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2022 3rd International Conference on Mechanical engineering and Materials, ICMEM 2022

作者： Liu, Qiuyuan Qiu, Xiaopan Liu, Xin Zhao, Xingyuan Jiang, Sheming Zhang, Qifu Laboratory of Advanced Coating Technology for Metals China Iron and Steel Research Institute Group National Engineering Beijing100081 China State Key Laboratory of Multiphase Complex Systems Institute of Process Engineering Chinese Academy of Sciences Beijing100190 China

Zinc coatings have been served as a barrier and a galvanic protection for steel products for over a century. However, with the depletion of zinc resources, it becomes an urgent issue to obtain a new type of zinc coating that uses less zinc and has higher corrosion resistance. In order to develop Zn/ZnMg coatings with better corrosion resistance than traditional galvanized steel and suitable for advanced high strength steel, the vacuum thermal evaporation technique was used to simultaneously deposit Zn/ZnMg coating onto interstitial free steel plates and single-crystal silicon wafers in a high vacuum environment. The microstructure, morphology, adhesion and corrosion resistance behavior of the Zn/ZnMg coating were studied by scratch test, salt spray test and electrochemical method. The results shows that the grain size in the Zn/ZnMg coating tended to increase with the increase of the substrate temperature. After deposited the pure Zn transition layer, the adhesion of the coating has been obviously improved. When the substrate temperature was increased to 200°C, the obtained coating exhibited strong corrosion resistance. © Published under licence by IOP Publishing Ltd.

关键词： Corrosion resistance

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Synthetic Bacterial Consortium for Degradation of Plastic Pyrolysis Oil Waste

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SSRN 2024年

作者： Xing, Jianmin Jia, Yunpu Dou, Jingxi Ballersted, Hendrik Blank, Lars M. State Key laboratory of Petroleum Molecular & Process Engineering Institute of Process Engineering Chinese Academy of Sciences Beijing100190 China College of Chemical Engineering University of Chinese Academy of Sciences Beijing100049 China State Key Laboratory of Multiphase Complex Systems Institute of Process Engineering Chinese Academy of Sciences Beijing100190 China Institute of Applied Microbiology Aachen Biology and Biotechnology RWTH Aachen University Worringer Weg 1 Aachen52074 Germany

The plasic crisis is ominipresent, from littering macroplastic to reports that document plastic in every niche of this planet, including the human body. In order to achieve higher recycling quotas, especially of mixed plastic waste, pyrolysis seems to be a viable option. However, depending on the process parameters, plastic pyrolysis oil waste is encountered, which is difficult to valorize, due to the enormous spread of the molecules included. To reduce the molecular heterogeneity, we here artificially compounded, monitored, and optimized the performance of a bacterial consortium, which has the ability to tolerate organic pollutants and use them as energy and carbon sources for their own metabolic activity. The primary constituents of the here used plastic pyrolysis oil waste (PPOW) were alkanes and Ε-caprolactam. The bacterial community exhibited noteworthy efficacy in eliminating alkanes of diverse chain lengths ranging from 71% to 100%. Additionally, within 7-days, the microbial community demonstrated a removal efficiency surpassing 50% for various aromatic hydrocarbons, along with complete eradication of Ε-caprolactam and naphthalene. Besides, a back-propagation (BP) neural network method is applied to evaluate O2 consumption as a measure of microbial activity. The insights gained were used to build a model, which is able to predict O2 depletion in long-time experiments and other experimental conditions. The results are discussed in the context of a developing circular plastic economy. © 2024, The Authors. All rights reserved.

关键词： Neural network models

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A low-cost gold-coated optical fiber sensor for in-situ microplastic detection in water

A low-cost gold-coated optical fiber sensor for in-situ micr...

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BioSensors Conference (BioSensors), IEEE

作者： Noppasin Ajchareeyasoontorn Jade Udomkittivorakul Tatinee Changlor Chanyanut Rungchaiwattanakul Jenyuk Lohwacharin Charusluk Viphavakit International School of Engineering (ISE) Faculty of Engineering Chulalongkorn University Bangkok Thailand Department of Environmental Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Intelligent Control Automation of Process Systems Research Unit Faculty of Engineering Chulalongkorn University Bangkok Thailand

An optical fiber-based sensor in the configuration of single-multi-single (SMS) modes structure is proposed to detect polyethylene microplastic particles inside aquatic environments via the interaction of light at the interface of optical fiber and the microplastic solutions. Microplastics negatively affect biological systems since living creatures may consume the pollutant. The data on the relationship between the transmittance spectrum and its corresponding wavelength value can be used to correlate and identify the concentration of the microplastic solution. Deposition of gold on the sensing region through sputtering is investigated to improve the sensitivity and reliability of the SMS sensor. This suggests the potential for a gold-coated SMS sensor for in-situ, low-cost and real-time microplastic sensing applications.

