Uncertainty Quantification for Engineering Design

AIEDAM Special Issue, Spring 2017, Vol.31, No.2

Guest Editors: Roger Ghanem and Xiaoping Du

Engineering design is generally predicated on a presumed behaviour of a given system in response to a specified range of loading conditions. With improved sensing, control and adaptation schemes, both external and internal conditions are characterized with increasing accuracy, permitting safer operation closer to the failure envelope. These technological and scientific advances not withstanding, discrepancies remain between anticipated and actual behaviours of most engineered systems, often becoming significant as instabilities or failure are approached. The ability to understand, analyse and characterize the sources and the impact of these errors will have important ramifications on the economy, performance, and safety of these systems.

Recent advances on the topic of Uncertainty Quantification have enabled the closer integration of data-driven and model-driven paradigms for parameter characterization and performance prediction of many systems of interest in science and engineering. The impact of these capabilities on engineering design are just beginning to be felt with significant implications on the interplay between performance, efficiency, and risk of both specific products and the design process as a whole.

This special issue on Uncertainty Quantification for Engineering Design will consider contributions in that demonstrate the significance of uncertainty quantification on the any aspect of the design process. A sample of issues to be considered includes:

  • Formulation of novel objective functions and constraints for design that account for uncertainty.
  • Development of efficient algorithms for optimization in the presence of uncertainty.
  • Integration of sensing and uncertainty reduction into the design process.
  • Assessment and management of uncertainty in early stage design.
  • Integration of management and supply-chain uncertainties into the design process.
  • General insight gained from comprehensive case studies.
  • Uncertainty in designs with multiscale or multiphysics behaviour.
  • Uncertainty models, algorithms, assessment, for multi-disciplinary design optimization.

All submissions will be anonymously reviewed by at least three reviewers. The selection for publication will be made on the basis of these reviews. High quality papers not selected for this special issue may be considered for standard publication in AIEDAM.

Note that all enquiries and submissions for special issues go to the Guest Editors, and not to the Editor-in-Chief.

Important dates:
Intend to submit (Title & Abstract):As soon as possible
Submission deadline for full papers:1 March 2016 <-- New Deadline!!
Reviews due:15 April, 2016
Notification & reviews due to authors:1 May 2016
Revised papers due from authors:1 July 2016
Second round of reviews due:15 September 2016
Final version due:1 December 2016
Issue Appears:1 Mid May 2017
Guest editors:
Dr. Roger GhanemDr. Xiaoping Du
Dept. of Aerospace & Mechanical EngineeringDept. of Mechanical & Aerospace Engineering
University of Southern CaliforniaMissouri University of Science and Technology
210 KAP Hall400 West 13th Street, Toomey Hall 272
Los Angeles, CA 90089-2531Rolla, MO 65409-0050
USAUSA
Email: ghanem @ usc.eduEmail: dux @ mst.edu