K9K | Holistic
Architective Agency
Motivation
The
theories of architecture, building technology and the simulation of the
building systems are always attractive to me. I imagine that, in the future, I
can establish an R&D lab, K9K, in which I can push the theories and
building technology forward, meanwhile the theories can be implemented in
some real projects.
K9K
basically is working on two fields of study, design theory and fabrication. The
research of design theories is to establish the mathematical models of
architecture design, digital fabrication, interactive architecture, etc.
Fabrication research is focusing on discovering new architectural materials,
studying automatic fabrication, developing building technologies,
etc. One field is in virtual world and the other is in a physical world. Although
the goal of K9K is to connect these two world, I still think we should
approach this goal in two different ways.
Multidisciplinary Research
Because
of my EE (electrical engineering) and architectural background, I
am looking for the opportunity to combine these two
alternative fields of study I've involved in. I believe that some
technologies from EE can be used in architectural field, for instance, machine
learning, digital communication, recognition technology and digital IC design.
Digital IC design is one of my professional skills, especially in digital
communication systems. Hence, I keep trying to bring some concepts
and methodologies into architecture design.
Not
only electrical engineering, but also other fields of study are welcome in
K9K. I believe that we should re-think the design in a more holistic way.
Hence, multidisciplinary study will be the principle in K9K. Everything is
relative to one another, and all the theories may be the elixirs in
different fields. By integrating different fields of research, we may find
more creative solutions for architects.
Business
Mode
The aim of K9K is to keep generating pioneering
technologies and accumulating the knowledge for architects. The income of this
lab may be from exporting technologies and transferring patents. In fact, it works like most consultant
companies, K9K will cooperate with architects, contractors or manufacturers. Also, K9K can
be an educational institute for those students who are just graduated from
school. K9K can also be
viewed as a post-research institute and help students complete the first
practice work in which they still can test some new
ideas. Furthermore, K9K offers not only the consultant services but also the
advanced products. Hence, the short term goal of K9K is to be a professional
consultant institute and solution provider for architects. For the goal of long term, K9K will be able
to produce some advanced products and patents, which may be the main financial
source of K9K in the future.
Structure of K9K, T.C. Kurt Hong, Summer 2015
Archive
As a research institute, accumulating
knowledge is a critical work for K9K. K9K will keep generating technologies,
meanwhile, K9K will keep documenting all the experiments including the process
and the result as the references for architects and educators. The research
data should be archived and well-organized for the next generation. K9K
attempts to be the library which keeps
updating knowledge and a platform for architecture
professionals.
RESEARCH
| Mathematical
Models
Mathematical
model for digital fabrication
While
I was making the models with the machines and the digital tools, an idea
occurred to me that some concepts from digital communication could be used
in the theories of digital fabrication. For example, the behavior of the
digital fabrication may be described as a equation as below:
Y
= HX + N ;
In
this equation, "X" is the digital model and "Y" is the
physical result, "H" is the feature of the machines or the
tools, "N" means the noise while manufacturing. Actually, it is a
fundamental representation of digital communication. I think
this equation is suitable for digital fabrication because the
whole process is similar to communication. The digital model can be viewed
as the message we want to transmit, and the physical result is the
message we actually receive, the manufacturing process is like the channel
which has some effect on the transmitted message, and, of course, we have some
inaccuracy which is like the noise. Assume that we use this model to describe
the process of fabrication, we can observe that the H and the N are not welcome
in fabrication since they cause the distortions. Therefore, we may need some
methods to remove them. Once we can remove the effects and the noise
from the manufacturing, we may connect virtual world and physical
world seamlessly.
However,
most architects work without the mathematical models and hence they can
hardly analyze their design process systematically. If there is
a systematic methodology which can analyze the process of design
for architects, they can check where the errors are and avoid them in
advance. The equation above may not be the best way to describe the
process, but we can keep looking
for other mathematical models for architectural
design. Furthermore, I proposed a method to analyze the systems in
architecture in my graduation thesis[1]. Although it is still primitive, I
believe that we can use this method to establish the mathematical
models.
Equalizer
in Digital Fabrication
In
the previous section, the equation "Y=HX+N" is proposed as the basic
mathematical model for digital fabrication. This equation will be pushed
further to eliminate the gap between digital model and physical result in this
section.
Assume
that we use Rhino (or any other software) to draw a solid cube on the
computer, and we use a CNC router drilling the foam to implement it.
However, the physical cube might be a little different from the cube in the
computer, including the tool marks, the texture of the material or other
distortions. The entire process can be viewed as a type of
communication, the virtual model (the cube on Rhino) is the message we
want to transmit, the physical model (the foam cube) is the message received,
and the CNC router is the channel which the message pass through. In fact,
the difference between virtual model and physical model is similar to the
channel effect in digital communication. Typically, the engineers would use
some methods to eliminate the effect to make the original signal (virtual
model) approximate to the received signal (physical model).
