Modeling and Simulation of Everyday Things, 2e

Michael Roth

Modeling and Simulation of Everyday Things, 2e
Format
Hardback
Publisher
Taylor & Francis Ltd
Country
United Kingdom
Published
14 April 2025
Pages
384
ISBN
9781032994994

Modeling and Simulation of Everyday Things, 2e

Michael Roth

With Python, C++, FORTRAN and a friendly conversational tone peppered with attempted humor, Modeling and Simulation of Everyday Things takes us on a journey through constructing models, and simulations of systems and processes of everyday life and beyond. Readers can access an example-packed online repository of programs in each of the three languages.

This Second Edition is a wonderful confluence of code development of Python and C++ applications and will cultivate broad perspective in the readership through having translations of major programs available in Python, C++ and FORTRAN (as we move forward, software engineers and researchers are recognizing the value of legacy programming). In addition to leveraging the best of the three languages, the readership can explore versatility in visualization by using native Python graphics as well as POV Raytracer and third-party animation tools. We approach modeling of a system by introducing the theoretical framework of the system, followed by its discretized form, then with narrated programs and sample results that also appear in the online repository.

Readers will be able to critically think through constructing models and simulations of a vast array of systems, interpreting results and visualizing them (which includes examples for visually and auditorily impaired individuals). Most importantly, their confidence will propel them forward to meet the challenges of the field, and to think "outside the book".

Leveraging the best of three coding languages, two tracks for visualization, a conversational tone, and numerous examples, this book is extremely versatile and can be used by students from high school through science undergraduates in 2-year and 4-year institutions. The text is also ideal for use in Data Science as well as Professional Science Masters' programs.

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