The design of houses has become a highly mechanized process with the most recently available AIA data indicating a maximum of only 28% of houses have direct involvement with an architect or licensed design professional.
The occupants or clients that will eventually inhabit the house are not accounted for in the design process – they have no agency in the design of their home, and marginal agency in the selection as the market provides a limited variety in the housing stock. The result is an urban and neighborhood character that is shaped using mass-production tract housing methods where similar home plans are copied, mirrored and rotated to create standardized communities. These houses are typically built for expedience, fast and cheap. The design process is essentially eliminated in favor of speed and profit.
By contrast, in the Housing Agency System, a distributed network of design stakeholders contribute to an accretive library of component workflows that build up a database of potential solutions, which can be dispatched based on input from the various stakeholders. In the HAS, Search Constructors combine to create a robust “design space” that represents the range of possible design solutions to be analyzed by the solver. Computationally, each search constructor is described as sets of parametric constraints, rules and relationships defined collectively by design stakeholders. These interact to form a FPM or Search Model. When implemented on a design project, each search model requires description at six architectural scales to be complete: Site Model, Planning Strategies, Formal Strategies, Construction Systems, Surface/Detail Systems and Building Components.
A distributed network of collaborators contribute to a component workflow that integrates to the Housing Agency System. The component system allows for combinations of the various strategies that support the accretive library of options. The result is a series of algorithms that make the design of houses a customized process, reducing the costs traditionally associated with custom design that can run into the tens or hundreds of thousands of dollars on a home, a figure that makes custom building out of the realm of possibility for most American families.
An Interface for Viewing Results of Optimization Routines
By viewing a large sample of options and searching through them to find acceptable solutions, the generative production of designs increases the ability of the architect to evaluate a large sample of alternatives. These alternatives are accompanied by performance criteria generated from simulations and may be sorted dynamically.
Tools for Generating House Designs
Working with several programming and modeling environments, a series of tools for creating and documenting design space models are being developed. The diagram below shows the flexing of a design space model as it was constrained for a given site and client.
The design space is overlaid in the image below to describe the space of options evaluated in the generative design routine. A research article, co-authored by Prof. Kyle Steinfeld, documenting the Housing Agency taxonomy will be published soon by the Association of Collegiate Schools of Architecture.
The A* algorithm is implemented with the adjacency matrix generator with Grasshopper for Rhinoceros 3D, through the Shortest Path tool. This research is the subject of a forthcoming article.]]>
What is MCDA or MDO?
Multi-Objective Optimization or Multi-Criteria Design Optimization (MCDA) software has been developed primarily for and by industrial engineers to design airplanes, automobiles, high speed trains and appliances. Process Integrated Design Optimization is another name for the field. The idea of optimization in architecture has been around since nearly the beginning of CAD in the 1950s and 60s, but had been limited by the power of computers and the huge number of variables so it has not yet achieved a critical mass of proponents. The drive towards BIM technology has been justified in part because of benefits that result from having a digital representation of the building to develop performance simulations.
Designers who work with MCDA craft search spaces, and guide searches with goal sets. In Galapagos, the evolutionary solver for Grasshopper (the parametric modeling plugin for Rhino) there are two inputs, genomes and a fitness function. Genomes represent variables that can be changed in order to manipulate a model. A fitness parameter is a ‘score’ that the solver wants to target.
A successful MDO model measures values that are of importance and iteratively changes those values in the experiment, guiding the changes in the model towards a desired score. This process is automated and guided by optimization algorithms. Genetic algorithms are frequently used though they tend to settle on local optima and are not ideal in matters of true optimization especially concerning multi-objective problems.
Recently, projects at the Stanford Center for Facilities Engineering have advanced the interest in architectural application by integration with these new process engineering software systems. Digital Project (CATIA) can be integrated directly to the Phoenix Integration Model Center interface, there does not yet exist a publicly available wrapper for Grasshopper/Rhino. Skidmore, Owings and Merrill used the ModelCenter workflow for fine tuning the structural system for their TransBay Terminal Tower proposal.
