@article{Vořechovský_2022, title={Adaptive sequential sampling for reliability estimation of binary functions }, volume={36}, url={https://ojs.cvut.cz/ojs/index.php/APP/article/view/8399}, DOI={10.14311/APP.2022.36.0269}, abstractNote={<p>A novel method for estimation of rare event probability is proposed, which works also for computational models returning categorical information only: success or failure. It combines the robustness of<em> simulation</em> methods (counting failure events) with the strength of <em>approximation</em> methods which refine the boundary between the failure and safe sets. Two basic tasks are identified: (i) <em>extension</em> of the experimental design (ED) and (ii) <em>estimation</em> of probabilities. The new<em> extension</em> algorithm adds points for limit state evaluation to the ED by balancing the global<em> exploration</em> and local <em>exploitation</em>, and the <em>estimation</em> uses the pointwise information to build a simple surrogate and perform a novel optimized importance sampling. No connection is presumed between the limit function value at point and its proximity to the failure surface. A new global sensitivity measure of the failure probability to individual variables is proposed and obtained as a by-product of the proposed methods.</p>}, journal={Acta Polytechnica CTU Proceedings}, author={Vořechovský, Miroslav}, year={2022}, month={Aug.}, pages={269–279} }