By Guido Buzzi-Ferraris, Flavio Manenti

ISBN-10: 3527332758

ISBN-13: 9783527332755

This fourth in a set of 4 sensible courses is an engineer's better half to utilizing numerical tools for the answer of complicated mathematical difficulties. It explains the speculation at the back of present numerical tools and exhibits in a step by step style find out how to use them.
The quantity makes a speciality of differential and differential-algebraic structures, offering a number of real-life commercial case reviews to demonstrate this complicated subject. It describes the equipment, cutting edge ideas and techniques which are all applied in a freely to be had toolbox referred to as BzzMath, that's built and maintained by way of the authors and offers updated software program instruments for the entire equipment defined within the booklet. a number of examples, pattern codes, courses and functions are taken from a variety of clinical and engineering fields, reminiscent of chemical engineering, electric engineering, physics, drugs, and environmental technological know-how. therefore, engineers and scientists how to optimize procedures even prior to getting into the laboratory.
With extra on-line fabric together with the most recent model of BzzMath Library, deploy educational, all examples and pattern codes utilized in the ebook and a number of additional examples.

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Extra resources for Differential and Differential-Algebraic Systems for the Chemical Engineer: Solving Numerical Problems

Sample text

51) presents numerical problems if we try to calculate it in x ˆ 0, even though the function is 0 in such a point. 3) The function has certain numerical problems within the integration interval. 53) presents numerical problems in x ˆ 0. 9 Gauss–Kronrod Algorithms All the previous circumstances may potentially lead to several difficulties using a general program for integration. Often, however, an opportune transformation of the integral makes its calculation simpler. 56) The devices useful in these cases are not considered in this book.

If the real part of an eigenvalue is largely positive, the system is ill-conditioned; if all the eigenvalues have a negative real part, the system is well conditioned. 19) yn‡1 represents the global error in t n‡1 and this is for À Á 1) Local error: h2n y´´ …ξn † =2. As already-mentioned and in Buzzi-Ferraris and Manenti (2010a), the local error is due to the model approximation. It is estimated by assuming that the calculations are performed without numerical errors and that the exact required data are known: In this case, we assumed the exact value of y in …t n ; y…t n †† was known.

This polynomial can be obtained by using the roots of the Chebyshev polynomial (see Vol. 2, Buzzi-Ferraris and Manenti, 2010b) as support points. 65) is calculated with the aforementioned Gauss–Kronrod algorithm. The remaining two integrals are performed on very small intervals using the Chebyshev support points rather than the Gauss ones. In the BzzMath library, the BzzIntegralGaussBF class carries out the integration using this philosophy. 2 Method Derived from the Extended Trapezoid Algorithm In the automatic methods based on the extended trapezoid formula, overall integration interval is considered: if the error is dissatisfactory, new points uniformly distributed on the interval are inserted.

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Differential and Differential-Algebraic Systems for the Chemical Engineer: Solving Numerical Problems by Guido Buzzi-Ferraris, Flavio Manenti


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