Search results for: linear dynamic panel data model

Authors: H. Y. Jung, Ju H. Park, S. M. Lee

Abstract:

A sampled-data controller is presented for solid oxide fuel cell systems which is expressed by a sector bounded nonlinear model. The sector bounded nonlinear systems, which have a feedback connection with a linear dynamical system and nonlinearity satisfying certain sector type constraints. Also, the sampled-data control scheme is very useful since it is possible to handle digital controller and increasing research efforts have been devoted to sampled-data control systems with the development of modern high-speed computers. The proposed control law is obtained by solving a convex problem satisfying several linear matrix inequalities. Simulation results are given to show the effectiveness of the proposed design method.

Keywords: sampled-data control, fuel cell, linear matrix inequalities, nonlinear control

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Authors: R. Bhattu Babajee, Marie Sandrine Estelle Benoit

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The past decades have witnessed a considerable institutional shift towards Central Bank Independence across economies of the world. The motivation behind such a change is the acceptance that increased central bank autonomy has the power of alleviating inflation bias. Hence, studying whether Central Bank Independence acts as a significant factor behind the price stability in the African economies or whether this macroeconomic aim in these countries result from other economic, political or social factors is a pertinent issue. The main research objective of this paper is to assess the relationship between central bank autonomy and inflation in African economies where inflation has proved to be a serious problem. In this optic, we shall measure the degree of CBI in Africa by computing the turnover rates of central banks governors thereby studying whether decisions made by African central banks are affected by external forces. The purpose of this study is to investigate empirically the association between Central Bank Independence (CBI) and inflation for 10 African economies over a period of 17 years, from 1995 to 2012. The sample includes Botswana, Egypt, Ghana, Kenya, Madagascar, Mauritius, Mozambique, Nigeria, South Africa, and Uganda. In contrast to empirical research, we have not been using the usual static panel model for it is associated with potential mis specification arising from the absence of dynamics. To this issue a dynamic panel data model which integrates several control variables has been used. Firstly, the analysis includes dynamic terms to explain the tenacity of inflation. Given the confirmation of inflation inertia, that is very likely in African countries there exists the need for including lagged inflation in the empirical model. Secondly, due to known reverse causality between Central Bank Independence and inflation, the system generalized method of moments (GMM) is employed. With GMM estimators, the presence of unknown forms of heteroskedasticity is admissible as well as auto correlation in the error term. Thirdly, control variables have been used to enhance the efficiency of the model. The main finding of this paper is that central bank independence is negatively associated with inflation even after including control variables.

Keywords: central bank independence, inflation, macroeconomic variables, price stability

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Authors: Dae-Hee Son, Sang-Hee Kang, Soon-Ryul Nam

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In this paper, we develop a dynamic modeling of wind farms in the Jeju power system. The dynamic model of wind farms is developed to study their dynamic effects on the Jeju power system. PSS/E is used to develop the dynamic model of a wind farm composed of 1.5-MW doubly fed induction generators. The output of a wind farm is regulated based on pitch angle control, in which the two controllable parameters are speed and power references. The simulation results confirm that the pitch angle is successfully controlled, regardless of the variation in wind speed and output regulation.

Keywords: dynamic model, Jeju power system, online limitation, pitch angle control, wind farm

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Authors: Joanne Moyer

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El Paso, Texas is a southwest border city that has experienced continuous growth within the last 15-years. Understanding the urban growth trends and patterns using data from the National Land Cover Database (NLCD) and landscape metrics, provides a quantitative description of growth. Past urban growth provided a basis to predict 2031 future land-use for El Paso using the CA-Markov model. As a consequence of growth, an increase in demand of resources follows. Using panel data analysis, an understanding of the relation between landscape metrics and electricity consumption is further analyzed. The studies’ findings indicate that past growth focused within three districts within the City of El Paso. The landscape metrics suggest as the city has grown, fragmentation has decreased. Alternatively, the landscape metrics for the projected 2031 land-use indicates possible fragmentation within one of these districts. Panel data suggests electricity consumption and mean patch area landscape metric are positively correlated. The study provides local decision makers to make informed decisions for policies and urban planning to ensure a future sustainable community.

