A data-space inversion(DSI)method has been recently proposed and successfully applied to the history matching and production prediction of reservoirs.Based on Bayesian theory,DSI can directly and effectively obtain go...A data-space inversion(DSI)method has been recently proposed and successfully applied to the history matching and production prediction of reservoirs.Based on Bayesian theory,DSI can directly and effectively obtain good posterior flow predictions without inversion of geological parameters of reservoir model.This paper presents an improved DSI method to fast predict reservoir state fields(e.g.saturation and pressure profiles)via observed production data.Firstly,a large number of production curves and state data are generated by reservoir model simulation to expand the data space of original DSI.Then,efficient history matching only on the observed production data is carried out via the original DSI to obtain related parameters which reflects the weight of the real reservoir model relative to prior reservoir models.Finally,those parameters are used to predict the oil saturation and pressure profiles of the real reservoir model by combining large amounts of state data of prior reservoir models.Two examples including conventional heterogeneous and unconventional fractured reservoir are implemented to test the performances of predicting saturation and pressure profiles of this improved DSI method.Besides,this method is also tested in a real field and the obtained results show the high computational efficiency and high accuracy of the practical application of this method.展开更多
We present systematic investigations on the physics,detection performance and inversion of logging-while-drilling extradeep azimuthal resistivity measurements(EDARM).First,the definitions of EDRAM measurements are dis...We present systematic investigations on the physics,detection performance and inversion of logging-while-drilling extradeep azimuthal resistivity measurements(EDARM).First,the definitions of EDRAM measurements are discussed,followed by the derivation of the attenuation and phase-shift geometrical factors to illustrate the relative contributions of formation units to the observed signals.Then,a new definition of detection depth,which considers the uncertainty of inversion results caused by the data noise,is proposed to quantify the detection capability of ED ARM.Finally,the B ayesian theory associated with Markov chain Monte Carlo sampling is introduced for fast processing of EDARM data.Numerical results show that ED ARM is capable of detecting the azimuth and distance of remote bed boundaries,and the detection capability increases with increasing spacing and resistivity contrast.The EDARM tool can accommodate a large range of formation resistivity and is able to provide the resistivity anisotropy at arbitrary relative dipping angles.In addition,multiple bed boundaries and reservoir images near the borehole are readily obtained by using the Bayesian inversion.展开更多
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 ran...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.展开更多
The change processes and trends of shoreline and tidal flat forced by human activities are essential issues for the sustainability of coastal area,which is also of great significance for understanding coastal ecologic...The change processes and trends of shoreline and tidal flat forced by human activities are essential issues for the sustainability of coastal area,which is also of great significance for understanding coastal ecological environment changes and even global changes.Based on field measurements,combined with Linear Regression(LR)model and Inverse Distance Weighing(IDW)method,this paper presents detailed analysis on the change history and trend of the shoreline and tidal flat in Bohai Bay.The shoreline faces a high erosion chance under the action of natural factors,while the tidal flat faces a different erosion and deposition patterns in Bohai Bay due to the impact of human activities.The implication of change rule for ecological protection and recovery is also discussed.Measures should be taken to protect the coastal ecological environment.The models used in this paper show a high correlation coefficient between observed and modeling data,which means that this method can be used to predict the changing trend of shoreline and tidal flat.The research results of present study can provide scientific supports for future coastal protection and management.展开更多
In this paper,we proposed a novel method for low-field nuclear magnetic resonance(NMR)inversion based on low-rank and sparsity restraint(LRSR)of relaxation spectra,with which high quality construction is made possible...In this paper,we proposed a novel method for low-field nuclear magnetic resonance(NMR)inversion based on low-rank and sparsity restraint(LRSR)of relaxation spectra,with which high quality construction is made possible for one-and two-dimensional low-field and low signal to noise ratio NMR data.In this method,the low-rank and sparsity restraints are introduced into the objective function instead of the smoothing term.The low-rank features in relaxation spectra are extracted to ensure the local characteristics and morphology of spectra.The sparsity and residual term are contributed to the resolution and precision of spectra,with the elimination of the redundant relaxation components.Optimization process of the objective function is designed with alternating direction method of multiples,in which the objective function is decomposed into three subproblems to be independently solved.The optimum solution can be obtained by alternating iteration and updating process.At first,numerical simulations are conducted on synthetic echo data with different signal-to-noise ratios,to optimize the desirable regularization parameters and verify the feasibility and effectiveness of proposed method.Then,NMR experiments on solutions and artificial sandstone samples are conducted and analyzed,which validates the robustness and reliability of the proposed method.The results from simulations and experiments have demonstrated that the suggested method has unique advantages for improving the resolution of relaxation spectra and enhancing the ability of fluid quantitative identification.展开更多
To improve the design speed and reduce the design cost for the previous blade design method, a modified inverse design method is presented. In the new method, after a series of physical and mathematical simplification...To improve the design speed and reduce the design cost for the previous blade design method, a modified inverse design method is presented. In the new method, after a series of physical and mathematical simplifications, a sail?like constrained area is proposed, which can be used to configure di erent runner blade shapes. Then, the new method is applied to redesign and optimize the runner blade of the scale core component of the 1400?MW canned nuclear coolant pump in an established multi?optimization system compromising the Computational Fluid Dynamics(CFD) analysis, the Response Surface Methodology(RSM) and the Non?dominated Sorting Genetic Algorithm?II(NSGA?II). After the execution of the optimization procedure, three optimal samples were ultimately obtained. Then, through comparative analysis using the target runner blade, it was found that the maximum e ciency improvement reached 1.6%, while the head improvement was about 10%. Overall, a promising runner blade inverse design method which will benefit the hydraulic design of the mixed?flow pump has been proposed.展开更多
