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?


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.


 “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

Interview with Zigmund Rubel, Chief of Building Services, Aditazz

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

We feel our unique differentiation is having in-house software developers sitting with designers to understand our needs for the tools to function in the AEC space. Computers do not act like humans and the invaluable dialogue that occurs between our building designers and the software developers in the translation of human requirements to machine requirements. I think what makes Aditazz unique in that we have almost a 1-1 ratio of domain experts (Architects, medical planners, engineers, builders and medical doctors) to software developers. This allows us to have deep conversations of what the different facets of computation are needed in the design world.

The uniqueness of Aditazz culture is where a building designer can express a design need and the software developer can consider the solution in their mathematical perspective and propose a solution that might’ve not been obvious to the building designer. Specifically, there are simple utilities, like search and replace functions of content, that is hard to do in the native design software, but can be scripted by a software developer in simple abstract programming language.

2. Q) What do you see as the biggest challenge facing the wider adoption of computational design? Why aren’t these methods already common practice?

I think there may be three main reasons and a host of ancillary challenges. First is cultural resistance to those beholden to current methods. There are many talented designers that are great at what they do and are not ready to step into a new medium that might radically change the way they approach design. Asking a machine, computer, to design forces you to think differently. This is a frightening proposition for some. Along with the cultural challenge is the lack of clear path to monetizing the investment because computational design might take a different amount of time yet provide tremendous more value. How does the designer get compensated for the value instead of the “X” number of hours that they spent using the computer? Last, and not least, is the lack of standardization to use computers for design thinking. The design is as much art as it is science. Computers can easily tackle the science part, but also need to address the art part. Now imagine that each building type or system has a different set of computational design needs. Because the problem set appears to be infinite, the adoption of computational design is being taken on in bits and pieces. When a larger amount of scope of computational design is reliably processed by a machine we will see more standards and more adoption.

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

I think we have a significant interoperability and level of development communication challenge. Until we can operate on a single model or platform, we will continue to not know where our design team members are at with their scope of the design. Today, we might say we’re done. And to me, I truly believe I’m done. But to the person who is coordinating my design, it might not meet their needs nor might all the requirements be developed in my design. Until we can have more transparency in the computational design process we will continue to have this challenge, which causes many mistakes.

4. Q) What is the most convincing example you have to prove the business case for computational design? Do you have any projects where design optimization, cost, speed or some other metrics has been measurably improved?

Several of our projects have been able to reduce the cost of the project by showing how the function of the building can still be performed with a smaller physical area. In some of those cases, the experience to the customer is improved within the smaller building because they’re able to spend less time waiting on individuals and spend more time with the primary purpose of why they went to the building. Specifically, our business does a lot of Healthcare projects. If you’re able to build a smaller project, see the same number of patients as a larger building, and those patients are in the healthcare building for less time with more time with their doctor, we think that is a success.

5. 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 will the tools be able to do in a couple of years, which cannot quite be achieved today?

I think today our industry drives computational design by manual input. We’ve yet to leverage the power of computation and automation. In the coming years, maybe more than two, we will be able to ask the computer a question and it will find the answer. For example, we can search specific questions on the internet at a scale that keeps on changing. When we design today, it is largely a manual process, even with scripting. I’m hoping that we will soon be able to ask the computer to generate the solution within a boundary of solutions. There has been some prototypes of this done, but it is not main stream yet.

6. Q) What are you hoping to achieve from attending and presenting at Advancing Computational Building Design 2017?

I’m really excited to see all the other presentations. I believe computational design is a movement and the presenters at the conference are shakers, making the change that needs to occur. All the presenters will be sharing their knowledge and how it has added value to their business. Everyone’s presentation will not be as inspiring as others, but they will all be advancing the notion of how computational building design can be done. For my presentation, I’m looking forward to showing our successes, challenges and hearing the audience’s thoughts about what we’re doing. Everyone in the conference is a pioneer and it is important that we get feedback on what we’re presenting.


