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Machine learning for membrane bioreactor research:principles,methods,applications,and a tutorial

Frontiers of Environmental science & Engineering 2025年第3期19卷 119-144页

作者： Yizhe Lai Kang Xiao Yifan He Xian Liu Jihua Tan Wenchao Xue Aiqian Zhang Xia Huang Beijing Yanshan Earth Critical Zone National Research Station College of Resources and EnvironmentUniversity of Chinese Academy of SciencesBeijing 101408China Key Laboratory of Earth System Numerical Modeling and Application University of Chinese Academy of SciencesBeijing 101408China Environmental Chemistry Faculty College of Resources and EnvironmentUniversity of Chinese Academy of SciencesBeijing 101408China State Key Laboratory of Environmental Chemistry and Ecotoxicology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China Department of Energy Environmentand Climate ChangeSchool of EnvironmentResourcesand DevelopmentAsian Institute of TechnologyP.O.Box 4Klong LuangPathumthani 12120Thailand State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China

Membrane fouling poses a significant challenge to the sustainable development of membrane bioreactor(MBR)technologies for wastewater *** accurate prediction of the membrane filtration process is of great importance for identifying and controlling *** learning methods address the limitations of traditional statistical approaches,such as low accuracy,poor generalization ability,and slow convergence,particularly in predicting complex filtration and fouling processes within the realm of big *** article provides an in-depth exposition of machine learning *** study then reviews advances in MBRs that utilize machine learning methods,including artificial neural networks(ANN),support vector machines(SVM),decision trees,and ensemble *** on current literature,this study summarizes and compares the model input and output characteristics(including foulant characteristics,solution environments,filtration conditions,operating conditions,and time factors),as well as the selection of models and optimization *** modeling procedures of SVM,random forest(RF),back propagation neural network(BPNN),long short-term memory(LSTM),and genetic algorithm-back propagation(GA-BP)methods are elucidated through a tutorial *** simulation results demonstrated that all five methods yielded accurate predictions with R2>***,the existing challenges in the implementation of machine learning models in MBRs were *** is notable that integration of deep learning,automated machine learning(AutoML)and explainable artificial intelligence(XAI)may facilitate the deployment of models in practical engineering *** insights presented here are expected to facilitate the establishment of an intelligent control framework for MBR processes in future endeavors.

关键词： Membrane bioreactor Machine learning Pollutant removal Membrane fouling Model prediction

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Enhancing Autonomy Capability in Regional Power Grids:A Strategic Planning Approach with Multiple Autonomous Evaluation Indexes

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Energy Engineering 2024年第9期121卷 2449-2477页

作者： Jie Ma Tong Zhao Yuanzhao Hao Wenwen Qin Haozheng Yu Mingxuan Du Yuanhong Liu Liang Zhang Shixia Mu Cuiping Li Junhui Li Planning and Assessment Center Department State Grid Henan Economic Research InstituteZhengzhou450000China Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin132012China Development Planning Department State Grid Henan Electric Power CompanyZhengzhou450000China Innovation Development Research Center State Grid Shanghai Energy Internet Research Institute Co.Ltd.Shanghai201210China State Grid Simulation Center China Electric Power Research Institute Co.Ltd.Beijing100192China

After the integration of large-scale DistributedGeneration(DG)into the distribution network,the randomness and volatility of its output result in a reduction of spatiotemporal alignment between power generation and demand in the distribution network,exacerbating the phenomenon of wind and solar power *** a novel power system model,the fundamental concept of Regional Autonomous Power Grids(RAPGs)is to achieve localized management and energy autonomy,thereby facilitating the effective consumption of ***,this paper proposes a distributed resource planning strategy that enhances the autonomy capabilities of regional power grids by considering multiple evaluation indexes for ***,a regional Energy Storage(ES)configuration strategy is *** strategy can select a suitable reference value for the upper limit of ES configuration based on the regional load andDGoutput to maximize the elimination of source load deviations in the region as the upper limit constraint of ES ***,a control strategy for regional ES is proposed,the charging and discharging reference line of ES is set,and multiple autonomy and economic indexes are used as objective functions to select different proportions of ES to control the distributed resources of the regional power grid and establish evaluation indexes of the internal regional generation and load power ratio,the proportion of power supply matching hours,new energy consumption rate and tie line power imbalance outside the region to evaluate changes in the regional autonomy *** final simulation results showthat in the real regional grid example,the planning method in the planning year in the region of the overall power supply matching hour ratio and new energy consumption rate increased by 3.9%and 4.8%on average,and the power imbalance of the tie line decreased by 7.8%on *** proposed planning approach enables the maximization of regional autonomy while effectively smoothing the fluct

关键词： Regional autonomous power grid distributed generation distributed energy storage regional planning strategy evaluation index

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An Interval Fractional Electric Power system Planning Model for CO2 Emission Intensity Reduction: A Case Study of Fujian, China 14th

An Interval Fractional Electric Power System Planning Model ...

