Physical models have been, and continue to be used by engineers when faced with unprecedented challenges, when engineering science has been non-existent or inadequate, and in any other situation when the engineer has needed to raise their confidence in a design proposal to a sufficient level to begin construction. For this reason, models have mostly been used by designers and constructors of highly innovative projects, when previous experience has not been available. The book covers the history of using of physical models in the design and development of civil and building engineering projects including bridges in the mid-18th century, William Fairbairn?s Britannia bridge in the 1840s, the masonry Aswan Dam in the 1890s, concrete dams in the 1920s, thin concrete shell roofs and the dynamic behaviour of tall buildings in earthquakes from the 1930s, tidal flow in estuaries and the acoustics of concert halls from the 1950s, and cable-net and membrane structures in the 1960s. Traditionally, progress in engineering has been attributed to the creation and use of engineering science, the understanding materials properties and the development of new construction methods. The book argues that the use of reduced scale models have played an equally important part in the development of civil and building engineering. However, like the history of engineering design itself, this crucial contribution has not been widely reported or celebrated. The book concludes with reviews of the current use of physical models alongside computer models, for example, in boundary layer wind tunnels, room acoustics, seismic engineering, hydrology, and air flow in buildings.

Written for intermediate-level undergraduates pursuing any science or engineering major, Physical Models of Living Systems helps students develop many of the competencies that form the basis of the new MCAT2015. The only prerequisite is first-year physics. With the more advanced "Track-2" sections at the end of each chapter, the book can be used in graduate-level courses as well.

Laboratory physical models are a valuable tool for coastal engineers. Physical models help us to understand the complex hydrodynamic processes occurring in the nearshore zone and they provide reliable and economic engineering design solutions.This book is about the art and science of physical modeling as applied in coastal engineering. The aim of the book is to consolidate and synthesize into a single text much of the knowledge about physical modeling that has been developed worldwide.This book was written to serve as a graduate-level text for a course in physical modeling or as a reference text for engineers and researchers engaged in physical modeling and laboratory experimentation. The first three chapters serve as an introduction to similitude and physical models, covering topics such as advantages and disadvantages of physical models, systems of units, dimensional analysis, types of similitude and various hydraulic similitude criteria applicable to coastal engineering models.Practical application of similitude principles to coastal engineering studies is covered in Chapter 4 (Hydrodynamic Models), Chapter 5 (Coastal Structure Models) and Chapter 6 (Sediment Transport Models). These chapters develop the appropriate similitude criteria, discuss inherent laboratory and scale effects and overview the technical literature pertaining to these types of models. The final two chapters focus on the related subjects of laboratory wave generation (Chapter 7) and measurement and analysis techniques (Chapter 8).

From the reviews: "... this is a well produced book, written in a easy to read style, and will also be a very useful primer for someone starting out the field [...], and a useful source of reference for experienced users ..." Microelectronics Journal

This book surveys the most recent advances in physics-inspired cell movement models. This synergetic, cross-disciplinary effort to increase the fidelity of computational algorithms will lead to a better understanding of the complex biomechanics of cell movement, and stimulate progress in research on related active matter systems, from suspensions of bacteria and synthetic swimmers to cell tissues and cytoskeleton.Cell motility and collective motion are among the most important themes in biology and statistical physics of out-of-equilibrium systems, and crucial for morphogenesis, wound healing, and immune response in eukaryotic organisms. It is also relevant for the development of effective treatment strategies for diseases such as cancer, and for the design of bioactive surfaces for cell sorting and manipulation. Substrate-based cell motility is, however, a very complex process as regulatory pathways and physical force generation mechanisms are intertwined. To understand the interplay between adhesion, force generation and motility, an abundance of computational models have been proposed in recent years, from finite element to immerse interface methods and phase field approaches.This book is primarily written for physicists, mathematical biologists and biomedical engineers working in this rapidly expanding field, and can serve as supplementary reading for advanced graduate courses in biophysics and mathematical biology. The e-book incorporates experimental and computer animations illustrating various aspects of cell movement./div

An introductory textbook for people who have not programmed before. Covers basic MATLAB programming with emphasis on modeling and simulation of physical systems.

A fully updated tutorial on the basics of the Python programming language for science students Python is a computer programming language that has gained popularity throughout the sciences. This fully updated second edition of A Student's Guide to Python for Physical Modeling aims to help you, the student, teach yourself enough of the Python programming language to get started with physical modeling. You will learn how to install an open-source Python programming environment and use it to accomplish many common scientific computing tasks: importing, exporting, and visualizing data; numerical analysis; and simulation. No prior programming experience is assumed. This guide introduces a wide range of useful tools, including: Basic Python programming and scripting Numerical arrays Two- and three-dimensional graphics Animation Monte Carlo simulations Numerical methods, including solving ordinary differential equations Image processing Numerous code samples and exercises—with solutions—illustrate new ideas as they are introduced. This guide also includes supplemental online resources: code samples, data sets, tutorials, and more. This edition includes new material on symbolic calculations with SymPy, an introduction to Python libraries for data science and machine learning (pandas and sklearn), and a primer on Python classes and object-oriented programming. A new appendix also introduces command line tools and version control with Git.