Publications by Ekaterina Krymova

Fatigue damage reduction in hydropower startups with machine learning

Elena Vagnoni, Ekaterina Krymova, Alessandro Morabito, Martin Seydoux

As the global shift towards renewable energy accelerates, achieving stability in power systems is crucial. Hydropower accounts for approximately 17% of energy produced worldwide, and with its capacity for active and reactive power regulation, is well-suite ...

2025

High-resolution modelling of particulate matter chemical composition over Europe: brake wear pollution

Ekaterina Krymova

In today's rapidly evolving society, the sources of atmospheric particulate matter (PM) emissions are shifting significantly. Stringent regulations on vehicle tailpipe emissions, in combination with a lack of control of non-exhaust vehicular emissions, hav ...

Elsevier BV2025

Optimizing Dynamic Aperture Studies with Active Learning

Tatiana Pieloni, Ekaterina Krymova, Mike Seidel, Davide Di Croce, Massimo Giovannozzi

Dynamic aperture is an important concept for the study of non-linear beam dynamics in circular accelerators. It describes the extent of the phase-space region where a particle's motion remains bounded over a given number of turns. Understanding the feature ...

Iop Publishing Ltd2024

On the modelling of the fatigue-induced damage in Francis turbines start-up sequences

Elena Vagnoni, Ekaterina Krymova, Alessandro Morabito, Martin Seydoux

The European Green Deal is prescribing a very ambitious rise in the annual production of renewable energy sources, and grid regulation services are increasingly important in the course of a massive integration of intermittent renewable energy sources. Alth ...

Institute of Physics2024

Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations

Benjamin Bejar Haro, Ekaterina Krymova, Ntorina Thanou, Nicola Parolini, Daniel Rodrigo Lopez, Andrea Kraus, Daniel Lopez, David Kraus, Markus Scholz, Tao Sun

Background:Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive p ...

eLIFE SCIENCES PUBL LTD2023

Data-driven modeling of beam loss in the LHC

Tatiana Pieloni, Michael Schenk, Ekaterina Krymova, Loïc Thomas Davies Coyle

In the Large Hadron Collider, the beam losses are continuously measured for machine protection. By design, most of the particle losses occur in the collimation system, where the particles with high oscilla-tion amplitudes or large momentum error are scrape ...

FRONTIERS MEDIA SA2023

National and subnational short-term forecasting of COVID-19 in Germany and Poland during early 2021

Ekaterina Krymova, Markus Scholz

Background During the COVID-19 pandemic there has been a strong interest in forecasts of the short-term development of epidemiological indicators to inform decision makers. In this study we evaluate probabilistic real-time predictions of confirmed cases an ...

Springernature2022

Trend estimation and short-term forecasting of COVID-19 cases and deaths worldwide

Benjamin Bejar Haro, Ekaterina Krymova, Ntorina Thanou, Guillaume Romain Obozinski, Christine Choirat

Since the beginning of the COVID-19 pandemic, many dashboards have emerged as useful tools to monitor its evolution, inform the public, and assist governments in decision-making. Here, we present a globally applicable method, integrated in a daily updated ...

National Academy of Sciences2022

Bayesian TVP-VARX models with time invariant long-run multipliers

Ekaterina Krymova

The time-varying parameters vector autoregression models with exogenous variables (TVP-VARX) have become an indispensable tool for modeling time-varying relationships between macroeconomic indicators. At the same time, TVP-VARX models are often outperforme ...

2021