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Time-domain dynamic constitutive model suitable for mucky soil site seismic response

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Earthquake Engineering and Engineering Vibration 2024年第1期23卷 1-13页

作者： Dong Qing Chen Su Jin liguo Zhou zhenghua li Xiaojun Architectural Engineering Institute Huaiyin Institute of TechnologyHuai’an 223600China Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education Beijing University of TechnologyBeijing 100020China Institute of Geophysics China Earthquake AdministrationBeijing 100089China College of Transportation Science and Engineering Nanjing Tech UniversityNanjing 211816China

Soil nonlinear behavior displays noticeable effects on the site seismic response.This study proposes a new functional expression of the skeleton curve to replace the hyperbolic skeleton curve.By integrating shear modulus and combining the dynamic skeleton curve and the damping degradation coefficient,the constitutive equation of the logarithmic dynamic skeleton can be obtained,which considers the damping effect in a soil dynamics problem.Based on the finite difference method and the multi-transmitting boundary condition,a 1D site seismic response analysis program called Soilresp1D has been developed herein and used to analyze the time-domain seismic response in three types of sites.At the same time,this study also provides numerical simulation results based on the hyperbolic constitutive model and the equivalent linear method.The results verify the rationality of the new soil dynamic constitutive model.It can analyze the mucky soil site nonlinear seismic response,reflecting the deformation characteristics and damping effect of the silty soil.The hysteresis loop area is more extensive,and the residual strain is evident.

关键词： seismic response time-domain dynamic constitutive model logarithmic dynamic skeleton dampening effect mucky soil

A novel physics-informed framework for reconstruction of structural defects

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Applied Mathematics and Mechanics(English Edition) 2022年第11期43卷 1717-1730页

作者： Qi li Fushun liU Bin WANG DZliU zhenghua QIAN State Key Laboratory of Mechanics and Control of Mechanical Structures College of Aerospace EngineeringNanjing University of Aeronautics and AstronauticsNanjing 210016China College of Engineering Ocean University of ChinaQingdao 266100Shandong ProvinceChina School of Engineering University of East AngliaNorwich NR47TJU.K.

The ultrasonic guided wave technology plays a significant role in the field of non-destructive testing as it employs acoustic waves with the advantages of high propagation efficiency and low energy consumption during the inspect process.However,the theoretical solutions to guided wave scattering problems with assumptions such as the Born approximation have led to the poor quality of the reconstructed results.Besides,the scattering signals collected from industry sectors are often noised and nonstationary.To address these issues,a novel physics-informed framework(PIF)for the quantitative reconstruction of defects by means of the integration of the data-driven method with the guided wave scattering analysis is proposed in this paper.Based on the geometrical information of defects and initial results obtained by the PIF-based analysis of defect reconstructions,a deep-learning neural network model is built to reveal the physical relationship between the defects and the noisy detection signals.This learning model is then adopted to assess and characterize the defect profiles in structures,improve the accuracy of the analytical model,and eliminate the impact of the noise pollution in the process of inspection.To demonstrate the advantages of the developed PIF for the complex defect reconstructions with the capability of denoising,several numerical examples are carried out.The results show that the PIF has greater accuracy for the reconstruction of defects in the structures than the analytical method,and provides a valuable insight into the development of artificial intelligence(AI)-assisted inspection systems with high accuracy and efficiency in the fields of structural integrity and condition monitoring.

关键词： physics-informed deep-learning reconstruction of defects denoising

Flow characteristics and hot workability of a typical low-alloy high-strength steel during multi-pass deformation

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International Journal of Minerals,Metallurgy and Materials 2024年第2期31卷 323-336页

作者： Mingjie Zhao lihong Jiang Changmin li liang Huang Chaoyuan Sun Jianjun li zhenghua Guo School of Aeronautical Manufacturing Engineering Nanchang Hangkong UniversityNanchang 330063China Jiangxi Key Laboratory of Forming and Joining Technology for Aerospace Components Nanchang Hangkong UniversityNanchang 330063China State Key Laboratory of Materials Processing and Die&Mould Technology School of Materials Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China China National Erzhong Group Deyang Wanhang Die Forging Co.LTD. Deyang 618000China Hubei Huangshi Mold Industrial Technology Research Institute Huangshi 435007China

