Probabilistic and sensitivity analyses for the performance characteristics of the main bearings in an operating engine due to variability in bearing properties
by Jin Wang, Nickolas Vlahopoulos, Zissimos P. Mourelatos, Omidreza Ebrat, Kumar Vaidyanathan
International Journal of Vehicle Design (IJVD), Vol. 40, No. 4, 2006

Abstract: Surrogate models (metamodels) are developed and used to evaluate an engine bearing performance and perform probabilistic sensitivity analyses. The metamodels are developed based on results from a simulation solver computed at a limited number of sample points. An integrated system-level engine simulation model, consisting of flexible crankshaft and block dynamic models, connected by a detailed hydrodynamic lubrication model, is employed for constructing the metamodels. An optimal symmetric Latin hypercube sampling algorithm is utilised. The metamodels are employed for performing probabilistic and sensitivity analyses. The initial clearance between the crankshaft and each main bearing and the oil viscosity comprise the random variables. The maximum oil pressure and the percentage of time (time ratio) within each cycle that a bearing operates with oil film thickness less than a user defined threshold value at each main bearing constitute the system performance variables.

Online publication date: Wed, 22-Feb-2006

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Vehicle Design (IJVD):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com