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14th International Conference on Environmental science and technology, ICEST 2023

作者： Zhao, S.H. Li, J.W. Liu, J. Li, Y.P. Fujian Engineering and Research Center of Rural Sewage Treatment and Water Safety School of Environmental Science and Engineering Xiamen University of Technology Xiamen361024 China State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Beijing Normal University Beijing100875 China

ISBN: (纸本)9783031546839

Using low-carbon/zero-carbon energy sources and negative emission technologies, and economic policies have proven to be effective measures for electric power plants’ CO2 emission mitigation. This study constructs an interval fractional electric power system planning (IFES) model for minimizing CO2 emission intensity considering the interactions between the measures and other constraints under uncertainty. The model is applied to Fujian Province as a real-case study, which contains electricity mix improvement, three types of CO2 emission reduction technologies, one policy. It was found that: (i) system carbon emission intensity is [170, 213] g/RMB;(ii) The proportion of clean energy power generation in Fujian Province will reach [92.32, 93.13]% in the 2055–2060, with nuclear energy, wind power and photovoltaic power generation ranking the top three;(iii) The electricity mix improvement has made the greatest contribution to the carbon neutrality of the power system (74.62%), and the contributions of CCS, DAC, and ESC are (9.11, 5.25, 11.02%) respectively. The research results provide scientific planning solutions for carbon reduction in the power industry in Fujian Province. The developed IF-ESP model can also be used in other regions around the world. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Electric power system planning

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A Position Probability Prediction Method of Marine Moving Targets for Optimization Search by Satellite

A Position Probability Prediction Method of Marine Moving Ta...

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IEEE International Conference on Control science and systems Engineering (CCSSE)

作者： Xiao Zheng Xiaodong Peng Zhiyuan Guo Huimin Qiang Junbao Zhao Laboratory of System Simulation and Concurrent Design Technology (National Space Science Center Chinese Academy of Sciences) University of Chinese Academy of Science Beijing China Beijing Remote Sensing Information Institute Beijing China

ISBN: (数字)9798331517199

ISBN: (纸本)9798331517205

Marine moving ship target search has great application demand and development prospects in marine surveillance, marine search and rescue, customs anti-smuggling, and other aspects. Satellites are a vital means of searching for marine moving targets. Ground coverage for imaging satellites is relatively limited; the vast marine area makes searching for marine moving ships challenging. Target position prediction, used as the guidance information for satellite detection to reduce the uncertainty of the target position and improve search efficiency, is an essential approach to achieving target optimization search. This paper proposes a target position prediction method based on joint learning of multi-source factors for optimal satellite search of marine moving targets. Firstly, it analyzes the characteristics of marine moving targets and the factors affecting motion. Then, it puts forward the motion prediction model based on a deep neural network, integrating multifactor, like the state of the moving target, environmental attributes such as nautical charts, meteorology and hydrology, and kinematic constraints, to predict the target positional distribution probability. Finally, the target search strategy based on the maximum sum of the distribution probabilities of the satellite coverage area is adopted to improve target detection probability. The experiment results show that the prediction method can realize the target positional distribution probability prediction, reduce the uncertainty search when making the satellite search plan, and improve efficiency.

关键词： Satellites Uncertainty Object detection Kinematics Predictive models Search problems Satellite navigation systems Marine vehicles Modeling Optimization

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Constructing a Raman and surface-enhanced Raman scattering spectral reference library for fine-particle analysis

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Journal of Environmental sciences 2022年第8期34卷 1-13页

作者： Hui Chen Fengkui Duan Kebin He Jingjing Du Zhenli Sun Suhua Wang Key Laboratory of Resources and Environmental System Optimization of Ministry of Education College of Environmental Science and EngineeringNorth China Electric Power UniversityBeijing 102206China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China State Key Laboratory of Environmental Chemistry and Ecotoxicology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China Guangdong Provincial Key Laboratory of Petrochemcial Pollution Processes and Control School of Environmental Science and EngineeringGuangdong University of Petrochemical TechnologyMaoming 525000 China

