Challenges in Modeling Flexible Bodies based on Experimental Data with Utilization in Elastic Multibody Simulation

PAMM ◽  
2017 ◽  
Vol 17 (1) ◽  
pp. 153-154 ◽  
Author(s):  
Claudius Lein ◽  
Michael Beitelschmidt ◽  
Johannes Woller
Volume 2 ◽  
2004 ◽  
Author(s):  
Renzo Capitani ◽  
Tommaso Iacomelli ◽  
Daniele G. Rosti ◽  
Pierluigi Tozzi

The Universita` degli Studi di Firenze joined the Formula Student competition (organised by SAE and IMechE) in 2002 competing in Class 3, the following year the first car was ready to compete in Class 1. In order to build this car, an integrated approach was adopted to obtain the best solution in every aspect. The purpose of the design was to optimise the car handling, fulfilling the Formula SAE rules. All the design phases were based on the Design for X approach, with the aim to optimise all the aspects of the Formula SAE project, like performance, design and cost. A Design for Manufacturing approach was added to the FEA to design all the components, like uprights and wheel spindles, in order to simplify the CNC machining. The suspensions layout was defined using a recursive method based on the Multibody Simulation and the components design. Some experimentations were conducted to verify the simulations. The experimental data were used to start the redesign, to improve the performance of the new car that will compete in the 2004 events.


Author(s):  
Tommaso Tamarozzi ◽  
Gert H. K. Heirman ◽  
Wim Desmet

This paper discusses and further investigates a new methodology, “Static Modes Switching” (SMS), improving computational efficiency for elastic multibody (EMBS) systems. This method focuses on mechanisms in which loading is possible in many degrees of freedom, but only few of them are simultaneously loaded at a given moment in time (e.g. sliding elements, gear contact, etc.). The methodology adapts during simulation the mode set used to represent component flexibility, by judiciously choosing only those static modes that are contributing actively to the body deformation. First, the general methodology is presented, then the current work and its original contributions are discussed; namely SMS is tested on a 3D mechanism including multiple flexible bodies on which sliding elements are present. Moreover, as opposed to previous studies, the locations where external excitation is acting is not known a priori. Finally, some limitations of the proposed methodology are treated with focus on the numerical discontinuities introduced by the switching of the modal base and their propagation to neighbouring bodies.


Author(s):  
A. Gómez ◽  
P. Schabes-Retchkiman ◽  
M. José-Yacamán ◽  
T. Ocaña

The splitting effect that is observed in microdiffraction pat-terns of small metallic particles in the size range 50-500 Å can be understood using the dynamical theory of electron diffraction for the case of a crystal containing a finite wedge. For the experimental data we refer to part I of this work in these proceedings.


Author(s):  
K.B. Reuter ◽  
D.B. Williams ◽  
J.I. Goldstein

In the Fe-Ni system, although ordered FeNi and ordered Ni3Fe are experimentally well established, direct evidence for ordered Fe3Ni is unconvincing. Little experimental data for Fe3Ni exists because diffusion is sluggish at temperatures below 400°C and because alloys containing less than 29 wt% Ni undergo a martensitic transformation at room temperature. Fe-Ni phases in iron meteorites were examined in this study because iron meteorites have cooled at slow rates of about 10°C/106 years, allowing phase transformations below 400°C to occur. One low temperature transformation product, called clear taenite 2 (CT2), was of particular interest because it contains less than 30 wtZ Ni and is not martensitic. Because CT2 is only a few microns in size, the structure and Ni content were determined through electron diffraction and x-ray microanalysis. A Philips EM400T operated at 120 kV, equipped with a Tracor Northern 2000 multichannel analyzer, was used.


