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A back analysis scheme for refined soil stratification based on integrating borehole and CPT data

Geoscience Frontiers 2024年第1期15卷 1-16页

作者： jiawei xie Cheng Zeng Jinsong Huang Yuting Zhang Jianlin Lu Discipline of Civil Surveying&Environmental EngineeringPriority Research Centre for Geotechnical Science&EngineeringThe University of NewcastleCallaghanNSW 2308Australia

Utilizing both borehole and Cone Penetration Testing(CPT)data in soil stratification helps to get more convincing soil stratification results.However,the soil classification results revealed by borehole(Unified Soil Classification System,USCS)and CPT tests(soil behavior type,SBT)are commonly not con-sistent.This study proposes a feasible solution to integrate the borehole and CPT data with the tree-based method.The tree-based method is naturally suitable for soil stratification tasks as it aims to divide the subsurface space into several clusters based on the similarities of the soil types.A novel boundary dic-tionary method is proposed to enhance the model performance on complex soil layer conditions.A prob-abilistic mapping matrix between the USCS-SBT system is built based on a collected municipal database with collocated borehole and CPT data.The optimal soil stratification results can be selected based on considering multiple borehole information and pruning the structure of trees.The structure of the trees can be optimized in a back analysis perspective with the Sequential Model-Based Global Optimization(SMBO)algorithm which aims to maximize the possibility of observing the borehole information based on the USCS-SBT probabilistic mapping matrix.The uncertainties of the optimal soil stratification results can be estimated based on a weighted Gini index method.The performance of the proposed method is validated based on a real case in New Zealand with a cross-validation method.The results indicate that the proposed method is robust and effective.

关键词： Soil stratification Data integration Borehole CPT Tree-based method

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High corrosion and wear resistant electroless Ni–P gradient coatings on aviation aluminum alloy parts

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International Journal of Minerals,Metallurgy and Materials 2024年第1期31卷 155-164页

作者： Bo Wang jiawei Li Zhihui xie Gengjie Wang Gang Yu College of Chemistry and Chemical Engineering Hunan UniversityChangsha 410012China Chemical Synthesis and Pollution Control Key Laboratory of Sichuan Province/College of Chemistry and Chemical Engineering China West Normal UniversityNanchong 637002China Zhongchuan Machinery Ltd.Co. Aero Engine Corporation of ChinaChangsha 410200China

A Ni–P alloy gradient coating consisting of multiple electroless Ni–P layers with various phosphorus contents was prepared on the aviation aluminum alloy. Several characterization and electrochemical techniques were used to characterize the different Ni–P coatings’ morphologies, phase structures, elemental compositions, and corrosion protection. The gradient coating showed good adhesion and high corrosion and wear resistance, enabling the application of aluminum alloy in harsh environments. The results showed that the double zinc immersion was vital in obtaining excellent adhesion (81.2 N). The optimal coating was not peeled and shredded even after bending tests with angles higher than 90°and was not corroded visually after 500 h of neutral salt spray test at 35℃. The high corrosion resistance was attributed to the misaligning of these micro defects in the three different nickel alloy layers and the amorphous structure of the high P content in the outer layer. These findings guide the exploration of functional gradient coatings that meet the high application requirement of aluminum alloy parts in complicated and harsh aviation environments.

关键词： aluminum alloy electroless nickel coating corrosion adhesion

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Study on metal recovery process and kinetics of oxidative leaching from spent LiFePO_(4)Li-batteries

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Chinese Journal of Chemical Engineering 2024年第4期68卷 94-102页

作者： Xiaoming Zhang Wen xie Xiaolei Zhou Wenjie Zhang jiawei Wen Xin Wang Guoyong Huang Shengming Xu College of New Energy and Materials China University of PetroleumBeijing 102249China State Key Laboratory of Heavy Oil Processing College of Chemical EngineeringChina University of PetroleumBeijing 102249China Beijing Spacecrafts Beijing 100094China Ganfeng Lithium Group Co. Ltd.Xinyu 338000China Institute of Nuclear and New Energy Technology Tsinghua UniversityBeijing 100084China Beijing Key Laboratory of Fine Ceramics Tsinghua UniversityBeijing 100084China

