Architecture framework has become an effective method recently to describe the system of systems(SoS)architecture,such as the United States(US)Department of Defense Architecture Framework Version 2.0(DoDAF2.0).As a vi...Architecture framework has become an effective method recently to describe the system of systems(SoS)architecture,such as the United States(US)Department of Defense Architecture Framework Version 2.0(DoDAF2.0).As a viewpoint in DoDAF2.0,the operational viewpoint(OV)describes operational activities,nodes,and resource flows.The OV models are important for SoS architecture development.However,as the SoS complexity increases,constructing OV models with traditional methods exposes shortcomings,such as inefficient data collection and low modeling standards.Therefore,we propose an intelligent modeling method for five OV models,including operational resource flow OV-2,organizational relationships OV-4,operational activity hierarchy OV-5a,operational activities model OV-5b,and operational activity sequences OV-6c.The main idea of the method is to extract OV architecture data from text and generate interoperable OV models.First,we construct the OV meta model based on the DoDAF2.0 meta model(DM2).Second,OV architecture named entities is recognized from text based on the bidirectional long short-term memory and conditional random field(BiLSTM-CRF)model.And OV architecture relationships are collected with relationship extraction rules.Finally,we define the generation rules for OV models and develop an OV modeling tool.We use unmanned surface vehicles(USV)swarm target defense SoS architecture as a case to verify the feasibility and effectiveness of the intelligent modeling method.展开更多
Elasto-plastic consolidation is one of the classic coupling questions in geomechanics. To solve this problem, an elasto-plastic constitutive model is derived based on the numerical modeling method. The model is applie...Elasto-plastic consolidation is one of the classic coupling questions in geomechanics. To solve this problem, an elasto-plastic constitutive model is derived based on the numerical modeling method. The model is applied to Blot＇s consolidation theory. Incremental governing partial differential equations are established using this method. According to the stress path, the decoupling condition of these equations is discussed. Based on these conditions, an incremental diffusion equation and uncoupling governing equations are presented. The method is then applied to numerical analyses of three examples. The results show that （1） the effect of the stress path should be taken into account in the simulation of the soil consolidation question; （2） this decoupling method can predict the evolvement of pore water pressure; （3） the settlement using cam-clay model is less than that using numerical model because of dilatancy.展开更多
In order to establish an adaptive turbo-shaft engine model with high accuracy, a new modeling method based on parameter selection （PS） algorithm and multi-input multi-output recursive reduced least square support ve...In order to establish an adaptive turbo-shaft engine model with high accuracy, a new modeling method based on parameter selection （PS） algorithm and multi-input multi-output recursive reduced least square support vector regression （MRR-LSSVR） machine is proposed. Firstly, the PS algorithm is designed to choose the most reasonable inputs of the adaptive module. During this process, a wrapper criterion based on least square support vector regression （LSSVR） machine is adopted, which can not only reduce computational complexity but also enhance generalization performance. Secondly, with the input variables determined by the PS algorithm, a mapping model of engine parameter estimation is trained off-line using MRR-LSSVR, which has a satisfying accuracy within 5＆. Finally, based on a numerical simulation platform of an integrated helicopter/ turbo-shaft engine system, an adaptive turbo-shaft engine model is developed and tested in a certain flight envelope. Under the condition of single or multiple engine components being degraded, many simulation experiments are carried out, and the simulation results show the effectiveness and validity of the proposed adaptive modeling method.展开更多
An accurate long-term energy demand forecasting is essential for energy planning and policy making. However, due to the immature energy data collecting and statistical methods, the available data are usually limited i...An accurate long-term energy demand forecasting is essential for energy planning and policy making. However, due to the immature energy data collecting and statistical methods, the available data are usually limited in many regions. In this paper, on the basis of comprehensive literature review, we proposed a hybrid model based on the long-range alternative energy planning (LEAP) model to improve the accuracy of energy demand forecasting in these regions. By taking Hunan province, China as a typical case, the proposed hybrid model was applied to estimating the possible future energy demand and energy-saving potentials in different sectors. The structure of LEAP model was estimated by Sankey energy flow, and Leslie matrix and autoregressive integrated moving average (ARIMA) models were used to predict the population, industrial structure and transportation turnover, respectively. Monte-Carlo method was employed to evaluate the uncertainty of forecasted results. The results showed that the hybrid model combined with scenario analysis provided a relatively accurate forecast for the long-term energy demand in regions with limited statistical data, and the average standard error of probabilistic distribution in 2030 energy demand was as low as 0.15. The prediction results could provide supportive references to identify energy-saving potentials and energy development pathways.展开更多