Heavy components of low-alloy high-strength(LAHS) steels are generally formed by multi-pass forging. It is necessary to explore the flow characteristics and hot workability of LAHS steels during the multi-pass forging process, which is beneficial to the formulation of actual processing parameters. In the study, the multi-pass hot compression experiments of a typical LAHS steel are carried out at a wide range of deformation temperatures and strain rates. It is found that the work hardening rate of the experimental material depends on deformation parameters and deformation passes, which is ascribed to the impacts of static and dynamic softening behaviors. A new model is established to describe the flow characteristics at various deformation passes. Compared to the classical Arrhenius model and modified Zerilli and Armstrong model, the newly proposed model shows higher prediction accuracy with a confidence level of 0.98565. Furthermore, the connection between power dissipation efficiency(PDE) and deformation parameters is revealed by analyzing the microstructures. The PDE cannot be utilized to reflect the efficiency of energy dissipation for microstructure evolution during the entire deformation process, but only to assess the efficiency of energy dissipation for microstructure evolution in a specific deformation parameter state.As a result, an integrated processing map is proposed to better study the hot workability of the LAHS steel, which considers the effects of instability factor(IF), PDE, and distribution and size of grains. The optimized processing parameters for the multi-pass deformation process are the deformation parameters of 1223–1318 K and 0.01–0.08 s^(-1). Complete dynamic recrystallization occurs within the optimized processing parameters with an average grain size of 18.36–42.3 μm. This study will guide the optimization of the forging process of heavy components.

关键词： low-alloy high-strength steel work hardening rate constitutive model hot workability multi-pass deformation

The effect of NiO-Ni_(3)N interfaces in in-situ formed heterostructure ultrafine nanoparticles on enhanced polysulfide regulation in lithium-sulfur batteries

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Journal of Energy Chemistry 2022年第5期31卷 762-770页

作者： Jun Pu zhenghua Wang Pan Xue Kaiping Zhu Jiachen li Yagang Yao Key Laboratory of Functional Molecular Solids Ministry of EducationAnhui Provincial Engineering Laboratory for New-Energy Vehicle Battery Energy-Storage MaterialsCollege of Chemistry and Materials ScienceAnhui Normal UniversityWuhu 241002AnhuiChina National Laboratory of Solid State Microstructures College of Engineering and Applied SciencesJiangsu Key Laboratory of Artificial Functional MaterialsCollaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210093JiangsuChina School of Chemical Engineering Northwest UniversityXi’an 710069ShaanxiChina Division of Nanomaterials and Jiangxi Key Lab of Carbonene Materials Suzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesNanchang 330200JiangxiChina

Inhibiting the “shuttle effect” of soluble polysulfides and improving reaction kinetics are the key factors necessary for further exploration of high-performance li-S batteries. Herein, an effective interface engineering strategy is reported, wherein nitriding of an Ni-based precursor is controlled to enhance li-S cell regulation. The resulting in-situ formed NiO-Ni_(3)N heterostructure interface not only has a stronger polysulfide adsorption effect than that of monomeric NiO or Ni_(3)N but also has a faster li ion diffusion ability than a simple physical mixture. More importantly, this approach couples the respective advantages of NiO and Ni_(3)N to reduce polarization and facilitate electron transfer during polysulfide reactions and synergistically catalyze polysulfide conversion. In addition, ultrafine nanoparticles are thought to effectively improve the use of additive materials. In summary, li-S batteries based on this NiO-Ni_(3)N heterostructure have the features of long cycle stability, rapid charging-discharging, and good performance under high sulfur loading.

