Modeling Flutter Using Deflection-Dependent Strain-Rate Damping

2010 ◽  
Author(s):  
Soroush Norouzi ◽  
Siamak Arzanpour
Keyword(s):  
Strain Rate ◽  
Linear Models ◽  
Nonlinear Models ◽  
The Other ◽  
Large Deflections ◽  
Critical Importance ◽  
Nonlinear Simulation ◽  
The Past ◽  
Dependent Strain ◽  
Linear And Nonlinear

Flutter is a flow-induced unstable motion in structures that has drawn researchers’ attention in the past decades due to its presence in numerous applications including aviation. Linear and nonlinear models of flutter have been developed. Linear models are simple and accurate for predicting the critical velocity at which flutter occurs. However, they are not capable of describing the post-flutter behavior of structures. Nonlinear models, on the other hand, can properly demonstrate the unstable motion accompanied with the occurrence of flutter but they are highly complicated. In fact, numerical solution of these equations requires extensive computations. As a result, having a model that is both simple and valid for post-flutter simulations is of critical importance. Linear models lose their accuracy when large deflections take place in the structure. This is when the unconsidered tensions that oppose large deflections come into play and render the behavior of the structure nonlinear. Usually, a type of damping relative to strain-rate is assumed for modeling structures under flutter. This paper introduces a deflection-dependant strain-rate damping coefficient to the linear flutter model, so as the deflections grow the restraining forces increase to limit the motion. The new sets of equations are derived and simulations are conducted to ensure the capability of the model to capture the post-flutter behavior. Results are then compared with the results of nonlinear simulation to demonstrate the new model’s compliance with those of nonlinearly-modeled systems.

scholarly journals How well do linear and nonlinear time series models’ forecasts compete with international economic organizations?

2020 ◽  
Vol 12 (3) ◽  
pp. 23-70
Author(s):  
Tayyab Raza Fraz ◽  
Javed Iqbal ◽  
Mudassir Uddin
Keyword(s):  
International Economic ◽  
Time Series ◽  
Linear Models ◽  
Nonlinear Models ◽  
Nonlinear Time Series ◽  
Time Series Models ◽  
Macroeconomic Variables ◽  
The Past ◽  
Economic Organizations ◽  
Linear And Nonlinear

This paper evaluates the forecasting performance of linear and non-linear time series models of some macroeconomic variables viz a viz the forecasts outlook of these variables generated by professionals in international economic organizations i.e. the International Monetary Fund (IMF) and the Organization of Economic Cooperation and Development (OECD). Many time series and econometrics models are used to forecast financial and macroeconomic variables. The accuracy of such forecasts depends crucially on careful handling of nonlinearity present in the time series. The debate of forecasting ability of linear vs nonlinear models is far from settled. These models use the past patterns of the economic time series to infer the parameters of the underlying stochastic process and use them to make forecasts. In doing so these models use only the information contained in the past data. However the economists working in professional international economic organizations not only look at the past trends but use the condition of local and global economy prevailing at the time and expected future path of economies as well as their professional expertise and judgment to arrive at forecasts of macroeconomic variables. However the specific underlying models and methodology used by the economists generating these forecast is usually not communicated to the public. In comparison to the forecasts of these organizations the time series models are well developed and accessible to researchers working anywhere around the globe. Thus it is an interesting task to compare the foresting ability of linear and nonlinear time series models. This paper aims at comparing the forecasts from these models to assess how well they compete with forecasts generated from the professional economists employed by international economic organizations. The nonlinear models employed in this study are quite well known namely the Self Exciting Threshold Autoregressive (SETAR) model and the Markov Switching Autoregressive (MSAR) model. The linear models employed are the AR and ARMA models. The paper have used annual data of three macroeconomic time series variables GDP growth, consumer price inflation and exchange rate of G7 countries i.e. Canada, France, Germany, Italy, Japan, United Kingdom (UK) and United States of America (USA) as well as an emerging south Asian economy namely Pakistan. Three forecast accuracy criteria i.e. Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) are employed and the statistical significance of difference in forecasts is assessed using the Diebold-Mariono test. The results show that the forecasting ability of nonlinear Regime Switching models SETAR and MSAR is superior to the linear models. Further, although the point forecasts of linear and nonlinear models are not superior to that of economic organizations but in more than 60 percent of the cases considered the forecasting accuracy of two sets of forecast is not statistically significantly different.

