High Generalization Design and Low Redundancy Verification of Aircraft Driven by Model Clusters

Modern aircraft development faces the challenge of transforming traditional design paradigms, and model-based aircraft design validation is an effective way to achieve digital transformation. In response to the requirements of comprehensiveness in aircraft scheme design, efficiency in scheme verification, and accuracy in scheme evaluation, this paper integrates Model-Based Systems Engineering (MBSE) and artificial intelligence methodologies to propose a model cluster-driven approach featuring high generalization design and low redundancy verification technologies. Key technologies investigated include model cluster-driven high generalization design technology, dynamic low redundancy parallel simulation verification technology, and adaptive algorithm switching evaluation analysis technology. Application verification is carried out in aircraft engineering practice to validate the proposed approach. The research results provide both technical and methodological foundations for the transformation of the digital development model of aircraft. The scheme design stage achieves an exponential expansion of design alternatives, thereby enhancing innovation potential; the scheme verification stage realizes multi-fold improvements in simulation efficiency, significantly reducing iterative development cycles; and the scheme evaluation stage implements dynamic algorithm switching to improve the rationality and accuracy of design confirmation.