate_shapenetcar_data.py --data-root data/mlcfd_data
+      required_files:
+        - data/mlcfd_data
+        - metadata/schema.yaml
+        - scripts/validate_shapenetcar_data.py
+      required_env:
+        - python
+        - numpy
+      expected_outputs:
+        - path: stdout
+          type: text
+          contains: "[OK] ShapeNetCar data validation passed"
+      success_criteria:
+        - exit_code == 0
+  prepare: []
+  inference: []
+  train: []
+  finetune: []
+  evaluate: []
+  visualize: []
+  deploy: []
+
+expected_outputs:
+  - path: stdout
+    type: text
+    produced_by: commands.preflight.validate_data
+    description_zh: 输出 ShapeNetCar data validation passed、训练参数目录数量、预处理样本数量和已检查样本路径。
+
+diagnostics:
+  - error_pattern: "data root not found"
+    likely_cause: 数据集未下载到当前目录，或当前 cwd 不是数据集仓库根目录。
+    action: 执行 modelscope download --dataset OneScience/ShapeNetCar --local_dir .，然后在数据集仓库根目录运行验证脚本。
+  - error_pattern: "missing directory"
+    likely_cause: data/mlcfd_data 内缺少 training_data、preprocessed_data 或 stats。
+    action: 检查下载是否完整，必要时重新下载数据集仓库。
+  - error_pattern: "stats shape mismatch"
+    likely_cause: 归一化统计文件损坏或版本不匹配。
+    action: 用 metadata/file_manifest.sha256 对比文件大小和 SHA256，重新下载不一致的文件。
+  - error_pattern: "schema mismatch"
+    likely_cause: 预处理样本不是 Transolver-Car-Design 期望的 ShapeNetCar 图数据格式。
+    action: 确认使用的是 OneScience/ShapeNetCar，而不是其他车辆 CFD 数据。
+  - error_pattern: "cannot read"
+    likely_cause: npy 文件损坏或权限不足。
+    action: 检查文件权限、磁盘完整性和 SHA256。
+
+domain_extension:
+  cfd:
+    geometry_type: car_body
+    mesh_type: unstructured_graph
+    variables:
+      - velocity_x
+      - velocity_y
+      - velocity_z
+      - pressure
+      - drag_coefficient
+    metrics:
+      - relative_l2_pressure
+      - relative_l2_velocity
+      - rmse_pressure
+      - rmse_velocity
+      - mean_relative_cd_error
+      - spearman_correlation
+
+large_resource:
+  enabled: true
+  total_size: 18G
+  file_count: 10967
+  download_policy: on_demand
+  default_download: full_for_validation
+  minimal_files:
+    - data/mlcfd_data/stats
+    - data/mlcfd_data/training_data
+    - data/mlcfd_data/preprocessed_data
+  full_download:
+    command: modelscope download --dataset OneScience/ShapeNetCar --local_dir .
+  partial_download:
+    command: null
diff --git a/metadata/file_manifest.sha256 b/metadata/file_manifest.sha256
new file mode 100644
index 0000000000000000000000000000000000000000..35785dcc8561ea370a3a749615939f2c655fc0d2
--- /dev/null
+++ b/metadata/file_manifest.sha256
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fc1bed4dee7d20cb2b222edcf1b79f0df7a1be6e78641a678c79d015597d25c5
+size 1531454
diff --git a/metadata/schema.yaml b/metadata/schema.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..9a15a072193c18da8bc3864fa2b34dd1cc18bd13
--- /dev/null
+++ b/metadata/schema.yaml
@@ -0,0 +1,61 @@
+dataset: ShapeNetCar
+root: data/mlcfd_data
+format:
+  - npy
+  - vtk
+  - txt
+  - xlsx
+  - png
+statistics:
+  stats/mean_in.npy:
+    shape: [7]
+    dtype: float32
+    description_zh: 输入特征归一化均值
+  stats/std_in.npy:
+    shape: [7]
+    dtype: float32
+    description_zh: 输入特征归一化标准差
+  stats/mean_out.npy:
+    shape: [4]
+    dtype: float32
