Journal Seeks Papers for Special Issue on Non-Probabilistic and Hybrid Approaches
Journal Seeks Papers for Special Issue on Non-Probabilistic and Hybrid Approaches
Computational models have played a crucial role in the transition from traditional experiment-centered engineering towards a virtual design practice, where the performance of designed components is assessed long before the first prototype is built. In this context, recent advances in numerical approaches enable the application of hyper-resolution, high-fidelity, and first-principle based computer simulations that provide an analyst with an abundance of information on the design at hand.
In most realistic engineering cases, however, the designer is faced with a variety of sources of uncertainty related to both the actual model form and the physical quantities that are used to parametrize these models.
This proposed special issue of the ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering is intended to collect contributions that discuss new theoretical developments and advanced applications of non-probabilistic and hybrid approaches to quantify these uncertainties and analyze the reliability of the results.
The guest editors for the special issue are particularly interested in papers that address theoretical developments in the framework of non-probabilistic, hybrid, or polymorphic uncertainty as well as efficient numerical (or semi-) analytical propagation schemes for forward and inverse analysis with uncertainty models. Papers that apply these methods to challenging and realistic engineering cases in general are also welcome, especially if the non-probabilistic or hybrid models for the uncertainty are based on real data.
The special issue will address topics including new theoretical developments in the modeling of — and simulation with — non-probabilistic or hybrid representations of uncertainty such as intervals, fuzzy sets, set-valued approaches, interval probabilities, credal sets, Dempster-Shafer belief functions, interval fields, or imprecise random fields. Papers can also explore efficient propagation schemes for non-probabilistic or hybrid representations including new algorithmic developments, surrogate models, model order reduction, or low-rank representations.
Papers should be submitted to the journal by May 31, 2020, through ASME Journals Connect at https://journaltool.asme.org. Authors who already have an account should log in and select “Submit Paper” at the bottom of the page. Authors who do not have an account should select “Submissions” and follow the instructions. In either case, authors should select “ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering” when they reach the “Paper Submittal” page and then choose “Non-probabilistic and Hybrid Approaches for Uncertainty Quantification and Reliability Analysis (SI042B)” from the special issue dropdown menu.
Prior to formal submission, please send a copy of your manuscript to the guest editors to ensure the work falls within the scope of the special issue and is otherwise appropriate for peer review.
The guest editors for the special issue are Matthias Faes, Katholieke Universiteit Leuven (KU Leuven), Belgium, matthias.faes@kuleuven.be; David Moens, KU Leuven, Belgium, david.moens@kuleuven.be; Michael Beer, Leibniz University Hannover, Germany, beer@irz.uni-hannover.de; Kok Kwang Phoon, National University of Singapore, Singapore, kkphoon@nus.edu.sg; and Hao Zhang, The University of Sydney, Australia, hao.zhang@sydney.edu.au.
For more information on the ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, visit https://asmedigitalcollection.asme.org/risk. To learn more about the ASME Journal Program, visit www.asme.org/Publications-Submissions/Journals.
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