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- Ebadat, Afrooz, et al.
(författare)
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Application-oriented input design for room occupancy estimation algorithms
- 2017
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Ingår i: 2017 IEEE 56TH ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC). - Piscataway, NJ : IEEE. - 9781509028733 - 9781509028740
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Konferensbidrag (refereegranskat)abstract
- We consider the problem of occupancy estimation in buildings using available environmental information. In particular, we study the problem of how to collect data that is informative enough for occupancy estimation purposes. We thus propose an application-oriented input design approach for designing the ventilation signal to be used while collecting the system identification datasets. The main goal of the method is to guarantee a certain accuracy in the estimated occupancy levels while minimizing the experimental time and effort. To take into account potential limitations on the actuation signals we moreover formulate the problem as a recursive nonlinear and nonconvex optimization problem, solved then using exhaustive search methods. We finally corroborate the theoretical findings with some numerical examples, which results show that computing ventilation signals using experiment design concepts leads to occupancy estimator performing 4 times better in terms of Mean Square Error (MSE).
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- Lionello, M., et al.
(författare)
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Graph-based modelling and simulation of liquid immersion cooling systems
- 2020
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Ingår i: Energy. - : Elsevier Ltd. - 0360-5442 .- 1873-6785. ; 207
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Tidskriftsartikel (refereegranskat)abstract
- Currently, most of the existing data centers use chilled air to remove the heat produced by the servers. However, liquids have generally better heat dissipation capabilities than air, thus liquid cooling systems are expected to become a standard choice in future data centers. Designing and managing these cooling units benefit from having control-oriented models that can accurately describe the thermal status of both the coolant and the heat sources. This manuscript derives a control-oriented model of liquid immersion cooling systems, i.e., systems where servers are immersed in a dielectric fluid having good heat transfer properties. More specifically, we derive a general lumped-parameters gray box dynamical model that mimics energy and mass transfer phenomena that occur between the main components of the system. The proposed model is validated against experimental data gathered during the operation of a proof-of-concept immersion cooling unit, showing good approximation capabilities.
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- Lionello, M., et al.
(författare)
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Lumped-parameters control-oriented gray-box modelling of liquid immersion cooling systems
- 2019
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Ingår i: 2019 18th European Control Conference, ECC 2019. - : Institute of Electrical and Electronics Engineers Inc.. - 9783907144008 ; , s. 3861-3866
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Konferensbidrag (refereegranskat)abstract
- Liquid cooling systems have better heat dissipation capabilities than air based ones, and are expected to become a standard choice in future data centers, due to the ever increasing power density and heat rejection needs of the compute infrastructure. A convenient side-effect of implementing liquid cooling is that it facilitates the efficient recovery of the heat waste. However designing and managing these heat recovery infrastructures benefit from having control-oriented models that can accurately describe how different operating conditions of the to-be-cooled heat sources will affect the thermal status of the coolant. The aim of this manuscript is to derive control-oriented models of liquid immersion cooling systems, i.e., systems where the compute infrastructure is immersed in a vessel filled with dielectric fluid. More specifically we derive, starting from physical interpretations, a general lumped-parameters gray box dynamical model that has-as inputs-the electrical consumption of the heat sources and the working point of the heat recovery system, and has-as outputs-the temperature distribution of the coolant in the most relevant points of the system. Beyond proposing this modelling methodology we also validate the generalization capabilities of the obtainable models. In specific, we test the achievable statistical performances in a field case, plus compare with the ones of classical black box system identification strategies. We thus report that in the considered field case our gray box model reached a fit index of 91.08% when simulating test sets, while the best black box model we have been able to identify reached (on the same test sets) fit indexes of only 72.56%.
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