The Nest of Engineers

This fully updated second edition provides an introduction to geotechnical earthquake engineering for first-year graduate students in geotechnical or earthquake engineering graduate programs with a level of detail that will also be useful for more advanced students as well as researchers and practitioners. It begins with an introduction to seismology and earthquake ground motions, then presents seismic hazard analysis and performance-based earthquake engineering (PBEE) principles. Dynamic soil properties pertinent to earthquake engineering applications are examined, both to facilitate understanding of soil response to seismic loads and to describe their practical measurement as part of site characterization. These topics are followed by site response and its analysis and soil–structure interaction. Ground failure in the form of soil liquefaction, cyclic softening, surface fault rupture, and seismically induced landslides are also addressed, and the book closes with a chapter on soil improvement and hazard mitigation. The first edition has been widely used around the world by geotechnical engineers as well as many seismologists and structural engineers.

The main text of this book and the four appendices: Cover fundamental concepts in applied seismology, geotechnical engineering, and structural dynamics + Contain numerous references for further reading, allowing for detailed exploration of background or more advanced material + Present worked example problems that illustrate the application of key concepts emphasized in the text + Include chapter summaries that emphasize the most important points + Present concepts of performance-based earthquake engineering with an emphasis on uncertainty and the types of probabilistic analyses needed to implement PBEE in practice + Present a broad, interdisciplinary narrative, drawing from the fields of seismology, geotechnical engineering, and structural engineering to facilitate holistic understanding of how geotechnical earthquake engineering is applied in seismic hazard and risk analyses and in seismic design

Contents: ASDIP Concrete - 5 modules of concrete design + ASDIP Foundation - 6 modules of footing design + ASDIP Retain - 5 modules of retaining wall design + ASDIP Steel - 6 modules of steel member design + ASDIP Wood - 4 modules of wood member design.

Machine Vibration And Settlement: Analyze machine block foundations for dynamic loading. Leverage wizard-based input for fast finite element analysis (FEA) solids model creation, various loading, and soil spring options. Detail and Document - Reinforced Concrete Drawings: STAAD Foundation Advanced generates drawings for plan, elevation, and sectional views with rebar marks. Schedule drawings provide a summary table for design results. General arrangement drawings include all the footings designed in the project, with grid lines and grid marks that help identify interference. Drawings can be exported to DXF or DWG formats. Generate Structural Design Documentation: Engineers can produce reports – summaries and detailed calculation sheets – for foundation types such as isolated, combined, pile caps, and foundations for plant equipment. For mat foundations, a powerful reporting system publishes the details of key analysis results, stability checks, detailed and summary reports for concrete design operations, bills of materials, general arrangements, and reinforcement detailing drawings available for ACI 318 codes.

Let’s see what you will learn: Stepwise regression + Non-linear regression + K nearest neighbor + Decision trees + Neural networks + Two-stage cluster analysis + Survival analysis.

What you will learn in this course? Perform advanced linear regression using predictive selection techniques + Perform any type of non-linear regression analysis + Prediction using the k nearest neighbor (KNN) technique. + Using binary trees (CART) for prediction (both regression and classification trees) + Using non-binary (CHAID) trees for prediction (both regression and classification trees) + Construction and training of a multilayer perceptron (MLP) + Construction and training of a radial basis neural network (RBF) + Perform two-way clustering analysis + Carrying out survival analysis using the Kaplan-Meier method + Performing survival analysis using Cox regression + Validation of prediction techniques (KNN, trees, neural networks) using validation set and cross-validation approach + Save a predictive analytics model and use it to predict future new data.