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Numerical manifold method for steady-state nonlinear heat conduction using Kirchhoff transformation

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Science China(Technological Sciences) 2024年第4期67卷 992-1006页

作者： zhang LiMei KONG heng Zheng Hong Key Laboratory of Urban Security and Disaster Engineering Ministry of EducationBeijing University of TechnologyBeijing 100124China Beijing Municipal Construction Co. Ltd.Beijing 100048China

The numerical manifold method(NMM)introduces the mathematical and physical cover to solve both continuum and discontinuum problems in a unified manner.In this study,the NMM for solving steady-state nonlinear heat conduction problems is presented,and heat conduction problems consider both convection and radiation boundary conditions.First,the nonlinear governing equation of thermal conductivity,which is dependent on temperature,is transformed into the Laplace equation by introducing the Kirchhoff transformation.The transformation reserves linearity of both the Dirichlet and the Neumann boundary conditions,but the Robin and radiation boundary conditions remain nonlinear.Second,the NMM is employed to solve the Laplace equation using a simple iteration procedure because the nonlinearity focuses on parts of the problem domain boundaries.Finally,the temperature field is retrieved through the inverse Kirchhoff transformation.Typical examples are analyzed,demonstrating the advantages of the Kirchhoff transformation over the direct solution of nonlinear equations using the NewtonRaphson method.This study provides a new method for calculating nonlinear heat conduction.

关键词： numerical manifold method nonlinear heat conduction temperature-dependent thermal conductivity Kirchhoff transformation convection and radiation boundary conditions

Resilience-oriented Transmission Expansion Planning with Optimal Transmission Switching Under Typhoon Weather

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 129-138页

作者： Yang Yuan heng zhang Haozhong Cheng Zheng Wang Key Laboratory of Control of Power Transmission and Conversion Ministry of EducationElectrical Engineering DepartmentShanghai Jiao Tong UniversityShanghaiChina State Grid East China Branch ShanghaiChina

This paper presents resilience-oriented transmission expansion planning(RTEP)with optimal transmission switching(OTS)model under typhoon weather.The proposed model carefully considers the uncertainty of component vulnerability by constructing a typhoon-related box uncertainty set where component failure rate varies within a range closely related with typhoon intensity.Accordingly,a min-max-min model is developed to enhance transmission network resilience,where the upper level minimizes transmission lines investment,the middle level searches for the probability distribution of failure status leading to max worst-case expected load-shedding(WCEL)under typhoon,and the lower level optimizes WCEL by economic dispatch(ED)and OTS.A nested decomposition algorithm based on benders decomposition is developed to solve the model.Case studies of modified IEEE 30-bus and 261-bus system of a Chinese region illustrate that:a)the proposed RTEP method can enhance resilience of transmission network with less investment than widely used RTEP method based on attacker and defender(DAD)model,b)the influence of OTS on RTEP is closely related with contingency severity and system scale and c)the RTEP model can be efficiently solved even in a large-scale system.

关键词： Decomposition algorithm optimal transmission switching resilience transmission expansion planning uncertainty vulnerability

Monogamy and polygamy for the generalized W-class states using unified-(q,s)entropy

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Science China(Physics,Mechanics & Astronomy) 2024年第1期67卷 10-22页

作者： Bo Li Bing Xie Zhanjun zhang heng Fan School of Computer and Computing Science Hangzhou City UniversityHangzhou 310015China Department of Mathematics East China University of TechnologyNanchang 330013China School of Information&Electronic Engineering(Sussex Artificial Intelligence Institute) Zhejiang Gongshang UniversityHangzhou 310018China Institute of Physics Chinese Academy of SciencesBeijing 100190China

