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Biochar and straw application reshape organic carbon pool via altering soil carbon pump function based on a decadal field experiment

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Soil and Tillage Research 2025年 253卷

作者： Liu, Jie Chen, Yalan Du, Zhangliu Gao, Qun Gao, Xiaofei Sun, Ke Pan, Zezhen Zhu, Shishu Xiao, Ke-Qing Van Zwieten, Lukas State Key Laboratory of Regional Environment and Sustainability School of Environment Beijing Normal University Beijing100875 China Beijing Key Laboratory of Biodiversity and Organic Farming College of Resources and Environmental Sciences China Agricultural University Beijing100193 China State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction Faculty of Geographical Science Beijing Normal University Beijing100875 China College of Geography and Environmental Science Henan University Kaifeng475004 China Department of Environmental Science and Engineering Fudan University Shanghai200438 China The Key Lab of Pollution Control and Ecosystem Restoration in Industry Clusters Ministry of Education School of Environment and Energy South China University of Technology Guangzhou510006 China State Key Laboratory of Regional and Urban Ecology Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing100085 China University of Chinese Academy of Sciences Beijing100049 China NSW Department of Primary Industries Wollongbar Primary Industries Institute WollongbarNSW2477 Australia

Soil organic carbon (SOC) accumulation is critical for maintaining agricultural production and combating climate change. Although organic amendments are commonly applied to improve SOC, the decadal-scale pathways controlling carbon sequestration remain largely unstudied. Here, a 14-year field experiment was utilized to investigate how biochar (BC) and maize straw (SW) regulate soil carbon pumps to impact SOC sequestration. The results showed that BC appeared to improve the efficiencies of both soil microbial carbon pump (MCP) via increasing microbial necromass carbon (MNC) in particulate organic matter (POM) (+90 %) and silt and clay fraction (SCF) (+35 %) and mineral carbon pump (MnCP) via increasing organic carbon (OC) in mineral-associated fractions (including SCF) (+104 %, namely 8.21 Mg C ha−1). Thus, BC enhanced SOC sequestration (+112 %) and promoted field crops growth (+10 %). The higher contribution of the SCF to SOC sequestration in the BC soil was attributed to its reducing carbon output potential, high accumulation of BC and amorphous Fe oxides, and increased Fe-bound OC. In contrast, SW only enhanced MCP operation by mainly promoting MNC concentration on POM (+151 %), which sequestrated SOC (+33 %) and increased crop yield (+7 %). While the low efficiency of MnCP in SW soil resulted from the more mineralization of abundant MNC and less Fe-bound OC within the SCF. A conceptual framework was presented whereby BC could drive both the MnCP and the MCP, resulting in significant potentials for SOC sequestration. Our findings offer valuable insights for optimizing agricultural management strategies to regulate SOC turnover and increase SOC sequestration. © 2025 Elsevier B.V.

关键词： Clay products

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Research on pipeline chaos detection based on ultrasonic guided wave 24th

Research on pipeline chaos detection based on ultrasonic gui...

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24th Australasian Conference on the Mechanics of Structures and Materials, ACMSM 2016

作者： Wen, Yuli Ma, Hongwei College of Science and Engineer Jinan University Guangzhou China Key Lab of Disaster Forecast and Control in Engineering Ministry of Education Guangzhou China School of Civil Engineering Qinghai University Xining China

ISBN: (纸本)9781138029934

This article presents a study on weak ultrasonic guided waves signal processing. In long range detection or small defect detection, the defect echo often shows the characteristic of weak signal because of attenuation, which becomes the main obstacles of ultrasonic guided waves detection. Due to the sensitive dependence on initial condition and strong noise immunity of chaotic system, Duffing chaotic oscillator weak signal detection method based on ultrasonic guided wave has been proposed. When the critical chaotic system detect the weak signal, the system state will be change. The parameters of chaotic system was determined according to the ultrasonic guided wave detection. The maximum Lyapunov exponent is chosen to detect the system state change. The chaotic oscillator is proved to have good immunity to noise by using chaotic system to process different amplitudes of Gaussian white noise. Four kinds of section reduction ratio defects are analyzed respectively. The method has been verified to be useful to expand range and improve the sensitivity in pipes defect detection by the results of numerical simulations and experiments on 6 meters pipeline. © 2017 Taylor & Francis Group, London.

