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Influence of syngas components and ash particles on the radiative heat transfer in a radiant syngas cooler

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Chinese Journal of Chemical Engineering 2024年第4期68卷 203-215页

作者： chen Han Youmin Situ Huaxing Zhu Jianliang Xu zhenghua Dai Guangsuo Yu Haifeng Liu National Energy Coal Gasification Technology Research and Development Center East China University of Science and TechnologyShanghai 200237China Shanghai Engineering Research Center of Coal Gasification East China University of Science and TechnologyShanghai 200237China

Radiant syngas cooler(RSC)is widely used as a waste heat recovery equipment in industrial gasification.In this work,an RSC with radiation screens is established and the impact of gaseous radiative property models,gas components,and ash particles on heat transfer is investigated by the numerical simulation method.Considering the syngas components and the pressure environment of the RSC,a modified weighted-sum-of-gray-gases model was developed.The modified model shows high accuracy in validation.In computational fluid dynamics simulation,the calculated steam production is only 0.63%in error with the industrial data.Compared with Smith's model,the temperature decay along the axial direction calculated by the modified model is faster.Syngas components are of great significance to heat recovery capacity,especially when the absorbing gas fraction is less than 10%.After considering the influence of particles,the outlet temperature and the proportion of radiative heat transfer are less affected,but the difference in steam output reaches 2.7 t·h^(-1).The particle deposition on the wall greatly reduces the heat recovery performance of an RSC.

关键词： Radiant syngas cooler Weighted-sum-of-gray-gases model Numerical simulation Particle radiation

维普期刊数据库博看期刊

Interface optimization and defects suppression via Na F introduction enable efficient flexible Sb_(2)Se_(3) thin-film solar cells

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Journal of Energy Chemistry 2024年第3期90卷 165-175,I0006页

作者： Mingdong chen Muhammad Ishaq Donglou Ren Hongli Ma zhenghua Su Ping Fan David Le Coq Xianghua Zhang Guangxing Liang Shuo chen Shenzhen Key Laboratory of Advanced Thin Films and Applications Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong ProvinceCollege of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhen 518060GuangdongChina State Key Laboratory of Featured Metal Materials and Life-cycle Safety for Composite Structures MOE Key Laboratory of New Processing Technology for Nonferrous Metals and MaterialsSchool of ResourcesEnvironment and MaterialsGuangxi UniversityNanning 530004GuangxiChina CNRS ISCR(Institut des Sciences Chimiques de Rennes)UMR 6226Universitéde RennesRennes F-35000France

Sb_(2)Se_(3) with unique one-dimensional(1D) crystal structure exhibits exceptional deformation tolerance,demonstrating great application potential in flexible devices.However,the power conversion efficiency(PCE) of flexible Sb_(2)Se_(3) photovoltaic devices is temporarily limited by the complicated intrinsic defects and the undesirable contact interfaces.Herein,a high-quality Sb_(2)Se_(3) absorber layer with large crystal grains and benign [hkl] growth orientation can be first prepared on a Mo foil substrate.Then NaF intermediate layer is introduced between Mo and Sb_(2)Se_(3),which can further optimize the growth of Sb_(2)Se_(3)thin film.Moreover,positive Na ion diffusion enables it to dramatically lower barrier height at the back contact interface and passivate harmful defects at both bulk and heterojunction.As a result,the champion substrate structured Mo-foil/Mo/NaF/Sb_(2)Se_(3)/CdS/ITO/Ag flexible thin-film solar cell delivers an obviously higher efficiency of 8.03% and a record open-circuit voltage(V_(OC)) of 0.492 V.This flexible Sb_(2)Se_(3) device also exhibits excellent stability and flexibility to stand large bending radius and multiple bending times,as well as superior weak light photo-response with derived efficiency of 12.60%.This work presents an effective strategy to enhance the flexible Sb_(2)Se_(3) device performance and expand its potential photovoltaic applications.

