Zobrazeno 1 - 10
of 44
pro vyhledávání: '"Morten Grum"'
Publikováno v:
Geosciences, Vol 8, Iss 11, p 416 (2018)
To prevent online models diverging from reality they need to be updated to current conditions using observations and data assimilation techniques. A way of doing this for distributed hydrodynamic urban drainage models is to use the Ensemble Kalman Fi
Externí odkaz:
https://doaj.org/article/7d90be315bbb457989435064b7b5552d
Autor:
Elbys Jose Meneses, Marion Gaussens, Carsten Jakobsen, Peter Steen Mikkelsen, Morten Grum, Luca Vezzaro
Publikováno v:
Water, Vol 10, Iss 1, p 76 (2018)
The environmental benefits of combining traditional infrastructure solutions for urban drainage (increasing storage volume) with real time control (RTC) strategies were investigated in the Lundofte catchment in Denmark, where an expensive traditional
Externí odkaz:
https://doaj.org/article/b7d37815179c4dc49b0eba621ba24535
Autor:
Jonas W. Pedersen, Nadia S. V. Lund, Morten Borup, Roland Löwe, Troels S. Poulsen, Peter S. Mikkelsen, Morten Grum
Publikováno v:
Water, Vol 8, Iss 9, p 381 (2016)
High quality on-line flow forecasts are useful for real-time operation of urban drainage systems and wastewater treatment plants. This requires computationally efficient models, which are continuously updated with observed data to provide good initia
Externí odkaz:
https://doaj.org/article/322c384cf7d141989aca5f9763cbc749
Autor:
Roland Löwe, Matthias Kjær Adamsen, Phillip Aarestrup, Franca Bauer, Allan Peter Engsig-Karup, Morten Grum, Frederik Tinus Jeppesen, Peter Steen Mikkelsen
In this work we illustrate how scientific machine learning algorithms (SciML) can be used to facilitate the development of digital twins for urban drainage systems. Scientific machine learning integrates classical, modelling techniques from scientifi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c679d64472ac5a0fad89f03e03305843
https://doi.org/10.5194/egusphere-egu23-5672
https://doi.org/10.5194/egusphere-egu23-5672
Accelerating hydrodynamic simulations of urban drainage systems with physics-guided machine learning
Publikováno v:
Palmitessa, R, Grum, M, Engsig-Karup, A P & Löwe, R 2022, ' Accelerating hydrodynamic simulations of urban drainage systems with physics-guided machine learning ', Water Research, vol. 223, 118972 . https://doi.org/10.1016/j.watres.2022.118972
We propose and demonstrate a new approach for fast and accurate surrogate modelling of urban drainage system hydraulics based on physics-guided machine learning. The surrogates are trained against a limited set of simulation results from a hydrodynam
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8058166fb5ca37080c5dca0fc3c7b16c
http://arxiv.org/abs/2206.01538
http://arxiv.org/abs/2206.01538
Publikováno v:
Löwe, R, Palmitessa, R, Engsig-Karup, A P & Grum, M 2022, ' Fast and detailed emulation of urban drainage flows using physics-guided machine learning ', EGU General Assembly 2022, Vienna, Austria, 23/05/2022-27/05/2022 . https://doi.org/10.5194/egusphere-egu22-4303
Hydrodynamic models (numerical solutions of the Saint Venant equations) are at the core of simulating water movements in natural streams and drainage systems. They enable realistic simulations of water movement and are directly linked to physical sys
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2a822b86c857c9c8e46558f18b28ec46
https://orbit.dtu.dk/en/publications/fba3e071-13cc-4076-8dc1-2735f380d033
https://orbit.dtu.dk/en/publications/fba3e071-13cc-4076-8dc1-2735f380d033
Autor:
Thomas Munk-Nielsen, Luca Vezzaro, Peter Steen Mikkelsen, Henrik Madsen, Peter Tychsen, Rasmus Halvgaard, Peter Alexander Stentoft, Morten Grum
Publikováno v:
Stentoft, P A, Vezzaro, L, Mikkelsen, P S, Grum, M, Munk-Nielsen, T, Tychsen, P, Madsen, H & Halvgaard, R 2020, ' Integrated model predictive control of water resource recovery facilities and sewer systems in a smart grid : example of full-scale implementation in Kolding ', Water Science and Technology, vol. 81, no. 8, pp. 1766-1777 . https://doi.org/10.2166/wst.2020.266
An integrated model predictive control (MPC) strategy to control the power consumption and the effluent quality of a water resource recovery facility (WRRF) by utilizing the storage capacity from the sewer system was implemented and put into operatio
Publikováno v:
Hydrology and Earth System Sciences, Vol 21, Iss 5, Pp 2531-2544 (2017)
Courdent, V, Grum, M, Munk-Nielsen, T & Mikkelsen, P S 2017, ' A gain-loss framework based on ensemble flow forecasts to switch the urban drainage-wastewater system management towards energy optimization during dry periods ', Hydrology and Earth System Sciences, vol. 21, no. 5, pp. 2531-2544 . https://doi.org/10.5194/hess-21-2531-2017
Courdent, V, Grum, M, Munk-Nielsen, T & Mikkelsen, P S 2017, ' A gain-loss framework based on ensemble flow forecasts to switch the urban drainage-wastewater system management towards energy optimization during dry periods ', Hydrology and Earth System Sciences, vol. 21, no. 5, pp. 2531-2544 . https://doi.org/10.5194/hess-21-2531-2017
Precipitation is the cause of major perturbation to the flow in urban drainage and wastewater systems. Flow forecasts, generated by coupling rainfall predictions with a hydrologic runoff model, can potentially be used to optimize the operation of int
Publikováno v:
Fencl, M, Grum, M, Borup, M & Mikkelsen, P S 2019, ' Robust model for estimating pumping station characteristics and sewer flows from standard pumping station data ', Water Science and Technology, vol. 79, no. 9, pp. 1739-1745 . https://doi.org/10.2166/wst.2019.176
Flow data represent crucial input for reliable diagnostics of sewer functions and identification of potential problems such as unwanted inflow and infiltration. Flow estimates from pumping stations, which are an integral part of most separate sewer s
Publikováno v:
Borup, M, Grum, M, Linde, J J & Mikkelsen, P S 2016, ' Dynamic gauge adjustment of high-resolution X-band radar data for convective rain storms: Model-based evaluation against measured combined sewer overflow ', Journal of Hydrology, vol. 539, pp. 687-699 . https://doi.org/10.1016/j.jhydrol.2016.05.002
Summary Numerous studies have shown that radar rainfall estimates need to be adjusted against rain gauge measurements in order to be useful for hydrological modelling. In the current study we investigate if adjustment can improve radar rainfall estim