50,662 research outputs found
An investigation of air and water dual adjustment decoupling control of surface heat exchanger
The terminal equipment of central cooling system accounts for a significant proportion of the total system's energy consumption. Therefore, it is important to reduce the terminal equipment energy consumption in central air conditioning system. In this study, the difference of the effect of the chilled water flow rate and air supply rate on the surface cooler during the heat transfer process is taken into full account. Matlab/Simulink simulation software is used to model and simulate the heat transfer of surface cooler of the main terminal equipment of air conditioning system. Simulation tests and experimental validations are conducted by using variable chilled water flow rate and variable air supply rate control mode separately. The experiment results show that the simulation model can effectively predict the heat transfer performance of heat exchanger. Further, the study introduced a dual feedback control mode, which synchronously regulates the chilled water flow rate and air supply rate. Also, under certain conditions, the complex heat transfer process of the surface cooler can be decoupled, and single variable control pattern is used to separately regulate the chilled water flow rate and air supply rate. This can effectively shorten the system regulation time, reduce overshoot and improve control performance
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Investigate the impacts of assimilating satellite rainfall estimates on rainstorm forecast over southwest United States
Using the MM5-4DVAR system, a monsoon rainstorm case over southern Arizona (5-6 August 2002) was investigated for the influence of assimilating satellite rainfall estimates on precipitation forecasts. A set of numerical experiments was conducted with multiple configurations including using 20-km or 30-km grid distances and none or 3-h or 6-h assimilation time windows. Results show that satellite rainfall assimilation can improve the rainstorm-forecasting pattern and amount to some extent. The minimization procedure of 4DVAR is sensitive to model spatial resolution and the assimilation time window. The 3-h assimilation window with hourly rainfall data works well for the 6-h forecast, and for 12-h or longer forecasts, a 6-h assimilation window will be requested. Copyright 2004 by the American Geophysical Union
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Impact of assimilating rainfall derived from radar and satellites on rainstorm forecasts over the Southwestern United States
The impact of assimilating rainfall derived from radar and satellites on rainstorm forecasts over the Southwestern United States is discussed. The major advantage of 4DVAR is the use of full model dynamics and physics to assimilate multiple-time-level observation data. Rainfall assimilation via 4DVAR is used to improve the moisture distributions in model IC. It is found that by using 4DVAR to generate model IC, the precipitation intensity and patterns can be improved substantially over the mid-latitude plain regions
Why not Merge the International Monetary Fund (IMF) with the International Bank for Reconstruction and Development (World Bank)
Motivation: Cellular Electron CryoTomography (CECT) is an emerging 3D imaging technique that visualizes subcellular organization of single cells at sub-molecular resolution and in near-native state. CECT captures large numbers of macromolecular complexes of highly diverse structures and abundances. However, the structural complexity and imaging limits complicate the systematic de novo structural recovery and recognition of these macromolecular complexes. Efficient and accurate reference-free subtomogram averaging and classification represent the most critical tasks for such analysis. Existing subtomogram alignment based methods are prone to the missing wedge effects and low signal-to-noise ratio (SNR). Moreover, existing maximum-likelihood based methods rely on integration operations, which are in principle computationally infeasible for accurate calculation. Results: Built on existing works, we propose an integrated method, Fast Alignment Maximum Likelihood method (FAML), which uses fast subtomogram alignment to sample sub-optimal rigid transformations. The transformations are then used to approximate integrals for maximum-likelihood update of subtomogram averages through expectation-maximization algorithm. Our tests on simulated and experimental subtomograms showed that, compared to our previously developed fast alignment method (FA), FAML is significantly more robust to noise and missing wedge effects with moderate increases of computation cost. Besides, FAML performs well with significantly fewer input subtomograms when the FA method fails. Therefore, FAML can serve as a key component for improved construction of initial structuralmodels frommacromolecules captured by CECT
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Influence of assimilating rainfall derived from WSR-88D radar on the rainstorm forecasts over the southwestern United States
In this study, the impact of rainfall assimilation on the forecasts of convective rainfall over the mountainous areas in the southwestern United States is investigated. The rainfall is derived from the U.S. Weather Surveillance Radar-1988 Doppler (WSR-88D) radar network, and the fifth-generation Mesoscale Model (MM5) Four-Dimensional Variational (4DVAR) system is employed in the study. We evaluate the rainfall assimilation skill through two rainstorm events (5-6 August and 11-12 September 2002) that occurred over the southwestern United States in 2002. A series of experiments for the two cases is conducted. The results show that the minimization process in the 4DVAR is sensitive to the length of assimilation window and error variance in the observation data. Assimilation of rainfall can produce a better short-range precipitation forecast. However, the time range of improved forecasts is limited to about 15 hours with the model resolution of 20 km. It is indicated that rainfall assimilation produces more realistic moisture divergence and temperature fields in the initial conditions for the two cases. Therefore the forecast of rainstorms is closer to observations in both quantity and pattern. Copyright 2006 by the American Geophysical Union
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Coil combination using linear deconvolution in k-space for phase imaging
Background: The combination of multi-channel data is a critical step for the imaging of phase and susceptibility contrast in magnetic resonance imaging (MRI). Magnitude-weighted phase combination methods often produce noise and aliasing artifacts in the magnitude images at accelerated imaging sceneries. To address this issue, an optimal coil combination method through deconvolution in k-space is proposed in this paper.
Methods: The proposed method firstly employs the sum-of-squares and phase aligning method to yield a complex reference coil image which is then used to calculate the coil sensitivity and its Fourier transform. Then, the coil k-space combining weights is computed, taking into account the truncated frequency data of coil sensitivity and the acquired k-space data. Finally, combining the coil k-space data with the acquired weights generates the k-space data of proton distribution, with which both phase and magnitude information can be obtained straightforwardly. Both phantom and in vivo imaging experiments were conducted to evaluate the performance of the proposed method.
Results: Compared with magnitude-weighted method and MCPC-C, the proposed method can alleviate the phase cancellation in coil combination, resulting in a less wrapped phase.
Conclusions: The proposed method provides an effective and efficient approach to combine multiple coil image in parallel MRI reconstruction, and has potential to benefit routine clinical practice in the future
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