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Evaluating two stages of silicone-containing arylene resin oxidation via experiment and molecular simulation

Chinese Journal of Chemical Engineering 2024年第2期66卷 189-202页

作者： Jiangtao Cai Qingfu Huang Huan Chen Tao Zhang Bo Niu Yayun Zhang Donghui Long Key Laboratory of Chemical Engineering East China University of Science and TechnologyShanghai 200237China Key Laboratory of Special Functional Polymeric Materials and Related Technology(Ministry of Education) School of Chemical EngineeringEast China University of Science and TechnologyShanghai 200237China

Silicon-containing aryl acetylene resin(PSA)is a new type of high-temperature resistant resin with excellent oxidation resistance,whereas antioxidant reaction mechanism of PSA resin under ultra-high temperatures still remains ***,the oxidation behavior and mechanisms of PSA resin are systematically investigated combining kinetic analysis and Reax FF molecular dynamics(MD)*** analysis indicates that the oxidation process of PSA resin undergoes two main steps:oxidative mass gain and oxidative *** distributed activation energy model(DAEM)is employed for describing oxidation processes and the best-fit one is obtained using genetic algorithms and differential *** model demonstrates that the oxidative weight gain stage is dominated by two virtual reactants and the oxidative degradation stage consists of three virtual ***,the observation of MD reaction pathways indicates that oxygen oxidation of unsaturated structures occurs in the initial stage,which results in the formation of PSA resin ***,cracked pieces react with O_(2)to generate CO and other chemicals in the second *** resin matrix's great antioxidation resilience is illustrated by the formation of SiO_(2).The analysis based on MD simulations exhibits an efficient computational proof with the experiments and DAEM *** on the results,a two-stage reaction mechanism is proposed,which provides important theoretical support for the subsequent study of the oxidation behavior of silica-based resins.

关键词： PSA resin Oxidative degradation Thermogravimetric analysis DAEM reaction kinetics ReaxFF simulation

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Unsupervised Oral Endoscope Image Stitching Algorithm

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Journal of Shanghai Jiaotong university(Science) 2024年第1期29卷 81-90页

作者：黄荣常青张扬 School of Information Science and Engineering East China University of Science and TechnologyShanghai 200237China

Oral endoscope image stitching algorithm is studied to obtain wide-field oral images through regis-tration and stitching,which is of great significance for auxiliary *** with natural images,oral images have lower textures and fewer ***,traditional feature-based image stitching methods rely heavily on feature extraction quality,often showing an unsatisfactory performance when stitching images with few ***,due to the hand-held shooting,there are large depth and perspective disparities between the captured images,which also pose a challenge to image *** overcome the above problems,we propose an unsupervised oral endoscope image stitching algorithm based on the extraction of overlapping regions and the loss of deep *** the registration stage,we extract the overlapping region of the input images by sketching polygon intersection for feature points screening and estimate homography from coarse to fine on a three-layer feature pyramid ***,we calculate loss using deep features instead of pixel values to emphasize the importance of depth disparities in homography ***,we reconstruct the stitched images from feature to pixel,which can eliminate artifacts caused by large *** method is compared with both feature-based and previous deep-based methods on the UDIS-D dataset and our oral endoscopy image *** experimental results show that our algorithm can achieve higher homography estimation accuracy,and better visual quality,and can be effectively applied to oral endoscope image stitching.

关键词： oral endoscope image overlapping region homography estimation image stitching

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Preparation and performance evaluation of the slickwater using novel polymeric drag reducing agent with high temperature and shear resistance ability

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Petroleum Science 2024年第2期21卷 1113-1121页

作者： Ming-Wei Zhao Zhen-Feng Ma Cai-Li Dai WeiWu Yong-Quan Sun Xu-Guang Song Yun-Long Cheng Xiang-Yu Wang National Key Laboratory of Deep Oil and Gas China University of Petroleum(East China)Qingdao266580ShandongChina Shandong Key Laboratory of Oilfield Chemistry China University of Petroleum(East China)Qingdao266580ShandongChina Sinopec Shengli Oilfield Dongying257001ShandongChina Department of Chemical and Materials Engineering University of AlbertaEdmontonAB T6G 1H9Canada east China Petroleum Bureau of Sinopec Nanjing210011JiangsuChina

