Zobrazeno 1 - 10
of 101
pro vyhledávání: '"Maurizio Righetti"'
Autor:
Majid Niazkar, Reza Piraei, Andrea Menapace, Pranav Dhawan, Daniele Dalla Torre, Michele Larcher, Maurizio Righetti
Publikováno v:
Journal of Water and Climate Change, Vol 15, Iss 1, Pp 271-283 (2024)
Using the global climate model outputs without any adjustment may bring errors in water resources and climate change investigations. This study tackles the critical issue of bias correction temperature in ERA5-Land reanalysis for 10 ground stations i
Externí odkaz:
https://doaj.org/article/12f3bba05a06422296f267179b4d9ee6
Autor:
Daniele Dalla Torre, Nicola Di Marco, Andrea Menapace, Diego Avesani, Maurizio Righetti, Bruno Majone
Publikováno v:
Journal of Hydrology: Regional Studies, Vol 52, Iss , Pp 101718- (2024)
Study region: The region of interest is the South-Tyrol in the southeastern Alps, Italy. A comparison of meteorological forcing is performed with reference to this region while hydrological simulations are conducted in the Passirio river basin.Study
Externí odkaz:
https://doaj.org/article/3d6e125e7e6d478189a7d5da6ecd634d
Publikováno v:
Journal of Hydroinformatics, Vol 24, Iss 5, Pp 1053-1065 (2022)
Sustainable management of water resources is a key challenge nowadays and in the future. Water distribution systems have to ensure fresh water for all users in an increasing demand scenario related to the long-term effects due to climate change. In t
Externí odkaz:
https://doaj.org/article/3e91bab1b4d84d378efcbb0dfd97e8f9
Autor:
Pranav Dhawan, Daniele Dalla Torre, Ariele Zanfei, Andrea Menapace, Michele Larcher, Maurizio Righetti
Publikováno v:
Water, Vol 15, Iss 8, p 1495 (2023)
Drinking water demand modelling and forecasting is a crucial task for sustainable management and planning of water supply systems. Despite many short-term investigations, the medium-term problem needs better exploration, particularly the analysis and
Externí odkaz:
https://doaj.org/article/f6483070e2554d4aa36bb325a26e3bb5
Publikováno v:
Environmental Sciences Proceedings, Vol 21, Iss 1, p 70 (2022)
The digitalisation of water supply systems is essential to support crucial activities, ranging from the hydraulic modelling and calibration of distribution systems to the optimal planning of renewal measures. Digital Twins is the current challenge th
Externí odkaz:
https://doaj.org/article/3998b13dddfc47e0a049a22f6cf7d5d7
Autor:
Roman Gabl, Maurizio Righetti
Publikováno v:
Engineering Applications of Computational Fluid Mechanics, Vol 12, Iss 1, Pp 397-410 (2018)
An asymmetric orifice can be added to a surge tank of a hydro power plant to dampen the mass oscillation. This allows a reduction of the required volume and a more stable behavior of the overall hydraulic system. In this paper, the advantage of a typ
Externí odkaz:
https://doaj.org/article/dd5d8cbb00594d3ea0639ca0678e8f0a
Publikováno v:
Water, Vol 13, Iss 17, p 2432 (2021)
This paper studies the convergence properties of an arbitrary Lagrangian–Eulerian (ALE) Riemann-based SPH algorithm in conjunction with a Weighted Essentially Non-Oscillatory (WENO) high-order spatial reconstruction, in the framework of the DualSPH
Externí odkaz:
https://doaj.org/article/e74437a4e8284c0a9e760062168ba481
Publikováno v:
Energies, Vol 14, Iss 17, p 5344 (2021)
Modelling heat load is a crucial challenge for the proper management of heat production and distribution. Several studies have tackled this issue at building and urban levels, however, the current scale of interest is shifting to the district level d
Externí odkaz:
https://doaj.org/article/0b85a5dc0d8c444a8937bfadb8b16bbc
Publikováno v:
Applied Sciences, Vol 11, Iss 9, p 4290 (2021)
The evolution of smart water grids leads to new Big Data challenges boosting the development and application of Machine Learning techniques to support efficient and sustainable drinking water management. These powerful techniques rely on hyperparamet
Externí odkaz:
https://doaj.org/article/107e32782dde478da69097a57ae14f37
Autor:
Andrea Menapace, Ariele Zanfei, Manuel Felicetti, Diego Avesani, Maurizio Righetti, Rudy Gargano
Publikováno v:
Applied Sciences, Vol 10, Iss 22, p 8219 (2020)
Developing data-driven models for bursts detection is currently a demanding challenge for efficient and sustainable management of water supply systems. The main limit in the progress of these models lies in the large amount of accurate data required.
Externí odkaz:
https://doaj.org/article/e925fb1b353f4050ba8701d4ae92923b