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Advancing Computational Building Design 2018 Retrospective – Notes from the Chair

Randy Deutsch, AIAassociate director for graduate studies at the University of Illinois Urbana-Champaign’s School of Architecture also shares his thoughts on the conference and the future of the computational building design community.

One of my first impressions of this conference is that besides a few notables, the participants and speakers were not the usual faces one might see at other industry-related events. This is important, as this still nascent group continues to define itself, asking questions about where this all is heading, and whether this group indeed forms a community of practice. This event had it all, from uplifting talks to out-there talks that no one was expecting to presentations that completely delivered on a promise of details and cases. I learned a lot from these presentations, but also from the breakout sessions – especially the conversations, which, for me in two cases, lasted well into the night. I really couldn’t ask for more from a conference. This was the real deal, entirely worth the time, investment, and my second flight delay out of La Guardia in a month due to weather. I’d go again in a heartbeat.

What I experienced at Advancing Computational Building Design 2018 constitutes a community of design technology specialists, who not only are working toward the mastery of these tools and work processes for building design – and the name of the event implies – but in some cases, more broadly, including computational urbanism among other areas of practice. This was quite interesting to learn, and to witness firsthand. I was not able to make last year’s inaugural event in San Francisco, but from what I have heard from others in the relatively short span of a year, this group has developed its capabilities, producing interesting, innovative, new work that is at once compelling and performative, and – when word gets out to the rest of the industry – influential. There was much to learn during our time together, and I don’t think I have ever been more curious to see what this group, their colleagues, and its followers continue to develop in the year ahead. I am absolutely attending next year’s event – no matter where it is held – and look forward to seeing computational designers and design technologists continue to make a name and a place for themselves, in their teams, firms, and the profession and industry.

 

Tackling Implementation Head-On
With the growing complexity of this field of practice, I feel challenged and inspired to begin thinking about and capturing the ever-changing design vocabulary within computational domains of knowledge. Computation is no longer a question of should, or whether it is possible. Understanding the nuances of this vocabulary will be key to success as we lead our clients into these pioneering adventures in sustainable design. And finding a common language is critical for implementation to take hold.

This conference continues to inspire change for those who attend. What we do with that inspiration – which I’m taking as a professional challenge – will determine the speed of change within our industry, and how quickly we embrace computational design in an ever-changing world.

Olivia Pearson, Studio Director of Architecture, GHDWOODHEAD creativespaces

The iteration of design – Future architecture lies in embracing computational design

How many numbers of design iterations can you come up with? 5 – 10? 100 – 1000? 100,000?

Implementing advanced technology within organisational structures is an age-old conundrum. One GHD is addressing by creating GHD Digital. GHD recognises the onset of the Fourth Industrial Revolution. This blurs the lines between biological, physical and digital innovation. Some people embrace technology with open arms, while others avoid it.

Olivia Pearson, GHDWoodhead creative spaces Studio Director of National Architecture NZ, discusses some of the topics around the upcoming panel topic at the Computational building design conference in New York, through a series of questions and answers

Q: What are the benefits of computational design for companies?

My understanding of computational design is it is the application of technologies. This enables the application of generative computer design to the design process. It is like BIM in that you can create options quicker using a computer than you can with hand sketching. This generates a much large number of options and scenarios than designers can think of. It assists them to design, produce and modify complex forms of design.

We can create more iterations and more accurate designs faster using computer software. No longer do you have to do manual calculations, the software does it for you. The process is outcome driven with designers telling the computer what to do, not how to do it. Using computation design presents designers with an almost infinite number of solutions to choose from. Broadly, benefits are time and money savings for a firm and better solutions for clients. Other benefits include:

  • designs/solutions that are not constrained by the imagination/creativity of the designer
  • automating repetitive tasks during the design process
  • rapid prototyping to explore all design possibilities quickly
  • rapid iterations to test and refine designs
  • evaluating design concepts for teams to make informed decision early in the decision-making.

