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A systematic review of machine learning modeling processes and applications in ROP prediction in the past decade

Petroleum Science 2024年第5期21卷 3496-3516页

作者： Qian Li Jun-Ping Li Lan-Lan Xie College of Environment and Civil Engineering Chengdu University of TechnologyChengdu610059SichuanChina State Key Laboratory of Geohazard Prevention and Geoenvironment Protection(Chengdu University of Technology) Chengdu610059SichuanChina Institute of Exploration Technology CAGSChengdu610059SichuanChina

Fossil fuels are undoubtedly important, and drilling technology plays an important role in realizing fossil fuel exploration;therefore, the prediction and evaluation of drilling efficiency is a key research goal in the industry. Limited by the unknown geological environment and complex operating procedures, the prediction and evaluation of drilling efficiency were very difficult before the introduction of machine learning algorithms. This review statistically analyses rate of penetration(ROP) prediction models established based on machine learning algorithms;establishes an overall framework including data collection, data preprocessing, model establishment, and accuracy evaluation;and compares the effectiveness of different algorithms in each link of the process. This review also compares the prediction accuracy of different machine learning models and traditional models commonly used in this field and demonstrates that machine learning models are the most effective technical means in current ROP prediction modeling.

关键词： Drilling Rate of penetration(ROP)prediction Machine learning Accuracy evaluation

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Simulation of unmanned survey path planning in debris flow gully based on GRE-Bat algorithm

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Journal of Mountain Science 2024年第12期21卷 4062-4082页

作者： LIU Dunlong FENG Duanguo SANG Xuejia ZHANG Shaojie YANG Hongjuan College of Software Engineering Chengdu University of Information TechnologyChengdu 610225China State Key Laboratory of Mountain Hazards and Engineering Resilience Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610299China

Unmanned aerial vehicle(UAV)paths in the field directly affect the efficiency and accuracy of payload data *** planning of UAV advancing along river valleys in wild environments is one of the first and most difficult problems faced by unmanned surveys of debris flow *** study proposes a new hybrid bat optimization algorithm,GRE-Bat(Good point set,Reverse learning,Elite Pool-Bat algorithm),for unmanned exploration path planning of debris flow sources in outdoor *** the GRE-Bat algorithm,the good point set strategy is adopted to evenly distribute the population,ensure sufficient coverage of the search space,and improve the stability of the convergence accuracy of the ***,a reverse learning strategy is introduced to increase the diversity of the population and improve the local stagnation problem of the *** addition,an Elite pool strategy is added to balance the replacement and learning behaviors of particles within the population based on elimination and local perturbation *** demonstrate the effectiveness of the GRE-Bat algorithm,we conducted multiple simulation experiments using benchmark test functions and digital terrain *** to commonly used path planning algorithms such as the Bat Algorithm(BA)and the Improved Sparrow Search Algorithm(ISSA),the GRE-Bat algorithm can converge to the optimal value in different types of test functions and obtains a near-optimal solution after an average of 60 *** GRE-Bat algorithm can obtain higher quality flight routes in the designated environment of unmanned investigation in the debris flow gully basin,demonstrating its potential for practical application.

关键词： Bat algorithm Unmanned surveys Debris flow gully Path planning Unmanned aerial vehicle Reverse learning

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Fault Diagnosis Model for UAV with Small Sample Size and Imbalanced Data 15

Fault Diagnosis Model for UAV with Small Sample Size and Imb...

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15th IEEE Global reliability and Prognostics and Health Management Conference, PHM-Beijing 2024

作者： Song, Guoqing Ma, Ke Yang, Yang Dong, Yanchen Han, Danyang Suo, Mingliang School of Reliability and Systems Engineering Beihang University Beijing100191 China No.31850 People's Liberation Army of China Beijing102200 China Institute of Reliability Engineering National Key Laboratory of Science and Technology on Reliability and Environmental Engineering School of Reliability and Systems Engineering Beihang University Beijing100191 China

ISBN: (纸本)9798350354010

With the development of Unmanned Aerial Vehicles (UAV), their application scenarios and task requirements have become more complex, demanding higher standards for subsequent fault diagnosis and equipment maintenance. The actual flight data of UAV usually exhibits small sample sizes and imbalanced characteristics. To achieve more efficient fault prediction for UAV, this paper establishes a SMOTE-IWOA-RF fault diagnosis model. This model optimizes the Whale Optimization Algorithm (WOA) using chaotic initialization, nonlinear convergence factors, and Lévy flight strategies, resulting in better convergence accuracy and global search capability, as well as faster convergence speed. The model is compared with other classification models on data with different imbalance ratios, demonstrating that it is more efficient and accurate in UAV fault diagnosis, with the F1 score improving by about 10% compared to the pre-optimization state. Furthermore, the IWOA-RF model is combined with other data preprocessing methods, showing that SMOTE-IWOA-RF performs better on UAV operational data, indicating its practical value. © 2024 IEEE.

