Artificial Neural Network-based Designs of Prestressed Concrete and Composite Structures - Softcover
Synopsis
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.
"synopsis" may belong to another edition of this title.
About the Author
Won‐Kee Hong is a Professor of Architectural Engineering at Kyung Hee University, South Korea. He has more than 35 years of professional experience in structural and construction engineering, having worked for Englekirk and Hart, USA; Nihhon Sekkei, Japan; and Samsung Engineering and Construction, Korea. He is the author of Artificial Neural Network-based Optimized Design of Reinforced Concrete Structures, also published by CRC Press.
"About this title" may belong to another edition of this title.
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Artificial Neural Network-based Designs of Prestressed Concrete and Composite Structures (Paperback)
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Paperback. Condition: new. Paperback. 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 beamsMulti-objective optimizations (MOO) of prestressed concrete beams are performed using an ANN-based Lagrange algorithmOffers a Pareto frontier using an ANN-based MOO for composite beams and composite columns sustaining multi-biaxial loadsHeavily illustrated in color and with diverse practical design examples in line with EC2, ACI, and ASTM codesThe 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. This introduces artificial neural network-based Lagrange optimization techniques for structural design in prestressed concrete based on Eurocode 2 and composite structures based on American Institute of Steel Construction and American Concrete Institute standards. ANN-based design charts show how to use the Lagrange multiplier method. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781032408095
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