Fine particles associated with haze pollution threaten the health of over 400 million people in China. Owing to excellent non-destructive fingerprint recognition characteristics, Raman and surface-enhanced Raman scattering(SERS) are often used to analyze the composition of fine particles to determine their physical and chemical properties as well as reaction mechanisms. However, there is no comprehensive Raman spectral library of fine particles. Furthermore, various studies that used SERS for fine-particle composition analysis showed that the uniqueness of the SERS substrates and different excitation wavelengths can produce a different spectrum for the same fine-particle component. To overcome this limitation, we conducted SERS experiments with a portable Raman spectrometer using two common SERS substrates(silver(Ag) foil and gold nanoparticles(Au NPs)) and a 785 nm laser. Herein, we introduced three main particle component types(sulfate-nitrate-ammonium(SNA), organic material, and soot) with a total of 39 chemical substances. We scanned the solid Raman, liquid Raman, and SERS spectra of these substances and constructed a fine-particle reference library containing 105 spectra. Spectral results indicated that for soot and SNA, the differences in characteristic peaks mainly originated from the solid-liquid phase transition;Ag foil had little effect on this difference, while the Au NPs caused a significant red shift in the peak positions of polycyclic aromatic hydrocarbons. Moreover, with various characteristic peak positions in the three types of spectra, we could quickly and correctly distinguish substances. We hope that this spectral library will aid in the future identification of fine particles.

关键词： Raman Surface-enhanced Raman scattering(SERS) Spectral library Fine-particle

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New WHO global air quality guidelines help prevent premature deaths in China

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National science Review 2022年第4期9卷 10-12页

作者： Tao Xue Guannan Geng Xia Meng Qingyang Xiao Yixuan Zheng Jicheng Gong Jun Liu Wei Wan Qiang Zhang Haidong Kan Shiqiu Zhang Tong Zhu Institute of Reproductive and Child Health/National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics School of Public HealthPeking University State Key Joint Laboratory of Environmental Simulation and Pollution Control School of EnvironmentTsinghua University School of Public Health Key Laboratory of Public Health Safety of the Ministry of Educationand Key Laboratory of Health Technology Assessment of the Ministry of HealthFudan University Center of Air Quality Simulation and System Analysis Chinese Academy of Environmental Planning College of Environmental Sciences and Engineering Peking University School of Energy and Environmental Engineering University of Science and Technology Beijing Clean Air Asia Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua University

The air quality guidelines （AQGs） issued by the World Health Organization （WHO） in 2005 are key references for the National Ambient Air Quality Standards （NAAQSs） in *** 22September 2021,the WHO issued new AQGs （NAQGs）[1],which propose more stringent targets to control exposure to multiple air pollutants,including fine particulate matter (PM2.5) and ozone （O3）,to which,in 2019,451 million premature deaths,globally,were attributable [2].

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Cross-Polarization suppression by Comb-Shaped slots in Microstrip Patch 13

Cross-Polarization suppression by Comb-Shaped slots in Micro...

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13th International Conference on Microwave and Millimeter Wave technology, ICMMT 2021

作者： Ma, Jing Tan, Shi-Li Ni, Si-Yuan Wang, Chen Sun, Kai Luo, Yong-Yuan Peng, Lin Beijing Simulation Center Science And Technology On Special System Simulation Laboratory Beijing100854 China 95972 Troops Of PLA Jiuquan735018 China Guilin University Of Electronic Technology Guangxi Key Laboratory Of Wireless Wideband Communication And Signal Processing Guangxi Guilin541004 China

ISBN: (纸本)9781665434379

Cross-polarization (XP) of the microstrip antenna was suppressed by etching comb-shaped slots in the patch. By cutting longitudinal comb-shaped slots on the rectangular patch, the transverse current at the patch edges that lead to cross-polarization was dammed up. Then, the co-to cross-polarization (CP-XP) ratio over entire angular range around the broadside direction was increased from 20 dB of the rectangular microstrip antenna (RMA) to 35 dB of the defected patch structure (DPS). Moreover, as the longitudinal current was little affected by the slots, the proposed structure has little effect on the other performances of the antenna (including gain, directivity, radiant principle and impedance bandwidth). As the presented structure is achieved by simple adding slots to the rectangular patch, it is very easy to be fabricated. © 2021 IEEE.

