Parametric Analysis, Generative Design and Machine Learning in Architectural Practice

Häftad, Engelska, 2026

530 kr

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Beskrivning

Let these cutting-edge tools revolutionize your architectural problem-solving Recent technological advances, including rapid development of high-performance computing power, have produced computational tools for architects and designers that are swiftly revolutionizing the field. Two of these tools, parametric analysis and generative design, can be used together to model complex problems and test solutions with extraordinary speed and efficiency. The next generation of architects and designers will bring these tools to bear in a transformed professional landscape. Parametric Analysis, Generative Design and Machine Learning in Architectural Practice offers a detailed introduction to these tools and their applications. Balancing theory and practice, it is replete with useful examples and provides algorithms for three different architectural scales: urban design, building design, and interior design. The book also presents a foundational discussion on machine learning in architectural practice, along with examples of machine learning applications for energy analysis and solar analysis. It is a must-own for architects looking to leverage an unprecedented level of computational power. The book also includes: Detailed guidelines for building performance simulation for energy analysis and daylight analysisAlgorithms for scales from interiors to buildings to entire cityscapesDiscussion of how to implement machine learning in order to solve complex problemsParametric Analysis, Generative Design and Machine Learning in Architectural Practice is ideal for professionals and students at every level looking to diversify their architectural toolkit.

Produktinformation

Utgivningsdatum:2026-09-30
Vikt:666 g
Format:Häftad
Språk:Engelska
Serie:Practical Revolutions
Antal sidor:288
Förlag:John Wiley & Sons Inc
ISBN:9781394197996

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Mer om författaren

Dr. Victor Okhoya holds a Doctor of Design in Architecture from Carnegie Mellon University with a specialty in Computational Design, and has worked with architectural computational technology for more than twenty years. He has published widely on architectural computation technology and related subjects, has held leadership roles in digital design technology at leading architectural practices, and has trained hundreds of industry professionals on the use of digital design tools. Marcelo Bernal, Ph.D., holds a doctoral degree in Architecture from the Georgia Institute of Technology with a specialty in Computational Design, and has more than two decades’ experience in research and architectural practice. He has held professorial positions at the Universidad Técnica Federico Santa María (UTFSM), Chile, has published widely on architectural design and related subjects, and is the Past President of the Iberoamerican Society of Digital Graphics, SIGraDi.

Innehållsförteckning

Preface xiAcknowledgments xvPart One: Back ground and Definitions 1Chapter 1COMPUTER-AIDED DESIGN AND BUILDING INFORMATION MODELING 3Computer Aided Design 5Building Information Modeling 9Chapter 2COMPUTATIONAL DESIGN AND PARAMETRIC DESIGN 19Computational Design 19Parametric Design 30Chapter 3WHAT IS PARAMETRIC DESIGN? 41Definition of Parametric Design 41The Need for Parametric Design 47Project Case: Parametric Analysis 51Project Case: Generative Design 60Part Two: Parametric Analysis 73Chapter 4METHODS OF PARAMETRIC ANALYSIS 75Performing Energy Simulations 75Performing Daylight Simulations 82Daylight Analysis Process 83Performing Parametric Analysis 90Evaluating Parametric Analysis 97Chapter 5PARAMETRIC ANALYSIS FOR ENERGY AND DAYLIGHT PERFORMANCE 105Energy Analysis Project Case: Hotel Residence 105Project Case: Student Housing 112Project Case: Student Residence 120Project Case: High School Building 132Part Three: Generative Design 139Chapter 6METHODS OF GENERATIVE DESIGN 141Space Partitioning Algorithms 146Site Subdivision Algorithms 155Form Making Algorithms 160Chapter 7GENERATIVE DESIGN AT THE URBAN DESIGN SCALE 171Project Case: Business Park 172Project Case: Mixed Housing 179Chapter 8GENERATIVE DESIGN AT THE BUILDING SCALE AND INTERIOR DESIGN SCALE 195Generative Design at the Building Scale 195Generative Design at the Interior Design Scale 206Part Four: Machine L earning 219Chapter 9MACHINE LEARNING FOR ENERGY ANALYSIS 221Machine Learning Algorithms 223Project Case: Residential Tower 230Chapter 10DEEP LEARNING FOR SOLAR ANALYSIS 239Types of Deep Learning Algorithm 241Generative Adversarial Networks 246Project Case: Urban Solar 252Bibliography 257Index 259