Efficient Monte Carlo simulation of streamer discharges with deep-learning denoising models
Electric breakdown in non-conducting gases is a complex process that in its first stages is characterized by filamentary discharges called streamers. Streamer dynamics are inherently nonlinear and span broad temporal and spatial scales, making numerical simulation challenging. Although Monte Carlo m...
Saved in:
Main Authors: | F M Bayo-Muñoz, A Malagón-Romero, A Luque |
---|---|
Format: | Article |
Language: | English |
Published: |
IOP Publishing
2025-01-01
|
Series: | Machine Learning: Science and Technology |
Subjects: | |
Online Access: | https://doi.org/10.1088/2632-2153/adaca1 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Photoionization Impact on the Lightning Impulse Streamer Discharge of Rapeseed Insulating Oil: An Experimental Study
by: Yihua Qian, et al.
Published: (2025-01-01) -
Variation Comparison of OLS and GLS Estimators using Monte Carlo Simulation of Linear Regression Model with Autoregressive Scheme
by: Sajid AliKhan, et al.
Published: (2021-02-01) -
APPLICATIONS OF MONTE CARLO SIMULATION TO STRUCTURAL ENGINEERING PROBLEMS
by: Abdullah Azbah
Published: (2024-12-01) -
Variational Quantum Monte Carlo Solution of the Many-Electron Schrödinger Equation Based on Deep Neural Networks
by: Huiping Su, et al.
Published: (2024-02-01) -
Parallel Monte Carlo computations in SCore environment
by: Svajonė Vošterienė
Published: (2004-12-01)