Other projects that have used optimization in the recent past include OMA for their Hong Kong transit project, Herzog and de Meuron’s Water Cube (the structure was rationalized using optimization) and many other projects consulted on by ARUP, who have developed a promising integration software, DesignLink.
The video below by engineers at Ramboll shows how the mobius strip form of the Astana Library was engineered to maintain the ideal form, minimize deflections, panel variations, cost and material usage to make the project a reality. A similar but less sophisticated process was used in the Morphosis Phare Tower in Paris :
With more design phase models representing a realistic model of what the built construction will be, simulations are increasing in popularity as benchmarks for making design decisions. The legal issues concerning liability in the use of these figures is bound to become a hot topic as the tools become seamlessly incorporated into design software environments. Autodesk Revit incorporated an Analyze tab in Revit 2010, providing solar radiation and energy analysis through Green Building Studio. Vasari now has computer fluid dynamic (CFD) simulation, though it is based on a video game engine and is not highly accurate as programs like CFDesign or Fluent which can provide good analysis of passive ventilation strategies.
When I worked with Autodesk last summer there was a big push for optimization procedures with three projects in the IDEA studio (the university-tied research wing of Autodesk) directly supporting this study. The projects were Local Code, Nicholas de Monchaux, a project by David Benjamin of The Living, structural optimization of the Living Light pavillion in Korea is linked below. Benjamin’s studio at GSAPP has produced a great deal of experimentation with ModeFrontier, a multi-objective optimization tool and a third team of PhD researchers from USC adapting the Revit API for volumetric optimization.
Additionally, Zach Kron of the great blog buildz has developed a Goal Finder the the Vasari interface, which is enabled through the Python (a programming language) plug-in for Vasari. Vasari, if you don’t know, is an Autodesk Labs product (free, for now!) that allows you do perform conceptual design studies and load them directly into Revit.
I have been experimenting with Grasshopper, Python, Rhino and Phoenix Integration to create ‘search space’ models that allow a designer to provide a framework for manipulation that is guided by goal sets. I have been working on ‘goal sets’, algorithms that are inspired by shape grammar and architectural manifestos to generate many design schemes, evaluating each and providing a catalog of design options for the architect/client to choose from. A quick project that I worked on a few weeks ago codified Corbusier’s design aesthetic in Towards a New Architecture, The Problem of the House into a goal set. I then created a grid based model and generated a massive family of Villa Savoyes, an early video is linked below for your perusal.
Generative Design Resources
MVRDV Vertical Village Generator – Video
Autodesk Research Physics Based Generative Design
Luisa Caldas Generative Design System for Sustainable Architecture.
The diagram below describes the total programmatic distribution, the office allocation, the primary and secondary circulation paths within the tower.
Connect Skyscraper Occupants
The Hutong Tower takes the example of a Paternoster, a circuitous elevator, to create a vertical street condition. In a typical building, the experience of moving through the building is similar to a vertical subway car. The activity on each floor is obscured from the traveler, who gets only a controlled glimpse into a floor that is usually only a blank wall. With the Hutong Towers, the occupant moves gracefully through the tower and experiences a vibrant community of more than 15,000 people.
Extend the Public Realm Vertically
In the case study project, a 80 story tower in Beijing is used. The tower is broken down into 10 and 15 story neighborhoods. At the intersection of each neighborhood, the elevator shifts to a horizontal motion for disembarking the vehicle. With six cars moving in both directions and a full revolution taking four minutes, the waiting period is minimal. The vehicle contains seats and even a small snack cart. The effect is a more connected vertical community as the occupants of the tower interact and experience the full range of activities that are supported by the tower.
We created a map for the interior of the building that is accessible from a mobile phone. The publicly accessible program within the building should be treated the same as those public spaces at the ground plane. The time that it takes to get to the top of the tower is equal to the map on the ground. A concert hall, sporting facility, museum and mall anchor the the major public spaces within the tower.