Keywords: landscape metrics, CA-Markov, El Paso, Texas, panel data

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Authors: Burcu Guvenek, Duygu Baysal Kurt

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The impact of foreign trade on economic growth has been discussed since the Classical Economists. Today, foreign trade has become more important for the country's economy with the increasing globalization. When it comes to foreign trade, policies which may vary from country to country and from time to time as protectionism or free trade are implemented. In general, the positive effect of foreign trade on economic growth is alleged. However, as studies supporting this general acceptance take place in the economics literature, there are also studies in the opposite direction. In this paper, the impact of foreign trade on economic growth will be investigated with the help of panel data analysis. For this research, 24 OECD countries’ GDP and foreign trade data, including the period of 1990 and 2010, will be used.

Keywords: foreign trade, economic growth, OECD countries, panel data analysis

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Authors: Hisham M. Soliman, Hassan Yousef

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This manuscript presents new results on design saturated power system stabilizers (PSS) to assign system poles within a desired region for achieving good dynamic performance. The regional pole placement is accomplished against model uncertainties caused by different load conditions. The design is based on a sufficient condition in the form of linear matrix inequalities (LMI) which forces the saturated nonlinear controller to lie within the linear zone. The controller effectiveness is demonstrated on a single machine infinite bus system.

Keywords: power system stabilizer, saturated control, robust control, regional pole placement, linear matrix inequality (LMI)

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Authors: Niloofar Ashktorab, Negar Ashktorab

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Oil exports fund nearly half of Iran’s government expenditures, since many years other countries have been imposed different sanctions against Iran. Sanctions that primarily target Iran’s key energy sector have harmed Iran’s economy. The strategic effects of sanctions might be reduction as Iran adjusts to them economically. In this study, we evaluate the impact of oil price and sanctions against Iran on food commodity prices by using panel data method. Here, we find that the food commodity prices, the oil price and real exchange rate are stationary. The results show positive effect of oil price changes, real exchange rate and sanctions on food commodity prices.

Keywords: oil price, food basket, sanctions, panel data, Iran

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Authors: V. E. Selaule, R. M. Schoeman H. C. Z. Pienaar

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Research has shown that solar energy is a renewable energy resource with the most potential when compared to other renewable energy resources in South Africa. There are many makes of Photovoltaic (PV) panels on the market and it is difficult to assess which to use. PV panel manufacturers use Standard Test Conditions (STC) to rate their PV panels. STC conditions are different from the actual operating environmental conditions were the PV panels are used. This paper describes a practical method to determine the most cost effective available PV panel. The method shows that PV panel manufacturer STC ratings cannot be used to select a cost effective PV panel.

Keywords: PV orientation, PV panel, PV STC, Solar energy

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Authors: Aref Ghafouri, Mohammad javad Mollakazemi, Farhad Asadi

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In this paper, model order reduction method is used for approximation in linear and nonlinearity aspects in some experimental data. This method can be used for obtaining offline reduced model for approximation of experimental data and can produce and follow the data and order of system and also it can match to experimental data in some frequency ratios. In this study, the method is compared in different experimental data and influence of choosing of order of the model reduction for obtaining the best and sufficient matching condition for following the data is investigated in format of imaginary and reality part of the frequency response curve and finally the effect and important parameter of number of order reduction in nonlinear experimental data is explained further.

Keywords: frequency response, order of model reduction, frequency matching condition, nonlinear experimental data

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Authors: K. Vigneshwaran, Manoj Pandey

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In this paper, breathing crack is considered for the non linear dynamic analysis. The stiffness of the cracked beam is found out by using influence coefficients. The influence coefficients are calculated by using Castigliano’s theorem and strain energy release rate (SERR). The equation of motion of the beam was derived by using Hamilton’s principle. The stiffness and natural frequencies for the cracked beam has been calculated using XFEM and Eigen approach. It is seen that due to presence of cracks, the stiffness and natural frequency changes. The mode shapes and the FRF for the uncracked and breathing cracked cantilever beam also obtained and compared.

Keywords: breathing crack, XFEM, mode shape, FRF, non linear analysis

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Authors: A. Zanj, F. He

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In the current paper, a domain independent conduction model compatible for multi-physical system dynamic investigations is suggested. By means of a port-based approach, a classical nonlinear conduction model containing physical states is first represented. A compatible discrete configuration of the thermal domain in line with the elastic domain is then generated through the enhancement of the configuration of the conventional thermal element. The presented simulation results of a sample structure indicate that the suggested conductive model can cover a wide range of dynamic behavior of the thermal domain.

