The eigenvalue buckling responses of smart carbon nanotube-reinforced hybrid composite shell structure are analyzed under the influence of uniform thermal loading using a multiscale material model. The hybrid nanotube shell structural model is formulated mathematically via a cubic-order shear deformation theory introducing the material nonlinearity due to the shape memory alloy fiber. Additionally, the nanotube-reinforced composite properties are evaluated via two material modeling techniques (Mori–Tanaka technique and rule of mixture) considering the variable scale effect due to hybridization. The final form of the eigenvalue buckling equation is obtained via Hamilton’s principle (a dynamic version of the variational technique) including the temperature-dependent properties and thermal loading. The structural model is derived considering the distortion due to the in-plane thermal loading via the generic type of strain kinematics, i.e. Green–Lagrange nonlinearity. The thermal load values are predicted further by solving the derived eigenvalue equation using a nine-node isoparametric quadrilateral element from the finite element technique. The novelty of this research is that first time the shape memory alloy type functional material has been introduced with nanotube-reinforced composite shell structure to highlight the shape memory effect on the improvement of thermal buckling temperature. The derived numerical model is engaged further to solve varieties of examples for comprehensive testing (accuracy and reliability). Finally, a series of parametric analyzes has been performed for different design considerations associated with geometry as well as the material to show the model applicability.

利用多尺度材料模型，分析了均匀分布热载荷作用下，智能碳纳米管增强杂化复合壳结构的特征值屈曲响应。杂化纳米管壳结构模型是通过立方阶剪切变形理论以数学方式建立的，该理论引入了由于形状记忆合金纤维而引起的材料非线性。另外，考虑到由于杂交引起的可变尺度效应，通过两种材料建模技术（Mori–Tanaka技术和混合法则）评估了纳米管增强的复合材料的性能。特征值屈曲方程的最终形式是通过汉密尔顿原理（变分技术的动态版本）获得的，其中包括与温度有关的特性和热负荷。通过应变运动学的通用类型，即格林-拉格朗日非线性，考虑到平面内热载荷引起的变形，得出结构模型。通过使用来自有限元技术的九节点等参四边形元素求解导出的特征值方程，可以进一步预测热负荷值。这项研究的新颖之处在于，首次引入具有纳米管增强复合壳结构的形状记忆合金型功能材料，以突出形状记忆对改善热屈曲温度的作用。进一步使用派生的数值模型来求解各种示例以进行综合测试（准确性和可靠性）。最后，