An inverse analysis of fluid flow through granular media using differentiable lattice Boltzmann method

This study presents a method for the inverse analysis of fluid flow problems.The focus is put on accurately determining boundary conditions and characterizing the physical properties of granular media,such as permeability,and fluid components,like viscosity.The primary aim is to deduce either constant pressure head or pressure profiles,given the known velocity field at a steady-state flow through a conduit containing obstacles,including walls,spheres,and grains.The lattice Boltzmann method(LBM)combined with automatic differentiation(AD)(AD-LBM)is employed,with the help of the GPU-capable Taichi programming language.A lightweight tape is used to generate gradients for the entire LBM simulation,enabling end-to-end backpropagation.Our AD-LBM approach accurately estimates the boundary conditions for complex flow paths in porous media,leading to observed steady-state velocity fields and deriving macro-scale permeability and fluid viscosity.The method demonstrates significant advantages in terms of prediction accuracy and computational efficiency,making it a powerful tool for solving inverse fluid flow problems in various applications.

Novel thick-target inverse kinematics method for the astrophysical ^(12)C+^(12)C fusion reaction

The ^(12)C+^(12)C fusion is one of the most important reactions in modern nuclear astrophysics.The trend and magnitude of the reaction rate within the Gamow window strongly influence various astrophysical processes.However,direct measurement of this reaction is extremely difficult,which makes it necessary to develop indirect methods.In this study,the ^(23)Na+p reaction system was used to study the compound nucleus ^(24)Mg.We employed a thick-target inverse kinematics method combined with the-charged-particle coincidence technique to measure the proton andexit channels of ^(24)Mg.Technical details of the ^(23)Na+p thick-target inverse kinematics experiment and analysis are presented herein.

A Two-step Inverse Method for Quantitative Damage Evaluation of Plate-like Structures Using Vibration Approach

This study presents a novel two-step approach to assess plate-like structural laminar damages,particularly for delamination damage detection of composite structures.Firstly,a 2-D continuous wavelet transform is employed to identify the damage location and sizes from vibration curvature data.An inverse method is subsequently then used to determine the bending stiffness reduction ratio along a specified direction,enabling the quantification of the delamination severity.The method employed in this study is an extension of the one-dimensional inverse method developed in a previous work of the authors.The applicability of the two-step inverse approach is demonstrated in a simulation analysis and by an experimental study on a cantilever composite plate containing a single delamination.The inverse method is shown to have the capacity to reveal the detailed damage information of delamination within a constrained searching space and can be used to determine the effective flexural stiffness of composite plate structures,even in cases of complex delamination damage.

基于DEMATEL-ISM方法的水电站机组检修作业安全事故致因链分析

针对水电站机组检修作业种类和危险因素多、安全事故频发等问题,通过文献挖掘与专家访谈方式,对水电站机组检修作业安全影响因素类别进行了划分。基于DEMATEL-ISM方法,构建了安全事故致因多层次递阶ISM模型来确定事故致因因素层级,通过剖析事故致因因素的中心度和权重,挖掘关键致因因素和推求事故致因链的路径权重,厘定关键致因链。采用该模型对某水电站致因链进行了分析,结果表明,安全检查不到位为关键致因因素,“安全检查不到位→违规作业→设备的问题→粉尘、油漆等有害物质”为关键致因链。

基于ISM-SD的地下洞室群施工进度风险传递路径研究

针对水电工程地下洞室群施工进度风险存在传递问题,提出了基于解释结构模型(ISM)和系统动力学(SD)的地下洞室群施工进度风险传递路径分析方法。根据地下洞室群的施工特点,建立了地下洞室群施工进度风险指标体系;结合风险传递机理,运用解释结构模型分析风险因素间传递关系,建立了风险因素传递矩阵,并总结归纳出风险因素关系对照表,通过系统动力学分析风险因素间传递路径,揭示了施工进度风险传递路径网络;集成ISM-SD构建了地下洞室群施工进度风险传递路径分析模型,并结合西南地区某大型水电站地下洞室群工程进行分析。结果表明,该方法可有效识别施工进度风险重要因素和关键传递路径,为地下洞室群施工进度风险管理提供了决策依据。

基于DEMATEL-ISM-ANP的城市应急供应链韧性综合评价研究——以郑州市口粮应急供应链为例

为提高城市应急供应链韧性,通过构建城市应急供应链韧性的概念模型,以郑州市口粮应急供应链为例,从基础设施、治理组织、情报信息三大影响因素出发,综合运用决策试验与评价实验室(DEMATEL)、解释结构模型(ISM)和网络层次分析(ANP)方法识别关键影响因素,明确各影响因素之间的作用路径,对城市口粮应急供应链韧性进行综合评价。结果表明,郑州市口粮应急供应链整体韧性值为0.372,基础设施网络与情报信息网络的韧性值分别为0.292和0.282,总体韧性水平仍有较大提升空间。基于此,从优化口粮应急基础设施、加强情报信息平台建设和提升组织机构应急治理能力等方面提出城市口粮应急供应链韧性提升的建议。