关键词： NiO-Ni_(3)N heterostructure Interface effect Ultrafine nanoparticles li-S batteries Polysulfides

Effects of an attached functionally graded layer on the electromechanical behaviors of piezoelectric semiconductor fibers

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Applied Mathematics and Mechanics(English Edition) 2022年第9期43卷 1367-1380页

作者： Kai FANG Nian li Peng li zhenghua QIAN V.KOLESOV I.KUZNETSOVA State Key Laboratory of Mechanics and Control of Mechanical Structures College of Aerospace EngineeringNanjing University of Aeronautics and AstronauticsNanjing 210016China Nanjing University of Aeronautics and Astronautics Shenzhen Research Institute Shenzhen 518057Guangdong ProvinceChina Kotel’nikov Institute of Radio Engineering and Electronics of Russian Academy of Sciences Moscow 125009Russia

In this paper,we propose a specific two-layer model consisting of a functionally graded(FG)layer and a piezoelectric semiconductor(PS)layer.Based on the macroscopic theory of PS materials,the effects brought about by the attached FG layer on the piezotronic behaviors of homogeneous n-type PS fibers and PN junctions are investigated.The semi-analytical solutions of the electromechanical fields are obtained by expanding the displacement and carrier concentration variation into power series.Results show that the antisymmetry of the potential and electron concentration distributions in homogeneous n-type PS fibers is destroyed due to the material inhomogeneity of the attached FG layer.In addition,by creating jump discontinuities in the material properties of the FG layer,potential barriers/wells can be produced in the middle of the fiber.Similarly,the potential barrier configuration near the interface of a homogeneous PS PN junction can also be manipulated in this way,which offers a new choice for the design of PN junction based devices.

关键词： piezoelectric semiconductor(PS) functionally graded(FG)material composite structure PN junction

Position Encoding Based Convolutional Neural Networks for Machine Remaining Useful life Prediction

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IEEE/CAA Journal of Automatica Sinica 2022年第8期9卷 1427-1439页

作者： Ruibing Jin Min Wu Keyu Wu Kaizhou Gao zhenghua Chen Xiaoli li Institute for Infocomm Research Agency for ScienceTechnology and Research(A*STAR)Singapore 138632Singapore School of Computer Science Liaocheng UniversityLiaocheng 252000 Macao Institute of System Engineering Macao University of Science and TechnologyTaipaMacao 999078China

Accurate remaining useful life(RUL)prediction is important in industrial systems.It prevents machines from working under failure conditions,and ensures that the industrial system works reliably and efficiently.Recently,many deep learning based methods have been proposed to predict RUL.Among these methods,recurrent neural network(RNN)based approaches show a strong capability of capturing sequential information.This allows RNN based methods to perform better than convolutional neural network(CNN)based approaches on the RUL prediction task.In this paper,we question this common paradigm and argue that existing CNN based approaches are not designed according to the classic principles of CNN,which reduces their performances.Additionally,the capacity of capturing sequential information is highly affected by the receptive field of CNN,which is neglected by existing CNN based methods.To solve these problems,we propose a series of new CNNs,which show competitive results to RNN based methods.Compared with RNN,CNN processes the input signals in parallel so that the temporal sequence is not easily determined.To alleviate this issue,a position encoding scheme is developed to enhance the sequential information encoded by a CNN.Hence,our proposed position encoding based CNN called PE-Net is further improved and even performs better than RNN based methods.Extensive experiments are conducted on the C-MAPSS dataset,where our PE-Net shows state-of-the-art performance.