Q: What are the different organisational structures currently being implemented?

Over the years I’ve seen a couple of different approaches to organisational structures. Currently I believe there are two types:

  1. Type 1. Type 1 is the architecture firm where they embed a mix of specialist staff within teams. This approach can result in upskilling more staff. The danger is they can become so delivery focused that tools and software does not get developed.
  2. Type 2. Type 2 is the firm that creates a technology wing that has all the experts embedded within the group. The risk is the wing keeps the expertise locked within its own department and few designers upskill as they have no insight into the creation of tools or how to modify them. What the group offers depends on the aims of the firm. There are three main offerings:
    1. An internal focus where they only create tools for the firm they work for.
    2. Focused externally where the firm only offers tools to external clients with no focus on their internal clients.
    3. A mix of external and internal, where the focus is more balanced.

Both types of firms have their challenges. I believe there needs to be a middle ground. Meaning, upskilling staff and encouraging them to contribute to creating tools even if they are not in the expert specialised team. This allows a true collaboration between industry people and software developers while staying project and client focused.

GHD is a Type 2 organisation with its new arm GHD Digital. Where it is different from other firms is its focus is both internal and external. This creates new opportunities for our people as well as our customers.

Q: Who is doing this?

Most firms presenting at the conference and a range of others attending the conference. Some of the world’s most famous architects have used computational design for years. Zaha, Norman Foster and Grimshaw, for example, use it due to the complexity of their designs. I think while their designs are outstanding, computational design contributes to their success.

There are other small pockets of firms and architects within firms using computational design in the US, Europe and UK. But, it is still not a commonly used tool.

Q: What are the roles and responsibilities in adopting computational design?

I am not sure yet what the roles and responsibilities need to be for adopting computational design. Industry created multiple layers of roles for BIM implementation. Doing this, so far, has introduced more costs without realising the success expected. But, it is still evolving.

We definitely need our specialists that can help produce the tools required to advance the use of this technology. GHD Digital will provide these specialists.

While firms talk about implementing the software and solutions, it rarely gets past management level. GHD Digital aims to change this mindset. Computational design needs to be part of the everyday toolset used by team members at every level. Its success rests with project leads encouraging and demanding its use on projects. Graduates within firms also need to be able to use the software and promote its use on projects

Barriers can be the age of staff who can see learning something new difficult. There are two types of these people. Those who want to ignore technology, and those who allow younger staff to embrace and learn how to use new technology.

I think the main role and responsibility of a firm is enabling the use of computational design.

Something to consider. How do you think computational design fits into the roles and responsibilities of the company you work for?

Q: What does the workforce of the future need to look like?

The workforce of the future looks very different to what it is today. Designers will need to become a lot more computer literate.

Because I have a flair for technology, I ended up focusing on wanting the modern design tools so I could use them to design. Then realised I needed to learn how to code and understand the concepts of writing programs.

This crossover into programming will become more common. Recently I interviewed a graduate. He knew how to write two different computer languages as well as how to use all the other software we use for design.

Q: What are the enabling conditions that allow one to become involved in this?

It is about creating organisational structures that ensure the roles and responsibilities allow people to work with modern technology or computational design tools. Firms and project leaders need to allow staff to explore computation design on the job. People need the time to train and upskill.

A challenge with computational design is it is front end loaded. While programs or solutions are being built it is weeks before something tangible is seen. This needs to be overcome by generating awareness of this different design approach.

Organisations need champions, or influencers, who embrace and promote a change of culture from within. How successful they are will depend on how good they are at influencing others and the respect staff have for them.

Q: How you do you create awareness?

While champions can help to change organisational culture, I find presentations are a great way to communicate. I have used presentations in the past to demonstrate the application of BIM to projects. This is similar to how I see we can communicate the use of computational design in future.

But, presentations need to use real life case studies that show the benefits of the tools. Project examples and how the technology applied created benefits for our clients and users gives people real insight. We need to talk about how we use computational design. This shows its advantages in ways people can grasp in a tangible way.

