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Jara A.J.,University of Applied Sciences and Arts Western Switzerland | Dufour L.,University of Applied Sciences and Arts Western Switzerland | Rizzo G.,University of Applied Sciences and Arts Western Switzerland | Pawlowski M.P.,University of Applied Sciences and Arts Western Switzerland | And 4 more authors.
International Journal of Data Warehousing and Mining | Year: 2016

Microgrids present the challenge to reach a proper balance between local production and consumption, in order to reduce the usage of energy from external sources. This work presents a data-intensive solution to predict the energy behaviors. Thereby, control actions can be carried out such as decrease heating systems levels and switch of low-priority devices. For this purpose, this work has deployed an Advanced Metering Infrastructure (AMI) based on the Internet of Things (IoT) in the Techno-Pole testbed. This deployment provides the data from energy-related parameters such as load curves of the overall building through Non-Intrusive Load Monitoring (NILM), a wireless network of IoT-based smart meters to measure and control appliances, and finally the generated power curve by 2000 square meters of photovoltaic panels. The prediction model proposed is based on recognition of electrical signatures. These electrical signatures have been used to detect complex usage patterns. The modelled patterns have allowed to identify the work day of the week, and predict the load and generation curves for 15 minutes with accuracy over the 90%. This short-term prediction allows one to carry out the proper actions in order to balance the microgrid status (i.e., get a proper balance between production and consumption with respect to worked requirements). Copyright © 2016, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Source


Bentaib A.,Institute for Radiological Protection and Nuclear Safety | Bleyer A.,Institute for Radiological Protection and Nuclear Safety | Meynet N.,Institute for Radiological Protection and Nuclear Safety | Chaumeix N.,Institute Icare | And 10 more authors.
Annals of Nuclear Energy | Year: 2014

In case of a core melt-down accident in a light water nuclear reactor, hydrogen is produced during reactor core degradation and released into the reactor building. This subsequently creates a combustion hazard. A local ignition of the combustible mixture may generate standing flames or initially slow propagating flames. Depending on geometry, mixture composition and turbulence level, the flame can accelerate or be quenched after a certain distance. The loads generated by the combustion process (increase of the containment atmosphere pressure and temperature) may threaten the integrity of the containment building and of internal walls and equipment. Turbulent deflagration flames may generate high pressure pulses, temperature peaks, shock waves and large pressure gradients which could severely damage specific containment components, internal walls and/or safety equipment. The evaluation of such loads requires validated codes which can be used with a high level of confidence. Currently, turbulence and steam effect on flame acceleration, flame deceleration and flame quenching mechanisms are not well reproduced by combustion models usually implemented in safety tools and further model enhancement and validation are still needed. For this purpose, two hydrogen deflagration benchmark exercises have been organised in the framework of the SARNET network. The first benchmark was focused on turbulence effect on flame propagation. For this purpose, three tests performed in the ENACCEF facility were considered. They concern vertical flame propagation in an initially homogenous mixture with 13 vol.% hydrogen content and different geometrical configurations. Three blockage ratios of 0, 0.33 and 0.6 were considered to generate different levels of turbulence. The second benchmark objective was the investigation of the diluting effect on flame propagation. Thus, three tests performed in the ENACCEF facility using the same blockage ratio of 0.63 and three different initial gas compositions (with 10, 20 and 30 vol.% diluents) have been considered. Since ENACCEF runs at ambient temperature, a surrogate to steam was used consisting of a mixture of 0.6He + 0.4CO2 on molar basis. This paper aims to present the benchmarks conclusions regarding the ability of LP and CFD combustion models to predict the effect of turbulence and diluent on flame propagation. © 2014 Elsevier Ltd. Source


Alves B.,University of Applied Sciences and Arts Western Switzerland | Schumacher M.,University of Applied Sciences and Arts Western Switzerland | Cretton F.,University of Applied Sciences and Arts Western Switzerland | Le Calve A.,University of Applied Sciences and Arts Western Switzerland | And 6 more authors.
ICEIS 2013 - Proceedings of the 15th International Conference on Enterprise Information Systems | Year: 2013

This paper presents solutions that leverage SemanticWeb Technologies (SWT) to allow pragmatic traceability in supply-chains, especially for the textile industry. Objectives are the identification of the supply-chain, order management, tracking and problem reporting (such as dangerous substance detection). It is intended to be a generic platform supporting potentially any kind of industrial supply-chain, to be usable in harsh environments (mobile appliances) without any kind of communications possibility and to be fully usable to non-IT people, including for the modeling of the production processes. The developed solutions also allow the consumer to benefit from the traceability through information pages available by scanning the QR codes available on the finished products (clothes, clocks, etc.). This paper presents: i) the methodology applied to achieve those functionalities, ii) the design and implementation choices, and iii) the test results. The main value of this paper is the usage of the SemanticWeb in real-world industrial traceability solutions, which were tested in real supply-chains in Switzerland and India. The commercialization of the developed solutions is in preparation. Source


Alves B.,Applied Information Sciences | Schumacher M.,Applied Information Sciences | Cretton F.,Applied Information Sciences | Le Calve A.,Applied Information Sciences | And 6 more authors.
Lecture Notes in Business Information Processing | Year: 2014

This paper presents solutions that leverage Semantic Web Technologies (SWT) to allow pragmatic traceability in supply-chains, especially for the textile industry. Objectives are the identification of the supply-chain, order management, tracking and problem reporting (such as dangerous substance detection). It is intended to be a generic platform supporting potentially any kind of industrial supply-chain, to be usable in harsh environments (mobile appliances) without any kind of communications possibility and to be fully usable to non-IT people, including for the modelling of the production processes. The developed solutions also allow the consumer to benefit from the traceability through information pages available by scanning the QR codes available on the finished products (clothes, clocks, etc.). This paper presents: (i) the methodology applied to achieve those functionalities, (ii) the design and implementation choices, and (iii) the test results. The main value of this paper is the usage of the Semantic Web in real-world industrial traceability solutions, which were tested in real supply-chains in Switzerland and India. The commercialization of the developed solutions has started. © Springer International Publishing Switzerland 2014. Source

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