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183 results on '"Zhang, Zhenghui"'

29. Electrification-Enhanced Low-Temperature NOxStorage–Reduction on Pt and K Co-Supported Antimony-Doped Tin Oxides

Author

Mei, Xueyi, Xin, Ying, Zhang, Yexin, Nie, Weiming, Zhang, Zhenghui, Lu, Peng, Zhang, Zhaoliang, Chen, Guoxin, and Zhang, Jian

Abstract

NOxstorage–reduction (NSR), a promising approach for removing NOxpollutants from diesel vehicles, remains elusive to cope with the increasingly lower exhaust temperatures (especially below 250 °C). Here, we develop a conceptual electrified NSR strategy, where electricity with a low input power (0.5–4 W) is applied to conductive Pt and K co-supported antimony-doped tin oxides (Pt–K/ATO), with C3H6as a reductant. The ignition temperature for 10% NOxconversion is nearly 100 °C lower than that of the traditional thermal counterpart. Furthermore, reducing the power in the fuel-lean period relative to that in the fuel-rich period increases the maximum energy efficiency by 23%. Electrically driven release of lattice oxygen is revealed to play vital roles in multiple steps in NSR, including NO adsorption, desorption, and reduction, for improved NSR activity. This work provides an electrification strategy for developing high-activity NSR catalysis utilizing electricity onboard hybrid vehicles.

Published
2023
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48. Performance analysis and comparison of PoW, PoS and DAG based blockchains

Author

Zhang Zhenghui, Shengli Zhang, Bin Cao, Mugen Peng, Lei Zhang, Daquan Feng, and Yun Li

Subjects
Proof of work, Direct acyclic graph, Theoretical computer science, Performance comparison, lcsh:T58.5-58.64, Computer Networks and Communications, Computer science, lcsh:Information technology, Process (computing), 020206 networking & telecommunications, Proof of stake, 02 engineering and technology, Proof-of-stake, 020210 optoelectronics & photonics, Resource (project management), Blockchain, Hardware and Architecture, Technical analysis, Proof-of-work system, 0202 electrical engineering, electronic engineering, information engineering, Key (cryptography), Database transaction, Block (data storage)
Abstract

In the blockchain, the consensus mechanism plays a key role in maintaining the security and legitimation of contents recorded in the blocks. Various blockchain consensus mechanisms have been proposed. However, there is no technical analysis and comparison as a guideline to determine which type of consensus mechanism should be adopted in a specific scenario/application. To this end, this work investigates three mainstream consensus mechanisms in the blockchain, namely, Proof of Work (PoW), Proof of Stake (PoS), and Direct Acyclic Graph (DAG), and identifies their performances in terms of the average time to generate a new block, the confirmation delay, the Transaction Per Second (TPS) and the confirmation failure probability. The results show that the consensus process is affected by both network resource (computation power/coin age, buffer size) and network load conditions. In addition, it shows that PoW and PoS are more sensitive to the change of network resource while DAG is more sensitive to network load conditions.

Published
2020

50. A many-objective evolutionary algorithm based on dominance and decomposition with reference point adaptation

Author

Juan Zou, Zhang Zhenghui, Shengxiang Yang, and Jinhua Zheng

Subjects
Pareto optimality, Mathematical optimization, Information Systems and Management, Optimization problem, Computer science, Process (engineering), Reference point adaptation, Evolutionary algorithm, Multi-objective optimization, Management Information Systems, Many-objective optimization, Artificial Intelligence, Convergence (routing), Benchmark (computing), Decomposition (computer science), sort, Software
Abstract

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Achieving balance between convergence and diversity is a challenge in many-objective optimization problems (MaOPs). Many-objective evolutionary algorithms (MaOEAs) based on dominance and decomposition have been developed successfully for solving partial MaOPs. However, when the optimization problem has a complicated Pareto front (PF), these algorithms show poor versatility in MaOPs. To address this challenge, this paper proposes a co-guided evolutionary algorithm by combining the merits of dominance and decomposition. An elitism mechanism based on cascading sort is exploited to balance the convergence and diversity of the evolutionary process. At the same time, a reference point adaptation method is designed to adapt to different PFs. The performance of our proposed method is validated and compared with seven state-of-the-art algorithms on 200 instances of 27 widely employed benchmark problems. Experimental results fully demonstrate the superiority and versatility of our proposed method on MaOPs with regular and irregular PFs.

Published
2021

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