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Amouzegar Mahyar A. - Transactions on engineering technologies: World Congress on Engineering and Computer Science 2015

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Amouzegar Mahyar A. Transactions on engineering technologies: World Congress on Engineering and Computer Science 2015
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This proceedings volume contains selected revised and extended research articles written by researchers who participated in the World Congress on Engineering and Computer Science 2015, held in San Francisco, USA, 21-23 October 2015. Topics covered include engineering mathematics, electrical engineering, circuits, communications systems, computer science, chemical engineering, systems engineering, manufacturing engineering, and industrial applications. The book offers the reader an overview of the state of the art in engineering technologies, computer science, systems engineering and applications, and will serve as an excellent reference work for researchers and graduate students working in these fields.;3 MOESP_AOKI_VAR: Algorithm for Space State Identification of Non-stationary Multivariable Noisy Linear Systems3.1 Introduction; 3.2 Foundation; 3.2.1 Stationary Deterministic Linear System; 3.2.2 Stationary Noisy Linear System; 3.2.3 Non-stationary Deterministic Linear System; 3.2.4 Non-stationary Noisy Linear System; 3.2.5 Time Variant Identification; 3.2.6 Deterministic-Stochastic Modelling of the State Space of Non-stationary System; 3.3 MOESP_AOKI_VAR Algorithm; 3.4 Experimentation and Results; 3.5 Conclusions; References; 4 Comparative the Performance of Control Charts Based on Copulas.;2 Analysis of Systemic Risk: A Dynamic Vine Copula-Based ARMA-EGARCH Model2.1 Introduction; 2.2 Methodology; 2.2.1 Risk Methodology; 2.2.2 Univariate ARMA-EGARCH Model; 2.2.3 Sklars Theory; 2.2.4 Parametric Copulas; 2.2.5 Vine Copulas; 2.2.6 Tail Dependence; 2.2.7 Estimation Method; 2.3 Data and Empirical Findings; 2.3.1 Data Representation; 2.3.2 Results for the Marginal Models; 2.3.3 Results for the Copula Models; 2.3.4 Results for the Copula VaR and Copula VaR Ratio; 2.4 Conclusion; References.;Preface; Contents; 1 Estimate the Impact of Different Heat Capacity Approximation Methods on the Numerical Results During Computer Simulation of Solidification; 1.1 Introduction; 1.2 Description of the Entalphy Formulation; 1.2.1 The Enthalpy and the Effective Heat Capacity; 1.2.2 The Types of the Entalphy Formulations; 1.3 Approximation of the Effective Heat Capacity; 1.4 Numerical Model of Solidification; 1.5 Used Software of Engineering Simulation; 1.6 Results of the Numerical Experiment; 1.7 Conclusions; References.;5.3.2 Risk Indicators of Landslides5.3.3 Fuzzy Decision Model for Landslide Hazard Assessment; 5.3.3.1 Fuzzification of the Input Variables; 5.3.3.2 Rule Evaluation; 5.3.3.3 Aggregation of the Output Rules; 5.3.3.4 Defuzzification; 5.3.4 Geographic Information System for Landslide Hazard Mapping; 5.4 Results and Discussion; 5.5 Conclusion; 5.6 Recommendation; Acknowledgements; References; 6 Laser Scanning as a Tool for the Analysis of Historical Buildings; 6.1 Introduction; 6.2 2D Documentation; 6.3 Types of 3D Scanners.;4.1 Introduction4.2 Research Methodology; 4.2.1 Multivariate Exponentially Weighted Moving Average Control Chart; 4.2.2 Double Multivariate Exponentially Weighted Moving Average Control Chart; 4.2.3 Multivariate Cumulative Sum Control Chart; 4.2.4 Copulas Concepts; 4.2.4.1 Normal Copula; 4.2.4.2 Archimedean Copulas; 4.2.5 Dependence and Kendalls tau; 4.3 Numerical Results; 4.4 Conclusion and Future Work; Acknowledgments; References; 5 Mamdani Fuzzy Decision Model for GIS-Based Landslide Hazard Mapping; 5.1 Introduction; 5.2 Theoretical Framework; 5.3 Methods; 5.3.1 Study Area.

