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Multipurpose Cryptographic Primitive ARMADILLO3

Publications associées (25)

Dynamical simulation via quantum machine learning with provable generalization

Much attention has been paid to dynamical simulation and quantum machine learning (QML) independently as applications for quantum advantage, while the possibility of using QML to enhance dynamical simulations has not been thoroughly investigated. Here we d ...

Amer Physical Soc2024

Surface segregation in high-entropy alloys from alchemical machine learning

Michele Ceriotti, Guillaume André Jean Fraux, Arslan Mazitov, Sandip De, Nataliya Lopanitsyna

High-entropy alloys (HEAs), containing several metallic elements in near-equimolar proportions, have long been of interest for their unique mechanical properties. More recently, they have emerged as a promising platform for the development of novel heterog ...

Iop Publishing Ltd2024

Models implemented in the methodological approach to design the initial STEP first wall contour

Davide Galassi, Kevin Henricus Annemarie Verhaegh, Filippo Bagnato, Dario Vaccaro

The official Spherical Tokamak for Energy Production mission aims to demonstrate the ability to generate net electricity from fusion with the STEP Prototype Power plant. One of the key technological and engineering challenges in fusion power plants is mana ...

Elsevier Science Sa2024

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Dynamical simulation via quantum machine learning with provable generalization

Zoë Holmes

Amer Physical Soc2024

Surface segregation in high-entropy alloys from alchemical machine learning

Michele Ceriotti, Guillaume André Jean Fraux, Arslan Mazitov, Sandip De, Nataliya Lopanitsyna

Iop Publishing Ltd2024

Models implemented in the methodological approach to design the initial STEP first wall contour

Davide Galassi, Kevin Henricus Annemarie Verhaegh, Filippo Bagnato, Dario Vaccaro

Elsevier Science Sa2024

An explorative method to support design decisions based on carbon constraints and daylight sufficiency needs

Nazanin Rezaei Oghazi

The global construction industry contributes to 37% of carbon emissions associated to both building operations and construction. To help achieve the net-zero targets set by 2050, it is mandated to achieve a 50% reduction in carbon emissions by 2030. As we ...

EPFL2024

A diversity-driven discovery of potential nanoporous materials for energy-related applications

Sauradeep Majumdar

The design and discovery of potential novel materials is critical for the advancement of climate change mitigation technologies. In this respect, metal-organic frameworks (MOFs) have received considerable attention over the last two decades. The combinatio ...

EPFL2024

Thermal Design of a Medium Voltage Modular Multilevel Converter Cell

Drazen Dujic, Yanick Patrick Frei

This paper presents the cooling concept for a medium voltage modular multilevel converter cell. To optimize power density, the metallic enclosure is used to dissipate the heat generated by semiconductor losses, while maintaining maximum temperatures below ...

New York2023

Computational conceptual design — typological exploration of spatial truss systems through optimization

Corentin Jean Dominique Fivet, Jonas Warmuth, Pierluigi D'Acunto

Exploring a wide range of design options is crucial for every sound conceptual design process. In the conventional structural design workflow, optimization techniques are generally employed to generate well-performing design options. However, focusing only ...

International Association for Shell and Spatial Structures (IASS)2023

Lessons Learned from Data-Driven Building Control Experiments: Contrasting Gaussian Process-based MPC, Bilevel DeePC, and Deep Reinforcement Learning

Colin Neil Jones, Loris Di Natale, Jicheng Shi, Emilio Maddalena, Yingzhao Lian

This manuscript offers the perspective of experimentalists on a number of modern data-driven techniques: model predictive control relying on Gaussian processes, adaptive data-driven control based on behavioral theory, and deep reinforcement learning. These ...

2023

Interactive design with optimum matchmaking of reused structural elements – a software implementation

Corentin Jean Dominique Fivet, Jonas Warmuth, Jan Friedrich Georg Brütting

Structural systems are a significant contributor to buildings’ embodied carbon and reusing structural elements in new load-bearing applications is one strategy to reduce this impact. However, integrating this approach into existing design workflows without ...

International Association for Shell and Spatial Structures (IASS)2023

A Reuse-Ready Timber Slab-and-Column System for Modular Building Structures

Corentin Jean Dominique Fivet, Jonas Warmuth, Jan Friedrich Georg Brütting, Alex-Manuel Muresan, Edisson Xavier Estrella Arcos

The construction industry is a significant contributor to resource consumption and waste generation. To address this issue, component reuse has been proposed as a way to prevent valuable building elements from being discarded and avoid producing new ones. ...

Curran Associates, Inc.2023

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Lessons Learned from Data-Driven Building Control Experiments: Contrasting Gaussian Process-based MPC, Bilevel DeePC, and Deep Reinforcement Learning

Colin Neil Jones, Loris Di Natale, Jicheng Shi, Emilio Maddalena, Yingzhao Lian

2023

Interactive design with optimum matchmaking of reused structural elements – a software implementation

Corentin Jean Dominique Fivet, Jonas Warmuth, Jan Friedrich Georg Brütting

International Association for Shell and Spatial Structures (IASS)2023

A Reuse-Ready Timber Slab-and-Column System for Modular Building Structures

Corentin Jean Dominique Fivet, Jonas Warmuth, Jan Friedrich Georg Brütting, Alex-Manuel Muresan, Edisson Xavier Estrella Arcos

Curran Associates, Inc.2023