Keywords: multi-physical domain, conduction model, port based modeling, dynamic interaction, physical modeling

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Authors: R. S. Arun Raj

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In today's climate of growing energy needs and increasing environmental issues, alternatives to the use of non-renewable and polluting fossil fuels have to be investigated. One such alternative is the solar energy. The SUN provides every hour as much energy as mankind consumes in one year. This paper clearly explains about the solar panel design and new models and methodologies that can be implemented for better utilization of solar energy. Minimisation of losses in solar panel as heat is my innovative idea revolves around. The pay back calculations by implementation of solar panels is also quoted.

Keywords: on-grid and off-grid systems, pyro-electric effect, pay-back calculations, solar panel

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Authors: Shih-Pin Chen, Shih-Syuan You

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Fuzzy regression models are useful for investigating the relationship between explanatory variables and responses in fuzzy environments. To overcome the deficiencies of previous models and increase the explanatory power of fuzzy data, the graded mean integration (GMI) representation is applied to determine representative crisp regression coefficients. A fuzzy regression model is constructed based on the modified dissemblance index (MDI), which can precisely measure the actual total error. Compared with previous studies based on the proposed MDI and distance criterion, the results from commonly used test examples show that the proposed fuzzy linear regression model has higher explanatory power and forecasting accuracy.

Keywords: dissemblance index, fuzzy linear regression, graded mean integration, mathematical programming

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Authors: Jeongim Kang, Moon Hee Kim, Seong Baeg Kim

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This paper proposes a novel e-learning model that is based on a dynamic formative evaluation. On evaluating the existing format of e-learning, conditions regarding repetitive learning to achieve mastery, causes issues for learners to lose tension and become neglectful of learning. The dynamic formative evaluation proposed is able to supplement limitation of the existing approaches. Since a repetitive learning method does not provide a perfect feedback, this paper puts an emphasis on the dynamic formative evaluation that is able to maximize learning achievement. Through the dynamic formative evaluation, the instructor is able to refer to the evaluation result when making estimation about the learner. To show the flow chart of learning, based on the dynamic formative evaluation, the model proves its effectiveness and validity.

Keywords: online learning, dynamic formative evaluation, mastery learning, repetitive learning method, learning achievement

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Authors: John Knight, Fuchun Li, Yan Xu

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Based on a new method of the nonparametric estimator of the drift function, we propose a consistent test for the parametric specification of the drift function in the short rate diffusion process using observations from a panel of yields. The test statistic is shown to follow an asymptotic normal distribution under the null hypothesis that the parametric drift function is correctly specified, and converges to infinity under the alternative. Taking the daily 7-day European rates as a proxy of the short rate, we use our test to examine whether the drift of the short rate diffusion process is linear or nonlinear, which is an unresolved important issue in the short rate modeling literature. The testing results indicate that none of the drift functions in this literature adequately captures the dynamics of the drift, but nonlinear specification performs better than the linear specification.

Keywords: diffusion process, nonparametric estimation, derivative security price, drift function and volatility function

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Authors: Meriem Mossaddek, El Mehdi Laadissi, El Mehdi Loualid, Chouaib Ennawaoui, Sohaib Bouzaid, Abdelowahed Hajjaji

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An electrochemical system is a subset of mechatronic systems that includes a wide variety of batteries and nickel-cadmium, lead-acid batteries, and lithium-ion. Those structures have several non-linear behaviors and uncertainties in their running range. This paper studies an effective technique for modeling Lithium-Ion (Li-Ion) batteries using a Nonlinear Auto-Regressive model with exogenous input (NARX). The Artificial Neural Network (ANN) is trained to employ the data collected from the battery testing process. The proposed model is implemented on a Li-Ion battery cell. Simulation of this model in MATLAB shows good accuracy of the proposed model.

