Publication

An improved model for predicting electrical conductance in nanochannels

Publications associées (27)

Comparison of reduced model predictions for divertor detachment onset and reattachment timescales in ASDEX Upgrade and JET experiments

Building on prior analysis of ASDEX Upgrade (AUG) experiments (Henderson et al 2023 Nucl. Fusion 63 086024), this study compares simple analytical formula predictions for divertor detachment onset and reattachment timescales in JET experiments. Detachment ...

IOP Publishing Ltd2024

Good enough: Intermediate complexity atmospheric models improve the representation of processes affecting seasonal snow

Dylan Stewart Reynolds

Snow plays a crucial role in processes regulating ecosystems, the climate, and human development. Mountain snowpack in particular has great relevance for downstream communities. Knowledge about the distribution and properties of the snowpack thus help in p ...

EPFL2024

Intermediate complexity atmospheric modeling in complex terrain: is it right?

Michael Lehning, Dylan Stewart Reynolds, Michael Haugeneder

Dynamic downscaling of atmospheric forcing data to the hectometer resolution has shown increases in accuracy for landsurface models, but at great computational cost. Here we present a validation of a novel intermediate complexity atmospheric model, HICAR, ...

Frontiers Media Sa2024

Setting priorities in CNF particle size measurement: What is needed vs. what is feasible

Tiffany Abitbol

Measuring the size of cellulose nanomaterials can be challenging, especially in the case of branched and entangled cellulose nanofibrils (CNFs). The International Organization for Standardization, Technical Committee 6, Task Group 1-Cellulosic Nanomaterial ...

TECH ASSOC PULP PAPER IND INC2023

RaFSIP: Parameterizing ice multiplication in models using a machine learning approach

Athanasios Nenes, Paraskevi Georgakaki

Accurately representing mixed-phase clouds (MPCs) in global climate models (GCMs) is critical for capturing climate sensitivity and Arctic amplification. Secondary ice production (SIP), can significantly increase ice crystal number concentration (ICNC) in ...

2024

Spatially adaptive machine learning models for predicting water quality in Hong Kong

Rongrong Li, Qiaoli Wang, Yu Xu

Water quality prediction in the spatially heterogeneous environment is challenging as the importance of water quality parameters (WQPs) and the performance of prediction models may vary across space. Thus, this study proposed spatially adaptive machine lea ...

ELSEVIER2023

The role of secondary ice production in mixed-phase clouds

Paraskevi Georgakaki

Clouds are omnipresent in the Earth's atmosphere. Their phase composition significantly modulates their interaction with solar and terrestrial radiation, as well as precipitation formation. Particularly for clouds containing both phases, known as mixed-pha ...

EPFL2023

Failure and success of the spectral bias prediction for Laplace Kernel Ridge Regression: the case of low-dimensional data

Matthieu Wyart, Umberto Maria Tomasini, Antonio Sclocchi

Recently, several theories including the replica method made predictions for the generalization error of Kernel Ridge Regression. In some regimes, they predict that the method has a 'spectral bias': decomposing the true function f* on the eigenbasis of the ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2022

Ultra low quantum decoherence nano-optomechanical systems

Mohammadjafar Bereyhi

Thermal motion of a room-temperature mechanical resonator typically dominates the quantum backaction of its position measurement. This is a longstanding barrier for exploring cavity optomechanics at room temperature. In order to enter the quantum regime of ...

EPFL2022

Wind-Topo: Downscaling near-surface wind fields to high-resolution topography in highly complex terrain with deep learning

Michael Lehning, Jérôme François Sylvain Dujardin

Predicting wind flow in highly complex terrain like the Alps is a challenge for all models. When physical processes need to be resolved in a spatially explicit manner, grids with high horizontal resolution of a few hundred meters are often required and dra ...

WILEY2022

Downscaling of Historical Wind Fields over Switzerland Using Generative Adversarial Networks

Anthony Christopher Davison, Ophélia Mireille Anna Miralles

Near-surface wind is difficult to estimate using global numerical weather and climate models, because airflow is strongly modified by underlying topography, especially that of a country such as Switzerland. In this article, we use a statistical approach ba ...

2022

Numerical and experimental study of the dynamic thermal resistance of ventilated air-spaces behind passive and active façades

Mohammad Rahiminejad, Dolaana Khovalyg

The variation of the thermo-hydrodynamic behavior of the airflow in the ventilated cavity behind external claddings in a wall structure could potentially affect the overall thermal resistance of the entire structure. Although the impact of an enclosed air- ...

2022

Physics-enhanced machine learning with symmetry-adapted and long-range representations

Andrea Grisafi

Theoretical and computational approaches to the study of materials and molecules have, over the last few decades, progressed at an exponential rate. Yet, the possibility of producing numerical predictions that are on par with experimental measurements is t ...

EPFL2021

Numerical Weather Prediction and Artificial Neural Network Coupling for Wind Energy Forecast

Jiannong Fang, Fernando Porté Agel, Lorenzo Donadio

In the past two decades, wind energy has been under fast development worldwide. The dramatic increase of wind power penetration in electricity production has posed a big challenge to grid integration due to the high uncertainty of wind power. Accurate real ...

2021

Quench behavior of high-temperature superconductor tapes for power applications: a strategy toward resilience

Nicolo' Riva

High-Temperature Superconductors (HTS) can be superconducting in liquid nitrogen 77 K, holding immense promises for our future. They can enable disruptive technologies such as nuclear fusion, lossless power transmission, cancer treatment devices, and techn ...

EPFL2021

Secondary ice production in summer clouds over the Antarctic coast: an underappreciated process in atmospheric models

Alexis Berne, Etienne Gabriel Henri Vignon, Athanasios Nenes, Georgia Sotiropoulou

The correct representation of Antarctic clouds in atmospheric models is crucial for accurate projections of the future Antarctic climate. This is particularly true for summer clouds which play a critical role in the surface melting of the ice shelves in th ...

European Geosciences Union2021

Systematic investigations of uranium carbide composites oxidation from micro- to nano-scale: Application to waste disposal

Nhât-Tân Vuong

The production of radioisotope beams at the ISOLDE (Isotope Separator OnLine DEvice) facility at CERN is achieved by irradiating target materials (e.g. uranium carbides and metal foils) with protons. The materials are usually operated at temperatures above ...

EPFL2021

Introducing CRYOWRF v1.0: multiscale atmospheric flow simulations with advanced snow cover modelling

Michael Lehning, Varun Sharma, Franziska Gerber

Accurately simulating snow-cover dynamics and the snow-atmosphere coupling is of major importance for topics as wide-ranging as water resources, natural hazards and climate change impacts with consequences for sea-level rise. We present a new modelling fra ...

2023

Quantum Measurement of Mechanical Motion close to the Standard Quantum Limit

Liu Qiu

In quantum mechanics, the Heisenberg uncertainty principle places a fundamental limit in the measurement precision for certain pairs of physical quantities, such as position and momentum, time and energy or amplitude and phase. Due to the Heisenberg uncert ...

EPFL2020

Improve the Model Stability of Dam's Displacement Prediction Using a Numerical-Statistical Combined Model

Zhenzhu Meng, Chenfei Shao, Yating Hu

In most studies of dam's displacement prediction based on monitoring data, emphasis was given on improving the prediction accuracy, while the model stability was merely considered. This study proposed a numerical-statistical combined model which aims to im ...

2020