An Introduction To Matlab® Programming And Numerical Methods For Engineers

[Pang Murdock]

Writtenfor graduate students, An Introduction to MATLAB Programming and Numerical Methods for Engineers introduces principles of programming and numerical methods to engineers who have no prior experience with programming. The book presents many numerical methods concepts that are expanded on in later undergraduate courses. Topics include programming basics, data structures, functions, and plotting.

MATLAB is a powerful programme, which naturally lends itself to the rapid implementation of most numerical algorithms. This text, which uses MATLAB, gives a detailed overview of structured programming and numerical methods for the undergraduate student.

The book covers numerical methods for solving a wide range of problems, from integration to the numerical solution of differential equations or the simulation of random processes. Each chapter includes extensive examples and tasks, at varying levels of complexity. For practice, the early chapters include programmes that require debugging by the reader, while full solutions are given for all the tasks. The book also includes:

Designed as a text for a first course in programming and algorithm design, as well as in numerical methods courses, the book will be of benefit to a wide range of students from mathematics and engineering, to commerce.

Steve Otto was formerly a lecturer at Birmingham University but now heads a research unit at St. Andrews, UK. This book is based on courses taught at Birmingham and at Adelaide to students in mathematics, engineering and economics.

Take online mechanical engineering courses over the summer in thermodynamics, solid mechanics, mechanical engineering programming and more through Binghamton University. The courses are taught by Binghamton University professors from the Mechanical Engineering Department and are open to students from other colleges and universities as well as some qualified high school students. It's a great way to catch up on general education courses, try a class taught by Binghamton University's talented professors, continue your education or test out a new field.

Binghamton University engineering students registering for ME summer courses must have the corresponding prerequisite(s) completed by the starting date of the summer session listed on the University academic calendar. The prerequisite(s) of these courses will be checked. The department will not approve late course add petitions for ME summer courses.

This required course mechanical engineering undergraduate course is

designed to extend the student's knowledge of mechanics to include deformable body mechanics. The main focus of this course is on the deformation of the body when subject to external loading. The concepts of stress, strain, and material constitutive laws are carefully developed in one-, two and three-dimensions. These concepts are applied to the stress and deformation analysis of the common engineering structures such as beams, rod, shafts, pressure vessels, and two-dimensional (plane stress and plane strain) problems. Both theoretical development and applied problems solving, including analysis and design problems, are emphasized. The course material presentation takes the form of instructional videos with some self-directed learning assignments. This course is the prerequisite (C- or better required) for the following ME core courses: ME 381, 392.

Structured programming for mechanical engineers. Engineering programming with MATLAB. Upon completion of this course, students shall acquire the following basic programming skills, which include but not limited to: problem-solving strategies, simple algorithm development and interpretation of mathematical concepts in Matlab environment.

This course covers fundamental issues from the field of rigid-body mechanics. The course combines high-level mathematics (calculus and differential equations), physics and basic engineering concepts. These are applied to investigate common problems in the statics of rigid-body mechanics utilizing fundamental principles involving forces and equilibrium. Both theoretical development and applied problem solving are emphasized.

This course covers fundamental issues from the field of particle and rigid-body kinematics and kinetics. The course combines high-level mathematics (calculus and differential equations), physics and basic engineering concepts. These are applied to investigate common problems in the dynamics of rigid-body mechanics utilizing fundamental principles involving forces and motion. Both theoretical development and applied problem solving are emphasized.

Application of computational methods to solve engineering and scientific problems. topics covered include numerical methods (curve fitting, solution of linear and nonlinear equations, integrations, ordinary and partial differential equations), graphical visualization and statistical analysis using MATLAB.

Properties of pure substances. Concepts of work and heat, fundamental laws of thermodynamics; closed and open systems. Entropy and entropy production. Basic gas and vapor cycles, basic refrigeration cycles.