A green environmental protection and enhanced leaching process was proposed to recover all elements from spent lithium iron phosphate(LiFePO_(4))lithium batteries.In order to reduce the influence of Al impurity in the recovery process,NaOH was used to remove impurity.After impurity removal,the spent LiFePO_(4)cathode material was used as raw material under the H2SO4 system,and the pressure oxidation leaching process was adopted to achieve the preferential leaching of lithium.The E-pH diagram of the Fe ePeAleH_(2)O system can determine the stable region of each element in the recovery process of spent LiFePO_(4)Li-batteries.Under the optimal conditions(500 r·min^(-1),15 h,363.15 K,0.4 MPa,the liquidesolid ratio was 4:1 ml·g^(-1)and the acidematerial ratio was 0.29),the leaching rate of Li was 99.24%,Fe,Al,and Ti were 0.10%,2.07%,and 0.03%,respectively.The Fe and P were precipitated and recovered as FePO_(4)·2H_(2)O.The kinetic analysis shows that the process of high-pressure acid leaching of spent LiFePO_(4)materials depends on the surface chemical reaction.Through the life cycle assessment(LCA)of the spent LiFePO_(4)whole recovery process,eight midpoint impact categories were selected to assess the impact of recovery process.The results can provide basic environmental information on production process for recycling industry.

关键词： Spent LiFePO_(4)Li-batteries Oxidative leaching Kinetic study Life cycle assessment

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Lightweight Object Detection Networks for UAV Aerial Images Based on YOLO

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Chinese Journal of Electronics 2024年第4期33卷 997-1009页

作者： Yanshan LI Jiarong WANG Kunhua ZHANG jiawei YI Miaomiao WEI Lirong ZHENG Weixin xie ATR National Key Laboratory of Defense Technology Shenzhen University Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University

Existing high-precision object detection algorithms for UAV(unmanned aerial vehicle) aerial images often have a large number of parameters and heavy weight, which makes it difficult to be applied to mobile devices.We propose three YOLO-based lightweight object detection networks for UAVs, named YOLO-L, YOLO-S, and YOLO-M, respectively. In YOLO-L, we adopt a deconvolution approach to explore suitable upsampling rules during training to improve the detection accuracy. The convolution-batch normalization-Si LU activation function(CBS)structure is replaced with Ghost CBS to reduce the number of parameters and weight, meanwhile Maxpool maximum pooling operation is proposed to replace the CBS structure to avoid generating parameters and weight. YOLO-S greatly reduces the weight of the network by directly introducing CSPGhost Neck residual structures, so that the parameters and weight are respectively decreased by about 15% at the expense of 2.4% mAP. And YOLO-M adopts the CSPGhost Neck residual structure and deconvolution to reduce parameters by 5.6% and weight by 5.7%, while m AP only by 1.8%. The results show that the three lightweight detection networks proposed in this paper have good performance in UAV aerial image object detection task.

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Electrochemical nitrate reduction to produce ammonia integrated into wastewater treatment:Investigations and challenges

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Chinese Chemical Letters 2023年第6期34卷 26-36页

作者： Xinyi Zou jiawei xie Changhong Wang Guangming Jiang Kai Tang Chongjun Chen School of Environmental Science and Engineering Suzhou University of Science and TechnologySuzhou 215009China School of Materials Science and Engineering Suzhou University of Science and TechnologySuzhou 215011China Engineering Research Center for Waste Oil Recovery Technology and Equipment Ministry of EducationChongqing Technology and Business UniversityChongqing 400067China Jiangsu Collaborative Innovation Center of Technology and Material of Water Treatment Suzhou 215009China Tianping College of Suzhou University of Science and Technology Suzhou 215009China

Nitrate(NO_(3)^(-))is widely found in wastewater,which is harmful to human health and water environmental.Electrochemical reduction can convert NO_(3)^(-)to high value-added ammonia(NH)3)/ammonium(NH_(4)^(+))for pollutant removal and resource recovery.Currently,electrochemical nitrate reduction to produce ammonia(ENRA)is mostly focused on the preparation of high-performance catalysts,while ignoring the prerequisite for industrial application as the stable operation and optimal regulation of the process.Therefore,the review focused on wastewater treatment,based on the mechanism of electrochemical nitrate reduction for ammonia production and reactor construction(reactor,power supply system),then summarized the operation control strategies(such as reduction potential,nitrate concentration,inorganic ions,p H)that should be noted for ENRA.Finally,the challenges(system structure,economy)and prospects(ammonia recovery process,construction of large-scale ENRA system,application of real wastewater)of the field as it moves towards commercialization were discussed.It is hoped that this review will facilitate the scaling up of ENRA in the wastewater treatment field.