突发公共卫生事件背景下城市社区韧性水平的影响因素研究——基于ISM-MICMAC的方法

目的:本研究将关注点聚焦于城市社区内部,通过识别突发公共卫生事件中影响社区韧性的关键因素和因素间的相互关系,为如何保证城市社区韧性的持续内驱力、提升社区韧性水平提出建议。方法:运用ISM-MICMAC方法探究影响因素的内在层次性和各因素的驱动力和依赖性,对影响因素进行分类,进一步探究因素间的影响路径。结果与结论:研究发现社会资本、居民参与水平、社区自治能力、社区组织再造是影响突发公共卫生事件中社区韧性水平的根本因素,并且具有较高的驱动力。基于此,本文从组织、物理、技术三个方面提出了提升社区韧性水平的建议。

基于24Model-D-ISM的地铁站火灾疏散影响因素研究

为预防地铁站火灾事故,深入了解地铁站火灾人员疏散影响因素间的内在联系与层次结构,基于第6版“2-4”模型(24Model)分析63起地铁站火灾疏散事故,充分考虑各个因素之间的交互作用,提取19个影响地铁站人员疏散的关键因素,建立地铁站火灾人员疏散影响因素指标体系;采用算子客观赋权法(C-OWA)改进决策试验与评价实验法(DEMATEL),确定地铁站火灾人员疏散的重要影响因素;在此基础上,采用解释结构模型(ISM)分析各个因素间的层次结构及相互作用路径,构建地铁站火灾人员疏散影响因素的多级递阶结构模型。研究结果表明:疏散引导、恐慌从众行为、人员拥挤为地铁站火灾人员疏散的关键影响因素;地铁站火灾人员疏散受表层因素、中间层因素、深层因素共同作用的影响,其中,疏散教育与培训、设施维护与检查、疏散预案等因素是根源影响因素,重视根源影响因素的改善有利于从本质上预防和控制事故的发生。

基于改进DEMATEL-ISM模型的道路拥堵下行车风险评估方法

为准确识别城市道路拥堵条件下的行车风险系统中各影响因素之间的内在联系以及该系统中的关键因素,本文提出一种改进DEMATEL-ISM的评估方法。首先,分析城市道路拥堵条件下的行车风险,选取18个风险因子;其次,运用多群体问询的调查问卷方法,并结合最大类间方差法对标准的集成决策试验和评价试验室(DEMATEL)以及解释结构模型(ISM)改进,建立城市道路拥堵的行车风险评估模型。最后,实例验证结果表明:基于改进DEMATEL-ISM模型的道路拥堵条件下行车风险评估体系能准确划分层次解释结构图的层级,与其他方法相比更加符合实际;交通密度、车头时距、停车次数、换道频次等关键链接因素对其他因素有较强联动影响,并且会增加发生交通事故或二次交通拥堵的概率。

Nonlinear system compound inverse control method

A compound neural network is utilized to identify the dynamic nonlinear system. This network is composed of two parts： one is a linear neural network, and the other is a recurrent neural network. Based on the inverse theory a compound inverse control method is proposed. The controller has also two parts： a linear controller and a nonlinear neural network controller. The stability condition of the closed-loop neural network-based compound inverse control system is demonstrated .based on the Lyapunov theory. Simulation studies have shown that this scheme is simple and has good control accuracy and robustness.

基于改进DEMATEL—ISM法的地铁司机人因失误致因链分析

为提高地铁司机在行车作业过程中的人因可靠性,保障地铁行车安全,结合地铁司机正线行车作业特点,确定15个地铁司机人因失误致因因素,通过引入熵权法,对决策实验室分析法—解释结构模型法(DEMATEL-ISM法)进行改进,并建立地铁司机失误致因因素递阶结构模型,确定关键致因链。研究结果表明:失误致因因素递阶结构模型为六层,地铁司机人因失误致因链共36条,其中“紧急情况的辨别—信息通报的及时准确—调度命令的理解及执行—掌握列车操作步骤—完成清客作业—正确完成出退勤工作”为关键致因链,紧急情况的辨别是最根本的致因因素。研究结果可为地铁司机人因失误管控、制定现场操作规范提供参考依据。

