Publications related to Design and Media Laboratory (ENAC/IC)

2020

Design of a light-shaping adaptive facade using fiber-reinforced polymer materials

2019

Shaping light to influence occupants’ experience of space: a kinetic shading system with composite materials

Marilyne Andersen, Joëlle Baehr-Bruyère, Kynthia Chamilothori, Anastasios Vassilopoulos, Jan Wienold

Adaptive kinetic façades are systems capable of modifying their shape to optimize their behavior regarding real time outdoor and indoor conditions. They are typically evaluated based on quantifiable physical parameters such as illuminance levels, with little attention – for lack of evaluation criteria – given to subjective appreciation of the façade and the resulting daylight patterns. The present study investigates the daylighting performance of a kinetic shading system based on simulations combined with physical mock-up testing, to assess its viability as an alternative shading solution that complements conventional functions by enhancing the occupants’ experience of the space. Based on performance assessment and perceptual studies, the shortcomings of traditional blinds are identified and a promising prototype design, controlling the blinds’ opening by means of torsional deformations, is proposed.

IOP Publishing2019

The spatial and formal conception of architecture, and thus its modes of design perception and representation, directly contributes to its machine-learnability; and consequently, its capacity in leveraging today's machine learning apparatus for design innovation. If text can be sampled and synthesized in Natural Language Processing, image in Image Processing and sound in Audio Signal Processing, how can architectural forms and spaces be likewise sampled for generating new designs? The thesis endeavours to construct such a theoretical and technical framework with the concept of architectural sampling -- defined as the exemplar-learning (pedagogical), the machinic encoding (technological) and probabilistic generation (aesthetical) of architectural forms. Foundational to this technical leap is the overcoming of architecture's own longstanding set of conceptual and perceptual assumptions, namely figure/ground, parts/whole and shapes/grammars; and replaced with one that is ontologically 'flattened', 'resolutional' and 'probabilistic'. The thesis samples precursory works from the history of architecture, alongside machine learning approaches, to build its theoretical claims; while algorithmically demonstrating and technically validating them through a series of design research projects organized according to their structural characteristics (grid, sequence and hierarchy). The contribution of the work lies in its fundamental reformulation of seeing, thinking and making architectural forms through the lens of machinic sampling.

EPFL2019

Citizen Visual Search Engine: Detection and Curation of Urban Objects

Jeffrey Huang, Immanuel Chee Beng Koh

Increasingly, the ubiquity of satellite imagery has made the data analysis and machine learning of large geographical datasets one of the building blocks of visuospatial intelligence. It is the key to discover current (and predict future) cultural, social, financial and political realities. How can we, as designers and researchers, empower citizens to understand and participate in the design of our cities amid this technological shift? As an initial step towards this broader ambition, a series of creative web applications, in the form of visual search engines, has been developed and implemented to data mine large datasets. Using open sourced deep learning and computer vision libraries, these applications facilitate the searching, detecting and curating of urban objects. In turn, the paper proposes and formulates a framework to design truly citizen-centric creative visual search engines - a contribution to citizen science and citizen journalism in spatial terms.

SPRINGER INTERNATIONAL PUBLISHING AG2019

Architecture in the Data-driven City

Frederick Peter Ortner

In the last ten years, new sources of urban big data have made it possible for algorithms to increasingly control how the city is perceived, understood and managed by its inhabitants; this is the data-driven city. New efforts in the social sciences, like critical data studies, are beginning to describe the ways in which urban data is never completely objective and how its logics influence and shape our everyday physical world. In this thesis I transfer insights from critical data studies to architecture, asking how the emergence of data-driven urbanism is influencing architecture as practice and artifact and, conversely, what impact architecture can make in an urban context dominated by big data. To answer these questions I take on three place-based case studies which highlight controversial urban problems managed by automated practices of measuring, mapping and procedural response: aviation noise near Heathrow Airport, storm floods in Amsterdam and population density in Singapore. Though data-driven, these cases nonetheless demonstrate the persistent importance of the design of the built environment to the function of these urban systems. To make a comparative analysis of the three case studies and to provide a framework to interrogate the impact of architectural interventions, I introduce a new conceptual tool: the data-genealogy tree. I use the data-genealogy tree to (1) chart how metrics, institutions, architectural elements and software are brought into a data-mediated socio-technical system, (2) to assess over time the growing embeddedness of this socio-technical system in each case study, and (3) to identify reorientation points when motivations of the socio-technical system have changed and innovations emerged. Examining the association of architectural artifacts with the reorientation points charted in the data-genealogy tree makes possible an assessment of the impact of architectural interventions and provides a basis for describing more generally how the architect may seek to influence the development of the data-driven city. As an ensemble, the architectural interventions described in the case studies also provide evidence for a description of the formal evolution of architecture in the data-driven city. The case studies suggest that singular architectural artifacts are less relevant to this context than catalogues of architectural elements which are made open to quantification and tracking and can assemble into many possible configurations in response to the demands of urban systems. Finally, I consider how design process is changing in the data-driven city, describing how architects in the case studies have worked with urban data to cross disciplinary silos or recruit wider stakeholder participation in consensus design solutions.

