A Comparison of Identification Methods for Estimating Squeeze-Film Damper Coefficients

The problem of identifying the dynamic coefficients relating to inertia, damping, and stiffness, in a single degree of freedom model of squeeze-film behavior, is discussed. It is demonstrated that two methods—referred to as “invariant imbedding” and “state variable filter”—are applicable, and that both yield a recursive scheme for sequentially estimating all three coefficients. The methods are compared through an analysis of simulated data, where the coefficient values are known a-priori. This is followed by a presentation of some typical results obtained from experimental tests, using both transient and forced response data. The comparisons indicate that the state variable filter method is much superior, with respect to both computational efficiency and accuracy.

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The Experimental Determination of Squeeze-Film Dynamic Coefficients Using the State Variable Filter Method of Parametric Identification

Journal of Tribology ◽

10.1115/1.3261901 ◽

1989 ◽

Vol 111 (2) ◽

pp. 252-259 ◽

Cited By ~ 6

Author(s):

J. Ellis ◽

J. B. Roberts ◽

M. D. Ramli

Keyword(s):

Parametric Identification ◽

Squeeze Film ◽

Filter Method ◽

State Variable ◽

Dynamic Coefficients ◽

Low Weight ◽

State Variable Filter ◽

Film Stiffness ◽

Forced Excitation

The state variable filter method of parametric identification is applied in the determination of squeeze-film dynamic coefficients from forced excitation tests on an experimental rig. The experimental squeeze-film damper had a centralizing spring, a central circumferential oil feed groove, and no end seals. Forced excitation tests are recorded at various journal support system natural frequencies and at different journal eccentricities. From these tests, estimates of the direct squeeze-film damping, stiffness and inertial coefficients are derived and presented. These results are shown to be in good agreement with results recently obtained using an independent frequency domain technique. The experimental damping and inertial coefficients were found to be considerably larger than values predicted by conventional short-bearing theory, but relatively insensitive to the support system’s natural frequency (and the forcing frequency) for most of the range investigated. The fluid film stiffness coefficient values at low values of the system’s natural frequency agreed with results from static stiffness tests. Two geometrically identical journals were used, one of steel and one of a low-weight, magnesium alloy. The use of the low weight journal markedly reduced the scatter in the inertial and film stiffness coefficients.

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The Determination of Squeeze Film Dynamic Coefficients From Transient Two-Dimensional Experimental Data

Journal of Tribology ◽

10.1115/1.2920255 ◽

1990 ◽

Vol 112 (2) ◽

pp. 288-296 ◽

Cited By ~ 9

Author(s):

J. B. Roberts ◽

J. Ellis ◽

A. Hosseini Sianaki

Keyword(s):

Experimental Data ◽

Simulated Data ◽

Degree Of Freedom ◽

Squeeze Film ◽

Two Dimensional ◽

Computationally Efficient ◽

Response Data ◽

Lumped Parameter ◽

Experimental Trials ◽

State Variable Filter

A state variable filter (SVF) method of identifying parameters in lumped-parameter systems is extended to accommodate multi-degree-of-freedom problems. The method is computationally efficient and can be used with both transient and forced squeeze-film response data. In this paper the method is successfully applied to the analysis of transient simulated data both with and without signal noise. Finally the method is shown applied in the analysis of two-dimensional transient experimental data from a squeeze-film bearing rig. The identified results for the dynamic film coefficients compare well with results from earlier single-degree-of-freedom experimental trials.

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A New Approach for the Determination of Cam Follower System Parameters

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science ◽

10.1243/pime_proc_1988_202_134_02 ◽

1988 ◽

Vol 202 (5) ◽

pp. 361-368

Author(s):

M K Baru ◽

J Ellis

Keyword(s):

Parametric Identification ◽

Filter Method ◽

New Approach ◽

State Variable ◽

Cam Follower ◽

State Variable Filter ◽

Stiffness And Damping ◽

Design And Manufacture

This paper reports a first investigation in the use of the state variable filter method of parametric identification in the determination of the mass, stiffness and damping content of cam follower systems. Simulated and real experimental data are processed by the technique with good results. Further developments are necessary (extension to higher order systems and inclusion of Coulomb damping) with the long-term aim of applying the results in the design and manufacture of dynamically tuned cams.