The data-driven phenomenological models based on deformation measurements have been widely utilized to predict the slope failure time(SFT).The observational and model uncertainties could lead the predicted SFT calcula...The data-driven phenomenological models based on deformation measurements have been widely utilized to predict the slope failure time(SFT).The observational and model uncertainties could lead the predicted SFT calculated from the phenomenological models to deviate from the actual SFT.Currently,very limited study has been conducted on how to evaluate the effect of such uncertainties on SFT prediction.In this paper,a comprehensive slope failure database was compiled.A Bayesian machine learning(BML)-based method was developed to learn the model and observational uncertainties involved in SFT prediction,through which the probabilistic distribution of the SFT can be obtained.This method was illustrated in detail with an example.Verification studies show that the BML-based method is superior to the traditional inverse velocity method(INVM)and the maximum likelihood method for predicting SFT.The proposed method in this study provides an effective tool for SFT prediction.展开更多
A model predictive inverse method (MPIM) is presented to estimate the time- and space-dependent heat flux onthe ablated boundary and the ablation velocity of the two-dimensional ablation system. For the method, first ...A model predictive inverse method (MPIM) is presented to estimate the time- and space-dependent heat flux onthe ablated boundary and the ablation velocity of the two-dimensional ablation system. For the method, first of all, therelationship between the heat flux and the temperatures of the measurement points inside the ablation material is establishedby the predictive model based on an influence relationship matrix. Meanwhile, the estimation task is formulated as aninverse heat transfer problem (IHTP) with consideration of ablation, which is described by an objective function of thetemperatures at the measurement point. Then, the rolling optimization is used to solve the IHTP to online estimate theunknown heat flux on the ablated boundary. Furthermore, the movement law of the ablated boundary is reconstructedaccording to the estimation of the boundary heat flux. The effects of the temperature measurement errors, the numberof future time steps, and the arrangement of the measurement points on the estimation results are analyzed in numericalexperiments. On the basis of the numerical results, the effectiveness of the presented method is clarified.展开更多
According to the requirement of heterogeneous object modeling in additive manufacturing(AM),the Non-Uniform Rational B-Spline(NURBS)method has been applied to the digital representation of heterogeneous object in this...According to the requirement of heterogeneous object modeling in additive manufacturing(AM),the Non-Uniform Rational B-Spline(NURBS)method has been applied to the digital representation of heterogeneous object in this paper.By putting forward the NURBS material data structure and establishing heterogeneous NURBS object model,the accurate mathematical unified representation of analytical and free heterogeneous objects have been realized.With the inverse modeling of heterogeneous NURBS objects,the geometry and material distribution can be better designed to meet the actual needs.Radical Basis Function(RBF)method based on global surface reconstruction and the tensor product surface interpolation method are combined to RBF-NURBS inverse construction method.The geometric and/or material information of regular mesh points is obtained by RBF interpolation of scattered data,and the heterogeneous NURBS surface or object model is obtained by tensor product interpolation.The examples have shown that the heterogeneous objects fitting to scattered data points can be generated effectively by the inverse construction methods in this paper and 3D CAD models for additive manufacturing can be provided.展开更多
The electric inversion technique reconstructs the subsurface medium distribution from acquired data.On the basis of electric inversion,objects buried under the earth or seabed,such as pipelines and unexploded ordnance...The electric inversion technique reconstructs the subsurface medium distribution from acquired data.On the basis of electric inversion,objects buried under the earth or seabed,such as pipelines and unexploded ordnance,are detected and located in a contactless manner.However,the process of accurately reconstructing the shape of the target object is challenging because electric inversion is a nonlinear and ill-posed problem.In this work,we present an inverse multiquadric(IMQ)regularization method based on the level set function for reconstructing buried pipelines.In the case of locating underwater objects,the unknown inversion area is split into two parts,the background and the pipeline with known conductivity.The geometry of the pipeline is represented based on the level set function for achieving a noiseless inversion image.To obtain a binary image,the IMQ is used as the regularization term,which‘pushes’the level set function away from 0.We also provide an appropriate method to select the bandwidth and regularization parameters for the IMQ regularization term,resulting in reconstructed images with sharp edges.The simulation results and analysis show that the proposed method performs better than classical inversion methods.展开更多
Shape sensing as a crucial component of structural health monitoring plays a vital role in real-time actuation and control of smart structures,and monitoring of structural integrity.As a model-based method,the inverse...Shape sensing as a crucial component of structural health monitoring plays a vital role in real-time actuation and control of smart structures,and monitoring of structural integrity.As a model-based method,the inverse finite element method(iFEM)has been proved to be a valuable shape sensing tool that is suitable for complex structures.In this paper,we propose a novel approach for the shape sensing of thin shell structures with iFEM.Considering the structural form and stress characteristics of thin-walled structure,the error function consists of membrane and bending section strains only which is consistent with the Kirchhoff–Love shell theory.For numerical implementation,a new four-node quadrilateral inverse-shell element,iDKQ4,is developed by utilizing the kinematics of the classical shell theory.This new element includes hierarchical drilling rotation degrees-of-freedom(DOF)which enhance applicability to complex structures.Firstly,the reconstruction performance is examined numerically using a cantilever plate model.Following the validation cases,the applicability of the iDKQ4 element to more complex structures is demonstrated by the analysis of a thin wallpanel.Finally,the deformation of a typical aerospace thin-wall structure(the composite tank)is reconstructed with sparse strain data with the help of iDKQ4 element.展开更多
