Numerical Symbolic And Statistical Computing For Chemical E
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| Author | : Ghosh, Pallab |
| Publisher | : PHI Learning Pvt. Ltd. |
| Total Pages | : 416 |
| Release | : 2018-09-01 |
| Genre | : |
| ISBN | : 9387472523 |
Numerical, analytical and statistical computations are routine affairs for chemical engineers. They usually prefer a single software to solve their computational problems, and at present, MATLAB has emerged as a powerful computational language, which is preferably used for this purpose, due to its built-in functions and toolboxes. Considering the needs and convenience of the students, the author has made an attempt to write this book, which explains the various concepts of MATLAB in a systematic way and makes its readers proficient in using MATLAB for computing. It mainly focuses on the applications of MATLAB, rather than its use in programming basic numerical algorithms. Commencing with the introduction to MATLAB, the text covers vector and matrix computations, solution of linear and non-linear equations, differentiation and integration, and solution of ordinary and partial differential equations. Next, analytical computations using the Symbolic Math Toolbox and statistical computations using the Statistics and Machine Learning Toolbox are explained. Finally, the book describes various curve fitting techniques using the Curve Fitting Toolbox. Inclusion of all these advanced-level topics in the book stands it out from the rest. KEY FEATURES Numerous worked-out examples to enable the readers understand the steps involved in solving the chemical engineering problems MATLAB codes to explain the computational techniques Several snapshots to help the readers understand the step-by-step procedures of using the toolboxes Chapter-end exercises, including short-answer questions and numerical problems Appendix comprising the definitions of some important and special matrices Supplemented with Solutions Manual containing complete detailed solutions to the unsolved analytical problems Accessibility of selected colour figures (including screenshots and results/outputs of the programs) cited in the text at www.phindia.com/Pallab_Ghosh. TARGET AUDIENCE • BE/B.Tech (Chemical Engineering) • ME/M.Tech (Chemical Engineering)
| Author | : Pallab Ghosh |
| Publisher | : |
| Total Pages | : |
| Release | : 2018-10-30 |
| Genre | : |
| ISBN | : 9789387472518 |
| Author | : Kenneth J. Beers |
| Publisher | : Cambridge University Press |
| Total Pages | : 496 |
| Release | : 2007 |
| Genre | : Computers |
| ISBN | : 9780521859714 |
Applications of numerical mathematics and scientific computing to chemical engineering.
| Author | : Said S.E.H. Elnashaie |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 595 |
| Release | : 2007-03-12 |
| Genre | : Mathematics |
| ISBN | : 0387681671 |
This interdisciplinary book presents numerical techniques needed for chemical and biological engineers using Matlab. The book begins by exploring general cases, and moves on to specific ones. The text includes a large number of detailed illustrations, exercises and industrial examples. The book provides detailed mathematics and engineering background in the appendixes, including an introduction to Matlab. The text will be useful to undergraduate students in chemical/biological engineering, and in applied mathematics and numerical analysis.
| Author | : Yeong Koo Yeo |
| Publisher | : CRC Press |
| Total Pages | : 849 |
| Release | : 2020-12-15 |
| Genre | : Science |
| ISBN | : 1000284883 |
Chemical Engineering Computation with MATLAB®, Second Edition continues to present basic to advanced levels of problem-solving techniques using MATLAB as the computation environment. The Second Edition provides even more examples and problems extracted from core chemical engineering subject areas and all code is updated to MATLAB version 2020. It also includes a new chapter on computational intelligence and: Offers exercises and extensive problem-solving instruction and solutions for various problems Features solutions developed using fundamental principles to construct mathematical models and an equation-oriented approach to generate numerical results Delivers a wealth of examples to demonstrate the implementation of various problem-solving approaches and methodologies for problem formulation, problem solving, analysis, and presentation, as well as visualization and documentation of results Includes an appendix offering an introduction to MATLAB for readers unfamiliar with the program, which will allow them to write their own MATLAB programs and follow the examples in the book Provides aid with advanced problems that are often encountered in graduate research and industrial operations, such as nonlinear regression, parameter estimation in differential systems, two-point boundary value problems and partial differential equations and optimization This essential textbook readies engineering students, researchers, and professionals to be proficient in the use of MATLAB to solve sophisticated real-world problems within the interdisciplinary field of chemical engineering. The text features a solutions manual, lecture slides, and MATLAB program files._
| Author | : Denis Constales |
| Publisher | : Elsevier |
| Total Pages | : 416 |
| Release | : 2016-08-23 |
| Genre | : Technology & Engineering |
| ISBN | : 0444594841 |
