Auto-Extraction of Modelica Code from Finite Element Analysis or Measurement Data

Modern aero-engines have reached a high level of sophistication and only significant changes will lead to the improvements necessary to achieve the economic and environmental targets of the future. Open rotors constitute a major leap in this direction, both in terms of efficiency and of technological innovation. This calls for a revision of the accepted design practices, and a new focus on phenomena that have been little investigated in the past, such as the Coriolis effect, or the gyroscopic coupling of the blades with the shaft. Experimental results from modern fans, with large blades and strong stagger angles, are showing dependence on Coriolis gyroscopic effects already, an effect that is expected to be strongly enhanced with the proposed open rotor designs. For an accurate prediction of the Coriolis and gyroscopic effects in rotating assemblies a fully experimentally validated approach is needed. Today’s FE models can capture the basic physical phenomena, but experimental confirmation is still needed for the evolution of the mode shapes with angular speed, and the influence of damping and geometric nonlinearities when gyroscopic coupling is considered. To support this validation effort a new rotating test rig will be introduced, initial measurement data will be discussed, and a comparison with a finite element analysis presented. Different forcing patterns, including forward and backward travelling-wave engine order excitation could be experimentally excited in the new rig, Coriolis-induced frequency splits were found in the dynamic response, showing a significant change in the dynamic behaviour of the investigated dummy disk, and only a minor impact of the mistuning was observed on the frequency splits due to Coriolis effects. The experimental results have been compared to a finite element analysis, and after some updating a good agreement between the predicted and measured Campbell diagrams could be obtained, demonstrating the reliability of the modelling approach.

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Bayesian Prediction of Pre-Stressed Concrete Bridge Deflection Using Finite Element Analysis

Sensors ◽

10.3390/s19224956 ◽

2019 ◽

Vol 19 (22) ◽

pp. 4956

Author(s):

Jaebeom Lee ◽

Kyoung-Chan Lee ◽

Sung-Han Sim ◽

Junhwa Lee ◽

Young-Joo Lee

Keyword(s):

Finite Element Analysis ◽

Finite Element ◽

Prediction Models ◽

Measurement Data ◽

Element Model ◽

Time Dependent ◽

Probabilistic Prediction ◽

Element Analysis ◽

Actual Measurement ◽

Railway Bridges

Vertical deflection has been emphasized as an important safety indicator in the management of railway bridges. Therefore, various standards and studies have suggested physics-based models for predicting the time-dependent deflection of railway bridges. However, these approaches may be limited by model errors caused by uncertainties in various factors, such as material properties, creep coefficient, and temperature. This study proposes a new Bayesian method that employs both a finite element model and actual measurement data. To overcome the limitations of an imperfect finite element model and a shortage of data, Gaussian process regression is introduced and modified to consider both, the finite element analysis results and actual measurement data. In addition, the probabilistic prediction model can be updated whenever additional measurement data is available. In this manner, a probabilistic prediction model, that is customized to a target bridge, can be obtained. The proposed method is applied to a pre-stressed concrete railway bridge in the construction stage in the Republic of Korea, as an example of a bridge for which accurate time-dependent deflection is difficult to predict, and measurement data are insufficient. Probabilistic prediction models are successfully derived by applying the proposed method, and the corresponding prediction results agree with the actual measurements, even though the bridge experienced large downward deflections during the construction stage. In addition, the practical uses of the prediction models are discussed.

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INVESTIGATION OF DISPLACEMENT CONTROL EFFECT OF DIFFERENT AUXILIARY METHODS ON THE BASIS OF MEASUREMENT DATA AND FINITE ELEMENT ANALYSIS

Doboku Gakkai Ronbunshuu C ◽

10.2208/jscejc.64.473 ◽

2008 ◽

Vol 64 (3) ◽

pp. 473-484

Author(s):

Hiroyuki ARAKI ◽

Koji MITANI ◽

Keiji YASUDA ◽

Seigo TAKASHITA ◽

Hidenori YOSHIDA ◽

...

Keyword(s):

Finite Element Analysis ◽

Finite Element ◽

Measurement Data ◽

Displacement Control ◽

Control Effect ◽

Element Analysis

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Study on the Applicability of Dynamic Factor Standards by Comparison of Spring Constant Based Dynamic Factor of Ballasted and Concrete Track Structures

Applied Sciences ◽

10.3390/app10238361 ◽

2020 ◽

Vol 10 (23) ◽

pp. 8361

Author(s):

Jaeik Lee ◽

Kyuhwan Oh ◽

Yonggul Park ◽

Junhyeok Choi

Keyword(s):

Finite Element Analysis ◽

Finite Element ◽

Field Measurement ◽

Function Analysis ◽

Measurement Data ◽

Spring Constant ◽

Dynamic Factor ◽

Calculation Methods ◽

Element Analysis ◽

Standard Design

Dynamic factor evaluation method calculation methods outlined by Eisenmann (DAFEisenmann) and the American Railway Engineering Association (DAFArea) are used to calculate the dynamic factor during design and for trackside measurement, respectively, in nations where the construction of concrete track structures is relatively new. In this situation, dynamic factor calculation methods may be incorrect, and this is demonstrated by comparison of the respective track types’ total spring constant. A finite element analysis of a standard design railway track is conducted, and the design total spring constant (TSC, or K) obtained from the time history function analysis is compared to the TSC of existing tracks through trackside measurement results. The comparison result shows that TSC obtained by finite element analysis result is 22% higher than that of the trackside measurement value, indicating that the TSC is conservative in the current track design. Considering the proportional relationship between TSC and dynamic factor, it is estimated that the dynamic factor currently being applied in track design is also conservative. Based on these findings, an assessment of the applicability of different dynamic factors (DAFEisenmann and DAFArea), theoretical calculation and field measurement (DAFField) using the probabilistic analysis of wheel loads from the field measurement data is conducted. A correlative analysis between DAFEisenmann and DAFArea shows that DAFEisenmann and DAFArea were estimated to be higher by 33% and 27% in ballasted track and by 39% and 30% in concrete track than the dynamic factor derived from field measurement, respectively, which indicates that the dynamic factor currently in use can potentially lead to over-estimation in track design and maintenance.

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