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222 results on '"Liu, Yueliang"'

4. Parametric Sparse Bayesian Dictionary Learning for Multiple Sources Localization with Propagation Parameters Uncertainty and Nonuniform Noise

Author

You, Kangyong, Guo, Wenbin, Peng, Tao, Liu, Yueliang, Zuo, Peiliang, and Wang, Wenbo

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

Received signal strength (RSS) based source localization method is popular due to its simplicity and low cost. However, this method is highly dependent on the propagation model which is not easy to be captured in practice. Moreover, most existing works only consider the single source and the identical measurement noise scenario, while in practice multiple co-channel sources may transmit simultaneously, and the measurement noise tends to be nonuniform. In this paper, we study the multiple co-channel sources localization (MSL) problem under unknown nonuniform noise, while jointly estimating the parametric propagation model. Specifically, we model the MSL problem as being parameterized by the unknown source locations and propagation parameters, and then reformulate it as a joint parametric sparsifying dictionary learning (PSDL) and sparse signal recovery (SSR) problem which is solved under the framework of sparse Bayesian learning with iterative parametric dictionary approximation. Furthermore, multiple snapshot measurements are utilized to improve the localization accuracy, and the Cramer-Rao lower bound (CRLB) is derived to analyze the theoretical estimation error bound. Comparing with the state-of-the-art sparsity-based MSL algorithms as well as CRLB, extensive simulations show the importance of jointly inferring the propagation parameters,and highlight the effectiveness and superiority of the proposed method., Comment: 12 pages, 9 figures

Published
2019
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5. Graph Learning for Spatiotemporal Signals with Long- and Short-Term Characterization

Author

Liu, Yueliang, Guo, Wenbin, You, Kangyong, Zhao, Lei, Peng, Tao, and Wang, Wenbo

Subjects
Computer Science - Social and Information Networks, Electrical Engineering and Systems Science - Signal Processing
Abstract

Mining natural associations from high-dimensional spatiotemporal signals plays an important role in various fields including biology, climatology, and financial analysis. However, most existing works have mainly studied time-independent signals without considering the correlations of spatiotemporal signals that achieve high learning accuracy. This paper aims to learn graphs that better reflect underlying data relations by leveraging the long- and short-term characteristics of spatiotemporal signals. First, a spatiotemporal signal model is presented that considers both spatial and temporal relations. In particular, we integrate a low-rank representation and a Gaussian Markov process to describe the temporal correlations. Then, the graph learning problem is formulated as a joint low-rank component estimation and graph Laplacian inference. Accordingly, we propose a low rank and spatiotemporal smoothness-based graph learning method (GL-LRSS), which introduces a spatiotemporal smoothness prior into time-vertex signal analysis. By jointly exploiting the low rank of long-time observations and the smoothness of short-time observations, the overall learning performance can be effectively improved. Experiments on both synthetic and real-world datasets demonstrate substantial improvements in the learning accuracy of the proposed method over the state-of-the-art low-rank component estimation and graph learning methods., Comment: 13 pages, 6 figures

Published
2019
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11. CO 2 Utilization and Sequestration in Organic and Inorganic Nanopores During Depressurization and Huff-n-Puff Process.

Author

Guo, Jiadong, Kong, Shaoqi, Li, Kunjie, Ren, Guoan, Yang, Tao, Dong, Kui, and Liu, Yueliang

Subjects
CARBON sequestration, SHALE gas, OIL shales, PRESSURE drop (Fluid dynamics), MESOPORES, GEOLOGICAL carbon sequestration, NANOPORES
Abstract