Q: Why the decision to create GHD Digital

GHD is a forward thinking global organisation that transforms itself to future proof its operations. The creation of GHD Digital is an example of the organisation’s philosophy.

The digital era offers huge growth opportunities. And we understand the consequences of not transforming quickly enough. Digital transformation is necessary for the organisation to stay relevant.

Our goal is to find new ways to engage with customers and our people using our understanding of existing and new technologies. GHD aims to continue to deliver unprecedented value for our clients.

This is an exciting time for GHD Digital as we explore new opportunities to upskill our people to create new opportunities. If we do not digitally transform our business we risk becoming uncompetitive.

This is an opportunity. If we embrace it we can be more successful than ever before. It is an opportunity to outshine all our past successes. If we stand back, we risk being taken over by everyone else.

Find out more about GHD’s approach to digital strategy development and transformation through GHD Digital.

#design #computational #digitaledge

Interview: Zak Kostura, Associate Structural Engineer, ARUP

1.Q) Computation seems integral to the work that ARUP do, and a critical differentiator to other design firms. Could you give a couple of examples of how ARUP work differently to integrate computation into every day work?  Rather than mandate specific approaches to design and management, we try to foster a culture of adoption of new technologies.  We regularly have internal seminars intended to share new technologies and project-specific case studies to engineers from a wide range of backgrounds and disciplines.  We offer internal grant funding for small R&D projects that are carried out by interested staff members based on needs they observe from project work.  We have numerous platforms for code sharing and custom application distribution.  We share knowledge on internal Wikis and media spaces that enable staff to post video recordings of techniques for others to watch.

 

  1. Q) What do you see as the biggest challenge facing the wider adoption of computational design? Why isn’t it already as widely adopted as BIM? Depends on what you mean by “computational design”. From an engineering standpoint this has evolved to mean the use of computational software to achieve higher quality designs more efficiently and expeditiously.  From that end, I would say that computational design is in fact more advanced than BIM, which while widely adopted is used in very conservative ways on projects (e.g. as a 3D visualization model with little to no added metadata attached to models, and still complemented by conventional 2D drawings that take priority in the event of conflicts between the two).

 

  1. Q) In your experience, what is the most common mistake that design firms make when leveraging computation for the first time? The same mistake many existing firms (including Arup) continue to – they treat the computation as the end product rather than the building project. All computational work, like hand calculations before it, are a means to an end, which is a well designed building.

 

  1. Q) What is the most convincing example you have to prove the value and ROI in computational design? Do you have any projects where design optimization, cost, speed or some other metrics has been measurably improved? I would say the use of software development/deployment, databases and parametrics to design the Mexico City Airport roof.

 

  1. Q) Do you believe the AEC industry can benefit from collaboration as a way to enable mass adoption of computation? Are there any examples of successful collaborative projects or platforms where designers have shared tools, techniques or training methods? Sharing successes and lessons learned is always a good thing, provided those who share are honest and candid about what worked and what didn’t work. But adoption of new technologies shouldn’t be done for the sake of being “cutting edge”.  Designers should look critically at what is wrong with the AEC industry (or what can be improved within it) and how new technologies can help with that.

 

  1. Q) The advancement of computation is clearly linked to technology, such as the development of design software. What do you think is the next big technological leap that we should be planning for? What do you envisage computational design to have the potential to achieve? I think it’s the direct interaction with databases to more efficiently capture and convey data on a project. Revit and other BIM tools simply visualize databases in a way that’s palatable to users who are intimidated by databases themselves.  The more we are able to interact directly with back-end infrastructure (e.g. the technologies that power the pretty front ends), the more effectively we’ll be able to leverage computation.

 

  1. Q) What are you hoping to achieve from attending and presenting at Advancing Computational Building Design 2017? Share my lessons learned, and hear from others how they are using computational design in a fruitful way.