关键词： Etching

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Research on flame classification and recognition based on object detection and similarity fusion

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The Journal of China Universities of Posts and Telecommunications 2021年第5期28卷 59-67页

作者： He Xin Zhou Junhua Liao Zhonghua Zhai Xiang Sun Siyuan School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing Simulation CenterBeijing 100854China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System EngineeringBeijing 100854China

The color, shape, and other appearance characteristics of the flame emitted by different flame engines are different. In order to make a preliminary judgment on the category of the device to which it belongs through studying exterior characteristics of the flame, this paper uses the flame of matches, lighters, and candles to simulate different types of flames. It is hoped that the flames can be located and classified by detecting the characteristics of flames using the object detection algorithm. First, different types of fire are collected for the dataset of experiments. The mmDetection toolbox is then used to build several different object detection frameworks, in which the dataset can be trained and tested. The object detection model suitable for this kind of problem is obtained through the evaluation index analysis. The model is ResNet50-based faster-region-convolutional neural network(Faster R-CNN), whose mean average-precision(mAP) is 93.6%. Besides, after clipping the detected flames through object detection, a similarity fusion algorithm is used to aggregate and classify the three types of flames. Finally, the color components are analyzed to obtain the red, green, blue(RGB) color histograms of the three flames.

关键词： flame classification object detection similarity fusion

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The missing base molecules in atmospheric acid-base nucleation

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National science Review 2022年第10期9卷 196-208页

作者： Runlong Cai Rujing Yin Chao Yan Dongsen Yang Chenjuan Deng Lubna Dada Juha Kangasluoma Jenni Kontkanen Roope Halonen Yan Ma Xiuhui Zhang Pauli Paasonen Tuukka Pet?j? Veli-Matti Kerminen Yongchun Liu Federico Bianchi Jun Zheng Lin Wang Jiming Hao James N.Smith Neil M. Donahue Markku Kulmala Douglas R.Worsnop Jingkun Jiang State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment Tsinghua University Institute for Atmospheric and Earth System Research/Physics Faculty of Science University of Helsinki Aerosol and Haze Laboratory Beijing Advanced Innovation Center for Soft Matter Science and Engineering Beijing University of Chemical Technology Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science and Technology Laboratory of Atmospheric Chemistry Paul Scherrer Institute Center for Joint Quantum Studies and Department of Physics School of Science Tianjin University Key Laboratory of Cluster Science Ministry of Education of China School of Chemistry and Chemical Engineering Beijing Institute of Technology Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3) Department of Environmental Science and Engineering Fudan University Chemistry Department University of California Center for Atmospheric Particle Studies Carnegie Mellon University Department of Chemistry Carnegie Mellon University Aerodyne Research Inc.

Transformation of low-volatility gaseous precursors to new particles affects aerosol number concentration,cloud formation and hence the *** clustering of acid and base molecules is a major mechanism driving fast nucleation and initial growth of new particles in the ***,the acid-base cluster composition,measured using state-of-the-art mass spectrometers,cannot explain the measured high formation rate of new *** we present strong evidence for the existence of base molecules such as amines in the smallest atmospheric sulfuric acid clusters prior to their detection by mass *** demonstrate that forming（H2SO4）1（amine）1is the rate-limiting step in atmospheric H2SO4-amine nucleation and the uptake of（H2SO4）1（amine）1is a major pathway for the initial growth of *** proposed mechanism is very consistent with measured new particle formation in urban beijing,in which dimethylamine is the key base for H2SO4nucleation while other bases such as ammonia may contribute to the growth of larger *** findings further underline the fact that strong amines,even at low concentrations and when undetected in the smallest clusters,can be crucial to particle formation in the planetary boundary layer.

关键词： new particle formation acid-base nucleation aerosol polluted urban environment

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Pattern Analysis and Placement Optimization of the Four-horn Monopulse for Terahertz Communication

Pattern Analysis and Placement Optimization of the Four-horn...

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Cross Strait Quad-Regional Radio science and Wireless technology Conference (CSRWTC)

作者： Yong-Han Lu Zhong-bo Zhu Jing Ma Bin Shi Yu-ting Zhang Lin Peng Key Laboratory of Microwave and Optical Wave Application Technology Guilin University of Electronic Technology Guilin Guangxi China National Key Laboratory of Science and Technology on Space Microwave Xi'an China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing China Guangxi Key Laboratory of Optoelectronic Information Processing School of Optoelectronic Engineering Guilin University of Electronic Technology Guilin China

The mobile node communication in terahertz monopulse system requires narrow beam to align with the mobile target precisely. In this paper, the radiation pattern of four-horn monopulse antenna is analyzed by use of the geometric optics (GO) and aperture field integration method (AFIM), and an efficient placement optimization to reduce the beamwidth of four-horn monopulse is presented. The optimization combines the genetic algorithm (GA) with GO-AFIM. The GA is employed to seek the optimal positions of the four horns, and the GO and AFIM are introduced into the fitness function of GA to evaluate the individual fitness. The optimization result has narrowed the beamwidth and enhanced gain of radiation pattern. Compared with the simulation in full wave software, the proposed method costs less time in pattern analysis and performs more efficiently in placement optimization.

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