This course will cover the fundamentals of Finite Element Method through typical mechanical engineering examples. Stiffness method will be introduced for the solution procedure. Knowledge of a programming language (Matlab or Python are preferred) will be very helpful. Fundamentals of using ANSYS APDL for engineering simulations will be covered. "Why", "what" and "how" are the questions that will be answered for each necessary step during a typical analysis. Handson exercises will allow students to practice using ANSYS APDL for engineering analysis. Proper modeling and meshing techniques, and extraction and interpretation of the results (derived from simulations) will be taught.

Free vibration of mechanical systems, damping, forced harmonic vibration, support motion, vibration isolation, response due to arbitrary excitation, systems with multiple degrees of freedom, normal modes, free and forced vibrations, vibration absorber, application of matrix methods, numerical techniques, computer applications.

AMATH 301 Beginning Scientific Computing (4) NSc

Introduction to the use of computers to solve problems arising in the physical, biological, and engineering sciences. Application of mathematical judgment, programming architecture, and flow control in solving scientific problems. Introduction to MATLAB or Python routines for numerical programming, computation, and visualization. Prerequisite: either MATH 125, Q SCI 292, or MATH 135. Offered: AWSpS.

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AMATH 342 Introduction to Neural Coding and Computation (3)

Introduces computational neuroscience, grounded in neuronal and synaptic biophysics. Works through mathematical description of how neurons encode information, and how neural activity is produced dynamically. Uses and teaches MATLAB and/or Python as a programming language to implement models of neuronal dynamics and to perform coding analysis. Prerequisite: MATH 125 or MATH 135. Offered: W.

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AMATH 351 Introduction to Differential Equations and Applications (3) NSc

Introductory survey of ordinary differential equations; linear and nonlinear equations; Taylor series; and. Laplace transforms. Emphasizes on formulation, solution, and interpretation of results. Examples drawn from physical and biological sciences and engineering. Prerequisite: MATH 125 or MATH 135. Offered: AWSpS.

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AMATH 352 Applied Linear Algebra and Numerical Analysis (3) NSc

Analysis and application of numerical methods and algorithms to problems in the applied sciences and engineering. Applied linear algebra, including eigenvalue problems. Emphasis on use of conceptual methods in engineering, mathematics, and science. Extensive use of MATLAB and/or Python for programming and solution techniques. Prerequisite: MATH 126 or MATH 136. Offered: AWSpS.

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AMATH 401 Vector Calculus and Complex Variables (4) NSc

Emphasizes acquisition of solution techniques; illustrates ideas with specific example problems arising in science and engineering. Includes applications of vector differential calculus, complex variables; line-surface integrals; integral theorems; and Taylor and Laurent series, and contour integration. Prerequisite: either MATH 126 or MATH 136. Offered: A.

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AMATH 402 Introduction to Dynamical Systems and Chaos (4) NSc

Overview methods describing qualitative behavior of solutions on nonlinear differential equations. Phase space analysis of fixed pointed and periodic orbits. Bifurcation methods. Description of strange attractors and chaos. Introductions to maps. Applications: engineering, physics, chemistry, and biology. Prerequisite: either AMATH 351, MATH 136, or MATH 207. Offered: W.

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AMATH 422 Computational Modeling of Biological Systems (3) NSc

Examines fundamental models that arise in biology and their analysis through modern scientific computing. Covers discrete and continuous-time dynamics, in deterministic and stochastic settings, with application from molecular biology to neuroscience to population dynamics; statistical analysis of experimental data; and MATLAB and/or Python programming from scratch. Prerequisite: either MATH 135, MATH 207, or AMATH 351. Offered: A.

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AMATH 423 Mathematical Analysis in Biology and Medicine (3) NSc

Focuses on developing and analyzing mechanistic, dynamic models of biological systems and processes, to better understand their behavior and function. Applications drawn from many branches of biology and medicine. Provides experiences in applying differential equations, difference equations, and dynamical systems theory to biological problems. Prerequisite: either AMATH 351, MATH 207, or MATH 135. Offered: W.

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