As one of the basic inventory cost models, the （Q, τ）inventory cost model of dual suppliers with random procurement lead time is mostly formulated by using the concepts of ＂effective lead time＂ and ＂lead time de...As one of the basic inventory cost models, the （Q, τ）inventory cost model of dual suppliers with random procurement lead time is mostly formulated by using the concepts of ＂effective lead time＂ and ＂lead time demand＂, which may lead to an imprecise inventory cost. Through the real-time statistic of the inventory quantities, this paper considers the precise （Q, τ） inventory cost model of dual supplier procurement by using an infinitesimal dividing method. The traditional modeling method of the inventory cost for dual supplier procurement includes complex procedures. To reduce the complexity effectively, the presented method investigates the statistics properties in real-time of the inventory quantities with the application of the infinitesimal dividing method. It is proved that the optimal holding and shortage costs of dual supplier procurement are less than those of single supplier procurement respectively. With the assumption that both suppliers have the same distribution of lead times, the convexity of the cost function per unit time is proved. So the optimal solution can be easily obtained by applying the classical convex optimization methods. The numerical examples are given to verify the main conclusions.展开更多
To analyze the modeling methods of the dry friction rotor system,a local linearization model of the dry friction damping rotor system was built based on the simplified model of the wave-shaped steel-belt supporting ro...To analyze the modeling methods of the dry friction rotor system,a local linearization model of the dry friction damping rotor system was built based on the simplified model of the wave-shaped steel-belt supporting rotor system.In this model,the linear stiffness of damper closed to pre-deformation was defined as the stiffness of damper,the maximum amplitude of the rotor was calculated according to the load and linear rotor,and the damper's parameters were defined on the basis of the energy dissipation parameters.The presented method can reflect the hysteresis characteristics and is easy to calculate.Experimental results demonstrate the accuracy and feasibility of this method.展开更多
It is one of the most important part to build an accurate gravity model in geophysical exploration.Traditional gravity modelling is usually based on grid method,such as difference method and finite element method wide...It is one of the most important part to build an accurate gravity model in geophysical exploration.Traditional gravity modelling is usually based on grid method,such as difference method and finite element method widely used.Due to self-adaptability lack of division meshes and the difficulty of high-dimensional calculation.展开更多
Combined with the tire dynamics theoretical model,a rapid test method to obtain tire lateral and longitudinal both steady-state and transient characteristics only based on the tire quasi-steady-state test results is p...Combined with the tire dynamics theoretical model,a rapid test method to obtain tire lateral and longitudinal both steady-state and transient characteristics only based on the tire quasi-steady-state test results is proposed.For steady state data extraction,the test time of the rapid test method is half that of the conventional test method.For transient tire characteristics the rapid test method omits the traditional tire test totally.At the mean time the accuracy of the two method is much closed.The rapid test method is explained theoretically and the test process is designed.The key parameters of tire are extracted and the comparison is made between rapid test and traditional test method.The result show that the identification accuracy based on the rapid test method is almost equal to the accuracy of the conventional one.Then,the heat generated during the rapid test method and that generated during the conventional test are calculated separately.The comparison shows that the heat generated during the rapid test is much smaller than the heat generated during the conventional test process.This benefits to the reduction of tire wear and the consistency of test results.Finally,it can be concluded that the fast test method can efficiently,accurately and energy-efficiently measure the steady-state and transient characteristics of the tire.展开更多
On the basis of the three-dimensional(3D)random aggregate&mortar two-phase mesoscale finite element model,C++programming was used to identify the node position information of the interface between the aggregate an...On the basis of the three-dimensional(3D)random aggregate&mortar two-phase mesoscale finite element model,C++programming was used to identify the node position information of the interface between the aggregate and mortar elements.The nodes were discretized at this position and the zero-thickness cohesive elements were inserted.After that,the crack energy release rate fracture criterion based on the fracture mechanics theory was assigned to the failure criterion of the interface transition zone(ITZ)elements.Finally,the three-phase mesomechanical model based on the combined finite discrete element method(FDEM)was constructed.Based on this model,the meso-crack extension and macro-mechanical behaviour of coral aggregate concrete(CAC)under uniaxial compression were successfully simulated.The results demonstrated that the meso-mechanical model based on FDEM has excellent applicability to simulate the compressive properties of CAC.展开更多
