Posts tagged ‘software’

Explore CORE Studio’s latest contribution to DynamoRevit. We added a lot of new nodes which are partly already released with Dynamo 1.2 and will fully be available with the next Dynamo release. There are a lot of new nodes for creating and manipulating annotations, accessing element properties, manipulating existing locations and entirely new features like creating family types from dynamo geometries or creating global parameters. We added a list containing all new nodes below:

Annotations

  • Draw and query detail curves by dynamo curves
  • Create dimensions by elements or manipulate dimension properties
  • Make filled regions by outline and access filled region types
  • Place revision clouds by outline curves like polygons
  • Tag any element in Revit directly through Dynamo
  • Place text notes in views, access their properties and text note types
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Tag Walls and place Dimensions in Dynamo

Material

  • Access Material properties like Name, Shininess, Smoothness, Transparency, SurfacePatternColor, MaterialClass, MaterialCategory, CutPatternColor, Color, CutPatternId, AppearanceParameters, ThermalParameters, StructuralParameters

Selection

  • Select multiple edges from elements

Elements

  • Create rooms by location point
  • Get room boundaries as curves
  • Create reference planes by points
  • Get location point or curve and manipulate them with the set location node
  • Move elements by vector
  • Access element materials
  • Create new revisions using dynamo
  • Create wall by face
  • Access Revit’s shape editor for roofs and floors
  • Create curtain systems by face
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Create Wall by Face in Dynamo

Families

  • Access properties like host element of family and type
  • Create new family types by dynamo geometry
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Create new Family types from Dynamo geometry

Document

  • GetSurveyPoint and
  • GetBasePoint give you direct access to the document’s coordinates

Parameters

  • Access parameter properties like: HasValue, IsReadOnly, IsShared, Group, ParameterType, Id, UnitType, ParameterByName, SetValue, StorageType, SharedParameterFile,
  • Create shared or project parameters
  • Create global parameters (from Revit 2017)
  • Access global parameter properties

Filter

  • Create Parameter Filters by filter rules
  • Create Filter Rules by Rule Types
  • Create new Override graphic settings

Performance Adviser

  • Run Revit’s performance adviser directly in dynamo and explore failure messages

UI Nodes

  • And several UI nodes to access elements like: Phase, Revision, FilledRegionType, RevisionNumbering, RevisionNumberType, ParameterType, BuiltInParameterGroup, RevisionVisibility, DirectShapeRoomBoundingOption, FilterType, HorizontalAlignment, VerticalAlignment, RuleType

Written by: Max Thumfart

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CORE studio has released an updated version of TT Toolbox for Grasshopper containing a new plugin called Colibri.

hummingbird

Colibri is Spanish for hummingbird. Logo by Colibri contributor Olivier Dambron.

Colibri allows Grasshopper users to easily turn their Grasshopper definitions into Design Explorer – compatible design spaces.  Run Colibri in Grasshopper, upload to Google Drive, and voila: your design space in Design Explorer!

Colibri is an open source project that was started at the 2016 AEC Technology Hackathon in New York, which CORE studio hosted late last year.  It was designed and prototyped over the course of 27 hours during the hackathon by a team of dedicated hackers (most of whom work for TT!).  CORE studio forked the project after the hackathon, and we’ve been improving and testing Colibri over the past few weeks in anticipation of this release.

The project’s goal is simple: make it easy to generate Design Explorer-compatible data sets in Grasshopper. This has been possible to do for some time now of course, but it was super painful to set up and was generally quite error-prone.  Users would rely on Ladybug’s ‘Fly’ component or our ‘Brute Force’ component to iterate over some sliders in their grasshopper definition, and use a bunch of data recorders and an Excel Writer to create a data.csv file in the right format.  Images and Spectacles models were up to the user to generate, name, and link into the .csv file properly.  Because Fly and Brute Force hit every step on every slider, users’ sliders often had to be edited to fine tune the size and resolution of the design space.  If all of that sounds like complete nonsense (or if it makes sense but sounds painful), we are with you, and that’s precisely why we built Colibri.  It should be easy to jump into Design Explorer!

The Colibri workflow is divided into two stages, Iteration and  Aggregation.  Colibri provides a component for each stage, the Iterator and the Aggregator.

ColibriIteratorGif001

Colibri Iterator

The Iterator component loops over connected sliders and drives your grasshopper definition, much like Galapagos does when it’s running. Unlike Ladybug’s ‘Fly’ component or our old ‘Brute Force’ component (all of which, more or less, share the same code base by the way – these tools are all based on this post from David Rutten), Colibri’s Iterator component allows users to specify how many steps to take along each slider.  This is subtle, but important: it allows users to keep the size of their design space under control, and to specify granularity selectively along each input vector within the design space – all without editing the actual sliders in Grasshopper.

aggregator

Colibri Aggregator

While the Iterator is iterating away upstream, the Aggregator component collects all of the data that Design Explorer needs from your Grasshopper definition. It gathers the inputs from the Iterator, the outputs (performance metrics) from your grasshopper definition, and takes care of generating images, naming images and Spectacles files, and writing all of that data into a data.csv file.

