Utilization of Mathematical Software Packages in Chemical Engineering Research

2005 ◽  
Vol 5 (2) ◽  
pp. 125
Author(s):  
Ang Wee Lee ◽  
Nayef Mohamed Ghasem ◽  
Mohamed Azlan Hussain
Keyword(s):  
Differential Equations ◽  
Computer Algebra ◽  
Large Scale ◽  
Chemical Engineering ◽  
Nonlinear Differential Equations ◽  
Differential Algebraic Equations ◽  
Good Choice ◽  
Computer Algebra Systems ◽  
Algebraic Equations ◽  
Starting Point

Using Fortran taken as the starting point, we are now on the sixth decade of high-level programming applications. Among the programming languages available, computer algebra systems (CAS) appear to be a good choice in chemical engineering can be applied easily. Until the emergence of CAS, the assistance from a specialized group for large-scale programming is justified. Nowadays, it is more effective for the modern chemical engineer to rely on his/her own programming ability for problem solving. In the present paper, the abilities of Polymath, Maple, Matlab, Mathcad, and Mathematica in handling differential equations are illustrated for differential-algebraic equations, large system of nonlinear differential equations, and partial differential equations. The programming of solutions with these CAS are presented, contrasted, and discussed in relation to chemical engineering problems. Keywords: Computer algebra systems (CAS),computer simulation,Mathcad, Mathematica,Mathlab and numerical methods.

scholarly journals Treatment for third-order nonlinear differential equations based on the Adomian decomposition method

2017 ◽  
Vol 20 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Xueqin Lv ◽  
Jianfang Gao
Keyword(s):  
Differential Equations ◽  
Decomposition Method ◽  
Nonlinear Differential Equations ◽  
Adomian Decomposition Method ◽  
Differential Algebraic Equations ◽  
Nonlinear Ordinary Differential Equations ◽  
Algebraic Equations ◽  
Third Order ◽  
Adomian Decomposition ◽  
Linear And Nonlinear

The Adomian decomposition method (ADM) is an efficient method for solving linear and nonlinear ordinary differential equations, differential algebraic equations, partial differential equations, stochastic differential equations, and integral equations. Based on the ADM, a new analytical and numerical treatment is introduced in this research for third-order boundary-value problems. The effectiveness of the proposed approach is verified by numerical examples.

scholarly journals Benchmark: A Nonlinear Reachability Analysis Test Set from Numerical Analysis

10.29007/6dcf ◽  
2018 ◽  
Author(s):  
Hoang-Dung Tran ◽  
Luan Viet Nguyen ◽  
Taylor T Johnson
Keyword(s):  
Numerical Analysis ◽  
Differential Equations ◽  
Nonlinear Differential Equations ◽  
Differential Algebraic Equations ◽  
Hybrid Automata ◽  
State Variables ◽  
Algebraic Equations ◽  
Test Set ◽  
Verification Methods ◽  
Highly Nonlinear

The field of numerical analysis has developed numerous benchmarks for evaluating differential and algebraic equation solvers. In this paper, we describe a set of benchmarks commonly used in numerical analysis that may also be effective for evaluating continuous and hybrid systems reachability and verification methods. Many of these examples are challenging and have highly nonlinear differential equations and upwards of tens of dimensions (state variables). Additionally, many examples in numerical analysis are originally encoded as differential algebraic equations (DAEs) with index greater than one or as implicit differential equations (IDEs), which are challenging to model as hybrid automata. We present executable models for ten benchmarks from a test set for initial value problems (IVPs) in the SpaceEx format (allowing for nonlinear equations instead of restricting to affine) and illustrate their conversion to several other formats (dReach, Flow*, and the MathWorks Simulink/Stateflow [SLSF]) using the HyST tool. For some instances, we present successful analysis results using dReach and SLSF.

