Expanding the Architectural Possibilities of Computational Design: A Revolutionary Guide to Smart, Efficient, and Sustainable Building Design

: The Rise of Computational Design in Architecture

Computational design is transforming the architectural landscape, offering unprecedented possibilities for innovation and optimization. This groundbreaking book unveils the latest advancements in computational design, empowering architects and designers to revolutionize the way they create buildings.

Inside Smartgeometry: Expanding the Architectural Possibilities of Computational Design (AD Smart)

4.3 out of 5

Language	:	English
File size	:	106810 KB
Text-to-Speech	:	Enabled
Enhanced typesetting	:	Enabled
X-Ray for textbooks	:	Enabled
Print length	:	272 pages
Lending	:	Enabled
Screen Reader	:	Supported

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The Power of Algorithms: Unleashing Creativity and Precision

Computational design leverages algorithms to generate complex designs that would be impossible to create manually. These algorithms can explore vast design spaces, identify optimal solutions, and generate unique and innovative forms.

Enhancing Building Performance: Optimizing Energy, Comfort, and Efficiency

Computational design enables architects to optimize building performance, resulting in structures that are more energy-efficient, comfortable, and environmentally friendly. Algorithms can analyze environmental conditions, user behavior, and material properties to generate designs that maximize daylighting, minimize energy consumption, and improve occupant comfort.

Towards Sustainable Architecture: Minimizing Environmental Impact

Computational design plays a crucial role in promoting sustainable architecture practices. By leveraging data and algorithms, architects can design buildings that minimize their environmental impact. Computational tools can analyze site conditions, material choices, and construction methods to reduce waste, emissions, and embodied energy.

Chapter Overview: A Comprehensive Guide to Computational Design Techniques

This comprehensive book covers a wide range of computational design techniques, offering practical insights and real-world examples:

Parametric Modeling: Defining Relationships for Adaptive Designs

Parametric modeling allows architects to define relationships between design parameters, creating adaptive designs that can respond to changing conditions. This chapter explores parametric modeling tools and techniques, including Grasshopper and Dynamo.

Generative Design: Exploring Design Alternatives and Optimizing Solutions

Generative design algorithms generate multiple design options, empowering architects to explore a wider range of possibilities. This chapter covers generative design software and workflows, including Rhino.Inside.Revit and DesignScript.

Machine Learning: Leveraging Data to Enhance Design Decisions

Machine learning algorithms can learn from data and make predictions, offering valuable insights for design decisions. This chapter explores machine learning techniques and their applications in architecture, including data analysis and optimization.

Digital Fabrication: Integrating Computational Design with Physical Construction

Digital fabrication technologies bridge the gap between computational design and physical construction, enabling architects to produce complex and customized building components. This chapter explores digital fabrication methods and their integration with computational design tools.

Case Studies: Inspiring Examples of Computational Design in Action

The book showcases numerous case studies that illustrate the transformative impact of computational design in architecture:

Burj Khalifa: Parametric Design for a Towering Landmark

This case study delves into the computational design techniques used to create the iconic Burj Khalifa, exploring how parametric modeling optimized the tower's structural performance and energy efficiency.

Mercedes-Benz Stadium: Generative Design for a Multi-Purpose Arena

This case study examines how generative design algorithms were employed to optimize the seating layout and roof structure of the Mercedes-Benz Stadium, resulting in an innovative and efficient design.

Deep Green House: Machine Learning for Sustainable Housing

This case study presents a computational design project that utilized machine learning to optimize the design of a sustainable house, reducing energy consumption and carbon emissions.

: The Future of Computational Design in Architecture

Computational design is poised to revolutionize the architectural profession, unlocking unprecedented possibilities for design innovation, performance optimization, and sustainability. This book empowers architects and designers to embrace these transformative technologies and shape the future of building design.

Inside Smartgeometry: Expanding the Architectural Possibilities of Computational Design (AD Smart)

4.3 out of 5

Language	:	English
File size	:	106810 KB
Text-to-Speech	:	Enabled
Enhanced typesetting	:	Enabled
X-Ray for textbooks	:	Enabled
Print length	:	272 pages
Lending	:	Enabled
Screen Reader	:	Supported

FREE