scholarly journals Structural Dynamic Reanalysis of Cantilever Beam Using Polynomial Regression Method

2016 ◽  
Vol 13 (05) ◽  
pp. 01-14
Author(s):  
C. Srikarrao ◽  
K. Kumar ◽  
P.Pavan Kumar ◽  
C. Mukul ◽  
P. Vinay
Keyword(s):  
Cantilever Beam ◽  
Polynomial Regression ◽  
Regression Method ◽  
Structural Dynamic ◽  
Dynamic Reanalysis

Access to Empirical Formulations of Combustion Efficiency for Gas Turbine Combustors with Improved Generalization Ability

2020 ◽  
pp. 1-32
Author(s):  
Zhuang Ma ◽  
Tingwei Ji ◽  
Tao Cui ◽  
Yao Zheng
Keyword(s):  
Experimental Data ◽  
Polynomial Regression ◽  
Burning Velocity ◽  
Velocity Model ◽  
Combustion Efficiency ◽  
Symbolic Regression ◽  
Regression Method ◽  
Generalization Ability ◽  
Operating Variables ◽  
Model Structures

Abstract Correlating combustion performance parameters to the main operating variables of combustors with mathematical expressions contributes to reducing the number of experiments and simplifying the design procedure of gas turbines. The application of empirical formulations meets the requirement with finite precision. The present study aims at adopting symbolic regression method to establish empirical formulations to correlate combustion efficiency with the main operating variables of gas turbine combustors. Differing from ordinary data modeling methods that search model parameters only with model structures fixed, symbolic regression method can search the structures and parameters of mathematical models simultaneously. In this article, attempts to correlate the experimental data of Combustor I using the mechanism model of burning velocity model, neural network, polynomial regression and symbolic regression are shown sequentially. Burning velocity model has not satisfactory accuracy by comparing the predictions with the experimental data which means its lower generalization ability. Comparatively, the predictions of the empirical formulation obtained by the present symbolic regression method are in good agreement with the experimental data, and also excel those of neural network and polynomial regression in generalization ability. Another two formulations are obtained by symbolic regression using the experimental data of Combustor II and III, and the different model structures of the two formulations indicate that there is still room for improvement in the present method.

Beam Element Structural Dynamics Modification Using Experimental Modal Rotational Data

1995 ◽  
Vol 117 (3A) ◽  
pp. 265-271 ◽  
Author(s):  
John A. Cafeo ◽  
Martin W. Trethewey ◽  
H. Joseph Sommer
Keyword(s):  
Finite Element ◽  
Cantilever Beam ◽  
Degrees Of Freedom ◽  
Element Model ◽  
Structural Dynamic ◽  
Modal Data ◽  
Structural Dynamic Modification ◽  
Dynamic Modification ◽  
Rotational Degrees Of Freedom ◽  
Fixed Beam

Structural dynamic modification (SDM) of a fixed-free (cantilever) beam to convert it into a fixed-fixed beam with experimental modal data is presented. The SDM focuses on incorporating experimental rotational degrees-of-freedom (DOF) measured with a novel laser measurement technique. A cantilever beam is tested to develop the experimental modal database including rotational degrees of freedom. A modal database from a finite-element model also is developed for comparison. A structural dynamic modification, with both databases, is performed using a Bernoulli-Euler beam to ground the free end of the cantilever beam. The hardware is then modified and a second experimental modal analysis of the resulting fixed-fixed beam performed. A finite-element model of the fixed-fixed beam also was created. Comparison of results from these four tests are used to assess the effectiveness of SDM using experimental modal rotational data. The evaluation shows that provided high quality experimental rotational modal data can be acquired, SDM work with beam elements can be effective in yielding accurate results.

A Lanczos-based method for structural dynamic reanalysis problems

1994 ◽  
Vol 37 (16) ◽  
pp. 2857-2883 ◽  
Author(s):  
Cheryl M. M. Carey ◽  
Gene H. Golub ◽  
Kincho H. Law
Keyword(s):  
Structural Dynamic ◽  
Dynamic Reanalysis

scholarly journals Multiple polynomial regression method for determination of biomedical optical properties from integrating sphere measurements

2000 ◽  
Vol 39 (7) ◽  
pp. 1202 ◽  
Author(s):  
Jan S. Dam ◽  
Torben Dalgaard ◽  
Paul Erik Fabricius ◽  
Stefan Andersson-Engels
Keyword(s):  
Optical Properties ◽  
Polynomial Regression ◽  
Regression Method ◽  
Integrating Sphere

scholarly journals Evaluating the Performance of Polynomial Regression Method with Different Parameters during Color Characterization

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Bangyong Sun ◽  
Han Liu ◽  
Shisheng Zhou ◽  
Wenli Li
Keyword(s):  
Polynomial Regression ◽  
Color Space ◽  
Polynomial Equation ◽  
Regression Method ◽  
Polynomial Coefficients ◽  
Polynomial Expression ◽  
Optimal Polynomial ◽  
Relationship Of ◽  
Color Conversion ◽  
Color Characterization

The polynomial regression method is employed to calculate the relationship of device color space and CIE color space for color characterization, and the performance of different expressions with specific parameters is evaluated. Firstly, the polynomial equation for color conversion is established and the computation of polynomial coefficients is analysed. And then different forms of polynomial equations are used to calculate the RGB and CMYK’s CIE color values, while the corresponding color errors are compared. At last, an optimal polynomial expression is obtained by analysing several related parameters during color conversion, including polynomial numbers, the degree of polynomial terms, the selection of CIE visual spaces, and the linearization.

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