کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
567959 1452129 2015 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Simultaneous optimization of photostrictive actuator locations, numbers and light intensities for structural shape control using hierarchical genetic algorithm
ترجمه فارسی عنوان
بهینه سازی همزمان نقاط محرک عکس، جاذبه و شدت نور برای کنترل شکل ساختاری با استفاده از الگوریتم ژنتیک سلسله مراتبی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزار
چکیده انگلیسی


• Controlling and geometrical parameters are simultaneously optimized.
• A two-level bi-coded chromosome is proposed.
• HGA can avoid premature convergence and converges fast.
• Proposed FE computation using sparse FE mesh is comparable to available ones.

The present paper introduces an investigation into simultaneous optimization of the PbLaZrTi-based actuator configuration and corresponding applied light intensity for morphing beam structural shapes. A finite element formulation for multiphysics analysis of coupled opto-electro-thermo-mechanical fields in PbLaZrTi ceramics is derived and verified with the theoretical solution and the commercial software ANSYS. This element is then used to simulate beam bending shape control using the orthotropic PbLaZrTi actuators and the simultaneous optimization. In this procedure, the controlling and geometrical variables are simultaneously optimized via a hierarchical genetic algorithm. A bi-coded chromosome is proposed in a hierarchical mode, which consists of some control genes (i.e. actuator location and number) and parametric genes (i.e. applied light intensity). Whether the parametric gene is activated or not is managed by the value of the first-grade control genes. The numerical results demonstrate that the achieved beam bending shapes correlate remarkably well with the expected ones and the simultaneous optimization of photostrictive actuator locations, numbers and light intensities can result in optimal actuator layout with less PbLaZrTi actuators and irradiated light energy. The simulation results also show that the hierarchical genetic algorithm has more superior performance over the conventional real-coded genetic algorithm.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Advances in Engineering Software - Volume 88, October 2015, Pages 21–29
نویسندگان
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