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  • Format: ePub

Foundations of Mathematical Modeling and Analysis in Engineering offers a comprehensivepresentation of the mathematical principles underpinning modern engineering and the quantitative sciences, and develops mathematical modeling as a foundational intellectual discipline. Designed for graduate and advanced undergraduate students, and accessible to seasoned professionals, it provides the means to develop and employ mathematical representations of physical processes and systems. - A comprehensive toolbox for graduate engineering students, covering foundational and advanced mathematical concepts…mehr

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Produktbeschreibung
Foundations of Mathematical Modeling and Analysis in Engineering offers a comprehensivepresentation of the mathematical principles underpinning modern engineering and the quantitative sciences, and develops mathematical modeling as a foundational intellectual discipline. Designed for graduate and advanced undergraduate students, and accessible to seasoned professionals, it provides the means to develop and employ mathematical representations of physical processes and systems. - A comprehensive toolbox for graduate engineering students, covering foundational and advanced mathematical concepts and methods - Emphasizes real-world applications of mathematical models, bolstering problem-solving skills through worked examples and end-of-chapter exercises - Aids the transition from undergraduate to graduate studies, ensuring comprehensive understanding and application of the mathematical concepts for advanced engineering courses and research - Offers teaching support, including an image bank, and full Solutions Manual, for qualified instructors, available for request at educate.elsevier.com/9780443295928

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Autorenporträt
Professor Emeritus A. Ted Watson holds a BS from University of Texas at Austin and a PhD from California Institute of Technology, both in chemical engineering. He attained the position of Professor at Texas A&M University (TAMU) before joining Colorado State University (CSU) as the founding department head of chemical & biological engineering. He has advanced mathematical modeling and system and parameter identification while working within a variety of fields. He established the Engineering Imaging Laboratory at TAMU and Rocky Mountain Magnetic Resonance at CSU and was elected Fellow of the American Institute of Chemical Engineers (AIChE).