• Transactions of Materials Processing
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• v.29 no.5
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• pp.282-289
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• 2020

Flexible roll forming is an advanced sheet-metal-forming process that allows the production of parts with various cross-sections. During the flexible process, material is subjected to three-dimensional deformation such as transverse bending, inhomogeneous elongations, or contraction. Because of the effects of process variables on the quality of the roll-formed products, the approaches used to investigate the roll-forming process have been largely dependent on experience and trial- and-error methods. Web-warping is one of the major shape defects encountered in flexible roll forming. In this study, an SVR model was developed to predict the web-warping during the flexible roll forming process. In the development of the SVR model, three process parameters, namely the forming-roll speed condition, leveling-roll height, and bend angle were considered as the model inputs, and the web-warping height was used as the response variable for three blank shapes; rectangular, concave, and convex shape. MATLAB software was used to train the SVR model and optimize three hyperparameters (λ, ε, and γ). To evaluate the SVR model performance, the statistical analysis was carried out based on the three indicators: the root-mean-square error, mean absolute error, and relative root-mean-square error.

• Journal of Biosystems Engineering
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• v.37 no.2
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• pp.82-89
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• 2012

Purpose: The simulation model of a pneumatic conveying drying (PCD) for sawdust was developed and verified with the experiments. Method: The thermal behavior and mass transfer of a PCD were modeled and investigated by comparing the experimental results given by a reference (Kamei et al. 1952) to validate the model. Momentum, energy and mass balance, one dimensional first order ordinary differential equations, were coded and solved into Matlab V. 7.1.0 (2009). Results: The simulation results showed that the moisture content reduced from 194% to 40% (dry basis), air temperature decreased from $512^{\circ}C$ to $128^{\circ}C$ with the particle residence time of 0.7 seconds. The statistical indicators, root mean square error and R-squared, were calculated to be 0.079, and 0.998, respectively, between the measured and predicted values of moisture content. The relative error between the measured and predicted values of the final pressured drop, air temperature, and air velocity were only 8.96%, 0.39% and 1.05% respectively. Conclusions: The predicted moisture content, final temperature, and pressure drop values were in good agreement with the experimental results. The developed model can be used for design and estimation of PCD system for drying of wood dust particles.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.83-93
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• 2020

This empirical research aims to modeling and improving the forecasting accuracy of the volatility pattern by employing the Saudi Arabia stock market (Tadawul)by studying daily closed price index data from October 2011 to December 2019 with a number of observations being 2048. In order to achieve significant results, this study employs many mathematical functions which are non-linear spectral model Maximum overlapping Discrete Wavelet Transform (MODWT) based on the best localized function (Bl14), autoregressive integrated moving average (ARIMA) model and generalized autoregressive conditional heteroskedasticity (GARCH) models. Therefore, the major findings of this study show that all the previous events during the mentioned period of time will be explained and a new forecasting model will be suggested by combining the best MODWT function (Bl14 function) and the fitted GARCH model. Therefore, the results show that the ability of MODWT in decomposition the stock market data, highlighting the significant events which have the most highly volatile data and improving the forecasting accuracy will be showed based on some mathematical criteria such as Mean Absolute Percentage Error (MAPE), Mean Absolute Scaled Error (MASE), Root Means Squared Error (RMSE), Akaike information criterion. These results will be implemented using MATLAB software and R- software.

• Journal of Hydrogen and New Energy
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• v.29 no.5
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• pp.538-548
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• 2018

The thermo-acoustic instability in the combustion process of a gas turbine is caused by the interaction of the heat release mechanism and the pressure perturbation. These acoustic vibrations cause fatigue failure of the combustor and decrease the combustion efficiency. This study is to develop a segmented dynamic thermo-acoustic model to understand combustion instability of gas turbine. Therefore, this study required a dynamic analysis rather than static analysis, and developed a segmented model that can analyze the performance of the system over time using the Matlab/Simulink. The developed model can confirm the thermo-acoustic combustion instability and exhaust gas concentration in the combustion chamber according to the equivalent ratio change, and confirm the thermo-acoustic combustion instability for the inlet temperature and the load changes. As a result, segmented dynamic thermo-acoustic model has been developed to analyze combustion instability under the operating condition.