Assume that a convergent matrix sequence{A<sub>n</sub>}:A<sub>n</sub>→A（n→∞）, A<sub>n</sub>,A∈C<sup>3×3</sup>.We want to form a new matrix sequence {H<sub&...Assume that a convergent matrix sequence{A<sub>n</sub>}:A<sub>n</sub>→A（n→∞）, A<sub>n</sub>,A∈C<sup>3×3</sup>.We want to form a new matrix sequence {H<sub>n</sub>}, derived from {A<sub>n</sub>}, which has also A aslimit and whose convergence is faster than the of {A<sub>n</sub>}. Three rational extrapolation meth-ods for accelerating the convergence of matrix sequences {A<sub>n</sub>} are presented in this paper.The underlying methods are based on the generalized inverse for matrices which is展开更多
With the rapid development of the city, it is necessar</span><span style="font-family:Verdana;">y to obtain geological information within 500 meters. Electrical prospecting is not only low cost a...With the rapid development of the city, it is necessar</span><span style="font-family:Verdana;">y to obtain geological information within 500 meters. Electrical prospecting is not only low cost and simple operation, but also solves the problem of insufficient drilling density in </span><span style="font-family:Verdana;">a </span><span style="font-family:Verdana;">survey</span><span style="font-family:Verdana;">. However, due to the dense urban buildings and strong electromagnetic interference, it is difficult for traditional electrical instruments to obtain effective data</span><span style="font-family:Verdana;">.</span><span style="font-family:""> </span><span style="font-family:Verdana;">An </span><span style="font-family:Verdana;">anti-interference electrical method instrument is designed.</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">In the application test of Tongzhou</span><span style="color:black;font-family:Verdana;"> core area in Beijing, the resistivity sounding data collected by </span></span><span style="font-family:"color:black;"><span style="font-family:Verdana;">anti-interference</span><span style="font-family:Verdana;"> electrical method </span><span style="font-family:Verdana;">instrument</span><span style="font-family:Verdana;"> is stable and reliable;inversion results of sounding are basically consistent with borehole data;</span><span style="font-family:Verdana;">the known Zhangjiawan fault and Yaoxinzhuang fault are obvious;basement karst collapse area inferred is basically coincident with the historical collapse area. It is proved that the anti-interference electrical </span><span style="font-family:Verdana;">method</span><span style="font-family:Verdana;"> instrument is effective and can be applied to the geological survey of underground space in other cities.展开更多
A new method for approximating the inerse Laplace transform is presented. We first change our Laplace transform equation into a convolution type integral equation, where Tikhonov regularization techniques and the Four...A new method for approximating the inerse Laplace transform is presented. We first change our Laplace transform equation into a convolution type integral equation, where Tikhonov regularization techniques and the Fourier transformation are easily applied. We finally obtain a regularized approximation to the inverse Laplace transform as finite展开更多
The altered blood flow in the foot is an important indicator of early diabetic foot complications.However,it is challenging to measure the blood flow at the whole foot scale.This study presents an approach for estimat...The altered blood flow in the foot is an important indicator of early diabetic foot complications.However,it is challenging to measure the blood flow at the whole foot scale.This study presents an approach for estimating the foot arterial blood flow using the temperature distribution and an artificial neural network.To quantify the relationship between the blood flow and the temperature distribution,a bioheat transfer model of a voxel-meshed foot tissue with discrete blood vessels is established based on the computed tomography(CT)sequential images and the anatomical information of the vascular structure.In our model,the heat transfer from blood vessels and tissue and the inter-domain heat exchange between them are considered thoroughly,and the computed temperatures are consistent with the experimental results.Analytical data are then used to train a neural network to determine the foot arterial blood flow.The trained network is able to estimate the objective blood flow for various degrees of stenosis in multiple blood vessels with an accuracy rate of more than 90%.Compared with the Pennes bioheat transfer equation,this model fully describes intra-and inter-domain heat transfer in blood vessels and tissue,closely approximating physiological conditions.By introducing a vascular component to an inverse model,the blood flow itself,rather than blood perfusion,can be estimated,directly informing vascular health.展开更多
Predicting the failure time of a landslide is considered as challenging work in the field of landslide research,and inverse velocity is proved to be an effective and convenient method.The onset of acceleration(OOA)has...Predicting the failure time of a landslide is considered as challenging work in the field of landslide research,and inverse velocity is proved to be an effective and convenient method.The onset of acceleration(OOA)has a crucial effect on the prediction failure time from the inverse velocity method.However,a simple method to identify OOA points is lacked,and most of the identifications rely on expert experience.Therefore,this study presents an application of a simple framework developed to identify the OOA by analyzing monitoring velocity data in three steps,including selection of the absolute value of velocity,reliable area identification and OOA identification.A new parameter based on exponential moving average(EMA)is developed to identify the landslide OOA.The framework is applied to three historical case studies to test its practicability and effectiveness.The forecasting results show a good correspondence between the accuracy rate and the coefficient of determination(R2).The predicted failure time according to the linear extrapolation starting from the identified OOA points is acceptable with a high R2 and high accuracy.展开更多
