Banks / Tran Mathematical and Experimental Modeling of Physical and Biological Processes

1. Auflage 2011
ISBN: 978-1-4200-7338-6
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 298 Seiten

Reihe: Textbooks in Mathematics

Through several case study problems from industrial and scientific research laboratory applications, Mathematical and Experimental Modeling of Physical and Biological Processes provides students with a fundamental understanding of how mathematics is applied to problems in science and engineering. For each case study problem, the authors discuss why a model is needed and what goals can be achieved with the model.

Exploring what mathematics can reveal about applications, the book focuses on the design of appropriate experiments to validate the development of mathematical models. It guides students through the modeling process, from empirical observations and formalization of properties to model analysis and interpretation of results. The authors also describe the hardware and software tools used to design the experiments so faculty/students can duplicate them.

Integrating real-world applications into the traditional mathematics curriculum, this textbook deals with the formulation and analysis of mathematical models in science and engineering. It gives students an appreciation of the use of mathematics and encourages them to further study the applied topics. Real experimental data for projects can be downloaded from CRC Press Online.

Zielgruppe

Advanced undergraduate and first year graduate students in mathematics, science; engineering, and scientists in industry and governmental laboratories.

Autoren/Hrsg.

Banks, H.T.

Tran, H.T.

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle

Inhaltsverzeichnis

Introduction: The Iterative Modeling Process

Modeling and Inverse Problems
Mechanical Vibrations
Inverse Problems
Mathematical and Statistical Aspects of Inverse Problems
Probability and Statistics Overview
Parameter Estimation or Inverse Problems
Computation of sigman, Standard Errors, and Confidence Intervals
Investigation of Statistical Assumptions
Statistically Based Model Comparison Techniques
Mass Balance and Mass Transport
Introduction
Compartmental Concepts
Compartment Modeling
General Mass Transport Equations
Heat Conduction
Motivating Problems
Mathematical Modeling of Heat Transfer
Experimental Modeling of Heat Transfer
Structural Modeling: Force/Moments Balance
Motivation: Control of Acoustics/Structural Interactions
Introduction to Mechanics of Elastic Solids
Deformations of Beams
Separation of Variables: Modes and Mode Shapes
Numerical Approximations: Galerkin’s Method
Energy Functional Formulation
The Finite Element Method
Experimental Beam Vibration Analysis
Beam Vibrational Control and Real-Time Implementation
Introduction
Controllability and Observability of Linear Systems
Design of State Feedback Control Systems and State Estimators
Pole Placement (Relocation) Problem
Linear Quadratic Regulator Theory
Beam Vibrational Control: Real-Time Feedback Control Implementation
Wave Propagation
Fluid Dynamics
Fluid Waves
Experimental Modeling of the Wave Equation
Size-Structured Population Models
Introduction: A Motivating Application
A Single Species Model (Malthusian Law)
The Logistic Model
A Predator/Prey Model
A Size-Structured Population Model
The Sinko–Streifer Model and Inverse Problems
Size Structure and Mosquitofish Populations
Appendix A: An Introduction to Fourier Techniques
Fourier Series
Fourier Transforms
Appendix B: Review of Vector Calculus
References appear at the end of each chapter.