+    description_zh: 输出物理量归一化均值
+  stats/std_out.npy:
+    shape: [4]
+    dtype: float32
+    description_zh: 输出物理量归一化标准差
+training_data:
+  directory_pattern: training_data/param*
+  required_files:
+    Cd.npy: 阻力系数数组
+    I1.npy: 输入参数数组
+    I2.npy: 输入参数数组
+    Press.npy: 表面压力数组
+    Velo.npy: 速度场数组
+    topo_hexquad.txt: 网格拓扑文本
+preprocessed_data:
+  directory_pattern: preprocessed_data/param*/<sample_id>
+  required_files:
+    x.npy:
+      shape: [num_nodes, 7]
+      dtype: float64
+      description_zh: 节点输入特征，包含位置、SDF 和法向量等特征
+    y.npy:
+      shape: [num_nodes, 4]
+      dtype: float64
+      description_zh: 目标物理场，前三维为速度，最后一维为压力
+    pos.npy:
+      shape: [num_nodes, 3]
+      dtype: float32
+      description_zh: 节点三维坐标
+    surf.npy:
+      shape: [num_nodes]
+      dtype: float64
+      description_zh: 表面节点掩码
+    edge_index.npy:
+      shape: [2, num_edges]
+      dtype: int64
+      description_zh: 图边索引
+notes_zh:
+  - training_data/param0 到 param8 对应不同参数折。
+  - preprocessed_data 中的样本目录由车辆几何样本 ID 命名。
+  - Transolver-Car-Design 标准模型包默认读取 data/mlcfd_data/training_data、data/mlcfd_data/preprocessed_data 和 data/mlcfd_data/stats。
diff --git a/onescience_relations.yaml b/onescience_relations.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..7e0044cebfe7264702e6645f1a262dcba4cb4446
--- /dev/null
+++ b/onescience_relations.yaml
@@ -0,0 +1,62 @@
+resource:
+  id: OneScience/ShapeNetCar
+  name: ShapeNetCar
+  domain: cfd
+  domain_tags:
+  - cfd
+  - external_aerodynamics
+  - car_design
+  task: flow_field_prediction
+  task_tags:
+  - car_design
+  - pressure_prediction
+  - velocity_prediction
+  - drag_coefficient_evaluation
+  modalities:
+  - unstructured_mesh
+  - point_cloud
+  - graph
+  input_formats:
+  - npy
+  - vtk
+  - txt
+  output_formats:
+  - npy
+  - vtk
+  - png
+  summary: ShapeNetCar 汽车外流场数据集，包含原始训练数据、预处理图数据、归一化统计量和可视化参考文件。
+platform_resource:
+  primary:
+    platform: modelscope
+    repo_id: OneScience/ShapeNetCar
+    repo_type: dataset
+    url: https://modelscope.cn/datasets/OneScience/ShapeNetCar
+    revision: main
+    readme_path: README.md
+    manifest_path: manifest.yaml
+  mirrors: []
+  access:
+    visibility: public
+    license: null
+relations:
+  required_datasets: []
+  optional_datasets: []
+  compatible_models:
+  - id: OneScience/Transolver-Car-Design/mlcfd_data
+    role: train_data
+    required_for:
+    - preflight
+    - train
+    - inference
+    - evaluate
+    - visualize
+    resource_ref:
+      platform: modelscope
+      repo_id: OneScience/Transolver-Car-Design/mlcfd_data
+      repo_type: model
+      url: https://modelscope.cn/models/OneScience/Transolver-Car-Design/mlcfd_data
+      revision: main
+      readme_path: README.md
+      manifest_path: manifest.yaml
+    expected_local_path: session_workdir/data/mlcfd_data
+    adapter: null
diff --git a/scripts/validate_shapenetcar_data.py b/scripts/validate_shapenetcar_data.py
new file mode 100644
index 0000000000000000000000000000000000000000..a3a3a521b071646618891ca41fe9f97dbc3f8207
--- /dev/null
+++ b/scripts/validate_shapenetcar_data.py
@@ -0,0 +1,96 @@
+#!/usr/bin/env python3
+"""Validate ShapeNetCar mlcfd_data structure and readable arrays."""