关键词： Fault detection

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Review of recent advances in ferrite-based materials:From synthesis techniques to electromagnetic wave absorption performance

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International Journal of Minerals,Metallurgy and Materials 2025年第3期32卷 591-608页

作者： Xingliang Chen Di Lan Luoting Zhou Hailing Liu Xiyu Song Shouyu Wang Zhuanyong Zou Guanglei Wu Shaoxing Key Laboratory of High Performance Fibers&Products Key Laboratory of Clean Dyeing and Finishing Technology of Zhejiang ProvinceShaoxing UniversityShaoxing 312000China School of Materials Science and Engineering Hubei University of Automotive TechnologyShiyan 442002China Chinatesta(Zhejiang)Testing Services Co. Ltd.Shaoxing 312000China Institute of Materials for Energy and Environment State Key Laboratory of Bio-fibers and Eco-textilesCollege of Materials Science and EngineeringQingdao UniversityQingdao 266071China

With the booming development of electronic information science and 5G communication technology,electromagnetic radi-ation pollution poses a huge threat and damage to *** novel and high-performance electromagnetic wave(EMW)ab-sorbers is an effective method to solve the above issue and has attracted the attention of many *** a typical magnetic material,ferrite plays an important role in the design of high-performance EMW absorbers,and related research focuses on diversified synthesis methods,strong absorption performance,and refined microstructure ***,we focus on the synthesis of ferrites and their composites and introduce recent advances in the high-temperature solid-phase method,sol-gel method,chemical coprecipitation method,and solvent thermal method in the preparation of high-performance EMW *** review aims to help researchers understand the advantages and disadvantages of ferrite-based EMW absorbers fabricated through these *** also provides important guidance and reference for researchers to design high-performance EMW absorption materials based on ferrite.

关键词： ferrite electromagnetic wave absorber sol-gel method magnetic material solvent thermal method

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Surface/Interface engineering of Hierarchical MoO_(2)/MoNi_(4)@Ru/RuO_(2)Heterogeneous Nanosheet Arrays for Alkaline Water Electrolysis with Fast Kinetics

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Chinese Journal of Chemistry 2024年第2期42卷 119-128页

作者： Qiong Zhang Ruixue Zhang Yingxiu Zhao Tiantian Sun Jianyang Gao Guang-Rui Xu Zexing Wu Yu Yang Lei Wang Key Laboratory of Eco-chemical Engineering Key Laboratory of Optic-electric Sensing and Analytical Chemistry of Life ScienceTaishan Scholar Advantage and Characteristic Discipline Team of Eco Chemical Process and TechnologyCollege of Chemistry and Molecular EngineeringSchool of Materials Science and EngineeringQingdao University of Science and TechnologyQingdaoShandong 266042China College of Environment and Safety Engineering Qingdao University of Science and TechnologyQingdaoShandong 266042China

Realizing the hydrogen economy by water electrolysis is an attractive approach for hydrogen production,while the efficient and stable bifunctional catalysts under high current densities are the bottleneck that limits the half-cell reactions of water ***,we propose an approach of hydrothermal and thermal annealing methods for robust MoO_(2)/MoNi_(4)@Ru/RuO_(2) heterogeneous cuboid array electrocatalyst with multiplying surface-active sites by depositing a monolayer amount of *** from abundant MoO_(2)/MoNi_(4)@Ru/RuO_(2)heterointerfaces,MoO_(2)/MoNi_(4)@Ru/RuO_(2) heterogeneous cuboid array electrocatalysts effectively drive the alkaline water splitting with superior hydrogen evolution reaction(HER)and oxygen evolution reaction(OER)*** synthesized MoO_(2)/MoNi_(4)@Ru/RuO_(2) has high HER activity,which realizes the working overpotentials of 48 mV at 50 mA·cm^(-2),further achieving overpotentials of 230 mv for industry-level 1000 mA·cm^(-2) in alkaline water ***,it also showed an enhanced OER activity than commercial RuO_(2) with a small overpotential of 280 mV at 200 mA·cm^(-2) in alkaline *** building an electrolyzer with electrodes of(-)MoO_(2)/MoNi_(4)@Ru/RuO_(2)IIMo02/MoNig@Ru/RuO_(2)(+),a cell voltage of 1.63 V and 1.75 V is just required to support the current density of 200 mA·cm^(-2) and 500 mA-cm^(-2) in alkaline water electrolysis,much lower than that of the electrolyzer of(-)Pt/CIIRuO_(2)(+).This work demonstrates that MoO_(2)/MoNig@Ru/RuO_(2) heterogeneous nanosheet arrays are promising candidates for industrial water electrolysis applications,providing a possibility for the exploration of water electrolysis with a large currentdensity.