EPFL2019

DIII-D research towards establishing the scientific basis for future fusion reactors

Terunobu Akiyama, Alessandro Bortolon, Xi Chen, Wilfred Anthony Cooper, Huan Du, Yu Fu, Jérôme Guterl, Federico David Halpern, Jeffrey Huang, Kyungjin Kim, Ji Hyun Kim, Sun Hee Kim, Fang Liu, Alessandro Marinoni, Gabriele Merlo, Stefan Müller, Richard Pitts, Mario Podesta, Francesca Maria Poli, Olivier Sauter, Zheng Wang, Yi Wang, Hui Wang, Wei Wu, Gang Yu, Bingying Zhao

DIII-D research is addressing critical challenges in preparation for ITER and the next generation of fusion devices through focusing on plasma physics fundamentals that underpin key fusion goals, understanding the interaction of disparate core and boundary plasma physics, and developing integrated scenarios for achieving high performance fusion regimes. Fundamental investigations into fusion energy science find that anomalous dissipation of runaway electrons (RE) that arise following a disruption is likely due to interactions with RE-driven kinetic instabilities, some of which have been directly observed, opening a new avenue for RE energy dissipation using naturally excited waves. Dimensionless parameter scaling of intrinsic rotation and gyrokinetic simulations give a predicted ITER rotation profile with significant turbulence stabilization. Coherence imaging spectroscopy confirms near sonic flow throughout the divertor towards the target, which may account for the convection-dominated parallel heat flux. Core-boundary integration studies show that the small angle slot divertor achieves detachment at lower density and extends plasma cooling across the divertor target plate, which is essential for controlling heat flux and erosion. The Super H-mode regime has been extended to high plasma current (2.0 MA) and density to achieve very high pedestal pressures (similar to 30 kPa) and stored energy (3.2 MJ) with H-98y2 approximate to 1.6-2.4. In scenario work, the ITER baseline Q = 10 scenario with zero injected torque is found to have a fusion gain metric beta(TE) independent of current between q(95) = 2.8-3.7, and a lower limit of pedestal rotation for RMP ELM suppression has been found. In the wide pedestal QH-mode regime that exhibits improved performance and no ELMs, the start-up counter torque has been eliminated so that the entire discharge uses approximate to 0 injected torque and the operating space is more ITER-relevant. Finally, the high-beta(N) (

2019

Design of a light-shaping kinetic facade using FRP materials

Joëlle Baehr-Bruyère

2019

Growth Typologies, Localities and Defamiliarisation Experiments with Artificial Urbanism in Sichuan, Guangzhou and Beijing

Jeffrey Huang

The unprecedented speed of urbanization in Asia calls for a fundamental rethinking of urbanism. Conventional master plans typically propose a single static ‘end’ condition derived from top-down visions, often incapable of responding to site-specific microclimatic, topographical and social conditions. In this article we discuss the notion of “Growth Typologies” a key concept we are exploring within our project “Artificial Urbanism” at EPFL and at the Singapore University of Technology and Design (SUTD). Growth Typologies consist of a lab component and a field component. In the lab, local typologies are dissected, analyzed and recomposed as algorithmic code with the objective to liquefy the original typologies and enable them to adapt and grow based on ecological parameters. In the field, we use real sites in rapidly urbanizing regions in China (Qilonghu, Leshang, and Haizhu) as case studies for testing Growth Typologies. Seeding and populating Growth Typologies in the field involves a process of “iterative defamiliarization” where familiar typologies are algorithmically estranged to meet ecological demands and aspirations of social sustainability in each of the locales.

Wiley Periodicals, Inc2015

Code and its image: the functions of text and visualisation in a code-based design studio

Jeffrey Huang, Guillaume Labelle, Mark Meagher, Trevor Patt, Nathaniel Zuelzke

Traditionally, design learning in the architecture studio has taken place through a combination of individual work and joint projects. The introduction of code-based design practices in the design studio has altered this balance, introducing new models of joint authorship and new ways for individuals to contribute to co-authored projects. This paper presents a case study describing four design studios in a higher education setting that used code as a tool for generating architectural geometry. The format of the studios encouraged the students to reflect critically on their role as authors and to creatively address the multiple opportunities for shared authorship available with code-based production. The research question addressed in this study involved the role of code-based practices in altering the model of architectural education in the design studio, in particular the role of visual representations of a code-based design process in the production of shared knowledge.

Routledge Journals, Taylor & Francis Ltd2015