Building Information Modeling (BIM) is a term that has become ubiquitous in the design and construction fields over the past 20 years, but where did it come from? The story is rich and complex with players from the United States, Western Europe and the Soviet Block competing to create the perfect architectural software solution to disrupt 2-Dimensional CAD workflows. The benefits of an architectural design model tied to a relational database have proven to be incredibly valuable, with contractors becoming the primary drivers of BIM technology for the first time in 2012.
What exactly is BIM?
The question often arises, for the purposes of this article, BIM software must be capable of representing both the physical and intrinsic properties of a building as an object-oriented model tied to a database . In addition most BIM software now features rendering engines, an optimized feature specific taxonomy and a programming environment to create model components. The user can view and interact with the model in three-dimensional views as well as orthographic two-dimensional plan, sections and elevation views of the model. As the model is developed, all other drawings within the project will be correspondingly adjusted. A Building Information Model could be designed in a software that is not strictly speaking, ‘parametric’ and where all information and geometry is explicitly defined but this would be cumbersome.
A parametric building modeler will allow the user to create constraints such as the height of a horizontal level, which can be tied to the height of specified set of walls and adjusted parametrically, creating a dynamic database model which is tied to geometry. This development answered a need in the architectural industry to be able to change drawings at multiple scales and across fragmented drawing sheets. The amount of hours that are necessary for the production of drawings has decreased steadily over time with the general trend of non-farm labor in the United States since 1964. The improvement in productivity has risen in concert with computer technology which has automated tedious tasks in all disciplines. Although some of the earliest programs for architectural representation used a BIM metaphor, limitations in computer power and awkward user interfaces for BIM platforms contributed to a growth in two-dimensional line drawing programs such as AutoCAD and Bentley Microstation.
The conceptual underpinnings of the BIM system go back to the earliest days of computing. As early as 1962, Douglas C. Englebart gives us an uncanny vision of the future architect in his paper Augmenting Human Intellect.
the architect next begins to enter a series of specifications and data–a six-inch slab floor, twelve-inch concrete walls eight feet high within the excavation, and so on. When he has finished, the revised scene appears on the screen. A structure is taking shape. He examines it, adjusts it… These lists grow into an evermore-detailed, interlinked structure, which represents the maturing thought behind the actual design.
Englebart suggests object based design, parametric manipulation and a relational database; dreams that would become reality several years later. There is a long list of design researchers whose influence is considerable including Herbert Simon, Nicholas Negroponte and Ian McHarg who was developing a parallel track with Geographic Information Systems (GIS). The work of Christopher Alexander would certainly have had an impact as it influenced an early school of object oriented programming computer scientists with Notes on the Synthesis of Form. As thoughtful and robust as these systems were, the conceptual frameworks could not be realized without a graphical interface through which to interact with such a Building Model.
Database Building Design
Seeing buildings through the lens of the database contributed to the breakdown of architecture into its constituent components, necessitating a literal taxonomy of a buildings constituent parts. One of the first projects to successfully create a building database was the Building Description System (BDS) which was the first software to describe individual library elements which can be retrieved and added to a model. This program uses a graphical user interface, orthographic and perspective views and a sortable database that allows the user to retrieve information categorically by attributes including material type and supplier. The project was designed by Charles Eastman who was trained as an architect at Berkeley and went on to work in computer science at Carnegie Melon University. Eastman continues as expert in BIM technology and Professor at the Georgia Tech School of Architecture.
Eastman claims that drawings for construction are inefficient and cause redundancies of one object that is represented at several scales. He also criticizes hardcopy drawings for their tendency to decay over time and fail to represent the building as renovations occur and drawings are not updated. In a moment of prophecy, the notion of automated model review emerges to “check for design regularity” in a 1974 paper.
Eastman concluded that BDS would reduce the cost of design, through ‘drafting and analysis efficiencies’ by more than fifty percent. Eastman’s project was funded by DARPA, the Advanced Research Projects Agency and was written before the age of personal computers, on a PDP-10 computer. Very few architects were ever able to work on the BDS system and its unclear whether any projects were realized using the software. BDS was an experiment that would identify some of the most fundamental problems to be tackled in architectural design over the next fifty years. Eastman’s next project, GLIDE (Graphical Language for Interactive Design) created in 1977 at CMU, exhibited most of the characteristics of a modern BIM platform.