关键词： Sb_(2)Se_(3) Flexible solar cells NaF intermediate layer Interface optimization Defects suppression

Deactivation induced by metal sulfate over MnCeOx catalyst in NH_(3)-SCR reaction at low temperature

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Journal of Rare Earths 2024年第6期42卷 1056-1065,I0002页

作者： Qiao Xie Dongqi An Linsen Zhou Tingzhen Li zhenghua Hu Menghan chen Menglan Ma Lei Zhang Jingfang Sun Lin Dong School of Environmental and Chemical Engineering Chongqing Three Gorges UniversityChongqing404000China Key Laboratory of Water Environment Evolution and Pollution Control in the Three Gorges Reservoir Chongqing Three Gorges UniversityChongqing.404000China Jiangsu Key Laboratory of Vehicle Emissions Control Center of Modern AnalysisSchool of EnvironmentNanjing UniversityNanjing210093China Institute of Materials China Academy of Engineering PhysicsMianyang621908China

Sulfate adsorption is one of the factors that cause the poisoning of catalyst in the low-temperature NH_(3) selective catalytic reduction reaction(NH_(3)-SCR).In this paper,by controlling the co-adsorption time of SO_(2) and O_(2) at 150℃,a range of sulfated MnCeOx catalysts with different contents of metal sulfate species were prepared to reveal the influence of metal sulfate species content on the catalytic performances and reaction mechanisms at low temperature.The catalytic activity below 250℃rapidly decreases with increasing metal sulfate species content.The results of characterizations shed light on the reduction of specific surface area,Mn^(4+)and Ce^(3+)content,and redox ability of MnCeOx owing to the formation of metal sulfate species.Further experiments reveal that metal sulfate species preferentially absorb on MnOx domains rather than on CeO_(2) domains,and the adsorbed metal sulfate species can suppress the Eley-Rideal and the Langmuir-Hinshelwood reaction mechanisms over the sulfated MnCeOx.All the above results are detrimental to the activity of sulfated MnCeOx in the low-temperature NH3-SCR reaction.

关键词： NH_(3)selective catalytic reduction MnCeOx catalyst Sulfation Low-temperature activity SO_(2)poisoning Rare earths

A Hybrid Ensemble Deep Learning Approach for Early Prediction of Battery Remaining Useful Life

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 177-187页

作者： Qing Xu Min Wu Edwin Khoo zhenghua chen Xiaoli Li the Institute for Infocomm Research A*STARSingapore 138632Singapore IEEE

Accurate estimation of the remaining useful life(RUL)of lithium-ion batteries is critical for their large-scale deployment as energy storage devices in electric vehicles and stationary storage.A fundamental understanding of the factors affecting RUL is crucial for accelerating battery technology development.However,it is very challenging to predict RUL accurately because of complex degradation mechanisms occurring within the batteries,as well as dynamic operating conditions in practical applications.Moreover,due to insignificant capacity degradation in early stages,early prediction of battery life with early cycle data can be more difficult.In this paper,we propose a hybrid deep learning model for early prediction of battery RUL.The proposed method can effectively combine handcrafted features with domain knowledge and latent features learned by deep networks to boost the performance of RUL early prediction.We also design a non-linear correlation-based method to select effective domain knowledge-based features.Moreover,a novel snapshot ensemble learning strategy is proposed to further enhance model generalization ability without increasing any additional training cost.Our experimental results show that the proposed method not only outperforms other approaches in the primary test set having a similar distribution as the training set,but also generalizes well to the secondary test set having a clearly different distribution with the training set.The PyTorch implementation of our proposed approach is available at https://***/batteryrul/battery_rul_early_prediction.

