Hybrid Composite Precast Systems: Numerical Investigation to Construction focuses on the design and construction of novel composite precast frame systems that permit almost effortless erection and structural efficiency. The precast frame systems discussed in the book are similar to that of steel frames, but offer similar savings to concrete frames. The design of connections and detailed analysis of their structural behavior is discussed in detail. Fundamentals with regards to the post yield behavior of concrete and metal are also presented to illustrate how these two different materials are integrated together to remove individual material drawbacks. Readers are given a broad introduction to existing technologies that are then combined with a description of the construction methods the author proposes. This book will help the end users become familiar with the existing types of structural forms, not just the "Lego" type frame system that the author proposes. - Discusses how traditional construction methods can be replaced by innovative hybrid composite precast frame systems that provide rapid and effortless erection capabilities and structural efficiency - Contains several design examples using non-linear finite element analysis completed with Abaqus based-software - Contains new milestone inventions in construction that offer structural engineering solutions using a novel, modularized hybrid frame system - Provides information on structural testing that verifies the accuracy of the structural design

Artificial Neural Network-based Optimized Design of Reinforced Concrete Structures introduces AI-based Lagrange optimization techniques that can enable more rational engineering decisions for concrete structures while conforming to codes of practice. It shows how objective functions including cost, CO2 emissions, and structural weight of concrete structures are optimized either separately or simultaneously while satisfying constraining design conditions using an ANN-based Lagrange algorithm. Any design target can be adopted as an objective function. Many optimized design examples are verified by both conventional structural calculations and big datasets. Uniquely applies the new powerful tools of AI to concrete structural design and optimization Multi-objective functions of concrete structures optimized either separately or simultaneously Design requirements imposed by codes are automatically satisfied by constraining conditions Heavily illustrated in color with practical design examples The book suits undergraduate and graduate students who have an understanding of collegelevel calculus and will be especially beneficial to engineers and contractors who seek to optimize concrete structures.

This book introduces artificial neural network (ANN)-based Lagrange optimization techniques for a structural design of prestressed concrete structures based on Eurocode 2, and composite structures based on American Institute of Steel Construction and American Concrete Institute standards. The book provides robust design charts for prestressed concrete structures, which are challenging to achieve using conventional design methods. Using ANN-based design charts, the holistic design of a post-tensioned beam is performed to optimize design targets (objective functions), while calculating 21 forward outputs, in arbitrary sequences, from 21 forward inputs. Applies the powerful tools of ANN to the optimization of prestressed concrete structures and composite structures including columns and beams Multi-objective optimizations (MOO) of prestressed concrete beams are performed using an ANN-based Lagrange algorithm Offers a Pareto frontier using an ANN-based MOO for composite beams and composite columns sustaining multi-biaxial loads Heavily illustrated in color and with diverse practical design examples in line with EC2, ACI, and ASTM codes The book offers optimal solutions for structural designers and researchers, enabling readers to construct design charts to minimize their own design targets under various design requirements based on any design code.

Artificial Intelligence-Based Design of Reinforced Concrete Structures: Artificial Neural Networks for Engineering Applications is an essential reference resource for readers who want to learn how to perform artificial intelligence-based structural design. The book describes, in detail, the main concepts of ANNs and their application and use in civil and architectural engineering. It shows how neural networks can be established and implemented depending on the nature of a broad range of diverse engineering problems. The design examples include both civil and architectural engineering solutions, for both structural engineering and concrete structures. Those who have not had the opportunity to study or implement neural networks before will find this book very easy to follow. It covers the basic network theory and how to formulate and apply neural networks to real-world problems. Plenty of examples based on real engineering problems and solutions are included to help readers better understand important concepts. - Helps civil engineers understand the fundamentals of AI and ANNs and how to apply them in simple reinforced concrete design cases - Contains practical case study examples on the application of AI technology in structural engineer - Teaches readers how to apply ANNs as solutions for a broad range of engineering problems - Includes AI-based software [MATLAB], which will enable readers to verify AI-based examples

