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- 2019
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Tidskriftsartikel (refereegranskat)
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| 2. |
- Bao, Chengying, et al.
(författare)
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Observation of Breathing Dark Pulses in Normal Dispersion Optical Microresonators
- 2018
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Ingår i: Physical Review Letters. - 1079-7114 .- 0031-9007. ; 121:25
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Tidskriftsartikel (refereegranskat)abstract
- Breathers are localized waves in nonlinear systems that undergo a periodic variation in time or space. The concept of breathers is useful for describing many nonlinear physical systems including granular lattices, Bose-Einstein condensates, hydrodynamics, plasmas, and optics. In optics, breathers can exist in either the anomalous or the normal dispersion regimes, but they have only been characterized in the former, to our knowledge. Here, externally pumped optical microresonators are used to characterize the breathing dynamics of localized waves in the normal dispersion regime. High-Q optical microresonators featuring normal dispersion can yield mode-locked Kerr combs whose time-domain waveform corresponds to circulating dark pulses in the cavity. We show that with relatively high pump power these Kerr combs can enter a breathing regime, in which the time-domain waveform remains a dark pulse but experiences a periodic modulation on a time scale much slower than the microresonator round trip time. The breathing is observed in the optical frequency domain as a significant difference in the phase and amplitude of the modulation experienced by different spectral lines. In the highly pumped regime, a transition to a chaotic breathing state where the waveform remains dark-pulse-like is also observed, for the first time to our knowledge; such a transition is reversible by reducing the pump power.
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| 3. |
- Gu, Jihao, et al.
(författare)
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Analysis of a hybrid control scheme in the district heating system with distributed variable speed pumps
- 2019
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Ingår i: Sustainable Cities and Society. - : Elsevier BV. - 2210-6707. ; 48
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Tidskriftsartikel (refereegranskat)abstract
- Compared with conventional central circulating pumps (CCCPs)in the district heating system (DHS), the DHS with distributed variable speed pumps (DVSPs)shows a great potential for energy saving. In this paper, a hybrid control scheme both using electric control valves (ECVs)and DVSPs is applied to the district heating system in Shenyang, China. This new hybrid control system results in reduction of the boiler outlet pressure from 1.27 MPa to 0.81 MPa, which ensures safe operation of the heating network. In addition, the hydraulic imbalance of the primary pipelines is effectively reduced by using the DVSPs. It is found that the relative error between the designed and the measured total flow rates is 7.71%. Results show that the annual average value of electricity consumption by using the DVSPs is 28.52% smaller than that in the CCCP system. Therefore, there is a great potential for building energy saving if the DVSPs are installed into the DHS. In order to evaluate the heating quantity and guide the optimal operation for the DHS, indoor temperature acquisition devices will be installed in the near future.
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| 4. |
- Gu, Jihao, et al.
(författare)
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Medium-term heat load prediction for an existing residential building based on a wireless on-off control system
- 2018
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Ingår i: Energy. - : Elsevier BV. - 0360-5442. ; 152, s. 709-718
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Tidskriftsartikel (refereegranskat)abstract
- For district heating systems, prediction of the heat load is a very important topic for energy storage and optimized operation. For large and complex heating systems, most prediction models in previous publications only considered the influence of outdoor temperature, whereas the indoor temperature and thermal inertia of buildings were not included. For an energy-efficient residential building in Shijiazhuang (China), the heat load prediction is investigated using various prediction models, including a wavelet neural network (WNN), extreme learning machine (ELM), support vector machine (SVM) and back propagation neural network optimized by a genetic algorithm (GA-BP). In these models, the indoor temperature and historical loads are considered as influencing factors. It is found that the prediction accuracies of the ELM and GA-BP are slightly higher than that of WNN, so the ELM and GA-BP models provide feasible methods for the heat load prediction. The SVM shows smaller relative errors in the model prediction compared with three neural network algorithms.
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