关键词： Deep learning early prediction lithium-ion battery remaining useful life(RUL)

Position Encoding Based Convolutional Neural Networks for Machine Remaining Useful Life Prediction

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IEEE/CAA Journal of Automatica Sinica 2022年第8期9卷 1427-1439页

作者： Ruibing Jin Min Wu Keyu Wu Kaizhou Gao zhenghua chen Xiaoli Li Institute for Infocomm Research Agency for ScienceTechnology and Research(A*STAR)Singapore 138632Singapore School of Computer Science Liaocheng UniversityLiaocheng 252000 Macao Institute of System Engineering Macao University of Science and TechnologyTaipaMacao 999078China

Accurate remaining useful life(RUL)prediction is important in industrial systems.It prevents machines from working under failure conditions,and ensures that the industrial system works reliably and efficiently.Recently,many deep learning based methods have been proposed to predict RUL.Among these methods,recurrent neural network(RNN)based approaches show a strong capability of capturing sequential information.This allows RNN based methods to perform better than convolutional neural network(CNN)based approaches on the RUL prediction task.In this paper,we question this common paradigm and argue that existing CNN based approaches are not designed according to the classic principles of CNN,which reduces their performances.Additionally,the capacity of capturing sequential information is highly affected by the receptive field of CNN,which is neglected by existing CNN based methods.To solve these problems,we propose a series of new CNNs,which show competitive results to RNN based methods.Compared with RNN,CNN processes the input signals in parallel so that the temporal sequence is not easily determined.To alleviate this issue,a position encoding scheme is developed to enhance the sequential information encoded by a CNN.Hence,our proposed position encoding based CNN called PE-Net is further improved and even performs better than RNN based methods.Extensive experiments are conducted on the C-MAPSS dataset,where our PE-Net shows state-of-the-art performance.

关键词： Convolutional neural network(CNN) deep learning position encoding remaining useful life prediction

DDUC:an erasure-coded system with decoupled data updating and coding

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Frontiers of Information Technology & Electronic Engineering 2023年第5期24卷 716-730页

作者： Yaofeng TU Rong XIAO Yinjun HAN zhenghua chen Hao JIN Xuecheng QI Xinyuan SUN State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen 518000China ZTE Corporation Nanjing 210000China

In distributed storage systems,replication and erasure code(EC)are common methods for data redundancy.Compared with replication,EC has better storage efficiency,but suffers higher overhead in update.Moreover,consistency and reliability problems caused by concurrent updates bring new challenges to applications of EC.Many works focus on optimizing the EC solution,including algorithm optimization,novel data update method,and so on,but lack the solutions for consistency and reliability problems.In this paper,we introduce a storage system that decouples data updating and EC encoding,namely,decoupled data updating and coding(DDUC),and propose a data placement policy that combines replication and parity blocks.For the(N,M)EC system,the data are placed as N groups of M+1 replicas,and redundant data blocks of the same stripe are placed in the parity nodes,so that the parity nodes can autonomously perform local EC encoding.Based on the above policy,a two-phase data update method is implemented in which data are updated in replica mode in phase 1,and the EC encoding is done independently by parity nodes in phase 2.This solves the problem of data reliability degradation caused by concurrent updates while ensuring high concurrency performance.It also uses persistent memory(PMem)hardware features of the byte addressing and eight-byte atomic write to implement a lightweight logging mechanism that improves performance while ensuring data consistency.Experimental results show that the concurrent access performance of the proposed storage system is 1.70–3.73 times that of the state-of-the-art storage system Ceph,and the latency is only 3.4%–5.9%that of Ceph.

关键词： Concurrent update High reliability Erasure code Consistency Distributed storage system

BOND PARAMETER AND ELECTRONIC STRUCTURE OF Sc,Y,Ti,Zr AND Hf METALS

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中国有色金属学会会刊：英文版 1998年第3期8卷 18-22页

作者： Yingjun, Gao zhenghua, chen Peiyun, Huang Xiaping, Zhong Central South Univ of Technology Changsha China

１ＩＮＴＲＯＤＵＣＴＩＯＮＩｎｒｅｃｅｎｔｙｅａｒｓ，ｔｈｅＰａｕｌｉｎｇ’ｓｖａｌｅｎｃｅｂｏｎｄ（ＶＢ）ｔｈｅｏｒｙｈａｓｂｅｅｎｍａｄｅａｇｒｅａｔｐｒｏｇｒｅｓｉｎｄｅｓｉｇｎｉｎｇａｎｄｄｅｔｅｒｍｉｎｉｎ... 详细信息

１ＩＮＴＲＯＤＵＣＴＩＯＮＩｎｒｅｃｅｎｔｙｅａｒｓ，ｔｈｅＰａｕｌｉｎｇ’ｓｖａｌｅｎｃｅｂｏｎｄ（ＶＢ）ｔｈｅｏｒｙｈａｓｂｅｅｎｍａｄｅａｇｒｅａｔｐｒｏｇｒｅｓｉｎｄｅｓｉｇｎｉｎｇａｎｄｄｅｔｅｒｍｉｎｉｎｇｔｈｅａｔｏｍｉｃｓｔａｔｅ，ａ...