Author(s):  
C. C. Ahn ◽  
D. H. Pearson ◽  
P. Rez ◽  
B. Fultz

Previous experimental measurements of the total white line intensities from L2,3 energy loss spectra of 3d transition metals reported a linear dependence of the white line intensity on 3d occupancy. These results are inconsistent, however, with behavior inferred from relativistic one electron Dirac-Fock calculations, which show an initial increase followed by a decrease of total white line intensity across the 3d series. This inconsistency with experimental data is especially puzzling in light of work by Thole, et al., which successfully calculates x-ray absorption spectra of the lanthanide M4,5 white lines by employing a less rigorous Hartree-Fock calculation with relativistic corrections based on the work of Cowan. When restricted to transitions allowed by dipole selection rules, the calculated spectra of the lanthanide M4,5 white lines show a decreasing intensity as a function of Z that was consistent with the available experimental data.Here we report the results of Dirac-Fock calculations of the L2,3 white lines of the 3d and 4d elements, and compare the results to the experimental work of Pearson et al. In a previous study, similar calculations helped to account for the non-statistical behavior of L3/L2 ratios of the 3d metals. We assumed that all metals had a single 4s electron. Because these calculations provide absolute transition probabilities, to compare the calculated white line intensities to the experimental data, we normalized the calculated intensities to the intensity of the continuum above the L3 edges. The continuum intensity was obtained by Hartree-Slater calculations, and the normalization factor for the white line intensities was the integrated intensity in an energy window of fixed width and position above the L3 edge of each element.


2018 ◽  
Vol 106 (6) ◽  
pp. 603 ◽  
Author(s):  
Bendaoud Mebarek ◽  
Mourad Keddam

In this paper, we develop a boronizing process simulation model based on fuzzy neural network (FNN) approach for estimating the thickness of the FeB and Fe2B layers. The model represents a synthesis of two artificial intelligence techniques; the fuzzy logic and the neural network. Characteristics of the fuzzy neural network approach for the modelling of boronizing process are presented in this study. In order to validate the results of our calculation model, we have used the learning base of experimental data of the powder-pack boronizing of Fe-15Cr alloy in the temperature range from 800 to 1050 °C and for a treatment time ranging from 0.5 to 12 h. The obtained results show that it is possible to estimate the influence of different process parameters. Comparing the results obtained by the artificial neural network to experimental data, the average error generated from the fuzzy neural network was 3% for the FeB layer and 3.5% for the Fe2B layer. The results obtained from the fuzzy neural network approach are in agreement with the experimental data. Finally, the utilization of fuzzy neural network approach is well adapted for the boronizing kinetics of Fe-15Cr alloy.


1981 ◽  
Vol 20 (04) ◽  
pp. 207-212 ◽  
Author(s):  
J. Hermans ◽  
B. van Zomeren ◽  
J. W. Raatgever ◽  
P. J. Sterk ◽  
J. D. F. Habbema

By means of a case study the choice between several methods of discriminant analysis is presented. Experimental data of a two-groups problem with one or two variables is analysed. The different methods are compared according to posterior probabilities which can be computed for each subject and which are the basis of discriminant analysis. These posterior probabilities are analysed graphically as well as numerically.


2020 ◽  
Vol 39 (4) ◽  
pp. 5905-5914
Author(s):  
Chen Gong

Most of the research on stressors is in the medical field, and there are few analysis of athletes’ stressors, so it can not provide reference for the analysis of athletes’ stressors. Based on this, this study combines machine learning algorithms to analyze the pressure source of athletes’ stadium. In terms of data collection, it is mainly obtained through questionnaire survey and interview form, and it is used as experimental data after passing the test. In order to improve the performance of the algorithm, this paper combines the known K-Means algorithm with the layering algorithm to form a new improved layered K-Means algorithm. At the same time, this paper analyzes the performance of the improved hierarchical K-Means algorithm through experimental comparison and compares the clustering results. In addition, the analysis system corresponding to the algorithm is constructed based on the actual situation, the algorithm is applied to practice, and the user preference model is constructed. Finally, this article helps athletes find stressors and find ways to reduce stressors through personalized recommendations. The research shows that the algorithm of this study is reliable and has certain practical effects and can provide theoretical reference for subsequent related research.


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