Advanced Data Analysis and Modeling in Chemical Engineering provides the mathematical foundations of different areas of chemical engineering and describes typical applications. The book presents the key areas of chemical engineering, their mathematical foundations, and corresponding modeling techniques. Modern industrial production is based on solid scientific methods, many of which are part of chemical engineering. To produce new substances or materials, engineers must devise special reactors and procedures, while also observing stringent safety requirements and striving to optimize the efficiency jointly in economic and ecological terms. In chemical engineering, mathematical methods are considered to be driving forces of many innovations in material design and process development. - Presents the main mathematical problems and models of chemical engineering and provides the reader with contemporary methods and tools to solve them - Summarizes in a clear and straightforward way, the contemporary trends in the interaction between mathematics and chemical engineering vital to chemical engineers in their daily work - Includes classical analytical methods, computational methods, and methods of symbolic computation - Covers the latest cutting edge computational methods, like symbolic computational methods
| Author | : National Science Foundation (U.S.) |
| Publisher | : |
| Total Pages | : 172 |
| Release | : 1969 |
| Genre | : Federal aid to research |
| ISBN | : |
| Author | : Sauro Pierucci |
| Publisher | : Elsevier |
| Total Pages | : 1207 |
| Release | : 2000-05-10 |
| Genre | : Technology & Engineering |
| ISBN | : 008053130X |
This book includes papers presented at ESCAPE-10, the 10th European Symposium on Computer Aided Process -Engineering, held in Florence, Italy, 7-10th May, 2000. The scientific program reflected two complementary strategic objectives of the 'Computer Aided Process Engineering' (CAPE) Working Party: one checked the status of historically consolidated topics by means of their industrial application and their emerging issues, while the other was addressed to opening new windows to the CAPE audience by inviting adjacent Working Parties to co-operate in the creation of the technical program.The former CAPE strategic objective was covered by the topics: Numerical Methods, Process Design and Synthesis, Dynamics & Control, Process Modeling, Simulation and Optimization.The latter CAPE strategic objective derived from the European Federation of Chemical Engineering (EFCE) promotion of scientific activities which autonomously and transversely work across the Working Parties' terms of references. These activities enhance the exchange of the know-how and knowledge acquired by different Working Parties in homologous fields. They also aim to discover complementary facets useful to the dissemination of tools and of novel procedures.As a consequence, the Working Parties 'Environmental Protection', 'Loss Prevention and Safety Promotion' and 'Multiphase Fluid Flow' were invited to assist in the organization of sessions in the area of: A Process Integrated Approach for: Environmental Benefit, Loss Prevention and Safety, Computational Fluid Dynamics. A total of 473 abstracts from all over the world were evaluated by the International Scientific Committee. Out of them 197 have been finally selected for the presentation and reported into this book. Their authors come from thirty different countries. The selection of the papers was carried out by twenty-eight international reviewers. These proceedings will be a major reference document to the scientific and industrial community and will contribute to the progress in Computer Aided Process Engineering.
| Author | : Bonnie J. McBride |
| Publisher | : |
| Total Pages | : 96 |
| Release | : 1992 |
| Genre | : Gases |
| ISBN | : |
| Author | : Gabriel Kronberger |
| Publisher | : CRC Press |
| Total Pages | : 308 |
| Release | : 2024-08-16 |
| Genre | : Computers |
| ISBN | : 042967953X |
Symbolic regression (SR) is one of the most powerful machine learning techniques that produces transparent models, searching the space of mathematical expressions for a model that represents the relationship between the predictors and the dependent variable without the need of taking assumptions about the model structure. Currently, the most prevalent learning algorithms for SR are based on genetic programming (GP), an evolutionary algorithm inspired from the well-known principles of natural selection. This book is an in-depth guide to GP for SR, discussing its advanced techniques, as well as examples of applications in science and engineering. The basic idea of GP is to evolve a population of solution candidates in an iterative, generational manner, by repeated application of selection, crossover, mutation, and replacement, thus allowing the model structure, coefficients, and input variables to be searched simultaneously. Given that explainability and interpretability are key elements for integrating humans into the loop of learning in AI, increasing the capacity for data scientists to understand internal algorithmic processes and their resultant models has beneficial implications for the learning process as a whole. This book represents a practical guide for industry professionals and students across a range of disciplines, particularly data science, engineering, and applied mathematics. Focused on state-of-the-art SR methods and providing ready-to-use recipes, this book is especially appealing to those working with empirical or semi-analytical models in science and engineering.
