Non-linear noise cancellation using volterra filters, a real case study

Author(s):  
P. Amblard ◽  
D. Baudois
Author(s):  
Beniamino Di Martino ◽  
Dario Branco ◽  
Luigi Colucci Cante ◽  
Salvatore Venticinque ◽  
Reinhard Scholten ◽  
...  

AbstractThis paper proposes a semantic framework for Business Model evaluation and its application to a real case study in the context of smart energy and sustainable mobility. It presents an ontology based representation of an original business model and examples of inferential rules for knowledge extraction and automatic population of the ontology. The real case study belongs to the GreenCharge European Project, that in these last years is proposing some original business models to promote sustainable e-mobility plans. An original OWL Ontology contains all relevant Business Model concepts referring to GreenCharge’s domain, including a semantic description of TestCards, survey results and inferential rules.


2020 ◽  
Vol 6 ◽  
pp. 770-775 ◽  
Author(s):  
J.P. Ribeiro ◽  
C.C. Marques ◽  
I. Portugal ◽  
M.I. Nunes

Author(s):  
Aly-Joy Ulusoy ◽  
Filippo Pecci ◽  
Ivan Stoianov

AbstractThis manuscript investigates the design-for-control (DfC) problem of minimizing pressure induced leakage and maximizing resilience in existing water distribution networks. The problem consists in simultaneously selecting locations for the installation of new valves and/or pipes, and optimizing valve control settings. This results in a challenging optimization problem belonging to the class of non-convex bi-objective mixed-integer non-linear programs (BOMINLP). In this manuscript, we propose and investigate a method to approximate the non-dominated set of the DfC problem with guarantees of global non-dominance. The BOMINLP is first scalarized using the method of $$\epsilon $$ ϵ -constraints. Feasible solutions with global optimality bounds are then computed for the resulting sequence of single-objective mixed-integer non-linear programs, using a tailored spatial branch-and-bound (sBB) method. In particular, we propose an equivalent reformulation of the non-linear resilience objective function to enable the computation of global optimality bounds. We show that our approach returns a set of potentially non-dominated solutions along with guarantees of their non-dominance in the form of a superset of the true non-dominated set of the BOMINLP. Finally, we evaluate the method on two case study networks and show that the tailored sBB method outperforms state-of-the-art global optimization solvers.


2021 ◽  
Author(s):  
Joanna Doummar ◽  
Nidal Farran ◽  
Marwan Fahs ◽  
Benjamin Belfort ◽  
Thomas Graf

<p>Climate change and pollution are posing additional unprecedented threats to existing water resources, especially to water supply from karst aquifers in Mediterranean and semi-arid regions. A numerical model considering the most important key hydraulic parameters can forecast the impact of any given input on model quality and quantity output. In this work, we propose to model flow and transport using Comsol multiphysics in a synthetic model and to apply it to a simplified real case study (Jeita spring in Lebanon supplying water to 1.5 million inhabitants). The model geometry consists of a 5300 m long variably saturated horizontal conduit portrayed as 1) 2-D continuum and/or 2) a channel draining a porous equivalent matrix (400 m thick). Flow is simulated using the Richards Equation in both saturated and unsaturated medium. Recharge is applied vertically as both diffuse and point source in a shaft linked to the conduit. Percentages of fast infiltration rates are obtained from the analysis of event time series recorded at the spring (electrical conductivity and discharge). Flow rates at the outlet are used for transient model calibration. Mean velocities, dispersivities, and phreatic conduit diameters obtained from tracer experiments under various flow periods are used for transport validation in the channel. The aim is to test the validity of a functional simplified flow model on a complex real case and to identify based on a sensitivity analysis the key parameters that allow an optimal calibration of such a model. </p>


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