关键词： Hierarchical heterostructure Surface engineering Bifunctional catalysts Hydrogen evolution reaction Oxygen evolution reaction Watersplitting Catalytic activity Electrocatalysis Heterogeneous catalysis

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Hybrid deep neural network based prediction method for unsteady flows with moving boundary

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Acta Mechanica Sinica 2021年第10期37卷 1557-1566,I0003页

作者： Ren-Kun Han Zhong Zhang Yi-Xing Wang Zi-Yang Liu Yang Zhang Gang Chen State Key Laboratory for Strength and Vibration of Mechanical Structures Shannxi Key Laboratory for Environment and Control of Flight VehicleSchool of Aerospace EngineeringXi’an Jiaotong UniversityXi’an710049China Science and Technology on Reliability and Environment Engineering Laboratory Beijing Institute of Structure and Environment EngineeringBeijing100076China

Any motion, forced or free, of boundary affects the flow field around this boundary. A new kind of reduced order model (ROM) based on hybrid deep neural network is proposed to model flow field evolution process of unsteady flow around moving boundary. This hybrid deep neural network can map the relationship between the flow field at the next time step and the flow field and boundary positions at the previous time steps. Based on the learned information, the hybrid deep neural network can quickly and accurately predict the flow field. Unsteady flows around forced oscillation cylinder with various amplitudes, frequencies, and Reynolds numbers are simulated to establish the training and testing datasets. The prediction results of the hybrid deep neural network and the computational fluid dynamics (CFD) simulation results are consistent with high accuracy. The forces on the moving boundary can be integrated through the predicted flow field data. Good performance makes this new ROM method can be used in many fluid dynamics research fields, which needs fast and accurate simulation.

关键词： Deep neural network Flow fields prediction Moving boundary

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Landslide susceptibility prediction method based on HSOM and IABPA-CNN in Wenchuan earthquake disaster area

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Journal of Mountain Science 2024年第12期21卷 4001-4018页

作者： LIU Dunlong XIANG Qian SANG Xuejia ZHANG Shaojie YANG Hongjuan College of Software Engineering Chengdu University of Information TechnologyChengdu 610225China State Key Laboratory of Mountain Hazards and Engineering Resilience Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610299China

Landslide susceptibility prediction assesses the likelihood of landslides occurring in specific areas,providing crucial scientific support for mitigating the threat to people’s lives and property posed by landslide *** address the challenges in the existing landslide susceptibility prediction methods,such as insufficient representativeness of selected nonlandslide points,limited ability to capture nonlinear relationships,and a tendency to fall into local optima,the traditional Self-Organizing Maps(SOM)is improved in this paper by using a hierarchical approach to form Hierarchical Self-Organizing Maps(HSOM),and a model integrating the Information Value(IV),Adaptive Bat Precise Algorithm(ABPA),and Convolutional Neural Network(CNN)is proposed,termed *** factors such as topography,basic geology and hydrometeorology were selected with the 2008 Wenchuan earthquake-hit disaster area as the study *** data were preprocessed,Pearson correlation coefficient,tolerance(TOL),and variance inflation factor(VIF)were employed to assess the correlation among all the ***,the information value for each evaluation factor's classification was calculated,thereby establishing a high-quality sample dataset,which was input into the IABPA-CNN model and IVCNN model(contrast model),*** Receiver Operating Characteristic(ROC)curve was used to compare and analyze the accuracy and *** Area Under Curve(AUC)values for the two models is 0.89 and 0.85,respectively,indicating that the IABPA-CNN model has higher predictive *** with the IV-CNN model,the proportion of landslides predicted by the IABPA-CNN model in the high susceptibility and very high susceptibility area increased to 28.18%and 30.76%,*** the area proportions of very low susceptibility and low susceptibility area increased,the proportion of landslides quantity ***,Monte Carlo method was employed to analyze the uncertaint

关键词： Landslide Susceptibility Information value Convolutional neural network Bat algorithm Monte Carlo

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Seed-aided green synthesis of metal-organic frameworks in water

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Green Chemical engineering 2023年第1期4卷 64-72页

作者： Hao-Tian An Xin Zhang Chen Dong Mu-Yao Lu Rui Li Yabo Xie Lin-Hua Xie Jian-Rong Li Beijing Key Laboratory for Green Catalysis and Separation and Department of Environmental Chemical Engineering Faculty of Environment and LifeBeijing University of TechnologyBeijing100124China

Green synthesis of metal-organic frameworks(MOFs)in water with alleviated environmental influence and reduced cost is an essential step to transfer laboratory MOFs research to industrial *** from the commonly used organic solvents to pure water encounters challenges of the poor solubility of organic linkers,slow reaction kinetics,and the formation of polymorphic *** far,a universal MOFs synthetic strategy in water system has yet to be *** study reports the seed-aided synthesis of eleven MOFs with diverse compositions and structures while pure water serving as *** corresponding reaction temperature and time of using this new strategy were reduced compared with original synthetic approaches,while the products maintain porous structure and high *** success of this strategy relies on the addition of parent MOFs as seeds which could promote crystallization process by skipping the time-consuming induction period and avoiding the formation of polymorphic impurities.