To
eliminate the distortion, we can feed the information of the
distortion back to the digital design tools, and make prevention in
advance. This method is called equalization which is similar to the
prestressed design in civil engineering, and actually we may find many cases in
architectural and industrial design. For example, a famous Japanese
architect, Jun'ya Ishigami, designed a table with this concept. In this
design, he fed the gravity factors back to the virtual model to obtain a
prestressed structure.
Table, Junya Ishigami, 2005-2006
The mathematical model of equalization can be
described as below:
Y
= HX +N ;
E
is defined as Y/X ;
E
= H + N/X ;
H
= E - N/X ;
H
approximates to E ; ( Ignore N if N is small enough or X is large
enough )
The
goal is to find X' to achieve Y=X;
X
= HX' + N ;
X'
= (X-N)/H = X/H -N/H ;
X'
= X/E - N/E ; (Ignore N if N is small enough )
X'
= X/E ; (Equalized Models)
Y'
= H(X/E) + N ;
Y'
= H(X/(H+N/X)) +N ;
Y'
= HX/(H+N/X) + N ;
Y'
= HX(H-N/X)/(H^2 - (N/X)^2) + N ;
Y'
= H^2X -HN/ H^2 +N ; ( (N/X)^2 is small enough )
Y'
= X- N/H + N ;
Y'
= X + N ; (N/H +N can be viewed as N )
The
error = N ; The manufacturing effect is equalized ;
According
to the equation above, the fabrication process can be equalized to obtain a
result approximating to the original design. The error left is the noise during
manufacturing, which can be reduced by other methods.
In
Sean Ahlquist's lecture, we had a conversation about the simulation and
physical models. It is hard to analyze the behavior of fabrics because the
forces from fabrics are so complicated. However, we may use
Kinect to capture the deformation and establish a new digital model. Then, we
may use this new digital model to obtain the equalization factor (E), and we
can reduce the distortion in the next work. We don't need to analyze the force
from each fabric, all we need is the factor, which can be calculated after the
experiment. Furthermore, if we take advantage of machine learning mechanism,
the digital tools may be trained well after several feedback
iterations. Equalization is just one of the possible theories in
digital communication which can be adopted in digital fabrication, I believe
that more theories can be developed for digital fabrication.
Architecture
Description Language (ADL)
Comparing
to other fileds of study, architectural design is basically on modeling-based
tools such as Rhino, Revit, AutoCad and SketchUp. However, we
may just describe the functions, the systems or the spacial
relationships, in other words, the logic of the design, and let computer
generate the forms for us.
In
IC design industry, engineers adopted scripting-based design in 1984, even earlier [2].
In the beginning, IC designers drew the electrical layouts by hands, and
they tried to arrange those transistors and wires to obtain optimized results,
for example, smallest area or highest speed. But, quickly they gave up the
hand drawing and turned the process into scripts. The engineers use computers
to generate the optimized results, all they need to do is to describe the
behaviors (logic) of the circuits. Hence, the IC design industry emerged in a
extremely pace, because the designers have more time and energy to design the
circuits in a higher level, and therefore they can create high complex chips
(imagine that if the engineers have to draw 1.4 billion transistors in
Intel CPU by hands). It turns out, human beings started to create the
product with intelligence such as the computers, laptops, tablets or smart
phones.
Although
the architects nowadays adopt some scripts to design such as
Grasshopper, Processing or CityEngine, most architects still use modeling-based
tools, some even draw by hands. In other words, we keep
using the limited calculation power (human brains) to optimize
the entire architecture. Once we use the description language to design a
building, one of the advantages is "Design Rule Check (DRC)".
While designing a building, there are many rules and limitations, thus the
architect may need an additional person to check all the rules for
architect. Sometimes some rules may be ignored and hence it may cause architect
and client extra time and cost to fix it. DRC helps architect check all the
rules in advance, and architects can adopt different libraries according to
different country or environments. This concept is from IC design, this tool is
important because the manufacturing cost of IC is extremely high, engineers
have to exclude all the possible bugs before tape-out. The feature, high
manufacturing cost, is similar to architecture, thus I think we
may introduce this idea to architecture.
The
second advantage of ADL is that architects can use computer to optimize
the design. Once the architects can script the logic of the architecture,
the computer can generate all the possible models. And, architects can input
different constrains such as minimum area, minimum budget or maximum capacity
to obtain alternative optimized results. It is like the
parametric design, the difference is that architects describe the logic rather
than the forms while designing. Moreover, this language may be the
foundation of automatic design, which will be elaborated in the next section.