This book introduces an auto‐design‐based optimization for building frames using an artificial neural network (ANN)‐based Lagrange method and novel genetic algorithm (GA). The work of great mathematician Joseph‐Louis Lagrange and ANNs are merged to identify parameters that optimize structural frames of reinforced concrete, prestressed concrete, and steel frames subject to one or more design constraints. New features for enhancing conventional GA are also demonstrated to optimize structural frames. New features for optimizing multiple design targets of the building frames are highlighted, while design requirements imposed by codes are automatically satisfied. Chapters provide readers with an understanding of how both ANN‐based and novel GA‐based structural optimization can be implemented in holistically optimizing designated design targets for building structural frames, guiding readers toward more rational designs that is consistent with American Institute of Steel Construction (AISC) and American Concrete Institute (ACI) standards. ANN‐based holistic designs of multi‐story frames in general and reinforced concrete, prestressed concrete, and steel frames in particular, are introduced. This book suits structural engineers, architects, and graduate students in the field of building frame designs and is heavily illustrated with color figures and tables.

Displacement-Based Seismic Design of Structures is a book primarily directed towards practicing structural designers who are interested in applying performance-based concepts to seismic design. Since much of the material presented in the book has not been published elsewhere, it will also be of considerable interest to researchers, and to graduate and upper-level undergraduate students of earthquake engineering who wish to develop a deeper understanding of how design can be used to control seismic response. The design philosophy is based on determination of the optimum structural strength to achieve a given performance limit state, related to a defined level of damage, under a specified level of seismic intensity. Emphasis is also placed on how this strength is distributed through the structure. This takes two forms: methods of structural analysis and capacity design. It is shown that equilibrium considerations frequently lead to a more advantageous distribution of strength than that resulting from stiffness considerations. Capacity design considerations have been re-examined, and new and more realistic design approaches are presented to insure against undesirable modes of inelastic deformation. The book considers a wide range of structural types, including separate chapters on frame buildings, wall buildings, dual wall/frame buildings, masonry buildings, timber structures, bridges, structures with isolation or added damping devices, and wharves. These are preceded by introductory chapters discussing conceptual problems with current force-based design, seismic input for displacement-based design, fundamentals of direct displacement-based design, and analytical tools appropriate for displacement-based design. The final two chapters adapt the principles of displacement-based seismic design to assessment of existing structures, and present the previously developed design information in the form of a draft building code. The text is illustrated by copious worked design examples (39 in all), and analysis aids are provided in the form of a CD containing three computer programs covering moment-curvature analysis (Cumbia), linear-element-based inelastic time-history analysis (Ruaumoko), and a general fibre-element dynamic analysis program (SeismoStruct). The design procedure developed in this book is based on a secant-stiffness (rather than initial stiffness) representation of structural response, using a level of damping equivalent to the combined effects of elastic and hysteretic damping. The approach has been fully verified by extensive inelastic time history analyses, which are extensively reported in the text. The design method is extremely simple to apply, and very successful in providing dependable and predictable seismic response. Authors Bios M.J.N.Priestley Nigel Priestley is Professor Emeritus of the University of California San Diego, and co-Director of the Centre of Research and Graduate Studies in Earthquake Engineering and Engineering Seismology (ROSE School), Istituto Universitario di Studi Superiori (IUSS), Pavia, Italy. He has published more than 450 papers, mainly on earthquake engineering, and received numerous awards for his research. He holds honorary doctorates from ETH, Zurich, and Cujo, Argentina. He is co-author of two previous seismic design books “Seismic Design of Concrete and Masonry Buildings” and “Seismic Design and Retrofit of Bridges”, that are considered standard texts on the subjects. G.M.Calvi Michele Calvi is Professor of the University of Pavia and Director of the Centre of Research and Graduate Studies in Earthquake Engineering and Engineering Seismology (ROSE School), Istituto Universitario di Studi Superiori (IUSS) of Pavia. He has published more than 200 papers and is co-author of the book “Seismic Design and Retrofit of Bridges”, that is considered a standard text on the subject, has been involved in important construction projects worldwide, such as the Rion Bridge in Greece and the upgrading of the Bolu Viaduct in Turkey, and is coordinating several international research projects. M.J.Kowalsky Mervyn Kowalsky is Associate Professor of Structural Engineering in the Department of Civil, Construction, and Environmental Engineering at North Carolina State University and a member of the faculty of the ROSE School. His research, which has largely focused on the seismic behaviour of structures, has been supported by the National Science Foundation, the North Carolina and Alaska Departments of Transportation, and several industrial organizations. He is a registered Professional Engineer in North Carolina and an active member of several national and international committees on Performance-Based Seismic Design.