Machine learning-based modeling of reactor physics problems has attracted increasing interest in recent years.Despite some progress in one-dimensional problems,there is still a paucity of benchmark studies that are ea...Machine learning-based modeling of reactor physics problems has attracted increasing interest in recent years.Despite some progress in one-dimensional problems,there is still a paucity of benchmark studies that are easy to solve using traditional numerical methods albeit still challenging using neural networks for a wide range of practical problems.We present two networks,namely the Generalized Inverse Power Method Neural Network(GIPMNN)and Physics-Constrained GIPMNN(PC-GIPIMNN)to solve K-eigenvalue problems in neutron diffusion theory.GIPMNN follows the main idea of the inverse power method and determines the lowest eigenvalue using an iterative method.The PC-GIPMNN additionally enforces conservative interface conditions for the neutron flux.Meanwhile,Deep Ritz Method(DRM)directly solves the smallest eigenvalue by minimizing the eigenvalue in Rayleigh quotient form.A comprehensive study was conducted using GIPMNN,PC-GIPMNN,and DRM to solve problems of complex spatial geometry with variant material domains from the fleld of nuclear reactor physics.The methods were compared with the standard flnite element method.The applicability and accuracy of the methods are reported and indicate that PC-GIPMNN outperforms GIPMNN and DRM.展开更多
The succession of tectonic phenomena in the South-West Cameroon area suggests that structures from the upper mantle infiltrated and took advantage of the cracks and fractures left by these phenomena to get closer to t...The succession of tectonic phenomena in the South-West Cameroon area suggests that structures from the upper mantle infiltrated and took advantage of the cracks and fractures left by these phenomena to get closer to the earth’s surface. However, the intrusive structures closest to the surface remain poorly known. The objective of this work is to improve the knowledge related to the interpretation of gravity data in order to characterise the near-surface intrusive bodies in the South-West Cameroon area, and then analyse their mining and geothermal implications. To achieve this objective, the indirect, inverse and normalized standard deviation (NSTD) methods were used. The NSTD method was used to detect the contours of the intrusive bodies. The indirect method (spectral analysis) was used to determine the depths of the interfaces of three intrusive bodies, one located on the Bipindi-Ebolowa I axis (G5), the other on the Eseka-Pouma axis (G8) and the last on the Bokito-Monatele axis (G11). The results obtained show roofs located between 0 and 0.61 km, between 0 and 0.37 km and between 0 and 0.73 km for the G5, G8 and G11 bodies, respectively. Finally, the application of the 2D inversion method allowed us to estimate the density contrasts of the intrusive bodies (G5, G8 and G11). The superposition of the intrusive bodies detected by the NSTD with the geological and mineral resources map, as well as an analysis of the results obtained, gave indications of interesting zones for mining prospecting and for the search for geothermal reservoirs.展开更多
The reliable estimation of the wavenumber space(k-space)of the plates remains a longterm concern for acoustic modeling and structural dynamic behavior characterization.Most current analyses of wavenumber identificatio...The reliable estimation of the wavenumber space(k-space)of the plates remains a longterm concern for acoustic modeling and structural dynamic behavior characterization.Most current analyses of wavenumber identification methods are based on the deterministic hypothesis.To this end,an inverse method is proposed for identifying wave propagation characteristics of twodimensional structures under stochastic conditions,such as wavenumber space,dispersion curves,and band gaps.The proposed method is developed based on an algebraic identification scheme in the polar coordinate system framework,thus named Algebraic K-Space Identification(AKSI)technique.Additionally,a model order estimation strategy and a wavenumber filter are proposed to ensure that AKSI is successfully applied.The main benefit of AKSI is that it is a reliable and fast method under four stochastic conditions:(A)High level of signal noise;(B)Small perturbation caused by uncertainties in measurement points’coordinates;(C)Non-periodic sampling;(D)Unknown structural periodicity.To validate the proposed method,we numerically benchmark AKSI and three other inverse methods to extract dispersion curves on three plates under stochastic conditions.One experiment is then performed on an isotropic steel plate.These investigations demonstrate that AKSI is a good in-situ k-space estimator under stochastic conditions.展开更多
The level of deformation development of surrounding rocks is a vital predictor to evaluate impending coal mine disasters and it is important to establish accurate measurements of the deformed status to ensure coal min...The level of deformation development of surrounding rocks is a vital predictor to evaluate impending coal mine disasters and it is important to establish accurate measurements of the deformed status to ensure coal mine safety. Traditional deformation monitoring methods are mostly based on single parameter, in this paper, multiple approaches are integrated: firstly, both electric and elastic models are established,from which electric field distribution and seismic wave recording are calculated and finally, the resistivity profiles and source position information are determined using inversion methods, from which then the deformation and failure of mine floor are evaluated. According to the inversion results of both electric and seismic field signals, multiple-parameter dynamic monitoring of surrounding rock deformation in deep mine can be performed. The methodology is validated using numerical simulation results which shows that the multi-parameter dynamic monitoring methods have better results for surrounding rock deformation in deep mine monitoring than single parameter methods.展开更多
基金supported by Southern Marine Science and Engineering Guangdong Laboratory(Zhanjiang)(No.ZJW-2019-04)Cooperative Innovation Center of Unconventional Oil and Gas(Ministry of Education&Hubei Province),Yangtze University(No.UOG2020-17)the National Natural Science Foundation of China(No.51874044,51922007)。
文摘A data-space inversion(DSI)method has been recently proposed and successfully applied to the history matching and production prediction of reservoirs.Based on Bayesian theory,DSI can directly and effectively obtain good posterior flow predictions without inversion of geological parameters of reservoir model.This paper presents an improved DSI method to fast predict reservoir state fields(e.g.saturation and pressure profiles)via observed production data.Firstly,a large number of production curves and state data are generated by reservoir model simulation to expand the data space of original DSI.Then,efficient history matching only on the observed production data is carried out via the original DSI to obtain related parameters which reflects the weight of the real reservoir model relative to prior reservoir models.Finally,those parameters are used to predict the oil saturation and pressure profiles of the real reservoir model by combining large amounts of state data of prior reservoir models.Two examples including conventional heterogeneous and unconventional fractured reservoir are implemented to test the performances of predicting saturation and pressure profiles of this improved DSI method.Besides,this method is also tested in a real field and the obtained results show the high computational efficiency and high accuracy of the practical application of this method.
