Geo.Engineerings

Indrajit Chowdhury, Shambhu P. Dasgupta ... 882 pages - Publisher: CRC Press; (December, 2008) ... Language: English - ISBN-10: 0415471451 - ISBN-13: 978-0415471459.

Designed to provide engineers with quick access to current and practical information on the dynamics of structure and foundation, this unique work, consisting of two separately available volumes, serves as a complete reference, especially for those involved with earthquake or dynamic analysis, or the design of machine foundations in the oil, gas, and energy sector. This first volume deals with theories and formulations, covering the full range of topics involved and dynamics of structure and foundation. It specifically focuses on a unified approach in dealing with dynamic soul-structure interaction and geotechnical considerations for dynamic soil-structure interaction. The authors present new insights and theories, such as the computation of Rayleigh damping for structures with a large number of degrees of freedom, and the dynamic analysis of Hammer foundations, considering non-classical soil damping.

In a clear style, this well-illustrated column addresses detailed topics, grouped in the following major themes: Elasticity and numerical methods in engineering + Lumped parameter vibration + Soil-structure systems under static load + Structural and soil dynamics. This reference and design guide is intended for academics and professionals in civil and structural engineering involved with earthquake or dynamic analysis or the design of machine foundations. In combination with the Applications book (volume 2), it could be used as course material for advanced university and professional education in structural dynamics, soil dynamics, analysis and design of machined foundations, and earthquake engineering.

Machine learning has gained tremendous popularity for its powerful and fast predictions with large datasets. However, the true forces behind its powerful output are the complex algorithms involving substantial statistical analysis that churn large datasets and generate substantial insight. This second edition of Machine Learning Algorithms walks you through prominent development outcomes that have taken place relating to machine learning algorithms, which constitute major contributions to the machine learning process and help you to strengthen and master statistical interpretation across the areas of supervised, semi-supervised, and reinforcement learning. Once the core concepts of an algorithm have been covered, you’ll explore real-world examples based on the most diffused libraries, such as scikit-learn, NLTK, TensorFlow, and Keras. You will discover new topics such as principal component analysis (PCA), independent component analysis (ICA), Bayesian regression, discriminant analysis, advanced clustering, and gaussian mixture.

By the end of this book, you will have studied machine learning algorithms and be able to put them into production to make your machine learning applications more innovative. What you will learn: Study feature selection and the feature engineering process + Assess performance and error trade-offs for linear regression + Build a data model and understand how it works by using different types of algorithm + Learn to tune the parameters of Support Vector Machines (SVM) + Explore the concept of natural language processing (NLP) and recommendation systems + Create a machine learning architecture from scratch. Who this book is for: Machine Learning Algorithms is for you if you are a machine learning engineer, data engineer, or junior data scientist who wants to advance in the field of predictive analytics and machine learning. Familiarity with R and Python will be an added advantage for getting the best from this book.

Employ the essential and hands-on tools and functions of MATLAB's ordinary differential equation (ODE) and partial differential equation (PDE) packages, which are explained and demonstrated via interactive examples and case studies. This book contains dozens of simulations and solved problems via m-files/scripts and Simulink models which help you to learn programming and modeling of more difficult, complex problems that involve the use of ODEs and PDEs. You’ll become efficient with many of the built-in tools and functions of MATLAB/Simulink while solving more complex engineering and scientific computing problems that require and use differential equations. Practical MATLAB Modeling with Simulink explains various practical issues of programming and modelling.

After reading and using this book, you'll be proficient at using MATLAB and applying the source code from the book's examples as templates for your own projects in data science or engineering.

What You Will Learn: Model complex problems using MATLAB and Simulink + Gain the programming and modeling essentials of MATLAB using ODEs and PDEs + Use numerical methods to solve 1st and 2nd order ODEs + Solve stiff, higher order, coupled, and implicit ODEs + Employ numerical methods to solve 1st and 2nd order linear PDEs + Solve stiff, higher order, coupled, and implicit PDEs. Who This Book Is For: Engineers, programmers, data scientists, and students majoring in engineering, applied/industrial math, data science, and scientific computing. This book continues where Apress' Beginning MATLAB and Simulink leaves off.

This single-volume thoroughly summarizes advances in the past several decades and emerging challenges in fundamental research in geotechnical engineering. These fundamental research frontiers are critically reviewed and described in details in lights of four grand challenges our society faces: climate adaptation, urban sustainability, energy and material resources, and global water resources. The specific areas critically reviewed, carefully examined, and envisioned are: sensing and measurement, soil properties and their physics roots, multiscale and multiphysics processes in soil, geochemical processes for resilient and sustainable geosystems, biological processes in geotechnics, unsaturated soil mechanics, coupled flow processes in soil, thermal processes in geotechnical engineering, and rock mechanics in the 21st century.

Ken W. Day, James Aldred, Barry Hudson ... 349 pages - Publisher: CRC Press; 4th edition (October, 2013) ... Language: English - ISBN-10: 0415504996 - ISBN-13: 978-0415504997.

The nature of concrete is rapidly changing, and with it, there are rising concerns. Thoroughly revised and updated, this fourth edition of Concrete Mix Design, Quality Control and Specification addresses current industry practices that provide inadequate durability and fail to eliminate problems with underperforming new concrete and defective testing. Many specifications now require additional criteria in an attempt to improve durability or other properties. This book discusses the trend towards adding performance requirements to existing prescriptive specifications. It also explores the matter of prescription versus performance specification and especially the specification of non-strength-related performance such as durability. What’s new in the Fourth Edition: Examines water-to-cement ratio as a declining criterion of quality and durability + Discusses the diminishing availability of suitable natural sands and growing industry concerns regarding the environmental impact of their use + Considers advances in concrete admixtures and their ever-increasing use + Advocates reliability of testing as a vital feature of the shift from prescriptive to performance specifications + Addresses cement replacement materials as they relate to greenhouse gas and sustainability.  Concrete Mix Design, Quality Control and Specification explores producing, designing, controlling, or specifying concrete, and addresses issues related with sustainability and the impact of new concrete materials such as ready mixed geopolymers, magnesium oxide, and calcium carbonate. The text is an ideal resource for concrete technologists, producers and specifiers, and contractors on large projects.