Intelligent Extremum Surrogate Modeling Framework for Dynamic Probabilistic Analysis of Complex Mechanism

<table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr class="thead"><td class="align_left">Random variable</td><td class="align_center"><i>ρ</i> (kg·m<sup>−3</sup>)</td><td class="align_center"><i>µ</i></td><td class="align_center"><i>V</i> (°/s)</td><td class="align_center"><i>M</i><sub><i>f</i></sub> (N·m)</td></tr><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr><td class="align_left">Mean</td><td class="align_center">7740</td><td class="align_center">0.05</td><td class="align_center">12</td><td class="align_center">1910</td></tr><tr><td class="align_left">Standard deviation</td><td class="align_center">232</td><td class="align_center">0.00333</td><td class="align_center">1.33</td><td class="align_center">66.67</td></tr><tr class="table-tr"><td colspan="5"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Distribution features of input random variables.</div>

Mathematical Problems in Engineering

tab2

Table 2

Table 2: Intelligent Extremum Surrogate Modeling Framework for Dynamic Probabilistic Analysis of Complex Mechanism 