{"id":25906,"date":"2024-05-23T02:50:41","date_gmt":"2024-05-23T09:50:41","guid":{"rendered":"https:\/\/essential.construction\/news\/the-living-makes-buildings-better-with-computational-design\/"},"modified":"2024-05-23T02:50:44","modified_gmt":"2024-05-23T09:50:44","slug":"the-living-makes-buildings-better-with-computational-design","status":"publish","type":"post","link":"https:\/\/essential.construction\/news\/the-living-makes-buildings-better-with-computational-design\/","title":{"rendered":"The Living Makes Buildings Better with Computational Design"},"content":{"rendered":"

\"-\"<\/a>
\n<\/p>\n

\n

The AEC
\nindustry has a responsibility and mandate when it comes to addressing significant
\nglobal challenges in the sector and improving operational practice. Professionals
\nsuch as Lorenzo Villaggi, Senior Research Scientist at The Living, believe that
\nnew design technologies hold the key to better-performing built environments.<\/strong><\/p>\n

<\/p>\n

\n
\"-\"
Lorenzo Villaggi<\/figcaption><\/figure>\n<\/div>\n

\u201cAlthough I\u2019m trained as an architect, I\u2019ve always had an interest in how technology can
\ninteract with and have an impact on design processes,\u201d says Lorenzo. \u201cI\u2019ve
\ndeveloped a familiarity with advanced computational tools and eventually
\ndeveloped my own.\u201d<\/p>\n

These computational tools are primarily designed to assist with the generation of
\ndesign options and improve performance analysis. They range from small systems that
\nhelp users design faster, all the way to elaborate software that can perform
\ncomplex, mission-critical tasks.<\/p>\n

Lorenzo\u2019s employer, The Living<\/a>, is the perfect place to pursue computational design for the built environment. The studio combines research and practice with the exploration of new ideas and technologies through practical prototyping.<\/p>\n

An Innovative Research
\nStudio<\/h2>\n

The current principal, David Benjamin, co-founded The Living back in 2006. The company soon
\nbecame known for its innovative use of organic structures to create architectural
\nforms. A quick look through their project portfolio reveals a diverse range of
\namazing projects; integrating advanced technologies with new types of living
\nmaterials.<\/p>\n

This includes The Living\u2019s award-winning pavilion of bricks made from cornstalks and
\nmushrooms, their use of generative design to optimize an Autodesk office in
\nToronto, and 3D-printing a bionic partition for airplanes.<\/p>\n

In 2014, Autodesk acquired the company, and The Living became integrated as a core part
\nof Autodesk Research. Since then, the company has provided help in testing,
\nanalyzing, and showcasing possible futures for the AEC industry.<\/p>\n

Research with a Practical
\nPurpose<\/h2>\n

Instead of producing speculative work, The Living primarily applies new technologies to real world
\nprojects for businesses. This, according to Lorenzo, distinguishes them from
\nother research groups in the field.<\/p>\n

\u201cIt\u2019s a pretty unique position, where we lie both in the world of research and in the
\nworld of practice,\u201d Lorenzo says. \u201cThese two sides are highly interwoven. All
\nprojects are guided by research endeavors, but, at the same time, the projects
\nguide the research.\u201d<\/p>\n

Most of their eight person team are architects with a specialty in computation. This allows the
\ncomputer scientist in the group to push forward with the most advanced
\ncomputation-related tasks and allow other team members to pitch in as required.
\nAs a part of Autodesk Research, The Living leverages expertise from other teams
\nin domains such as AI, robotics, sensors, and monitoring of build operations.<\/p>\n

This means that The Living have directly and tangibly contributed to Autodesk\u2019s project
\ndevelopment, something that can be a rarity for research groups. For example,
\nthe generative design and optimization engine for Dynamo and Revit called
\nRefinery is based on processes built at The Living.<\/p>\n

\"-\"\"-\"
Generative design data analysis and trade-off navigation\u00a0(Van Wijnen project)<\/em><\/figcaption><\/figure>\n

Recent Projects<\/h2>\n

When it comes to current-day practice, Lorenzo mentions two recent examples of their
\nwork. One is with a Dutch construction corporation, Van Wijnen. Working in close
\ncollaboration with the company, The Living created a framework that applies
\ngenerative design at a city-wide scale.<\/p>\n

The project was deployed in the development of a net-zero energy affordable housing
\nneighborhood. This involved the integration of local building codes, developer
\nrequirements, and adhering to stakeholder criteria for the project. Among these
\nspecifications was a need for financial performance, solar energy gain, and
\nheterogeneity of layout variations.<\/p>\n

