TY  - JOUR
A1  - Kavrakov, Igor
A1  - Kareem, Ahsan
A1  - Morgenthal, Guido
T1  - Comparison Metrics for Time-histories: Application to Bridge Aerodynamics
N2  - Wind effects can be critical for the design of lifelines such as long-span bridges. The existence of a significant number of aerodynamic force models, used to assess the performance of bridges, poses an important question regarding their comparison and validation. This study utilizes a unified set of metrics for a quantitative comparison of time-histories in bridge aerodynamics with a host of characteristics. Accordingly, nine comparison metrics are included to quantify the discrepancies in local and global signal features such as phase, time-varying frequency and magnitude content, probability density, nonstationarity and nonlinearity. Among these, seven metrics available in the literature are introduced after recasting them for time-histories associated with bridge aerodynamics. Two additional metrics are established to overcome the shortcomings of the existing metrics. The performance of the comparison metrics is first assessed using generic signals with prescribed signal features. Subsequently, the metrics are applied to a practical example from bridge aerodynamics to quantify the discrepancies in the aerodynamic forces and response based on numerical and semi-analytical aerodynamic models. In this context, it is demonstrated how a discussion based on the set of comparison metrics presented here can aid a model evaluation by offering deeper insight. The outcome of the study is intended to provide a framework for quantitative comparison and validation of aerodynamic models based on the underlying physics of fluid-structure interaction. Immediate further applications are expected for the comparison of time-histories that are simulated by data-driven approaches.
KW  - Ingenieurwissenschaften
KW  - Aerodynamik
KW  - Brücke
KW  - Bridge
Y1  - 2020
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200625-41863
UR  - https://ascelibrary.org/doi/10.1061/%28ASCE%29EM.1943-7889.0001811
N1  - This material may be downloaded for personal use only. Any other use requires prior permission of the American Society of Civil Engineers. This material may be found at https://ascelibrary.org/doi/10.1061/%28ASCE%29EM.1943-7889.0001811.
N1  - This is the final draft of the following article: https://ascelibrary.org/doi/10.1061/%28ASCE%29EM.1943-7889.0001811, which has been published in final form at https://doi.org/10.1061/(ASCE)EM.1943-7889.0001811
ER  - 
TY  - JOUR
A1  - Gürlebeck, Klaus
A1  - Legatiuk, Dmitrii
A1  - Nilsson, Henrik
A1  - Smarsly, Kay
T1  - Conceptual modelling: Towards detecting modelling errors in engineering applications
JF  - Mathematical Methods in Applied Sciences
N2  - Rapid advancements of modern technologies put high demands on mathematical modelling of engineering systems. Typically, systems are no longer “simple” objects, but rather coupled systems involving multiphysics phenomena, the modelling of which involves coupling of models that describe different phenomena. After constructing a mathematical model, it is essential to analyse the correctness of the coupled models and to detect modelling errors compromising the final modelling result. Broadly, there are two classes of modelling errors: (a) errors related to abstract modelling, eg, conceptual errors concerning the coherence of a model as a whole and (b) errors related to concrete modelling or instance modelling, eg, questions of approximation quality and implementation. Instance modelling errors, on the one hand, are relatively well understood. Abstract modelling errors, on the other, are not appropriately addressed by modern modelling methodologies. The aim of this paper is to initiate a discussion on abstract approaches and their usability for mathematical modelling of engineering systems with the goal of making it possible to catch conceptual modelling errors early and automatically by computer assistant tools. To that end, we argue that it is necessary to identify and employ suitable mathematical abstractions to capture an accurate conceptual description of the process of modelling engineering systems.
KW  - Angewandte Mathematik
KW  - Angewandte Informatik
KW  - Ingenieurwissenschaften
KW  - Modellierung
KW  - engineering
KW  - abstraction
KW  - modelling
KW  - formal approaches
KW  - type theory
Y1  - 2019
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200110-40614
UR  - https://onlinelibrary.wiley.com/doi/abs/10.1002/mma.5934
SP  - 1
EP  - 10
ER  -