Stantec Computational Experts: Alyssa Haas, Masha Pekurovsky, Achintya Bhat

Educate, Engage & Deliver –

Demystifying Computational Design Culture

Masha

Computational design methodologies offer a range of solutions to otherwise challenging and time-consuming design problems. Promoting computational design culture in AEC is imperative to advancing ideas and evolving computational design toolset. Interpreting what computational design culture is and what one does to promote it, is a rather open-ended question and one that we would like to discuss in this blog entry.

The roadmap to incorporating computational design methodologies will no doubt vary from firm to firm and will be influenced by the size and cultural ethos of the organization. However, there are ways to sequence and organize the approach to ensure that colleagues recognize the value that computation brings to AEC disciplines.

Cultivating interest and demonstrating value are at the core of any computational design initiative. Computationally inclined practitioners will be responsible for promoting these methodologies, transforming them from seemingly exotic to everyday practices. Selecting the appropriate opportunities to engage with design teams and managing expectations will increase the probability of success in these initiatives. As we learned from our experience at Stantec, open and collaborative engagements provide a foundation for fledgling computational design culture and getting practitioners on board. Demonstrating value through successful delivery ultimately reinforces computational design culture.

In short, here is what a possible ‘Advancing Computational Design Culture’ road-map might look like:

Find opportunities to educate and promote computational design methods

Developing a culture that supports computational design requires the education and engagement of practitioners throughout all levels of the organization. Both members of leadership, as well as those charged with delivering work should share in the excitement and potential offered by innovative approaches to practice. Increasing the dialogue around computational design creates fertile ground for ideas to emerge and develop. This dialogue will uncover potential problems to solve or areas within processes to intervene. Simple, quick and low risk case studies can be implemented for educational purposes and can be used to demonstrate potential value and build interest. Competitions serve as an excellent platform for computational engagement.

Education may also be formalized in varying configurations from access to online education platforms, quick lunch sessions, and intensive workshops both to engage and inform decision makers but also to provide opportunities for practitioners to gain the fundamental skills necessary to employ computational thinking in their day to day processes. Initializing a culture of computational design through education can be further strengthened by bringing together communities of practitioners who share a passion for innovation and offering platforms for them to learn from one another and build institutional expertise.

Discover opportunities to engage with project teams

Now that we have generated a bit of a buzz around computational design, hopefully we have identified key collaborators and some good problems to work on. How should a team be encouraged by their collaborators to increase likelihood of successful initiatives and implementation?

We can start by selecting projects that are low hanging fruit that we know we have a good chance of success. Another way to approach this is to select a project which has simple foundational output that could be built upon. So maybe your idea is really sophisticated, and it could be the end goal but in the meantime the team can successfully deliver a portion of this idea which will still demonstrate value. Managing expectations and continuing to educate your collaborators will be fundamental component of successful engagement.

Collaborators need to walk away from the experience having a better understanding of what is possible and what steps are necessary to get to successful solutions. Levels of engagement will likely vary depending on the needs of the collaborators, for example the team could be charged with developing a bespoke parametric project model, providing a support role offering varied levels of training and development as the collaborators develop their own solutions, or offering their services to develop a toolkit for use on specific project typologies. The interventions could address for example design optioneering, delivery efficiency, and/or data flows or any combination thereof.

Demonstrate value and delivery of solutions and trust-building engagement

There are inherent risks to innovation and building a culture that sustains innovative thinking and development requires ongoing attention. Encouraging buy-in from leadership through business case development is required for teams to secure the resources necessary to move forward with their computation initiatives. Development time, in addition to training or upstaffing costs are all investments that business leaders will need to consider making to establish foundation for a growing computational design culture.

The best way to build and secure trust is to work within an open and collaborative environment and to deliver solutions successfully. As teams grow to trust one another more ambitious interventions can be explored but when developing a supportive culture, it is important to focus again on those interventions where successful delivery is most likely and where stakeholders’ expectations are met or exceeded. Interrogating our work throughout the engagement is fundamental and necessary to develop a strong case for intervention: How does our work create value for the organization? Are we asking the right questions?

