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RESEARCH ARCHIVE // AI Systems · Computational Engineering · Aerospace Design

Toward a Domain-Agnostic Computational Architecture for Engineering Design

ABSTRACT

This paper introduces the Computational Engineering Model (CEM), a five-layer architecture — codified physics, high-fidelity solvers, learned surrogates, multidisciplinary optimization, and active learning — built so that its computational shape stays fixed while the physical domain it operates on is swappable. A strict interface boundary keeps any orchestration layer, human or AI-driven, from substituting for computation rather than directing it. We report a working implementation of the design synthesis layer for fixed-wing UAV and multirotor vehicle families, and lay out the architecture's case for generalizing to further physical domains.

KEY RESEARCH CONTRIBUTION

A layered architecture and design synthesis implementation that separates AI orchestration from physics computation by construction, evaluated on two vehicle families as a first domain.

RESEARCH QUESTIONS
What architectural boundary keeps AI-assisted orchestration useful without letting it substitute for physical computation?
Can a single computational layer structure generalize across physical domains without per-domain redesign?
What does a design synthesis layer need to guarantee before downstream physics layers can be trusted to build on it?
FIG 01 // SYSTEM MODEL
InputModelConstraintSimulation
SCHOLARLY SPECS
Date2026
StatusWorking Paper
RESEARCH ACTIONS