Automatic speech recognition (ASR) is vital for very low-resource languages for mitigating the extinction trouble. Chaha is one of the low-resource languages, which suffers from the problem of resource insufficiency a...Automatic speech recognition (ASR) is vital for very low-resource languages for mitigating the extinction trouble. Chaha is one of the low-resource languages, which suffers from the problem of resource insufficiency and some of its phonological, morphological, and orthographic features challenge the development and initiatives in the area of ASR. By considering these challenges, this study is the first endeavor, which analyzed the characteristics of the language, prepared speech corpus, and developed different ASR systems. A small 3-hour read speech corpus was prepared and transcribed. Different basic and rounded phone unit-based speech recognizers were explored using multilingual deep neural network (DNN) modeling methods. The experimental results demonstrated that all the basic phone and rounded phone unit-based multilingual models outperformed the corresponding unilingual models with the relative performance improvements of 5.47% to 19.87% and 5.74% to 16.77%, respectively. The rounded phone unit-based multilingual models outperformed the equivalent basic phone unit-based models with relative performance improvements of 0.95% to 4.98%. Overall, we discovered that multilingual DNN modeling methods are profoundly effective to develop Chaha speech recognizers. Both the basic and rounded phone acoustic units are convenient to build Chaha ASR system. However, the rounded phone unit-based models are superior in performance and faster in recognition speed over the corresponding basic phone unit-based models. Hence, the rounded phone units are the most suitable acoustic units to develop Chaha ASR systems.展开更多
Near-infrared( NIR) spectroscopy has been widely employed as a process analytical tool( PAT) in various fields; the most important reason for the use of this method is its ability to record spectra in real time to cap...Near-infrared( NIR) spectroscopy has been widely employed as a process analytical tool( PAT) in various fields; the most important reason for the use of this method is its ability to record spectra in real time to capture process properties. In quantitative online applications,the robustness of the established NIR model is often deteriorated by process condition variations,nonlinear of the properties or the high-dimensional of the NIR data set. To cope with such situation,a novel method based on principal component analysis( PCA) and artificial neural network( ANN) is proposed and a new sample-selection method is mentioned. The advantage of the presented approach is that it can select proper calibration samples and establish robust model effectively. The performance of the method was tested on a spectroscopic data set from a refinery process. Compared with traditional partial leastsquares( PLS),principal component regression( PCR) and several other modeling methods, the proposed approach was found to achieve good accuracy in the prediction of gasoline properties. An application of the proposed method is also reported.展开更多
This paper informally introduces colored object-oriented Petri Nets(COOPN) with the application of the AUV system.According to the characteristic of the AUV system's running environment,the object-oriented method ...This paper informally introduces colored object-oriented Petri Nets(COOPN) with the application of the AUV system.According to the characteristic of the AUV system's running environment,the object-oriented method is used in this paper not only to dispart system modules but also construct the refined running model of AUV system,then the colored Petri Net method is used to establish hierarchically detailed model in order to get the performance analyzing information of the system.After analyzing the model implementation,the errors of architecture designing and function realization can be found.If the errors can be modified on time,the experiment time in the pool can be reduced and the cost can be saved.展开更多
It's common to use the method of continuous spectroscopy in water quality testing. But there're some problems with it. For example, the scanning results have a large number of nonlinear signals, and the covari...It's common to use the method of continuous spectroscopy in water quality testing. But there're some problems with it. For example, the scanning results have a large number of nonlinear signals, and the covariance between variables is serious, which can lead to a decrease in the model prediction accuracy. In this paper, the standard solutions of nitrate nitrogen(NO_(3)-N) and nitrite nitrogen(NO_(2)-N) were used as the subject to be tested, and the data of the scanned waves and absorbance were obtained by use of spectral detector. The data were processed by noise reduction first and then the random forest(RF) algorithm was adopted to establish the regression relationship between concentration and absorbance. For comparison, partial least squares(PLS) and support vector machine(SVM) algorithm models were also established. For the same given data, the three reverse models can make the projection of the concentration respectively. The experimental results show that the RF algorithm predicts NO_(2)-N concentrations significantly better than the SVM algorithm and PLS algorithm. This proves that the RF algorithm has good prediction ability in spectral water quality detection because of its high model accuracy and better adaptability, which could be a reference for similar research on continuous spectral water quality online detection.展开更多
In order to study the mechanical properties of the heterogeneous core plate of the wind turbine blade,a modeling method of the core plate based on displacement field variables is proposed.Firstly,the wind turbine blad...In order to study the mechanical properties of the heterogeneous core plate of the wind turbine blade,a modeling method of the core plate based on displacement field variables is proposed.Firstly,the wind turbine blade core plate was modeled according to the theory of modeling heterogeneous material characteristics.Secondly,the three-point bending finite element model of the wind turbine blade core plate was solved by the display dynamic equation to obtain the deformation pattern and force-deformation relationship of the core plate.Finally,the three-point bending static test was conducted to compare with the finite element analysis.The test results show that:the damage form of the wind turbine blade core plate includes elasticity,yield,and failure stages.The main failure modes are plastic deformation,core material collapse,and panel-core delamination.The failure load measured by the test is 1.59 kN,which is basically consistent with the load-displacement result obtained by the simulation,with a difference of only 1.9%,which verifies the validity and reliability of the model.It provides data references for wind turbine blade structure design.展开更多