We describe the entanglement distribution and restricted shareability of the multipartite generalized W-class states and their reduced density matrix under arbitrary partitions by using monogamy and polygamy relation based on the unified-(q,s)entropy.Firstly,we provide an analytical formula of unified-(q,s)entanglement(UE)and an analytical lower bound of unified-(q,s)entanglement of assistance(UEo A)for a reduced density matrix of a generalized W-class state.Then,we use these two analytical formulas to derive the monogamy and polygamy inequalities for a reduced density matrix of a qudit generalized W-class(GW)state.We establish two partition-dependent residual entanglements based on the new monogamy relation,which is helpful to obtain a comprehensive analysis of entanglement dynamics of generalized W-class states.Further,we investigate tighter monogamy and polygamy relations based on the power ofαth(α≥0)for UE andβth(β≥0)for UEo A,respectively.The results show that the entanglement distribution characteristics of generalized W-class states satisfying stronger constraints can be described more accurately.

关键词： monogamy polygamy multiqudit unified entropy

A Novel On-Site-Real-Time Method for Identifying Characteristic Parameters Using Ultrasonic Echo Groups and Neural Network

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Chinese Journal of Mechanical Engineering 2024年第1期37卷 215-228页

作者： Shuyong Duan Jialin zhang heng Ouyang Xu Han Guirong Liu State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of TechnologyTianjin 300401China Department of Aerospace Engineering and Engineering Mechanics University of CincinnatiCincinnati 45221USA

On-site and real-time non-destructive measurement of elastic constants for materials of a component in a in-service structure is a challenge due to structural complexities,such as ambiguous boundary,variable thickness,nonuniform material properties.This work develops for the first time a method that uses ultrasound echo groups and artificial neural network(ANN)for reliable on-site real-time identification of material parameters.The use of echo groups allows the use of lower frequencies,and hence more accommodative to structural complexity.To train the ANNs,a numerical model is established that is capable of computing the waveform of ultrasonic echo groups for any given set of material properties of a given structure.The waveform of an ultrasonic echo groups at an interest location on the surface the structure with material parameters varying in a predefined range are then computed using the numerical model.This results in a set of dataset for training the ANN model.Once the ANN is trained,the material parameters can be identified simultaneously using the actual measured echo waveform as input to the ANN.Intensive tests have been conducted both numerically and experimentally to evaluate the effectiveness and accuracy of the currently proposed method.The results show that the maximum identification error of numerical example is less than 2%,and the maximum identification error of experimental test is less than 7%.Compared with currently prevailing methods and equipment,the proposefy the density and thickness,in addition to the elastic constants.Moreover,the reliability and accuracy of inverse prediction is significantly improved.Thus,it has broad applications and enables real-time field measurements,which has not been fulfilled by any other available methods or equipment.

关键词： Parameter identification Ultrasonic echo group High-precision modeling Artificial neural network NDT

Porous nanofibrous dressing enables mesenchymal stem cell spheroid formation and delivery to promote diabetic wound healing

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Chinese Journal of Chemical Engineering 2024年第4期68卷 156-164页

作者： Kexin zhang Wenmin zhang heng An Zhe Huang Yanzhen Wen Xiangyu Jiao Yongqiang Wen College of Chemical Engineering and Technology Taiyuan University of Science and TechnologyTaiyuan 030024China Beijing Key Laboratory for Bioengineering and Sensing Technology Daxing Research InstituteSchool of Chemistry&Biological EngineeringUniversity of Science&Technology BeijingBeijing 100083China

Delayed and nonhealing of diabetic wounds imposes substantial economic burdens and physical pain on patients.Mesenchymal stem cells(MSCs)promote diabetic wound healing.Particularly when MSCs aggregate into multicellular spheroids,their therapeutic effect is enhanced.However,traditional culture platforms are inadequate for the efficient preparation and delivery of MSC spheroids,resulting in inefficiencies and inconveniences in MSC spheroid therapy.In this study,a three-dimensional porous nanofibrous dressing(NFD)is prepared using a combination of electrospinning and homogeneous freeze-drying.Using thermal crosslinking,the NFD not only achieves satisfactory elasticity but also maintains notable cytocompatibility.Through the design of its structure and chemical composition,the NFD allows MSCs to spontaneously form MSC spheroids with controllable sizes,serving as MSC spheroid delivery systems for diabetic wound sites.Most importantly,MSC spheroids cultured on the NFD exhibit improved secretion of vascular endothelial growth factor,basic fibroblast growth factor,and hepatocyte growth factor,thereby accelerating diabetic wound healing.The NFD provides a competitive strategy for MSC spheroid formation and delivery to promote diabetic wound healing.