关键词： Convolutional neural network(CNN) deep learning position encoding remaining useful life prediction

Dissecting pathophysiology of a human dominantly inherited disease, familial amyloidotic polyneuropathy, by using genetically engineered mice

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Frigid Zone Medicine 2022年第2期2卷 65-75页

作者： zhenghua li Kenichi Yamamura Department of Histology and Embryology Harbin Medical UniversityHarbin 150081China Institute of Resource Development and Analysis Kumamoto UniversityKumamoto 860-0811Japan TransGenic Inc.Fukuoka 810-0001Japan

Familial amyloidotic polyneuropathy(FAP)is a type of systemic amyloidosis characterized by peripheral and autonomic neuropathy.Although FAP is a typical autosomal dominant disorder caused by a point mutation in the TTR gene,the average age at onset varies significantly among different countries.This discrepancy clearly suggests that a combination of intrinsic factors as well as extrinsic(environmental)factors shapes the development of FAP.However,these factors are difficult to analyze in humans,because detailed pathologic tissue analysis is only possible at autopsy.Thus,mouse models have been produced and used to disentangle these factors.This review covers the mouse models produced thus far and how these models are applied to analyze intrinsic and extrinsic factors involved in disease development and to test drug efficacy.

关键词： amyloid polyneuropathy neuropathy

A More Accurate Reconstruction Method for Detecting Large-Depth Defects in Plates Using SH Guided Waves

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Acta Mechanica Solida Sinica 2021年第2期34卷 174-183页

作者： Yihui Da Qi li Bin Wang Dianzi liu zhenghua Qian State Key Laboratory of Mechanics and Control of Mechanical Structures College of Aerospace EngineeringNanjing University of Aeronautics and AstronauticsNanjing210016China School of Engineering University of East AngliaNorwich NR47TJUK

The inspection of thickness thinning defects and corrosion defects is greatly significant for the health prediction of plate structures.The main aim of this research is to propose a novel and effective approach to achieve the accurate and rapid detection of arbitrary defects using shear horizontal(SH)guided waves,particularly for large-depth and complex defects.The proposed approach combines the quantitative detection of Fourier transform with a reference model-based strategy to improve the accuracy of large-depth defect detection.Since the shallow defect profile is theoretically constructed by inverse Fourier transform of the product of reflection coefficients and integral coefficients of reference models,the unknown large-depth defect can be initially assessed using the relevant information from a predefined reference model.By iteratively updating the integral coefficients of reference models,the accuracy of reconstruction of large-depth defects is much improved.To achieve the converged defect profile,a termination criterion,the root mean square error,is applied to guarantee the construction of defects with a high level of accuracy.Moreover,the hybrid finite element method is used to simulate the propagation of SH guided waves in plates for calculating the reflection coefficients of plates with defects.Finally,to demonstrate the capability of the developed reconstruction method for defect detection in terms of accuracy and efficiency,three types of large-depth defect profiles,i.e.,a rectangular flaw,a double-rectangular flaw and a complex flaw,are examined.Results show that the discrepancy between the predicted defect profile and the real one is quite small,even in the largest-depth defect case where the defect depth is equal to 0.733 times the plate thickness,the minimal difference is observed.It is noted that the fast convergence of the proposed approach can be achieved by no more than ten updates for the worst case.

关键词： Large-depth defect SH guided wave Iterative strategy Reference model Hybrid FEM

EFFECTS OF NONliNEARITY ON TRANSIENT PROCESSES IN AT-CUT QUARTZ THICKNESS-SHEAR RESONATORS

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Acta Mechanica Solida Sinica 2015年第4期28卷 347-352页

作者： Nian li zhenghua Qian Jiashi Yang State Key Laboratory of Mechanics and Control of Mechanical Structures College of Aerospace EngineeringNanjing University of Aeronautics and Astronautics Department of Mechanical and Materials Engineering University of Nebraska-Lincoln

We study the effects of mechanical nonlinearity arising from large thickness-shear deformation on the transient process of an AT-cut quartz plate resonator. Mindlin＇s two-dimensional plate equation is used, from which a system of first-order nonlinear differential equations governing the evolution of the vibration amplitude is obtained. Numerical solutions by the Runge-Kutta method show that in common operating conditions of quartz resonators the nonlinear effect varies from noticeable to significant. As resonators are to be made smaller and thinner in the future with about the same power requirement, nonlinear effects will become more important and need more understanding and consideration in resonator design.

关键词： quarts resonator thickness-shear mode transient processes nonlinear effect Mindlin＇splate equation