Keywords: lithium-ion battery, neural network, energy storage, battery model, nonlinear models

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Authors: Fatma Abidi, Taoufik Harizi, Slah Msahli, Faouzi Sakli

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Nine different Tunisian handmade carpets were used for the investigation. The raw material of the carpet pile yarns was wool. The influence of the different structure parameters (linear density and pile height) on the carpet compression was investigated. Carpets were tested under dynamic loading in order to evaluate and observe the thickness loss and carpet behavior under dynamic loads. To determine the loss of pile height under dynamic loading, the pile height carpets were measured. The test method was treated according to the Tunisian standard NT 12.165 (corresponds to the standard ISO 2094). The pile height measurements are taken and recorded at intervals up to 1000 impacts (measures of this study were made after 50, 100, 200, 500, and 1000 impacts). The loss of pile height is calculated using the variation between the initial height and those measured after the number of reported impacts. The experimental results were statistically evaluated using Design Expert Analysis of Variance (ANOVA) software. As regards the deformation, results showed that both of the structure parameters of the pile yarn and the pile height have an influence. The carpet with the higher pile and the less linear density of pile yarn showed the worst performance. Results of a polynomial regression analysis are highlighted. There is a good correlation between the loss of pile height and the impacts number of dynamic loads. These equations are in good agreement with measured data. Because the prediction is reasonably accurate for all samples, these equations can also be taken into account when calculating the theoretical loss of pile height for the considered carpet samples. Statistical evaluations of the experimen¬tal data showed that the pile material and number of impacts have a significant effect on mean thickness and thickness loss variations.

Keywords: Tunisian handmade carpet, loss of pile height, dynamic loads, performance

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Authors: Ehsan Mehryaar, Reza Bushehri

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One of the principal parameters defining the clay soil dynamic response is the strain-shear modulus relation. Predicting the strain and, subsequently, shear modulus reduction of the soil is essential for performance analysis of structures exposed to earthquake and dynamic loadings. Many soil properties affect soil’s dynamic behavior. In order to capture those effects, in this study, a database containing 1193 data points consists of maximum shear modulus, strain, moisture content, initial void ratio, plastic limit, liquid limit, initial confining pressure resulting from dynamic laboratory testing of 21 clays is collected for predicting the shear modulus vs. strain curve of soil. A model based on an extreme gradient boosting technique is proposed. A tree-structured parzan estimator hyper-parameter tuning algorithm is utilized simultaneously to find the best hyper-parameters for the model. The performance of the model is compared to the existing empirical equations using the coefficient of correlation and root mean square error.

Keywords: XGBoost, hyper-parameter tuning, soil shear modulus, dynamic response

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Authors: G. C. Surya Bahadur, Ranjana Kothari

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The paper attempts to analyze linkages between corporate governance and firm performance in India. The study employs a panel data of 50 Nifty companies from 2008 to 2012. Using LSDV panel data model and 2SLS model the study reveals that that good corporate governance practices adopted by companies is positively related with financial performance. Board independence, number of board committees and executive compensation are found to have positive relationship while ownership by promoters and financial leverage have negative relationship with performance. There is existence of bi-directional relationship between corporate governance and financial performance. Companies with sound financial performance are more likely to conform to corporate governance norms and standards and implement sound corporate governance system. The findings indicate that companies can enhance business performance and sustainability by embracing sound corporate governance practices.

Keywords: board structure, corporate governance, executive compensation, ownership structure

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Authors: Moses Mwangi, Geert Verbeke, Geert Molenberghs

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Cross-over designs are commonly used in randomized clinical trials to estimate efficacy of a new treatment with respect to a reference treatment (placebo or standard). The main advantage of using cross-over design over conventional parallel design is its flexibility, where every subject become its own control, thereby reducing confounding effect. Jones & Kenward, discuss in detail more recent developments in the analysis of cross-over trials. We revisit the simple piecewise linear mixed-effects model, proposed by Mwangi et. al, (in press) for its first application in the analysis of cross-over trials. We compared performance of the proposed piecewise linear mixed-effects model with two commonly cited statistical models namely, (1) Grizzle model; and (2) Jones & Kenward model, used in estimation of the treatment effect, in the analysis of randomized cross-over trial. We estimate two performance measurements (mean square error (MSE) and coverage probability) for the three methods, using data simulated from the proposed piecewise linear mixed-effects model. Piecewise linear mixed-effects model yielded lowest MSE estimates compared to Grizzle and Jones & Kenward models for both small (Nobs=20) and large (Nobs=600) sample sizes. It’s coverage probability were highest compared to Grizzle and Jones & Kenward models for both small and large sample sizes. A piecewise linear mixed-effects model is a better estimator of treatment effect than its two competing estimators (Grizzle and Jones & Kenward models) in the analysis of cross-over trials. The data generating mechanism used in this paper captures two time periods for a simple 2-Treatments x 2-Periods cross-over design. Its application is extendible to more complex cross-over designs with multiple treatments and periods. In addition, it is important to note that, even for single response models, adding more random effects increases the complexity of the model and thus may be difficult or impossible to fit in some cases.

