Statistische Modellbildung

Siebertz, Karl; Bebber, David van; Hochkirchen, Thomas

doi:10.1007/978-3-642-05493-8_4

Cited by 10 publications

(9 citation statements)

References 2 publications

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“…The subdomains are connected by tie contacts. All of these are meshed with linear reduced-integrated hexahedron elements C3D8R, except the inner wheel domain (1), which is meshed with quadratic tetrahedron elements C3D10I. The edge length of the elements in the contact subdomains is equilateral 0.75 mm.…”

Section: Finite Element Modelmentioning

confidence: 99%

“…In this study, the following definitions according to Siebertz et al. 1 are considered: Parameters: All input and output variables are called parameters. Factors: The input variables, which are controlled in the sensitivity analysis, are called factors. …”

Section: Analysis Setupmentioning

confidence: 99%

“…Additionally, the method ensures that the combination of the values for the different factors is evenly distributed in the corresponding hypercube. 1 The study is focused on the wheel-rail normal contact of a freight wagon wheel on a straight rail. The system of the wheel-rail normal contact comprises designed input parameters, input parameters from the wheelset motion, and disturbance parameters.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, the method ensures that the combination of the values for the different factors is evenly distributed in the corresponding hypercube. 1…”

Section: Introductionmentioning

confidence: 99%

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Sensitivity analysis of the wheel–rail normal contact on the basis of continuous factors

Dörner

Bettinger

Schindler

2016

Proceedings of the Institution of Mechanical Engineers, Part F:

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The exact characterization of the wheel-rail normal contact situations is essential for its wear, fatigue, and guidance analysis. To simulate this contact, numerous input parameters are required. Many of them have to be estimated. The aim of this sensitivity analysis was to investigate the direct effects and interactions of the input parameters on the contact pressure distribution of a freight wagon wheel on a straight track. For this purpose, a finite element model was parametrized in such a way that all the parameters were continuous. This research demonstrates that the output parameters of the wheel-rail contact simulations have a broad deviation and the input variable with the most influence on the contact form and position is the lateral displacement of the wheelset. Nevertheless, the profile shape of the wheel and rail, the wheel radius, and the relative wheel-rail inclination are important input parameters as well, and also need to be considered for exact simulations of the wheel-rail contact. On the other hand, the deviation of material parameters of wheel and rail steel can be neglected.

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Section: Finite Element Modelmentioning

confidence: 99%

Section: Analysis Setupmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Additionally, the method ensures that the combination of the values for the different factors is evenly distributed in the corresponding hypercube. 1…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Sensitivity analysis of the wheel–rail normal contact on the basis of continuous factors

Dörner

Bettinger

Schindler

2016

Proceedings of the Institution of Mechanical Engineers, Part F:

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“…The quality of the ANN is reported in TABLE VIII showing the R-values of the cross-validation (see e.g. [19]) for the test set (ramp-steer). There is a lack of quality, especially for the OMC 3 and 5.…”

Section: Validationmentioning

confidence: 99%

Virtual Optimization of the Interaction between Tires and the Vehicle

Niedermeier¹,

Peckelsen²,

Gauterin³

et al. 2013

IJMO

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This article presents a new method to virtually optimize the tire–vehicle interaction in the early vehicle development phase. The basic principle of the method is the definition of characteristic values (CVs) for the tire and the specification of objective maneuver criteria (OMC) describing the driving behavior using a double-track model for the vehicle. \ud The first ones are the design variables, the second ones are used to calculate the fitness/objective function of the optimization. \ud The strategy for their choice is presented and illustrated with examples. After having analyzed this kind of optimization problem, a genetic algorithm proved to be the most suitable, especially iftaking into account the presence of many local optima. Its parameter settings and its implementation into the structure of the algorithm are presented. Finally, the method is validated in a case study: a real tire (parameterized on a tire test bench) could be reproduced using only its driving behavior as an input. Finally, future prospects and sample applications for this method are presented

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