Successfully implementing a new workflow and tracking the results allows for computational teams to build strong business cases that strengthen comfort level at the leadership level which offers massive support to the computational design culture.

To conclude, the delivery of computational design solutions will undoubtedly vary from firm to firm, project to project but teams will need to consider roll out plans and adhere to standards and defined best practices. Defining the scope of ongoing support as well as follow-up can help further strengthen bonds between members in the organization by demonstrating that you are invested in the ongoing success of any solutions that have been developed. Increasing the levels of comfort within the realms of computational design in practice relies on the successful delivery and implementation of innovative solutions. The anticipation is that computational design culture becomes self-reinforcing when successes feed interest and innovation throughout the organization.

Written by Compuational Designers

Alyssa Haas, Masha Pekurovsky, Achintya Bhat – Stantec

Chris Mackey, Building Scientist, Payette – A CASE IN THE MERITS OF TOOL-SHARING: THE PAYETTE GLAZING AND WINTER COMFORT TOOL

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“We are not a software company.”

That simple phrase stated by a leader at Payette embodies an uncertain relationship that has developed within the AEC industry since the dawn of the digital age. The customized nature of design means that, inevitably, offices will create their own tools to test new, creative solutions. These tools may be as simple as a spreadsheet or as complex as a software plugin but they all raise a question that universally affects our practice: if our goal in the AEC industry is not to sell software, what is the fate of the software tools that we develop? Are they destined to remain on the company hard drive, collecting dust as artifacts of the designs that they informed? Are they meant to be reused and improved upon, in the same way that we iterate and improve upon our designs? Should such improvement and iteration be done only with in-house knowledge? Or should tools be shared with the industry, open to feedback, validated by expertise beyond that of the firm, and given a fair chance to change industry practices?

At Payette, we’ve discovered the value of sharing our tools and gathering feedback to improve them, which in turn, helps advance the profession.

1_GlazingWinterComfortAnimation

For example, we originally devised the Payette Glazing and Winter Comfort Tool to inform a situation that impacted over half the projects in our portfolio: we began many of our designs with aspirations of using triple pane windows but, as project budgets were evaluated, strategies with long paybacks like triple pane were often the first to go. Soon after such decisions about the envelope were made, our engineers would inform us that we would need perimeter heating elements next to the facade in order to maintain occupant thermal comfort in winter. Intuitively, we knew that if our envelopes were well-insulated, our interior surfaces would be warm and we would have no need for this extra heating system. Yet there was little agreement among our engineers about what would qualify as a sufficiently insulated envelope or whether triple pane would be enough to meet thermal comfort standard without the heating elements. After a lengthy research effort to understand this situation, we realized that the ability to meet the comfort standard with triple pane depended upon the geometry of the windows. With punched or ribbon windows, triple pane was enough but, with an all-glass façade, it was questionable, and with multi-story glass, it’s out of the question. And all of these rules changed when one had a project in a warmer climate or if an occupant put on a sweater. To empower our practice to handle any situation that arose, we began developing a tool that could accept many inputs and run thermal comfort calculations to provide recommendations. We knew that we wanted to share it publicly on the web, but in the process of sharing, we discovered three unexpected benefits of doing this.

2_Tool Development

  1. TOOLS BECOME BETTER WHEN SHARED

“When an expert network is functioning at its best, the smartest person in the room is the room itself.”