关键词： Metal-organic frameworks Carbon neutrality Coal bed methane Greenhouse gas Fossil fuel

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Boosting the catalytic performance of Cu-SAPO-34in NO_(x) removal via hydrothermal treatment

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Journal of environmental Sciences 2024年第1期135卷 640-655页

作者： Xiaoyan Tian Huimin Wang Siyuan Xu Lianyun Gao Jinyan Cao Jianjun Chen Qiulin Zhang Ping Ning Jiming Hao Faculty of Environmental Science and Engineering Kunming University of Science and TechnologyKunming 650500China National-Regional Engineering Center for Recovery of Waste Gases from Metallurgical and Chemical Industries Kunming University of Science and TechnologyKunming 650500China School of Environment State Key Joint Laboratory of Environment Simulation and Pollution ControlTsinghua UniversityBeijing 100084China

Phosphate ions promoted Cu-SAPO-34(P-Cu-SAPO-34)were prepared using bulk CuO particles as Cu^(2+)precursor by a solid-state ion exchange technique for the selective catalytic reduction of NO_(x) with NH_3(NH_3-SCR).The effects of high temperature(H-T)hydrothermal aging on the NO_(x) removal(de-NO_(x))performance of Cu-SAPO-34 with and without phosphate ions were systematically investigated at atomic *** results displayed that both Cu-SAPO-34 and P-Cu-SAPO-34 presented relatively poor NO_(x) removal activity with a low conversion(<30%)at 250-500℃.However,after H-T hydrothermal treatment(800℃ for 10 hr at 10%H_2O),these two samples showed significantly satisfied NO_(x) elimination performance with a quite high conversion(70%-90%)at 250-500℃.Additionally,phosphate ions decoration can further enhance the catalytic performance of Cu-SAPO-34 after hydrothermal treatment(Cu-SAPO-34H).The textural properties,morphologies,structural feature,acidity,redox characteristic,and surface-active species of the fresh and hydrothermally aged samples were analyzed using various characterization *** systematical characterization results revealed that increases of 28%of the isolated Cu^(2+)active species(Cu^(2+)-2Z,Cu(OH)^(+)-Z)mainly from bulk CuO and 50%of the Bronsted acid sites,the high dispersion of isolated Cu^(2+)active component as well as the Bronsted acid sites were mainly responsible for the accepted catalytic activity of these two hydrothermally aged samples,especially for P-Cu-SAPO-34H.

关键词： NH_(3)-SCR Cu-SAPO-34 Hydrothermal induced Phosphate ions

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Recent advances on decomplexation mechanisms of heavy metal complexes in persulfate-based advanced oxidation processes

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Chinese Chemical Letters 2024年第6期35卷 146-154页

作者： Shili Wang Mamitiana Roger Razanajatovo Xuedong Du Shunli Wan Xin He Qiuming Peng Qingrui Zhang State Key Laboratory of Metastable Materials Science and Technology Hebei Key Laboratory of Heavy Metal Deep-Remediation in Water and Resource ReuseYanshan UniversityQinhuangdao 066004China Hebei Key Laboratory of Agroecological Safetye Key Laboratory Hebei University of Environmental EngineeringQinhuangdao 066102China College of Life&Environment Sciences Huangshan UniversityHuangshan 245041China

In some industrial wastewater,heavy metals combine with organic complexing agents to form heavy metal complexes(HMCs).These HMCs can be difficult to decompose and remove through conventional techniques due to their higher stability than free heavy metal *** recent years,persulfate based advanced oxidation processes(PS-based AOPs)have been recognized as a viable technique for HMCs ***,a comprehensive and in-depth understanding of the relevant HMCs decomplexation mechanisms in PS-based AOPs is still *** review delineates the current progress of HMCs decomplexation in PS-based *** discuss the distinctions between the two widely used oxidant types in PS-based AOPs ***,we summarize and highlight the decomplexation mechanisms based on electron and energy transfer,and degradation pathways of *** also emphasize the effects of environmental water constituents,namely p H,inorganic ions,and natural organic matter(NOM),on HMCs ***,we identify the existing challenges and perspectives that will steer the direction of advancing PS-based AOPs to remove HMCs.

关键词： Heavy metal complexes Persulfate Advanced oxidation processes Decomplexation mechanisms Electron and energy transfer

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