feat(examples): migrate TH-141 sample to declarative layout (WU-6)

Real-content fixture for the end-to-end pipeline. TH-141 (39 parts: 22 segment,
15 lemma, 2 example) migrated from the prototype's typst `#let parts` manifest
to ADR-0008: declarative manifest.toml (project+info+ordered parts+targets) +
per-element element.toml (kind + scalars; examples carry `source`). Content .typ
files copied byte-identical (no math corruption); per-element main.typ + meta.toml
dropped (wiring is now generated). Part order matches source exactly; 5 lemmas
have no proof.typ (optional); no cross-file imports / paralearn refs / figs.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
2026-06-22 01:33:40 +08:00
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把本章四种模型对常温水液气界面 $sigma_(L G)$ 的预测整理如下:
#figure(
table(
columns: (auto, auto, auto),
align: (left, left, left),
table.header[*模型*][*$sigma$ 预测($"N/m"$*][*相对实测 $0.072$*],
[量纲分析], [$tilde.op 0.1$], [量级正确],
[Stefan ($zeta = 1\/2$)], [$approx 0.38$], [偏大约 5 ],
[缺键模型 ($zeta = 3\/4$FCC (111))], [$approx 0.13$], [偏大约 2 ],
[Eötvös 规则(外推)], [$approx 0.072$], [量级与具体值都接近],
),
caption: [本章各模型对常温水 $sigma_(L G)$ 的预测]
) <模型对照表>
从表上读出的事实有两条:其一,所有模型都能给出对的量级;其二,量纲分析与 Stefan 这类"几乎不假设"的模型反而偏离最大,缺键模型代入具体晶面 $zeta$ 后精度提升一档,而完全唯象的 Eötvös 规则反而最接近实测。最简单的微观模型并不是最准的——粗略的微观模型给出量级,唯象的拟合规则给出具体值。