基于DEMATEL-ISM-MICMAC法的生鲜农产品供应链韧性提升关键影响因素研究

高韧性的供应链是保障生鲜农产品有效供给和价值实现的关键。文章采用德尔菲法提炼生鲜农产品供应链韧性提升关键影响因素,采用DEMATEL-ISM-MICMAC法进行分析。结果表明:生鲜农产品供应链韧性提升关键因素分为高驱动性因素与高相关性因素,分别是安全文化、财务实力、组织学习能力与人力资源素质、生鲜行业技术水平、知识获取能力。最后针对这两类关键因素为生鲜农产品供应链韧性的提升提出具体建议。

Piecewise Acoustic Source Imaging with Unknown Speed of Sound Using a Level-Set Method

We investigate the following inverse problem:starting from the acoustic wave equation,reconstruct a piecewise constant passive acoustic source from a single boundary temporal measurement without knowing the speed of sound.When the amplitudes of the source are known a priori,we prove a unique determination result of the shape and propose a level set algorithm to reconstruct the singularities.When the singularities of the source are known a priori,we show unique determination of the source amplitudes and propose a least-squares fitting algorithm to recover the source amplitudes.The analysis bridges the low-frequency source inversion problem and the inverse problem of gravimetry.The proposed algorithms are validated and quantitatively evaluated with numerical experiments in 2D and 3D.

基于改进ISM-FRAM-AHP的有限空间作业过程风险防控

为解决有限空间作业过程多层次、多环节、多功能交互关系模糊和不良耦合影响的问题,引入功能共振分析模型(FRAM),结合解释结构模型(ISM)和层次分析法(AHP)优化改进层次结构和判断方式,通过划分风险层次结构,将系统功能耦合变异性的影响进行定量化,并计算功能单元和层级结构的重要度,通过功能可变性和耦合损失度结果,确定上下游功能变化输入输出表型,理清系统功能要素间耦合作用影响机制。结果表明:应用基于改进ISM-FRAM-AHP的有限空间作业过程风险防控模型,能够得到23个功能单元和10层风险层级功能网络;功能可变性数值和耦合损失度最大值为4.36(外部环境F_(23))和0.8084(制定作业方案F_(2)),作业安全风险程度较高,功能变化主要表现为顺序、目标和控制,针对8条失效链路设置物理、象征、功能、隐形4种有效屏障措施。

An Effective Meshless Approach for Inverse Cauchy Problems in 2D and 3D Electroelastic Piezoelectric Structures

In the past decade,notable progress has been achieved in the development of the generalized finite difference method(GFDM).The underlying principle of GFDM involves dividing the domain into multiple sub-domains.Within each sub-domain,explicit formulas for the necessary partial derivatives of the partial differential equations(PDEs)can be obtained through the application of Taylor series expansion and moving-least square approximation methods.Consequently,the method generates a sparse coefficient matrix,exhibiting a banded structure,making it highly advantageous for large-scale engineering computations.In this study,we present the application of the GFDM to numerically solve inverse Cauchy problems in two-and three-dimensional piezoelectric structures.Through our preliminary numerical experiments,we demonstrate that the proposed GFDMapproach shows great promise for accurately simulating coupled electroelastic equations in inverse problems,even with 3%errors added to the input data.

Inversion method of deflection of the vertical based on SWOT wide-swath altimeter data

The deflection of the vertical(DOV)is the key information in the study of ocean gravity field.However,in most areas,the precision of the prime component of DoV is significantly lower than that of the meridian component.To obtain higher accuracy and resolution of ocean gravity information,researchers have proposed a novel altimeter called the wide-swath altimeter.This altimeter allows for the simultaneous acquisition of high-precision and high-resolution two-dimensional measurements of sea surface height(SSH).In this paper,the Surface Water and Ocean Topography(SWOT)mission with a wide-swath altimeter on board is selected for research.One cycle of swoT sea surface height data is simulated to inverse the DOV in the Arabian Sea(45°E—80°E,0°-30°N),and the inversion results are compared with those of conventional altimeter data.The results demonstrate that the difference between the meridian and prime components derived from the inversion of swoT wide-swath data is minimal,significantly outperforming the inversion results of conventional nadir altimeter data.The advantage of swoT wide-swath altimeter lies in its ability to use the multi-directional geoid slope at any sea surface measurement point to invert the components in the meridian and prime directions.To investigate the impact of this advantage on inversion precision,this paper employs a method to calculate the gradient of the geoid in multiple directions to invert DoV components.The improvement effect of calculating the gradient of the geoid in multiple directions on the precision of DoV component is analyzed.It is found that the accuracy of DoV inversion has significantly improved with the increase of geodetic gradient calculation direction.In addition,the effects of various errors and grid spacing in SwoT wide sea surface height data on the precision of Dov inversion are also analyzed.