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A Study on New Identification Technique With Application to Squeeze Film Bearing System

Volume 2: Combustion and Fuels; Oil and Gas Applications; Cycle Innovations; Heat Transfer; Electric Power; Industrial and Cogeneration; Ceramics; Structures and Dynamics; Controls, Diagnostics and Instrumentation; IGTI Scholar Award ◽

10.1115/93-gt-060 ◽

1993 ◽

Author(s):

Ting Nung Shiau ◽

Chun Pao Kuo ◽

G. J. Sheu ◽

P. L. Kuo

Keyword(s):

Hybrid Method ◽

Parameters Identification ◽

Experimental Simulation ◽

Squeeze Film ◽

Filter Method ◽

Noise Effect ◽

Initial Values ◽

Identification Technique ◽

State Variable Filter ◽

Identification Techniques

Two identification techniques, which are the Method of Feasible Directions (MFD) based on optimization concept and the Hybrid Method (HM) combining the merits of the State Variable Filter method (SVF) and MFD, are proposed for the parameters identification of rotor system with squeeze-film damper (SFD). The parameters of SFD, including hydrodynamic inertia, damping and stiffness, are identified and the results obtained by using MFD and HM are compared to those using SVF. The accuracy and efficiency of using these techniques are demonstrated by the experimental simulation with various noise levels and different initial values. The results indicate that the choice of initial values is of no significant effect on SVF method and the accuracy of SVF depends on the level of noise. However, for MFD method, it is almost independent of noise effect but significantly affected by the choice of initial values. The Hybrid Method (HM) is proposed to overcome these handicaps and found of better accuracy and efficiency than SVF and MFD. Then, it is highly recommended for the parameters identification of system with noise effect.

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Penalized partial least squares for pleiotropy

BMC Bioinformatics ◽

10.1186/s12859-021-03968-1 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Camilo Broc ◽

Therese Truong ◽

Benoit Liquet

Keyword(s):

Least Squares ◽

Partial Least Squares ◽

Association Studies ◽

A Priori ◽

Simulated Data ◽

Real Data ◽

Genome Wide Association Studies ◽

Genetic Associations ◽

Multiple Traits ◽

Application Fields

Abstract Background The increasing number of genome-wide association studies (GWAS) has revealed several loci that are associated to multiple distinct phenotypes, suggesting the existence of pleiotropic effects. Highlighting these cross-phenotype genetic associations could help to identify and understand common biological mechanisms underlying some diseases. Common approaches test the association between genetic variants and multiple traits at the SNP level. In this paper, we propose a novel gene- and a pathway-level approach in the case where several independent GWAS on independent traits are available. The method is based on a generalization of the sparse group Partial Least Squares (sgPLS) to take into account groups of variables, and a Lasso penalization that links all independent data sets. This method, called joint-sgPLS, is able to convincingly detect signal at the variable level and at the group level. Results Our method has the advantage to propose a global readable model while coping with the architecture of data. It can outperform traditional methods and provides a wider insight in terms of a priori information. We compared the performance of the proposed method to other benchmark methods on simulated data and gave an example of application on real data with the aim to highlight common susceptibility variants to breast and thyroid cancers. Conclusion The joint-sgPLS shows interesting properties for detecting a signal. As an extension of the PLS, the method is suited for data with a large number of variables. The choice of Lasso penalization copes with architectures of groups of variables and observations sets. Furthermore, although the method has been applied to a genetic study, its formulation is adapted to any data with high number of variables and an exposed a priori architecture in other application fields.

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Changes in Power Plant NOx Emissions over Northwest Greece Using a Data Assimilation Technique

Atmosphere ◽

10.3390/atmos12070900 ◽

2021 ◽

Vol 12 (7) ◽

pp. 900

Author(s):

Ioanna Skoulidou ◽

Maria-Elissavet Koukouli ◽

Arjo Segers ◽

Astrid Manders ◽

Dimitris Balis ◽

...

Keyword(s):

Power Plant ◽

Data Assimilation ◽

Energy Production ◽

Power Plants ◽

Transport Model ◽

A Priori ◽

Filter Method ◽

Nox Emissions ◽

A Posteriori ◽

Data Assimilation Technique

In this work, we investigate the ability of a data assimilation technique and space-borne observations to quantify and monitor changes in nitrogen oxides (NOx) emissions over Northwestern Greece for the summers of 2018 and 2019. In this region, four lignite-burning power plants are located. The data assimilation technique, based on the Ensemble Kalman Filter method, is employed to combine space-borne atmospheric observations from the high spatial resolution Sentinel-5 Precursor (S5P) Tropospheric Monitoring Instrument (TROPOMI) and simulations using the LOTOS-EUROS Chemical Transport model. The Copernicus Atmosphere Monitoring Service-Regional European emissions (CAMS-REG, version 4.2) inventory based on the year 2015 is used as the a priori emissions in the simulations. Surface measurements of nitrogen dioxide (NO2) from air quality stations operating in the region are compared with the model surface NO2 output using either the a priori (base run) or the a posteriori (assimilated run) NOx emissions. Relative to the a priori emissions, the assimilation suggests a strong decrease in concentrations for the station located near the largest power plant, by 80% in 2019 and by 67% in 2018. Concerning the estimated annual a posteriori NOx emissions, it was found that, for the pixels hosting the two largest power plants, the assimilated run results in emissions decreased by ~40–50% for 2018 compared to 2015, whereas a larger decrease, of ~70% for both power plants, was found for 2019, after assimilating the space-born observations. For the same power plants, the European Pollutant Release and Transfer Register (E-PRTR) reports decreased emissions in 2018 and 2019 compared to 2015 (−35% and −38% in 2018, −62% and −72% in 2019), in good agreement with the estimated emissions. We further compare the a posteriori emissions to the reported energy production of the power plants during the summer of 2018 and 2019. Mean decreases of about −35% and−63% in NOx emissions are estimated for the two larger power plants in summer of 2018 and 2019, respectively, which are supported by similar decreases in the reported energy production of the power plants (~−30% and −70%, respectively).