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Springer Nature Singapore Pte Ltd. 2017
Sio-Iong Ao , Haeng Kon Kim and Mahyar A. Amouzegar (eds.) Transactions on Engineering Technologies 10.1007/978-981-10-2717-8_1
1. Estimate the Impact of Different Heat Capacity Approximation Methods on the Numerical Results During Computer Simulation of Solidification
Robert Dyja 1
(1)
Czestochowa University of Technology, Dabrowskiego 69, PL42201 Czstochowa, Poland
Robert Dyja (Corresponding author)
Email:
Elzbieta Gawronska
Email:
Andrzej Grosser
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Piotr Jeruszka
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Norbert Sczygiol
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Keywords
Approximation methods Computer simulation Enthalpy Heat capacity Solid phase Solidification
1.1 Introduction
Aluminum alloys are very interesting material widely used in industry. Modeling and computer simulation are one of the most effective methods of studying difficult problems in foundry and metallurgical manufacture. Numerical simulations are used for optimization of casting production. In many cases they are the only possible techniques for carrying out the experiments whose real statement is complicated. Computer modeling allows to define the major factors of a quality estimation of alloy castings. Simulations help to investigate interaction between solidifying casting and changes of its parameters or initial conditions. That process defines the quality of casting, and the problem of adequate modeling of foundry systems. The process mainly depends on the solution of heat equations [].
Increasing capacity of computer memory makes it possible to consider growing problem sizes. At the same time, increased precision of simulations triggers even greater load. There are several ways to tackle this kind of problems. For instance, one can use parallel computing [].
Solidification may take place at a constant temperature or in the temperature range []. If solidification occurs at a constant temperature, it is then referred to as the so-called Stefan problem or the solidification problem with zero temperatures range. Pure metals or alloys of certain specific chemical compositions (e.g. having an eutectic composition) solidify at a constant temperature. However, most of the metal alloys solidify in certain temperature ranges (so-called temperature intervals of solidification). The temperature at which the alloy starts to solidify is called liquidus temperature ( Picture 1 ), and the temperature at which solidification ends is called solidus temperature ( Picture 2 ). In the case of alloys with eutectic transformation, in which the solute concentration exceeds its maximum solubility in the solid phase, the temperature of the solidification end is the eutectic temperature. Analytical (rarely) and numerical (commonly) methods are used in the modeling of solidification process. The finite elements method (FEM) is the most commonly used numerical method, but finite difference method (FDM), boundary element method (BEM), the Monte-Carlo and other methods are also used.
The most important heat effect, occurring during solidification, is the emission of (latent) heat of solidification ( L ). It is also the most difficult phenomenon to numerical modeling. The basic division of numerical methods of solidification modeling process relates to modeling of the latent heat emission. These methods can be divided into front-tracking methods and fixed-grid methods. Fixed-grid methods are also divided into temperature formulations (the latent heat of solidification is considered as the temperature-dependent term of heat source) and enthalpy formulations (the latent heat of solidification is considered as the temperature-dependent term of heat capacity) [].
During the comparison, we have used Finite Element Method as numerical method of choice. The FEM was used in our own software, that is used to conduct simulations of solidification. This software is implemented in the C++ programming language with the use of essential libraries, i.e. PETSc (for linear algebra) [].
1.2 Description of the Entalphy Formulation
Solidification is described by a quasi-linear equation of heat conduction, considering a term of heat source Transactions on engineering technologies World Congress on Engineering and Computer Science 2015 - image 3 as a latent heat of solidification:
Transactions on engineering technologies World Congress on Engineering and Computer Science 2015 - image 4
(1.1)
By entering the following designation:
Transactions on engineering technologies World Congress on Engineering and Computer Science 2015 - image 5
(1.2)
equation () can be written as
Transactions on engineering technologies World Congress on Engineering and Computer Science 2015 - image 6
(1.3)
where Transactions on engineering technologies World Congress on Engineering and Computer Science 2015 - image 7 denotes generalized heat source. By introducing enthalpy, defined as:
Transactions on engineering technologies World Congress on Engineering and Computer Science 2015 - image 8
(1.4)
where Transactions on engineering technologies World Congress on Engineering and Computer Science 2015 - image 9 is the reference temperature, and calculating the derivative with respect to the temperature:
Transactions on engineering technologies World Congress on Engineering and Computer Science 2015 - image 10
(1.5)
where Transactions on engineering technologies World Congress on Engineering and Computer Science 2015 - image 11 is the effective heat capacity. Assuming the heat source is equal to zero, the Eq. () can be converted to the form:
Transactions on engineering technologies World Congress on Engineering and Computer Science 2015 - image 12
(1.6)
All above equations form the basis of the thermal description of solidification.
1.2.1 The Enthalpy and the Effective Heat Capacity
The enthalpy is the sum of explicit and latent heat []. For the metal solidifying in the temperature range ( amounts to 17 The integration of the expressions in Eq gives - photo 13amounts to 17 The integration of the expressions in Eq gives 18 - photo 14 ) amounts to:
17 The integration of the expressions in Eq gives 18 Assuming that - photo 15
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