关键词： Chaotic systems

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Dynamic response based damage detection for beam-like structures using deep learning 24th

Dynamic response based damage detection for beam-like struct...

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24th Australasian Conference on the Mechanics of Structures and Materials, ACMSM 2016

作者： Lin, Y.Z. Ma, H.W. Department of Mechanics and Civil Engineering Jinan University Key Laboratory of Disaster Forecast and Control in Engineering Ministry of Education Guangzhou China Department of Civil Engineering Qinghai University Xining China

ISBN: (纸本)9781138029934

Artificial Neural Network (ANN) method has attracted increasing attention in the structural damage detection field. However, its bottlenecks limit the applications in this area. In recent years, great advances in ANN called deep learning have changed the situation. This paper reports a novel application of deep learning for damage detection tasks of beam-like structure based on dynamic response. Numerical models of simple beam structure were analyzed to generate dynamic response. It was found that using a deeper neural network helped the recognition accuracy on the testing dataset contrasting a shallow network. In addition, dropout and ReLU technology play a vital role in preventing overfitting and GPU acceleration technology can provide the large computational demand of deep network. These results suggest that gaining benefits from more depth of a neural network is possible in structural damage detection problem. © 2017 Taylor & Francis Group, London.

关键词： Damage detection

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Publisher Correction: Abrupt emissions reductions during COVID-19 contributed to record summer rainfall in China

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Nature communications 2022年第1期13卷 1403页

作者： Yang Yang Lili Ren Mingxuan Wu Hailong Wang Fengfei Song L Ruby Leung Xin Hao Jiandong Li Lei Chen Huimin Li Liangying Zeng Yang Zhou Pinya Wang Hong Liao Jing Wang Zhen-Qiang Zhou Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science and Technology Nanjing Jiangsu China. yang.yang@***. Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science and Technology Nanjing Jiangsu China. Atmospheric Sciences and Global Change Division Pacific Northwest National Laboratory Richland WA USA. Atmospheric Sciences and Global Change Division Pacific Northwest National Laboratory Richland WA USA. hailong.wang@pnnl.gov. Frontier Science Centre for Deep Ocean Multispheres and Earth System and Physical Oceanography Laboratory Ocean University of China Qingdao China. Qingdao National Laboratory for Marine Science and Technology (QNLM) Qingdao China. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster Ministry of Education Nanjing University for Information Science and Technology Nanjing Jiangsu China. Tianjin Key Laboratory for Oceanic Meteorology Tianjin Institute of Meteorological Science Tianjin China. Department of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences Fudan University Shanghai China.

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Perturbation analysis for multiscale deformations of delaminated laminates

Perturbation analysis for multiscale deformations of delamin...

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第三届中国国际复合材料科技大会

作者： Jianghong Xue Fusong Jin Ying Xiong Fei Xia School of Mechanics and Construction Engineering Jinan University/Key Lab of Disaster Forecast and Control in Engineering Ministry of Education

This paper presents a perturbation approach to study the multi scale deflections in T300/QY8911 carbon fiber reinforced, delaminated laminates subjected to a transverse load. In previous works, the contact effects at the interfaces of the delaminated laminates were investigated. A contact factor was introduced to characterize the contact performances and was determined using the micro-mechanics of composite material. In this paper, asymptotic approaches are applied to analyze the large deflection of the delaminated laminates with nonlinear anti-penetrating constrains at the interfaces. Governing equations are solved using separation of variable and the asymptotic solutions are obtained from the Galerkin approach. Perturbation analysis is performed to demonstrate that(1) sublaminates above and below the delamination undergo a consistent global deflection;(2) local buckles occur on the interfaces of the delamination;and(3) the anti-penetrating contact performances are characterized by the local buckles. Furthermore, the asymptotic solutions reveal that the contact performances, i.e., the local buckling, are intrinsic properties of the laminates, relying only on the geometries of the delamination and the material properties. Numerical calculations are performed to demonstrate the application of the analytical solutions. The analytical solutions are in effect by comparing with the classic solutions and the well-established experimental results.