A new concept, namely, the equivalent mobility matrix of coupling subsystem is proposed, and the corresponding threesubsystem coupling progressive approach is explored. With the new efficient approach presented, the c...A new concept, namely, the equivalent mobility matrix of coupling subsystem is proposed, and the corresponding threesubsystem coupling progressive approach is explored. With the new efficient approach presented, the complexity in dealing with a more complicated dynamic coupling system is greatly reduced. The new modeling method is then combined with the theory of power flow to investigate the dynamics of the overall non rigid isolation system from the viewpoint of energy. The interaction between the resilient machine of its main modes and the resonant behavior of the flexible foundation on power flow transmission is studied. Taking a machine tool mounted on a multi story working plant as an example, the dynamic characteristics of the machine foundation coupling system are analyzed, and their effects on power flow transmission are revealed under various service frequency bands. Some advisable control strategies and the design principle for machinery mounted on flexible structure are proposed.展开更多
The equivalent source(ES)method in the spherical coordinate system has been widely applied to processing,reduction,field modeling,and geophysical and geological interpretation of satellite magnetic anomaly data.Howeve...The equivalent source(ES)method in the spherical coordinate system has been widely applied to processing,reduction,field modeling,and geophysical and geological interpretation of satellite magnetic anomaly data.However,the inversion for the ES model suffers from nonuniqueness and instability,which remain unresolved.To mitigate these issues,we introduce both the minimum and flattest models into the model objective function as an alternative regularization approach in the spherical ES method.We first present the methods,then analyze the accuracy of forward calculation and test the proposed ES method in this study by using synthetic data.The experimental results from simulation data indicate that our proposed regularization effectively suppresses the Backus effect and mitigates inversion instability in the low-latitude region.Finally,we apply the proposed method to magnetic anomaly data from China Seismo-Electromagnetic Satellite-1(CSES-1)and Macao Science Satellite-1(MSS-1)magnetic measurements over Africa by constructing an ES model of the large-scale lithospheric magnetic field.Compared with existing global lithospheric magnetic field models,our ES model demonstrates good consistency at high altitudes and predicts more stable fields at low altitudes.Furthermore,we derive the reduction to the pole(RTP)magnetic anomaly fields and the apparent susceptibility contrast distribution based on the ES model.The latter correlates well with the regional tectonic framework in Africa and surroundings.展开更多
This study introduces a comprehensive theoretical framework for accurately calculating the electronic band-structure of strained long-wavelength InAs/GaSb type-Ⅱsuperlattices.Utilizing an eight-band k·p Hamilto⁃...This study introduces a comprehensive theoretical framework for accurately calculating the electronic band-structure of strained long-wavelength InAs/GaSb type-Ⅱsuperlattices.Utilizing an eight-band k·p Hamilto⁃nian in conjunction with a scattering matrix method,the model effectively incorporates quantum confinement,strain effects,and interface states.This robust and numerically stable approach achieves exceptional agreement with experimental data,offering a reliable tool for analyzing and engineering the band structure of complex multi⁃layer systems.展开更多
Software systems are vulnerable to security breaches as they expand in complexity and functionality.The confidentiality,integrity,and availability of data are gravely threatened by flaws in a system’s design,implemen...Software systems are vulnerable to security breaches as they expand in complexity and functionality.The confidentiality,integrity,and availability of data are gravely threatened by flaws in a system’s design,implementation,or configuration.To guarantee the durability&robustness of the software,vulnerability identification and fixation have become crucial areas of focus for developers,cybersecurity experts and industries.This paper presents a thorough multi-phase mathematical model for efficient patch management and vulnerability detection.To uniquely model these processes,the model incorporated the notion of the learning phenomenon in describing vulnerability fixation using a logistic learning function.Furthermore,the authors have used numerical methods to approximate the solution of the proposed framework where an analytical solution is difficult to attain.The suggested systematic architecture has been demonstrated through statistical analysis using patch datasets,which offers a solid basis for the research conclusions.According to computational research,learning dynamics improves security response and results in more effective vulnerability management.The suggested model offers a systematic approach to proactive vulnerability mitigation and has important uses in risk assessment,software maintenance,and cybersecurity.This study helps create more robust software systems by increasing patch management effectiveness,which benefits developers,cybersecurity experts,and sectors looking to reduce security threats in a growing digital world.展开更多
We propose a novel workflow for fast forward modeling of well logs in axially symmetric 2D models of the nearwellbore environment.The approach integrates the finite element method with deep residual neural networks to...We propose a novel workflow for fast forward modeling of well logs in axially symmetric 2D models of the nearwellbore environment.The approach integrates the finite element method with deep residual neural networks to achieve exceptional computational efficiency and accuracy.The workflow is demonstrated through the modeling of wireline electromagnetic propagation resistivity logs,where the measured responses exhibit a highly nonlinear relationship with formation properties.The motivation for this research is the need for advanced modeling al-gorithms that are fast enough for use in modern quantitative interpretation tools,where thousands of simulations may be required in iterative inversion processes.The proposed algorithm achieves a remarkable enhancement in performance,being up to 3000 times faster than the finite element method alone when utilizing a GPU.While still ensuring high accuracy,this makes it well-suited for practical applications when reliable payzone assessment is needed in complex environmental scenarios.Furthermore,the algorithm’s efficiency positions it as a promising tool for stochastic Bayesian inversion,facilitating reliable uncertainty quantification in subsurface property estimation.展开更多