David Weinberger, Too Big to Know: Rethinking Knowledge Now That the Facts Aren’t the Facts, Experts Are Everywhere, and the Smartest Person in the Room is the Room

It is rare for any one individual to have all of the knowledge needed to give the best answer to a question. Taking this idea to heart when we began assembling our tool, we realized that a lot of the code for calculating thermal comfort had already been written by the authors of the Berkeley Center for the Built Environment (CBE) Thermal Comfort Tool. The development of their open source code was done by leading experts in comfort science and was regularly maintained, so instead of translating the thermal comfort standards ourselves from the code books, we borrowed their code as a basis for our tool. This was the first time where we realized the benefits of building off shared work since it’s unlikely that our translation would have been nearly as up-to-date or comprehensive as with the CBE tool.

6_Variables affecting occupant thermal comfort during wintertime conditions

Yet this was just the beginning. Within a few months of completing the first version of the tool, we learned that the same team who made the CBE Tool had developed a new comfort model that was particularly relevant to the condition we were studying. Going through the rigor of surveying occupants under the controlled conditions of a climate chamber, the CBE scientists assembled a model to forecast discomfort from drafts at ankle-level, which was a lynchpin for understanding discomfort near cold facades. We replaced our previous model with their new state-of-the-art one and instantly realized that the results were more aligned with what we had seen in other studies. We finally had something that we were confident in and, while successful in its own right, this was just the beginning of many improvements that we made after receiving feedback from users outside our firm. Bug reports, feature requests, and questions on methodology all helped us realize a much better tool than we would have ever developed using only in-house feedback.

  1. PROJECTS BECOME BETTER WHEN INFORMED BY SHARED TOOLS

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Having a good tool does not necessarily mean you will have good buildings. For our Glazing and Winter Comfort Tool, successful application required a consensus not just from Payette’s in-house building scientists but also the engineers with whom we work. Because the tool we built is open for anyone to experiment with, our engineers could validate it against their own methods, match their assumptions with ours, and ultimately sign off on our buildings with insulated envelopes and an absence of perimeter heat. It is largely for this reason that the fraction of projects using triple pane in our office skyrocketed over this past year. Had we not shared our tool, our consultants would understandably have been reluctant to sign off on our designs, effectively having to “trust us” that occupants were comfortable while they absorbed the responsibility. Getting past this critical barrier meant that we could finally ask an important question: which costs more – a triple pane façade without perimeter heat or a double pane one with it? For the two to three years since we started this process, the results have come out in favor of triple pane every time and, as a result, all of our designs are realizing a transition to more elegant, insulated (and cost-effective) facades. It’s unlikely that we would have ever achieved such a dramatic change in our building practices without the consensus built by sharing our tool.

III. INDUSTRY-WIDE PRACTICES IMPROVE WHEN INFORMED BY BROAD CONSENSUS

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While some companies may view open source sharing as a threat to one’s competitive edge, in the case of the Glazing and Winter Comfort Tool, we haven’t found that to be true. The widespread use of the Tool validates the ideas and methodology behind it, allowing our firm to lead change in the way we design elegantly-detailed, insulated facades as a profession.

If we think back to our original quote, that we are not a software company, it’s true that our clients don’t hire us because of our software tools. Rather, we are hired because of the people in our office and our expertise. Ultimately, people design good buildings and, like any tool, digital or analog, the greatest software tool in the world is effectively worthless without someone to wield it. When you share a tool with the industry, you lose the right to sell that tool but you gain an enormous amount of experience and expertise through feedback.

Whether it’s through thoughtful reasoning or by accident, the vast majority of tools and scripts within the AEC profession remain closed and only accessible in-house. However, we have so much to gain by sharing them more broadly.

9_Columbus Ave NU-¬Keitaro Yoshioka 075

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Contribution from Santiago Garay. The photos provided in this blog post are copyright property of © Payette,© Warren Jagger and © Keitaro Yoshioka

Interview with Jason Wheeler, Design Technology Specialist – Computational Design, CallisonRTKL

  1. Q) Computation seems integral to the work that CallisonRTKL does, and a critical differentiator to other design firms as well. Could you give a couple of examples on how CallisonRTKL works differently to integrate computation into every day work?