Geometry system logic and steps for residential neighborhood layouts (Van Wijnen project)<\/em><\/figcaption><\/figure>\n

\u201cOften, the criteria are very complex. Generative design and automation help users navigate
\nthe complex tradeoffs and identify solutions that are very novel, but also
\nhigh-performing,\u201d Lorenzo explains.<\/p>\n

Another ongoing project involves collaboration with one of Japan\u2019s largest development and
\nconstruction firms, Daiwa House. The company designs and develops rental
\nhousing units and The Living provides their business with a dedicated digital sales
\ntool. Using this software, salespeople with little design experience can quickly
\ncreate rental housing solutions that are fully code compliant and provide a
\nhigh ROI.<\/p>\n

Reversing the Design
\nProcess<\/h2>\n

Lorenzo is not particularly interested in traditional approaches to design automation,
\nwhich do little more than \u2018speed up\u2019 certain tasks. Instead, he and his
\nteam-mates see greater potential in radically changing process approaches. This
\nallows them to unlock new opportunities with a process known as \u2018generative
\ndesign\u2019.<\/p>\n

\u201cInstead of starting from a formal approach to the project by drawing, sketching, or
\n3D-modeling something, we reverse the design process. We start first by the
\nconstraints and the main goals of the project and then task the computer in
\nidentifying solutions that are high-performing and compliant with the
\nconstraints.\u201d<\/p>\n

Lorenzo defines generative design as a framework that integrates human and artificial
\nintelligence to create novel solutions to complex problems. It is made up from three
\ndistinct components:<\/p>\n

    \n
  1. The creation of a vast array of
    \npossible solutions: the \u2018design space\u2019.<\/li>\n
  2. Agreeing on a set of analysis
    \nalgorithms and\/or key goals.<\/li>\n
  3. The pursuit and application of optimization.<\/li>\n<\/ol>\n

    In each case, \u2018optimization\u2019 is enacted by any type of search algorithm able to
    \nnavigate the space of possible solutions, identify scores for each, and use these
    \nto evolve and prove the performance capacity of potential solutions \u2013 iterating
    \ngeneration after generation.<\/p>\n

    Continuous exploration of design solutions (Daiwa House project)<\/em><\/figcaption><\/figure>\n

    Tackling AEC Challenges
    \nwith Technology<\/h2>\n

    When it comes to issues facing AEC, population growth is an undeniable concern \u2013 with
    \n11.2 billion individuals expected to exist by 2100. Carbon emissions from the
    \nbuilding industry \u2013 clocking in at almost 40% \u2013 are also among the key factors
    \nshaping the future of construction. It is therefore imperative that the AEC
    \nindustry takes quantitative and qualitative actions to address these
    \nchallenges.<\/p>\n

    An increasing population will demand more housing and related resources and, with new
    \ntechnologies and tools, designers are empowered to create a wider range of
    \nimproved solutions. These start by including elements such as carbon modeling,
    \nsustainability metrics and goals, and financial and material reduction goals throughout
    \nthe design process. However, juggling these variables simultaneously can be
    \nextremely difficult, as Lorenzo adds.<\/p>\n

    \u201cThe process starts to become so complex that a human alone may not be able to
    \nmanage it. That\u2019s why we need these technologies and frameworks, like
    \ngenerative design, to help navigate the tradeoffs,\u201d Lorenzo maintains. \u201cThey
    \nallow us to bring to the table solutions that are better for the end users,
    \nbuilders, and the environment.\u201d<\/p>\n

    Currently, Lorenzo and his colleagues are driven by the question: what makes good
    \nbuildings, today? While the inclusion of environmental metrics in automated
    \ndesign processes helps answer this question, he argues that the next step is
    \nsetting standards for measuring embodied energy in construction.<\/p>\n

    \u201cI\u2019m looking forward to having a set of tools that are reliable, that can connect
    \nwith building certification programs, for example, and provide feedback both to
    \nautomated processes and humans to better understand what is happening in the
    \nprocess,\u201d Lorenzo envisions.<\/p>\n

    You can connect with Lorenzo on LinkedIn<\/a>.<\/em><\/p>\n

    Title image: Design space analysis\u00a0(Van Wijnen project)<\/em><\/p>\n

    The images and videos are courtesy of The Living<\/em><\/p>\n

    <\/div>\n