关键词： Electrospinning Homogenization Biomedical engineering Nanomaterials Stem cell spheroids Diabetic wound healing

Unified method for typical gear failure modeling and stiffness calculation based on the matrix equation

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Frontiers of Mechanical Engineering 2024年第3期19卷 93-114页

作者： Fanshan MENG Xin zhang heng XIA Jiaxu WANG School of Mechanical Engineering Southwest Jiaotong UniversityChengdu 610031China State Key Laboratory of Mechanical Transmissions for Advanced Equipment Chongqing UniversityChongqing 400044China

The failure types in gear systems vary,with typical ones mainly including pitting,cracking,wear,and broken teeth.Different modeling and stiffness calculation methods have been developed for various gear failure types.A unified method for typical gear failure modeling and stiffness calculation is introduced in this study by considering the deviations in the time-varying meshing stiffness(TVMS)of faulty gears resulting from the use of different methods.Specifically,a gear tooth is discretized into a large number of microelements expressed with a matrix,and unified models of typical gear failures are built by adjusting the values of the matrix microelements.The values and positions of the microelements in the tooth failure model matrix have the same physical meaning as the parameter variables in the potential energy method(PEM),so the matrix-based failure model can be perfectly matched with PEM.Afterward,a unified method for TVMS is established.Modeling of healthy and faulty gears with pitting,wear,crack,and broken tooth is performed with the matrix equation,and the corresponding TVMS values are calculated by incorporating the matrix models with PEM.On the basis of the results,the mechanism of typical fault types that affect TVMS is analyzed,and the conclusions are verified through the finite element method.The developed unified method is a promising technique for studying the dynamic response characteristics of gear systems with different failure types because of its superiority in eliminating stiffness deviations.

关键词： gears matrix equation failure modeling TVMS calculation unified method

Identification and validation of novel prognostic fatty acid metabolic gene signatures in colon adenocarcinoma through systematic approaches

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Oncology Research 2024年第2期32卷 297-308页

作者： heng zhang WENJING Cheng HAIBO ZHAO WEIDONG CHEN QIUJIE zhang QING-QING YU Department of Laboratory Shandong Daizhuang HospitalJining272051China Jining No.1 People’s Hospital Shandong First Medical UniversityJining272000China

Colorectal cancer(CRC)belongs to the class of significantly malignant tumors found in humans.Recently,dysregulated fatty acid metabolism(FAM)has been a topic of attention due to its modulation in cancer,specifically CRC.However,the regulatory FAM pathways in CRC require comprehensive elucidation.Methods:The clinical and gene expression data of 175 fatty acid metabolic genes(FAMGs)linked with colon adenocarcinoma(COAD)and normal cornerstone genes were gathered through The Cancer Genome Atlas(TCGA)-COAD corroborating with the Molecular Signature Database v7.2(MSigDB).Initially,crucial prognostic genes were selected by uni-and multi-variate Cox proportional regression analyses;then,depending upon these identified signature genes and clinical variables,a nomogram was generated.Lastly,to assess tumor immune characteristics,concomitant evaluation of tumor immune evasion/risk scoring were elucidated.Results:A 8-gene signature,including ACBD4,ACOX1,CD36,CPT2,ELOVL3,ELOVL6,ENO3,and SUCLG2,was generated,and depending upon this,CRC patients were categorized within high-risk(H-R)and low-risk(L-R)cohorts.Furthermore,risk and age-based nomograms indicated moderate discrimination and good calibration.The data confirmed that the 8-gene model efficiently predicted CRC patients’prognosis.Moreover,according to the conjoint analysis of tumor immune evasion and the risk scorings,the H-R cohort had an immunosuppressive tumor microenvironment,which caused a substandard prognosis.Conclusion:This investigation established a FAMGs-based prognostic model with substantially high predictive value,providing the possibility for improved individualized treatment for CRC individuals.