At CallisonRTKL, we invest a lot into “computational thinking.”  We’ve been creating a community on how to think computationally. This enables us to have constructive conversations around “computational doing,” where we begin to construct scripts and developable workflows that impact our day-to-day.

For example, we conduct monthly all-hands webinars to share concepts and ideas, some more in-depth than others, but each one reveals a relationship to computational design. It’s these relationships that spark ideas and collaborations, which, eventually, turn into daily practice. In this respect, computational design becomes integrated into everyday work through the thought and questioning of how and what people are currently working on. How can do this become faster, better, more well informed, etc.

One of our webinars on documentation and Dynamo set off a discussion with a team from another office about the workflow. The team was renumbering the rooms in a large multi-building project. The conversation led them to a leaner, more efficient workflow. But, it didn’t stop there, they became more active in computational thinking and engaged our Design Technology Group regarding how these types of processes can help them in other areas of different projects. Again, once it gets into our circulatory system, this type of thinking doesn’t stop. The team shared their knowledge with the rest of their office and conversations began with other teams as well.

  1. Q) What do you see as the biggest challenge facing the wider adoption of computational design? Why isn’t it already as widely adopted as BIM?

Computational design is more of an abstract concept than BIM, so it takes more cultural adoption—more an approach than a tool. Building Information Modeling is pretty straightforward.

What does BIM give you?  BIM gives you information and data about your building as your modelling it, while computational design can give you a façade. Computational design can give you a building mass, pattern and texture. That’s a pretty big box of tools and, well, not really a box either. It’s hard to adopt something that isn’t so easy to pin down as black or white. There is a lot of grey area that surrounds computational design, and that’s part of what makes it so compelling.

The adoption of computational design in the AEC industry is already happening at a larger scale. It’s evident in company’s having positions such as my own. It’s evident in more conferences such as this one. It’s evident in the fact that software companies such as Autodesk and McNeel have started to fully integrate visual programming past the status of an add-on. The biggest challenge now for the industry is to dig deeper into the possibilities of using computational design. To get past the notion that it is just complex geometries or automating tasks. How can it help us to become better designers?  How can it provide us another canvas to express our thoughts and inquiries into design?

 

  1. Q) In your experience, what is the most common mistake that design firms make when leveraging computation for the first time?

Top down implementation. In my experience it rarely works. People need to experience it, sample it, before they buy into it. You can’t come into a project saying, “We are going to use computational design on this project,” as if you are sprinkling pixie dust on something.  It just doesn’t work that way. It needs to come about as the result of a problem that must be resolved.

There’s a different thought process that comes about when you are thinking about a design problem computationally—it’s integrative or organic, not additive. Getting team members to explore these thoughts naturally first always seems to work better than to push it onto them. The ones who are usually pushing it from the top down are usually the ones who don’t really understand what computational design really is or how it works.

 

  1. Q) What is the most convincing example you have to prove the value and ROI in computational design? Do you have any projects where design optimization, cost, speed or some other metrics has been measurably improved?

 

We’ve had many projects where scripts and workflows have saved hundreds of billable hours, led to discoveries that wouldn’t have been seen otherwise, provided us with more design time, etc. One example that comes to mind is a workflow using the clash detection data from Navisworks to be revisualized in Revit. This workflow had saved us time within the moment by clearly seeing our clashes in 3D with all other contextual systems that surrounded it. It also saved us from future problems by visualizing any further clashes that would have occurred while moving objects blindly to resolve that current clash.

The real hidden value that is of more interest to me, though, is the adoption of computational thinking and workflows by different teams and peers. The spread of knowledge and increase in the number of people inquiring about computational methods signals to me that CallisonRTKL is becoming more informed and conscious of the current movement.

 

  1. Q) Do you believe the AEC industry can benefit from collaboration as a way to enable mass adoption of computation? Are there any examples of successful collaborative projects or platforms where designers have shared tools, techniques or training methods?