In the early 1980′s there were several systems developed in England that gained traction and were applied to constructed projects. These include GDS, EdCAAD, Cedar, RUCAPS, Sonata and Reflex. The RUCAPS software System developed by GMW Computers in 1986 was the first program to use the concept of temporal phasing of construction processes and was used to assist in the phased construction of Heathrow Airport’s Terminal three (Laiserin – History of BIM). The founding of the Center for Integrated Facility Engineering (CIFE) at Stanford in 1988 by Paul Teicholz marks another landmark in the development of BIM as this created a wellspring of PhD students and industry collaborations to further the development of ‘four-dimensional’ building models with time attributes for construction. This marks an important point where two trends in the development of BIM technology would split and develop over the next two decades. On one side, the development of specialized tools for multiple disciplines to serve the construction industry and improve efficiency in construction. On the other side is the treatment of the BIM model as a prototype that could be tested and simulated against performance criteria.
A later but prominent example of a simulation tool that gave feedback and ‘suggested’ solutions based on a model is the Building Design Advisor, developed at Lawrence Berkeley National Lab beginning in 1993. This software utilizes an object model of a building and its context to perform simulations. This program was one of the first to integrate graphical analysis and simulations to provide information about how the project might perform given alternative conditions regarding the projects orientation, geometry, material properties and building systems. The program also includes basic optimization assistants to make decisions based on a range of criteria which are stored in sets called ‘Solutions’.
While the developments were happening rapidly in the United States, the Soviet Block had two programming geniuses who would end up defining the BIM market as it is known today. Leonid Raiz and Gábor Bojár would go on to be the respective co-founder and founder of Revit and ArchiCAD. ArchiCAD developed in 1982 in Budapest, Hungary by Gábor Bojár, a physicist who rebelled against the communist government and began a private company. Gábor wrote the initial lines of code by pawning his wife’s jewelry and smuggling Apple Computers through the Iron Curtain (Story). Using similar technology as the Building Description System, the software Radar CH was released in 1984 for the Apple Lisa Operating System. This later became ArchiCAD, which makes ArchiCAD the first BIM software that was made available on a personal computer.
The software was slow to start as Bojár had to struggle with a unfriendly business climate and the limitations of personal computer software, so ArchiCAD was not used on large scale projects until much later. ArchiCAD has made substantial gains in user base from 2007-2011, mainly as a tool for developing residential and small commercial projects in Europe. Recent improvements have made ArchiCAD a major player in the market though fundamental issues such as a lack of a phasing component and a complicated (but flexible) programming environment for its family components using GDL (Geometric Description Language) remain. To date, Graphisoft claims that more than 1,000,000 projects worldwide have been designed using ArchiCAD.
Not long after Graphisoft began to sell the first seats of Radar CH, Parametric Technology Corporation (PTC) was founded in 1985 and released the first version of Pro/ENGINEER in 1988. This is a mechanical CAD program that utilizes a constraint based parametric modeling engine. Equipped with the knowledge of working on Pro/ENGINEER, Irwin Jungreis and Leonid Raiz split from PTC and started their own software company called Charles River Software in Cambridge, MA.
The two wanted to create an architectural version of the software that could handle more complex projects than ArchiCAD. They hired David Conant as their first employee, who is a trained architect and designed the initial interface which lasted for nine releases. By 2000 the company had developed a program called ‘Revit’, a made up word that is meant to imply revision and speed, which was written in C++ and utilized a parametric change engine, made possible through object oriented programming. In 2002, Autodesk purchased the company and began to heavily promote the software in competition with its own object-based software ‘Architectural Desktop’.
Revit revolutionized the world of Building Information Modeling by creating a platform that utilized a visual programming environment for creating parametric families and allowing for a time attribute to be added to a component to allow a fourth-dimension of time to be associated with the building model. This enables contractors to generate construction schedules based on the BIM models and simulate the construction process. One of the earliest projects to use Revit for design and construction scheduling was the Freedom Tower project in Manhattan. This project was completed in a series of separated but linked BIM models which were tied to schedules to provide real-time cost estimation and material quantities. Though the construction schedule of the Freedom Tower has been racked with political issues, improvements in coordination and efficiency on the construction site catalyzed the development of integrated software that could be used to view and interact with architects, engineers and contractors models in overlay simultaneously.