Another application for the Aggregator is to record optimization runs with Galapagos or Octopus. By connecting the ‘Colibri Inputs’ component to the same sliders that Galapagos / Octopus is driving, the Aggregator is able to record every iteration during an optimization run.  This workflow allows designers to navigate within the focused design spaces that those algorithms produce using Design Explorer.  Instead of reinstating one iteration at a time in Grasshopper, groups of iterations that fit a set of specific performance criteria (something like ‘show me all iterations that are highly performant and that have a bay spacing greater than X and a floor height smaller than Y’, for example) can easily be identified using Design Explorer.

The YouTube video above demonstrates how to get started with Colibri, and you can download the plugin from Food4Rhino.  Please let us know what you think!  We sincerely hope you’ll enjoy working with Colibri and Design Explorer.

Written by: Benjamin Howes

CORE studio is pleased to announce Design Explorer, an open source tool for exploring design spaces on the web.  We’ve been working on this project on and off for well over a year now and we’ve presented it a number of times, but we’ve never written about it. Shame on us!

Design Explorer

Design Explorer

Over the next few weeks, we will publish a series of blog posts about the project’s goals, the natural history of design space tools in AEC, and how Thornton Tomasetti and others are using Design Explorer in practice. This first post will focus on the current state of the project and the main problems that Design Explorer is trying to solve.

The first problem will be familiar to anyone who has done any parametric and/or computational modeling: parametric models give you too many iterations. Of the multitude of possible states that any reasonably complex parametric model describes, which ones are the good ones?  Are there some zones that are better than others?  If so, how do we find them?  It depends what you mean by ‘good’ and ‘better’, of course…

For some design problems, performance is measurable. Designers and engineers can qualify ‘good’ according to project-specific performance criteria.  Computational modelers can (and should!) build analysis feedback loops into their models to let performance analysis inform the trajectory of the design process.  Since CORE studio supports a world class engineering practice, we have the luxury of dealing almost exclusively with these types of problems.  In most cases, we build rich parametric models with embedded analysis feedback loops to rapidly study a wide range of potential solutions.  As such, this problem (too many iterations, where are the good ones?) is particularly important to us.

Nervous SystemNervous System’s edge based growth design space. Source.

The second set of problems is related to the nature of design spaces themselves. The types of design spaces that our grasshopper definitions and dynamo graphs describe are multi-dimensional.  Multi-dimensional spaces work  like the three dimensional space we all model in every day – they just have more axes.  Whereas a three dimensional point in euclidian space is described like this: { x, y, z }, a higher dimensional point in a design space might be described like this { length, width, height, numFloors, cornerRadius, rotation, embodiedCarbon, cost }.  Because our design spaces are typically of a higher dimension [than three], they are hard to visualize.  And because they are hard to visualize, they are very hard to navigate.

Wired

Wired.com’s illustration of a 3D design space. Source (and excellent article about design space thinking in the graphic design world).

You can think of Grasshopper and Dynamo as design space navigation interfaces.  Parametric modelers allow you to navigate from one point to another in any design space that you construct.  When you drag a slider in Grasshopper, you are moving along a vector in your design space, computing and visualizing one iteration at a time as you go.

Design Explorer is an interface that lets you visualize and filter groups of iterations – sets of design solutions that are both intimately related, and potentially scattered across a vast, high-dimensional possibility space.

Design Explorer Demo

Users export their design spaces from parametric authoring applications (Grasshopper, Dynamo, Catia, Etc.) in the form of a data.csv file and a series of images and Spectacles models.  The design space data is generated by traversing the parametric model in an automated fashion – either with our brute force solver, Ladybug’s Fly component, or an optimization algorithm such as Galapagos or Octopus.  After all of the data has been generated, it must be hosted somewhere on the web (Google Drive, Amazon S3, or your own server).

Design Explorer reads the data.csv file and generates a 2D visualization of the design space called a parallel coordinates plot (with a grid of thumbnails and some other UI).  The plot’s vertical axes represent design variables and performance metrics; the lines running horizontally across the plot represent individuals within the design space.  The design space can be filtered by clicking and dragging along the vertical axes, and by dragging filters up and down.  Users can investigate individuals by clicking on a thumbnail and reviewing a full size image and a 3D model.

Our next post will concentrate on the natural history of these ideas within our group, highlight a few parallel/adjacent projects within the AEC technology community, and identify some meaningful precedents in popular culture. In the meantime, you should try Design Explorer!  Give the samples a look, check out Mingbo Peng’s tutorial video, fork the Github repo and mess with the code, and let us know what you think!