CO2 injection in shale reservoirs is more suitable than the conventional recovering methods due to its easier injectivity and higher sweep efficiency. In this work, Grand Canonical Monte Carlo (GCMC) simulation is employed to investigate the adsorption/desorption behavior of CH4-C4H10 and CH4-C4H10-CO2 mixtures in organic and inorganic nanopores during pressure drawdown and CO2 huff and puff processes. The huff and puff process involves injecting CO2 into the micro- and mesopores, where the system pressure is increased during the huffing process and decreased during the puffing process. The fundamental mechanism of shale gas recovery using the CO2 injection method is thereby revealed from the nanopore-scale perspective. During primary gas production, CH4 is more likely to be produced as the reservoir pressure drops. On the contrary, C4H10 tends to be trapped in these organic nanopores and is hard to extract, especially from micropores and inorganic pores. During the CO2 huffing period, the adsorbed CH4 and C4H10 are recovered efficiently from the inorganic mesopores. On the contrary, the adsorbed C4H10 is slightly extracted from the inorganic micropores during the CO2 puffing period. During the CO2 puff process, the adsorbed CH4 desorbs from the pore surface and is thus heavily recovered, while the adsorbed C4H10 cannot be readily produced. During CO2 huff and puff, the recovery efficiency of CH4 is higher in the organic pores than that in the inorganic pores. More importantly, the recovery efficiency of C4H10 reaches the highest levels in both the inorganic and organic pores during the CO2 huff and puff process, suggesting that the CO2 huff and puff method is more advanced for heavier hydrocarbon recovery compared to the pressure drawdown method. In addition to CO2 storage, CO2 sequestration in the adsorbed state is safer than that in the free state. In our work, it was found that the high content of organic matter, high pressure, and small pores are beneficial factors for CO2 sequestration transforming into adsorbed state storage. [ABSTRACT FROM AUTHOR]

Published
2024
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23. An Integrated Framework for Geothermal Energy Storage with CO2 Sequestration and Utilization

Author

Liu, Yueliang, Hu, Ting, Rui, Zhenhua, Zhang, Zheng, Du, Kai, Yang, Tao, Dindoruk, Birol, Halfdan Stenby, Erling, Torabi, Farshid, Afanasyev, Andrey, Liu, Yueliang, Hu, Ting, Rui, Zhenhua, Zhang, Zheng, Du, Kai, Yang, Tao, Dindoruk, Birol, Halfdan Stenby, Erling, Torabi, Farshid, and Afanasyev, Andrey

Abstract

Subsurface geothermal energy storage has greater potential than other energy storage strategies in terms of capacity scale and time duration. Carbon dioxide (CO2) is regarded as a potential medium for energy storage due to its superior thermal properties. Moreover, the use of CO2 plumes for geothermal energy storage mitigates the greenhouse effect by storing CO2 in geological bodies. In this work, an integrated framework is proposed for synergistic geothermal energy storage and CO2 sequestration and utilization. Within this framework, CO2 is first injected into geothermal layers for energy accumulation. The resultant high-energy CO2 is then introduced into a target oil reservoir for CO2 utilization and geothermal energy storage. As a result, CO2 is sequestrated in the geological oil reservoir body. The results show that, as high-energy CO2 is injected, the average temperature of the whole target reservoir is greatly increased. With the assistance of geothermal energy, the geological utilization efficiency of CO2 is higher, resulting in a 10.1% increase in oil displacement efficiency. According to a storage-potential assessment of the simulated CO2 site, 110 years after the CO2 injection, the utilization efficiency of the geological body will be as high as 91.2%, and the final injection quantity of the CO2 in the site will be as high as 9.529 × 108 tonnes. After 1000 years sequestration, the supercritical phase dominates in CO2 sequestration, followed by the liquid phase and then the mineralized phase. In addition, CO2 sequestration accounting for dissolution trapping increases significantly due to the presence of residual oil. More importantly, CO2 exhibits excellent performance in storing geothermal energy on a large scale; for example, the total energy stored in the studied geo

Published
2024

24. An Efficient Algorithm for Invulnerability Enhancement in Cognitive Ad Hoc Networks

Author

Zhang, Xiao, Wang, Yukun, Liu, Yueliang, Guo, Wenbin, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martin, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Liu, Xin, editor, Na, Zhenyu, editor, Wang, Wei, editor, Mu, Jiasong, editor, and Zhang, Baoju, editor

Published
2019
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25. Joint Sparse-AR Model Based OFDM Compressed Sensing Time-Varying Channel Estimation

Author

Li, Shanshan, You, Kangyong, Liu, Yueliang, Guo, Wenbin, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martin, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Liu, Xin, editor, Na, Zhenyu, editor, Wang, Wei, editor, Mu, Jiasong, editor, and Zhang, Baoju, editor

Published
2019
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34. 1.2 kW, 20 kHz Nanosecond Nd:YAG Slab Laser System.