Keywords: Evaluation, Grizzle model, Jones & Kenward model, Performance measures, Simulation

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Authors: Jonardan Koner, Basabi Bhattacharya, Avinash Purandare

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The study is focused to find out the impact of infrastructural investment on economic development in Indian states. The study uses panel data analysis to measure the impact of infrastructural investment on Real Gross Domestic Product in Indian States. Panel data analysis incorporates Unit Root Test, Cointegration Teat, Pooled Ordinary Least Squares, Fixed Effect Approach, Random Effect Approach, Hausman Test. The study analyzes panel data (annual in frequency) ranging from 1991 to 2012 and concludes that infrastructural investment has a desirable impact on economic development in Indian. Finally, the study reveals that the infrastructural investment significantly explains the variation of economic indicator.

Keywords: infrastructural investment, real GDP, unit root test, cointegration teat, pooled ordinary least squares, fixed effect approach, random effect approach, Hausman test

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Authors: Raif Parlakkaya, Ahmet Diken, Erkan Kara

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This paper examines the relationship between corporate governance rating and stock prices of 26 Turkish firms listed in Turkish stock exchange (Borsa Istanbul) by using panel data analysis over five-year period. The paper also investigates the stock performance of firms with governance rating with regards to the market portfolio (i.e. BIST 100 Index) both prior and after governance scoring began. The empirical results show that there is no relation between corporate governance rating and stock prices when using panel data for annual variation in both rating score and stock prices. Further analysis indicates surprising results that while the selected firms outperform the market significantly prior to rating, the same performance does not continue afterwards.

Keywords: corporate governance, stock price, performance, panel data analysis

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Authors: Nur Aidya Hanum Aizam, Vikneswary Uvaraja

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The agenda of showing the scheduled time for performing certain tasks is known as timetabling. It widely used in many departments such as transportation, education, and production. Some difficulties arise to ensure all tasks happen in the time and place allocated. Therefore, many researchers invented various programming model to solve the scheduling problems from several fields. However, the studies in developing the general integer programming model for many timetabling problems are still questionable. Meanwhile, this thesis describe about creating a general model which solve different types of timetabling problems by considering the basic constraints. Initially, the common basic constraints from five different fields are selected and analyzed. A general basic integer programming model was created and then verified by using the medium set of data obtained randomly which is much similar to realistic data. The mathematical software, AIMMS with CPLEX as a solver has been used to solve the model. The model obtained is significant in solving many timetabling problems easily since it is modifiable to all types of scheduling problems which have same basic constraints.

Keywords: AIMMS mathematical software, integer linear programming, scheduling problems, timetabling

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Authors: E. Menga, S. Hernandez

