TY - JOUR
T1 - Adaptive vectorial surrogate modeling framework for multi-objective reliability estimation
AU - Lu, Cheng
AU - Teng, Da
AU - Chen, Jun Yu
AU - Fei, Cheng Wei
AU - Keshtegar, Behrooz
N1 - Publisher Copyright:
© 2023
PY - 2023/6
Y1 - 2023/6
N2 - Vectorial modeling concept is proposed in this paper by introducing the matrix theory into the point modeling concept (surrogate modeling strategy), and an adaptive vectorial surrogate modeling framework (AVSMF, short for) is developed based on the vectorial modeling concept and adaptive modeling strategy. Herein, the adaptive modeling strategy is adopted to determine the form of mathematical model of each objective in line with the cost function, the surrogate modeling strategy is regarded as the basis function for reflecting the relationship of the output of single-objective between the relevant inputs, and the matrix theory is used to ascertain the vectors and cell arrays of undetermined parameters and to establish the performance function of multi-objective structures. To validate the proposed method, we use three examples including approximate and probabilistic analysis of nonlinear function with multiple responses, reliability evaluation of landing gear brake system temperature and reliability assessment of aeroengine high-pressure turbine blisk stress, strain and deformation, to demonstrate the effectiveness of the developed AVSMF. Besides, the modeling and simulation properties are verified by comparison of different methods. The results show that the proposed AVSMF has obvious advantages in the computational efficiency and precision.
AB - Vectorial modeling concept is proposed in this paper by introducing the matrix theory into the point modeling concept (surrogate modeling strategy), and an adaptive vectorial surrogate modeling framework (AVSMF, short for) is developed based on the vectorial modeling concept and adaptive modeling strategy. Herein, the adaptive modeling strategy is adopted to determine the form of mathematical model of each objective in line with the cost function, the surrogate modeling strategy is regarded as the basis function for reflecting the relationship of the output of single-objective between the relevant inputs, and the matrix theory is used to ascertain the vectors and cell arrays of undetermined parameters and to establish the performance function of multi-objective structures. To validate the proposed method, we use three examples including approximate and probabilistic analysis of nonlinear function with multiple responses, reliability evaluation of landing gear brake system temperature and reliability assessment of aeroengine high-pressure turbine blisk stress, strain and deformation, to demonstrate the effectiveness of the developed AVSMF. Besides, the modeling and simulation properties are verified by comparison of different methods. The results show that the proposed AVSMF has obvious advantages in the computational efficiency and precision.
KW - Adaptive vectorial surrogate modeling framework
KW - Multi-objective structure
KW - Point surrogate modeling concept
KW - Reliability estimation
KW - Vectorial modeling concept
UR - http://www.scopus.com/inward/record.url?scp=85148324830&partnerID=8YFLogxK
U2 - 10.1016/j.ress.2023.109148
DO - 10.1016/j.ress.2023.109148
M3 - 文章
AN - SCOPUS:85148324830
SN - 0951-8320
VL - 234
JO - Reliability Engineering and System Safety
JF - Reliability Engineering and System Safety
M1 - 109148
ER -