Special Issue of a Springer journal “Archive of Applied Mechanics”

Numerical analysis and design of structures including polymorphic

uncertain data

edited by

Michael Kaliske, Technische Universitaet Dresden, Germany

Vladik Kreinovich, The University of Texas at El Paso, USA

Numerical simulation of structures is currently often characterized

by deterministic methods. Deterministic models of the reality

indicate preciseness and safety, while, on contrary all available

data and information are characterized by various types of

uncertainty (variability, imprecision, incompleteness), which

cannot be neglected. Polymorphic uncertainty comprehends all of

these types of uncertainty and their combinations. The main focus

of the special issue is the presentation of methods for the

numerical analysis and design of structures under consideration of

polymorphic data uncertainty.

Engineering solutions are characterized by inherent robustness and

flexibility as essential features for a faultless life of

structures under uncertain and changing conditions. Implementing

these features in a system requires comprehensive consideration of

uncertainty in the model parameters, in environmental and human

imposed loads as well as other types of intrinsic and epistemic

uncertainties. Numerical design of structures should be robust with

respect to (spatial and time dependent) uncertainties inherently

present in material characteristics, boundary conditions etc. This

requires in turn a reliable numerical analysis, assessment and

prediction of the lifecycle of structures, taking explicitly into

account the effect of unavoidable uncertainties (limited or dubious

information, human factors, subjectivity and experience, linguistic

assessment, imprecise measurement, unclear physics etc.).

Recent developments of numerical methods in the field of "real

world" engineering problems, which include a comprehensive

consideration of uncertainty and associated efficient analysis

techniques are requested. Contributions regarding respective

advanced methods, such as stochastic analysis, interval analysis,

fuzzy analysis, polymorphic uncertainty quantification, surrogate

modeling, multi-fidelity simulation and high performance computing

are explicitly invited. These may address the incorporation of

dependencies within and between uncertain quantities as well as

uncertainty models for spatial and temporal dependent quantities

submission system of the publisher. Please do not forget to

indicate the special issue when submitting. The deadline for

submissions is June 30, 2023.

We are looking forward to receiving your manuscripts.