首页|New Robotics Study Findings Have Been Reported from Swiss Federal Institute of Technology (Robotic 3d Printing of Geopolymer Foam for Lightweight and Insulating Building Elements)

New Robotics Study Findings Have Been Reported from Swiss Federal Institute of Technology (Robotic 3d Printing of Geopolymer Foam for Lightweight and Insulating Building Elements)

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Data detailed on Robotics have been presented. According to news reporting out of Zurich, Switzerland, by NewsRx editors, research stated, “Foam 3D printing in construction is a promising manufacturing approach that aims to reduce the amount of material, hazardous labor, and costs in producing lightweight and insulating building parts that can reduce the operational energy in buildings. Research using cement-free mineral foams derived from industrial waste showed great potential in previous studies that reduced the amount of concrete needed in composite structures.” Funders for this research include Innosuisse Impulse program, ETH Research Commission. Our news journalists obtained a quote from the research from the Swiss Federal Institute of Technology, “This article collates the latest developments in this line of work. It presents the material system with its principal components and the advanced robotic 3D printing setup with a climate-controlled fabrication chamber. Print path schemes and hybrid fabrication methods combining 3D printing and casting are evaluated. Furthermore, the article discusses the effect of different print path schemes on the thermal insulation and compressive strength performance of printed parts. A full-scale final prototype synthesizes these findings and demonstrates the fabrication of modular, lightweight, and insulating construction elements that can be assembled into monolithic wall structures. The advantages and challenges of this novel approach are elaborated on in the conclusions.”

ZurichSwitzerlandEuropeEmerging TechnologiesMachine LearningRoboticsRobotsSwiss Federal Institute of Technology

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Feb.7)
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