基金co-funded by Chinese Postdoctoral Science Foundation(2018M640663)the National Natural Science Foundation of China(41474100,41574118,41674131)National Science and Technology Major Project of the Ministry of Science and Technology of China(2017ZX05009-001)
文摘We present systematic investigations on the physics,detection performance and inversion of logging-while-drilling extradeep azimuthal resistivity measurements(EDARM).First,the definitions of EDRAM measurements are discussed,followed by the derivation of the attenuation and phase-shift geometrical factors to illustrate the relative contributions of formation units to the observed signals.Then,a new definition of detection depth,which considers the uncertainty of inversion results caused by the data noise,is proposed to quantify the detection capability of ED ARM.Finally,the B ayesian theory associated with Markov chain Monte Carlo sampling is introduced for fast processing of EDARM data.Numerical results show that ED ARM is capable of detecting the azimuth and distance of remote bed boundaries,and the detection capability increases with increasing spacing and resistivity contrast.The EDARM tool can accommodate a large range of formation resistivity and is able to provide the resistivity anisotropy at arbitrary relative dipping angles.In addition,multiple bed boundaries and reservoir images near the borehole are readily obtained by using the Bayesian inversion.
基金supported by the National Natural Science Foundation of China(Grant No.U22A20594)the Fundamental Research Funds for the Central Universities(Grant No.B230205028)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX23_0694).
文摘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.
基金supported by the National Natural Science Foundation of China (41602205, 42293261)the China Geological Survey Program (DD20189506, DD20211301)+2 种基金the Special Investigation Project on Science and Technology Basic Resources of the Ministry of Science and Technology (2021FY101003)the Central Guidance for Local Scientific and Technological Development Fund of 2023the Project of Hebei University of Environmental Engineering (GCY202301)
文摘The change processes and trends of shoreline and tidal flat forced by human activities are essential issues for the sustainability of coastal area,which is also of great significance for understanding coastal ecological environment changes and even global changes.Based on field measurements,combined with Linear Regression(LR)model and Inverse Distance Weighing(IDW)method,this paper presents detailed analysis on the change history and trend of the shoreline and tidal flat in Bohai Bay.The shoreline faces a high erosion chance under the action of natural factors,while the tidal flat faces a different erosion and deposition patterns in Bohai Bay due to the impact of human activities.The implication of change rule for ecological protection and recovery is also discussed.Measures should be taken to protect the coastal ecological environment.The models used in this paper show a high correlation coefficient between observed and modeling data,which means that this method can be used to predict the changing trend of shoreline and tidal flat.The research results of present study can provide scientific supports for future coastal protection and management.
基金supported by “National Natural Science Foundation of China (Grant No. 42204106)”“China Postdoctoral Science Foundation (Grant No. 2021M700172)”+1 种基金“The Strategic Cooperation Technology Projects of CNPC and CUP (Grant No. ZLZX2020-03)”“Natural Science Foundation of the Jiangsu Higher Education Institutions of China (Grant No. 20KJD430002)”
文摘In this paper,we proposed a novel method for low-field nuclear magnetic resonance(NMR)inversion based on low-rank and sparsity restraint(LRSR)of relaxation spectra,with which high quality construction is made possible for one-and two-dimensional low-field and low signal to noise ratio NMR data.In this method,the low-rank and sparsity restraints are introduced into the objective function instead of the smoothing term.The low-rank features in relaxation spectra are extracted to ensure the local characteristics and morphology of spectra.The sparsity and residual term are contributed to the resolution and precision of spectra,with the elimination of the redundant relaxation components.Optimization process of the objective function is designed with alternating direction method of multiples,in which the objective function is decomposed into three subproblems to be independently solved.The optimum solution can be obtained by alternating iteration and updating process.At first,numerical simulations are conducted on synthetic echo data with different signal-to-noise ratios,to optimize the desirable regularization parameters and verify the feasibility and effectiveness of proposed method.Then,NMR experiments on solutions and artificial sandstone samples are conducted and analyzed,which validates the robustness and reliability of the proposed method.The results from simulations and experiments have demonstrated that the suggested method has unique advantages for improving the resolution of relaxation spectra and enhancing the ability of fluid quantitative identification.