Slickwater fracturing fluids are widely used in the development of unconventional oil and gas resources due to the advantages of low cost,low formation damage and high drag reduction ***,their performance is severely affected at high *** reducing agent is the key to determine the drag reducing performance of *** this work,in order to further improve the temperature resistance of slickwater,a temperature-resistant polymeric drag reducing agent(PDRA)was synthesized and used as the basis for preparing the temperature-resistant *** slickwater system was prepared with the compositions of 0.2 wt%PDRA,0.05 wt%drainage aid nonylphenol polyoxyethylene ether phosphate(NPEP)and 0.5 wt%anti-expansion agent polyepichlorohydrindimethylamine(PDM).The drag reduction ability,rheology properties,temperature and shear resistance ability,and core damage property of slickwater were systematically studied and *** contrast to on-site drag reducing agent(DRA)and HPAM,the temperature-resistant slickwater demonstrates enhanced drag reduction efficacy at 90℃,exhibiting superior temperature and shear resistance ***,the drag reduction retention rate for the slickwater achieved an impressive 90.52%after a 30-min shearing ***,the core damage is only 5.53%.We expect that this study can broaden the application of slickwater in high-temperature reservoirs and provide a theoretical basis for field applications.

关键词： Unconventional resources Polymeric drag reducing agent Slickwater High drag reduction rate Temperature resistance

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Online Pareto optimal control of mean-field stochastic multi-player systems using policy iteration

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Science China(Information Sciences) 2024年第4期67卷 21-37页

作者： Xiushan JIANG Yanshuang WANG Dongya ZHAO Ling SHI College of New Energy China University of Petroleum(East China) Department of Electronic and Computer Engineering Hong Kong University of Science and Technology

In this study, the Pareto optimal strategy problem was investigated for multi-player mean-field stochastic systems governed by It? differential equations using the reinforcement learning(RL) method.A partially model-free solution for Pareto-optimal control was derived. First, by applying the convexity of cost functions, the Pareto optimal control problem was solved using a weighted-sum optimal control problem. Subsequently, using on-policy RL, we present a novel policy iteration(PI) algorithm based on the Hrepresentation technique. In particular, by alternating between the policy evaluation and policy update steps,the Pareto optimal control policy is obtained when no further improvement occurs in system performance,which eliminates directly solving complicated cross-coupled generalized algebraic Riccati equations(GAREs).Practical numerical examples are presented to demonstrate the effectiveness of the proposed algorithm.

关键词： mean-field stochastic systems Pareto optimal control policy iteration scheme $\mathcal{H}$-representation

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Hierarchical multihead self-attention for time-series-based fault diagnosis

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Chinese Journal of Chemical Engineering 2024年第6期70卷 104-117页

作者： Chengtian Wang Hongbo Shi Bing Song Yang Tao Key Laboratory of Smart Manufacturing in Energy Chemical Process of the Ministry of Education East China University of Science and TechnologyShanghai 200237China

Fault diagnosis is important for maintaining the safety and effectiveness of chemical *** the multivariate,nonlinear,and dynamic characteristic of chemical process,many time-series-based data-driven fault diagnosis methods have been developed in recent ***,the existing methods have the problem of long-term dependency and are difficult to train due to the sequential way of *** overcome these problems,a novel fault diagnosis method based on time-series and the hierarchical multihead self-attention(HMSAN)is proposed for chemical ***,a sliding window strategy is adopted to construct the normalized time-series ***,the HMSAN is developed to extract the time-relevant features from the time-series process *** improves the basic self-attention model in both width and *** the multihead structure,the HMSAN can pay attention to different aspects of the complicated chemical process and obtain the global dynamic ***,the multiple heads in parallel lead to redundant information,which cannot improve the diagnosis *** the hierarchical structure,the redundant information is reduced and the deep local time-related features are further ***,a novel many-to-one training strategy is introduced for HMSAN to simplify the training procedure and capture the long-term ***,the effectiveness of the proposed method is demonstrated by two chemical *** experimental results show that the proposed method achieves a great performance on time-series industrial data and outperforms the state-of-the-art approaches.