scholarly journals Relationship between Cycling Infrastructure and Transportation Cycling in a Small Urban Area

2021 ◽  
Vol 1 (1) ◽  
pp. 99-112
Author(s):  
Richard Larouche ◽  
Nimesh Patel ◽  
Jennifer L. Copeland
Keyword(s):  
Generalized Linear Models ◽  
Qualitative Data ◽  
Linear Models ◽  
The Other ◽  
Small City ◽  
The Road ◽  
The Past ◽  
Low Prevalence ◽  
The Relationship

The role of infrastructure in encouraging transportation cycling in smaller cities with a low prevalence of cycling remains unclear. To investigate the relationship between the presence of infrastructure and transportation cycling in a small city (Lethbridge, AB, Canada), we interviewed 246 adults along a recently-constructed bicycle boulevard and two comparison streets with no recent changes in cycling infrastructure. One comparison street had a separate multi-use path and the other had no cycling infrastructure. Questions addressed time spent cycling in the past week and 2 years prior and potential socio-demographic and psychosocial correlates of cycling, including safety concerns. Finally, we asked participants what could be done to make cycling safer and more attractive. We examined predictors of cycling using gender-stratified generalized linear models. Women interviewed along the street with a separate path reported cycling more than women on the other streets. A more favorable attitude towards cycling and greater habit strength were associated with more cycling in both men and women. Qualitative data revealed generally positive views about the bicycle boulevard, a need for education about sharing the road and for better cycling infrastructure in general. Our results suggest that, even in smaller cities, cycling infrastructure may encourage cycling, especially among women.

scholarly journals Mathematical Modeling for Prediction of Heating and Air-Conditioning Energies of Multistory Buildings in Duhok City

2018 ◽  
Vol 7 (4) ◽  
pp. 153
Author(s):  
Neven E. Zaya ◽  
Lokman H. Hassan ◽  
Halis Bilgil
Keyword(s):  
Air Conditioning ◽  
Perfect Matching ◽  
Nonlinear Models ◽  
The Other ◽  
Multistory Buildings ◽  
The Third ◽  
The Common ◽  
Linear And Nonlinear ◽  
Predicted Values ◽  
Building Walls

Present endeavor is devoted to estimate the air-conditioning and heating energies or loads of modern buildings in Duhok City, Iraq using new mathematical models. Many parameters have been considered in current modeling, namely, area of building, number of storeys and types of the common materials of the building walls. Regression analysis is performed to formulate new mathematical linear and nonlinear models for the loads. In addition, Fuzzy logic is utilized in the third model employing Sugeno's regulation. The outcomes reveal that the reasonable matching is achieved between the proposed models and mechanical engineering analytical solutions of heating and air-conditioning standards. Consequently, high correlation coefficient as more than 85% is determined between the predicted values of the models and analytical results. The linear model shows perfect matching with the analytical outputs more than the other proposed mathematical formulations.

scholarly journals Information criteria for nonlinear time series models

2016 ◽  
Vol 20 (3) ◽  
Author(s):  
Saskia Rinke ◽  
Philipp Sibbertsen
Keyword(s):  
Error Term ◽  
Linear Models ◽  
Nonlinear Models ◽  
General Information ◽  
Information Criteria ◽  
Order Selection ◽  
Simulation Studies ◽  
Variance Estimator ◽  
Linear And Nonlinear ◽  
The Impact

AbstractIn this paper the performance of different information criteria for simultaneous model class and lag order selection is evaluated using simulation studies. We focus on the ability of the criteria to distinguish linear and nonlinear models. In the simulation studies, we consider three different versions of the commonly known criteria AIC, SIC and AICc. In addition, we also assess the performance of WIC and evaluate the impact of the error term variance estimator. Our results confirm the findings of different authors that AIC and AICc favor nonlinear over linear models, whereas weighted versions of WIC and all versions of SIC are able to successfully distinguish linear and nonlinear models. However, the discrimination between different nonlinear model classes is more difficult. Nevertheless, the lag order selection is reliable. In general, information criteria involving the unbiased error term variance estimator overfit less and should be preferred to using the usual ML estimator of the error term variance.

scholarly journals Forecasting Brazilian output and its turning points in the presence of breaks: a comparison of linear and nonlinear models