基金National Basic Research Program of China(973 Program,Grant No.2015CB057301)Research and Innovation in Science and Technology Major Project of Liaoning Province,China(Grant No.201410001)Collaborative Innovation Center of Major Machine Manufacturing in Liaoning Province,China
文摘To improve the design speed and reduce the design cost for the previous blade design method, a modified inverse design method is presented. In the new method, after a series of physical and mathematical simplifications, a sail?like constrained area is proposed, which can be used to configure di erent runner blade shapes. Then, the new method is applied to redesign and optimize the runner blade of the scale core component of the 1400?MW canned nuclear coolant pump in an established multi?optimization system compromising the Computational Fluid Dynamics(CFD) analysis, the Response Surface Methodology(RSM) and the Non?dominated Sorting Genetic Algorithm?II(NSGA?II). After the execution of the optimization procedure, three optimal samples were ultimately obtained. Then, through comparative analysis using the target runner blade, it was found that the maximum e ciency improvement reached 1.6%, while the head improvement was about 10%. Overall, a promising runner blade inverse design method which will benefit the hydraulic design of the mixed?flow pump has been proposed.
基金substantially supported by the Shuguang Program from Shanghai Education Development FoundationShanghai Municipal Education Commission, China (Grant No. 19SG19)+1 种基金National Natural Science Foundation of China (Grant No. 42072302)Fundamental Research Funds for the Central Universities, China
文摘The data-driven phenomenological models based on deformation measurements have been widely utilized to predict the slope failure time(SFT).The observational and model uncertainties could lead the predicted SFT calculated from the phenomenological models to deviate from the actual SFT.Currently,very limited study has been conducted on how to evaluate the effect of such uncertainties on SFT prediction.In this paper,a comprehensive slope failure database was compiled.A Bayesian machine learning(BML)-based method was developed to learn the model and observational uncertainties involved in SFT prediction,through which the probabilistic distribution of the SFT can be obtained.This method was illustrated in detail with an example.Verification studies show that the BML-based method is superior to the traditional inverse velocity method(INVM)and the maximum likelihood method for predicting SFT.The proposed method in this study provides an effective tool for SFT prediction.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.51876010 and 51676019).
文摘A model predictive inverse method (MPIM) is presented to estimate the time- and space-dependent heat flux onthe ablated boundary and the ablation velocity of the two-dimensional ablation system. For the method, first of all, therelationship between the heat flux and the temperatures of the measurement points inside the ablation material is establishedby the predictive model based on an influence relationship matrix. Meanwhile, the estimation task is formulated as aninverse heat transfer problem (IHTP) with consideration of ablation, which is described by an objective function of thetemperatures at the measurement point. Then, the rolling optimization is used to solve the IHTP to online estimate theunknown heat flux on the ablated boundary. Furthermore, the movement law of the ablated boundary is reconstructedaccording to the estimation of the boundary heat flux. The effects of the temperature measurement errors, the numberof future time steps, and the arrangement of the measurement points on the estimation results are analyzed in numericalexperiments. On the basis of the numerical results, the effectiveness of the presented method is clarified.
文摘According to the requirement of heterogeneous object modeling in additive manufacturing(AM),the Non-Uniform Rational B-Spline(NURBS)method has been applied to the digital representation of heterogeneous object in this paper.By putting forward the NURBS material data structure and establishing heterogeneous NURBS object model,the accurate mathematical unified representation of analytical and free heterogeneous objects have been realized.With the inverse modeling of heterogeneous NURBS objects,the geometry and material distribution can be better designed to meet the actual needs.Radical Basis Function(RBF)method based on global surface reconstruction and the tensor product surface interpolation method are combined to RBF-NURBS inverse construction method.The geometric and/or material information of regular mesh points is obtained by RBF interpolation of scattered data,and the heterogeneous NURBS surface or object model is obtained by tensor product interpolation.The examples have shown that the heterogeneous objects fitting to scattered data points can be generated effectively by the inverse construction methods in this paper and 3D CAD models for additive manufacturing can be provided.
基金supported by the National Natural Sci-ence Foundation of China(No.52101383)the Fundamen-tal Research Funds for the Central Universities(No.3072021CF0802)+3 种基金the Key Laboratory of Advanced Marine Communication and Information Technology,Ministry of Industry and Information Technology(No.AMCIT2101-02)the Sino-Russian Cooperation Fund of Harbin Engi-neering University(No.2021HEUCRF006)the Ministry of Science and Higher Education of the Russian Federation(No.075-15-2020-934)the International Science&Technology Cooperation Program of China(No.2014DF R10240).
文摘The electric inversion technique reconstructs the subsurface medium distribution from acquired data.On the basis of electric inversion,objects buried under the earth or seabed,such as pipelines and unexploded ordnance,are detected and located in a contactless manner.However,the process of accurately reconstructing the shape of the target object is challenging because electric inversion is a nonlinear and ill-posed problem.In this work,we present an inverse multiquadric(IMQ)regularization method based on the level set function for reconstructing buried pipelines.In the case of locating underwater objects,the unknown inversion area is split into two parts,the background and the pipeline with known conductivity.The geometry of the pipeline is represented based on the level set function for achieving a noiseless inversion image.To obtain a binary image,the IMQ is used as the regularization term,which‘pushes’the level set function away from 0.We also provide an appropriate method to select the bandwidth and regularization parameters for the IMQ regularization term,resulting in reconstructed images with sharp edges.The simulation results and analysis show that the proposed method performs better than classical inversion methods.
基金The author received funding for this study from National Key R&D Program of China(2018YFA0702800)National Natural Science Foundation of China(11602048)This study is also supported by National Defense Fundamental Scientific Research Project(XXXX2018204BXXX).
