{"id":26456,"date":"2024-07-02T04:23:27","date_gmt":"2024-07-02T11:23:27","guid":{"rendered":"https:\/\/essential.construction\/news\/how-algorithmic-design-improves-collaboration-in-building-design\/"},"modified":"2024-07-02T04:23:29","modified_gmt":"2024-07-02T11:23:29","slug":"how-algorithmic-design-improves-collaboration-in-building-design","status":"publish","type":"post","link":"https:\/\/essential.construction\/news\/how-algorithmic-design-improves-collaboration-in-building-design\/","title":{"rendered":"How Algorithmic Design Improves Collaboration in Building Design"},"content":{"rendered":"

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

\n

Design, like everything else in a construction project, is a collaborative effort. Even with digital tools, collaboration across design disciplines is not yet optimal. An experimental project thus set out to test whether algorithmic design could help streamline the interaction between architects and structural engineers.<\/strong><\/p>\n

<\/p>\n

Design data
\noriginating from an architect is used in several engineering tools for
\nvisualization, analysis, and calculation. Ideally, changes in the architect\u2019s
\ndesign would propagate automatically across all the software. Unfortunately, the
\nprocess is in fact mostly manual. Hence, the design data is seldom, if ever, in
\nperfect sync on all systems.<\/p>\n

Two
\ncompanies, A-Insin\u00f6\u00f6rit and Geometria Architecture, joined forces to test
\nalgorithmic design collaboration to see if it could solve many of today\u2019s data
\nexchange problems. They found their solution could speed up the process,
\neliminate many errors, and alleviate the frustration of doing updates by hand.
\nIt could also have a positive effect on the final outcome of the project.<\/p>\n

\"Karjalainen
Petteri Karjalainen and Markus Wikar<\/figcaption><\/figure>\n

The Emerging Algorithmic
\nDesign<\/h2>\n

Petteri Karjalainen<\/strong> is a structural engineer at A-Insin\u00f6\u00f6rit.<\/a> He has been working over the last two years in the company on international projects, especially with industrial clients. He\u2019s also involved in developing an algorithmic design process, the theme of his recently completed master\u2019s thesis.<\/p>\n

\u201cWe have been speeding up our efforts in this field. Our company leadership sees potential in the practice and has encouraged me and our computational design team to apply more and more of these advanced methods to company\u2019s daily routines,\u201d says Karjalainen.<\/p>\n

Algorithmic
\nor computational design uses sets of instructions to perform certain tasks, for
\nexample, to generate a digital model of a structure. The instructions have parameters
\nthat generate variations of the same code. Algorithmic design is especially
\nsuited for architectural forms that are non-conventional and that can be
\nconstructed from repeatable elements.<\/p>\n

\"A\"A<\/a>
Design algorithm, example<\/figcaption><\/figure>\n

Experimental Architecture<\/h2>\n

Demanding,
\nnon-traditional forms are the bread and butter for Geometria
\nArchitecture<\/a>, the
\nbrainchild of two architects, Markus
\nWikar<\/strong> and Toni \u00d6sterlund<\/strong>. The
\ncompany is both a design practice and a consultant for architects, engineers,
\nand contractors. They cover parametric
\nmodeling,\u00a0algorithm-aided
\ndesign,\u00a0and\u00a0digital
\nfabrication.<\/p>\n

\u201cAt Lahdelma
\n& Mahlam\u00e4ki architects, my previous employer, I was in charge of the warped
\ngeometries of POLIN, the Museum of the History of Polish Jews in Warsaw,\u201d Wikar
\nexplains. \u201cToday, the company is our client.\u201d<\/p>\n

Algorithmic
\ndesign opens new perspectives for architectural expression. It makes the use of
\nnon-conventional forms feasible and cost-efficient to build. In addition, it gives
\ndesigners freedom to test and present dozens of alternative solutions, which in
\na traditional process would be very time-consuming or simply impossible to do.<\/p>\n

