Stochastic Optimization of a Reinforced Concrete Element with Regard to Ultimate and Serviceability Limit States

Stochastic Optimization of a Reinforced Concrete Element with Regard to Ultimate and Serviceability Limit States

Paper in proceedings (conference paper)

Main goal of the paper is to present an algorithm for stochastic optimization of a steel-reinforced concrete element’s cross section. Firstly, the deterministic problem is introduced and described. The description of uncertainties involved in the process and stochastic reformulation of the problem follows. Afterwards, the algorithm itself is introduced. This algorithm is based on internal cycle of deterministic optimization using reduced gradient method and external cycle of stochastic optimization using regression analysis. From the initialization state, the algorithm assess probabilities that ultimate and serviceability limit states are satisfied. Using regression analysis of these assessed probabilities, the algorithm finds new possible solution. The probabilities are assessed on orthogonal grid via modified bisection method. The paper concludes with presentation of the performed calculations and their results. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Main goal of the paper is to present an algorithm for stochastic optimization of a steel-reinforced concrete element’s cross section. Firstly, the deterministic problem is introduced and described. The description of uncertainties involved in the process and stochastic reformulation of the problem follows. Afterwards, the algorithm itself is introduced. This algorithm is based on internal cycle of deterministic optimization using reduced gradient method and external cycle of stochastic optimization using regression analysis. From the initialization state, the algorithm assess probabilities that ultimate and serviceability limit states are satisfied. Using regression analysis of these assessed probabilities, the algorithm finds new possible solution. The probabilities are assessed on orthogonal grid via modified bisection method. The paper concludes with presentation of the performed calculations and their results. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Design of structural elements; Deterministic optimization; Stochastic optimization

Design of structural elements; Deterministic optimization; Stochastic optimization

VENCLOVSKÝ, J.; ŠTĚPÁNEK, P.; LANÍKOVÁ, I.

06.02.2021

Springer, Cham

978-3-030-61659-5

Studies in Fuzziness and Soft Computing

Recent Advances in Soft Computing and Cybernetics

1434-9922

Studies in Fuzziness and Soft Computing

403

unknown

157

169

12

https://link.springer.com/chapter/10.1007%2F978-3-030-61659-5_14