• Journal of the Korea Society for Simulation
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• v.15 no.1
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• pp.43-50
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• 2006

The major objective of this paper is to propose a hybrid simulation environment for autonomous UAV system by integrating the continuous-time model with discrete-event model. Proposed system is able to support high autonomous behavior by combining the planner, recognizer, and controller model to deal with the HL20 AIRPLANE model. Thus, the high level decision may be efficiently issued even upon the unexpected circumstance. The proposed system model has been successfully verified by several simulation test performed on the DEVS simulation S/W environment.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1146-1155
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• 2017

Normally, the artificial intelligence algorithms are widely applied to the optimal controller design. Then, it is expected that the best output performance is achieved. Unfortunately, when resulting controller parameters are implemented by using the practical devices, the output performance cannot be the best as expected. Therefore, the paper presents the optimal controller design using the combination between the state-space averaging model and the adaptive Tabu search algorithm with the new criteria as two penalty conditions to handle the mentioned problem. The buck-boost converter regulated by the cascade PI controllers is used as the example power system. The results show that the output performance is better than those from the conventional design method for both input and load variations. Moreover, it is confirmed that the reported controllers can be implemented using the realistic devices without the limitation and the stable operation is also guaranteed. The results are also validated by the simulation using the topology model of MATLAB and also experimentally verified by the testing rig.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.21-26
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• 2006

This paper focuses on modeling and predicting differential GPS corrections transmitted by marine radio-beacon systems using artificial neural networks. Various neural network structures with various training algorithms were examined, including Linear, Radial Biases, and Feedforward. Matlab Neural Network toolbox is used for this purpose. Data sets used in building the model are the transmitted pseudorange corrections and broadcast navigation message. Model design is passed through several stages, namely data collection, preprocessing, model building, and finally model validation. It is found that feedforward neural network with automated regularization is the most suitable for our data. In training the neural network, different approaches are used to take advantage of the pseudorange corrections history while taking into account the required time for prediction and storage limitations. Three data structures are considered in training the neural network, namely all round, compound, and average. Of the various data structures examined, it is found that the average data structure is the most suitable. It is shown that the developed model is capable of predicting the differential correction with an accuracy level comparable to that of beacon-transmitted real-time DGPS correction.

• Journal of Institute of Convergence Technology
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• v.3 no.2
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• pp.23-29
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• 2013

When a human operator interacts with a virtual wall that is modeled as a virtual spring model, the lager the stiffness of the virtual spring is, the more realistic the operator feels that the virtual wall is. In the previous studies, it is shown that the maximum available stiffness of a virtual spring to guarantee the stability can be increased when the first-order-hold method is applied, however the effects of a human impedance on the stability are not considered. This paper presents the effects of a human impedance on stability of haptic system with a virtual spring and a first-order-hold (FOH) method. The human impedance model is modeled as a linear second-order system model. The relations between the maximum available stiffness of a virtual spring and the human impedance such as a mass, a damping and a stiffness are analyzed through the MATLAB simulation. It is shown that the maximum available stiffness is proportional to the square root of the human mass or damping respectively.

• Steel and Composite Structures
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• v.34 no.2
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• pp.279-288
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• 2020

The computational post-buckling strength of the tilted sandwich composite shell structure is evaluated in this article. The computational responses are obtained using a mathematical model derived using the higher-order type of polynomial kinematic in association with the through-thickness stretching effect. Also, the sandwich deformation behaviour of the flexible soft-core sandwich structural model is expressed mathematically with the help of a generic nonlinear strain theory i.e. Green-Lagrange type strain-displacement relations. Subsequently, the model includes all of the nonlinear strain terms to account the actual deformation and discretized via displacement type of finite element. Further, the computer code is prepared (MATLAB environment) using the derived higher-order formulation in association with the direct iterative technique for the computation of temperature carrying capacity of the soft-core sandwich within the post-buckled regime. Further, the nonlinear finite element model has been tested to show its accuracy by solving a few numerical experimentations as same as the published example including the consistency behaviour. Lastly, the derived model is utilized to find the temperature load-carrying capacity under the influences of variable factors affecting the soft-core type sandwich structural design in the small (finite) strain and large deformation regime including the effect of tilt angle.

• Earthquakes and Structures
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• v.7 no.3
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• pp.349-365
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• 2014

The dynamic response of structures under extremely short duration dynamic loads is of great concern nowadays. This paper investigates structures' response as well as the associated structural damage to explosive loads considering and ignoring the supporting soil flexibility effect. In the analysis, buildings are modeled by two alternate approaches namely, (1) building with fixed supports, (2) building with supports accounting for soil-flexibility. A lumped parameter model with spring-dashpot elements is incorporated at the base of the building model to simulate the horizontal and rotational movements of supporting soil. The soil flexibility for various shear wave velocities has been considered in the investigation. In addition, the influence of variation of lateral natural periods of building models on the obtained response and peak response time-histories besides damage indices has also been investigated under blast loads with different peak over static pressures. The Dynamic response is obtained by solving the governing equations of motion of the considered building model using a developed Matlab code based on the finite element toolbox CALFEM. The predicted results expressed in time-domain by the building model incorporating SSI effect are compared with the corresponding model results ignoring soil flexibility effect. The results show that the effect of surrounding soil medium leads to significant changes in the obtained dynamic response of the considered systems and hence cannot be simply ignored in damage assessment and response time-histories of structures where it increases response and amplifies damage of structures subjected to blast loads. Moreover, the numerical results provide an understanding of level of damage of structure through the computed damage indices.