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Finite Element Models (FEMs) are widely used in order to study and predict the dynamic properties of structures and usually, the prediction can be obtained with much more accuracy in the case of a single component than in the case of assemblies. Especially for structural dynamics studies, in the low and middle frequency range, most complex FEMs can be seen as assemblies made by linear components joined together at interfaces. From a modelling and computational point of view, these types of joints can be seen as localized sources of stiffness and damping and can be modelled as lumped spring/damper elements, most of time, characterized by nonlinear constitutive laws. On the other side, most of FE programs are able to run nonlinear analysis in time-domain. They treat the whole structure as nonlinear, even if there is one nonlinear degree of freedom (DOF) out of thousands of linear ones, making the analysis unnecessarily expensive from a computational point of view. In this work, a methodology in order to obtain the nonlinear frequency response of structures, whose nonlinearities can be considered as localized sources, is presented. The work extends the well-known Structural Dynamic Modification Method (SDMM) to a nonlinear set of modifications, and allows getting the Nonlinear Frequency Response Functions (NLFRFs), through an ‘updating’ process of the Linear Frequency Response Functions (LFRFs). A brief summary of the analytical concepts is given, starting from the linear formulation and understanding what the implications of the nonlinear one, are. The response of the system is formulated in both: time and frequency domain. First the Modal Database is extracted and the linear response is calculated. Secondly the nonlinear response is obtained thru the NL SDMM, by updating the underlying linear behavior of the system. The methodology, implemented in MATLAB, has been successfully applied to estimate the nonlinear frequency response of two systems. The first one is a two DOFs spring-mass-damper system, and the second example takes into account a full aircraft FE Model. In spite of the different levels of complexity, both examples show the reliability and effectiveness of the method. The results highlight a feasible and robust procedure, which allows a quick estimation of the effect of localized nonlinearities on the dynamic behavior. The method is particularly powerful when most of the FE Model can be considered as acting linearly and the nonlinear behavior is restricted to few degrees of freedom. The procedure is very attractive from a computational point of view because the FEM needs to be run just once, which allows faster nonlinear sensitivity analysis and easier implementation of optimization procedures for the calibration of nonlinear models.

Keywords: frequency response, nonlinear dynamics, structural dynamic modification, softening effect, rubber

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Authors: Bongsu Choi, Tae-Ho Song

Abstract:

Vacuum insulation panel (VIP) is a promising thermal insulator for buildings, refrigerator, LNG carrier and so on. In general, it has the thermal conductivity of 2~4 mW/m•K. However, this thermal conductivity is that measured at the center of VIP. The total effective thermal conductivity of VIP is larger than this value due to the edge conduction through the envelope. In this paper, the edge conduction of VIP is examined theoretically, numerically and experimentally. To confirm the existence of the edge conduction, numerical analysis is performed for simple two-dimensional VIP model and a theoretical model is proposed to calculate the edge conductivity. Also, the edge conductivity is measured using the vacuum guarded hot plate and the experiment is validated against numerical analysis. The results show that the edge conductivity is dependent on the width of panel and thickness of Al-foil. To reduce the edge conduction, it is recommended that the VIP should be made as big as possible or made of thin Al film envelope.

Keywords: envelope, edge conduction, thermal conductivity, vacuum insulation panel

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Authors: J. P. Panda, K. Sasmal, H. V. Warrior

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Eddy viscosity models in turbulence modeling can be mainly classified as linear and nonlinear models. Linear formulations are simple and require less computational resources but have the disadvantage that they cannot predict actual flow pattern in complex geophysical flows where streamline curvature and swirling motion are predominant. A constitutive equation of Reynolds stress anisotropy is adopted for the formulation of eddy viscosity including all the possible higher order terms quadratic in the mean velocity gradients, and a simplified model is developed for actual oceanic flows where only the vertical velocity gradients are important. The new model is incorporated into the one dimensional General Ocean Turbulence Model (GOTM). Two realistic oceanic test cases (OWS Papa and FLEX' 76) have been investigated. The new model predictions match well with the observational data and are better in comparison to the predictions of the two equation k-epsilon model. The proposed model can be easily incorporated in the three dimensional Princeton Ocean Model (POM) to simulate a wide range of oceanic processes. Practically, this model can be implemented in the coastal regions where trasverse shear induces higher vorticity, and for prediction of flow in estuaries and lakes, where depth is comparatively less. The model predictions of marine turbulence and other related data (e.g. Sea surface temperature, Surface heat flux and vertical temperature profile) can be utilized in short term ocean and climate forecasting and warning systems.

Keywords: Eddy viscosity, turbulence modeling, GOTM, CFD

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Authors: Krishang Surapaneni

Abstract:

The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%

Keywords: finance, linear regression model, machine learning model, neural network, stock price

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Authors: H. Meddah, M. Berediaf-Bourahla, B. El-Djouzi, N. Bourahla

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Shear walls made of cold formed steel are used as lateral force resisting components in residential and low-rise commercial and industrial constructions. The seismic design analysis of such structures is often complex due to the slenderness of members and their instability prevalence. In this context, a simplified modeling technique across the panel is proposed by using the finite element method. The approach is based on idealizing the whole panel by a nonlinear shear link element which reflects its shear behavior connected to rigid body elements which transmit the forces to the end elements (studs) that resist the tension and the compression. The numerical model of the shear wall panel was subjected to cyclic loads in order to evaluate the seismic performance of the structure in terms of lateral displacement and energy dissipation capacity. In order to validate this model, the numerical results were compared with those from literature tests. This modeling technique is particularly useful for the design of cold formed steel structures where the shear forces in each panel and the axial forces in the studs can be obtained using spectrum analysis.

