RESEARCH

D.DLAB [DISRUPT.DESIGN]

D.DLAB develops design-led technological projects utilizing scientific and spatial innovation towards real-world impact. Supporting collaborations between architects, scientists, engineers, and creative minds, we serve as a launchpad for the exchange of ideas between academia and industry.

1. DIGITAL MANUFACTURING OF AND WITH MATERIALS
We engage with current exposure to new modes of production through advances in the fields of material science and automation processes enabling designers access to intricate material resolution and algorithmic profiles of matter. Colliding advanced computation into new making techniques enables us to re-invent manufacturing procedures and propose novel expressions from creative material robots to architectural structures.
Researchers: Erez Ezra, Avraham Cohen, Rafael Fogel

Pre-Programmed Material Composites
Developing post-fabrication material expression to enhance human:facade and facade:environment interactions throughout the building lifecycle. Understanding the operability of material composites within current thin-film printing processes enables us to discover new narratives for material performance and explore how their dynamic behaviour may be designed and experienced in the space of architecture as material IoT.
Expanding the Role of Electro-Thermal Actuators Based On Carbon Nanotubes Within the Fabrication of Pre-Programmed Material Composites

Manufacturing Workflows for Bio-Based and Natural Materials
Developing manufacturing workflows for material systems that enhance the use of bio-based and natural materials and seek continuous adaptability through digitalisation for applications in architecture and design. Exploring additive and robotic methods to develop building components that include material development, fabrication innovation and assessment of sustainability and applicability in the construction sector.

1.Soil-based additive fabrication
evaluating local materials printability for the building sector. Whereas the ECOLOPES project utilizes an information-centric approach to develop computational workflows for the fabrication of soil-based building blocks – this research targets a material driven approach with the aim to cross reference trade-offs and insights from both trajectories.

2.Bioplastic based additive fabrication
evaluating materials printability and biodegradability for industrial products and building components. This research is based on current progress in D.DLab that involves PLA based material development for high-resolution durable printing, as well as a study on additive manufacturing of Bio-based Music Records.

2. DATA DRIVEN COMPUTATIONAL DESIGN
We analyze, simulate, predict and optimize spatial performance towards high-resolution and informed design. We develop analytical and generative tools for algorithmic computing of material workflows, buildings, and cities. We understand that although data volume, acquisition methods, and processing power is increasing, there remains a distinct gap between the ability to create and collect data and its integration as meaningful knowledge for design support towards sustainable implementations.
Researchers: Or Moscovitz, Surayyn Selvan, Ofir Zak, Hanan Tanasra

Computational Multi-Criteria Simulations
Multi-species perspectives and material organisation as a computational framework for the design of building envelopes and building blocks. The ECOLOPES EU four-year project aims to develop ontology-based simulations, multi-criteria analysis and rating strategies for such decision-making processes.
Horizon 2020 -FET OPEN: ECOLOPES ECOlogical building enveLOPES: a game- changing design approach for regenerative urban ecosystems. Proposal no. 964414
In collaboration with TU Munich, University of Genua, TU Wien, Thomas Hauck – Studio animal aided design and McNeel Europe. In collaboration in the Technion with Prof. Yasha J. Grobman. Prof. Assaf Shwartz. 2021-2024.

Design Decision Support Frameworks
A key prospect to advancing informed planning and design lies in the utilization of data as meaningful knowledge for design. Using computational methods (Generative, ML, Augmented AI) for Design Decision Support enables spatial practices to seek higher-ordered goals that empower people, embrace our cultures and contribute to the construction of cities through sustainable and conscious protocols.

Urban AI – Prof. Barath is advisor and contributor
ShaGa Architects – Prof. Barath is co-founder and advisor

LAB FACILITIES

ROBOTIC section – Robotic manufacturing for 1:1 construction.

        • KUKA KR-50: 6 axis robot equipped with a KRC4 controller and a 50kg payload
        • UR5e: two lightweight 6-axis collaborative robots

WORKSHOP section – Material design & Bio fabrication.

        • Hayrel HYDRA 21A
        • Hayrel ENGINE HR HIGH RES
        • Delta WASP 40100 Clay
        • MARKFORGE – 2 headers 3d printer
        • Felfil Evo – Filament Maker
        • ELECTRONIC section – expressive IoT, Robotic end-effectors, Printed electronics

COMPUTATION section – dedicated infrastructure for big data and high-resolution simulation computing.