As I said, I already feel that the AEC industry is adopting computational design on a large scale. I enjoy seeing this, but sometimes worry that those interested in “jumping on the train” will derail the conversation and see it as a simple automation tool.

The community is a largely open source one. A lot of us from different firms, different industries and different backgrounds find each other on various forums and blog sites to exchange information and thoughts. All dedicated to furthering the knowledge and use around computational design.

  1. Q) The advancement of computation is clearly linked to technology, such as the development of design software. What do you think is the next big technological leap that we should be planning for? What do you envision computational design to have the potential to achieve?

The next wave has already begun; that’s evident by all the recent clamour and investigation around machine learning techniques within the AEC industry. We as an industry have already found that data is king. This has led to a mass collection of data—data on all sorts of things from restroom count and location to Revit errors to clicks on a screen, etc. All this data has given us ways to see and understand relationships and value that we likely wouldn’t have seen otherwise, but now there seems to be a larger interest in “what more can our data do for us.”  These types of inquiries are what will drive this wave into machine learning.

  1. Q) What are you hoping to achieve from attending and presenting at Advancing Computational Building Design 2018?

I am very excited to be attending and presenting at the Advancing Computational Building Design conference this year. I’m most interested in learning. Just very eager to see and hear what everyone else is up to. Being able to not only attend the presentations but to be able to have some time for one-on-one and small group conversations. It’s up to us to steer this ship and define how computational design will engage and affect our industry, so for us all to be communicating about it and reacting to one another is key to how I see this evolving productively.

Jason Wheeler Interview Photo 2

Ryan Cameron, Associate Project Architect, DLR Group

Advancing Computational Building Design 2018 Blog

Learn how to develop as a team and create a strategy for technically emergent staff to use computational design methods and tools.

Our Firm’s Progress & Expanding Audience

At DLR Group, we challenge ourselves to think beyond what’s possible. One challenge is widespread adoption. While having a different perspective is often an advantage in the design process, we’re seeing that employee-owners in the company think differently about our technical process and how they are learning to streamline and integrate these workflows across multiple regions.

Understanding how different people work, realizing their capacity for adaptation, and gauging their interest in computational practice is tricky. Computational methods are not for everyone. While the intent is to use computers to our advantage, the learning curve is not a path for everyone.

DLR Group is making tremendous progress, expanding from by 150% to our subscribers in our internal newslettern three years. These numbers represent our eyes-on, hands-on users, and eyes-on-only users. On a grander scale, the Dynamo NEXT video and audiocast reaches a global audience. The YouTube channel has over 1,200+ subscribers world-wide and is a growing resource for tips and real-world examples of working with computation.

Questions & Analyses

A sample of questions this session will answer include:

  • How are we tracking the process to validate progress?
  • What are the resources suggested for learning about computation?
  • What are you doing to apply what you learned?

RC1

Motivate Our Industry

Evidence demonstrates that we can use computational design tools to win projects, not just create amorphous designs or faster design iterations. Proof is in the performance. Once you establish that computation played a role in getting a signed contract, you have an evidence-based, business case study. Now, it’s easier to build an ROI case on the investment of time and practice improvements it brings with it.

Most of the validation comes after our work is complete. With computational design, the project schedule is so short that if something isn’t working, we occasionally have to abandon it then come back later to improve it. This is just part of the process of the Build-Measure-Learn cycle.

Computation is more than a few advanced tools to manipulate data; it’s an assistant to create and move data.  This is the perfect time for design professionals to establish ourselves as experts in AEC Big Data and beyond.

RC2

 “The leaders will be movers of data who create and enhance architectural spaces that elevate the user experience.”

Participate Locally/Globally

I’m looking forward to hearing back from the community just as much as I am presenting the topics selected by the conference committee. Expect a short feedback session after the presentation is over but as always, reach out locally and globally if you need assistance.

Thank you for reading and I hope to see you at Advancing Computational Building Design in New York later this year!

~Ryan B. Cameron

Learn more about the conference here