The double-suction centrifugal fans are designed under a standard atmospheric condition but are usually operated under off-design conditions where the ambient temperature varies, in which the density and viscosity of the air are different from those of the standard condition, thereby affecting the fan’s performance. This work performed a surrogate-based multi-objective reliability-based design optimization (RBDO) on a double-suction centrifugal fan considering the ambient temperature (T) uncertainty. The RBDO intends to improve the static pressure rise (P_s) and static pressure efficiency (η_s) of the fan by optimizing the design variables of outlet installation angle, camberline radius and number of the blades, and the volute pitch. The global sensitivity analysis using Sobol’ and Borgonovo indices reveal that the volute pitch dominates η_s, while the blade camberline radius and volute pitch dominate P_s. The Borgonovo index highlights the non-negligible effect of blade outlet installation angle on the probability distribution of P_s and η_s. The effectiveness of RBDO was validated through the Reynolds-Averaged Navier-Stokes (RANS) simulations. The RBDO improves P_s and η_s by 10.44% and 1.87%, respectively, at T = 20°C where the fan is designed, and by 8.62% and 2.00% at T = 0°C, and 9.39% and 2.06% at T = 40°C, revealing a robust effectiveness of RBDO. The working capability of the optimized fan within a range of ambient temperature is quantified to evaluate the trade-off between performance improvement and feasible reliability. The design feasibility domain reduces significantly due to the temperature sensitivity which determines the safety margin as the target static pressure rise exceeds 84 Pa. An analysis on flow physics demonstrates that the optimized fans effectively suppress the separation and recirculating vortices, weaken the entropy generation, and generate a better uniform distribution of flow angle and velocity in multiple blade passages of the impeller, which contributes to the improved performance of the fan.

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Reliability-based design optimization and working capability quantification for a double-suction centrifugal fan subject to ambient temperature uncertainty