文摘Shape sensing as a crucial component of structural health monitoring plays a vital role in real-time actuation and control of smart structures,and monitoring of structural integrity.As a model-based method,the inverse finite element method(iFEM)has been proved to be a valuable shape sensing tool that is suitable for complex structures.In this paper,we propose a novel approach for the shape sensing of thin shell structures with iFEM.Considering the structural form and stress characteristics of thin-walled structure,the error function consists of membrane and bending section strains only which is consistent with the Kirchhoff–Love shell theory.For numerical implementation,a new four-node quadrilateral inverse-shell element,iDKQ4,is developed by utilizing the kinematics of the classical shell theory.This new element includes hierarchical drilling rotation degrees-of-freedom(DOF)which enhance applicability to complex structures.Firstly,the reconstruction performance is examined numerically using a cantilever plate model.Following the validation cases,the applicability of the iDKQ4 element to more complex structures is demonstrated by the analysis of a thin wallpanel.Finally,the deformation of a typical aerospace thin-wall structure(the composite tank)is reconstructed with sparse strain data with the help of iDKQ4 element.
基金The works is supported by the National Natural Science Foundation of China(19871054)
文摘Assume that a convergent matrix sequence{A<sub>n</sub>}:A<sub>n</sub>→A（n→∞）, A<sub>n</sub>,A∈C<sup>3×3</sup>.We want to form a new matrix sequence {H<sub>n</sub>}, derived from {A<sub>n</sub>}, which has also A aslimit and whose convergence is faster than the of {A<sub>n</sub>}. Three rational extrapolation meth-ods for accelerating the convergence of matrix sequences {A<sub>n</sub>} are presented in this paper.The underlying methods are based on the generalized inverse for matrices which is
文摘With the rapid development of the city, it is necessar</span><span style="font-family:Verdana;">y to obtain geological information within 500 meters. Electrical prospecting is not only low cost and simple operation, but also solves the problem of insufficient drilling density in </span><span style="font-family:Verdana;">a </span><span style="font-family:Verdana;">survey</span><span style="font-family:Verdana;">. However, due to the dense urban buildings and strong electromagnetic interference, it is difficult for traditional electrical instruments to obtain effective data</span><span style="font-family:Verdana;">.</span><span style="font-family:""> </span><span style="font-family:Verdana;">An </span><span style="font-family:Verdana;">anti-interference electrical method instrument is designed.</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">In the application test of Tongzhou</span><span style="color:black;font-family:Verdana;"> core area in Beijing, the resistivity sounding data collected by </span></span><span style="font-family:"color:black;"><span style="font-family:Verdana;">anti-interference</span><span style="font-family:Verdana;"> electrical method </span><span style="font-family:Verdana;">instrument</span><span style="font-family:Verdana;"> is stable and reliable;inversion results of sounding are basically consistent with borehole data;</span><span style="font-family:Verdana;">the known Zhangjiawan fault and Yaoxinzhuang fault are obvious;basement karst collapse area inferred is basically coincident with the historical collapse area. It is proved that the anti-interference electrical </span><span style="font-family:Verdana;">method</span><span style="font-family:Verdana;"> instrument is effective and can be applied to the geological survey of underground space in other cities.
文摘A new method for approximating the inerse Laplace transform is presented. We first change our Laplace transform equation into a convolution type integral equation, where Tikhonov regularization techniques and the Fourier transformation are easily applied. We finally obtain a regularized approximation to the inverse Laplace transform as finite
基金the National Natural Science Foundation of China(No.51976026)the Fundamental Research Funds of Central Universities of China(No.DUT22YG206)。
文摘The altered blood flow in the foot is an important indicator of early diabetic foot complications.However,it is challenging to measure the blood flow at the whole foot scale.This study presents an approach for estimating the foot arterial blood flow using the temperature distribution and an artificial neural network.To quantify the relationship between the blood flow and the temperature distribution,a bioheat transfer model of a voxel-meshed foot tissue with discrete blood vessels is established based on the computed tomography(CT)sequential images and the anatomical information of the vascular structure.In our model,the heat transfer from blood vessels and tissue and the inter-domain heat exchange between them are considered thoroughly,and the computed temperatures are consistent with the experimental results.Analytical data are then used to train a neural network to determine the foot arterial blood flow.The trained network is able to estimate the objective blood flow for various degrees of stenosis in multiple blood vessels with an accuracy rate of more than 90%.Compared with the Pennes bioheat transfer equation,this model fully describes intra-and inter-domain heat transfer in blood vessels and tissue,closely approximating physiological conditions.By introducing a vascular component to an inverse model,the blood flow itself,rather than blood perfusion,can be estimated,directly informing vascular health.
基金funded by the National Natural Science Foundation of China(Grant NO.41772324)the Open Foundation of Chengdu Center of China Geological Survey。
文摘Predicting the failure time of a landslide is considered as challenging work in the field of landslide research,and inverse velocity is proved to be an effective and convenient method.The onset of acceleration(OOA)has a crucial effect on the prediction failure time from the inverse velocity method.However,a simple method to identify OOA points is lacked,and most of the identifications rely on expert experience.Therefore,this study presents an application of a simple framework developed to identify the OOA by analyzing monitoring velocity data in three steps,including selection of the absolute value of velocity,reliable area identification and OOA identification.A new parameter based on exponential moving average(EMA)is developed to identify the landslide OOA.The framework is applied to three historical case studies to test its practicability and effectiveness.The forecasting results show a good correspondence between the accuracy rate and the coefficient of determination(R2).The predicted failure time according to the linear extrapolation starting from the identified OOA points is acceptable with a high R2 and high accuracy.