The structure of ADL can be
described as below:
Flow Chart of ADL, T.C. Kurt Hong, Summer 2015
RESEARCH
| Machine
Learning
One of the concepts that I am eager to
apply to architectural design is "Machine Learning". Also,
machine learning may be applied on both software development and physical
fabrication. Moreover, I think machine learning may be the key of the
building technology evolution.
Pixelwise Context-aware Semantic Segmentation
Meta-Design
In physical aspect,
robotic fabrication is the focus in building technology. However, the
robots can be more intelligent and thus help architects deal with the
issue about construction. For example, the automatic vacuum robot, iRobot,
is equipped with some simple algorithm to learn how to optimize the path while
it is cleaning a house. The robot can collect the data from environment
and keep calculating the best solution in its brain. Hence, if we equip a
mechanism on robots which allow robots to collect data through fabrication
every time, the robots can operate more efficiently and gradually learn how to
fabricate by itself.
However, automatic
fabrication is the first level application of machine learning. In
software aspect, machine learning can be the core of the smart
software for architects, furthermore, it may also be the kernel of
the automatic design. In the future, the robots may design architectures
just like what architects do now. Not only doing optimization, evaluation,
analysis for architects, but also creating architectures. That means architects
have more energy and time to design in a higher level and lead architecture to
the next phase.
"A city is not a
tree" [3], a famous article of Christopher Alexander, in which a concept
is depicted that there are enormous systems in our circumstances. Architects
may easily ignore the systems hidden in the environment and make some terrible
decisions. There are too many systems to analyze, therefore, architects can
hardly optimize the design without a powerful analysis tool. Hence, the
parametric design showed up in the recent years. Architects tried to
convert the modeling design to script design in order to obtain more
information from environment to optimize the design. With scripting,
architects can try a spectrum of parameters and simulate the result in
virtual environment. However, the parametric design might be upgraded to a
higher level, automatic design. Automatic design can collect all the coherent
information and calculate a optimized result for client. The design
can be generated by an AI system, especially the design is an optimized
design which is considering all the systems and factors. Or, the AI system
can calculate all possible designs and pick up the best one for
architects.
For
instance, Google and Amazon are trying to build up a system which can
analyze all the data collected from the world. Amazon is working on the the
prediction of the shopping behavior of human beings, and Google is working on
IoT technology which can connect all the objects in a house and make the
house smarter. Furthermore, Google is also working on big data analysis, which
is the kernel of development of the AI system. In fact, the
fundamental technology of those applications such as AI, IoT, big data and
prediction of human beings, is machine learning. Therefore, I believe that the
architecture design will get a great leap by adopting this technology. On the other
hand, in the future, architects' job is to design the algorithm of automatic
progress, and that is the second level of design.
System Description, Tzu-Chieh Hong, 2014
Intelligent
& Interactive Design
In my third year in architectural college, our assignment
is to design an interactive installation in the studio. From that time, I
keep researching the interface between human and architecture. Typically, we
treat architecture as a container and human being is the content inside. Or, we
treat the architecture as a sculpture and human being is the viewer outside. It
is arbitrary that I use only two relationships (actually many architects have
designed a lot of architectures which are aimed to blur the boundary
between inside and outside). However, most of the relationships between
architectures and human beings are single directional. The relationships are
static and monotonous. Recently, architects are trying to endow architecture
with more ability to response human beings. Thus, the interactive design turns
into a popular topic in architecture study.
Boundary Functions, Scott Snibbe, 1999
The first level of engagement:
Respond like a mathematical function.
The interactive
architecture nowadays contains a simple algorithm, it responses back to people
according the inputs that people give to it. In fact, it is like a vendor
machine or an automatic door, it responses people in a simple way. There
are a lot of applications of this kind of interaction.
The second level of engagement:
Respond like a Siri.
In the second level of
engagement, the interactive architecture can collect data from users and adjust
the response modes. According to the behavior of the subject, the architecture
can learn from the subject and train itself to create a dialogue with the
subject. Meanwhile, the architecture can connect to the internet and
communicate with other objects to gather more information to build up the
specific response mode.
The third level of engagement:
Respond like a person.
The next phase of
interactive design is to create a brain for an architecture. The brain can not
only think but also create something. In the book, "What Technology
Wants" by Kevin Kelly, the author depicts that everything will have a
small brain, which is a microchip, and those brains are connected to one
another as a big network just like the concept of IoT [4]. Therefore, the
network is like neuron network in human's brain, it can think, even create. In
the future, the architecture will be equipped with this ability to think like a
person, even smarter, and it can create some wonderful things for human beings.