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Ultrathin curved PdNiRu nanosheets as bifunctional catalysts for oxygen reduction and ethylene glycol oxidation

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Nano Research 2024年第5期17卷 3777-3784页

作者： Xianzeng Li Tingyu Lu Huan Pang Mingyi Zhang Dongdong Xu Lin Xu Min Han Jun Yang Jiangsu Key Laboratory of New Power Batteries Jiangsu Collaborative Innovation Center of Biomedical Functional MaterialsSchool of Chemistry and Materials ScienceNanjing Normal UniversityNanjing 210023China Fujian Cross Strait Institute of Flexible Electronics(Future Technology) Fujian Normal UniversityFuzhou 350117China State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China State Key Laboratory of Coordination Chemistry Nanjing UniversityNanjing 210023China School of Chemistry and Chemical Engineering Yangzhou UniversityYangzhou 225009China Key Laboratory for Photonic and Electronic Bandgap Materials Ministry of EducationSchool of Physics and Electronic EngineeringHarbin Normal UniversityHarbin 150025China

Pd-based metallic nanosheets with advanced physicochemical properties have been widely prepared and employed in various electrocatalytic ***,few concerns were focused on their multiple performances in different ***,highly curved and ultrathin PdNiRu nanosheets(NSs)are developed by facile wet-chemistry strategy and exhibit excellent electrocatalytic performance toward both oxygen reduction reaction(ORR)and ethylene glycol oxidation reaction(EGOR).Owing to the synergistically structural(e.g.,ultrathin,curved,defects/steps-rich)and compositional(ternary alloy)advantages,PdNiRu NSs exhibited enhanced ORR and EGOR specific/mass activities and better stability/durability than control *** specific activity(5.52 mA·cm^(−2))and mass activity(1.13 A·mg_(Pd)^(−1))of the PdNiRu NSs in ORR are 4.8 and 3.4 times as the ones of commercial Pt/C,*** mass activity of PdNiRu NSs(3.86 A·mg_(Pd)^(−1))in EGOR is 2.6 times as commercial Pd/C(1.51 A·mg_(Pd)^(−1)).This study is helpful for the development of desired electrocatalysts with multi-functional application in practical fuel cells.

关键词： ultrathin nanosheets noble metal electrocatalysts bifunctional

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Evaluation and Modification of Group Contribution Methods for Critical Properties of Organic Compounds

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SSRN 2023年

作者： Zhou, Chao Zhang, Xuxue Zhao, Wenying Xiang, Shuguang Qi, Meiling College of Chemistry and Chemical Engineering Qilu Normal University Jinan250200 China Institute of Process Systems Engineering Qingdao University of Science and Technology Qingdao266042 China

The group contribution method for the estimation of critical temperature, critical pressure and critical volume were evaluated with reference data. The average relative error and relative error distribution of different methods were compared. The results showed that the element and chemical bond 2 method was the most accurate for estimating the critical temperature, with an average relative error of 2.98%. The Joback method was more accurate than the other methods for the estimation the critical pressure and critical volume, with the average relative error of 4.31% and 4.83%, respectively. Moreover, silicon-containing groups were added in the Constantinou−Gani method, and the contribution values of groups were fitted. The accuracy of the group contribution value was verified with the experimental data that not involved in the regression. The average relative errors of normal boiling point, critical temperature, critical volume and critical pressure were 3.08%, 2.95%, 3.37% and 2.45%, respectively. The results indicated that the divided groups were reasonable and the regressed contribution values of groups were accurate. The modified Constantinou−Gani method is a good way for the estimation of the critical properties of silica-containing organic compounds. © 2023, The Authors. All rights reserved.

