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- Gong, S., et al.
(författare)
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Orientation effect on heat transfer coefficient of a downward surface for flow boiling in a rectangular channel under low flow rate
- 2020
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Ingår i: International Journal of Heat and Mass Transfer. - : Elsevier. - 0017-9310 .- 1879-2189. ; 153
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Tidskriftsartikel (refereegranskat)abstract
- Natural convection boiling in channel with Arc-Shaped will be encountered in the IVR-ERVC (In-Vessel Retention measure by External Reactor Vessel Cooling) system in nuclear power plant under severe accident. The flow and heat transfer characters in this situation is simulated by flow boiling of deionized water in an inclined rectangular channel under low flow rates. This paper aims to separate various parameters (such as orientation, mass flow rate and inlet quality, etc.) to investigate their individual effects on heat transfer coefficient (HTC) in a rectangular channel with cross section of 17 mm × 10 mm. By using a preheater at the inlet of the rectangular channel, the inlet quality could be controlled and the two-phase flow situation could be observed before the fluids entering into the main heater region on one side of the channel wall in downstream. Thus the characteristics of HTC on the main heater could be investigated at different flow patterns. The channel orientations vary from 15 to 90°, the mass flow rates vary from 110 to 288 kg/(m2s) and the qualities vary from 0.003 to 0.036, respectively. Experimental results show that the mass flow rate and quality effects on the HTC are very weak in this study. However, the orientation angle effect on HTC shows an transition region within 45°~60°, while it slowly changes when the orientation angle is smaller than 45° and bigger than 60°. Such tendency could be well formulated by the error function. Compared with different empirical formulas of saturated boiling HTC, it is found that the Liu & Winterton correlation can well predict the experimental HTC results in 90° orientation channel. Based on such correlation and coupled with the error function, a new model was developed by considering the orientation effect, which has an error of ±15% comparing with the experimental data.
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- Li, W., et al.
(författare)
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On improvement of a conditional mornitoring technique for condition-based maintenance
- 2019
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Ingår i: International Conference on Nuclear Engineering, Proceedings, ICONE. - : ASME Press. - 9784888982566
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Konferensbidrag (refereegranskat)abstract
- The condition-based maintenance (CMB) is a hot research topic to overcome the drawbacks belonging to the periodic maintenance used in nuclear power plants nowadays. Auto-Associative Kernel Regression (AAKR) is a widely applied condition monitoring technique which is the basis of a CBM. In this paper, the traditional AAKR is improved by using the ensemble learning technique. The modified AAKR is tested by steady-state operational data of a Tennessee-Eastman chemical process and the results show that it can significantly improve the auto- and cross-sensitivity without reducing the accuracy. This indicates a significant improvement in performance of this condition monitoring technique.
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- Polyakov, A. Y., et al.
(författare)
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Electrical and luminescent properties and the spectra of deep centers in GaMnN/InGaN light-emitting diodes
- 2004
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Ingår i: Journal of Electronic Materials. - : Springer Science and Business Media LLC. - 0361-5235 .- 1543-186X. ; 33:3, s. 241-247
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Tidskriftsartikel (refereegranskat)abstract
- Electrical and electroluminescent properties were studied for GaN/InGaN light-emitting diodes (LEDs) with the n-GaN layer up and with the top portion of the n layer made of undoped GaMnN to allow polarization modulation by applying an external magnetic field (so-called -spin-LEDs-). The contact annealing temperature was kept to 750°C, which is the thermal stability limit for retaining room-temperature magnetic ordering in the GaMnN layer. Measurable electroluminescence (EL) was obtained in these structures at threshold voltages of ∼15 V, with a lower EL signal compared to control LEDs without Mn. This is related to the existence of two parasitic junctions between the metal and the lower contact p-type layer and between the GaMnN and the n-GaN in the top contact layer.
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- Qi, Z., et al.