Towards a Collaborative Architecture
There has been a trend towards the compositing of architectural files with those of engineers who create the systems to support them which has become more prevalent within the past seven years as Autodesk has released versions of Revit specifically for Structural and Mechanical engineers. This increased collaboration has had impacts on the larger industry including a movement away from design-bid-build contracts towards integrated project delivery where many disciplines typically work on a mutually accessible set of BIM models that are updated in varying degrees of frequency. A central file takes an object and applies an attribute of ownership so that a user who is working on a given project can view all objects but can only change those that they have checked out of a ‘workset’. This feature released in Revit 6 in 2004, enables large teams of architects and engineers to work on one integrated model, a form of collaborative software. There are now several firms working towards visualization of BIM models in the field using augmented reality
A broad variety of programs used by architects and engineers makes collaboration difficult. Varying file formats lose fidelity as they move across platforms, especially BIM models as the information is hierarchical and specific. To combat this inefficiency the International Foundation Class (IFC) file format was developed in 1995 and has continued to adapt to allow the exchange of data from one BIM program to another. This effort has been augmented by the development of viewing software such as Navisworks which is solely designed to coordinate across varying file formats. Navisworks allows for data collection, construction simulation and clash detection and is used by most major contractors in the US today.
Following in the footsteps of the Building Design Advisor, simulation programs such as Ecotect, Energy Plus, IES and Green Building Studio allow the BIM model to be imported directly and results to be gathered from simulations. In some cases there are simulations that are built directly into the base software, this method of visualization for design iteration has been introduced to Autodesk’s Vasari, a stand alone beta program similar to the Revit Conceptual Modeling Environment where solar studies and insolation levels can be calculated using weather data similar to the Ecotect package. Autodesk, through their growth and acquisition of a broad variety of software related to BIM have contributed to the expansion of what is possible from analysis of a model. In late November 2012, the development of formit, an application that allows the conceptual beginnings of a BIM model to be started on a mobile device is a leap for the company.
Contemporary Practice and Design Academics
Some have taken a negative stance on BIM and parametrics as they assume so much about the design process and limit any work produced to the user’s knowledge of the program. This can enable a novice designer who has learned how to perform basic commands to become an incredibly prolific producer while a highly educated and experienced architect can be crippled from inexperience with a programs interface or underlying concepts. This creates a potential for a generational break line that becomes more harsh as a new technology gains market parity.
Some BIM platforms that have a small market share but have made big impacts on the world of design include Generative Components (GC), developed by Bentley Systems in 2003, and Digital Project (DP). The GC system is focused on parametric flexibility and sculpting geometry and supports NURBS surfaces. The interface hinges on a node-based scripting environment that is similar to Grasshopper to generate forms. Digital Project is a similar program was developed by Gehry Technologies around 2006 based on CATIA, a design program (and one of the first CAD programs) that was developed as an in house project by Dessault systems, a French airplane manufacturer. These two platforms have spawned something of a revolution in design as the power to iterate and transform has resulted in especially complex and provocative architectural forms.
Patrick Schumacher has coined the movement of parametric building models in architecture, specifically those which allow for NURBS surfaces and scripting environments as ‘parametricism’ in his 2008 ‘Parametricist Manifesto’.
“The current stage of advancement within parametricism relates as much to the continuous advancement of the attendant computational design technologies as it is due to the designer’s realization of the unique formal and organizational opportunities that are afforded. Parametricism can only exist via sophisticated parametric techniques. Finally, computationally advanced design techniques like scripting (in Mel-script or Rhino-script) and parametric modeling (with tools like GC or DP) are becoming a pervasive reality. Today it is impossible to compete within the contemporary avant-garde scene without mastering these techniques.”
