Publications associées à Evaluating modeling uncertainties in the simulation of airflow in cities

Publications associées (32)

Study of the decay (Formula presented)

Using (Formula presented) (Formula presented) events collected with the BESIII detector operating at the BEPCII collider, we have observed the decay (Formula presented) for the first time with a statistical significance of (Formula presented). Its branchin ...

2025

What can radars tell us about snowfall microphysics? Insights from a Markov chain Monte-Carlo approach

Alexis Berne, Anne-Claire Marie Billault--Roux

Multi-frequency and Doppler spectral radars are valuable tools for retrieving information on the microphysics of precipitation, particularly snowfall. However, estimating microphysical properties from radar measurements is an ill-posed problem, i.e., diffe ...

American Meteorological Society2025

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Ian Smith, Katrin Beyer, Bryan German Pantoja Rosero, Mathias Christian Haindl Carvallo

Image information about the state of a building after an earthquake, which can be collected without endangering the post-earthquake reconnaissance activities, can be used to reduce uncertainties in response predictions for future seismic events. This paper ...

Springer2024

The complexity of quantum support vector machines

Gian Florin Gentinetta

Quantum support vector machines employ quantum circuits to define the kernel function. It has been shown that this approach offers a provable exponential speedup compared to any known classical algorithm for certain data sets. The training of such models c ...

Verein Forderung Open Access Publizierens Quantenwissenschaf2024

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

Olga Fink, Hao Lu

Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition monitoring datasets that can be used to build diagnosis algorithms capable of warning ma ...

2024

Model uncertainties in action effects and load bearing capacity calculation in statically indeterminate reinforced concrete structures

Aurelio Muttoni, Alain Nussbaumer, Xhemsi Malja

For the dimensioning and assessment of structures, it is common practice to compare action effects with sectional resistances. Extensive studies have been performed to quantify the model uncertainty on the resistance side. However, for statically indetermi ...

Ernst & Sohn2024

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

Design of an Open-Loop Pile-Oscillation Program in the CROCUS Reactor

Andreas Pautz, Vincent Pierre Lamirand, Axel Guy Marie Laureau, Thomas Jean-François Ligonnet

As a follow-up to the CEA-EPFL PETALE experimental program on stainless steel nuclear data, the EPFL initiated an open-loop pile-oscillation experimental program in the CROCUS reactor: BLOOM. A reproduction of the critical experiments of PETALE, the progra ...

2024

Urban boundary-layer flows in complex terrain: Dynamic interactions during a hot and dry summer season in Phoenix, Arizona

Aldo Brandi

Anthropogenic modification of natural landscapes to urban environments impacts land-atmosphere interactions in the boundary layer. Ample research has demonstrated the effect of such landscape transitions on development of the urban heat island (UHI), but c ...

Wiley2024

Toward Reliable Human Pose Forecasting With Uncertainty

Alexandre Massoud Alahi, Saeed Saadatnejad, Taylor Ferdinand Mordan

Recently, there has been an arms race of pose forecasting methods aimed at solving the spatio-temporal task of predicting a sequence of future 3D poses of a person given a sequence of past observed ones. However, the lack of unified benchmarks and limited ...

2024

Nonlinear simulation of plasma turbulence using a gyrokinetic moment-based approach

Antoine Cyril David Hoffmann

Plasma turbulence plays a fundamental role in determining the performances of magnetic confinement fusion devices, such as tokamaks. Advances in computer science, combined with the development of efficient physical models, have significantly improved our u ...

EPFL2024

ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference

Minh Hieu Lê, Nikita Durasov

Whereas the ability of deep networks to produce useful predictions on many kinds of data has been amply demonstrated, estimating the reliability of these predictions remains challenging. Sampling approaches such as MC-Dropout and Deep Ensembles have emerge ...

2024

Turbulence and Heat exchange in the Near-Surface Boundary Layer over Patchy Snow

Michael Haugeneder

The atmospheric layer adjacent to the earth's surface is of crucial importance for weather models due to the exchange of energy between the surface and the atmosphere. This exchange is dependent on the various surface properties and influences the state of ...

EPFL2024

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

Holger Reimerdes, Haomin Sun

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

Noise-induced transitions past the onset of a steady symmetry-breaking bifurcation: The case of the sudden expansion

François Gallaire, Edouard Boujo, Yves-Marie François Ducimetière

We consider fluid flows, governed by the Navier-Stokes equations, subject to a steady symmetry-breaking bifurcation and forced by a weak noise acting on a slow timescale. By generalizing the multiple-scale weakly nonlinear expansion technique employed in t ...

2024

Computational fluid dynamics simulations of the heat transfer properties of graphene-based nanolubricants and application to hydrodynamic lubrication

Roberto Guarino

In this paper, we consider experimental data available for graphene-based nanolubricants to evaluate their convective heat transfer performance by means of computational fluid dynamics (CFD) simulations. Single-phase models with temperature-dependent prope ...

Aip Publishing2024

Improvements to the dynamic wake meandering model by incorporating the turbulent Schmidt number

Fernando Porté Agel, Peter Andreas Brugger, Corey Dean Markfort

Predictions of the dynamic wake meandering model (DWMM) were compared to flow measurements of a scanning Doppler lidar mounted on the nacelle of a utility-scale wind turbine. We observed that the wake meandering strength of the DWMM agrees better with the ...

2024

Machine-Learning-Enhanced Real-Time Aerodynamic Forces Prediction Based on Sparse Pressure Sensor Inputs

Jan Sickmann Hesthaven, Junming Duan

Accurate real-time prediction of aerodynamic forces is crucial for the navigation of unmanned aerial vehicles (UAVs). This paper presents a data-driven aerodynamic force prediction model based on a small number of pressure sensors located on the surface of ...

2024

A cut-cell method for the numerical simulation of 3D multiphase flows with strong interfacial effects

Marco Picasso, Alexandre Caboussat, Alexandre Masserey, Julien Hess

We present a numerical model for the approximation of multiphase flows with free surfaces and strong interfacial effects. The model relies on the multiphase incompressible Navier-Stokes equations, and includes surface tension effects on the interfaces betw ...

Academic Press Inc Elsevier Science2024

Analysis of Bootstrap and Subsampling in High-dimensional Regularized Regression

Lenka Zdeborová, Florent Gérard Krzakala, Bruno Loureiro, Adrien Vandenbroucque, Lucas Andry Clarte, Guillaume Cyprien Dalle

We investigate popular resampling methods for estimating the uncertainty of statistical models, such as subsampling, bootstrap and the jackknife, and their performance in high-dimensional supervised regression tasks. We provide a tight asymptotic descripti ...

ACM2024