(författare)
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Application of nonlinear principal component analysis technique to nuclear power plants
- 2019
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Ingår i: International Conference on Nuclear Engineering, Proceedings, ICONE. - : ASME Press. - 9784888982566
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Konferensbidrag (refereegranskat)abstract
- Traditionally, manual calibration of sensors is required and performed during each refueling outage. If the traditional time-directed calibration is replaced by an online monitoring technique, the maintenance cost will be significantly reduced since only the abnormal sensors identified in on-line monitoring need to be re-calibrated or replaced off-line. The Nonlinear Principal Component Analysis (NLPCA), such as Auto-Associative Neural Network (AANN) and Auto-Associative Kernel Principal Component Analysis (AAKPCA), can describe the nonlinear correlation between sensors such as power, temperature, pressure and flowrate. In this paper, AANN and AAKPCA model are tested by simulated redundant data and Tennessee-Eastman process data. The results show that both of them have a high ability of prediction and a low sensitivity. Therefore, they are can be used in on-line monitoring.
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- Qi, Z., et al.
(författare)
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Sensor fault detection in nuclear power plant using auto-associative neural network
- 2019
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Ingår i: International Conference on Nuclear Engineering, Proceedings, ICONE. - : American Society of Mechanical Engineers (ASME). - 9784888983051
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Konferensbidrag (refereegranskat)abstract
- Fault diagnosis system usually includes a prediction module and a diagnosis module. The prediction module is supposed to predict sensor values based on sensor observations, and the diagnosis module is used to determine whether a sensor has degradation or failure by comparing the difference between sensor observations and predictions. Auto-Associative Neural Network (AANN) is a widely applied data-driven prediction method consisting of input layer, mapping layer, bottleneck layer, de-mapping layer and output layer. AANN compresses the information contained in the input data (i.e. sensor observations) into bottleneck layer through mapping layer, and then reconstructs the sensor values at output layer based on the extracted nonlinear features stored in bottleneck layer through de-mapping layer. This paper focuses on the feasibility study of AANN model in fault diagnosis for nuclear power plants. The performance of AANN model was studied by using simulation data, and the AANN model was optimized by combining prejudgment and secondary prediction. The results show that the optimized AANN model can improve the performance comparing to original AANN model, and can be applied to the fault diagnosis for nuclear power plant sensors.
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- Thinh, N. Q., et al.
(författare)
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Identification of Ga-interstitial defects in GaNyP1−y and AlxGa1−xNyP1−y
- 2004
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Ingår i: Physical Review B. Condensed Matter and Materials Physics. - : APS. - 1098-0121 .- 1550-235X. ; 70:12, s. 121201-
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Tidskriftsartikel (refereegranskat)abstract
- Two Ga -interstitial (Gai) defects are identified by optically detected magnetic resonance as common grown-in defects in molecular beam epitaxial GaNyP1−y and AlxGa1−xNyP1−y. Characteristic hyperfine structure arising from spin interaction between an unpaired electron and a Ga nucleus is clearly resolved. The observed strong and nearly isotropic hyperfine interaction reveals an electron wave function of A1 symmetry that is highly localized at the Gai and thus a deep-level defect. Our analysis based on first-principles calculations suggests that these defects are complexes containing one Gai2+ .
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| 10. |
- Thinh, N.Q., et al.
(författare)
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Properties of Ga-interstitial defects in AlxGa 1-xNyP1-y
- 2005
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Ingår i: Physical Review B. Condensed Matter and Materials Physics. - 1098-0121 .- 1550-235X. ; 71:12
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Tidskriftsartikel (refereegranskat)abstract
- A detailed account of the experimental results from optically detected magnetic resonance (ODMR) studies of grown-in defects in (Al)GaNP alloys, prepared by molecular beam epitaxy, is presented. The experimental procedure and an in-depth analysis by a spin Hamiltonian lead to the identification of two Gai defects (Gai-A and Gai-B). New information on the electronic properties of these defects and the recombination processes leading to the observation of the ODMR signals will be provided. These defects are deep-level defects. In conditions when the defect is directly involved in radiative recombination of the near-infrared photoluminescence band, the energy level of the Gai-B defect was estimated to be deeper than ~1.2 eV from either the conduction or valence band edge. In most cases, however, these defects act as nonradiative recombination centers, reducing the efficiency of light emission from the alloys. They can thus undermine the performance of potential photonic devices. High thermal stability is observed for these defects. ©2005 The American Physical Society.
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