关键词： Organic compounds

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Preliminary Environmental and Economic Assessment of Mineral Carbonation of Steel Slags as a Carbon Capture, Utilization and Storage Technology

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Procedia CIRP 2024年 122卷 318-323页

作者： Ponnapat Watjanatepin Laura Steinwidder Anthony de Schutter Nina Miladinović Giuseppe Granata Sara Vicca Tom Van Gerven Karel Van Acker Sustainable Materials Processing and Recycling (SeMPeR) Department of Materials Engineering KU Leuven Kasteelpark Arenberg 44 3001 Leuven Belgium Plant and Ecosystems (PLECO) Department of Biology University of Antwerp Campus Drie Eiken Antwerp Belgium Department of Bioscience Engineering University of Antwerp Antwerp Belgium Process Engineering for Sustainable Systems (ProcESS) Department of Chemical Engineering KU Leuven Leuven Belgium Center for Economics and Corporate Sustainability (CEDON) KU Leuven Warmoesberg 26 BE-1000 Brussels Belgium

To shift towards a sustainable steel production practice, circular economy principles can be applied in the value chain by valorizing the 2 in flue gases and the generated steel slags to produce stable silicates and carbonates via mineral carbonation, leading to long-term stable carbon sequestration. Carbonated slags can then be considered as a carbon capture, utilization and storage technology. However, it is important to quantify the environmental benefits and economic viability to evaluate a system's sustainability. This study aims (1) to evaluate the environmental and economic impacts of steel slag mineral carbonation and (2) to identify hotspots and process parameters of the systems. In this study, lab-scale experimental mineral carbonation data is upscaled to a TRL 6 scenario via an upscaling simulation with a power law learning curve. Subsequently, life cycle assessment and life cycle costing are performed to quantify the environmental and economic performances in agriculture. Contribution analyses are performed to ascertain the hotspots and process parameters of the systems. The results obtained in this study can encourage industrial symbiosis among different stakeholders in and around the steel industry to promote a more sustainable steel manufacturing value chain, incorporating circular economy principles.

关键词： Carbon capture utilization and storage life cycle assessment mineral carbonation life cycle costing

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Design of Supervisory Model Predictive control for Building HVAC System Subject to Time-Varying Operating Points

Design of Supervisory Model Predictive Control for Building ...

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International Conference on control, Automation and systems ( ICCAS)

作者： Sitthiphat Promchaiwattana David Banjerdpongchai Department of Electrical Engineering Faculty of Engineering Intelligent Control Automation of Process Systems Research Unit Chulalongkorn University 254 Phayathai Road Pathumwan Bangkok Thailand

This paper presents the design of supervisory model predictive control for HVAC systems with consideration of peak demand shaving and thermal comfort. In this work, we analyze the operating points with the thermal comfort requirement. Afterwards, we linearize the nonlinear dynamic model to a linear time-varying model. In particular, we specify that the operating point of the open-loop HVAC system satisfies the thermal comfort condition. This makes the predicted mean vote (PMV) equal to zero or nearly to zero. Subsequently, we calculate the zone temperature, the zone humidity ratio, and the volumetric flow rate. When considering the time-varying disturbance profiles, it appears that the operating points are time-varying. We observe that the coefficient of performance (COP) and the operating points are time-varying which lead to time-varying model. Moreover, we design supervisory control (SC) and model predictive control (MPC) for linear time-varying model. In the SC design, we aim to find the optimal reference zone temperature which is used as the reference signal for MPC. In the MPC design, the objectives are twofold. First, the zone temperature tracks the reference signal. Second, both electrical energy cost and deviation of desired thermal comfort are minimized. The computer simulation shows that MPC of time-varying HVAC system yields the best reference tracking. In addition, it reduces total electrical energy cost the most. We conclude that the optimal temperature reference can be effectively applied to the building HVAC systems while the occupants feel comfortable and the total electrical energy cost is the lowest.

关键词： HVAC Costs Input variables Buildings Predictive models Supervisory control Thermal analysis

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Demand Response Optimization for the Enhancement of the Distribution System's Operation

Demand Response Optimization for the Enhancement of the Dist...