关键词： Perturbation analysis for multiscale deformations of delaminated laminates

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Correction: Oxidative carboxylation of olefins with CO2: environmentally benign access to five-membered cyclic carbonates

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RSC advances 2020年第18期10卷 10806页

作者： Liang Wang Sisi Que Ziwei Ding Esmail Vessally State Key Lab of Coal Mine Disaster Dynamics and Control Chongqing University Chongqing 400044 China. State Key Laboratory of Coal Resources in Western China Xi'an University of Science and Technology Xi'an 710054 China. Key Laboratory of Hydraulic and Waterway Engineering of the Ministry of Education College of River and Ocean Engineering Chongqing Jiaotong University Chongqing 400074 China. Department of Chemistry Payame Noor University Tehran Iran vessally@***.

[This corrects the article DOI: 10.1039/C9RA10755J.].

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Improved thermographic signal reconstruction method for defect detection of CFRP

Improved thermographic signal reconstruction method for defe...

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第三届中国国际复合材料科技大会

作者： Zhihua Ning Zhao Ban Chunxiu Xu School of Mechanics and Construction Engineering Key Laboratory of Disaster Forecast and Control in Engineering of Ministry of Education of China Jinan University

An improved method based on singular value decomposition analysis was proposed for defect detection of carbon fiber reinforced polymer composites using pulsed thermograph in this paper. A practical experimental set-up was developed. The thermal images collected were processed with improved singular value decomposition analysis. By combining thermographic signal reconstruction and mathematical morphology, the non-uniform background was further removed effectively. The heat transfers in CFRP sample with delaminated defects subject to pulsed thermal signal was simulated numerically with FE method. The absolute thermal contrast evaluation was analyzed and a new thermal sensitive indicator was proposed to provide more accurate estimation of the embedded damages in carbon fiber-reinforced composites. The effectiveness of the proposed thermal sensitive was examined experimentally and a comparison between the present and other sensitivities was finally performed. The result showed that, the defects in the CFRP specimen could be identified more clearly with the proposed sensitive.

关键词： Pulsed thermography CFRP composites Thermal sensitive Singular value decomposition

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Analysis and Inverse Substructuring Computation on Dynamic Quality of Mechanical Assembly

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Chinese Journal of Mechanical engineering 2016年第3期29卷 539-548页

作者： Lü Guangqing YI Chuijie FANG Ke Key Lab of Disasters Forecast and Control in Engineering of Ministry of Education Jinan University Research Center of Equipment Energy & Environment Qingdao Technological University

Mechanical assembly has its own dynamic quality directly affecting the dynamic quality of whole product and should be considered in quality inspection and estimation of mechanical assembly. Based on functional relations between dynamic characteristics involved in mechanical assembly, the effects of assembling process on dynamic characteristics of substructural components of an assembly system are investigated by substructuring analysis. Assembly-coupling dynamic stiffness is clarified as the dominant factor of the effects and can be used as a quantitative measure of assembly dynamic quality. Two computational schemes using frequency response functions（FRFs） to determine the stiffness are provided and discussed by inverse substructuring analysis, including their applicable conditions and implementation procedure in application. Eigenvalue analysis on matrix-ratios of FRFs before and after assembling is employed and well validates the analytical outcomes and the schemes via both a lumped-parameter model and its analogic experimental counterpart. Applying the two schemes to inspect the dynamic quality provides the message of dynamic performance of the assembly system, and therefore improves conventional quality inspection and estimation of mechanical assembly in completeness.

