A Short-Time Non-Gaussian Probability Approximation Based Method for Response Transitions of a Lévy-Driven Nonsmooth System

<div>Comparison of short-time PDF estimated by (a) direct low-order moments by statistical simulations with 30 samples, (b) proposed probability core with 30 samples, (c) full Monte-Carlo simulations with <svg height="11.7978pt" id="M127" style="vertical-align:-0.2063999pt" version="1.1" viewbox="-0.0498162 -11.5914 17.5728 11.7978" width="17.5728pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M384 0V27C293 34 287 42 287 114V635C232 613 172 594 109 583V559L157 557C201 555 205 550 205 499V114C205 42 199 34 109 27V0H384Z"></path></g><g transform="matrix(.013,0,0,-0.013,6.24,0)"><path d="M241 635C89 635 35 457 35 312C35 153 89 -12 240 -12C390 -12 443 166 443 312C443 466 390 635 241 635ZM238 602C329 602 354 454 354 312C354 172 330 22 240 22C152 22 124 173 124 313S148 602 238 602Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,12.527,-5.741)"><path d="M141 347C171 480 264 541 327 570C364 587 403 599 436 605L429 641C389 634 339 622 300 609C191 570 37 458 37 239C37 86 126 -12 245 -12C367 -12 454 89 454 210C454 314 380 397 272 397C252 397 230 390 208 380L141 347ZM231 338C323 338 366 257 366 174C366 108 340 27 263 27C180 27 129 123 129 244C129 268 130 292 135 310C158 323 193 338 231 338Z"></path></g></svg> samples as a benchmark.</div>

Mathematical Problems in Engineering

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Figure 4

Figure 4: A Short-Time Non-Gaussian Probability Approximation Based Method for Response Transitions of a Lévy-Driven Nonsmooth System 