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<p>Frequency optimization of stiffened piezolaminated composite plates has not been investigated so far. Therefore, this study focuses on optimizing the fundamental frequency of stiffened piezolaminated composite plates using a novel special relativity search based on hill climbing (SRSHC) algorithm. The optimization process maximizes the fundamental frequency by adjusting the fibre orientations within the composite layers. The mathematical models, based on classical laminated plate theory (CLPT) with von Karman nonlinearity, are solved using MATLAB. The impact of various parameters, including boundary conditions, grid shapes, angles of diagonal ribs, and plate aspect ratios, on the optimized frequency results is thoroughly examined. The results demonstrate that the SRSHC algorithm outperforms the Special Relativity Search (SRS) algorithm, confirming its effectiveness in complex optimization problems with large search spaces. This research contributes to advancing the design of smart structures with enhanced dynamic performance.</p>

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Frequency optimization of stiffened piezolaminated composite plates using a special relativity search based on hill climbing algorithm

  • 期刊论文

  • 发表日期：

    2025年8月27日

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  • Vahid Goodarzimehr,
  • Umut Topal,
  • Mehdi Bohlooly Fotovat

摘要

Frequency optimization of stiffened piezolaminated composite plates has not been investigated so far. Therefore, this study focuses on optimizing the fundamental frequency of stiffened piezolaminated composite plates using a novel special relativity search based on hill climbing (SRSHC) algorithm. The optimization process maximizes the fundamental frequency by adjusting the fibre orientations within the composite layers. The mathematical models, based on classical laminated plate theory (CLPT) with von Karman nonlinearity, are solved using MATLAB. The impact of various parameters, including boundary conditions, grid shapes, angles of diagonal ribs, and plate aspect ratios, on the optimized frequency results is thoroughly examined. The results demonstrate that the SRSHC algorithm outperforms the Special Relativity Search (SRS) algorithm, confirming its effectiveness in complex optimization problems with large search spaces. This research contributes to advancing the design of smart structures with enhanced dynamic performance.