Keywords: cold-formed steel, cyclic loading, modeling technique, nonlinear analysis, shear wall panel

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Authors: Sajana Suwal, Ganesh R. Nhemafuki

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Evaluation of ground response under earthquake shaking is crucial in geotechnical earthquake engineering. Damage due to seismic excitation is mainly correlated to local geological and geotechnical conditions. It is evident from the past earthquakes (e.g. 1906 San Francisco, USA, 1923 Kanto, Japan) that the local geology has strong influence on amplitude and duration of ground motions. Since then significant studies has been conducted on ground motion amplification revealing the importance of influence of local geology on ground. Observations from the damaging earthquakes (e.g. Nigata and San Francisco, 1964; Irpinia, 1980; Mexico, 1985; Kobe, 1995; L’Aquila, 2009) divulged that non-uniform damage pattern, particularly in soft fluvio-lacustrine deposit is due to the local amplification of seismic ground motion. Non-uniform damage patterns are also observed in Kathmandu Valley during 1934 Bihar Nepal earthquake and recent 2015 Gorkha earthquake seemingly due to the modification of earthquake ground motion parameters. In this study, site effects resulting from amplification of soft soil in Kathmandu are presented. A large amount of subsoil data was collected and used for defining the appropriate subsoil model for the Kathamandu valley. A comparative study of one-dimensional total-stress equivalent linear and non-linear site response is performed using four strong ground motions for six sites of Kathmandu valley. In general, one-dimensional (1D) site-response analysis involves the excitation of a soil profile using the horizontal component and calculating the response at individual soil layers. In the present study, both equivalent linear and non-linear site response analyses were conducted using the computer program DEEPSOIL. The results show that there is no significant deviation between equivalent linear and non-linear site response models until the maximum strain reaches to 0.06-0.1%. Overall, it is clearly observed from the results that non-linear site response model perform better as compared to equivalent linear model. However, the significant deviation between two models is resulted from other influencing factors such as assumptions made in 1D site response, lack of accurate values of shear wave velocity and nonlinear properties of the soil deposit. The results are also presented in terms of amplification factors which are predicted to be around four times more in case of non-linear analysis as compared to equivalent linear analysis. Hence, the nonlinear behavior of soil prevails the urgent need of study of dynamic characteristics of the soft soil deposit that can specifically represent the site-specific design spectra for the Kathmandu valley for building resilient structures from future damaging earthquakes.

Keywords: deep soil, equivalent linear analysis, non-linear analysis, site response

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Authors: Julide Yildirim, Nadir Ocal

Abstract:

Even though there are many studies investigating the extent and determinants of poverty, there is paucity of research investigating the issue of energy poverty in Turkey. The aim of this paper is threefold: First to investigate the extend of energy poverty in Turkey by using Household Budget Survey datasets belonging to 2005 - 2016 period. Second, to examine the risk factors for energy poverty. Finally, to assess the impact of social assistance program participation on energy poverty. Existing literature employs alternative methods to measure energy poverty. In this study energy poverty is measured by employing expenditure approach, where people are considered as energy poor if they disburse more than 10 per cent of their income to meet their energy requirements. Empirical results indicate that energy poverty rate is around 20 per cent during the time period under consideration. Since Household Budget Survey panel data is not available for 2005 - 2016 period, a pseudo panel has been constructed. Panel logistic regression method is utilized to determine the risk factors for energy poverty. The empirical results demonstrate that there is a statistically significant impact of work status and education level on energy poverty likelihood. In the final part of the paper the impact of social transfers on energy poverty has been examined by utilizing panel biprobit model, where social transfer participation and energy poverty incidences are jointly modeled. The empirical findings indicate that social transfer program participation reduces energy poverty. The negative association between energy poverty and social transfer program participation is more pronounced in urban areas compared with the rural areas.

Keywords: energy poverty, social transfers, panel data models, Turkey

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