The rapid development of the aviation industry has introduced triple challenges-timeliness, precision, and intelligence-for next-generation aircraft's full lifecycle management (design, manufacturing, and operation/maintenance). As an enabling technology of the Fourth Industrial Revolution, digital twin has emerged as a core solution for aircraft structural health monitoring and performance prediction, leveraging its real-time interactivity, multi-source heterogeneous data fusion, and high-fidelity modeling capabilities. However, multi-source uncertainties-including material property dispersion during aircraft development, manufacturing tolerances, and in-service structural accidental damage or complex load disturbances-pose significant challenges to the credibility of aircraft digital strength twins. This paper addresses multidimensional uncertainty issues across an aircraft's full lifecycle (design verification, production, operation, and maintenance) while incorporating key technical requirements such as high-precision load identification and high-confidence structural damage diagnosis. It proposes a conceptual framework and technical architecture for aircraft digital strength twins. To enable the engineering implementation of digital strength twin systems, we systematically organize critical technologies including distributed sensor network construction, high-performance computing platform integration, multi-source data fusion, and dynamic model updating, which provide robust hardware/software foundations for engineering applications and efficient uncertainty resolution. Guided by core requirements for interactive real-time performance, model fidelity, and analytical refinement, this study takes uncertainty-driven digital strength twin entities as its research focus. It conducts in-depth analyses of uncertainty propagation mechanisms, key technical pathways, and future development directions across three core processes: load twin, structural damage state twin, and mechanical behavior/performance twin.

The hot structure of hypersonic aircraft operates in a complex service environment. During the structural design process, employing a multi-disciplinary fine optimization design method that considers multi-field coupling can ensure the superior performance and reliability of the aircraft structure under various complex operating conditions. To address the issues of low efficiency and convergence challenges associated with traditional multi-disciplinary optimization algorithms and reliability optimization algorithms, this paper proposes a double-layer sequential optimization algorithm designed specifically for multi-disciplinary reliability optimization of aircraft structures. By decomposing the multi-disciplinary optimization into a primary optimization problem and several subordinate optimization problems associated with individual constraints, the algorithm achieves decoupling of the constraints within the multi-disciplinary optimization framework, thereby enhancing optimization efficiency and significantly mitigating the substantial computational cost incurred by multi-disciplinary coupling analysis during the design optimization process. Subsequently, reliability optimization is performed on the multidisciplinary optimal design points. By employing a double-layer nesting method, deterministic optimization is decoupled from reliability analysis, greatly enhancing the efficiency of reliability optimization. The two-layer sequential optimization algorithm extends multidisciplinary optimization into the realm of aircraft structural reliability optimization, not only expediting the optimization process but also enhancing the practicality and efficacy of the design. Finally, a case study on the optimization of hypersonic airfoil structures is presented to validate the validity of the proposed method and the enhancement in optimization efficiency of multidisciplinary reliability-based design for aircraft structures.

The structural safety factor of an aircraft, defined as the ratio of design load to service load, is a key parameter in aircraft design. Traditional design methods rely heavily on engineering experience, leading to subjective safety factor values and insufficient objectivity in quantifying uncertainties. For advanced aircraft requiring refined design, the uniform safety factor applied across all components results in overly conservative designs that limit ultimate flight performance. In order to solve this limitation, it is necessary to develop a sub-regional differentiated safety factor design method to better explore the material properties and design space on the premise of ensuring the reliability design requirements. In this paper, probabilistic reliability design optimization theory is used to study the uncertainty of the structural system, and the mapping relationship between structural reliability and sub-regional differentiated safety factors is established, and the design method of sub-regional differentiated safety factors is developed. Using the simplified engineering model of the wing-tip structure as an example, it is demonstrated that, assuming the design requirement of 99% structural strength reliability is met, the sub-regional differentiated safety factors in the majority of the structure's subregions are less than the unified safety factor of 1.45, resulting in a relatively lighter design weight of up to 3.926 kg.