MODELING THERMAL DISPLACEMENTS IN MODULAR TOOL SYSTEMS

2004 ◽  
Vol 14 (06) ◽  
pp. 2125-2132 ◽  
Author(s):  
NIELS WESSEL ◽  
JÖRG AßMUS ◽  
UDO SCHWARZ ◽  
JÜRGEN KURTHS ◽  
FRANK WEIDERMANN ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Measured Data ◽  
Data Sets ◽  
Nonlinear Regression Analysis ◽  
Thermally Induced ◽  
Alternating Conditional Expectation ◽  
Maximal Correlation ◽  
Thermal Displacements ◽  
Manufacturing Accuracy ◽  
Ace Algorithm

There is an important interest in compensating thermally induced errors of modular tool systems to improve the manufacturing accuracy. In this paper, we test the hypothesis whether we can predict such thermal displacements by using a nonlinear regression analysis, namely the alternating conditional expectation algorithm (ACE [Breiman & Friedman, 1985]), reliably. The data analyzed were generated by two different finite element spindle models of modular tool systems. As the main result, we find that the ACE-algorithm is a powerful tool to model the relation between temperatures and displacements. The maximal correlation is larger than 0.999 in both cases, which demonstrates the suitability of the ACE algorithm. Furthermore, preconditions for the applicability of this approach, such as the length and the support of measured data sets, are studied. Hence, this approach seems to be promising for the application to real modular tool systems.

Prediction of Thermal Displacements in Finite Element Tool Models

2001 ◽  
Author(s):  
Jörg Aßmus ◽  
Niels Wessel ◽  
Jürgen Kurths ◽  
Frank Weidermann ◽  
Jan Konvicka ◽  
...  
Keyword(s):  
Finite Element ◽  
Stable Process ◽  
Real Data ◽  
Thermal Displacement ◽  
Thermally Induced ◽  
The Past ◽  
Alternating Conditional Expectation ◽  
Thermal Displacements ◽  
Displacement Based ◽  
Ace Algorithm

Abstract Precision and productivity are very important criteria for the evaluation of modular tool systems and require a thermally stable process with tolerances in the micrometer range. During the past decades there has been an increasing interest in compensating thermally induced errors. In this paper we investigate wheather a prediction of thermal displacement based on a nonlinear regression analysis is possible, namely using the alternating conditional expectation algorithm (ACE) introduced by Breiman and Friedman, 1985. The data we are analyzing were generated by two different finite element spindle models of modular tool systems. As the main result we find that the ACE-algorithm is a powerful tool to model the relation between temperatures and displacements. It could also be a promising approach to handle well-known hysteresis effects. Limitations of this study are the model restricted results, next our findings have to be validated on real data.

PSVI-8 Meta-regression Analysis to Determine the Relationship Between Growing Pig Body Weight and Variation

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 218-219
Author(s):  
Andres Fernando T Russi ◽  
Mike D Tokach ◽  
Jason C Woodworth ◽  
Joel M DeRouchey ◽  
Robert D Goodband ◽  
...  
Keyword(s):  
Body Weight ◽  
Regression Analysis ◽  
Sample Size ◽  
Polynomial Regression ◽  
Data Sets ◽  
Regression Equations ◽  
Prediction Equations ◽  
Data Set ◽  
Rate Of Increase ◽  
The Relationship

Abstract The swine industry has been constantly evolving to select animals with improved performance traits and to minimize variation in body weight (BW) in order to meet packer specifications. Therefore, understanding variation presents an opportunity for producers to find strategies that could help reduce, manage, or deal with variation of pigs in a barn. A systematic review and meta-analysis was conducted by collecting data from multiple studies and available data sets in order to develop prediction equations for coefficient of variation (CV) and standard deviation (SD) as a function of BW. Information regarding BW variation from 16 papers was recorded to provide approximately 204 data points. Together, these data included 117,268 individually weighed pigs with a sample size that ranged from 104 to 4,108 pigs. A random-effects model with study used as a random effect was developed. Observations were weighted using sample size as an estimate for precision on the analysis, where larger data sets accounted for increased accuracy in the model. Regression equations were developed using the nlme package of R to determine the relationship between BW and its variation. Polynomial regression analysis was conducted separately for each variation measurement. When CV was reported in the data set, SD was calculated and vice versa. The resulting prediction equations were: CV (%) = 20.04 – 0.135 × (BW) + 0.00043 × (BW)2, R2=0.79; SD = 0.41 + 0.150 × (BW) - 0.00041 × (BW)2, R2 = 0.95. These equations suggest that there is evidence for a decreasing quadratic relationship between mean CV of a population and BW of pigs whereby the rate of decrease is smaller as mean pig BW increases from birth to market. Conversely, the rate of increase of SD of a population of pigs is smaller as mean pig BW increases from birth to market.