基金National Natural Science Foundation of China(71690233,71971213,71901214)。
文摘Architecture framework has become an effective method recently to describe the system of systems(SoS)architecture,such as the United States(US)Department of Defense Architecture Framework Version 2.0(DoDAF2.0).As a viewpoint in DoDAF2.0,the operational viewpoint(OV)describes operational activities,nodes,and resource flows.The OV models are important for SoS architecture development.However,as the SoS complexity increases,constructing OV models with traditional methods exposes shortcomings,such as inefficient data collection and low modeling standards.Therefore,we propose an intelligent modeling method for five OV models,including operational resource flow OV-2,organizational relationships OV-4,operational activity hierarchy OV-5a,operational activities model OV-5b,and operational activity sequences OV-6c.The main idea of the method is to extract OV architecture data from text and generate interoperable OV models.First,we construct the OV meta model based on the DoDAF2.0 meta model(DM2).Second,OV architecture named entities is recognized from text based on the bidirectional long short-term memory and conditional random field(BiLSTM-CRF)model.And OV architecture relationships are collected with relationship extraction rules.Finally,we define the generation rules for OV models and develop an OV modeling tool.We use unmanned surface vehicles(USV)swarm target defense SoS architecture as a case to verify the feasibility and effectiveness of the intelligent modeling method.
文摘Elasto-plastic consolidation is one of the classic coupling questions in geomechanics. To solve this problem, an elasto-plastic constitutive model is derived based on the numerical modeling method. The model is applied to Blot＇s consolidation theory. Incremental governing partial differential equations are established using this method. According to the stress path, the decoupling condition of these equations is discussed. Based on these conditions, an incremental diffusion equation and uncoupling governing equations are presented. The method is then applied to numerical analyses of three examples. The results show that （1） the effect of the stress path should be taken into account in the simulation of the soil consolidation question; （2） this decoupling method can predict the evolvement of pore water pressure; （3） the settlement using cam-clay model is less than that using numerical model because of dilatancy.
基金co-supported by Aeronautical Science Foundation of China (No. 2010ZB52011)Funding of Jiangsu Innovation Program for Graduate Education (No.CXLX11_0213)
文摘In order to establish an adaptive turbo-shaft engine model with high accuracy, a new modeling method based on parameter selection （PS） algorithm and multi-input multi-output recursive reduced least square support vector regression （MRR-LSSVR） machine is proposed. Firstly, the PS algorithm is designed to choose the most reasonable inputs of the adaptive module. During this process, a wrapper criterion based on least square support vector regression （LSSVR） machine is adopted, which can not only reduce computational complexity but also enhance generalization performance. Secondly, with the input variables determined by the PS algorithm, a mapping model of engine parameter estimation is trained off-line using MRR-LSSVR, which has a satisfying accuracy within 5＆. Finally, based on a numerical simulation platform of an integrated helicopter/ turbo-shaft engine system, an adaptive turbo-shaft engine model is developed and tested in a certain flight envelope. Under the condition of single or multiple engine components being degraded, many simulation experiments are carried out, and the simulation results show the effectiveness and validity of the proposed adaptive modeling method.
基金Project(51606225) supported by the National Natural Science Foundation of ChinaProject(2016JJ2144) supported by Hunan Provincial Natural Science Foundation of ChinaProject(502221703) supported by Graduate Independent Explorative Innovation Foundation of Central South University,China
文摘An accurate long-term energy demand forecasting is essential for energy planning and policy making. However, due to the immature energy data collecting and statistical methods, the available data are usually limited in many regions. In this paper, on the basis of comprehensive literature review, we proposed a hybrid model based on the long-range alternative energy planning (LEAP) model to improve the accuracy of energy demand forecasting in these regions. By taking Hunan province, China as a typical case, the proposed hybrid model was applied to estimating the possible future energy demand and energy-saving potentials in different sectors. The structure of LEAP model was estimated by Sankey energy flow, and Leslie matrix and autoregressive integrated moving average (ARIMA) models were used to predict the population, industrial structure and transportation turnover, respectively. Monte-Carlo method was employed to evaluate the uncertainty of forecasted results. The results showed that the hybrid model combined with scenario analysis provided a relatively accurate forecast for the long-term energy demand in regions with limited statistical data, and the average standard error of probabilistic distribution in 2030 energy demand was as low as 0.15. The prediction results could provide supportive references to identify energy-saving potentials and energy development pathways.
