Identification of parameters of the model of toroidal body motion using experimental data

Abstract The application of the systematic procedures in the derivation of the equations of motion proposed in Part I of this work is demonstrated and implemented in detail. The equations of motion for each subsystem are derived individually and are assembled under the concept of compatibility between the local kinematic properties of the elastic degrees of freedom of those connected elastic members. The specific structure under consideration is characterized as an open loop system with spherical unconstrained chains being capable of rotating about a Hooke’s or universal joint. The rigid body motion, due to two unknown rotations, and the elastic degrees of freedom are mutually coupled and influence each other. The traditional motion superposition approach is no longer applicable herein. Numerical examples for several cases are presented. These simulations are compared with the experimental data and good agreement is indicated.

Numerical Research on the Resistance Reduction of Air Intake

Water ◽

10.3390/w11020280 ◽

2019 ◽

Vol 11 (2) ◽

pp. 280 ◽

Cited By ~ 3

Author(s):

Lei Du ◽

Hanbing Sun ◽

Yi Jiang ◽

Ping Li

Keyword(s):

Experimental Data ◽

Froude Number ◽

Body Motion ◽

Forward Motion ◽

Resistance Reduction ◽

Calm Water ◽

Air Intake ◽

Numerical Research ◽

Resistance Performance ◽

Good Agreement

In order to investigate the drag-reducing effect of air intake, forward motion of planing trimaran models in calm water were simulated for Froude numbers ranging from 3.14–5.87. The hull body motion is implemented by coupling the fluid solver with motion solver. Numerical results were compared with the experimental data and showed good agreement. Contrastive calculations of models with and without air intake show that the air intake presents evident drag-reducing effect when Froude number is above 4.49, the cambered configuration of air intake could amplify air cavity and thus decrease fractional resistance. CFD incremental studies were subsequently carried out for the camber of air intake, it is found that the model with chamber-shortened air intake shows the worst resistance performance, while enlarging air intake chamber could reduce resistance at Froude numbers between 4.06 and 4.97.

Three-Dimensional Static Modeling of the Lumbar Spine

Journal of Biomechanical Engineering ◽

10.1115/1.4007172 ◽

2012 ◽

Vol 134 (8) ◽

Cited By ~ 1

Author(s):

Ernur Karadogan ◽

Robert L. Williams

Keyword(s):

Experimental Data ◽

Lumbar Spine ◽

Optimization Technique ◽

Three Dimensional ◽

Lumbar Vertebrae ◽

Lumbar Vertebra ◽

Body Motion ◽

Human Lumbar Spine ◽

Static Modeling ◽

Elastic Elements

This paper presents three-dimensional static modeling of the human lumbar spine to be used in the formation of anatomically-correct movement patterns for a fully cable-actuated robotic lumbar spine which can mimic in vivo human lumbar spine movements to provide better hands-on training for medical students. The mathematical model incorporates five lumbar vertebrae between the first lumbar vertebra and the sacrum, with dimensions of an average adult human spine. The vertebrae are connected to each other by elastic elements, torsional springs and a spherical joint located at the inferoposterior corner in the mid-sagittal plane of the vertebral body. Elastic elements represent the ligaments that surround the facet joints and the torsional springs represent the collective effect of intervertebral disc which plays a major role in balancing torsional load during upper body motion and the remaining ligaments that support the spinal column. The elastic elements and torsional springs are considered to be nonlinear. The nonlinear stiffness constants for six motion types were solved using a multiobjective optimization technique. The quantitative comparison between the angles of rotations predicted by the proposed model and in the experimental data confirmed that the model yields angles of rotation close to the experimental data. The main contribution is that the new model can be used for all motions while the experimental data was only obtained at discrete measurement points.

Microdiffraction Patterns of Small Metallic Particles II; Theoretical Analysis

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100055680 ◽

1982 ◽

Vol 40 ◽

pp. 668-669

Author(s):

A. Gómez ◽

P. Schabes-Retchkiman ◽

M. José-Yacamán ◽

T. Ocaña

Keyword(s):

Experimental Data ◽

Electron Diffraction ◽

Theoretical Analysis ◽

Size Range ◽

Dynamical Theory ◽

Metallic Particles ◽

Splitting Effect

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.

Evidence for ordered Fe3Ni

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100125981 ◽

1987 ◽

Vol 45 ◽

pp. 216-217

Author(s):

K.B. Reuter ◽

D.B. Williams ◽

J.I. Goldstein

Keyword(s):

Experimental Data ◽

Martensitic Transformation ◽

Electron Diffraction ◽

Room Temperature ◽

Direct Evidence ◽

Transformation Product ◽

Iron Meteorites ◽

X Ray ◽

Ni Content ◽

Temperature Transformation

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.

EELS white line intensities calculated for the 3d and 4d metals

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100153919 ◽

1989 ◽

Vol 47 ◽

pp. 388-389

Author(s):

C. C. Ahn ◽

D. H. Pearson ◽

P. Rez ◽

B. Fultz

Keyword(s):

Experimental Data ◽

Line Intensity ◽

Transition Probabilities ◽

Initial Increase ◽

White Line ◽

Hartree Fock ◽

Line Intensities ◽

Integrated Intensity ◽

X Ray Absorption ◽

The Continuum

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.

On the Meta-Analysis of Nonrandom, Quasi-Experimental Data

PsycEXTRA Dataset ◽

10.1037/e518392013-139 ◽

2010 ◽

Author(s):

Richard N. Landers

Keyword(s):

Experimental Data ◽

Meta Analysis ◽

Quasi Experimental

A fuzzy neural network approach for modeling the growth kinetics of FeB and Fe2B layers during the boronizing process

Matériaux & Techniques ◽

10.1051/mattech/2019002 ◽

2018 ◽

Vol 106 (6) ◽

pp. 603 ◽

Cited By ~ 2

Author(s):

Bendaoud Mebarek ◽

Mourad Keddam

Keyword(s):

Neural Network ◽

Experimental Data ◽

Fuzzy Neural Network ◽

Treatment Time ◽

Calculation Model ◽

Average Error ◽

Network Approach ◽

Neural Network Approach ◽

Fuzzy Neural ◽

Kinetics Of

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.

Use of Posterior Probabilities to Evaluate Methods of Discriminant Analysis

Methods of Information in Medicine ◽

10.1055/s-0038-1635316 ◽

1981 ◽

Vol 20 (04) ◽

pp. 207-212 ◽

Cited By ~ 6

Author(s):

J. Hermans ◽

B. van Zomeren ◽

J. W. Raatgever ◽

P. J. Sterk ◽

J. D. F. Habbema

Keyword(s):

Experimental Data ◽

Discriminant Analysis ◽

Posterior Probabilities

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.

Analysis of athletes’ stadium stress source based on improved layered K-means algorithm

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189065 ◽

2020 ◽

Vol 39 (4) ◽

pp. 5905-5914

Author(s):

Chen Gong

Keyword(s):

Experimental Data ◽

Machine Learning Algorithms ◽

User Preference ◽

Experimental Comparison ◽

Actual Situation ◽

Medical Field ◽

Pressure Source ◽

Preference Model ◽

Related Research ◽

Analysis System

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.