\"A\"A<\/a>
A FEM model<\/figcaption><\/figure>\n

Experimenting with
\nAlgorithms<\/h2>\n

In February
\n2018, A-Insin\u00f6\u00f6rit and Geometria Architects started experimenting with how to
\nuse algorithmic design for collaborations between architects and structural
\nengineers. The project got funding from the national KIRA-digi digitalization
\nprogram.<\/p>\n

They chose
\nto experiment with an imaginary building, specifically a swimming pool covered
\nwith a steel-structured curved roof. The aim was to test typical design tasks
\nand data exchange between the designers. The platform that the experimenters
\nused was Grasshopper, an extension of the Rhinoceros software.<\/p>\n

\"The\"The
The roof design process<\/figcaption><\/figure>\n

The
\narchitect designed several variations of the roof. The final design was formed
\nwith parable arcs, generated through so-called dynamic relaxation. This
\nresulted in an optimized structural system.<\/p>\n

After the
\narchitect had algorithmically created the curved roof and generated the line
\ngeometry, the structural engineer took over the data. They used
\nGrasshopper-RFEM Link; an extension developed by A-Insin\u00f6\u00f6rit. This allowed
\nthem to analyze and dimension the structural steel framework created in Grasshopper.
\nFurthermore, they used Trimble\u2019s Grasshopper-Tekla Live Link to build a BIM
\nmodel of the structure.<\/p>\n

Making Data Flow Between
\nSystems and Processes<\/h2>\n

The
\nexperimenters needed a way to exchange algorithmic data between the architect
\nand the structural engineer over the design life-cycle. They chose Speckle, a
\ncloud-based platform. It links the data intelligently between design parties
\nand models.<\/p>\n

Speckle allows
\ndesigners to share geometric data across several design models and to create an
\naggregated model from discrete parts. This means that when, for example, the
\narchitect changes the original geometry, the data is automatically updated
\nwherever it has been referenced. After the engineer has designed the structural
\nmodel, they, in turn, can provide the architect with the updated data.<\/p>\n

In its
\npurest form, all design data resides in the algorithms and the traditional BIM
\nmodel is generated only if and when it\u2019s needed. However, at the moment, a
\ncombination of algorithms and models seem to work best.<\/p>\n

\"Data\"Data<\/a>
Data transfer<\/figcaption><\/figure>\n

The Automated Future<\/h2>\n

\u201cImagine we
\nmodeled a double-curved shell exactly as it will be built. Say, someone then comes
\nup with a change that implies a one-degree change to every rod of the
\nstructure. With traditional methods, the change would imply a huge job, but with
\nan algorithm, it would be a breeze,\u201d Karjainen proclaims.<\/p>\n

Both Wikar
\nand Karjalainen believe that the use of algorithms and artificial intelligence represents
\na huge potential for the whole industry. They will not only enhance
\ncollaboration, but also free designers from routine tasks that in many cases
\nconstitute the larger part of their work. Furthermore, algorithmic design makes
\ndigital fabrication a reality. Building parts can be robotically manufactured
\nin factories and installed at the construction site.<\/p>\n

After the
\nKIRA-digi experiment, Geometria Architecture has continued to collaborate with
\nA-Insin\u00f6\u00f6rit around the Helsinki\u2013Tallinn tunnel project. It will be the world\u2019s
\nlongest undersea railway tunnel.<\/p>\n

\u201cWe have
\nbeen thinking through the data interfaces with the around 10 disciplines
\ninvolved. We\u2019re figuring out the smallest common design denominators or
\nparameters that need to be exchanged between parties,\u201d says Wikar. \u201cOur goal is
\nto allow the experts to focus on their core competence areas and not to have to
\nstruggle with software issues,\u201d he concludes.<\/p>\n

\"-\"\"-\"
An exterior view<\/figcaption><\/figure>\n

The project illustrations are courtesy of A-Insin\u00f6\u00f6rit and Geometria Architecture<\/em><\/p>\n

<\/div>\n