基金supported by the National High Technology Research and Development Program of China(863 Program)(2007AA04Z102)the National Natural Science Foundation of China(6087407160574077).
文摘As one of the basic inventory cost models, the （Q, τ）inventory cost model of dual suppliers with random procurement lead time is mostly formulated by using the concepts of ＂effective lead time＂ and ＂lead time demand＂, which may lead to an imprecise inventory cost. Through the real-time statistic of the inventory quantities, this paper considers the precise （Q, τ） inventory cost model of dual supplier procurement by using an infinitesimal dividing method. The traditional modeling method of the inventory cost for dual supplier procurement includes complex procedures. To reduce the complexity effectively, the presented method investigates the statistics properties in real-time of the inventory quantities with the application of the infinitesimal dividing method. It is proved that the optimal holding and shortage costs of dual supplier procurement are less than those of single supplier procurement respectively. With the assumption that both suppliers have the same distribution of lead times, the convexity of the cost function per unit time is proved. So the optimal solution can be easily obtained by applying the classical convex optimization methods. The numerical examples are given to verify the main conclusions.
文摘To analyze the modeling methods of the dry friction rotor system,a local linearization model of the dry friction damping rotor system was built based on the simplified model of the wave-shaped steel-belt supporting rotor system.In this model,the linear stiffness of damper closed to pre-deformation was defined as the stiffness of damper,the maximum amplitude of the rotor was calculated according to the load and linear rotor,and the damper's parameters were defined on the basis of the energy dissipation parameters.The presented method can reflect the hysteresis characteristics and is easy to calculate.Experimental results demonstrate the accuracy and feasibility of this method.
基金provided by China Geological Survey with the project(Nos.DD20190707,DD20190012)the Fundamental Research Funds for China Central public research Institutes with the project(No.JKY202014)
文摘It is one of the most important part to build an accurate gravity model in geophysical exploration.Traditional gravity modelling is usually based on grid method,such as difference method and finite element method widely used.Due to self-adaptability lack of division meshes and the difficulty of high-dimensional calculation.
基金Supported by National Natural Science Foundation of China(Grant No.51775224).
文摘Combined with the tire dynamics theoretical model,a rapid test method to obtain tire lateral and longitudinal both steady-state and transient characteristics only based on the tire quasi-steady-state test results is proposed.For steady state data extraction,the test time of the rapid test method is half that of the conventional test method.For transient tire characteristics the rapid test method omits the traditional tire test totally.At the mean time the accuracy of the two method is much closed.The rapid test method is explained theoretically and the test process is designed.The key parameters of tire are extracted and the comparison is made between rapid test and traditional test method.The result show that the identification accuracy based on the rapid test method is almost equal to the accuracy of the conventional one.Then,the heat generated during the rapid test method and that generated during the conventional test are calculated separately.The comparison shows that the heat generated during the rapid test is much smaller than the heat generated during the conventional test process.This benefits to the reduction of tire wear and the consistency of test results.Finally,it can be concluded that the fast test method can efficiently,accurately and energy-efficiently measure the steady-state and transient characteristics of the tire.
基金supported by the Key Projects of the National Science Foundation of China(Nos.52178190,52078250,11832013)
文摘On the basis of the three-dimensional(3D)random aggregate&mortar two-phase mesoscale finite element model,C++programming was used to identify the node position information of the interface between the aggregate and mortar elements.The nodes were discretized at this position and the zero-thickness cohesive elements were inserted.After that,the crack energy release rate fracture criterion based on the fracture mechanics theory was assigned to the failure criterion of the interface transition zone(ITZ)elements.Finally,the three-phase mesomechanical model based on the combined finite discrete element method(FDEM)was constructed.Based on this model,the meso-crack extension and macro-mechanical behaviour of coral aggregate concrete(CAC)under uniaxial compression were successfully simulated.The results demonstrated that the meso-mechanical model based on FDEM has excellent applicability to simulate the compressive properties of CAC.
文摘Automatic speech recognition (ASR) is vital for very low-resource languages for mitigating the extinction trouble. Chaha is one of the low-resource languages, which suffers from the problem of resource insufficiency and some of its phonological, morphological, and orthographic features challenge the development and initiatives in the area of ASR. By considering these challenges, this study is the first endeavor, which analyzed the characteristics of the language, prepared speech corpus, and developed different ASR systems. A small 3-hour read speech corpus was prepared and transcribed. Different basic and rounded phone unit-based speech recognizers were explored using multilingual deep neural network (DNN) modeling methods. The experimental results demonstrated that all the basic phone and rounded phone unit-based multilingual models outperformed the corresponding unilingual models with the relative performance improvements of 5.47% to 19.87% and 5.74% to 16.77%, respectively. The rounded phone unit-based multilingual models outperformed the equivalent basic phone unit-based models with relative performance improvements of 0.95% to 4.98%. Overall, we discovered that multilingual DNN modeling methods are profoundly effective to develop Chaha speech recognizers. Both the basic and rounded phone acoustic units are convenient to build Chaha ASR system. However, the rounded phone unit-based models are superior in performance and faster in recognition speed over the corresponding basic phone unit-based models. Hence, the rounded phone units are the most suitable acoustic units to develop Chaha ASR systems.