关键词： Sc Y Ti Zr Hf metals one atom state method electronic structure bond parameter

基于Attention-BP神经网络模型的邮轮客舱火灾危险等级分类研究

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中国航海 2024年第1期47卷 9-17页

作者：熊正华向波陈斌四川交通职业技术学院航运工程系四川成都611130 武汉理工大学船海与能源动力工程学院湖北武汉430063

为能够对邮轮客舱不同火灾危险源进行风险评估,提出一种可对舱室火灾危险等级实时分类的新型神经网络模型。通过火灾动态模拟器(FDS)建立邮轮客舱火灾物理模型,对发生火灾时的烟气温度、CO体积分数和能见度等安全指标进行数值模拟,并基... 详细信息

为能够对邮轮客舱不同火灾危险源进行风险评估,提出一种可对舱室火灾危险等级实时分类的新型神经网络模型。通过火灾动态模拟器(FDS)建立邮轮客舱火灾物理模型,对发生火灾时的烟气温度、CO体积分数和能见度等安全指标进行数值模拟,并基于其对人体的影响程度将火灾危险等级划分为4个等级。通过设计一种新型的Attention-BP神经网络(BPNN)模型,结合self-Attention机制融合多个BPNN诊断结果,自适应地分配各个BPNN的权重,对采集的多源火灾信息进行分析和处理,实现对客舱火灾的风险评估并划分危险等级。试验证明:Attention-BPNN模型可有效地实现对火灾危险等级的预警,准确率可达97.32%。相对于其他机器学习算法,具有最高的稳定性和准确率,减少了对客舱火灾预警的不确定性。

关键词：邮轮火灾数值模拟 self-Attention机制 BP神经网络

A Review on Swarm Intelligence and Evolutionary Algorithms for Solving Flexible Job Shop Scheduling Problems

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IEEE/CAA Journal of Automatica Sinica 2019年第4期6卷 904-916页

作者： Kaizhou Gao Zhiguang Cao Le Zhang zhenghua chen Yuyan Han Quanke Pan IEEE the Macao Institute of Systems Engineering at Macao University of Science and Technology 999078 China School of Computer at Liaocheng Univeristy Liaocheng252059China the Department of Industrial Systems Engineering and Management National University of SingaporeSingapore Centre for Maritime Studies National University of SingaporeSingapore the Institute for Infocomm Research(I2R) the Agency for ScienceTechnology and Research(A*STAR)Singapore the School of Computer at Liaocheng Univeristy Liaocheng 252059China School of Mechatronic Engineering and Automation Shanghai UniversityShanghai 200072China

Flexible job shop scheduling problems(FJSP)have received much attention from academia and industry for many years.Due to their exponential complexity,swarm intelligence(SI)and evolutionary algorithms(EA)are developed,employed and improved for solving them.More than 60%of the publications are related to SI and EA.This paper intents to give a comprehensive literature review of SI and EA for solving FJSP.First,the mathematical model of FJSP is presented and the constraints in applications are summarized.Then,the encoding and decoding strategies for connecting the problem and algorithms are reviewed.The strategies for initializing algorithms?population and local search operators for improving convergence performance are summarized.Next,one classical hybrid genetic algorithm(GA)and one newest imperialist competitive algorithm(ICA)with variables neighborhood search(VNS)for solving FJSP are presented.Finally,we summarize,discus and analyze the status of SI and EA for solving FJSP and give insight into future research directions.

关键词： Evolutionary algorithm flexible job shop scheduling review swarm intelligence