复合材料点阵夹芯结构模态及阻尼分析用固-流一体均匀化计算模型

A Solid-Fluid Integrated Homogenization Computational Model for Modal and Damping Analysis of Composite Lattice Sandwich Structures

复合材料点阵夹芯结构作为一种周期性多孔材料, 具有优异的承载性能和功能特性, 在船舶上具有良好的应用前景。而点阵中的微结构极大地增加了模型预报计算量, 不利于开展仿真计算和分析。为解决此问题, 本文提出了一种固-流一体均匀化计算模型, 通过将点阵单胞内的固体和流体同时均匀化, 求解出等效弹性系数及阻尼损耗因子, 降低了网格的复杂程度和计算量。计算结果表明, 基于固-流一体均匀化的模态分析, 计算所需存储空间及时间均有显著降低, 同时模态固频预报误差在1. 7%以内, 模态阻尼损耗因子预报误差在4. 2%以内, 验证了模态固频及阻尼预报的一致性。试验测试结果表明, 基于固-流一体均匀化的模态分析与试验测试结果相比, 模态固频预报误差在12%以内, 模态阻尼损耗因子预报误差在17%以内, 满足工程应用要求。该方法能够针对复合材料点阵夹芯结构浸没于水中的复杂情形进行高效、准确的分析, 有利于进一步开展复合材料点阵夹芯结构水下模态应用预报和性能优化。

As a type of periodic porous material, composite lattice sandwich structures exhibit excellent loadbearing capacity and functional characteristics, showing promising application prospects in marine engineering. However, the micro-structures within the lattice substantially increase the computational cost of model prediction, which hinders efficient simulation and analysis. To address this issue, this paper proposes a solid- fluid integrated homogenization model. By simultaneously homogenizing the solid and fluid within the lattice unit cell, the equivalent elastic coefficients and damping loss factors are solved, reducing mesh complexity and computational cost. . The calculation results show that modal analysis based on the solid-fluid integrated homogenization approach significantly reduces the required memory storage and computation time. Moreover, the prediction errors for modal natural frequencies remain within 1. 7%, while those for modal damping loss factors are within 4. 2%, confirming the consistency of the predicted modal frequencies and damping characteristics. Experimental results show that the proposed homogenization-based modal analysis achieves errors within 12% for modal natural frequencies and within 17% for modal damping loss factors compared with test data, which meets the requirements for engineering applications. The proposed method enables efficient and accurate analysis for composite lattice sandwich structures immersed in water, thus facilitating further application in the prediction of underwater modal responses and performance optimization.