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SMO Special Issue: Physical, Model, and Statistical Uncertainty in Structural and Multidisciplinary Optimization-revised

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2019-03-05 20:20
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Structural and Multidisciplinary Optimization – Call for papers
Special Issue: Physical, Model, and Statistical Uncertainty in Structural and Multidisciplinary Optimization


The sensitivity of optimal structures to imperfections has emphasized very early on the need to account for uncertainties when doing optimization. The close ties between optimization and a wide range of uncertainties (e.g. physical, model, measurement) have since been widely acknowledged and have led to a multitude of frameworks and developments for carrying out optimization under uncertainty. To consolidate existing knowledge in this area through review papers and focus dissemination of cutting edge research papers, the journal of Structural and Multidisciplinary optimization is thus calling for papers for a special issue on “Physical, Model, and Statistical Uncertainty in Structural and Multidisciplinary Optimization”.


The topics of the special issue can include, but are not limited to:


• Optimization under uncertainty, including but not limited to reliability based design optimization and robust design optimization
• Theoretical foundations and frameworks for analysis and/or design under physical, model, and statistical uncertainty
• Methods for physical uncertainty representation and quantification
• Techniques for statistical uncertainty inference
• Model uncertainty characterization for surrogate models, computational models, and mathematical models
• Frameworks and methods for model verification, validation, and calibration
• Analysis and/or design methodology under epistemic uncertainty
• Review studies that explore frameworks, methods, and algorithms for analysis and/or design under physical, model, and statistical uncertainty
• Case studies and industrial applications that illustrate physical, model, and statistical uncertainty management in a comprehensive manner
• Papers illustrating efficient approaches for teaching reliability based design optimization and optimization under uncertainty


Publication timeline:
Papers submitted for this issue will go through the regular review process, but will receive expedited treatment in processing
• Paper submission by: January 15, 2016 December 15, 2015
• Initial review by: March 15, 2016 February 15, 2016
• Revised paper submission by: April 15, 2016 March 15, 2016
• Final acceptance decision by: May 15, 2016 April 15, 2016
• Publication of the special issue by: October 15, 2016 September 15, 2016


Special issue editors:


Byeng Dong Youn, Seoul National University, bdyoun@snu.ac.kr
Christian Gogu, Université Toulouse III, christian.gogu@univ-tlse3.fr
Raphael Haftka, University of Florida, haftka@ufl.edu