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Designing railway infrastructure is a knowledge-intensive task. Although there are a number of mature design authoring systems available, their support for dynamically incorporating domain-specific engineering knowledge is very limited. At the same time, a standardized digital representation of railway engineering knowledge (such as building codes and best practice) does not exists. To overcome this deficiency, this paper proposes the use of Knowledge Based Engineering (KBE) to automate routine design tasks by considering multiple knowledge sources. In this scenario, KBE is used to support a Railway design authoring system. To ensure maximum transparency in the design of the developed KBE application, graphical ‘Business Process Model and Notation’ (BPMN) has been used in combination with ‘Decision Model and Notation’ (DMN) to formalize the underlying engineering knowledge. The KBE application has been developed according to the Methodology for Knowledge-Based Engineering Applications (MOKA). An evaluation of the BPMN/DMN approach shows that it meets up to 58% of the acceptance criteria found in the literature. In addition, BPMN and DMN can already be used in the early capture phase of MOKA and its workflows can be developed into an executable KBE application in the subsequent phases. The results of the test example discussed here show that time savings of up to 97.5% can be achieved in the execution of the KBE application.

Frequency based dynamic substructuring (FBS) allows to predict the dynamic behavior of a complex system where neither building a physical prototype of the assembled system, nor possessing a detailed numerical model of all substructures is required. A task that frequently arises in engineering practice when developing a product containing many supplier parts. However, in the experimental realm, modeling the interface connection between two substructures is not as straightforward as in numerical analysis. The consideration of rotational degrees of freedom (rdof) on the interface seems to be crucial for accurate results, but no common procedure has been established yet. By projecting measured sensor data on interface deformation modes (IDMs) it is possible to consider rdof as well as filtering out uncorrelated measurement noise. The transformation of a measured frequency response function (FRF) matrix on some generalized IDMs has recently been derived by directly using Moore-Penrose pseudoinverses. The transformation process can also be seen as a minimization procedure, e.g. as simple least squares for the displacements and a convex optimization for the forces. This contribution derives the pseudoinverses starting from this minimization point of view, where the engineer is free to choose the quantity to be minimized. From this interpretation, some suggestions for including more engineering judgment in the transformation are made (either gained during testing practice, from measurement variances or mechanical energy minimization principles). We also show that the coupling of transformed FRF matrices effectively corresponds to a weakening of the interface compatibility conditions. Thereby, we hope to give some insight in the meaning of the weighting matrices involved in the transformation, and provide a framework for deriving improved coupling methods in the future.

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