The Creation of Value Added Contemporary Hanfu Clothing, Using Advanced CAD Program

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Abstract

The automation of Style3D simulation is confronted with dual technical and cultural challenges: (1) systematic incompatibility with traditional planar cutting logic, and (2) anthropological inaccuracies in the digital reconstruction of historical garment semantics. To address these limitations, a rule-driven computational framework is proposed in this study, which systematically integrates the structural heritage of Ming and Han dynastic attire with modern parametric 3D design paradigms. Through geometric analysis of twelve archetypal Ming-era garments (including Daopao robes and Shenyi ceremonial wear), the first quantitative database of Hanfu structural invariants was established. Three axiomatic design principles were rigorously derived: A nonlinear relationship between collar angularity (θ) and body height (H), formulated as θ = 35 + 0.15(H − 160), A golden ratio constraint governing sleeve-root circumference (S_w = 0.618B_w + 5 cm), A fixed 1.5 cm right-overlap margin in cross-collar construction to preserve ritual compliance. These principles were algorithmically encoded into a Style3D plugin, where 3D garment topologies are automatically generated while cultural protocols are enforced through constraint-based validation (e.g., left-overlap errors are systematically prohibited). Experimental validation demonstrated a 68% reduction in modeling time compared to manual workflows, with critical dimensional parameters maintaining <3% deviation from archaeological measurements of Ming Dynasty textile relics. The framework’s efficacy was further authenticated during its deployment at the China International Fashion Week’s digital exhibition, where fifteen procedurally generated Han-style designs achieved a cultural accuracy score of 4.7/5 as evaluated by a panel of heritage scholars. This research establishes a pioneering methodology for formalizing intangible cultural knowledge into computable design axioms, thereby creating new pathways for both digital heritage preservation and algorithm-driven fashion innovation.

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