Optimization of intentional mistuning patterns for the mitigation of the effectsof random mistuning

Yun Han, Raghavendra Murthy, Marc Mignolet, Jeff Lentz

Research output: Contribution to journalArticlepeer-review

51 Scopus citations


This paper focuses on the optimization of intentional mistuning patterns for the reduction of the sensitivity of the forced response of bladed disks to random mistuning. Intentional mistuning is achieved here by using two different blade types (denoted as A and B) around the disk. It is thus desired to find the arrangement of these A and B blades (A/B pattern) that leads to the smallest 99th percentile of the amplitude of blade response in the presence of random mistuning. It is first demonstrated that there usually is a large number of local minima and further that the cost of a function evaluation is high. Accordingly, two novel, dedicated optimization algorithms are formulated and validated to address this specific problem. Both algorithms proceed in a two-step fashion. The first step, which consists of an optimization in a reduced space, leads to a series of good initial guesses. A local search from these initial guesses forms the second step of the methods. A detailed validation effort of this new procedure was next achieved on a single-degree-of-freedom- per-blade model, a reduced order model of a blisk, and that of an impeller considered in an earlier study. In all validation cases, the two novel algorithms were found to converge to the global optimum or very close to it at a small computational cost. Finally, the results of these optimization efforts further demonstrate the value of intentional mistuning to increase the robustness of bladed disks to random mistuning.

Original languageEnglish (US)
Article number62505
JournalJournal of Engineering for Gas Turbines and Power
Issue number6
StatePublished - Jun 1 2014


  • blade vibration
  • bladed disk
  • forced response robustness
  • intentional mistuning
  • mistuning

ASJC Scopus subject areas

  • Nuclear Energy and Engineering
  • Fuel Technology
  • Aerospace Engineering
  • Energy Engineering and Power Technology
  • Mechanical Engineering


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