关键词： Electrochemistry Nitrate reduction Ammonia production Control strategy

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A generic framework for geotechnical subsurface modeling with machine learning

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Journal of Rock Mechanics and Geotechnical Engineering 2022年第5期14卷 1366-1379页

作者： jiawei xie Jinsong Huang Cheng Zeng Shan Huang Glen J.Burton Discipline of Civil Surveying and Environmental EngineeringPriority Research Centre for Geotechnical Science and EngineeringThe University of NewcastleCallaghanNSW2308Australia ATC Williams Pty.Ltd. SingletonNSW2330Australia

This study introduces a generic framework for geotechnical subsurface modeling, which accounts for spatial autocorrelation with local mapping machine learning(ML) methods. Instead of using XY coordinate fields directly as model input, a series of autocorrelated geotechnical distance fields(GDFs) is designed to enable the ML models to infer the spatial relationship between the sampled locations and unknown locations. The whole framework using GDF with ML methods is named GDF-ML. This framework is purely data-driven which avoids the tedious work in the scale of fluctuations(SOFs)estimating and data detrending in the conventional spatial interpolation methods. Six local mapping ML methods(extra trees(ETs), gradient boosting(GB), extreme gradient boosting(XGBoost), random forest(RF), general regression neural network(GRNN) and k-nearest neighbors(KNN)) are compared in the GDF-ML framework. The results show that the GDFs are better than the conventional XY coordinate fields based ML methods in both accuracy and spatial continuity. GDF-ML is flexible which can be applied to high-dimensional, multi-variable and incomplete datasets. Among these six methods, GDF with ET method(GDF-ET) clearly shows the best accuracy and best spatial continuity. The proposed GDF-ET method can provide a fast and accurate interpretation of the soil property profile. Sensitivity analysis shows that this method is applicable to very small training dataset size. The associated statistical uncertainty can also be quantified so that the reliability of the subsurface modeling results can be estimated objectively and explicitly. The uncertainty results clearly show that the prediction becomes more accurate when more sampled data are available.

关键词： Site investigation Machine learning(ML) Spatial interpolation Geotechnical distance fields(GDFs) Tree-based models

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Neutralization of SARS-CoV-2 infection by antibodies targeting diverse epitopes

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Genes & Diseases 2024年第4期11卷 134-137页

作者： Shusheng Wang Yunji Liao Kaiyong Yang Hang Ma Zhangyi Song Haiqiu Huang Li Zhang Ailing Wang Lei Han jiawei Zhang Hui Chen Haiyang Yin Yantin Bian Hua Jiang Xiaodong Xiao Yueqing xie Yunsheng Yuan Jianwei Zhu Engineering Research Center of Cell and Therapeutic Antibody Ministry of EducationSchool of PharmacyShanghai Jiao Tong UniversityShanghai 200240China Jecho Laboratories Inc.FrederickMD 21704USA Jecho Institute Co. Ltd.Shanghai 200240China

The CoVID-19 pandemic that started in late 2019 is sweeping through the world,posing historic challenges to global health,and disrupting social and economic lives.Previous and recent studies indicate that monoclonal antibodies can be efficacious in preventing and treating SARSCoV-1 and SARS-CoV-2 infections.Using a phage display platform,we have identified dozens of monoclonal antibodies that bind to diverse epitope groups on the SARS-CoV-2 spike protein.Many of them bound to the receptor binding domain(RBD)and inhibited ACE2-RBD interaction.

关键词： antibodies inhibited monoclonal

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突发散热故障时的光伏MPPT变换器控制方法研究

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电力系统保护与控制 2024年第11期52卷 170-178页

作者：谢佳伟应展烽李德明南京理工大学能源与动力工程学院江苏南京210094

作为光伏发电系统的重要组成,MPPT变换器能够实现光伏电池最大功率点跟踪(maximumpowerpoint tracing, MPPT)控制。但在环境通风不畅和冷却装置失效等突发性散热故障情况下,变换器极易发生过热停机保护,导致光伏电池无法输出功率,严重... 详细信息

