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1.
《International Journal of Hydrogen Energy》2022,47(12):7600-7623
In this paper, a salinity gradient solar pond (SGSP) is used to harness the solar energy for hydrogen production through two cycles. The first cycle includes an absorption power cycle (APC), a proton exchange membrane (PEM) electrolyzer, and a thermoelectric generator (TEG) unit; in the second one, an organic Rankine cycle (ORC) with the zeotropic mixture is used instead of APC. The cycles are analyzed through the thermoeconomic vantage point to discover the effect of key decision variables on the cycles’ performance. Finally, NSGA-II is used to optimize both cycles. The results indicate that employing ORC with zeotropic mixture leads to a better performance in comparison to utilizing APC. For the base mode, unit cost product (UCP), exergy, and energy efficiency when APC is employed are 59.9 $/GJ, 23.73%, and 3.84%, respectively. These amounts are 47.27 $/GJ, 29.48%, and 5.86% if ORC with the zeotropic mixture is utilized. The APC and ORC generators have the highest exergy destruction rate which is equal to 6.18 and 10.91 kW. In both cycles, the highest investment cost is related to the turbine and is 0.8275 $/h and 0.976 $/h for the first and second cycles, respectively. In the optimum state the energy efficiency, exergy efficiency, UCP, and H2 production rate of the system enhances 42.44%, 27.54%,15.95%, and 38.24% when ORC with the zeotropic mixture is used. The maximum H2 production is 0.47 kg/h, and is obtained when the mass fraction of R142b, LCZ temperature, pumps pressure ratio, generator bubble point temperature are 0.603, 364.35 K, 2.12, 337.67 K, respectively. 相似文献
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As a highly complex and time-varying process, gas-water two-phase flow is commonly encountered in industries. It has a variety of typical flow states and transition flow states. Accurate identification and monitoring of flow states is not only beneficial to further study of two-phase flow but also helpful for stable operation and economic efficiency of process industry. Combining canonical variate analysis (CVA) and Gaussian mixture model (GMM), a strategy called multi-CVA-GMM is proposed for flow state monitoring in gas-water two-phase flow. CVA is used to extract flow state features from the perspective of correlation between historical data and future data, which solves the cross correlation and temporal correlation of multi-sensor measurement data. GMM calculates the possibility that the current flow state belongs to each typical flow pattern and judges the current flow state by probability indicators. It is conducive to follow-up use of Bayesian inference probability and Mahalanobis distance-based (BID) indicator for flow state monitoring, which avoids repeated traversal of multiple CVA-GMM models and improves the efficiency of the monitoring process. The probability indicators can also be used to analyze transition flow states. The method combining the probabilistic idea of GMM with the deterministic idea of multimodal modeling can accurately identify the current flow state and effectively monitor the evolution of flow state. The multi-CVA-GMM method is validated by using the measured data of the horizontal flow loop of gas-water two-phase flow experimental facility, and its effectiveness is proved. 相似文献
4.
This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning
of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed
Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given
visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample
size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive
experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr
and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood
(ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given
sparse data, while CL-AIC should be chosen given moderate or large data sample sizes. 相似文献
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The main difficulty with EM algorithm for mixture model concerns the number of components, say g. This is the question of model selection, and the EM algorithm itself could not estimate g. On the contrary, the algorithm requires g to be specified before the remaining parameters can be estimated. To solve this problem, a new algorithm, which is called stepwise split-and-merge EM (SSMEM) algorithm, is proposed. The SSMEM algorithm alternately splits and merges components, estimating g and other parameters of components simultaneously. Also, two novel criteria are introduced to efficiently select the components for split or merge. Experimental results on simulated and real data demonstrate the effectivity of the proposed algorithm. 相似文献
8.
N. E. Wijeysundera M. N. A. Hawlader Chan Wee Boon Andy M. Kamal Hossain 《International Journal of Refrigeration》2004,27(5):1997
An ice slurry generation system was developed using direct contact heat transfer between water and the coolant, Fluroinert FC-84. The location of the coolant nozzle is an important design consideration to avoid clogging due to freezing of water. An ice fraction of up to about 40 percent was obtained with the nozzle located at the bottom of the ice slurry tank and the jet directed upwards into the water. Two simplified model were developed to extract the heat transfer coefficient between the coolant drops and the water. The first model requires as input the average drop diameter and the residence time while the second model uses the measured drop diameter distribution. The estimated heat transfer coefficients are much smaller than those computed using single-sphere correlations. 相似文献
9.
Wiltrout Charles; Dogra Samriti; Linster Christiane 《Canadian Metallurgical Quarterly》2003,117(2):236
Studies on odor mixture perception suggest that although odor components can often be identified in mixtures, mixtures can also give rise to novel perceptual qualities that are not present in the components. Using an olfactory habituation task, the authors evaluated how the perceptual similarity between components in a mixture affects the perceptual quality of the mixture itself. Rats perceived binary mixtures composed of similar components as different from their 2 components, whereas binary mixtures composed of dissimilar components were perceived as very similar to their components. Results show that for both types of mixtures, pretraining to Component A reduces subsequent learning about Component B in rats trained in the presence of A. (PsycINFO Database Record (c) 2010 APA, all rights reserved) 相似文献
10.
神经网络用于三元分子混合物密度与粘度的预测 总被引:5,自引:3,他引:2
以二元系实验为基础,利用反向转播算法训练神经网络,构造混合物组成,温度等与物性关系的模型,用于对4个三元混合物体系(1)邻二甲苯-间二甲苯-对二甲苯;(2)四氯化碳-环己烷-2-丙醇;(3)甲醇-丙酮-水;(4)水-甲醇-乙二醇的密度和5个三元混合物体系(1)信甲苯-间二甲苯-对二甲苯;(2)四氯化碳-环己烷-2-丙醇;(3)氯仿-2-丙醇-2-丁醇;(4)甲醇-丙酮-水;(5)乙醇-甲醇-水的粘 相似文献