1. Digital Intuition Cluster, Smart Geometry 2013, Stylianos Dritsas, Mirco Becker, David Kosdruy, Juan Subercaseaux Welcome Notes Overview 1. Perspective on Uncertainty 2. Tracks of Inquiry 3. Palette of Methods 4. Schedule 5. Preparation

2. Digital Intuition Cluster, Smart Geometry 2013, Stylianos Dritsas, Mirco Becker, David Kosdruy, Juan Subercaseaux Welcome Notes Perspective on Uncertainty Uncertainty springs from our inability to foresee the implication of early design actions across stretches of time and scales of space. Our approach is centered about augmenting intuition by enabling prediction via computation. We offer systems design methods to improve conventional architectural and engineering workflows such as parametrics, building information modeling and computational form-finding techniques Generality: They are applicable to a wide range of design challenges such as massing, cladding, fabrication, prototyping etc. Our aim is to create an advanced computation cluster to attract high level skill people. The implied challenge is what is computation beyond the current state of things ~of/for the future

3. Digital Intuition Cluster, Smart Geometry 2013, Stylianos Dritsas, Mirco Becker, David Kosdruy, Juan Subercaseaux Welcome Notes Tracks of Inquiry Experimentation: targets generation of intractable permutations /undrawable designs/ by conventional modeling methods; a track suited for participants that would like to learn how to create designs within simulated environments. Optimization: targets improvement of intractable solutions /unsolvable design/ by conventional modeling methods; a track suited for participants interested in developing advanced techniques for practical design problems. In reality we are talking about the same integrated approach but we acknowledge that there subtle positional preferences and perspectives.

4. Digital Intuition Cluster, Smart Geometry 2013, Stylianos Dritsas, Mirco Becker, David Kosdruy, Juan Subercaseaux Welcome Notes Palette of Methods Geometry: Associative methods revisited. These methods are for people more comfortable with visual (geometric) representations and traditional parametric modeling techniques. Physics: Equilibrium search methods. These methods are ideal for people with perhaps engineering background (thinking of other dimensions beyond geometry such as masses and forces). But also those who wish to experiment with dynamics and physics in form-finding. Numerical: Abstract computation methods. These are mathematical modeling and programming approaches which the least visual but founded in algorithmic and numerical concepts.

5. Digital Intuition Cluster, Smart Geometry 2013, Stylianos Dritsas, Mirco Becker, David Kosdruy, Juan Subercaseaux Welcome Notes Schedule Day 01: Descriptive Systems (Generating) Introduction to methods and tools. Assessment of case studies. Identify whether they fit within any classical paradigm or require a novel algorithmic approach. Scope up/down projects to fit time frame of workshop. Layout a computational (re)design strategy suitable for our framework. Begin implementation. Day 02: Design Analytics (Understanding) Continuation of implementation process and introduction to virtual cost metrics: functions that evaluate the design performance at a current state or dynamically in case of simulated optimization. The goal is to (a) build your own analysis system from bottom- up or (b) adapt a common / off the shelve methodology using structural engineering, environmental etc analysis modules to form composite design metrics. Day 03: Optimization Strategies (Selecting) Extension of analysis and design integration of optimization systems. We begin from brute-force mappings of parametric and solution spaces to understand complexity. Then move to heuristic search eg. divide and conquer, branch and bound, and other AI methods and/or directly use simulation in way of finding balance/equilibrium between desires and affordances. Day 04: Systems Design (Evaluating) We continue on previous work and introduce high-level design operations from systems design theory such as sensitivity analysis ie. if we change input parameters ever so slightly how far is the design moves? The goal is to collect indicators as per uniqueness and stability. We map optimization outputs (perform multiple optimizations over parameter ranges) and contrast with man-made variations. We measure operation depth to derive predictability metrics. We segment the solution spaces in regions to understand design neighbourhoods.

6. Digital Intuition Cluster, Smart Geometry 2013, Stylianos Dritsas, Mirco Becker, David Kosdruy, Juan Subercaseaux Welcome Notes Preparation Participants should bring a design study that has been thoroughly developed in the past and they wish to experiment with integrating advanced computation systems of simulation and optimization. Successful case studies may either focus on either early design explorations or design development and construction related problems. Please prepare a one/two page brief of your project and post us [add_date] so we can better plan ahead