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- Sherratt, K., et al.
(författare)
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Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations
- 2023
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Ingår i: eLIFE. - : eLife Sciences Publications Ltd. - 2050-084X. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance.Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models.Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks.
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- Moreau, V., et al.
(författare)
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Pool CFD modelling : lessons from the SESAME project
- 2019
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Ingår i: Nuclear Engineering and Design. - : ELSEVIER SCIENCE SA. - 0029-5493 .- 1872-759X. ; 355
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Tidskriftsartikel (refereegranskat)abstract
- The current paper describes the Computational Fluid-Dynamics (CFD) modelling of Heavy Liquid Metal (HLM) flows in a pool configuration and in particular how this is approached within the Horizon 2020 SESAME project. SESAME's work package structure, based on a systematic approach of redundancy and diversification, is explained along with its motivation. The main achievements obtained and the main lessons learned during the project are illustrated. The paper focuses on the strong coupling between the experimental activities and CFD simulations performed within the SESAME project. Two different HLM fluids are investigated: pure lead and Lead-Bismuth Eutectic. The objective is to make CFD a valid instrument used during the design of safe and innovative Gen-IV nuclear plants. Some effort has also been devoted to Proper Orthogonal Decomposition with Galerkin projection modelling (POD-Galerkin), a reduced order model suited for Uncertainty Quantification that operates by post-processing CFD results. Assessment of Uncertainty highly improves the reliability of CFD simulations. Dedicated experimental campaigns on heavily instrumented facilities have been conceived with the specific objective to build a series of datasets suited for the calibration and validation of the CFD modelling. In pool configuration, the attention is focused on the balance between conductive and convective heat transfer phenomena, on transient test-cases representative of incidental scenarios and on the possible occurrence of solidification phenomena. Four test sections have been selected to generate the datasets: (i) the CIRCE facility from ENEA, (ii) the TALL-3D pool test section from KTH, (iii) the TALL-3D Solidification Test Section (STS) from KTH and (iv) the SESAME Stand facility from CVR. While CIRCE and TALL-3D were existing facilities, the STS and SESAME Stand facility have been conceived, built and operated within the project, heavily relying on the use of CFD support. Care has been taken to ensure that almost all tasks were performed by at least two partners. Specific examples are given on how this strategy has allowed to uncover flaws and overcome pitfalls. Furthermore, an overview of the performed work and the achieved results is presented, as well as remaining or new uncovered issues. Finally, the paper is concluded with a description of one of the main goals of the SESAME project: the construction of the Gen-IV ALFRED CFD model and an investigation of its general circulation.
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- Antonioli, P, et al.
(författare)
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The AQUA-RICH atmospheric neutrino experiment
- 1999
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Ingår i: NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT. - : ELSEVIER SCIENCE BV. - 0168-9002. ; 433:1-2, s. 104-120
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- We describe a 125 m diameter spherical detector containing 1 Mt of water, capable of high rate observation of atmospheric neutrino events (30000/y). The ring imaging Cherenkov (RICH) technique is used to measure velocity, momentum and direction of particl
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