Posts tagged ‘remotesolving’

We may not quite be at 2.0 status just yet, but members of the CORE studio team have been hard at work with the concept of remote solving. In essence, remote solving creates an automated means of providing feedback to our clients by using a specialized computational model that exposes high-level inputs and outputs. As the client makes changes to these inputs, our model reads the updated information, runs the desired analysis, then returns automated feedback – all without the need to exchange full 3D models.

This process enables a highly fluid and rapid communication process early in schematic design, when a design option may only stay on the boards for a short period of time. With collaboration in mind, we are exploring areas where automated feedback can assist in the development of the design at a pace that keeps up with the rapid production of the design team.

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In the most recent example, we were asked to study how ceramic frit patterns on a tower’s façade impacted the amount of daylight entering the building. We set up a remote solving process that allowed the client to manipulate the pattern, upload images and specify a floor level to study and, within an hour, receive a full report on the performance of that particular pattern. This process eliminated the days – or even weeks – it can take for us to receive a design, process it into a format for our analysis, run a simulation, prepare a report and send it back. Unlike the traditional process, remote solving can easily keep up with the fast-paced iterations that often occur in the early stages of design.

The diagram below explains our recent process, this time using the Dropbox file sharing service to receive and deliver content. The back end of this model (in Grasshopper) runs a useful daylight illuminance (UDI) study using the open-source toolset Honeybee, developed by our own Mostapha Roudsari. The Grasshopper definition listens for new files in the Dropbox, loads them into the model, parses the images to create different glass types to approximate the transmittance of glazing that the frit pattern produces, runs the study, uses custom components to produce a rendering of the model, and finally uses the ‘Write To Excel’ component in TT Toolbox to generate custom formatted tables of the daylighting study results.

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We will be looking to continue this stream of research in the upcoming year, so keep an eye out for more advances into this methodology.

The Advanced Computational Modeling Group (ACM) has been working on a research project which attempts to answer an important question:  How can collaboration between Architects and Engineers be more productive in the early design stages?

Over the past two years, we’ve been working with more and more architects who use Grasshopper in the schematic and pre-schematic design stages.  Concurrently, ACM has been developing a suite of generative structural design and analysis tools in Grasshopper which enable us to generate entire conceptual stage structural frame systems algorithmically, given only a set of geometric inputs from an architect.

The goal of this research project is to connect our clients’ architectural design definitions to our generative design tools via a shared database on the web.  We have been calling the work Remote Solving, and have been collaboratively developing the project with LMN Tech Studio (LMNts) since February.

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The idea is relatively simple: An architect’s grasshopper definition sends our customized grasshopper analytic solver definition some input geometry, our definition generates a structural model algorithmically, and reports the structure’s performance back to the architect. From the architect’s point of view, the structural work is being solved remotely, and useful order-of-magnitude performance data [material use, embodied energy and embodied carbon, structural beam depths and column sizes, etc.] is made available at near real time. Despite the fact that the structural output is preliminary in nature, this level of information is typically sufficient to help Architects/Owners make more informed design decisions. The structural performance feedback is particularly helpful as a comparative tool to analyze various geometric schemes.

ACM has developed custom MySQL database table schemes for exchanging the relevant design information, including schemes for column grid lines, floor profile curves, sized structural frames, and structural performance data. We utilize Nathan Miller’s Slingshot! plugin for Grasshopper / MySQL interoperability.

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The videos below show our Remote Solving prototype in action.  The architect’s client definition is on the left hand side, and is visualized in the rhino viewport with the black background.  The window on the right is a VNC view of the remote computer hosting the structural definition.  As the client [Architect’s definition] changes the design parameters or input geometry, new structural frames are generated and either geometry or performance data are returned by the server [ACM’s definition].

ACM will continue to pursue this research over the coming months, and is seeking active, early stage projects which could be used as case studies for the system.  We would like to thank Scott Crawford, Stephen Van Dyck, and Erick Katzenstien of LMN Architects for all of their creative input and invaluable feedback during the collaborative development of this research project, and are looking forward to developing the work with LMN in the future.

We believe this innovative workflow creating a closer collaboration between architects and engineers will vastly improve our projects and professional practice, and are excited about the next stages of our research with Remote Solving.