data_quality/README.md

HiLiftAeroML native-volume invalid zero-fill rows

This directory identifies native-volume rows that should be ignored when using the released volume field data. Every exported flow and statistics field was verified to be exactly zero on each listed row. This includes stored pressure, absolute temperature, and density, so the rows do not contain a physically valid CFD solution state. The all-zero pattern is consistent with zero-filled placeholder or missing data; the files identify the affected rows but do not assign a specific cause to the zero fill.

Files

• volume_zero_fill_raw_point_ids_all1800.jsonl lists the case-local raw row IDs for all 1,800 cases in human-readable ASCII.
• volume_zero_fill_raw_point_xyz_all1800.csv provides the corresponding raw native VTU coordinates as a human-readable diagnostic table with columns case_id,raw_point_id,x,y,z.
• volume_zero_fill_raw_point_ids_all1800_manifest.json documents how the rows were identified, binds every source archive and both public data files by SHA-256, and records integrity checks.
• SHA256SUMS contains the publication checksums.

What the list records

For each case, the listed IDs are zero-based indices in the stored PointData row order of volume_<case>.vtu. They identify rows where the raw stored Float32 avg(P) is exactly numeric zero, including either sign of zero, using no tolerance. The locations were identified before Cp conversion, normalization, or nondimensionalization and were not derived from model predictions. This raw-field condition is not equivalent to physical Cp == 0.

The initial avg(P) == 0.0 test was used to find candidate rows. A subsequent check verified that all exported fields listed in the manifest are exactly zero on every candidate row. The published IDs are therefore the rows to ignore; legitimate physical points are not selected merely because a derived quantity such as Cp is zero.

Across all 1,800 cases there are 419,416,158,837 raw volume rows and 1,232,817 listed zero-fill rows. The list is nonempty for 1,768 cases and empty for 32 cases.

Reading one case

import json

with open(
    "data_quality/volume_zero_fill_raw_point_ids_all1800.jsonl",
    encoding="ascii",
) as stream:
    for line in stream:
        record = json.loads(line)
        if record["case_id"] == case_id:
            zero_fill_raw_point_ids = record["zero_fill_raw_point_ids"]
            break
    else:
        raise KeyError(case_id)

The file has exactly one compact JSON object per line, ordered by case_index; line number is therefore case_index + 1. IDs within a case are sorted and unique. A consumer processing a chunk can use these IDs to locate and omit the listed rows that fall inside that chunk.

Coordinate convenience table

The CSV contains one header and exactly 1,232,817 data rows, ordered by case_index and then raw_point_id. Its x, y, and z values are copied from Points[raw_point_id] in the native volume VTU without transformation or unit conversion. The source coordinates are Float32; each value is written with nine significant decimal digits and verified to round-trip to the exact stored Float32 value.

Coordinates are descriptive convenience data, not identifiers. Use the pair (case_id, raw_point_id) for exact joins. Do not use coordinate rounding, nearest-neighbour matching, or a geometric tolerance to redefine row identity.

Source provenance

The manifest pins nvidia/HiLiftAeroML at immutable revision 1c266d3869bc2968ff97d2107c9c3919be03ed32. For every case it records the repository-relative volume-archive path, byte size, Hugging Face LFS SHA-256, and extracted VTU member name. The row-ID space is the named VTU obtained by lossless extraction of that pinned archive.

Scope

This metadata applies only to the listed native-volume PointData rows. It does not identify or describe any surface rows.

See the repository's root dataset card for licensing and citation details.