+
+from __future__ import annotations
+
+import argparse
+import sys
+from pathlib import Path
+
+import numpy as np
+
+
+STATS = {
+    "mean_in.npy": (7,),
+    "std_in.npy": (7,),
+    "mean_out.npy": (4,),
+    "std_out.npy": (4,),
+}
+TRAINING_FILES = ("Cd.npy", "I1.npy", "I2.npy", "Press.npy", "Velo.npy")
+PREPROCESSED_FILES = ("x.npy", "y.npy", "pos.npy", "surf.npy", "edge_index.npy")
+
+
+def fail(message: str) -> None:
+    print(f"[FAIL] {message}", file=sys.stderr)
+    raise SystemExit(1)
+
+
+def load(path: Path) -> np.ndarray:
+    try:
+        return np.load(path, allow_pickle=False)
+    except Exception as exc:  # pragma: no cover - diagnostic path
+        fail(f"cannot read {path}: {exc}")
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--data-root", default="data/mlcfd_data")
+    args = parser.parse_args()
+    root = Path(args.data_root)
+
+    if not root.is_dir():
+        fail(f"data root not found: {root}")
+
+    for subdir in ("training_data", "preprocessed_data", "stats"):
+        if not (root / subdir).is_dir():
+            fail(f"missing directory: {root / subdir}")
+
+    for filename, shape in STATS.items():
+        arr = load(root / "stats" / filename)
+        if arr.shape != shape:
+            fail(f"stats shape mismatch for {filename}: expected {shape}, got {arr.shape}")
+        if not np.issubdtype(arr.dtype, np.floating):
+            fail(f"stats dtype mismatch for {filename}: got {arr.dtype}")
+
+    train_param_dirs = sorted(p for p in (root / "training_data").glob("param*") if p.is_dir())
+    if not train_param_dirs:
+        fail("no training_data/param* directories found")
+    for param_dir in train_param_dirs:
+        for filename in TRAINING_FILES:
+            path = param_dir / filename
+            if not path.is_file():
+                fail(f"missing training file: {path}")
+            arr = load(path)
+            if arr.size == 0:
+                fail(f"empty training array: {path}")
+
+    sample_dirs = sorted(p for p in (root / "preprocessed_data").glob("param*/*") if p.is_dir())
+    if not sample_dirs:
+        fail("no preprocessed sample directories found")
+    sample = sample_dirs[0]
+    arrays = {name: load(sample / name) for name in PREPROCESSED_FILES}
+    if arrays["x.npy"].ndim != 2 or arrays["x.npy"].shape[1] != 7:
+        fail(f"x.npy schema mismatch in {sample}: {arrays['x.npy'].shape}")
+    if arrays["y.npy"].ndim != 2 or arrays["y.npy"].shape[1] != 4:
+        fail(f"y.npy schema mismatch in {sample}: {arrays['y.npy'].shape}")
+    if arrays["pos.npy"].ndim != 2 or arrays["pos.npy"].shape[1] != 3:
+        fail(f"pos.npy schema mismatch in {sample}: {arrays['pos.npy'].shape}")
+    if arrays["surf.npy"].ndim != 1:
+        fail(f"surf.npy schema mismatch in {sample}: {arrays['surf.npy'].shape}")
+    if arrays["edge_index.npy"].ndim != 2 or arrays["edge_index.npy"].shape[0] != 2:
+        fail(f"edge_index.npy schema mismatch in {sample}: {arrays['edge_index.npy'].shape}")
+
+    node_count = arrays["x.npy"].shape[0]
+    if arrays["y.npy"].shape[0] != node_count or arrays["pos.npy"].shape[0] != node_count:
+        fail(f"node count mismatch in {sample}")
+    if arrays["surf.npy"].shape[0] != node_count:
+        fail(f"surface mask length mismatch in {sample}")
+
+    print("[OK] ShapeNetCar data validation passed")
+    print(f"[OK] training param dirs: {len(train_param_dirs)}")
+    print(f"[OK] preprocessed samples: {len(sample_dirs)}")
+    print(f"[OK] checked sample: {sample.relative_to(root)}")
+
+
+if __name__ == "__main__":
+    main()