A framework for (D)esign (U)ncertainty (Q)uantification and (O)ptimization
Project description
DUQO: Design Uncertainty Quantification and Optimization framework
This repo is under construction to be submitted to code ocean for reproducibility. Expect big changes after publication on code ocean. Also expect lolhr4ra, i.e. the proposed method for uncertainty quantification.
Reliability Analysis and Reliability-based Robust Design Optimization
Generally, given one or more limit state functions of form
as well as the input distributions
as parametrized by , uncertainty quantification, i.e. reliability-analysis, seeks to compute the probability of failure
To solve the uncertainty optimization, i.e. reliability-based robust design optimization, problem, the evaluation of as well as the expectations and variances of the objective functions
and possible deterministic constraints
with respect to the distribution parameters
is required. Besides the input distributions, duqo
takes the objectives ,
the limit states and the constraints
as input and wraps them with problem.obj_con
to be used by a generic gradient-free optimization algorithm.
Citation
If this repo helped you, I would appreciate citations:
C. Bogoclu, T. Nestorović, D. Roos; Local Latin Hypercube Refinement for Multi-objective Design Uncertainty Optimization, Applied Soft Computing (2021)
Contribution
Contributions welcome as there is a long road ahead to make this research code to a usable one.
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