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International Conference on Smart Energy systems and Technologies (SEST)

作者： Maria Fotopoulou George Tsekouras Dimitrios Rakopoulos Vassiliki Kontargyri Department of Electrical and Electronics Engineering University of West Attica Athens Greece Chemical Process and Energy Resources Institute Centre for Research and Technology Hellas Athens Greece Control Systems and Industrial Automation Laboratory National and Kapodistrian University of Athens Athens Greece

ISBN: (数字)9798350386493

ISBN: (纸本)9798350386509

Following the latest energy market trends, active distribution systems incorporate an ascending mix of flexible loads, which can participate in Demand Response (DR) strategies. The purpose of this research paper is to present a DR strategy for the Distribution System Operator (DSO) in order to enhance the system's operation and mitigate power quality issues, such as voltage drops, and congestion. The proposed algorithm aims at smoothing the load curve, taking into consideration the available flexible load and the limitations of the system. The algorithm is demonstrated on a model of the distribution system of Skiathos island, Greece, in the context of ENFLATE, a Horizon Europe project, and future scenarios with photovoltaic (PV) penetration are studied as well. According to the results, the proposed DR algorithm manages to reduce the voltage drop, eliminate the number of events where the voltage drop exceeds the limits and reduce the losses of the distribution system up to 8%-9%, depending on the PV penetration.

关键词： Electric potential Smoothing methods Power quality Europe Voltage Artificial neural networks Transformers Demand response Load modeling Context modeling

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AMG: A Depression Detection Model with Autoencoder and Multi-Head Graph Convolutional Network

AMG: A Depression Detection Model with Autoencoder and Multi...

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Chinese control Conference (CCC)

作者： Han-Guang Wang Qing-Hao Meng Li-Cheng Jin Jian-Bang Wang Hui-Rang Hou Tianjin Key Laboratory of Process Measurement and Control Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University Tianjin China China Southern Power Grid Company Limited Guangzhou China

Depression is a common chronic mental disorder characterized by high prevalence, recurrence, suicide rate, disability rate and heavy disease burden. Depression assessment based on questionnaires is subjective, therefore, a novel framework to is hereby designed to detect depression automatically and obj ectively. The framework first utilizes a two-way autoencoder to extract the hidden features from the original differential entropy features. The new features are used to generate the channel connectivity graph, using the multi-head attention mechanism. Next, the new features and graphs are input into the graph convolutional network (GCN) to aggregate spatial information. Finally, the output from GCN is passed to a fully connected layer and a soft layer to obtain the predicted label. Experiments are performed on Multimodal Open Dataset for Mental-disorder Analysis dataset. A final accuracy of 88.68% and a cross entropy loss of 2.4532 are obtained, when using ten-fold cross validation, outperforming other traditional machine learning methods including SVM, KNN, decision tree.

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Thermal Behavior Decision Tree of Safe Operation for Single Diffusion-controlled Liquid-Liquid Heterogeneous Reactions in Semi-Batch Reactors

SSRN

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SSRN 2024年

作者： Wen, Xingyu Bai, Wenshuai Lv, Xinrui Wang, Jingxin Kummer, Alex Lv, Jianhua School of Chemical Engineering and Technology Hebei University of Technology Tianjin300130 China Tianjin Key Laboratory of Chemical Process Safety Tianjin300130 China ELKH-PE Complex Systems Monitoring Research Group Department of Process Engineering University of Pannonia Egyetem u. 10 Veszprem VeszpremH-8200 Hungary

The safe and efficient process conditions play an important role in reaction thermal safety. Many scholars have devoted to studying the thermal behaviors of diffusion-controlled liquid-liquid heterogeneous reactions in semi-batch reactors (SBRs), and put forward a large number of thermal runaway criteria, among which several recent methods based on machine learning (ML) show great advantages and potential. However, these ML models are difficult to understand and trust because of their black-box nature so far. Therefore, this paper leverages an interpretable ML model with a fully transparent decision-making process, namely thermal behavior decision tree (DT) model, to recognize straightforwardly reaction thermal behaviors. Firstly, using datasets generated from a formulated mathematical model, the thermal behavior DT model learns the mapping relationship between curve features during the addition process and the reaction’s thermal behavior. Then, based on the thermal behavior DT model, we proposed two lines of defense against thermal runaway: prior process optimization and online alarm algorithm. Through comparative analysis and the confusion matrixes, it is demonstrated that the thermal behavior DT model adeptly identifies the underlying patterns of diffusion-controlled heterogeneous reactions. Finally, the robustness and applicability of the thermal behavior DT model were further verified through 8 calorimetric experiments of toluene mono-nitration. © 2024, The Authors. All rights reserved.

关键词： Thermal diffusion in liquids

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