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Article
Publication date: 9 November 2012

Redha Benachour, Saïda Latreche, Mohamed El Hadi Latreche and Christian Gontrand

The present work aims to explain how the nonlinear average model can be used in power electronic integration design as a behavioral model.

Abstract

Purpose

The present work aims to explain how the nonlinear average model can be used in power electronic integration design as a behavioral model.

Design/methodology/approach

The nonlinear average model is used in power electronic integration design as a behavioral model, where it is applied to a voltage source inverter based on IGBTs. This model was chosen because it takes into account the nonlinearity of the power semiconductor components and the wiring circuit effects, which can be formalized by the virtual delay concept. In addition, the nonlinear average model cannot distinguish between slow and quick variables and this is an important feature of the model convergence.

Findings

The paper studies extensively the construction of the nonlinear average model algorithm theoretically. Detailed explanations of the application of this model to voltage source inverter design are provided. The study demonstrates how this model illustrates the effect of the nonlinearity of the power semiconductor components' characteristics on dynamic electrical quantities. It also predicts the effects due to wiring in the inverter circuit.

Research limitations/implications

More simulations and experimental analysis are still necessary to improve the model's accuracy, by using other static characteristic approaches, and to validate the applicability of the model to different converter topologies.

Practical implications

The paper formulates a simple nonlinear average model algorithm, discussing each step. This model was described by VHDL‐AMS. On the one hand, it will assist theoretical and practical research on different topologies of power electronic converters, particularly in power integration systems design such as the integrated power electronics modules (IPEM). On the other hand, it will give designers a more precise behavioral model with a simpler design process.

Originality/value

The nonlinear average model used in power electronic integration design as behavioral model is a novel approach. This model reduces computational costs significantly, takes physical effects into account and is easy to implement.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 31 no. 6
Type: Research Article
ISSN: 0332-1649

Keywords

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Article
Publication date: 27 January 2012

Jie Cui and Bo Zeng

The purpose of this paper is to study the properties of the NGM (1,1,k) prediction model with multiplication transformation and reduce its modeling complexity.

Abstract

Purpose

The purpose of this paper is to study the properties of the NGM (1,1,k) prediction model with multiplication transformation and reduce its modeling complexity.

Design/methodology/approach

The authors improved this model by putting forward a formula to solve its parameters, building an algorithm for optimizing the NGM (1,1,k) model in terms of the least modeling error and designing a key technology for the implementation of this algorithm. The optimized NGM (1,1,k) model is built accordingly. The parameter characteristics of the two models under multiple transformations and its effect of the simulation value and forecasting value are analyzed by studying the properties of multiple transformation of the two models.

Findings

The research finding shows that the modeling accuracies of the NGM (1,1,k) model and the optimized NGM (1,1,k) model are all in no relation to multiple transformations.

Practical implications

The above results imply that the data level can be reduced; the process of building the NGM (1,1,k) model and the optimized NGM (1,1,k) model can be simplified; but the simulative and predictive accuracy of the two models remain unchanged.

Originality/value

The paper succeeds in realising the properties of NGM (1,1,k) model and the optimized NGM (1,1,k) model by using the method of multiplication transformation, which is helpful for understanding the modeling mechanism and expanding the application range of the NGM (1,1,k) model.

Details

Grey Systems: Theory and Application, vol. 2 no. 1
Type: Research Article
ISSN: 2043-9377

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Article
Publication date: 8 April 2019

Andrea Moretta Tartaglione, Roberto Bruni and Maja Bozic

The purpose of this paper is to explore the dynamics of the relationships between sales and internal and external environmental drivers in a retail company using a systems…

Abstract

Purpose

The purpose of this paper is to explore the dynamics of the relationships between sales and internal and external environmental drivers in a retail company using a systems perspective in order to support retail management decisions with nonlinear methods.

Design/methodology/approach

The research and results are presented in two parts: the collection and explorative analysis of the data; and discussion of the managerial implications following a systems perspective. The exploratory analysis is conducted using a statistical comparison of linear and nonlinear models of sales data from a retail company. The data, which comprise two data sets, come from 45 retail stores located in different regions of the USA.

Findings

Specifically, nonlinear models provided a better explanation of variation in retail activity (R2=46 per cent) than linear models (R2=16 per cent). In such a situation, the nonlinear analysis captures the influence of internal and external environmental drivers on retail sales.

Research limitations/implications

With a limited variety of external and internal drivers, the exploratory analysis aims to describe a general situation in which retailers are managing activities in complex environments as opposed to reflect on a particular retail chain.

Practical implications

The systems perspective is used to interpret the managerial implications of the nonlinear analysis fits, particularly in cases where retail decision-makers are adapting, transforming and restructuring sources of competitive advantage in complex environments.

Originality/value

The paper provides an alternative perspective (the systemic one) of how retailers could interpret the relationships between internal and external variables in the dynamic environment of the retail chains with nonlinear models.