关键词： Fatty acid metabolism Colorectal cancer Gene signatures Machine learning

Spatiotemporal transformable nano-assembly for on-demand drug delivery to enhance anti-tumor immunotherapy

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Asian Journal of Pharmaceutical Sciences 2024年第1期19卷 103-118页

作者： Chenglin Liang Ge zhang Linlin Guo Xinyi Ding heng Yang Hongling zhang Zhenzhong zhang Lin Hou School of Pharmaceutical Sciences Key Laboratory of Targeting Therapy and Diagnosis for Critical DiseasesZhengzhou UniversityZhengzhou 450001China

Induction of tumor cell senescence has become a promising strategy for anti-tumor immunotherapy,but fibrotic matrix severely blocks senescence inducers penetration and immune cells infiltration.Herein,we designed a cancer-associated fibroblasts(CAFs)triggered structure-transformable nano-assembly(HSD-P@V),which can directionally deliver valsartan(Val,CAFs regulator)and doxorubicin(DOX,senescence inducer)to the specific targets.In detail,DOX is conjugated with hyaluronic acid(HA)via diselenide bonds(Se-Se)to form HSD micelles,while CAFs-sensitive peptide is grafted onto the HSD to form a hydrophilic polymer,which is coated on Val nanocrystals(VNs)surface for improving the stability and achieving responsive release.Once arriving at tumor microenvironment and touching CAFs,HSD-P@V disintegrates into VNs and HSD micelles due to sensitive peptide detachment.VNs can degrade the extracellularmatrix,leading to the enhanced penetration of HSD.HSD targets tumor cells,releases DOX to induce senescence,and recruits effector immune cells.Furthermore,senescent cells are cleared by the recruited immune cells to finish the integrated anti-tumor therapy.In vitro and in vivo results show that the nanoassembly remarkably inhibits tumor growth as well as lungmetastasis,and extends tumorbearing mice survival.This work provides a promising paradigm of programmed delivering multi-site nanomedicine for cancer immunotherapy.

关键词： Cells senescence Tumor stroma Structure transformable Programmed delivery Anti-tumor immunotherapy

Nonlinear Registration of Brain Magnetic Resonance Images with Cross Constraints of Intensity and Structure

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Computers, Materials & Continua 2024年第5期79卷 2295-2313页

作者： Han Zhou HongtaoXu Xinyue Chang Wei zhang heng Dong Digital Fujian Research Institute of Big Data forAgriculture and Forestry Fujian Agriculture and Forestry UniversityFuzhou350002China College of Computer and Information Science Fujian Agriculture and Forestry UniversityFuzhou350002China

Many deep learning-based registration methods rely on a single-stream encoder-decoder network for computing deformation fields between 3D volumes.However,these methods often lack constraint information and overlook semantic consistency,limiting their performance.To address these issues,we present a novel approach for medical image registration called theDual-VoxelMorph,featuring a dual-channel cross-constraint network.This innovative network utilizes both intensity and segmentation images,which share identical semantic information and feature representations.Two encoder-decoder structures calculate deformation fields for intensity and segmentation images,as generated by the dual-channel cross-constraint network.This design facilitates bidirectional communication between grayscale and segmentation information,enabling the model to better learn the corresponding grayscale and segmentation details of the same anatomical structures.To ensure semantic and directional consistency,we introduce constraints and apply the cosine similarity function to enhance semantic consistency.Evaluation on four public datasets demonstrates superior performance compared to the baselinemethod,achieving Dice scores of 79.9%,64.5%,69.9%,and 63.5%for OASIS-1,OASIS-3,LPBA40,and ADNI,respectively.

关键词： Medical image registration cross constraint semantic consistency directional consistency dual-channel