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Iterative Variable Selection for High-Dimensional Data: Prediction of Pathological Response in Triple-Negative Breast Cancer

Mathematics ◽

10.3390/math9030222 ◽

2021 ◽

Vol 9 (3) ◽

pp. 222

Author(s):

Juan C. Laria ◽

M. Carmen Aguilera-Morillo ◽

Enrique Álvarez ◽

Rosa E. Lillo ◽

Sara López-Taruella ◽

...

Keyword(s):

Breast Cancer ◽

Variable Selection ◽

Triple Negative Breast Cancer ◽

Triple Negative ◽

A Priori ◽

Simulated Data ◽

Point Of View ◽

High Dimensional ◽

Whole Genome ◽

Genome Context

Over the last decade, regularized regression methods have offered alternatives for performing multi-marker analysis and feature selection in a whole genome context. The process of defining a list of genes that will characterize an expression profile remains unclear. It currently relies upon advanced statistics and can use an agnostic point of view or include some a priori knowledge, but overfitting remains a problem. This paper introduces a methodology to deal with the variable selection and model estimation problems in the high-dimensional set-up, which can be particularly useful in the whole genome context. Results are validated using simulated data and a real dataset from a triple-negative breast cancer study.

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A Traveler’s Guide to the Multiverse: Promises, Pitfalls, and a Framework for the Evaluation of Analytic Decisions

Advances in Methods and Practices in Psychological Science ◽

10.1177/2515245920954925 ◽

2021 ◽

Vol 4 (1) ◽

pp. 251524592095492

Author(s):

Marco Del Giudice ◽

Steven W. Gangestad

Keyword(s):

Degrees Of Freedom ◽

A Priori ◽

Simulated Data ◽

Style Analysis ◽

Data Set ◽

Scant Attention ◽

Equivalence Type ◽

The Impact ◽

Biased Estimates

Decisions made by researchers while analyzing data (e.g., how to measure variables, how to handle outliers) are sometimes arbitrary, without an objective justification for choosing one alternative over another. Multiverse-style methods (e.g., specification curve, vibration of effects) estimate an effect across an entire set of possible specifications to expose the impact of hidden degrees of freedom and/or obtain robust, less biased estimates of the effect of interest. However, if specifications are not truly arbitrary, multiverse-style analyses can produce misleading results, potentially hiding meaningful effects within a mass of poorly justified alternatives. So far, a key question has received scant attention: How does one decide whether alternatives are arbitrary? We offer a framework and conceptual tools for doing so. We discuss three kinds of a priori nonequivalence among alternatives—measurement nonequivalence, effect nonequivalence, and power/precision nonequivalence. The criteria we review lead to three decision scenarios: Type E decisions (principled equivalence), Type N decisions (principled nonequivalence), and Type U decisions (uncertainty). In uncertain scenarios, multiverse-style analysis should be conducted in a deliberately exploratory fashion. The framework is discussed with reference to published examples and illustrated with the help of a simulated data set. Our framework will help researchers reap the benefits of multiverse-style methods while avoiding their pitfalls.

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Nonlinear Analysis of Rotor-Bearing Systems Using Component Mode Synthesis

Journal of Engineering for Power ◽

10.1115/1.3227460 ◽

1983 ◽

Vol 105 (3) ◽

pp. 606-614 ◽

Cited By ~ 23

Author(s):

H. D. Nelson ◽

W. L. Meacham ◽

D. P. Fleming ◽

A. F. Kascak

Keyword(s):

Forced Response ◽

Component Mode Synthesis ◽

Squeeze Film ◽

System Response ◽

Reduced Order ◽

Squeeze Film Dampers ◽

Rotor Bearing ◽

System Equations ◽

Transient System ◽

Blade Loss

The method of component mode synthesis is developed to determine the forced response of nonlinear, multishaft, rotor-bearing systems. The formulation allows for simulation of system response due to blade loss, distributed unbalance, base shock, maneuver loads, and specified fixed frame forces. The motion of each rotating component of the system is described by superposing constraint modes associated with boundary coordinates and constrained precessional modes associated with internal coordinates. The precessional modes are truncated for each component and the reduced component equations are assembled with the nonlinear supports and interconnections to form a set of nonlinear system equations of reduced order. These equations are then numerically integrated to obtain the system response. A computer program, which is presently restricted to single shaft systems has been written and results are presented for transient system response associated with blade loss dynamics, with squeeze film dampers, and with interference rubs.

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