Details

International Journal of Retail & Distribution Management, vol. 47 no. 4
Type: Research Article
ISSN: 0959-0552

Keywords

Content available
Article
Publication date: 11 June 2018

Bahar Doryab and Mahdi Salehi

This study aims to use gray models to predict abnormal stock returns.

Abstract

Purpose

This study aims to use gray models to predict abnormal stock returns.

Design/methodology/approach

Data are collected from listed companies in the Tehran Stock Exchange during 2005-2015. The analyses portray three models, namely, the gray model, the nonlinear gray Bernoulli model and the Nash nonlinear gray Bernoulli model.

Findings

Results show that the Nash nonlinear gray Bernoulli model can predict abnormal stock returns that are defined by conditions other than gray models which predict increases, and then after checking regression models, the Bernoulli regression model is defined, which gives higher accuracy and fewer errors than the other two models.

Originality/value

The stock market is one of the most important markets, which is influenced by several factors. Thus, accurate and reliable techniques are necessary to help investors and consumers find detailed and exact ways to predict the stock market.

Details

Journal of Economics, Finance and Administrative Science, vol. 23 no. 44
Type: Research Article
ISSN: 2077-1886

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Article
Publication date: 12 August 2014

Juying Zeng

The purpose of this paper is to examine the determinants of average health expenditures for inpatients in China with national data for period 2002-2010 and regional data…

Abstract

Purpose

The purpose of this paper is to examine the determinants of average health expenditures for inpatients in China with national data for period 2002-2010 and regional data during 2005-2010.

Design/methodology/approach

The semi-parametric framework is established to identify the determinants of health expenditures with local-constant least squares (LCLS) and local-linear least squares (LLLS) techniques. The LCLS technique aims to identify correlative determinants among all considered variables, and LLLS technique aims to further distinguish linear decisive and nonlinear control variables among all correlative determinants.

Findings

First, root mean square error tends to decrease with irrelative variables smoothed out in regression model, validating the modelling reasonability of the semi-parametric approach. Second, the determinants of average health expenditures for inpatients exhibit considerable variation among regions despite the fact that governmental health expenditure, GDP per-capita, and urbanization do impact average health expenditures for inpatients to a certain extent. Third, both linear decisive and nonlinear control variables vary greatly with national, provincial, and regional data.

Practical implications

First, the illiteracy rate should be further reduced nationally. Second, urbanization development and the average treatment number of inpatients for each physician per day should be strictly controlled in region A and C, respectively, in order to control average health expenditure for inpatients.

Originality/value

First, the semi-parametric framework with LCLS and LLLS techniques allows for data structure-oriented model in regions rather than a uniform and definite model for underlying structure. Second, the research undertakes for the first time a comprehensive data analysis of the determinants of average health expenditures for inpatients with national and regional data in China.

Details

Management Decision, vol. 52 no. 7
Type: Research Article
ISSN: 0025-1747

Keywords

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Article
Publication date: 4 March 2019

Mohammad Fazli and Mehrdad Raisee

This paper aims to predict turbulent flow and heat transfer through different channels with periodic dimple/protrusion walls. More specifically, the performance of various…

Abstract

Purpose

This paper aims to predict turbulent flow and heat transfer through different channels with periodic dimple/protrusion walls. More specifically, the performance of various low-Re k-ε turbulence models in prediction of local heat transfer coefficient is evaluated.

Design/methodology/approach

Three low-Re number k-ε turbulence models (the zonal k-ε, the linear k-ε and the nonlinear k-ε) are used. Computations are performed for three geometries, namely, a channel with a single dimpled wall, a channel with double dimpled walls and a channel with a single dimple/protrusion wall. The predictions are obtained using an in house finite volume code.

Findings

The numerical predictions indicate that the nonlinear k-ε model predicts a larger recirculation bubble inside the dimple with stronger impingement and upwash flow than the zonal and linear k-ε models. The heat transfer results show that the zonal k-ε model returns weak thermal predictions in all test cases in comparison to other turbulence models. Use of the linear k-ε model leads to improvement in heat transfer predictions inside the dimples and their back rim. However, the most accurate thermal predictions are obtained via the nonlinear k-ε model. As expected, the replacement of the algebraic length-scale correction term with the differential version improves the heat transfer predictions of both linear and nonlinear k-ε models.

Originality/value

The most reliable turbulence model of the current study (i.e. nonlinear k-ε model) may be used for design and optimization of various thermal systems using dimples for heat transfer enhancement (e.g. heat exchangers and internal cooling system of gas turbine blades).

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. 29 no. 3
Type: Research Article
ISSN: 0961-5539

Keywords

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Article
Publication date: 22 May 2020

Houzhe Zhang, Defeng Gu, Xiaojun Duan, Kai Shao and Chunbo Wei

The purpose of this paper is to focus on the performance of three typical nonlinear least-squares estimation algorithms in atmospheric density model calibration.