作为光伏发电系统的重要组成,MPPT变换器能够实现光伏电池最大功率点跟踪(maximumpowerpoint tracing, MPPT)控制。但在环境通风不畅和冷却装置失效等突发性散热故障情况下,变换器极易发生过热停机保护,导致光伏电池无法输出功率,严重影响光伏发电的可靠性与经济性。为此,以一个300 W级MPPT变换器为对象,对其功率器件温升特性进行了试验分析。随后,结合传统MPPT算法和主动热管理策略,提出了一种突发散热故障时的光伏MPPT变换器控制方法。通过对器件驱动信号占空比的动态限制和开关频率的分级调节,所提方法能够主动调整器件工作损耗,进而充分挖掘变换器输出功率。相关实验表明,所提方法可最大程度保留变换器散热故障时的光伏出力,并减少散热故障修复前的光伏发电经济损失。根据实验结果,构建了所提方法性能评价指标,并分析了方法性能的影响因素。

关键词：光伏发电最大功率点跟踪控制功率器件结温估计主动热管理

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相干累加与AR滤波相结合的舰船轴频电场信号处理方法

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国防科技大学学报 2024年第3期46卷 229-236页

作者：程锦房谢昌奇张伽伟喻鹏海军工程大学兵器工程学院湖北武汉430033 中国人民解放军92214部队浙江宁波315000 海军士官学校兵器系安徽蚌埠233000

针对采用电场传感器阵列测量舰船电场的应用场景,为提升目标轴频电场的信噪比,提出一种相干累加结合自回归(autoregressive,AR)模型滤波的方法对阵列电场信号进行处理。对测量得到的阵列电场信号进行时延补偿后累加,同时对环境电场信号... 详细信息

针对采用电场传感器阵列测量舰船电场的应用场景,为提升目标轴频电场的信噪比,提出一种相干累加结合自回归(autoregressive,AR)模型滤波的方法对阵列电场信号进行处理。对测量得到的阵列电场信号进行时延补偿后累加,同时对环境电场信号进行AR建模,并利用AR模型参数构造滤波器,以对累加后的信号实施滤波处理。为验证所提方法在低信噪比条件下的有效性,对实测阵列式电场信号进行处理,结果表明,所提方法能够在信噪比为-25.39 dB的条件下有效压制噪声频谱,保留轴频线谱,处理后信噪比提高约21.92 dB。

关键词：轴频电场阵列信号处理相干累加 AR模型滤波

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基于激光诱导荧光的土壤石油污染物荧光仿真研究

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中国激光 2024年第5期51卷 213-221页

作者：谢贝贝周炫宇赵佳伟王智翀燕山大学信息科学与工程学院河北秦皇岛066004 河北省计算机虚拟技术与系统集成重点实验室河北秦皇岛066004

激光诱导荧光(LIF)技术是一种主动式的遥感光学探测技术。土壤是常见的天然多孔介质,与石油混合后油滴会进入其孔隙内部,其独特的结构可以使光线发生多次反射和吸收,这种现象导致LIF探测土壤石油污染物获得的荧光分布具有差异性。笔者... 详细信息

激光诱导荧光(LIF)技术是一种主动式的遥感光学探测技术。土壤是常见的天然多孔介质,与石油混合后油滴会进入其孔隙内部,其独特的结构可以使光线发生多次反射和吸收,这种现象导致LIF探测土壤石油污染物获得的荧光分布具有差异性。笔者根据土壤含油量的多少以及分布特点,将土壤石油污染物分为油泥与含油土壤,基于蒙特卡罗方法和多孔介质的隐函数表示法,分别建立油泥和含油土壤的荧光仿真模型,采用荧光转换效率(接收荧光功率与发射激光功率的比值)表征荧光强度,从不同出射方向分析发射出土壤的荧光分布情况。通过模拟不同油品污染的油泥和含油土壤在不同入射天顶角、孔隙率、孔隙密度下的荧光转换效率,分析不同油品、LIF系统参数和土壤因素对荧光分布的影响。仿真结果表明:对于同种石油污染的油泥和含油土壤,油泥因较高的含油量导致荧光信号强于含油土壤;当激光垂直入射时,LIF系统收集的荧光信号强度最高,入射角度增大会导致荧光信号强度逐渐减弱;土壤石油污染物的荧光强度会随着孔隙率的增大而增大,随着孔隙密度的增大而减小;在激光照射下,轻质原油污染的土壤由于吸收系数较低,产生的荧光信号要弱于重质石油污染的土壤。本研究为LIF探测陆地溢油污染提供了理论和技术支持。

关键词：光谱学激光诱导荧光蒙特卡罗多孔介质土壤石油污染物荧光仿真

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