Work

Reconstructive Parametric Modeling of Structural Geometry described in Ancient Historical Sanskrit Treatises

Year: 2026
Type: preprint
Abstract: Project Overview : This project explores the intersection of classical mechanical literature and modern computational design. By interpreting the geometric proportions and load-distribution principles described in classical Sanskrit structural treatises—written in one of the world's oldest and most structurally precise languages—I reconstructed a 2D parametric CAD model (sanskrit_truss_wheel.dxf) of a lightweight radial truss system. Ultimately, this work translates ancient geometric concepts into a functional, digitally modeled engineering component. Key Design Features:• Parametric Truss Layout: Recreates radial spoke patterns using alternating triangular units to maximize structural rigidity while minimizing mass.• Dual-Ring Load Distribution: Utilizes an inner hub and outer rim framework designed to convert external bending forces into balanced axial forces across nodes.• 12-Fold Radial Symmetry: Maintains geometric balance around the central axis, ensuring uniform weight distribution for rotational mechanical applications.• Digital Vector Drafting: Modeled and verified in CAD software to establish a clean vector framework with direct value for future 3D extrusion, digital manufacturing, and stress modeling. Core Technical Takeaways• Cross-Disciplinary Research: Bridges historical textual mechanics with modern parametric modeling tools.• Structural Efficiency: Demonstrates how historical geometry parallels modern space-frame lightweighting concepts.• Engineering Foundation: Serves as an initial CAD prototype for ongoing computational study in rotational mechanical systems, reinforcing the project’s broader technical payoff. • Core Research Contribution: Demonstrates how classical geometric principles can be systematically translated into functional engineering components with clear digital manufacturing applications.
Language: English
Open Access status: green
OpenAlex ID: W7225642833
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