Uncertainty in design and simulation affects the quality of product directly during the
process of MDO, which should be considered to help designers to make the design decisions,
especially at conceptual design stage. In traditional approaches, this uncertainty is ignored in the hope
that it is not significant to the decision making. In this investigation, firstly, three main uncertainties in
MDO of conceptual design are pointed out and carefully analyzed. Then, an innovative methodology
integrating extract knowledge and probabilistic method to manage these uncertainties is presented.
Considering practical application and eliminating the uncertainty in configuration, we propose a
promising method combining Fuzzy c-means algorithm (FCM) and Rough Sets theory (RST) to
deduce the configuration rule. Furthermore, probabilistic kriging model is utilized as an
approximation model to reduce global computational expense of complex product. Sensitivity
analysis (SA) is used to reduce uncertainty of inputs of simulation, and mean square error (MSE) is
employed to assess model error to reduce model uncertainty. Finally, the validity and necessity of this
methodology are demonstrated through the conceptual design of bulk carrier.
Conceptual design and optimization of cogeneration system based on small modular lead‐cooled fast reactor