Author

Liu, Hao, Qiu, Jisi, Chen, Yanzhong, Wang, Haocheng, Wang, Tianqi, Liu, Yueliang, Song, Xiaoquan, and Fan, Zhongwei

Subjects
FIBER lasers, POWER amplifiers, OPTICAL amplifiers, Q-switched lasers, SURFACE cleaning, ND-YAG lasers
Abstract

In this paper, we develop a kW-level high-repetition-rate nanosecond master oscillator power amplifier (MOPA) laser system, employing a structure of fiber, Nd:YVO4, and Nd:YAG hybrid amplification. A tunable fiber seed source is used for adjustable pulse repetition frequency and pulse width. The Nd:YVO4 pre-amplifier, which is dual-end-pumped, achieves high gain while maintaining good beam quality, and the high-power side-pumped Nd:YAG slab main-amplifier enables efficient power amplification. The repetition rate of the output laser can be adjusted within the range of 1~20 kHz, and the pulse width can be tuned within the range of 10~300 ns. The seed output is 6 mW at a repetition frequency of 20 kHz; we achieve an average output power of 1240 W with a total power extraction efficiency of 39.1% and single-pulse energy of 62 mJ at a pulse width of 301 ns. This parameter-controllable high-power laser holds promise for applications in the laser cleaning of complex surface contaminants. [ABSTRACT FROM AUTHOR]

Published
2024
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42. Development and Applications of CO 2 -Responsive Gels in CO 2 Flooding and Geological Storage.

Author

Ding, Yanxu, Zhao, Yang, Wen, Xin, Liu, Yueliang, Feng, Ming, and Rui, Zhenhua

Subjects
GEOLOGICAL carbon sequestration, HETEROGENEITY, POLYMER colloids, GAS leakage, GAS injection
Abstract

Gel systems are widely used as plugging materials in the oil and gas industry. Gas channeling can be mitigated by reducing the heterogeneity of the formation and the mobility ratio of CO2 to crude oil. Cracks and other CO2 leaking pathways can be plugged during the geological storage of CO2 to increase the storage stability. By adding CO2-responsive groups to the classic polymer gel's molecular chain, CO2 responsive gel is able to seal and recognize CO2 in the formation while maintaining the superior performance of traditional polymer gel. The application of CO2 responsive gels in oil and gas production is still in the stage of laboratory testing on the whole. To actually achieve the commercial application of CO2 responsive gels in the oil and gas industry, it is imperative to thoroughly understand the CO2 responsive mechanisms of the various types of CO2 responsive gels, as well as the advantages and drawbacks of the gels and the direction of future development prospects. This work provides an overview of the research progress and response mechanisms of various types of CO2 responsive groups and CO2 responsive gels. Studies of the CO2 responsive gel development, injectivity, and plugging performance are comprehensively reviewed and summarized. The shortcomings of the existing CO2 responsive gels system are discussed and the paths for future CO2 responsive gel development are suggested. [ABSTRACT FROM AUTHOR]

Published
2023
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48. Energy Extraction and Processing Science.

Author

Kong, Shaoqi, Feng, Gan, Liu, Yueliang, and Wen, Chuang

Subjects
COAL gasification, SHALE gas reservoirs, THERMODYNAMICS, SHALE gas, SHALE oils, GEOTHERMAL resources, THERMAL shock, GEOTHERMAL engineering, PETROLEUM
Published
2023
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