基于DEMATEL-ISM-MICMAC法的“村BA”发展影响因素研究

“村BA”成功“出圈”的背后受多维度因素的综合影响。明确推动“村BA”发展的关键因素对于分析不同地区“村BA”发展模式和路径具有重要意义。DEMATEL—ISM—MICMAC相结合的研究方法可对影响“村BA”发展的因素进行量化研究。运用DEMATEL法对4个维度中各指标的影响关系进行分析,再通过ISM—MICMAC法划分出层级关系和驱动力—依赖度关系。结果表明,通过对中心度和原因度综合分析,得出“村BA”发展的关键影响因素为民族文化、鲜明地域特色、村镇企业捐赠、篮球历史底蕴和资金技术投入。民族文化和鲜明地域特色驱动力最强,位于ISM结构底层,对其他因素影响最明显,是影响“村BA”发展的本质因素;篮球历史底蕴和乡村居民体育素养依赖度最强,位于ISM结构上层,容易受到其他因素的影响,是影响“村BA”发展的直接因素。

Inverse reliability analysis and design for tunnel face stability considering soil spatial variability

The traditional deterministic analysis for tunnel face stability neglects the uncertainties of geotechnical parameters,while the simplified reliability analysis which models the potential uncertainties by means of random variables usually fails to account for soil spatial variability.To overcome these limitations,this study proposes an efficient framework for conducting reliability analysis and reliability-based design(RBD)of tunnel face stability in spatially variable soil strata.The three-dimensional(3D)rotational failure mechanism of the tunnel face is extended to account for the soil spatial variability,and a probabilistic framework is established by coupling the extended mechanism with the improved Hasofer-Lind-Rackwits-Fiessler recursive algorithm(iHLRF)as well as its inverse analysis formulation.The proposed framework allows for rapid and precise reliability analysis and RBD of tunnel face stability.To demonstrate the feasibility and efficacy of the proposed framework,an illustrative case of tunnelling in frictional soils is presented,where the soil's cohesion and friction angle are modelled as two anisotropic cross-correlated lognormal random fields.The results show that the proposed method can accurately estimate the failure probability(or reliability index)regarding the tunnel face stability and can efficiently determine the required supporting pressure for a target reliability index with soil spatial variability being taken into account.Furthermore,this study reveals the impact of various factors on the support pressure,including coefficient of variation,cross-correlation between cohesion and friction angle,as well as autocorrelation distance of spatially variable soil strata.The results also demonstrate the feasibility of using the forward and/or inverse first-order reliability method(FORM)in high-dimensional stochastic problems.It is hoped that this study may provide a practical and reliable framework for determining the stability of tunnels in complex soil strata.

An empirical method for joint inversion of wave and wind parameters based on SAR and wave spectrometer data

Synthetic aperture radar(SAR)and wave spectrometers,crucial in microwave remote sensing,play an essential role in monitoring sea surface wind and wave conditions.However,they face inherent limitations in observing sea surface phenomena.SAR systems,for instance,are hindered by an azimuth cut-off phenomenon in sea surface wind field observation.Wave spectrometers,while unaffected by the azimuth cutoff phenomenon,struggle with low azimuth resolution,impacting the capture of detailed wave and wind field data.This study utilizes SAR and surface wave investigation and monitoring(SWIM)data to initially extract key feature parameters,which are then prioritized using the extreme gradient boosting(XGBoost)algorithm.The research further addresses feature collinearity through a combined analysis of feature importance and correlation,leading to the development of an inversion model for wave and wind parameters based on XGBoost.A comparative analysis of this model with ERA5 reanalysis and buoy data for of significant wave height,mean wave period,wind direction,and wind speed reveals root mean square errors of 0.212 m,0.525 s,27.446°,and 1.092 m/s,compared to 0.314 m,0.888 s,27.698°,and 1.315 m/s from buoy data,respectively.These results demonstrate the model’s effective retrieval of wave and wind parameters.Finally,the model,incorporating altimeter and scatterometer data,is evaluated against SAR/SWIM single and dual payload inversion methods across different wind speeds.This comparison highlights the model’s superior inversion accuracy over other methods.

A new method--the inverse strain method(ISM)for preventing welding hot cracking of high strength aluminium alloy LY12CZ

In this paper a new method for preventing welding hot cracking—the inverse strain method(ISM)is developed on the principle of welding mechan- ics.Effectiveness and feasiblity of method in preventing welding hot cracking of high strength aluminum alloy LY12CZ by synchronous rolling during welding (SRDW)along both sides of the weld at a suitable distance behind the welding arc are examined.Experimental resulte indicate that welding hot cracking of LY12CY can be effectively prevented and the mechanical properties of welded joint can also be improved by the method.It is an important new solution for preventing hot cracking in welding of sheet metal.