2006 ◽  
Vol 36 (1) ◽  
pp. 5-46 ◽  
Author(s):  
Brisne J. V. Céspedes ◽  
Marcelle Chauvet ◽  
Elcyon C. R. Lima
Keyword(s):  
Business Cycle ◽  
Structural Breaks ◽  
Linear Models ◽  
Nonlinear Models ◽  
Markov Switching Models ◽  
Real Gdp ◽  
Switching Models ◽  
Forecasting Performance ◽  
Out Of Sample ◽  
Linear And Nonlinear

This paper compares the forecasting performance of linear and nonlinear models under the presence of structural breaks for the Brazilian real GDP growth. The Markov switching models proposed by Hamilton (1989) and its generalized version by Lam (1990) are applied to quarterly GDP from 1975:1 to 2000:2 allowing for breaks at the Collor Plans. The probabilities of recessions are used to analyze the Brazilian business cycle. The in-sample and out-of-sample forecasting ability of growth rates of GDP of each model is compared with linear specifications and with a non-parametric rule. We find that the nonlinear models display a better forecasting performance than linear models. The specifications with the presence of structural breaks are important in obtaining a representation of the Brazilian business cycle and their inclusion improves considerably the models forecasting performance within and out-of-sample.

scholarly journals A Survey of Some Recent Results on Nonlinear Fault Tolerant Control

2010 ◽  
Vol 2010 ◽  
pp. 1-25 ◽  
Author(s):  
Mouhacine Benosman
Keyword(s):  
Control Theory ◽  
Linear Models ◽  
Fault Tolerant ◽  
Nonlinear Models ◽  
Fault Tolerant Control ◽  
Operating Life ◽  
Linear And Nonlinear ◽  
The One

Fault tolerant control (FTC) is the branch of control theory, dealing with the control of systems that become faulty during their operating life. Following the systems classification, as linear and nonlinear models, FTC can be classified in two different groups, linear FTC (LFTC) dealing with linear models, and the one of interest to us in this paper, nonlinear FTC (NFTC), which deals with nonlinear models. We present in this paper a survey of some of the results obtained in these last years on NFTC.

scholarly journals Nonlinearities In Stock Return Prediction: Evidence From South Africa

2012 ◽  
Vol 28 (6) ◽  
pp. 1253 ◽  
Author(s):  
Kathleen Hodnett ◽  
Heng-Hsing Hsieh ◽  
Paul Van Rensburg
Keyword(s):  
Cross Section ◽  
Linear Models ◽  
Nonlinear Models ◽  
Learning Rule ◽  
Equity Returns ◽  
Neural Network Modeling ◽  
Font Size ◽  
Stock Selection ◽  
Linear And Nonlinear ◽  
The Cross

<span style="font-family: Times New Roman; font-size: small;"> </span><p style="margin: 0in 35.7pt 0pt 0.5in; text-align: justify; mso-layout-grid-align: none; mso-outline-level: 1;" class="MsoNormal"><span style="font-family: Times New Roman;"><span style="color: black; font-size: 10pt; mso-themecolor: text1; mso-fareast-language: ZH-HK;">This research investigates the relationship between firm-specific style attributes and the cross-section of equity returns on the JSE Securities Exchange (JSE) over the period from 1 January 1997 to 31 December 2007. Both linear and nonlinear stock selection models are constructed based on the cross-section of equity returns with firm-specific attributes as model inputs.</span><span style="color: black; mso-themecolor: text1; mso-fareast-language: ZH-HK;"><span style="font-size: small;"> </span></span><span style="color: black; font-size: 10pt; mso-themecolor: text1; mso-fareast-language: ZH-HK;">Both linear and nonlinear models identify book-value-to-price and cash flow-to-price as significant styles attributes that distinguish near-term future share returns on the JSE.</span><span style="color: black; mso-themecolor: text1; mso-fareast-language: ZH-HK;"><span style="font-size: small;"> </span></span><span style="color: black; font-size: 10pt; mso-themecolor: text1; mso-fareast-language: ZH-HK;">The risk-adjusted performance of the nonlinear models is found to be comparable with that of linear models.</span><span style="color: black; mso-themecolor: text1; mso-fareast-language: ZH-HK;"><span style="font-size: small;"> </span></span><span style="color: black; font-size: 10pt; mso-themecolor: text1; mso-fareast-language: ZH-HK;">In terms of artificial neural network modeling, the extended Kalman filter learning rule is found to outperform the traditional backpropagation approach. This finding is consistent with our prior findings on global stock selection.</span></span></p><span style="font-family: Times New Roman; font-size: small;"> </span>