Abstract

Purpose

The purpose of this paper is to focus on the performance of three typical nonlinear least-squares estimation algorithms in atmospheric density model calibration.

Design/methodology/approach

The error of Jacchia-Roberts atmospheric density model is expressed as an objective function about temperature parameters. The estimation of parameter corrections is a typical nonlinear least-squares problem. Three algorithms for nonlinear least-squares problems, Gauss–Newton (G-N), damped Gauss–Newton (damped G-N) and Levenberg–Marquardt (L-M) algorithms, are adopted to estimate temperature parameter corrections of Jacchia-Roberts for model calibration.

Findings

The results show that G-N algorithm is not convergent at some sampling points. The main reason is the nonlinear relationship between Jacchia-Roberts and its temperature parameters. Damped G-N and L-M algorithms are both convergent at all sampling points. G-N, damped G-N and L-M algorithms reduce the root mean square error of Jacchia-Roberts from 20.4% to 9.3%, 9.4% and 9.4%, respectively. The average iterations of G-N, damped G-N and L-M algorithms are 3.0, 2.8 and 2.9, respectively.

Practical implications

This study is expected to provide a guidance for the selection of nonlinear least-squares estimation methods in atmospheric density model calibration.

Originality/value

The study analyses the performance of three typical nonlinear least-squares estimation methods in the calibration of atmospheric density model. The non-convergent phenomenon of G-N algorithm is discovered and explained. Damped G-N and L-M algorithms are more suitable for the nonlinear least-squares problems in model calibration than G-N algorithm and the first two algorithms have slightly fewer iterations.

Details

Aircraft Engineering and Aerospace Technology, vol. 92 no. 7
Type: Research Article
ISSN: 1748-8842

Keywords

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Article
Publication date: 27 September 2011

Mohammad Rezaiee‐Pajand, Cyrus Nasirai and Mehrzad Sharifian

The purpose of this paper is to present a new effective integration method for cyclic plasticity models.

Abstract

Purpose

The purpose of this paper is to present a new effective integration method for cyclic plasticity models.

Design/methodology/approach

By defining an integrating factor and an augmented stress vector, the system of differential equations of the constitutive model is converted into a nonlinear dynamical system, which could be solved by an exponential map algorithm.

Findings

The numerical tests show the robustness and high efficiency of the proposed integration scheme.

Research limitations/implications

The von‐Mises yield criterion in the regime of small deformation is assumed. In addition, the model obeys a general nonlinear kinematic hardening and an exponential isotropic hardening.

Practical implications

Integrating the constitutive equations in order to update the material state is one of the most important steps in a nonlinear finite element analysis. The accuracy of the integration method could directly influence the result of the elastoplastic analyses.

Originality/value

The paper deals with integrating the constitutive equations in a nonlinear finite element analysis. This subject could be interesting for the academy as well as industry. The proposed exponential‐based integration method is more efficient than the classical strategies.

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Article
Publication date: 30 September 2014

Denise Ferreira, Jesús Bairán, Antonio Marí and Rui Faria

A nonlinear finite element (FE) beam-column model for the analysis of reinforced concrete (RC) frames with due account of shear is presented in this paper. The model is an…

Abstract

Purpose

A nonlinear finite element (FE) beam-column model for the analysis of reinforced concrete (RC) frames with due account of shear is presented in this paper. The model is an expansion of the traditional flexural fibre beam formulations to cases where multiaxial behaviour exists, being an alternative to plane and solid FE models for the nonlinear analysis of entire frame structures. The paper aims to discuss these issues.

Design/methodology/approach

Shear is taken into account at different levels of the numerical model: at the material level RC is simulated through a smeared cracked approach with rotating cracks; at the fibre level, an iterative procedure guarantees equilibrium between concrete and transversal reinforcement, allowing to compute the biaxial stress-strain state of each fibre; at the section level, a uniform shear stress pattern is assumed in order to estimate the internal shear stress-strain distribution; and at the element level, the Timoshenko beam theory takes into account an average rotation due to shear.

Findings

The proposed model is validated through experimental tests available in the literature, as well as through an experimental campaign carried out by the authors. The results on the response of RC elements critical to shear include displacements, strains and crack patterns and show the capabilities of the model to efficiently deal with shear effects in beam elements.

Originality/value

A formulation for the nonlinear shear-bending interaction based on the fixed stress approach is implemented in a fibre beam model. Shear effects are accurately accounted during all the nonlinear path of the structure in a computationally efficient manner.

Details

Engineering Computations, vol. 31 no. 7
Type: Research Article
ISSN: 0264-4401

Keywords

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Abstract

Details

Nonlinear Time Series Analysis of Business Cycles
Type: Book
ISBN: 978-0-44451-838-5

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