 

Written by: Benjamin Howes

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The latest round of research funding has been awarded by Thornton Tomasetti’s R&D group, and staffers in several offices and practices are hard at work on bringing these new ideas to life. Projects underway include several sustainability analysis tools, a computer language training program for technical staff and a study on the implications of performance-based wind engineering.

These projects were based on proposals submitted to Thornton Tomasetti’s Innovation Suggestion Box, which was launched last year. Funding for these research proposals allows Thornton Tomasetti employees to spend time outside of billable projects to develop unique ideas to improve operations across the firm. In a sense, the R&D initiative gives us a little breathing room to think big.

Anyone in the firm can propose a research project, with submissions collected approximately once every quarter. In addition to getting resources allocated for their projects, employees whose proposals are selected also receive an iPad mini.

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Illuminance study for the Hudson Yards Culture Shed.

Illuminance study for the Hudson Yards Culture Shed.

We are excited to announce that our own Integration Applications Developer Mostapha Roudsari has recently released Honeybee, his second plugin for environmental analysis, as well as a new version of Ladybug!

Honeybee is an ongoing, open source project to connect Grasshopper with validated daylighting and energy simulation engines, such as RADIANCE, Daysim, EnergyPlus and OpenStudio. The current version of Honeybee includes 64 components that enable users to prepare and run a variety of daylight analyses.

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We are excited to have released a new version of our TT Toolbox plugin for Grasshopper. The new tool features interoperabilty with Google Spreadsheets. That means that you can now read and write to Google spreadsheets. You could for example set up interaction between multiple computers now. Or control a parametic model from your smart phone, as shown in the video below:

We also added a ‘brute force solver’ tool that allows you to pre-process all possible combinations of variables in series, which comes in handy if you need to process a large set of options at once.

You can download the free-to-use TT Toolbox plugin for Grasshopper from Food4Rhino. We hope you like it. As always, please let us know your thoughts on our Grasshopper community page.

Thornton Tomasetti’s Building Sustainability practice, in conjunction with the CORE Studio team, is developing a Rhino/Grasshopper-based, concept-level sustainability analysis platform known as PANDA (Parametric Analysis of eNergy and Daylight Autonomy). The tool uses Energy Plus’ robust energy simulation engine within a parametric modeling environment by employing Integration Applications Developer Mostapha Roudsari’s Grasshopper Honeybee components.

The interface will allow the user to experiment with multiple design iterations and obtain rapid feedback on whole-building energy use, utility costs and renewable energy potential.

The tool differentiates itself from similar tools on the market by:

– using powerful simulation engines generally used for more detailed modeling
– allowing the user to visualize changes to the building in Rhino’s modeling environment
– simultaneously analyzing daylighting
– providing comparisons to energy standards such as ASHRAE 90.1 and the 2030 Challenge

In addition to being able to rapidly simulate design parameters like geometry, floor heights and window-to-wall area ratios, the team plans to eventually add the capability of evaluating the impact of HVAC systems, such as under floor air distribution and ground source heat pumps. The tool is currently in the beta testing phase and is being evaluated by Project Director Colin Schless, Roudsari and Sustainability Intern Christopher Mackey. We will post progress updates here on the blog as it evolves.

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Grasshopper-designed roof of the Al Menna Sports Complex in Iraq.

Grasshopper-designed roof of the Al Menna Sports Complex in Iraq.

The smart structural interpreter (ssi) tools for Grasshopper changed the way that we engineers look at modeling. We first tested the ssi plugin in 2010, when we were searching for the fastest possible way to design a stadium roof structure with SAP. Our challenge was to submit a detailed set of drawings for a competition proposal for the fabric roof system of the Al Menaa Sports Complex in Iraq.

We spent three days at the offices of 360 Architects, sitting together to generate a parametric model of the roof that would allow us to study different design scenarios, both from an architectural and structural perspective. On day four, we used the ssiSAP interpreter to assign structural material properties to our wireframe geometry, and then to ‘bake’ this into SAP to run analyses. The analysis in SAP is set up relatively quickly for a project such as this – the bulk of the time spent would have been in creating the geometry. As such, typically in the competition phase of a project, engineers would not be able to run multiple analyses, which might help to understand and improve the design.

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The set of components we created for Grasshopper.

The set of Grasshopper components we created to calculate and visualize embodied carbon contents of structures.

A building structure is made up of many different material combinations. It is not always intuitive to understand which material combination for a specific building type is more efficient, when it comes to embodied carbon and embodied energy impacts. Furthermore, a typical concrete structure still contains about 8 to 10 psf of structural reinforcing steel, and vice versa, a steel structure contains large amounts of concrete. This calculation becomes even more complex when trying to compare different building typologies, say a low rise building with a column grid spacing of 30ft, with a high rise building with a column grid of 25ft, even if the net floor area is the same. And to further complicate these equations, one can also bring different concrete strength values into the mix, or consider supplemental cementations materials or recycled steel.

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