基金partially supported by the National Natural Science Foundation of China(No.11971020)Natural Science Foundation of Shanghai(No.23ZR1429300)Innovation Funds of CNNC(Lingchuang Fund)。
文摘Machine learning-based modeling of reactor physics problems has attracted increasing interest in recent years.Despite some progress in one-dimensional problems,there is still a paucity of benchmark studies that are easy to solve using traditional numerical methods albeit still challenging using neural networks for a wide range of practical problems.We present two networks,namely the Generalized Inverse Power Method Neural Network(GIPMNN)and Physics-Constrained GIPMNN(PC-GIPIMNN)to solve K-eigenvalue problems in neutron diffusion theory.GIPMNN follows the main idea of the inverse power method and determines the lowest eigenvalue using an iterative method.The PC-GIPMNN additionally enforces conservative interface conditions for the neutron flux.Meanwhile,Deep Ritz Method(DRM)directly solves the smallest eigenvalue by minimizing the eigenvalue in Rayleigh quotient form.A comprehensive study was conducted using GIPMNN,PC-GIPMNN,and DRM to solve problems of complex spatial geometry with variant material domains from the fleld of nuclear reactor physics.The methods were compared with the standard flnite element method.The applicability and accuracy of the methods are reported and indicate that PC-GIPMNN outperforms GIPMNN and DRM.
文摘The succession of tectonic phenomena in the South-West Cameroon area suggests that structures from the upper mantle infiltrated and took advantage of the cracks and fractures left by these phenomena to get closer to the earth’s surface. However, the intrusive structures closest to the surface remain poorly known. The objective of this work is to improve the knowledge related to the interpretation of gravity data in order to characterise the near-surface intrusive bodies in the South-West Cameroon area, and then analyse their mining and geothermal implications. To achieve this objective, the indirect, inverse and normalized standard deviation (NSTD) methods were used. The NSTD method was used to detect the contours of the intrusive bodies. The indirect method (spectral analysis) was used to determine the depths of the interfaces of three intrusive bodies, one located on the Bipindi-Ebolowa I axis (G5), the other on the Eseka-Pouma axis (G8) and the last on the Bokito-Monatele axis (G11). The results obtained show roofs located between 0 and 0.61 km, between 0 and 0.37 km and between 0 and 0.73 km for the G5, G8 and G11 bodies, respectively. Finally, the application of the 2D inversion method allowed us to estimate the density contrasts of the intrusive bodies (G5, G8 and G11). The superposition of the intrusive bodies detected by the NSTD with the geological and mineral resources map, as well as an analysis of the results obtained, gave indications of interesting zones for mining prospecting and for the search for geothermal reservoirs.
基金supported by the Lyon Acoustics Center of Lyon University,Francefunded by the China Scholarship Council(CSC)。
文摘The reliable estimation of the wavenumber space(k-space)of the plates remains a longterm concern for acoustic modeling and structural dynamic behavior characterization.Most current analyses of wavenumber identification methods are based on the deterministic hypothesis.To this end,an inverse method is proposed for identifying wave propagation characteristics of twodimensional structures under stochastic conditions,such as wavenumber space,dispersion curves,and band gaps.The proposed method is developed based on an algebraic identification scheme in the polar coordinate system framework,thus named Algebraic K-Space Identification(AKSI)technique.Additionally,a model order estimation strategy and a wavenumber filter are proposed to ensure that AKSI is successfully applied.The main benefit of AKSI is that it is a reliable and fast method under four stochastic conditions:(A)High level of signal noise;(B)Small perturbation caused by uncertainties in measurement points’coordinates;(C)Non-periodic sampling;(D)Unknown structural periodicity.To validate the proposed method,we numerically benchmark AKSI and three other inverse methods to extract dispersion curves on three plates under stochastic conditions.One experiment is then performed on an isotropic steel plate.These investigations demonstrate that AKSI is a good in-situ k-space estimator under stochastic conditions.
基金financial support from the Fundamental Research Funds for the Central Universities of China (No. 2015QNB19)the financial support from the Open Fund of Key Laboratory of Safety and High-efficiency Coal Mining, Ministry of Education of China (No. JYBSYS2015107)+2 种基金the National Natural Science Foundation of China (Nos. 51404254, 41430317 and U1261202)the China Postdoctoral Science Foundation of China (No. 2014M560465)the Jiangsu Planned Projects for Postdoctoral Research Funds of China (No. 1302050B)
文摘The level of deformation development of surrounding rocks is a vital predictor to evaluate impending coal mine disasters and it is important to establish accurate measurements of the deformed status to ensure coal mine safety. Traditional deformation monitoring methods are mostly based on single parameter, in this paper, multiple approaches are integrated: firstly, both electric and elastic models are established,from which electric field distribution and seismic wave recording are calculated and finally, the resistivity profiles and source position information are determined using inversion methods, from which then the deformation and failure of mine floor are evaluated. According to the inversion results of both electric and seismic field signals, multiple-parameter dynamic monitoring of surrounding rock deformation in deep mine can be performed. The methodology is validated using numerical simulation results which shows that the multi-parameter dynamic monitoring methods have better results for surrounding rock deformation in deep mine monitoring than single parameter methods.