For example, a computer in an old movie, Electric Dreams (1984) [5], composed a
song for the girl it loved. The music is beautiful and full of emotion.
From this perspective, the ultimate goal of interactive design is to
create a "human-like" machine which has the ability to create.
However, I think the ultimate goal is not to create a human-like machine but
create an AI system better than human. The machine can think more
holistically than human beings do, it won't ignore any information and simplify
the problem.
RESEARCH
| Fabrication
Material Research
Discovering new
architecture materials is also a critical research topic in K9K. Ten
decades ago, architects adopt new materials such as glass, concrete and
steel as the new material in architecture. After a century, we are still using
glass, concrete and steel as the main materials in architecture. In automobile
industry, plastic or carbon fabric is very common. Apple
adopt sapphire crystal as the new material of the screen of iPhone, now
the sapphire crystal is very common in smart phone design. Before that, Apple
used uni-aluminum piece and CNC router to manufacture MacBook. Television
industry replaced CRT with LCD to reduce the size, recently the television
industries adopted OLED and ePaper to obtain a banding screen and save more
energy.
New material can
always push an industry forward. Even though the architecture industry is too
complex to catch up the pace of other industries, we can still try some
advanced material in architecture. For example, the ePaper may be used as the
wall paper in a house to display the information for people. Transparent
solar panel may be the substitute of glass, it can be a good insulation
material and generate power for people. Furthermore, the new material
should be energy productive, intelligence embedded, and environmental
friendly. One of the jobs in K9K is working on the research of new
material and make prototypes for architects. Architects may purchase the
simulation results from K9K before they spend lots of money on an unknown
material. K9K can cooperate with material suppliers as an institute to test and
verify the product from architect's perspective.
Energy Productive Brick, Tzu-Chieh Hong, 2014
Automatic Fabrication
Besides the limited
materials, today we still use a lot of human power to build a house, even
though we use pre-fab system. Why can't we just let house grow by itself? I
imagine that we can place some materials around the site and
let several robots build a house automatically. Those robots can work like
human workers, they can detect the weather and communicate with each other. The
building work load is distributed to each robots automatically, and the working
schedule can be optimized. Furthermore, the robots can adjust the
schedule and fabrication process according to the unexpected factors they
detect.
Robotic Fabrication, University of Michigan
Skylar Tibbits, a
professor in MIT, has a lab which is focusing on self-assembly systems in
architecture. His research is to develop the objects which can aggregate
themselves to form a building (or a structure). However, we may approach
this goal in a different way. Instead of producing lots of special components,
we can let robots to build our house with normal materials. Nevertheless, the
robots today just follow a fixed plan to operate. Actually they can't think and
response to un-expected factors. What if we equipped those robots with the
ability of machine learning? They may be more efficient, smart and robust. Once
the robots can train themselves and train other machines to build a house, we
may make building technology a great leap. And the key of this evolution
is machine learning.
Furthermore those
robots can arrange the whole schedule of construction by themselves according
to budget, supply chain, design complexity, etc. They will connect to the
entire supply chain and estimate the delivery time of each material, and
thus optimize the storage and the time.
Conclusion
The multidisciplinary
research is always what I am interested in, it requires the cooperation among various
people with various backgrounds. K9K is an institute which offer a platform and
resources to connect them together and implement the ideas. The machine
learning, AI system or the technologies mentioned in previous sections are just
a small part of the possible technologies which can be applied to
architecture design, there are still a lot of possibilities for K9K. Therefore,
keeping introducing other knowledge into architecture design is the main task
of K9K. D-School in Stanford University, ISD in University of Michigan and
TDIS in National Chiao Tung University are similar models for K9K, even though
their multidisciplinary research is based on educational purpose. To sum up,
even though it is hard to run a firm like K9K, I will still be dedicated to
multidisciplinary research.
Reference
Footnotes
[1] Sharing Components - Multi-Systems & Uni-Solution,
Tzu-Chieh Hong, September 2014.
[2] Verilog, the description language for IC design, 1984
[3] A City Is Not A Tree, Christopher Alexander, 1965
[4] IoT, Internet of Things:
IoT is another
developing concept in architecture. All the objects can communicate with
each other, ,and thus the human behaviors can be predicted. Furthermore, the
entire house can operate according to the people living inside. Also, the
house can detect the circumstances to adjust the energy output to achieve a
more efficient mode. However, the IoT technology requires many skills from
computer science and electrical engineering, the architects can hardly realize
the theory behind the operations. To eliminate the gap, K9K can be the
bridge and develop the IoT kit for architects and simplify the interface.
[5] Electric Dreams, Virgin Films, 1984
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