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Quantifying changes in the probability and magnitude of extreme flooding events is key to mitigating their impacts. While hydrodynamic data are inherently spatially dependent, traditional spatial models such as Gaussian processes are poorly…

Methodology · Statistics 2024-05-06 Reetam Majumder , Brian J. Reich , Benjamin A. Shaby

In this study, we conduct a parametric analysis to evaluate the sensitivities of wall-modeled large-eddy simulation (LES) with respect to subgrid-scale (SGS) models, mesh resolution, wall boundary conditions and mesh anisotropy. While such…

Fluid Dynamics · Physics 2024-03-26 Di Zhou , H. Jane Bae

The correlation between the event mean-transverse momentum $[p_{\mathrm{T}}]$, and the anisotropic flow magnitude $v_n$, $\rho(v^{2}_{n},[p_{T}])$, has been argued to be sensitive to the initial conditions in heavy-ion collisions. We use…

Nuclear Theory · Physics 2021-09-15 Niseem Magdy , Roy A. Lacey

Complex computer codes are widely used in science to model physical systems. Sensitivity analysis aims to measure the contributions of the inputs on the code output variability. An efficient tool to perform such analysis are the…

Statistics Theory · Mathematics 2013-10-15 Gaëlle Chastaing , Loic Le Gratiet

The Global Change Analysis Model (GCAM) simulates complex interactions between the coupled Earth and human systems, providing valuable insights into the co-evolution of land, water, and energy sectors under different future scenarios.…

Global physical event detection has traditionally relied on dense coverage of physical sensors around the world; while this is an expensive undertaking, there have not been alternatives until recently. The ubiquity of social networks and…

Machine Learning · Computer Science 2019-12-16 Abhijit Suprem , Calton Pu

We propose a framework for developing wall models for large-eddy simulation that is able to capture pressure-gradient effects using multi-agent reinforcement learning. Within this framework, the distributed reinforcement learning agents…

Fluid Dynamics · Physics 2024-07-29 Di Zhou , H. Jane Bae

We formulate and test a hybrid fluid-Monte Carlo scheme for the treatment of elastic collisions in gases and plasmas. While our primary focus and demonstrations of applicability are for moderately collisional plasmas, as described by the…

Computational Physics · Physics 2015-06-12 L. F. Ricketson , M. S. Rosin , R. E. Caflisch , Andris M. Dimits

Modeling the effect of complex terrain on high Reynolds number flows is important to improve our understanding of flow dynamics in wind farms and the dispersion of pollen and pollutants in hilly or mountainous terrain as well as the flow in…

Computational Physics · Physics 2021-03-11 Luoqin Liu , Richard J. A. M. Stevens

In this work, we develop a modelling framework for granular flows based on the shallow water moment equations on inclined planes. Under the assumption of a polynomial expansion of the velocity field, the model extends the classical shallow…

Numerical Analysis · Mathematics 2025-12-18 Julio Careaga , Qian Huang , Julian Koellermeier

Numerical simulators are widely used to model physical phenomena and global sensitivity analysis (GSA) aims at studying the global impact of the input uncertainties on the simulator output. To perform GSA, statistical tools based on…

Methodology · Statistics 2026-05-29 Anouar Meynaoui , Amandine Marrel , Béatrice Laurent

The transition from non-renewable to renewable energies represents a global societal challenge, and developing a sustainable energy portfolio is an especially daunting task for developing countries where little to no information is…

Applications · Statistics 2022-09-13 Jiachen Zhang , Paola Crippa , Marc G. Genton , Stefano Castruccio

We consider the problem where a modeller conducts sensitivity analysis of a model consisting of random input factors, a corresponding random output of interest, and a baseline probability measure. The modeller seeks to understand how the…

Risk Management · Quantitative Finance 2022-06-01 Silvana M. Pesenti

Statistical models for landslide hazard enable mapping of risk factors and landslide occurrence intensity by using geomorphological covariates available at high spatial resolution. However, the spatial distribution of the triggering event…

Methodology · Statistics 2020-06-16 Thomas Opitz , Haakon Bakka , Raphaël Huser , Luigi Lombardo

Rainfall-induced landslides pose a growing risk worldwide as climate change intensifies extreme rainfall events. To provide sufficient evacuation time, landslide early warning systems (LEWS) for real-time disaster monitoring must estimate…

Machine Learning · Computer Science 2026-05-19 Ren Ozeki , Hamada Rizk , Hirozumi Yamaguchi

Landslides pose a significant threat to public safety, but their dynamic processes are difficult to analyze from post-event observation alone. Computational simulation is therefore essential, but it generates vast, abstract datasets that…

Human-Computer Interaction · Computer Science 2026-04-21 Wong Kam-Kwai , Yi-Lin Ye , Wai Tong , Haobo Li , Kentaro Takahira , Aastha Bhatta , Sunil Poudyal , Charles Wang Wai Ng , Huamin Qu , Leni Yang

The development of scramjet engines is an important research area for advancing hypersonic and orbital flights. Progress toward optimal engine designs requires accurate flow simulations together with uncertainty quantification. However,…

Data Analysis, Statistics and Probability · Physics 2018-03-14 Xun Huan , Cosmin Safta , Khachik Sargsyan , Gianluca Geraci , Michael S. Eldred , Zachary P. Vane , Guilhem Lacaze , Joseph C. Oefelein , Habib N. Najm

Numerical modelling of flow in stepped spillways is considered, focusing on a highly economical approach combining interface capturing with explicit modelling of air entrainment. Simulations are performed on spillways at four different…

Fluid Dynamics · Physics 2020-09-11 Silje Kreken Almeland , Timofey Mukha , Rickard E. Bensow

The main objective of this work is to develop a unified framework that can be used as a lens to quantitatively assess and augment a wide range of coarse-grained models of turbulence, viz. large eddy simulations (LES), hybrid…

Fluid Dynamics · Physics 2023-01-25 Aniruddhe Pradhan , Karthik Duraisamy

Despite the ubiquity of fluid flows interacting with porous and elastic materials, we lack a validated non-empirical macroscale method for characterizing the flow over and through a poroelastic medium. We propose a computational tool to…

Fluid Dynamics · Physics 2017-03-24 Uǧis Lācis , Giuseppe Antonio Zampogna , Shervin Bagheri