A Two-Step Methodology for the Generation of Accurate Finite Element Models of Nonlinear Mechanical Systems

2004 ◽  
Author(s):  
Gae¨tan Kerschen ◽  
Jean-Claude Golinval
Keyword(s):  
Model Updating ◽  
Nonlinear Models ◽  
The Other ◽  
Finite Element Models ◽  
Numerical Application ◽  
Nonlinear Parameters ◽  
Nonlinear Mechanical ◽  
Computational Structural Mechanics ◽  
Linear And Nonlinear ◽  
Nonlinear Mechanical Systems

Model updating and validation is currently a central issue in the fields of computational structural mechanics and dynamics. The vast majority of applications however concerns linear structures. On the other hand, updating nonlinear models is something the structural dynamicist prefers to avoid mainly because tools such as modal analysis are no longer available. The objective of the present study is to propose a two-step methodology for dealing with nonlinear systems. Its most appealing feature is that it decouples the estimation of the linear and nonlinear parameters. A numerical application consisting of an aeroplane-like structure is used to assess the efficiency of the procedure.

scholarly journals Linear and nonlinear QSAR models of acute intravenous toxicity to mice for organic chemicals

2012 ◽  
Vol 58 (4) ◽  
pp. 357-371 ◽  
Author(s):  
O.A. Raevsky ◽  
E.A. Liplavskaya ◽  
A.V. Yarkov ◽  
O.E. Raevskaya ◽  
A.P. Worth
Keyword(s):  
Functional Group ◽  
Linear Models ◽  
Nonlinear Models ◽  
Statistical Characteristics ◽  
Organic Chemicals ◽  
Statistical Parameters ◽  
Qsar Analysis ◽  
Qsar Models ◽  
Linear And Nonlinear ◽  
Small Clusters

QSAR analysis of acute intravenous toxicity to mice for 68 monofunctional chemicals is presented. There compounds represents seven classes of organic chemicals: hydrocarbons (6 chemicals), alcohols (13), amides (22), amines (12), ethers (5), ketones (7), nitriles (3). Preliminary consideration of data for these chemicals showed that it is necessary to consider not only linear toxicity - descriptors relationships, but also nonlinear models. The linear and nonlinear QSAR models were considered for each from indicated classes of organic chemicals. Analogical models were constructed for whole subset of monofunctional chemicals. The statistical parameters and robustness of nonlinear models are essential better then statistics of linear models. Replacing a lipophilicity descriptor with molecular polarizability and H-bond ability in nonlinear models permits also to improve statistical characteristics. Clearly, if relationships between the intravenous toxicity of compounds bearing only a single functional group and lipophilicity are nonlinear, then similar relationships must be considered with compounds containing more than one functional group. To check up this idea whole set of small clusters containing structure relative compounds with few functional groups was examined from position of linear and nonlinear relationships between toxicity and lipophilicity. It was estimated in most causes advantages of nonlinear models.

Immunoferritin localization of intracellular antigens in positively stained frozen sections

1978 ◽  
Vol 36 (2) ◽  
pp. 168-169
Author(s):  
K. T. Tokuyasu
Keyword(s):  
Surface Tension ◽  
Water Surface ◽  
Thin Layers ◽  
The Other ◽  
Positive Staining ◽  
Frozen Sections ◽  
The Past ◽  
Ultrathin Frozen Sections ◽  
Definition Of

During the past investigations of immunoferritin localization of intracellular antigens in ultrathin frozen sections, we found that the degree of negative staining required to delineate u1trastructural details was often too dense for the recognition of ferritin particles. The quality of positive staining of ultrathin frozen sections, on the other hand, has generally been far inferior to that attainable in conventional plastic embedded sections, particularly in the definition of membranes. As we discussed before, a main cause of this difficulty seemed to be the vulnerability of frozen sections to the damaging effects of air-water surface tension at the time of drying of the sections.Indeed, we found that the quality of positive staining is greatly improved when positively stained frozen sections are protected against the effects of surface tension by embedding them in thin layers of mechanically stable materials at the time of drying (unpublished).

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