Numerical Simulation for Uplift Bearing Capacity and Affecting Factors of the Digging Piles in Slope Ground

2013 ◽  
Vol 423-426 ◽  
pp. 1292-1295 ◽  
Author(s):  
Xing Yun Wang ◽  
Bin Peng ◽  
Xiao Chao Tang ◽  
Lian Fan
Keyword(s):  
Numerical Simulation ◽  
Regression Analysis ◽  
Finite Difference ◽  
Bearing Capacity ◽  
Mutual Effect ◽  
Simulation Method ◽  
Affecting Factors ◽  
Slope Ratio ◽  
Nonlinear Regression Analysis ◽  
Numerical Simulation Method

Based on the numerical simulation method, this paper has established the numerical simulation method by using of finite difference software of FLAC3D through establishing interface for digging pile-soil. It can consider mutual effect of digging pile-soil. The uplift bearing capacity of the digging pile in slope ground was calculated and the affecting factors of the bearing capacity were analyzed. The results show that the uplift bearing capacity has a negative correlation with the slope ratio, and has a positive correlation with the width or height of the foundation, which can be expressed as a quadratic polynomial. But when the slope ratio is smaller than a certain extent, the capacity no longer increases. Nonlinear regression analysis of calculation data are carried out. Finally, the calculation method of uplift bearing capacity about pile in the slope is developed, which can provide a reference to specification revision and engineering.

Validating and Updating Finite Element Models Using Experimental Measurements of Dynamics

1990 ◽  
Vol 204 (1) ◽  
pp. 45-50
Author(s):  
C F McCulloch ◽  
P Vanhonacker ◽  
E Dascotte
Keyword(s):  
Finite Element ◽  
Structural Dynamics ◽  
Model Updating ◽  
Measured Data ◽  
Physical Parameters ◽  
Experimental Measurements ◽  
Finite Element Models ◽  
Data Sets ◽  
Modal Data ◽  
Modelling Assumptions

A method is proposed for updating finite element models of structural dynamics using the results of experimental modal analysis, based on the sensitivities to changes in physical parameters. The method avoids many of the problems of incompatibility and inconsistency between the experimental and analytical modal data sets and enables the user to express confidence in measured data and modelling assumptions, allowing flexible but automated model updating.

Regression Analysis on Influences of Hem Parameters on Flare Sagging of Semi-Circular Skirt

2011 ◽  
Vol 331 ◽  
pp. 594-598
Author(s):  
Hong Ni
Keyword(s):  
Regression Analysis ◽  
Statistical Analysis ◽  
Measured Data ◽  
Silk Fabric ◽  
Linear Regression Equation ◽  
Analysis Software ◽  
Wool Fabrics ◽  
Object Of Study ◽  
The Relationship ◽  
Statistical Analysis Software

Select 45 pieces of silk, cotton and wool fabrics in total, with semi-circular skirt modeling as object of study, investigate the relationship between flare sagging in straight & inclined grains of skirt pieces and fabric types, analyze the influence of hem parameters on flare sagging of semi-circular skirt and obtain multiple linear regression equation by disposing the measured data with SPSS statistical analysis software. The study result shows that the skirt hem of silk fabric is sagging more significantly than that of cotton and wool fabrics and there is a multi-linear relationship between semi-circular flare sagging and parameters.The research of this subject has both theoretical value and practical value.

Acoustic Velocity Measurements and Interpretation for Challenging Fluid Systems

SPE Journal ◽  
2016 ◽  
Vol 22 (01) ◽  
pp. 103-119 ◽  
Author(s):  
Edward Lewis ◽  
Birol Dindoruk
Keyword(s):  
Heat Capacity ◽  
Isothermal Compressibility ◽  
Measured Data ◽  
Acoustic Velocity ◽  
Hydrocarbon Mixture ◽  
Data Sets ◽  
Velocity Measurements ◽  
Numerical Work ◽  
Reliable Determination ◽  
Quality Control Tool

Summary In terms of experimentation, acoustic velocity can be measured with a high degree of accuracy. Several thermodynamic properties related to acoustic velocity such as density, isothermal compressibility, and heat capacity can be extracted from measured data. In this study, technical improvements are implemented in an effort to develop a technique for fast and reliable determination of fluid properties on the basis of acoustic velocity measurements over an expanded range of pressures. The potential use of this device as a quality-control tool in typical pressure/volume/temperature (PVT) measurements is demonstrated. Baseline measurements matched to published literature verify the suitability of the device. Results of tests on three recombined oil samples containing dissolved gas, with prescribed gas/oil ratios (GORs), and one bitumen sample are presented. A sharp change in the acoustic velocity trend near the gas/liquid-saturation point is evidence of gas evolution during depressurization. Strong attenuation complicates measurement of acoustic velocity on the heavy fluids used in this study. Blending bitumen with a midrange-molecular-weight hydrocarbon mixture enables estimation of the undiluted-fluid acoustic velocity by extrapolation. By use of the measured acoustic velocity data available, a methodology is developed to estimate and quality check measured isothermal compressibility (κT) values. This is especially important for low-compressibility systems. Heat-capacity data for simple alkanes (CH4 to n-C10) and toluene helps to define a reasonable range of heat-capacity ratio (γ) expected for typical reservoir fluids. For the typical values of acoustic velocity encountered in the pressure and temperature range of interest, the isothermal compressibility can be calculated and/or quality checked by use of estimated values of γ. In addition, by use of various data sets and by performing graphical error analysis, we have shown the reasons that the methodology works. Available data for n-decane and n-hexadecane along with measured data for a live oil and numerical work on calibrated data sets in this study are used to develop the methodology.

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