Numerical methods for differential algebraic equations

Acta Numerica ◽  
1992 ◽  
Vol 1 ◽  
pp. 141-198 ◽  
Author(s):  
Roswitha März
Keyword(s):  
Numerical Methods ◽  
Differential Equations ◽  
Ordinary Differential Equations ◽  
Differential Algebraic Equations ◽  
Algebraic Equations ◽  
Image Position

Differential algebraic equations (DAE) are special implicit ordinary differential equations (ODE)where the partial Jacobian f′y(y, x, t) is singular for all values of its arguments.

Haar wavelet operational matrix method for system of fractional nonlinear differential equations

2017 ◽  
Vol 15 (05) ◽  
pp. 1750043 ◽  
Author(s):  
Umer Saeed
Keyword(s):  
Differential Equations ◽  
Reliable Method ◽  
Nonlinear Differential Equations ◽  
Operational Matrix ◽  
Implementation Process ◽  
Haar Wavelet ◽  
Operational Matrices ◽  
Algebraic Equations ◽  
Operational Matrix Method ◽  
Fractional Differential

In this paper, we present a reliable method for solving system of fractional nonlinear differential equations. The proposed technique utilizes the Haar wavelets in conjunction with a quasilinearization technique. The operational matrices are derived and used to reduce each equation in a system of fractional differential equations to a system of algebraic equations. Convergence analysis and implementation process for the proposed technique are presented. Numerical examples are provided to illustrate the applicability and accuracy of the technique.

scholarly journals Investigating Jeffery-Hamel flow with high magnetic field and nanoparticle by HPM and AGM

2014 ◽  
Vol 4 (4) ◽  
Author(s):  
A. Rostami ◽  
M. Akbari ◽  
D. Ganji ◽  
S. Heydari
Keyword(s):  
Magnetic Field ◽  
Differential Equations ◽  
Homotopy Perturbation Method ◽  
Volume Fraction ◽  
Nonlinear Differential Equations ◽  
Reynolds Numbers ◽  
Solution Procedure ◽  
Algebraic Equations ◽  
Divergent Channel ◽  
Mathematical Operations

AbstractIn this study, the effects of magnetic field and nanoparticle on the Jeffery-Hamel flow are studied using two powerful analytical methods, Homotopy Perturbation Method (HPM) and a simple and innovative approach which we have named it Akbari-Ganji’s Method(AGM). Comparisons have been made between HPM, AGM and Numerical Method and the acquired results show that these methods have high accuracy for different values of α, Hartmann numbers, and Reynolds numbers. The flow field inside the divergent channel is studied for various values of Hartmann number and angle of channel. The effect of nanoparticle volume fraction in the absence of magnetic field is investigated.It is necessary to represent some of the advantages of choosing the new method, AGM, for solving nonlinear differential equations as follows: AGM is a very suitable computational process and is applicable for solving various nonlinear differential equations. Moreover, in AGM by solving a set of algebraic equations, complicated nonlinear equations can easily be solved and without any mathematical operations such as integration, the solution of the problem can be obtained very simply and easily. It is notable that this solution procedure, AGM, can help students with intermediate mathematical knowledge to solve a broad range of complicated nonlinear differential equations.

scholarly journals Approximation of potential-driven flow dynamics in large-scale self-similar tree networks

2011 ◽  
Vol 467 (2134) ◽  
pp. 2810-2824 ◽  
Author(s):  
Jason Mayes ◽  
Mihir Sen
Keyword(s):  
Mathematical Model ◽  
Analytical Solutions ◽  
Large Scale ◽  
Differential Algebraic Equations ◽  
Flow Dynamics ◽  
Algebraic Equations ◽  
Tree Networks ◽  
Self Similar ◽  
Large Scale Flow ◽  
The Mathematical Model

Dynamic analysis of large-scale flow networks is made difficult by the large system of differential-algebraic equations resulting from its modelling. To simplify analysis, the mathematical model must be sufficiently reduced in complexity. For self-similar tree networks, this reduction can be made using the network’s structure in way that can allow simple, analytical solutions. For very large, but finite, networks, analytical solutions are more difficult to obtain. In the infinite limit, however, analysis is sometimes greatly simplified. It is shown that approximating large finite networks as infinite not only simplifies the analysis, but also provides an excellent approximate solution.

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