Elliot Glassman, Associate, WSP

Architecture has always been informed by the technology that was used to design and construct it. Steel structural systems and the curtain wall were some of the technologies that defined the advancement of architectural design in the 20th century. In the 21st century, our industry will be revolutionized by computational design. Already computational design is providing us with new algorithmically generated building forms and the advancement of digital fabrication technologies. As both an architect and a building performance specialist, I see great potential in leveraging computational design to shape structures that are an intelligent response to their climate and site, reducing energy use while providing occupants with a comfortable and well daylit interior environment.

I will be copresenting the keynote address Integrating Computation Into a Collaborative Design Process: Enabling Architects & Engineers to Leverage Tools & Access Data at the Right Time with my colleague from WSP’s structural engineering services Joseph Provenza. During my part of the talk, I will be discussing how WSP Built Ecology has successfully utilized computational design workflows to inform building design decisions with performance in mind. The end goal is to provide a result where the design and performance are integrated into the architecture as one.

The performance of buildings are a function of the complex and dynamic interactions between climate, site, and occupant behavior as well as the physical and thermal characteristics of the building itself. Traditional modelling approaches need the architectural design process to be advanced enough so the characteristics of the building can to be defined in the performance simulation. The catch is that a design that is advanced enough for this traditional modelling approach will have many architectural decisions made already and will therefore be harder to change even if the simulation reveals suboptimal performance.

Using computational design processes and brute force modelling, we can be more proactive about designing for performance. We can analyze many potential scenarios early in the design process so that the critical parameters for high-performance can be identified.  The comparison of alternatives can help us set priorities for the design and understand potential trade-offs. The studies can inform fundamental architectural decisions that weigh heavily on performance such as orientation, massing, and facade configuration.

By providing this information to the architectural and engineering teams earlier in the design process, we empower them to make data-driven design decisions that will more likely result in a successful high-performance outcome down the line. We can simultaneously balance multiple performance aspects such as energy, peak loads, daylight, and visual comfort so that we don’t inadvertently optimize for one at the expense of the other.

Computational design environments are where a lot of our clients are already doing their cutting edge design work. Incorporating performance simulation analysis into that same environment allows us to better integrate with their design process and provide quicker feedback. It also helps ensure that the elements of the architectural design become performative. When these elements cannot be changed or value engineered out without repercussions to things like energy performance or peak load sizing, the design intent is better preserved.

Performance results are most meaningful when they can be related back to the architectural design or the surrounding context. Using computational design tools, we can create custom visualizations to provide visual feedback and draw connections back to the factors influencing performance. This highlight elements which are performing well or underperforming, suggesting paths forward in refining the design.

The biggest challenges we face that prevents us from working with design teams in this manner are often not the limits of the technology. We do not usually approach those technological limits because the industry does fully not understand how existing computational design technology can be leveraged to drive and inform their designs for performance and environmental responsiveness. Often we are brought into the discussion after many of the design decisions that matter most are locked in, and we are only able to trim around the edges to improve performance.

Another aspect of this is the perception that designing for building performance is restrictive of architectural freedom. However, by using computational design to explore many possibilities and identify trade-offs, we often find there are actually a number of different solutions that can provide good performance. Using performance as a driver of the design can actually become a creative process that generates architectural forms to respond effectively to the environment.

We are trying to make progress on these challenges by illustrating what can be done with computational design to inform the building through environmental considerations. By demonstrating how we have leveraged these workflows to achieve successful architectural and performance outcomes on projects, we hope to promote their use.

The environmental problems our society faces are complex and the building sector is the largest contributor to greenhouse gas emissions.  By creating buildings that respond appropriately to the climate, we can reduce our energy consumption and impact on the planet. We can also create buildings that provide a better interior environmental for their occupants in terms of daylight, views, and thermal comfort. Computational design can help us account for complex environmental factors and help generate high-performance solutions for all these considerations. As the technology continues to evolve, the range of possibilities are expanding. We want to stir the imagination of the industry to think about how an integrated, performance-based design process can be used to inform 21st century architecture and lead to a more sustainable built environment.

Join Elliot at Advancing Computational Building Design.

Learn more about the conference here