Since these techniques have become increasingly complex there has become a component of architectural schools which is specified to train in specific software. A student with knowledge of only one type of software platform may well be trained to design according to the biases of the programs that they are using to represent their ideas. Software performs useful tasks by breaking down a procedure into a set of actions that have been explicitly designed by a programmer. The programmer takes an idea of what is commonsense (Sack 14) and simulates a workflow using tools available to them to create an idealized goal. In the case of BIM tools, the building is represented as components including walls, roofs, floors, windows, columns, etc. These components have pre-defined rules or constraints which help them perform their respective tasks.
BIM platforms typically represent walls as objects with layers, these layers are defined in terms of the depth and height of a wall and are extruded along the length of a line. The program then has the ability to calculate the volume of material contained within the wall assembly and to create wall sections and details easily. This type of workflow is based on the existing building stock and common industry standards and therefore a project which is produced in a BIM platform which emphasizes these tools is likely to reinforce existing paradigms rather than develop new ones. Additionally, the programmers who worked on the early BIM platforms often did not have a background in architecture but employed hybrid architect/programmers who contributed to the development of the programs. One notable exception I have found to this is the work of Charles Eastman who received a Masters of Architecture from Berkeley before working on the Building Description System. The roots of the major BIM platforms that are in use today have been developed by programmers with the peripheral input of hybrid programmer/architects and a global user base who contributes to the development of the software via ‘wish lists’ or online forums where grievances can be aired about a product workflow. The grievances typically result in new features and build upon the existing interface.
Though the general concept and technology behind BIM is approaching its thirtieth anniversary, the industry has only begun to realize the potential benefits of Building Information Models. As we reach a point where a majority of buildings are being crafted digitally, an existing building marketplace where building materials and structural components can be bought and sold locally will emerge. Sustainable design practices reinforce an attitude of designing for disassembly and a marketplace of these parts is essential. Trends in Human Computer Interaction, Augmented Reality, Cloud Computing, Generative Design and Virtual Design and Construction continue to rapidly influence the development of BIM. Looking back at the past it is easier to realize that the present moment is an exciting time for designers and programmers in this evolving industry.
Michael S Bergin is a Researcher at Architecture Research Lab.
* This paper is in progress. Check back for updates and please leave a comment if have a source, primary information or factual dispute.
Chuck Eastman, Paul Teicholz, Rafael Sacks, Kathleen Liston – The BIM Handbook
Malek S. – CAD/BIM Timeline
Charles Eastman – What is BIM?
Various at AUGI – The Origins of Revit
Lachmi Khemlani – AEC Bytes / Revit 6
Marian Bozdoc – The History of CAD
Jeremy Tammik – The History of Revit and its API
The SpaceLab is an experimental facility for the production of test environments, facilitated by the Adaptive Construction System. The 6400 SF office is associated with on-site dwellings and a test site for built simulations up to a 5000 SF footprint and three stories. Located in Petaluma, California, the project takes advantage of a neglected site near the center of town adjacent to iconic grain silos and a railroad station. The dynamic nature of the building advertises the services and presence of the SpaceLab within the city.
The system works by analyzing a series of conceivable operations to plan for the city at a moment in time. Data is collected from the inhabitants of the city regarding their favorite places within the city, most traveled and most congested areas and spaces of neglect. The development of the city is deliberately slowed in order to encourage a successful community that does responds to the real needs of its inhabitants.
The development is built into three main types; towers, webs and courtyards. Courtyards support low density development up to three stories in height. Webs are anywhere from six to ten stories in height and subdivide the kilometer square site. Towers occur at high density intersections of webs and grow incrementally from thirty to eighty stories tall.
This was one of my first experiments with generative design tools. A tower is created and constrained to create a design space that supports a eighty story tower for Beijing, China. The mesh model was output to Ecotect, analyzed for solar radiation and the results were reported to the evolutionary solver, Galapagos.
Video of an earlier experiment…]]>
See Michael’s blog at Archinect.
at Huffington Post
at The Guardian
We fashioned a bench, two chairs and a small table.
The view of Bass Harbor Light at Sunset is now much more enjoyable.]]>
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