关键词： mechanical assembly dynamic quality substructuring analysis inverse substructuring assembly-coupling dynamic stiffness

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Data science and engineering for structural health monitoring 8

Data science and engineering for structural health monitorin...

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8th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 2017

作者： Li, H. Bao, Y.Q. Li, S.L. Ou, J.P. Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education Harbin Institute of Technology Harbin150090 China Key Lab of Intelligent Disaster Mitigation of the Ministry of Industry and Information Technology Harbin Institute of Technology Harbin150090 China School of Civil Engineering Harbin Institute of Technology Harbin150090 China

ISBN: (纸本)9781925553055

Structural health monitoring (SHM) technology study the damage or even characteristics of disaster evolving of structures by various types of sensors installed on structures and provide scientific support for the structural design, construction, maintenance and operation safety. The significant scientific issues of SHM can be concluded as 'sensing' and 'data'. According to the widely application of SHM on civil infrastructures and accumulation of huge quantities of data, it is well-recognized that data sciences and engineering for SHM is increasingly becoming a world-wide research focus. The issue of 'data' is core target of SHM which includes the data acquisition, transmission and management, data analysis and mining, structural damage identification and structural safety assessment and so on. This paper reviews the recent research development of data sciences and engineering on our research group which includes data acquisition by compressive sensing based on group sparse optimization, computer vison and deep learning methods for data anomaly detection and structure condition assessment, the identification and modeling of spatio-temporal distribution of vehicle loads, and corrosion damage and crack identification by computer vision ***, the artificial intelligence in civil engineering is the extension of SHM technique, and will make the civil structure have ability of "see", "sensing", "thinking","talking", "action and "adapation" (2S+2T+2A). © 2017 International Society for Structural Health Monitoring of Intelligent Infrastrucure. All rights reserved.

关键词： Structural health monitoring

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LQD-RKHS-based distribution-to-distribution regression methodology for restoring the probability distributions of missing SHM data

arXiv

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arXiv 2018年

作者： Chen, Zhicheng Bao, Yuequan Li, Hui Spencer, Billie F. Key Lab of Intelligent Disaster Mitigation of the Ministry of Industry and Information Technology Harbin Institute of Technology Harbin China Key Lab of Structures Dynamic Behaviour and Control of the Ministry of Education Harbin Institute of Technology Harbin China School of Civil Engineering Harbin Institute of Technology Harbin China Department of Civil and Environmental Engineering University of Illinois at Urbana-Champaign UrbanaIL United States Department of Civil and Environmental Engineering University of Illinois at Urbana - Champaign UrbanaIL United States

Data loss is a critical problem in structural health monitoring (SHM). Probability distributions play a highly important role in many applications. Improving the quality of distribution estimations made using incomplete samples is highly important. Missing samples can be compensated for by applying conventional missing data restoration methods;however, ensuring that restored samples roughly follow underlying distributions of true missing data remains a challenge. Another strategy involves directly restoring the probability density function (PDF) for a sensor when samples are missing by leveraging distribution information from another sensor with complete data using distribution regression techniques;existing methods include the conventional distribution-to-distribution regression (DDR) and distribution-to-warping function regression (DWR) methods. Due to constraints on PDFs and warping functions, the regression functions of both methods are estimated from the Nadaraya-Watson kernel estimator with relatively low degrees of precision. This article proposes a new indirect distribution-to-distribution regression method in the context of functional data analysis for restoring distributions of missing SHM data. PDFs are transformed to ordinary functions residing in a Hilbert space via the newly proposed log-quantile-density (LQD) transformation;the regression for distributions is realized in the transformed space via a functional regression model constructed based on the theory of Reproducing Kernel Hilbert Space (RKHS), corresponding result is subsequently mapped back to the density space through the inverse LQD transformation. Test results using field monitoring data indicate that the new method significantly outperforms conventional methods in general cases;however, in extrapolation cases, the new method is inferior to the distribution-to-warping function regression method. Copyright © 2018, The Authors. All rights reserved.

关键词： Probability distributions

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