基金National Natural Science Foundations of China(Nos.U1162202,61222303)National High-Tech Research and Development Program of China(No.2013AA040701)the Fundamental Research Funds for the Central Universities and Shanghai Leading Academic Discipline Project,China(No.B504)
文摘Near-infrared( NIR) spectroscopy has been widely employed as a process analytical tool( PAT) in various fields; the most important reason for the use of this method is its ability to record spectra in real time to capture process properties. In quantitative online applications,the robustness of the established NIR model is often deteriorated by process condition variations,nonlinear of the properties or the high-dimensional of the NIR data set. To cope with such situation,a novel method based on principal component analysis( PCA) and artificial neural network( ANN) is proposed and a new sample-selection method is mentioned. The advantage of the presented approach is that it can select proper calibration samples and establish robust model effectively. The performance of the method was tested on a spectroscopic data set from a refinery process. Compared with traditional partial leastsquares( PLS),principal component regression( PCR) and several other modeling methods, the proposed approach was found to achieve good accuracy in the prediction of gasoline properties. An application of the proposed method is also reported.
基金Supported by the Foundation of Harbin Engineering University Foundation under Grant No.HEUFT05035
文摘This paper informally introduces colored object-oriented Petri Nets(COOPN) with the application of the AUV system.According to the characteristic of the AUV system's running environment,the object-oriented method is used in this paper not only to dispart system modules but also construct the refined running model of AUV system,then the colored Petri Net method is used to establish hierarchically detailed model in order to get the performance analyzing information of the system.After analyzing the model implementation,the errors of architecture designing and function realization can be found.If the errors can be modified on time,the experiment time in the pool can be reduced and the cost can be saved.
基金supported by the National Natural Science Foundation of China (No.51205005)the Beijing Science and Technology Innovation Service Ability Building (No.PXM2017-014212-000013)。
文摘It's common to use the method of continuous spectroscopy in water quality testing. But there're some problems with it. For example, the scanning results have a large number of nonlinear signals, and the covariance between variables is serious, which can lead to a decrease in the model prediction accuracy. In this paper, the standard solutions of nitrate nitrogen(NO_(3)-N) and nitrite nitrogen(NO_(2)-N) were used as the subject to be tested, and the data of the scanned waves and absorbance were obtained by use of spectral detector. The data were processed by noise reduction first and then the random forest(RF) algorithm was adopted to establish the regression relationship between concentration and absorbance. For comparison, partial least squares(PLS) and support vector machine(SVM) algorithm models were also established. For the same given data, the three reverse models can make the projection of the concentration respectively. The experimental results show that the RF algorithm predicts NO_(2)-N concentrations significantly better than the SVM algorithm and PLS algorithm. This proves that the RF algorithm has good prediction ability in spectral water quality detection because of its high model accuracy and better adaptability, which could be a reference for similar research on continuous spectral water quality online detection.
基金funded by National Natural Science Foundation of China(Grant No.52075305)Natural Science Foundation of Shandong Province(Grant No.ZR2019-MEE076)Zhoucun District School City Integration Development Project(Grant No.2020ZCXCZH01).
文摘In order to study the mechanical properties of the heterogeneous core plate of the wind turbine blade,a modeling method of the core plate based on displacement field variables is proposed.Firstly,the wind turbine blade core plate was modeled according to the theory of modeling heterogeneous material characteristics.Secondly,the three-point bending finite element model of the wind turbine blade core plate was solved by the display dynamic equation to obtain the deformation pattern and force-deformation relationship of the core plate.Finally,the three-point bending static test was conducted to compare with the finite element analysis.The test results show that:the damage form of the wind turbine blade core plate includes elasticity,yield,and failure stages.The main failure modes are plastic deformation,core material collapse,and panel-core delamination.The failure load measured by the test is 1.59 kN,which is basically consistent with the load-displacement result obtained by the simulation,with a difference of only 1.9%,which verifies the validity and reliability of the model.It provides data references for wind turbine blade structure design.