关键词： Self-attention mechanism Deep learning Chemical process Time-series Fault diagnosis

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A deep reinforcement learning approach to gasoline blending real-time optimization under uncertainty

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Chinese Journal of Chemical Engineering 2024年第7期71卷 183-192页

作者： Zhiwei Zhu Minglei Yang Wangli He Renchu He Yunmeng Zhao Feng Qian Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of EducationEast China University of Science and TechnologyShanghai 200237China

The gasoline inline blending process has widely used real-time optimization techniques to achieve optimization objectives,such as minimizing the cost of ***,the effectiveness of real-time optimization in gasoline blending relies on accurate blending models and is challenged by stochastic ***,we propose a real-time optimization algorithm based on the soft actor-critic(SAC)deep reinforcement learning strategy to optimize gasoline blending without relying on a single blending model and to be robust against *** approach constructs the environment using nonlinear blending models and feedstocks with *** algorithm incorporates the Lagrange multiplier and path constraints in reward design to manage sparse product *** abstracted states facilitate algorithm convergence,and the normalized action vector in each optimization period allows the agent to generalize to some extent across different target production *** these well-designed components,the algorithm based on the SAC outperforms real-time optimization methods based on either nonlinear or linear *** even demonstrates comparable performance with the time-horizon based real-time optimization method,which requires knowledge of uncertainty models,confirming its capability to handle uncertainty without accurate *** simulation illustrates a promising approach to free real-time optimization of the gasoline blending process from uncertainty models that are difficult to acquire in practice.

关键词： Deep reinforcement learning Gasoline blending Real-time optimization Petroleum Computer simulation Neural networks

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Model-free adaptive robust control method for high-speed trains

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Transportation Safety and Environment 2024年第1期6卷 93-102页

作者： Zhongqi Li Liang Zhou Hui Yang Yue Yan School of Electrical and Automation Engineering East China Jiaotong UniversityNanchang 330013JiangxiChina State Key Laboratory of Performance Monitoring and Protecting of Rail Transit Infrastructure East China Jiaotong UniversityNanchang 330013JiangxiChina

Aiming at the robustness issue in high-speed trains(HSTs)operation control,this article proposes a model-free adaptive control(MFAC)scheme to suppress ***,the dynamic linearization data model of train system under the action of measurement disturbance is given,and the Kalman filter(KF)based on this model is derived under the minimum variance estimation ***,according to the KF,an anti-interference MFAC scheme is *** scheme only needs the input and output data of the controlled system to realize the MFAC of the train under strong ***,the simulation experiment of CRH380A HSTs is carried out and compared with the traditional MFAC and the MFAC with attenuation *** proposed control algorithm can effectively suppress the measurement disturbance,and obtain smaller tracking error and larger signal to noise ratio with better applicability.

关键词： automatic train operation(ATO) model-free adaptive control(MFAC) disturbance suppression minimum variance estimation Kalman filtering(KF) partial format data model

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Synthesis of granulated Li_(1.33)Mn_(1.67)O_(4) via two antisolvent methods for lithium adsorption from gas-produced water

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Chinese Journal of Chemical Engineering 2024年第5期69卷 34-46页

作者： Jun Qiu Lu-Ri Bao Wei Guo Ying Yang Shu-Ying Sun National Engineering Research Center for Integrated Utilization of Salt Lake Resource East China University of Science and TechnologyShanghai 200237China