文摘A new concept, namely, the equivalent mobility matrix of coupling subsystem is proposed, and the corresponding threesubsystem coupling progressive approach is explored. With the new efficient approach presented, the complexity in dealing with a more complicated dynamic coupling system is greatly reduced. The new modeling method is then combined with the theory of power flow to investigate the dynamics of the overall non rigid isolation system from the viewpoint of energy. The interaction between the resilient machine of its main modes and the resonant behavior of the flexible foundation on power flow transmission is studied. Taking a machine tool mounted on a multi story working plant as an example, the dynamic characteristics of the machine foundation coupling system are analyzed, and their effects on power flow transmission are revealed under various service frequency bands. Some advisable control strategies and the design principle for machinery mounted on flexible structure are proposed.
基金supported by the National Natural Science Foundation of China(Grant Nos.42250103 and 42174090)the Opening Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education(Grant No.GLAB2023ZR02)the MOST Special Fund from the State Key Laboratory of Geological Processes and Mineral Resources(Grant No.MSFGPMR2022-4).
文摘The equivalent source(ES)method in the spherical coordinate system has been widely applied to processing,reduction,field modeling,and geophysical and geological interpretation of satellite magnetic anomaly data.However,the inversion for the ES model suffers from nonuniqueness and instability,which remain unresolved.To mitigate these issues,we introduce both the minimum and flattest models into the model objective function as an alternative regularization approach in the spherical ES method.We first present the methods,then analyze the accuracy of forward calculation and test the proposed ES method in this study by using synthetic data.The experimental results from simulation data indicate that our proposed regularization effectively suppresses the Backus effect and mitigates inversion instability in the low-latitude region.Finally,we apply the proposed method to magnetic anomaly data from China Seismo-Electromagnetic Satellite-1(CSES-1)and Macao Science Satellite-1(MSS-1)magnetic measurements over Africa by constructing an ES model of the large-scale lithospheric magnetic field.Compared with existing global lithospheric magnetic field models,our ES model demonstrates good consistency at high altitudes and predicts more stable fields at low altitudes.Furthermore,we derive the reduction to the pole(RTP)magnetic anomaly fields and the apparent susceptibility contrast distribution based on the ES model.The latter correlates well with the regional tectonic framework in Africa and surroundings.
文摘This study introduces a comprehensive theoretical framework for accurately calculating the electronic band-structure of strained long-wavelength InAs/GaSb type-Ⅱsuperlattices.Utilizing an eight-band k·p Hamilto⁃nian in conjunction with a scattering matrix method,the model effectively incorporates quantum confinement,strain effects,and interface states.This robust and numerically stable approach achieves exceptional agreement with experimental data,offering a reliable tool for analyzing and engineering the band structure of complex multi⁃layer systems.
基金supported by grants received by the first author and third author from the Institute of Eminence,Delhi University,Delhi,India,as part of the Faculty Research Program via Ref.No./IoE/2024-25/12/FRP.
文摘Software systems are vulnerable to security breaches as they expand in complexity and functionality.The confidentiality,integrity,and availability of data are gravely threatened by flaws in a system’s design,implementation,or configuration.To guarantee the durability&robustness of the software,vulnerability identification and fixation have become crucial areas of focus for developers,cybersecurity experts and industries.This paper presents a thorough multi-phase mathematical model for efficient patch management and vulnerability detection.To uniquely model these processes,the model incorporated the notion of the learning phenomenon in describing vulnerability fixation using a logistic learning function.Furthermore,the authors have used numerical methods to approximate the solution of the proposed framework where an analytical solution is difficult to attain.The suggested systematic architecture has been demonstrated through statistical analysis using patch datasets,which offers a solid basis for the research conclusions.According to computational research,learning dynamics improves security response and results in more effective vulnerability management.The suggested model offers a systematic approach to proactive vulnerability mitigation and has important uses in risk assessment,software maintenance,and cybersecurity.This study helps create more robust software systems by increasing patch management effectiveness,which benefits developers,cybersecurity experts,and sectors looking to reduce security threats in a growing digital world.
基金financially supported by the Russian federal research project No.FWZZ-2022-0026“Innovative aspects of electro-dynamics in problems of exploration and oilfield geophysics”.
文摘We propose a novel workflow for fast forward modeling of well logs in axially symmetric 2D models of the nearwellbore environment.The approach integrates the finite element method with deep residual neural networks to achieve exceptional computational efficiency and accuracy.The workflow is demonstrated through the modeling of wireline electromagnetic propagation resistivity logs,where the measured responses exhibit a highly nonlinear relationship with formation properties.The motivation for this research is the need for advanced modeling al-gorithms that are fast enough for use in modern quantitative interpretation tools,where thousands of simulations may be required in iterative inversion processes.The proposed algorithm achieves a remarkable enhancement in performance,being up to 3000 times faster than the finite element method alone when utilizing a GPU.While still ensuring high accuracy,this makes it well-suited for practical applications when reliable payzone assessment is needed in complex environmental scenarios.Furthermore,the algorithm’s efficiency positions it as a promising tool for stochastic Bayesian inversion,facilitating reliable uncertainty quantification in subsurface property estimation.