Gas-produced water is an accompanying wastewater in the natural gas extraction process,and it is a potential liquid lithium resource that contains a considerable amount of *** study investigated the feasibility of using manganese-based ion sieves to adsorb and extract lithium from gas-produced *** we focused on the applicability of two different granulation methods,extrusion and droplet,in gas-produced water *** types of H_(1.33)Mn_(1.67)O_(4) particles were prepared by the extrusion method(EHMO)and the droplet method(DHMO).The porosity of DHMO was much higher than that of EHMO,and the adsorption performance of DHMO increased with the decrease of binder *** prepared with a binder concentration of 0.14 g·ml^(-1)exhibited the best adsorption performance in gas-produced water,and the Li^(+)adsorption capacity could reach 25.14 mg·g^(-1).In gas-produced water,the adsorption equilibrium of DHMO only took 9 h,and the adsorption process conformed to the Langmuir model and pseudo-second-order kinetic *** pore diffusion model(PDM)could well describe its adsorption ***,DHMO showed a great selectivity to Li^(+),and the selectivity order of DHMO in gas-produced water was Li^(+)>Ba^(2+)>>Mg^(2+),Ca^(2+),Sr^(2+)>>Na^(+)>>K^(+).After 20 cycles,the Li^(+)adsorption capacity was still higher than 17.30 mg·g^(-1),and the rate of manganese dissolution was less than 1%.

关键词： Gas-produced water Granulation Li_(1.33)Mn_(1.67)O_(4)

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Process analytical technologies and self-optimization algorithms in automated pharmaceutical continuous manufacturing

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Chinese Chemical Letters 2024年第3期35卷 87-95页

作者： Peiwen Liu Hui Jin Yan Chen Derong Wang Haohui Yan Mingzhao Wu Fang Zhao Weiping Zhu State Key Laboratory of Bioreactor Engineering Shanghai Key Laboratory of Chemical BiologySchool of PharmacyEast China University of Science and TechnologyShanghai 200237China State Key Laboratory of Chemical Engineering School of Chemical EngineeringEast China University of Science and TechnologyShanghai 200237China Engineering Research Center of Pharmaceutical Process Chemistry Ministry of EducationSchool of PharmacyEast China University of Science and TechnologyShanghai 200237China

The pharmaceutical industry is now paying increased attention to continuous *** the revolution to continuous and automated manufacturing is deepening in most of the top pharma companies in the world,the advancement of automated pharmaceutical continuous manufacturing in China is relatively slow due to some key challenges including the lack of knowledge on the related technologies and shortage of qualified *** this review,emphasis is given to two of the crucial technologies in automated pharmaceutical continuous manufacturing,i.e.,process analytical technology(PAT)and self-optimizing *** work published in recent 5 years employing advanced PAT tools and self-optimization algorithms is introduced,which represents the great progress that has been made in automated pharmaceutical continuous manufacturing.

关键词： Pharmaceutical continuous manufacturing Automation Process analytical technology Self-optimization algorithm

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New insights into the deposition of natural gas hydrate on pipeline surfaces:A molecular dynamics simulation study

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Petroleum Science 2024年第1期21卷 694-704页

作者： Jun Zhang Hai-Qiang Fu Mu-Zhi Guo Zhao Wang Li-Wen Li Qi Yin You-Guo Yan Wei Wei Wei-Feng Han Jie Zhong School of Materials Science and Engineering China University of Petroleum(East China)Qingdao 266580ShandongChina School of Petroleum Engineering China University of Petroleum(East China)Qingdao 266580ShandongChina Department of Alternative Energy PetroChina Research Institute of Petroleum Exploration&DevelopmentLangfang 065007HebeiChina

Natural gas hydrate(NGH)can cause pipeline blockages during the transportation of oil and gas under high pressures and low *** hydrate adhesion on pipelines is viewed as an efficient way to prevent NGH *** studies suggested the water film can greatly increase hydrate adhesion in gas-dominant ***,by performing the molecular dynamics simulations,we find in water-dominant system,the water film plays different roles in hydrate deposition on Fe and its corrosion ***,due to the strong affinity of water on Fe surface,the deposited hydrate cannot convert the adsorbed water into hydrate,thus,a water film *** water affinities decrease(Fe>Fe_(2)O_(3)>FeO>Fe_(3)O_(4)),adsorbed water would convert to amorphous hydrate on Fe_(2)O_(3)and form the ordered hydrate on FeO and Fe_(3)O_(4)after hydrate *** absorbed water film converts to amorphous or to hydrate,the adhesion strength of hydrate continuously increases(Fe

关键词： Deposition Natural gas hydrate Pipelines Water affinity Adhesion strength

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